Glycogen synthase 1 (GYS1) is the rate-limiting enzyme responsible for glycogen synthesis in skeletal muscle, heart, brain, and other extrahepatic tissues, playing a central role in systemic energy homeostasis. The human GYS1 gene maps to chromosome 19q13.33, comprises 16 exons, and encodes a 737-amino-acid polypeptide that is highly conserved across mammals. GYS1 activity is subject to multilayered and precisely coordinated regulation. At the transcriptional level, the GYS1 promoter contains a hypoxia response element (HRE) that mediates HIF-1α-dependent induction under low-oxygen conditions, as well as a muscle-specific enhancer harboring MEF2 and MyoD binding sites that confers tissue-restricted expression. At the post-translational level, a hierarchical phosphorylation cascade serves as the primary activity switch: glycogen synthase kinase 3β (GSK3β) sequentially phosphorylates four C-terminal serine residues following casein kinase II priming, while protein kinase A (PKA) and AMP-activated protein kinase (AMPK) provide parallel inhibitory inputs at both N- and C-terminal sites. Dephosphorylation and reactivation are mediated by protein phosphatase 1 (PP1) through tissue-specific glycogen-targeting regulatory subunits such as PPP1R3A and PPP1R3B, which anchor PP1 to glycogen particles and direct its activity toward GYS1. The allosteric activator glucose-6-phosphate (G6P) binds at the dimer interface, simultaneously enhancing catalytic efficiency and promoting dephosphorylation susceptibility, thereby establishing a feed-forward activation loop that couples substrate availability to glycogen synthesis. Beyond phosphorylation, GYS1 is regulated by ubiquitination (mediated by the E3 ligase PJA1), acetylation, O-linked β-N-acetylglucosamine (O-GlcNAc) modification, and SUMOylation, which collectively modulate protein stability, subcellular localization, and protein-protein interactions. Epigenetic mechanisms, including CpG island methylation and histone acetylation dynamics, govern chromatin accessibility at the GYS1 locus, while muscle-specific microRNAs such as miR-1 and miR-206 fine-tune GYS1 expression at the post-transcriptional level. Dysregulation of GYS1 has been identified as a central pathogenic driver in a spectrum of human diseases. In inherited glycogen storage disorders—including Lafora disease, adult polyglucosan body disease (APBD), and Pompe disease—loss of upstream regulatory control leads to GYS1 hyperactivation and the accumulation of structurally abnormal or excessive glycogen, resulting in progressive neurodegeneration, myopathy, and multiorgan dysfunction. In type 2 diabetes mellitus (T2DM), impaired insulin signaling through the PI3K-AKT-GSK3β axis maintains GYS1 in a hyperphosphorylated inactive state in skeletal muscle, compromising postprandial glucose disposal and exacerbating hyperglycemia. In oncology, GYS1 exhibits context-dependent roles across multiple cancer types. In hepatocellular carcinoma, FMO2⁺ cancer-associated fibroblasts stabilize GYS1 by competitively inhibiting PJA1-mediated ubiquitination, and stabilized GYS1 subsequently activates NF-κB/CCL19 signaling to promote tertiary lymphoid structure formation and enhance anti-PD-1 immunotherapy responsiveness. In clear cell renal cell carcinoma, GYS1 promotes tumor progression through non-canonical NF-κB pathway activation via the scaffold protein RPS27A. In triple-negative breast cancer, GYS1 has been identified as a trigger of disulfidptosis and an activator of NF-κB signaling through non-enzymatic facilitation of IκBα degradation. In colorectal cancer, mitochondrial fission deficiency drives AMPK-dependent GYS1 upregulation and glycogen accumulation as a compensatory survival mechanism, while in cervical cancer, GYS1-maintained glycogen reserves fuel the pentose phosphate pathway to generate NADPH for ROS clearance, thereby conferring cisplatin resistance in cancer stem cells. Therapeutic strategies targeting GYS1 have gained substantial momentum across these disease contexts. For glycogen storage disorders, antisense oligonucleotides, small interfering RNAs (e.g., ABX1100), and small-molecule inhibitors (e.g., MZ-101) have demonstrated preclinical and early clinical efficacy in reducing pathological glycogen accumulation. For T2DM, pharmacological activation of GYS1 through GSK3β inhibition or enhancement of PP1-mediated dephosphorylation is being explored to restore insulin-stimulated glycogen synthesis. In cancer, GYS1-directed interventions—including targeted silencing to sensitize tumors to chemotherapy and immune microenvironment modulation to enhance immunotherapy—represent emerging precision oncology approaches. This review provides a comprehensive and integrated account of GYS1 gene structure, tissue-specific distribution, regulatory networks, and pathogenic roles in metabolic disorders and malignancies, with the aim of establishing a theoretical framework for the development of GYS1-targeted precision therapies.

Atherosclerosis (AS) remains the core pathological basis underlying the high incidence and high rates of mortality and disability associated with cardiovascular disease (CVD) worldwide. Its essence is not merely lipid deposition, but rather an immune-mediated disease of the vascular wall characterized by an interplay of lipid metabolism disorders and chronic inflammation, with damage to vascular endothelial cells serving as the initiating event. As the disease progresses, it involves complex synergistic interactions among various cellular components, including endothelial cells, macrophages, and inflammatory cells, ultimately leading to plaque formation, instability, and even fatal thrombotic events. In recent years, the central driving role of lipid metabolic reprogramming in the progression of AS has garnered increasing attention from the scientific community. Among the vast array of lipid molecules, long-chain fatty acids (LCFAs) have become a primary focus of research due to their exceptional physiological functions. Traditional views have primarily emphasized the basic physiological functions of LCFAs: serving as highly efficient energy substrates through mitochondrial β-oxidation and acting as key structural components of cellular phospholipid membranes. However, emerging evidence clearly indicates that the functions of LCFAs extend far beyond those of mere metabolic fuel. They also act as potent bioactive signaling molecules, playing an indispensable multidimensional role in the pathogenesis of AS. Equally noteworthy and representing a paradigm shift in cardiovascular research is the emerging theory of the “gut-heart axis”. This theoretical framework views the human gut microbiota—comprising trillions of microorganisms—as a critical and metabolically active “bioreactor”. A wealth of clinical and multi-cohort epidemiological studies have conclusively demonstrated that imbalances in the composition and function of the gut microbiota are highly correlated with the clinical risk and severity of AS. Within this axis, the gut microbiota serves as the primary processing hub for dietary lipids. It actively participates in the digestion and biochemical remodeling of LCFAs, thereby altering their saturation and chemical structure and generating a wide variety of gut microbial metabolites. The effects of these gut-derived lipid metabolites extend far beyond the local intestinal microenvironment. Upon entering the bloodstream, these circulating microbiota metabolites act as endocrine signals. Given the extreme complexity of the underlying mechanisms, a comprehensive elucidation of the synergistic and bidirectional interactions between LCFAs and the gut microbiota in vascular pathology is particularly urgent. Therefore, this article aims to provide a systematic review of the multidimensional regulatory mechanisms of LCFAs and their associated gut microbiota metabolites in the onset, progression, and clinical manifestations of AS. By thoroughly exploring the interaction patterns within the “LCFAs-gut microbiota-AS” triad, this review seeks to fundamentally expand our understanding of the pathogenesis of CVDs. More importantly, translating these mechanistic insights into clinical practice holds tremendous promise. We hope to provide a solid theoretical foundation for the future development of novel AS prevention and treatment strategies based on non-traditional approaches. These include precision nutritional interventions (i.e., dietary lipid intake plans tailored to an individual’s unique microbiome profile) and targeted microbiome modulation therapies (such as next-generation probiotics, prebiotics, or specific metabolite supplements). Targeting the gut as a “reactor” to treat vascular wall lesions represents a promising direction for future cardiovascular medicine.

Diabetic retinopathy (DR) is one of the most prevalent and vision-threatening microvascular complications of diabetes mellitus, yet its pathogenesis extends far beyond vascular injury alone. As the retina is among the most energy-demanding tissues in the body, its neurons, glial cells, pigment epithelial cells, pericytes, and endothelial cells are highly dependent on mitochondrial oxidative phosphorylation to maintain visual signal transduction, ionic homeostasis, and neurovascular integrity. This review summarizes current evidence indicating that mitochondrial dysfunction is not merely a downstream consequence of chronic hyperglycemia, but a central pathogenic hub that initiates, amplifies, and perpetuates retinal neurovascular degeneration in DR. Persistent hyperglycemia activates multiple abnormal metabolic pathways, including the polyol pathway, hexosamine pathway, protein kinase C signaling, advanced glycation end-product formation, and angiotensin II-related responses. Although these pathways differ mechanistically, they converge on excessive reactive oxygen species (ROS) generation, antioxidant depletion, and mitochondrial injury. Under diabetic stress, electron transport chain overload promotes mitochondrial ROS leakage, damages mitochondrial DNA, disrupts membrane potential, and impairs the transcription of key respiratory chain components. In parallel, mitochondrial quality-control systems become progressively compromised. The balance between fusion and fission shifts toward pathological fragmentation through reduced MFN1/2 and OPA1 activity and enhanced DRP1-mediated fission. Mitochondrial biogenesis is suppressed through inhibition of the AMPK/SIRT1/PGC-1α/NRF1/TFAM axis, while mitophagy changes from an early compensatory response to a later state of autophagic flux blockade and accumulation of dysfunctional mitochondria. Importantly, damaged mitochondria serve as signal amplifiers linking metabolic stress to inflammation and programmed cell death. Mitochondrial ROS, oxidized mitochondrial DNA, calcium overload, cardiolipin exposure, and membrane permeabilization activate interrelated death pathways, including intrinsic apoptosis, ferroptosis, and pyroptosis. Cytochrome C and apoptosis-inducing factor promote caspase-dependent and caspase-independent apoptosis; iron dyshomeostasis, glutathione depletion, GPX4 dysfunction, and lipid peroxidation drive ferroptosis; and mitochondrial danger signals activate the NLRP3 inflammasome and gasdermin-dependent pyroptosis. These pathways jointly damage the retinal neurovascular unit and contribute to pericyte loss, endothelial barrier breakdown, Müller cell dysfunction, retinal ganglion cell apoptosis, retinal pigment epithelial injury, and photoreceptor degeneration. This review also emphasizes the role of epigenetic regulation in stabilizing mitochondrial pathology. DNA methylation, histone modifications, and non-coding RNAs interact to silence mitochondrial protective genes, alter antioxidant responses, and maintain the “metabolic memory” of DR even after glycemic normalization. Therefore, mitochondrial dysfunction should be understood as a dynamic, multidimensional network rather than a single pathological event. Current clinical approaches, such as laser photocoagulation, intravitreal anti-VEGF therapy, and vitrectomy, mainly target advanced vascular lesions and are limited by invasiveness, incomplete responsiveness, recurrence, and potential adverse effects. Therapeutically, strategies targeting mitochondrial ROS, restoring mitochondrial dynamics, enhancing biogenesis, regulating mitophagy, inhibiting inflammasome activation, correcting epigenetic abnormalities, and improving targeted delivery systems show promising potential. However, major translational barriers remain, including retinal cell heterogeneity, stage-specific mitochondrial responses, insufficient organelle-specific drug delivery, and long-term safety concerns. A deeper understanding of mitochondrial regulatory networks may support earlier, more precise, and multi-target interventions for preventing or slowing DR progression.

Liver cancer is one of the world""s serious diseases today because of its high frequency and fatality rate, genetic differences, and limited effectiveness of late-stage therapy. Although chemotherapy, targeted therapy, immunotherapy, ablation and transarterial chemoembolisation (TACE) have improved the disease control of some patients, recurrence and acquired resistance are still common, especially for tumors that are hypoxic, nutrient-deprived, acidic-stressed, vascularly insufficient and exposed to repeated drug pressure. A bad environment will cause a change in the quality-control system and metabolism of cancer cells, and as a result, lysosomes have started to alter. In addition to the above catabolic functions of lysosomes, they also take part in autophagic flux, substrate recycling, iron and lipid metabolism, nutrient sensing, drug distribution, membrane repair and cell death signalling. Under the stress of therapy in liver cancer cells, increased lysosomal acidification and enhanced terminal degradation lead to prolonged autophagy; TFEB/TFE3 promotes the formation of new lysosomes and lysophagosomes to sequester weakly basic drugs, thereby reducing the concentration of active drugs and mitigating proteotoxicity and oxidative stress to promote cell survival. The above processes produce a lysosome-dependent resistant phenotype that is particularly relevant to sorafenib and doxorubicin and other drugs whose effectiveness can be reduced by protective autophagy or changes in intracellular location. Conversely, the same dependency on lysosomal homeostasis is also a vulnerability. Natural products and monomeric compounds derived from Chinese herbal medicines have various structures, multiple target regulation capabilities, and the potential to act on several lysosome-related nodes simultaneously. Based on the evidence in this review, it is believed that such compounds may sensitise liver cancer cells by inhibiting V-ATPase-mediated acid hydrolysis, obstructing late-stage autophagy-mediated degradation, disrupting lysosomal calcium or membrane homeostasis, causing lysosomal membrane permeabilisation, reducing compensatory lysosomal biogenesis, promoting ferritin degradation and ferroptosis, or enhancing acid-responsive intracellular delivery. Agents that impair lysosomal function and protective autophagy, compounds that convert enlarged or drug-sequestering lysosomes into lethal targets, and nanodelivery systems that exploit the acidic environment of endolysosomes to co-deliver natural products with chemotherapeutic drugs are examples. Lysosome-targeted intervention will have different effects under different circumstances; for example, inhibiting autophagy may result in an increase in cytotoxic stress in some areas, whereas overstimulation of autophagy or iron release from lysosomes may induce autophagic cell death or ferroptosis in other areas. Therefore, the design of therapy should take into account the status of the tumour microenvironment, autophagic flux, lysosomal pH, TFEB/TFE3 activity, drug sequestration capacity, ferroptosis sensitivity, dosing sequence and delivery route. This review systematically examines the lysosomal homeostasis in the microenvironment of liver cancer, the mechanisms through which lysosomal adaptation contributes to chemoresistance, and the rationale for combining natural products with standard agents such as sorafenib and doxorubicin. Based on basic lysosome biology, pharmacodynamic and delivery data have also been collected; as a result, some applications for future studies have been proposed, such as dynamic monitoring of autophagy flux, in vivo spatial measurements of lysosomal functions, rational optimisation of combination therapy timings, and safety assessments in immunocompetent liver cancer models prior to clinical translation. Translation difficulties are also evident, such as insufficient tumour selectivity, pharmacokinetic limitations, compensatory lysosomal regeneration, toxicity to normal liver and immune cells, and a lack of validated predictive biomarkers. A new way will be found to use biomarkers to divide the patient group, optimize nanoparticles for better delivery, design specific schedules for combined treatments based on the problem they cause within the cell, etc., thereby overcoming drug resistance and reducing the harm patients suffer from toxic treatments. This system can help select biomarkers and rational drug pairs for the next round of lysosome-centred precision trials.

Exercise-induced muscle damage (EIMD) is a frequent form of skeletal muscle microdamage that occurs after high-intensity, prolonged, or unaccustomed exercise, especially exercise dominated by eccentric contractions. It is commonly characterized by delayed-onset muscle soreness, transient loss of muscle strength, local inflammation, structural disruption of myofibers, and delayed functional recovery. Although mild EIMD may serve as a stimulus for training adaptation, excessive or insufficiently recovered muscle damage can impair exercise performance, disturb training continuity, and reduce participation in physical activity. Therefore, clarifying the molecular mechanisms that underlie the initiation, amplification, and resolution of EIMD is important for optimizing athletic training, improving post-exercise recovery, and guiding evidence-based public fitness practice. Necroptosis is a regulated form of programmed cell death mediated primarily by the receptor-interacting protein kinase (RIPK) 1/RIPK3/mixed lineage kinase domain-like protein (MLKL) signaling axis. Recent studies have shown that necroptosis is closely involved in tissue injury, sterile inflammation, and repair remodeling. However, whether necroptosis acts as an initiating driver, a secondary damage amplifier, or an adaptive signal required for repair after EIMD remains unclear. This review aimed to summarize the potential role of necroptosis in EIMD and to establish a mechanistic framework linking regulated cell death, inflammatory amplification, immune regulation, and skeletal muscle repair. Relevant studies concerning EIMD, necroptosis, RIPK1/RIPK3/MLKL signaling, damage-associated molecular patterns (DAMPs), inflammatory responses, immune cell recruitment, extracellular matrix remodeling, and muscle regeneration were reviewed and integrated. On this basis, the possible temporal and functional involvement of necroptosis in different phases of EIMD was analyzed. The main evidence summarized in this review suggests that EIMD is not merely a consequence of primary mechanical disruption. Instead, it develops through a dynamic sequence that includes sarcolemmal instability, calcium overload, mitochondrial dysfunction, oxidative stress, inflammatory mediator production, immune cell infiltration, necrotic tissue clearance, and regeneration-associated remodeling. Necroptosis may participate in this process through at least two interconnected mechanisms. First, in the early or progressive phase of EIMD, activation of the RIPK1/RIPK3/MLKL signaling axis may promote MLKL phosphorylation and plasma membrane permeabilization, leading to the release of DAMPs such as high-mobility group box 1, ATP, mitochondrial DNA, and other intracellular components. These signals may activate innate immune pathways, amplify inflammatory cytokine production, and enhance the recruitment of neutrophils and macrophages, thereby aggravating secondary inflammation and extending muscle fiber injury. Second, during the resolution and repair phases, necroptosis-related signaling may also contribute indirectly to the formation of a regenerative microenvironment. By influencing the clearance of necrotic debris, the recruitment and phenotypic transition of immune cells, and the remodeling of extracellular matrix components, necroptosis may affect satellite cell activation, myogenic repair, and the eventual structural and functional recovery of injured skeletal muscle. Thus, the biological effect of necroptosis in EIMD may be context dependent rather than uniformly harmful. Its outcome may depend on exercise intensity, the extent of tissue damage, the timing of pathway activation, the involved cell types, inflammatory status, training background, age, and metabolic condition. In conclusion, necroptosis may represent an important molecular link between skeletal muscle injury, sterile inflammation, and tissue repair after damaging exercise. It may exert a dual role in EIMD by amplifying secondary damage while also contributing to repair coordination under appropriate temporal and microenvironmental conditions. Future studies should determine the activation pattern of RIPK1/RIPK3/MLKL signaling after different exercise protocols, identify the major cell populations undergoing necroptosis in injured skeletal muscle, and examine whether targeted modulation of necroptosis can reduce excessive inflammation without impairing necessary regenerative responses. This review provides a theoretical basis for understanding the pathogenesis of EIMD and for developing targeted strategies to improve skeletal muscle recovery after exercise-induced injury.

“Zinc overload” has emerged as a promising strategy in tumor nanomedicine, wherein exogenous modulation of metal ion homeostasis selectively triggers cancer cell death. Among various bioactive ions, zinc (Zn²⁺) stands out due to its unique ability to simultaneously disrupt energy metabolism, damage mitochondria, degrade mutant p53, and activate antitumor immunity. Notably, tumor cells exhibit greater sensitivity to Zn²⁺ overload while normal cells maintain higher tolerance. This review systematically summarizes design strategies for achieving “zinc overload” using biodegradable zinc-based nanomaterials, focusing on two fundamental questions: how to specifically deliver Zn²⁺ to tumors (targeted delivery), and how to trigger controlled release at the tumor site (release strategies). Current challenges are critically analyzed and future perspectives are offered. For targeted delivery, the strategies are categorized into passive, active, and biomimetic approaches. Passive targeting relies on the enhanced permeability and retention (EPR) effect but suffers from poor enrichment efficiency and rapid clearance. Active targeting conjugates ligands (e.g., folic acid, hyaluronic acid) to recognize overexpressed receptors, significantly enhancing cellular uptake. It is emphasized that hyaluronic acid-modified ZIF-8 can co-deliver siRNA for GLUT1 silencing, achieving systematic energy exhaustion. Biomimetic delivery using cell membranes confers immune evasion, prolonged circulation, and homologous targeting, exhibiting the lowest off-target toxicity. This approach is considered to guide future nanocarrier design. For Zn²⁺ release, 4 mechanisms are discussed. Endogenous environment-responsive release exploits acidic pH to degrade materials like ZIF-8 or ZnO, causing mitochondrial dysfunction, reactive oxygen species (ROS) burst, and autophagic blockade. Incorporation of other ions (Ca²⁺, Mn²⁺, Ni²⁺) enables synergistic metabolic interference and immune activation. Exogenous responsive release using near-infrared light offers spatiotemporally precise activation. For example, a nanorobot combining black phosphorus with ZIF-8 accelerates Zn²⁺ release under dual acid and light stimuli. Ion exchange represents an elegant trigger: zinc complexes (e.g., Zn-carnosine) have higher affinity for Cu²⁺; competitive coordination releases Zn²⁺ while depleting Cu²⁺, dually inhibiting oxidative phosphorylation and glycolysis. This mechanism is proposed to hold promise for overcoming metabolic reprogramming. Finally, biological regulation—silencing the ZnT1 zinc transporter to block Zn²⁺ efflux—represents a paradigm shift from passive delivery to active homeostatic disruption. This “block and attack” strategy may prevent acquired resistance. The therapeutic consequences of zinc overload are multifaceted. Zn²⁺ causes lysosomal membrane permeabilization and impaired SNARE complex formation, blocking autophagic flux and inducing a distinct cell death termed “zincosis”. In mitochondria, Zn²⁺ inhibits glutathione reductase, causing oxidative stress and electron transport chain blockade. Meanwhile, Zn²⁺ suppresses glycolytic enzymes (GAPDH, LDHA), leading to ATP depletion and reversing drug resistance by downregulating P-glycoprotein. Moreover, zinc overload triggers immunogenic cell death, promoting dendritic cell maturation and CD8⁺ T cell infiltration. Combined with cGAS-STING activation, this reshapes the immunosuppressive tumor microenvironment and inhibits distant metastasis. These interconnected mechanisms endow zinc overload with a unique advantage over single-modality treatments. Despite remarkable preclinical efficacy, challenges remain: systemic toxicity from off-target release, potential zinc tolerance via metallothionein upregulation, and insufficient pharmacokinetic data. Future directions should prioritize: (1) intelligent stimuli-responsive materials; (2) combination with immune checkpoint inhibitors; (3) theragnostic integration; (4) deeper mechanistic studies; and (5) artificial intelligence-assisted screening. Zinc overload therapy is expected to become an indispensable component of integrated tumor treatment.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective The frequency difference limen (FDL) serves as a fundamental metric utilized for effectively quantifying the precise perceptual capabilities of the central auditory system. However, traditional measurement methods rely heavily on the active behavioral responses of subjects and are consequently highly susceptible to the negative influence of confounding subjective factors. Furthermore, existing research paradigms frequently employ uniform stimulus configurations that overlook critical individual perceptual differences. Based on brain-computer interface (BCI) technology, this comprehensive study aims to establish an objective and quantitative evaluation method for auditory frequency discrimination by systematically analyzing and decoding the specific neural responses elicited at the exact threshold state.Methods We designed a personalized rapid serial auditory presentation (RSAP) paradigm customized based on each individual’s precise FDL. A cohort of eleven healthy participants was recruited to evaluate the paradigm using pure-tone sequences at a baseline frequency of 4 000 Hz. This experimental paradigm simulates a realistic auditory perception environment through the continuous presentation of acoustic stimuli, thereby allowing for an in-depth investigation into the specific neural representations evoked by weak frequency deviations at the threshold state. Given that auditory stimulus-evoked response features exhibit complex and differentiated spatiotemporal distribution patterns across multiple frequency domains, this study further deeply integrates the cross-scale feature interaction module with the dynamic spatiotemporal attention allocation strategy, innovatively proposing the Multi-Scale Spatial-Temporal Dual Attention Network (MS-STAMNet). Specifically, the network constructs parallel processing branches with multiple receptive fields and introduces a dynamic adaptive weighting strategy to precisely localize core neural activity signals, further deeply integrating multi-scale information through cross-branch feature information interaction to achieve robust single-trial decoding of weak auditory evoked responses.Results The comprehensive electrophysiological data analysis demonstrated that subtle auditory frequency deviation stimuli presented at the threshold level successfully elicited pronounced N2 and P3 event-related potential features, reflecting pre-attentive mismatch detection and subsequent cognitive evaluation, which were prominently distributed over the frontal, central, and temporal regions of the scalp. In the complex time-frequency domain, the extracted neural response characteristics exhibited distinct, statistically significant event-related synchronization within both the low-frequency δ and θ frequency bands, which was simultaneously accompanied by a widespread, prominent event-related desynchronization within the higher α band. A comparative analysis of model performance demonstrated that MS-STAMNet achieved an average unweighted average recall (UAR) of (69.67±6.12)% and area under the curve (AUC) of 0.761 8±0.07, significantly outperforming the established baseline models such as EEGNet and PLNet. Furthermore, a distinct dissociation phenomenon was verified between neural decoding and behavioral performance through regression analysis (R²=0.016, P=0.709), indicating that this model can effectively capture the implicit features of subtle frequency deviations, even when they fail to trigger explicit conscious responses. Additionally, attention weight visualization analysis further reveals the highly accurate focus of the network on key features concentrated over the bilateral temporal and fronto-parietal regions.Conclusion This study systematically and comprehensively uncovers the multi-dimensional spatiotemporal evolutionary patterns of complex neural responses processing subtle acoustic variations under long-sequence threshold auditory stimulation. Concurrently, it verifies the efficacy and robustness of the proposed MS-STAMNet architecture in accurately deciphering weak, single-trial electroencephalogram signals amidst complex background noise. Ultimately, these neurophysiological and algorithmic findings lay a solid theoretical and methodological foundation for the objective and quantitative evaluation of individual auditory cognitive capabilities in clinical applications, transcending the fundamental limitations of traditional behavioral paradigms and providing robust technical support for future auditory research and related clinical assessments.

Steroid-associated osteonecrosis of the femoral head (SANFH) is a progressive osteoarticular disorder associated with prolonged or high-dose glucocorticoid exposure. Its development involves local ischemia, oxidative stress, dysregulated bone metabolism, and disruption of the osteoimmune microenvironment. Macrophages exhibit marked phenotypic plasticity, and their polarization is essential for maintaining the dynamic balance among inflammation, angiogenesis, and bone remodeling. Persistent glucocorticoid stimulation, hypoxia, excessive reactive oxygen species, and damage-associated signals released from necrotic tissues can shift macrophages toward a pro-inflammatory phenotype. Classically activated macrophages (M1 macrophages) predominantly mediate inflammatory responses. By releasing tumor necrosis factor-α, interleukin-1β, interleukin-6, and other mediators, promoting osteoclast activation, suppressing the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), and impairing vascular endothelial function, M1 macrophages accelerate trabecular destruction and expansion of the necrotic lesion. In contrast, alternatively activated macrophages (M2 macrophages) contribute to inflammation resolution, neovascularization, osteogenic repair, and tissue remodeling, thereby supporting regeneration within the necrotic region. Macrophage-derived exosomes further influence disease progression through intercellular communication. Exosomes from different macrophage phenotypes can differentially regulate adipogenic differentiation, neutrophil extracellular trap formation, and endothelial phenotypic transition, thereby affecting the repair capacity of the necrotic area. These findings indicate that macrophage polarization shapes the local microenvironment not only through soluble mediators but also through vesicle-mediated communication with BMSCs, neutrophils, endothelial cells, and other cell populations. At the molecular level, the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome, nuclear factor kappa B (NF-κB), Janus kinase/signal transducer and activator of transcription (JAK/STAT), and phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathways jointly regulate macrophage polarization and its downstream osteoimmune effects. Dysregulation of these pathways may sustain inflammatory activation, aggravate oxidative and vascular injury, inhibit osteogenesis, and impair tissue repair. NLRP3 inflammasome activation links danger signals and oxidative stress to inflammatory cytokine maturation and pyroptotic injury; NF-κB signaling promotes pro-inflammatory gene transcription and M1 polarization; JAK/STAT signaling participates in the balance between inflammatory and reparative macrophage programs; and PI3K/Akt/mTOR signaling regulates cellular metabolism, survival, autophagy, and regeneration. Notably, the biological effects of PI3K/Akt/mTOR signaling are cell-type dependent, and Akt-mediated repair signaling should be distinguished from mTOR-related autophagy regulation. The pathological significance of macrophage polarization in SANFH is not determined simply by an increase or decrease in a single phenotype. Rather, disease progression appears to result from an imbalance between persistent pro-inflammatory activity and insufficient reparative responses at different stages of the disease. Such an imbalance disrupts the coordinated coupling of inflammation resolution, vascular regeneration, and bone remodeling, ultimately contributing to structural deterioration of the femoral head. This review summarizes the pathological roles, signaling regulation, and exosome-mediated intercellular communication associated with macrophage polarization imbalance in SANFH. A more precise understanding of these mechanisms may clarify the osteoimmune basis of SANFH and support the development of macrophage-targeted interventions. However, most available evidence is derived from cellular and animal studies, and the temporal evolution of macrophage phenotypes in patients remains insufficiently characterized. Therapeutic strategies should therefore move beyond the simple suppression of M1 macrophages or enhancement of M2 macrophages and instead aim to restore a stage-appropriate balance between inflammatory control and tissue repair while promoting angiogenesis and bone reconstruction.

Objective Community-acquired pneumonia (CAP) is a common infectious disease encountered in emergency departments, and timely severity stratification is essential for early risk identification and individualized treatment. Chest CT can accurately evaluate the extent of pulmonary involvement; however, its use for repeated bedside assessment is limited by radiation exposure, cost, limited portability, and the need for patient transport. In contrast, EIT is a radiation-free, noninvasive, and bedside functional imaging modality that can continuously monitor regional ventilation. Nevertheless, its relatively low spatial resolution limits its ability to directly characterize the anatomical extent of pulmonary lesions. Therefore, this study constructed a CT shape-prior-guided 3D CT-EIT composite image and explored its value for CAP severity assessment.Methods A total of 60 adult patients with CAP who were admitted to the Emergency Department of the Third Hospital of Hebei Medical University between October 2023 and October 2024 were retrospectively included. According to a five-lobe CT score ranging from 0 to 25, the patients were divided into a light pneumonia (LP) group and a moderate-to-severe pneumonia (MSP) group. Patients with CT scores of 0–8 were classified into the LP group (n=29), whereas those with CT scores of 9–25 were classified into the MSP group (n=31). Clinical indices, including oxygenation index (PaO₂/FiO₂), fibrinogen, and pneumonia severity index (PSI), were collected. The 3D EIT composite image based on the individual CT images of each patient was constructed, and the percentage of ventilation blocked regions (PVBR), ventilation distribution center error (VDCE), and global ventilation delay index (GVDI) were established. Receiver operating characteristic (ROC) curves were plotted to evaluate the discriminative performance, and Pearson correlation coefficient (r) was used to assess the correlation between 3D EIT ventilation indices and CT score.Results There were no statistically significant differences in baseline characteristics between the two groups (P>0.05). Compared with the LP group, the MSP group showed lower PaO₂/FiO₂ (166 mmHg vs. 298 mmHg, P<0.01), higher fibrinogen (4.59 g/L vs. 3.90 g/L, P<0.01), higher PSI (114.23 vs. 94.52, P<0.01), higher PVBR (39.33 vs. 26.33, P<0.001), higher VDCE (42.21 vs. 35.33, P<0.05), and higher GVDI (0.48 vs. 0.38, P<0.001). Among the conventional clinical indices, PaO₂/FiO₂ showed the highest area under the ROC curve (AUC=0.723). Among the 3D EIT ventilation indices, PVBR showed the best performance, with an AUC of 0.775 and a specificity of 96.6%. CT score was negatively correlated with PaO₂/FiO₂, but positively correlated with fibrinogen, PSI, and 3D EIT ventilation indices. Among these, CT score showed the strongest correlation with PVBR (r=0.696).Conclusion 3D CT-EIT composite imaging is feasible for rapid bedside functional assessment of CAP severity. PVBR, VDCE, and GVDI provide complementary information on the extent of ventilation blockage, the spatial redistribution of ventilation, and the temporal delay in ventilation, respectively. Among these indices, PVBR showed the best discriminatory performance and the strongest correlation with CT-defined lesion severity. Although 3D EIT cannot replace CT for structural diagnosis, it may serve as a practical radiation-free functional complement for bedside severity stratification, serial ventilation monitoring, and early clinical decision-making in patients with CAP.

Kynurenine pathway (KP) is a major catabolic route of tryptophan, generating a series of bioactive metabolites including kynurenine, kynurenic acid, quinolinic acid, and 3-hydroxykynurenine. Beyond its fundamental role in amino acid metabolism, KP exerts critical regulatory functions in neurodevelopment, synaptic plasticity, and immune modulation. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with onset in early childhood, characterized by persistent deficits in social communication and restricted, repetitive behaviors. Despite extensive research, the etiological mechanisms underlying ASD remain highly complex and incompletely understood, involving genetic, environmental, and immunological factors. Emerging clinical evidence has consistently revealed a significant imbalance in KP metabolites in individuals with ASD, often accompanied by altered ratios of neuroprotective versus neurotoxic byproducts. However, the primary drivers of this metabolic dysregulation and its causative contribution to ASD pathogenesis are not yet fully elucidated. In this review, we systematically examine the enzymatic steps of KP and the principal physiological functions of its major metabolites, with particular emphasis on their dual roles in neuroprotection and neurotoxicity. We then analyze the potential pathogenic mechanisms through which KP dysfunction may contribute to ASD, focusing on two interconnected etiological dimensions. First, KP imbalance can promote oxidative stress, which in turn triggers chronic inflammatory responses via microglial activation and release of pro-inflammatory cytokines, thereby disrupting neuronal homeostasis. Second, aberrant KP metabolism affects neurotransmitter systems, particularly glutamatergic and dopaminergic signaling, leading to impaired neural circuit development and synaptic pruning. By integrating current findings on the KP–ASD association, this review offers a comprehensive etiological framework and a clinically relevant paradigm. Furthermore, we highlight that specific KP metabolites, such as the kynurenic acid/quinolinic acid ratio, hold promise as peripheral biomarkers for early diagnosis and disease stratification. Finally, we discuss the therapeutic potential of targeting KP enzymes or receptors for personalized intervention strategies, while acknowledging the challenges in translating these findings into clinical practice.

Polyamine homeostasis is tightly coupled to tumor-cell proliferation, metabolic reprogramming, stress adaptation, and immune escape. Ornithine decarboxylase antizyme 1 (OAZ1) is a central negative regulator of this network. When intracellular polyamine levels increase, the ribosome shifts one nucleotide downstream and switches to a new reading frame during translation of OAZ1 mRNA, thereby enabling the production of the full-length active OAZ1 protein. OAZ1 then restrains polyamine accumulation through two complementary mechanisms. It binds ornithine decarboxylase (ODC), inhibits enzyme activity, promotes dissociation of the active ODC homodimer, and facilitates ubiquitin-independent proteasomal degradation of ODC, thereby reducing endogenous putrescine synthesis. In parallel, OAZ1 suppresses the polyamine transport system (PTS), limiting the uptake of extracellular polyamines that may compensate for reduced biosynthesis. Recent studies have reshaped the concept of the mammalian PTS. Rather than a single plasma-membrane transporter, it is now viewed as a multicomponent and compartmentalized network involving cell-surface enrichment by heparan sulfate proteoglycans, caveolin-associated endocytosis in selected cellular contexts, endosomal or lysosomal escape mediated by P5B-type ATPases such as ATP13A3 and ATP13A2, vesicular storage mediated by SLC18B1, and acetylation-coupled export mediated by spermidine/spermine N1-acetyltransferase 1 (SAT1) and the SLC3A2-associated diamine exporter pathway. These findings provide a broader framework for understanding how tumor cells maintain high polyamine availability even when synthesis is pharmacologically inhibited. However, several fundamental questions remain unresolved. The direct PTS targets recognized by OAZ1 have not been identified, the structural basis by which polyamine-induced OAZ1 dimerization contributes to transport inhibition is still unclear, and the relationship between dysregulation of the OAZ1-PTS axis and therapeutic responses varies among tumor types. In this review, we summarize the molecular mechanisms of OAZ1 polyamine sensing, programmed frameshift translation, ODC inhibition and degradation, and feedback control of polyamine uptake. We also integrate recent advances on ATP13A2, ATP13A3, ATP13A4, SLC3A2, SLC18B1, SAT1, and related transport or export modules, and compare their alterations in neuroblastoma, lung cancer, prostate cancer, colorectal cancer, hepatocellular carcinoma, breast cancer, pancreatic cancer, leukemia, glioma, and oral squamous cell carcinoma. Particular attention is given to tumor-type specificity. MYCN-driven neuroblastoma appears to depend on both enhanced biosynthesis and compensatory uptake, lung and prostate cancer models provide functional evidence for OAZ1-dependent feedback repression of uptake, hepatocellular carcinoma highlights the immunological role of acetylated-polyamine efflux, and breast and pancreatic cancer studies suggest nonredundant contributions of ATP13 family members. Finally, we discuss translational strategies that aim to mimic or restore the dual negative-feedback function of OAZ1, including difluoromethylornithine (DFMO), AMXT1501-based polyamine blockade therapy, ATP13A3-directed intervention, targeting of AZIN1-OAZ1 antagonism, and modulation of SAT1-SLC3A2-associated acetylated-polyamine export. Future work should combine transport assays, interaction mapping, spatial omics, metabolomics, and immune profiling to define actionable biomarkers, such as OAZ1, AZIN1, ODC, ATP13A3, SLC3A2, SAT1, and tumor polyamine signatures. Such biomarkers will be important for selecting patients, monitoring target engagement, and designing combinations with chemotherapy, targeted therapy, or immune checkpoint blockade. A better understanding of the OAZ1-PTS axis may support biomarker-guided patient stratification and rational combination therapies targeting polyamine dependence and the immunometabolic tumor microenvironment.

Both type 2 diabetes mellitus (T2DM) and metabolic associated fatty liver disease (MAFLD) fall within the spectrum of metabolic diseases, and they exhibit a bi-directional causal relationship and robust reciprocal association. Their shared pathological cornerstone is insulin resistance (IR), which involves the interplay of mitochondrial dysfunction and chronic inflammation, forming a cascading pathological process of “IR—mitochondrial dysfunction—inflammation”. This largely explains the notable upward trend in T2DM-MAFLD co-occurrence observed over recent years. Exercise intervention, as a safe and effective non-pharmacological approach, can improve the pathological progression of these patients at multiple levels. Following the logical framework of “pathogenesis—efficacy comparison—molecular mechanisms—clinical translation”, this article systematically compares the efficacy and molecular mechanisms of moderate-intensity continuous training (MICT), resistance exercise, high-intensity interval training (HIIT), and combined training. MICT reduces intrahepatic triglycerides by promoting lipolysis and improving cardiorespiratory fitness; resistance exercise increases muscle mass and basal metabolic rate, offering unique advantages in preserving muscle while reducing fat and improving insulin sensitivity; HIIT is a time-efficient exercise modality that enhances patients’ cardiorespiratory fitness and insulin sensitivity by alternating brief periods of vigorous exertion with recovery periods, with a prominent short-term triglyceride-lowering effect; combined training produces synergistic effects, comprehensively improving glucolipid metabolism and showing the best long-term adherence. Mechanistically, exercise exerts its beneficial effects through three common pathways: (1) AMPK-mediated lipid oxidation and mitochondrial biogenesis; (2) IRS/PI3K/Akt-mediated insulin signaling sensitization; and (3) Nrf2/ARE anti-oxidation and TGF-β/Smads anti-fibrosis regulation. Different exercise modalities activate these pathways with distinct emphases: MICT most directly and persistently activates the AMPK pathway; resistance exercise uniquely improves IRS/PI3K/Akt signaling through muscle mass gain; HIIT induces the highest AMPK activation intensity and triggers unique lactate-mediated signaling regulation; combined training integrates the above multiple mechanistic advantages. For clinical translation, multidisciplinary team collaboration is essential to ensure safety and adherence; individualized prescriptions should be formulated according to the FITT-VP principle and patient phenotypes—frequency of 3-5 sessions/week of aerobic exercise combined with 2-3 sessions/week of resistance exercise; intensity of moderate-intensity (40%–<60% heart rate reserve (HRR))aerobic exercise and 60%-80% of one-repetition maximum (1-RM) for resistance exercise; time of at least 150 min/week of moderate-intensity aerobic exercise, 30-60 min per session; type of combined training as the preferred modality; total volume of ≥500-1 000 MET-min/week; and progression adjusted every 4-6 weeks—with real-time adjustments supported by wearable devices, ultimately forming a closed-loop management system from initial assessment to long-term follow-up. Notably, current studies have limitations such as small sample sizes and short intervention periods. Future research should focus on long-term follow-up, multi-omics biomarkers, and combined exercise-drug strategies. In conclusion, the systematic integration of structured, individualized, and sustainable exercise interventions into the multidisciplinary management pathway for patients with T2DM complicated by MAFLD is an urgent need in current clinical practice.

Objective Oxygen partial pressure (pO?) is a critical indicator of the tumor microenvironment and plays an essential role in regulating tumor progression and therapeutic response, particularly for oxygen-dependent treatments such as photodynamic therapy (PDT). Although photoacoustic imaging (PAI) has shown great potential for functional and molecular imaging, conventional oxygenation imaging approaches based on hemoglobin absorption mainly provide relative oxygen saturation information and cannot directly quantify tissue oxygen partial pressure. Therefore, this study aimed to develop a fast laser sequence-based pump-probe photoacoustic tomography (PP-PAT) system for quantitative, non-invasive, and dynamic monitoring of oxygen partial pressure in tumor tissues.Methods The proposed PP-PAT system was developed based on the oxygen-sensitive triplet-state lifetime characteristics of methylene blue (MB). Upon optical excitation, MB molecules undergo transitions from the ground state to an excited state and subsequently form metastable triplet states through intersystem crossing. The lifetime of the triplet state is strongly affected by surrounding oxygen concentration due to dynamic oxygen quenching, providing a direct correlation between triplet-state kinetics and local oxygen partial pressure. A dual-wavelength pump-probe excitation scheme was implemented to selectively interrogate MB triplet-state dynamics. The pump pulse was used to initiate the triplet-state population, while the delayed probe pulse was applied to detect the transient triplet-state response. By optimizing the temporal interval between the pump and probe pulses, transient triplet-state differential (TTD) signals were extracted to enhance the specificity of oxygen-dependent molecular information and suppress background interference from conventional photoacoustic signals. The performance of the PP-PAT system was systematically evaluated through phantom and in vivo experiments. First, a single-tube phantom containing MB solution was used to investigate signal stability, reproducibility, and the influence of signal averaging on imaging quality. Subsequently, a dual-tube phantom model was established to simulate oxygen consumption during PDT, where one MB-containing tube was exposed to laser irradiation and the other served as a control. Finally, in vivo experiments were performed using a subcutaneous tumor model in nude mice. MB was locally injected into the tumor region before imaging to evaluate the feasibility of tumor oxygen partial pressure mapping using the proposed PP-PAT system.Results Phantom experiments demonstrated that the extracted TTD signals exhibited high stability and effectively reflected MB triplet-state dynamics while reducing non-specific background contributions. Signal averaging significantly improved the signal-to-noise ratio, and 50 repeated acquisitions provided an optimal compromise between image quality and acquisition efficiency. In the dual-tube phantom experiments, continuous PDT irradiation induced progressive oxygen depletion in the treated sample. The corresponding TTD decay rate gradually decreased, accompanied by an increase in the calculated triplet-state lifetime, indicating reduced oxygen quenching and decreased oxygen partial pressure. In contrast, the control sample showed relatively stable TTD kinetics and oxygenation levels during the same period. These results demonstrated that PP-PAT could quantitatively characterize oxygen consumption dynamics associated with photochemical reactions. In vivo experiments further demonstrated the capability of PP-PAT for spatially resolved oxygen partial pressure imaging in MB-injected tumor tissues. The reconstructed pO? maps revealed heterogeneous oxygen distributions within tumors, showing relatively hypoxic regions in the tumor core and higher oxygenation levels near the tumor boundary. This spatial oxygen distribution pattern was consistent with the typical physiological characteristics of solid tumors, where abnormal vascular structures and limited oxygen diffusion result in intratumoral oxygen gradients.Conclusion This study presents a fast laser sequence-based PP-PAT system capable of quantitative and non-invasive imaging of tissue oxygen partial pressure. By utilizing the oxygen-dependent triplet-state lifetime of MB and extracting TTD signals, the proposed method provides molecularly specific information related to oxygen dynamics beyond conventional photoacoustic oxygenation imaging. The system enables dynamic monitoring of oxygen consumption during PDT and reveals spatial oxygen heterogeneity within tumors. This technique provides a promising imaging approach for tumor hypoxia characterization, evaluation of oxygen-dependent therapeutic responses, and precision-guided cancer treatment.

Alzheimer's disease (AD) is pathologically characterized by cerebral amyloid β-protein (Aβ) aggregation, neurofibrillary tangles and progressive cognitive deterioration. There is an urgent clinical demand for targeted therapeutic agents against AD, whereas the blood-brain barrier (BBB) acts as a critical physical barrier that blocks over 98% small-molecule drugs and nearly all biomacromolecules from entering brain parenchyma. Nanomedicine-based drug delivery systems (NDDSs) with tunable physicochemical properties can cross the BBB via multiple transcytosis pathways including adsorptive-mediated, receptor-mediated and transporter-mediated routes, opening a promising avenue for targeted AD treatment. A core academic viewpoint proposed herein is that robust in vitro endothelial penetration of nanocarriers cannot guarantee effective accumulation in brain target cells. Comprehensive evaluation of BBB-crossing delivery efficiency should not merely rely on in vitro permeability tests, but cover the full multi-step transcytosis cascade, cellular tropism in brain tissues and in vivo therapeutic outcomes. This review systematically sorts out diverse nanoplatforms applicable to BBB penetration for AD intervention. Inorganic nanomaterials such as gold and ceria nanoparticles possess large specific surface areas and intrinsic antioxidant capacity, which eliminate reactive oxygen species and hinder Aβ fibrillization. Liposomal formulations and solid lipid nanoparticles exhibit superior biocompatibility with biomimetic phospholipid bilayer architectures, capable of co-loading hydrophilic nucleic acids for Tau regulation and lipophilic Aβ inhibitors; relying on receptor-mediated transcytosis, they achieve sustained drug retention in the brain. Polymeric nanocarriers including nanogels and polyamidoamine dendrimers enable multi-target combinatorial therapy, and can be engineered to release cargo in response to inflammatory microenvironments, thereby suppressing excessive microglial activation and protecting neuronal mitochondria. Beyond conventional nanocarriers, this work elaborates two cutting-edge BBB-crossing delivery platforms: biomimetic nanosystems and metal-organic frameworks (MOFs). Biomimetic nanoparticles camouflaged with erythrocyte, platelet or macrophage membranes, as well as natural exosomes, evade immune clearance, prolong systemic circulation and inherently home to inflammatory lesions. Serving as “nano-decoys”, they neutralize Aβ neurotoxins and remodel cerebral inflammatory microenvironments simultaneously. MOFs feature high porosity and customizable pore channels for co-delivery of multiple therapeutics, and can be integrated with near-infrared photothermal and photooxidation modalities to facilitate focal brain lesion therapy. This review highlights a transformative paradigm shift in the field of BBB-targeted AD therapy: research focus has shifted from simply maximizing cerebral drug penetration toward active modulation and functional restoration of the BBB. Impaired BBB transporters intrinsically impede endogenous Aβ clearance. Accordingly, BBB-regulating nanocarriers are designed to remodel the low-density lipoprotein receptor-related protein 1 (LRP1) trafficking cascade, redirecting endocytic vesicles from lysosomal degradation to non-degradable transcytosis and restoring the intrinsic Aβ efflux capacity of the BBB. Distinct from conventional strategies that only exert local lesion inhibition, this systemic clearance strategy eliminates cerebral Aβ deposits by accelerating peripheral excretion.

Glycosylation constitutes a critical, highly intricate, and diverse co- and post-translational modification characterized by the covalent attachment of sugar moieties to proteins, lipids, or small RNAs. Complex glycans are ubiquitously present across nearly all living organisms. Despite their prevalence, our comprehension of glycan diversity remains limited, likely due to the inherent challenges associated with elucidating their structural complexity. Among post-translational modifications, protein glycosylation is notably prevalent, involving the enzymatic transfer of oligosaccharides to specific amino acid residues by glycosyltransferases. This modification plays a pivotal role in modulating protein function, including participation in various biological and biochemical recognition processes. G protein-coupled receptors (GPCRs), encoded by approximately one thousand genes, share a conserved architecture comprising seven transmembrane helices interconnected by three intracellular and three extracellular loops. Representing the largest family of human membrane proteins, GPCRs regulate a vast array of physiological and pathological processes, thereby constituting the most extensive class of therapeutic targets. In mammalian systems, the majority of GPCRs undergo glycosylation predominantly at their extracellular N-terminus or extracellular loops, primarily through N-linked and O-linked glycosylation. These covalent carbohydrate modifications exert profound effects on multiple facets of GPCR biology, including endoplasmic reticulum folding and quality control, membrane trafficking and surface expression, receptor internalization and recycling or degradation, ligand binding and signal transduction, biased signaling, and receptor dimerization. Notably, glycosylation can exert both positive and negative regulatory influences on these processes. Dysregulation of GPCR glycosylation has been implicated in a range of pathological conditions, such as cancer, diabetes, and neurological disorders, underscoring its physiological and pathological significance. Aberrant glycosylation patterns may lead to dysfunctional receptor signaling, thereby contributing to disease progression. Consequently, elucidating the precise roles of glycosylation in GPCR function not only enhances fundamental understanding of receptor biology but also facilitates the development of novel therapeutic strategies targeting glycosylation pathways or specific GPCR glycoforms. Although the functional consequences of glycosylation have been investigated for several decades, delineating their exact structural underpinnings has remained challenging due to the intrinsic flexibility and heterogeneity of carbohydrate structures. Recent advances in structural biology, particularly single-particle cryo-electron microscopy (cryo-EM) and X-ray crystallography, have catalyzed a paradigm shift in our understanding of GPCR glycosylation. The integration of these sophisticated structural techniques with biochemical approaches has redefined glycosylation as a complex structural element integral to receptor function. These developments provide a molecular framework for comprehending how glycans influence receptor pharmacology and open new avenues for the rational design of glyco-engineered biologics and allosteric modulators targeting specific extracellular motifs. This mini-review concentrates on glycosylation within the GPCR superfamily, summarizing the impact of glycosylation modifications on receptor function and regulatory mechanisms, recent progress in the structural biology of GPCR glycosylation, and prospective directions for future research in this field.

CRISPR-Cas-based biosensing systems have become important platforms for rapid nucleic acid detection because of their programmable sequence recognition and high specificity. In many diagnostic workflows, the CRISPR reaction is coupled with polymerase chain reaction or isothermal pre-amplification to enrich low-abundance targets before readout. This design improves sensitivity, but it also introduces additional primers and enzymes, requirements for temperature control and reaction compatibility, and a higher demand for contamination management. These factors make the whole assay less convenient for integrated and field-deployable point-of-care testing. Developing pre-amplification-free CRISPR assays is therefore not simply a pursuit of shorter protocols, but a way to simplify molecular diagnosis at the system level, especially in settings where rapid decisions, closed workflows, and minimal manual operation are required. Microfluidic devices provide an important engineering route for this purpose. Their small reaction volumes, precise fluid manipulation, high-throughput partitioning, and compatibility with portable readout make it possible to integrate target confinement, reaction control, signal acquisition, and quantitative analysis on a chip. Droplet microfluidics and microwell arrays can divide a sample into large numbers of independent microreactors, enabling digital counting of rare recognition events. Continuous-flow, centrifugal, and paper-based microfluidic formats further provide options for automated operation, low-cost fabrication, and on-site use. In this context, microfluidics is not only a signal-enhancement method, but also a platform that connects CRISPR molecular recognition with practical assay implementation. This review summarizes recent progress in microfluidic-based pre-amplification-free CRISPR-Cas biosensing for rapid detection. We focus on four related technical directions. crRNA engineering, including spacer-length tuning, multi-crRNA design, chemical modification, and allosteric regulation, can improve recognition kinetics, nuclease stability, and mismatch discrimination. Digital microfluidic detection based on droplets or microwell arrays converts single-molecule recognition events into countable positive partitions, thereby improving quantitative capability without target pre-amplification. Physical signal transduction interfaces couple CRISPR activity to electrochemical, electrochemiluminescent, fluorescent, or surface-enhanced Raman scattering readouts, making weak molecular signals easier to detect with portable instruments. On-chip cascade signal amplification strategies further enhance output intensity through enzymatic reactions, DNA circuits, nanomaterials, or cross-domain amplification modules while avoiding direct amplification of the target nucleic acid. Together, these strategies show that the performance of a pre-amplification-free assay depends not only on biochemical recognition, but also on how the reaction is confined, amplified, transduced, and operated. In addition to describing these mechanisms, this review compares different strategies in terms of sensitivity improvement, operational complexity, cost, and suitability for point-of-care testing. Representative applications in food authenticity identification and rapid pathogen screening are also discussed to illustrate how these platforms perform in practical scenarios. Finally, we analyze the remaining challenges, including the detection of low-abundance targets in complex matrices, on-chip sample preparation, device-to-device reproducibility, long-term reagent storage, and standardization. Future development will likely depend on tighter integration of sample processing, CRISPR reaction, signal readout, and data interpretation, ultimately moving pre-amplification-free CRISPR diagnostics toward automated and user-friendly sample-to-answer systems.

Neurodegenerative diseases (NDs), particularly Alzheimer's disease (AD) and Parkinson's disease (PD), and cardiovascular diseases (CVDs), including heart failure (HF) and coronary artery disease (CAD), are major chronic disorders associated with population aging. Their frequent coexistence in clinical practice suggests that they may not progress independently, but may instead be linked through bidirectional pathological communication within the brain-heart axis. Epidemiological evidence underscores this clinical burden: systematic reviews and meta-analyses have reported pooled relative risks for dementia of approximately 1.27 among individuals with a history of CAD and 1.60 among those with HF, while the pooled prevalence of cognitive impairment and dementia in patients with HF has been estimated at approximately 41.42% and 19.79%, respectively. This review synthesizes current evidence on the mechanistic links, disease-state manifestations, biomarkers, and potential therapeutic strategies involved in the comorbidity between NDs and CVDs from the perspective of the brain-heart axis. The brain and heart communicate through autonomic, neuroendocrine, neuroimmune, vascular, and humoral pathways. Sympathetic activation, parasympathetic withdrawal, vagal dysfunction, cerebral hypoperfusion, endothelial injury, blood-brain barrier (BBB) alterations, peripheral immune activation, and circulating inflammatory mediators may jointly contribute to cross-organ pathological signaling. Oxidative stress and inflammatory response are not specific to the brain-heart axis; rather, they may act as candidate amplifying processes within this network. Mitochondrial dysfunction and NADPH oxidase activation can increase the generation of reactive oxygen species and reactive nitrogen species, which may activate nuclear factor-κB, the NLRP3 inflammasome, and mitogen-activated protein kinase/c-Jun N-terminal kinase signaling. These pathways can promote the release of interleukin-1β, interleukin-6, tumor necrosis factor-α, and other inflammatory mediators, which may in turn aggravate mitochondrial injury, endothelial dysfunction, immune cell activation, and further oxidant generation. Cytokines, chemokines, oxidized lipids, mitochondrial DNA, damage-associated molecular patterns, and extracellular vesicles may transmit these signals between the cardiovascular and central nervous systems, whereas autonomic reflexes provide an additional route for bidirectional amplification. Distinct disease states illustrate different manifestations of this network. The association between AD and CVDs may involve vascular risk factors, impaired amyloid-β clearance, abnormal cholesterol homeostasis, cerebral microvascular injury, neuroinflammation, and endothelial dysfunction. HF-related cognitive impairment may be linked to reduced cardiac output, recurrent cerebral hypoperfusion, hypoxia-related signaling, BBB dysfunction, circulating inflammation, and impaired autonomic feedback. In PD, cardiovascular autonomic dysfunction and abnormalities in heart rate and blood pressure regulation may interact with vascular injury, reduced cerebral perfusion, inflammation, and oxidative stress. However, the relationship between PD and CAD remains heterogeneous and may be modified by age, ethnicity, medication use, metabolic factors, and coexisting diseases. Biomarker evaluation should therefore move beyond isolated indicators. Traditional markers, including malondialdehyde, superoxide dismutase, glutathione, C-reactive protein, and interleukin-6, reflect systemic oxidative or inflammatory burden but lack sufficient specificity to distinguish primary neurodegeneration, cardiovascular injury, or a comorbid state involving both. Greater clinical value may be obtained from cross-system panels that combine oxidative stress and inflammatory markers with cardiac stress or injury biomarkers, such as N-terminal pro-B-type natriuretic peptide; glial or neuronal biomarkers, such as glial fibrillary acidic protein and neurofilament light chain; BBB- or endothelial injury-related biomarkers; and omics-derived candidates, including microRNAs, long non-coding RNAs, DNA methylation signatures, metabolites, and proteins. Multi-omics integration and artificial intelligence-assisted analysis may support risk stratification, disease monitoring, and prediction of treatment response. However, these approaches require standardized analytical platforms, validation in independent cohorts, and careful distinction between associative findings and causal mechanisms. Potential interventions include antioxidant, anti-inflammatory, mitochondria-targeted, and multi-target combination strategies, together with emerging approaches such as nanodelivery, CRISPR/Cas9- or CRISPR/dCas9-based regulation, mesenchymal stem cell-mediated mitochondrial transfer, and ergothioneine supplementation. Nevertheless, most available evidence is indirect, preclinical, or derived from other disease indications, and no single drug or technology can currently be regarded as specific to brain-heart axis comorbidity. The clinical relevance of these strategies will depend on whether they can be matched to dominant pathological phenotypes and improve both neurological and cardiovascular outcomes. Overall, comorbidity between NDs and CVDs is more appropriately understood as a heterogeneous cross-organ regulatory network than as a disorder driven by a single pathway. Future research should prioritize multicenter longitudinal cohorts, standardized clinical phenotyping, validation of cross-system biomarker panels, and mechanism-guided interventions in clearly defined patient subgroups, with integrated assessment of cognitive function, cardiovascular events, quality of life, long-term safety, and treatment response.

Nicotinic acetylcholine receptors (nAChRs) are pentameric ligand-gated ion channels (pLGICs) that mediate rapid cholinergic synaptic transmission throughout the central and peripheral nervous systems. These receptors are integral to neuromuscular junction signaling, autonomic regulation, cognitive learning, reward-related behavior, and neuroplasticity. The nAChR family exhibits remarkable functional diversity through combinatorial assembly of seventeen identified subunits (α1-α10, β1-β4, γ, δ, and ε). Among these, the α9 subunit occupies a distinctive phylogenetic position, exhibiting greater sequence divergence from other neuronal α subunits and possessing unique biochemical properties that distinguish it from all other family members. α9 can form homopentamers and also co-assemble with the α10 subunit to form functional heteropentamers, primarily in (α9)₂(α10)₃ and (α9)₃(α10)₂ stoichiometries. This dual assembly strategy generates functional heterogeneity, as distinct subunit compositions confer differential ion permeation, ligand sensitivity, and desensitization kinetics. The structural determinants governing this stoichiometric variability remain incompletely resolved, representing a critical gap in our mechanistic understanding. Unlike most other nAChR subtypes, traditional agonists of nAChRs (such as nicotine) elicit virtually no agonistic effect on α9* nAChRs (α9-containing receptors, including α9 homopentamers and α9α10 heteropentamers). This pharmacological divergence reflects structural differences within the orthosteric site, particularly in regions at complementary subunit interfaces. As cation-selective channels, α9* nAChRs exhibit high permeability to Ca²⁺. In cochlear outer hair cells, α9α10 nAChRs mediate cholinergic efferent modulation by the medial olivocochlear (MOC) bundle. Acetylcholine-evoked Ca²⁺ influx activates functionally coupled SK2 potassium channels, generating net hyperpolarization that dampens electromechanical amplification through a tightly constrained signaling microdomain. This Ca²⁺-dependent excitatory-to-inhibitory conversion exemplifies sophisticated sensory gain control, and its disruption contributes to noise-induced hearing loss, age-related hearing loss, and tinnitus. Beyond canonical ionotropic signaling, α9* nAChR engages metabotropic transduction pathways. In macrophages, receptor activation modulates cytokine production and inflammatory responses. In keratinocytes, it regulates wound healing by modulating cell migration and differentiation. In dorsal root ganglion sensory neurons, α9* signaling contributes to nociceptive processing and inflammatory hyperalgesia. This functional pleiotropy, spanning both ionotropic signaling and metabotropic transduction, positions α9* nAChR as an exemplary model for investigating signal polymorphism within the pLGIC superfamily. Pathophysiologically, α9* nAChR dysfunction is implicated across multiple organ systems. In the auditory system, disruption of α9α10 nAChR-mediated MOC efferent feedback impairs cochlear gain control, predisposing to noise-induced synaptopathy and age-related hearing loss. In immune cells, dysfunctional α9* nAChR signaling disrupts cholinergic anti-inflammatory pathway activity, exacerbating pro-inflammatory responses. In the peripheral sensory system, aberrant α9* nAChR signaling has been implicated in neuropathic and inflammatory pain states. In skin, impaired receptor function compromises keratinocyte migration and re-epithelialization through disrupted signaling pathways, leading to chronic wound healing defects and inflammation. These pathophysiological associations have catalyzed pharmacological interest, yielding promising chemical entities including α-conotoxins, small-molecule antagonists/agonists, and allosteric modulators. α-Conotoxin peptides, in particular, demonstrate remarkable subunit selectivity and potent antinociceptive effects in preclinical pain models. However, therapeutic translation faces substantial challenges: the broad tissue distribution of α9* nAChR risks on-target adverse effects in non-target organs; pronounced species differences between rodent and human receptors complicate preclinical validation; and the complexity of ionotropic-metabotropic signaling crosstalk demands pharmacological strategies that extend beyond conventional orthosteric agonism or antagonism. Looking forward, integrating cryo-electron microscopy of full-length receptors in distinct conformational states with single-channel electrophysiology and systems-level circuit analysis promises to illuminate the molecular mechanisms governing α9* nAChR function and regulation. The development of signal pathway-biased ligands and tissue-selective delivery strategies may ultimately harness the therapeutic potential of this receptor while mitigating safety liabilities. As a paradigm for understanding pLGIC signaling diversification, α9* nAChR research will continue to inform broader questions regarding ion channel evolution, allosteric regulation, and pathophysiological mechanisms of chronic pain and autoimmune inflammatory diseases.

Meiotic recombination is a core molecular event that generates genetic diversity in sexually reproducing organisms, and is of great significance for both genome evolution and proper chromosome segregation. Meiotic recombination occurs in two forms: crossover (CO) and non-crossover (NCO). Although NCO events are far more abundant than CO events, they have been difficult to detect. Consequently, previous research has largely focused on CO, leaving the characteristics and functional roles of NCO poorly understood. A recent study published in Nature used large-scale family-based whole-genome sequencing data to construct a high-resolution recombination map. This map revealed the mutational features induced by NCO—the dominant form of recombination—along with their sex-specific differences, and quantified, for the first time, the contribution of NCOs to de novo mutations and age-related effects, representing an important milestone in the field of meiotic recombination. Specifically, compared with paternal NCOs, maternal NCOs are fewer in number but span longer regions; they accumulate continuously with increasing maternal age and occur largely outside programmed recombination hotspots. NCOs also represent a major source of de novo mutations, with approximately 11% of maternal de novo mutations being attributable to NCOs. This study not only provides a high-resolution map of human meiotic recombination as a resource for future research, but also offers, for the first time, a genome-wide perspective on the contribution of meiotic NCO recombination to genetic diversity.

Organoid technology has become a highly promising in vitro model in biomedical research, but its traditional culture relies on animal-derived basement membrane matrices, which suffer from batch-to-batch variability, undefined biochemical composition, and poorly controllable mechanical properties. Recent studies have confirmed that matrix stiffness, viscoelasticity, topography, and temporal mechanical dynamics play regulatory roles equally as critical as biochemical signals in stem cell self-organization, lineage specification, and functional maturation of organoids. This review systematically summarizes the progress in understanding how extracellular matrix (ECM) mechanical properties regulate organoid formation. Focusing on the YAP/TAZ factors and the integrin receptors, which engage in crosstalk with biochemical signals to synergistically determine cell fate. We then elaborate how specific mechanical parameters, such as stiffness, viscoelasticity, and topography, influence each distinct stage of organoid development, from initial aggregation and compaction, through proliferative expansion, to lineage-committed differentiation and terminal functional maturation. Appropriate stiffness facilitates efficient aggregation and symmetry breaking, while excessive rigidity impairs proliferation and accelerates cellular senescence. In hepatic organoid expansion where only stiffness matching liver tissue (~6.2 kPa) supported robust growth. Viscoelastic stress relaxation promotes integrin clustering, enhances focal adhesion maturation, and stimulates endogenous ECM deposition, thereby supporting self-organized crypt-villus architecture and basement membrane assembly. Notably, dynamic softening of hydrogels enables optimal crypt budding, whereas rapid stress relaxation permits nephron segment coiling and drives vascular organoid maturation toward arteriole differentiation, highlighting stress relaxation as a key temporal parameter. Topographical cues provide contact guidance that directs polarized outgrowth, lumen formation, and neuronal orientation, all of which are essential for achieving organotypic architecture. The embedded 3D printing of complex neural networks enables precise control over branching geometries, facilitating studies of morphogenesis under spatial constraints. The engineered mechanical microenvironments have been successfully applied to recapitulate disease phenotypes: stiff matrices induce fibrosis and epithelial-mesenchymal transition in liver organoids, promote chemoresistance in cholangiocarcinoma. Furthermore, we summarize engineering strategies for both natural and synthetic hydrogels aimed at creating mechanically defined culture platforms. Natural biomaterial modifications achieve spatial separation of mechanical constraints from biochemical support, enabling self-limited compressive stimulation within a defined time window. Synthetic polymers allow independent tuning of stiffness, ligand density, and viscoelasticity through adjustable crosslinking and dynamic non-covalent interactions, thus providing orthogonal control over multiple mechanical parameters. Dynamic microenvironments that mimic progressive stiffening as observed in development, tumor evolution, or fibrosis can be constructed using composites that undergo spontaneous structural transitions. In the future, critical challenges include deciphering the synergistic rules governing mechanical-biochemical interplay, developing spatiotemporally programmable hydrogels that enable on-demand modulation of local mechanics, establishing comprehensive databases of tissue-specific mechanical parameter windows, and advancing standardized high-throughput screening platforms to accelerate preclinical validation and clinical translation. Moreover, integrating real-time mechanical sensors and non-invasive imaging techniques would allow dynamic monitoring of intracellular forces and tissue-level stress during culture. Ultimately, this review aims to provide a theoretical foundation for deepening our understanding of mechano-biological coupling mechanisms and for rationally designing high-fidelity, physiologically relevant organoid culture platforms that fully harness the regulatory power of mechanical cues.

Enhancer-promoter communication is fundamental to the spatial and temporal control of gene expression. Cohesin-mediated loop extrusion has long been considered a major structural mechanism that brings distal regulatory elements into proximity with their target promoters. Recent findings from Aboreden et al. refine this view by showing that depletion of Nipped-B-like protein (NIPBL), a key regulator of cohesin loading and loop extrusion, markedly disrupts architectural chromatin loops, whereas many cis-regulatory contacts and broad post-mitotic transcriptional reactivation are only modestly affected. These observations suggest that loop extrusion is important, but not sufficient, for explaining productive regulatory communication. In this Comment, we discuss how transcriptional condensate-like assemblies may provide an additional biochemical and kinetic layer that helps convert regulatory proximity into transcriptional output. By locally enriching transcription factors, coactivators, Mediator and RNA polymerase II (Pol II) around active loci, such regulatory hubs may stabilize productive enhancer–promoter encounters and modulate transcriptional activity. We further propose that transcriptional bursting provides a useful framework for understanding this conversion, because gene expression can be decomposed into burst frequency, burst duration and burst size. Integrating chromatin architecture, condensate organization and bursting dynamics may therefore provide a more complete view of how enhancer-promoter communication is re-established after mitosis and how regulatory proximity is converted into transcriptional output through mechanisms beyond loop extrusion.

The abnormal accumulation, structural change, and spread of tau protein in the brain are now considered important factors in the progression of Alzheimer’s disease (AD) and many other tau-related neurodegenerative diseases. Clinical and pathological studies have shown that the amount and distribution of abnormal tau protein are closely related to synaptic damage, neuronal loss, and cognitive decline. Therefore, tau protein has become an important target for disease-modifying therapy. However, tau is difficult to target because it has no fixed structure, lacks a clear active site, undergoes many post-translational modifications, and forms different abnormal structures in different diseases and disease stages. Therefore, the effective and selective removal of harmful tau species is both a major opportunity and a major challenge in drug discovery for neurodegenerative diseases. Proteolysis-targeting chimeras (PROTACs) offer a new strategy to deal with this problem. Unlike traditional inhibitors, PROTACs do not simply block protein function. Instead, they bring the target protein close to an E3 ubiquitin ligase, which leads to ubiquitination and degradation of the target protein by the proteasome. This event-driven mechanism may be especially useful for disease-related proteins such as tau, which are hard to inhibit with traditional small molecules. In recent years, tau protein-targeting PROTACs and related degradation strategies have shown promising effects in cell and animal models. These effects include reducing abnormal tau protein levels, lowering synaptic toxicity, regulating disease-related signaling pathways, and improving behavioral or cognitive outcomes. These studies support targeted tau protein degradation as a promising therapeutic approach, although many problems still need to be solved before clinical use. In this review, we summarize recent progress in the development of tau protein-targeting PROTACs and discuss the main factors that affect their design and activity. We focus on the choice of tau protein-binding ligands, their binding sites, and their ability to recognize abnormal tau protein rather than normal tau protein. We also discuss the selection of E3 ligase recruiters, linker length and structure, ternary complex formation, and structure-activity relationships that influence degradation potency and selectivity. In addition, we introduce new strategies beyond traditional proteasomal degradation, including the regulation of tau protein phosphorylation and autophagy-based clearance. These approaches may be more suitable for different tau species or different stages of disease. A major challenge for tau protein-targeting PROTACs is delivery to the central nervous system. Many PROTACs have high molecular weight, large polar surface area, flexible structures, and may be removed by efflux transporters. As a result, they often have poor ability to cross the blood-brain barrier and may not reach enough free drug levels in the brain. Therefore, the therapeutic potential of tau protein-targeting PROTACs depends not only on their ability to degrade tau protein <i>in vitro</i>, but also on whether they can achieve long-lasting, selective, and safe target engagement in important brain regions after practical administration. Future studies should focus on improving selectivity for abnormal tau protein, understanding E3 ligase function in neural cells, designing brain-penetrant molecules, developing better delivery methods, and testing these drugs in models that better reflect human disease. Overall, tau protein-targeting PROTACs are a promising and fast-developing strategy for treating tau-related diseases. However, their successful clinical translation will require progress in chemical biology, medicinal chemistry, neuroscience, drug delivery, and translational medicine.

Diabetic sarcopenia (DS) is a common but often ignored skeletal muscle complication in individuals with diabetes mellitus. It is characterized by progressive loss of skeletal muscle mass, reduced muscle strength, and impaired physical performance, which may further increase the risk of falls, disabilities, metabolic disorders, and adverse clinical outcomes. Traditionally, DS has been attributed mainly to hyperglycemia, insulin resistance, aging-related muscle decline, and chronic complications of diabetes. However, increasing evidence suggests that lipid metabolic disturbance and pathological lipid metabolic reprogramming are not merely secondary consequences of diabetes, but may actively participate in the initiation and progression of DS. Under diabetic conditions, impaired fatty acid uptake, transport, oxidation, and storage disrupt skeletal muscle metabolic homeostasis, leading to ectopic lipid deposition and accumulation of lipotoxic intermediates. These lipid-derived metabolites can aggravate insulin resistance, impair mitochondrial energy production, enhance oxidative stress, activate chronic low-grade inflammation, and disturb protein synthesis and degradation balance, thereby accelerating skeletal muscle atrophy and functional decline. Lipid metabolic dysregulation may also interact with multiple pathological processes involved in DS, including mitochondrial dysfunction, inflammatory signaling, oxidative damage, impaired autophagy, and gut microbiota imbalance. These mechanisms do not occur independently; instead, they form a complex bidirectional vicious cycle with diabetes-related metabolic disorders. Specifically, mitochondrial dysfunction reduces fatty acid oxidative capacity, which further promotes lipid accumulation and lipotoxicity. Inflammatory activation can impair insulin signaling and muscle protein metabolism, while lipid overload may in turn amplify inflammatory responses. Similarly, gut microbiota dysbiosis and altered microbial metabolites may influence systemic inflammation, lipid metabolism, and skeletal muscle homeostasis. Therefore, lipid metabolic reprogramming provides an important mechanistic perspective for understanding the progression of DS from metabolic disturbance to structural and functional muscle impairment. Exercise intervention is an effective and clinically feasible non-pharmacological strategy for the prevention and management of DS. Both aerobic exercise and resistance training have been shown to improve insulin sensitivity, enhance fatty acid oxidation, increase mitochondrial biogenesis, reduce ectopic lipid deposition, and attenuate lipotoxic metabolite accumulation. These adaptations not only improved glucose and lipid metabolism, but alsoincreased the preservation of muscle mass, muscle strength, and physical function. Moreover, combined exercise strategies may provide complementary benefits by integrating the metabolic advantages of aerobic exercise with the anabolic and functional effects of resistance training. Based on analyses of publicly available datasets and literature evidences, this review systematically summarizes the role of lipid metabolic disorders in the pathogenesis of DS, with particular attention to the molecular mechanisms linking lipid dysregulation to insulin resistance, chronic inflammation, oxidative stress, mitochondrial dysfunction, and gut microbiota disturbance. Furthermore, this review discusses the potential mechanisms by which exercise intervention improves DS through the regulation of lipid metabolic reprogramming, and outlines exercise prescription strategies in terms of modality, intensity, frequency, and duration. Understanding the interaction between lipid metabolism and skeletal muscle dysfunction may provide new theoretical evidence for early identification, mechanistic research, and precision exercise therapy in DS. Overall, targeting pathological lipid metabolic reprogramming through exercise intervention represents a promising and clinically actionable approach for improving muscle health and prognosis in individuals with DS.

Colorectal cancer (CRC) is characterized by persistently high incidence and mortality. Current therapies are limited by drug resistance and modest patient benefit, underscoring the urgent need for new perspectives rooted in tumor biology. The unique metabolic landscape of CRC makes it an ideal model in which to dissect the pathological roles of lactylation regulatory networks: microsatellite-stable (MSS) CRC, which accounts for approximately 85% of cases, concurrently upregulates glycolysis and oxidative phosphorylation, engaging in intense metabolic competition with immune cells; the intratumoral lactate pool exhibits a distinctive “dual-source supply” feature—in addition to tumor-intrinsic glycolysis, substantial exogenous lactate is provided by gut microbiota dysbiosis and by colonizing bacteria within liver metastases; high-frequency oncogenic mutations and lactylation modifications establish a feed-forward circuit of “oncogene-driven lactate accumulation-lactylation-facilitated tumor progression”. Moreover, MSS CRC displays near-complete unresponsiveness to immune checkpoint inhibitors, a phenomenon underpinned by multiple immune evasion mechanisms mediated by lactate and lactylation. Lactate metabolism is a hallmark of metabolic reprogramming in cancer. Lactate homeostasis provides tumor cells with metabolic substrates, modulates redox status, and regulates fatty acid metabolism to promote malignant progression. Notably, lactate can drive lactylation—an emerging post-translational modification (PTM) in which lactyl groups are attached to lysine residues, dynamically governing gene transcription and protein function and thereby establishing a bridge between metabolism and epigenetics. Lactate and lactylation form a multidimensional, coordinated network: lactylation of key metabolic enzymes such as LDHA reinforces a positive feedback loop that sustains lactate production; lactylation of upstream transcription factors such as HIF-1α drives metabolic reprogramming; furthermore, lactylation engages in crosstalk with m6A and m5C RNA modifications as well as with other PTMs such as acetylation, profoundly reshaping cellular behavior. In CRC, histone lactylation drives malignant phenotypes by activating immunosuppressive programs, inhibiting ferroptosis, and promoting invasion and migration; non-histone lactylation accelerates translation elongation, stabilizes β-catenin, maintains redox homeostasis, and prevents PD-L1 degradation, thereby facilitating tumor progression. Lactylation-related gene signatures have demonstrated potential for prognostic stratification. Therapeutic strategies targeting the lactylation network range from upstream metabolic intervention to modulation of the modifying enzymes and direct blockade of lactylation modifications, forming a hierarchical interventional framework. However, current evidence derives predominantly from cell lines and xenograft models, and a causal relationship between lactylation and malignant progression in CRC has yet to be rigorously established. Whether inhibition of lactylation can alter CRC phenotypes independently of metabolic alterations and acetylation fluctuations remains a central unanswered question in the field. This review systematically examines the research progress and translational challenges surrounding lactylation regulatory networks, aiming to provide a circumspect assessment to inform the development of novel therapeutic strategies for CRC.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a steadily rising global prevalence, yet effective pharmacological interventions remain notably limited, highlighting an urgent need for safe, accessible, and mechanism-based therapeutic strategies. Physical exercise has emerged as a promising non-pharmacological intervention that ameliorates both core symptoms—social communication deficits and restricted repetitive behaviors—and associated features including cognitive dysfunction and motor impairments, in children and adolescents with ASD. However, the molecular mechanisms mediating these beneficial effects remain incompletely defined, impeding the development of evidence-based exercise prescriptions and biomarker-driven rehabilitation protocols. MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that post-transcriptionally regulate approximately 60% of protein-coding genes. Within the central nervous system, miRNAs orchestrate diverse neurobiological processes including neural progenitor proliferation, neuronal differentiation, dendritic spine morphogenesis, synaptic plasticity, and neuroinflammatory homeostasis. Notably, miRNAs are remarkably stable in biological fluids and can be packaged into extracellular vesicles, rendering them attractive candidates as both mechanistic mediators and non-invasive peripheral biomarkers. Among the hundreds of miRNAs expressed in the brain, three—miR-132, miR-34a, and miR-146a—have emerged as particularly relevant to ASD pathophysiology. This review focuses on these three miRNAs for the following reasons: miR-132 is a master regulator of activity-dependent synaptic plasticity through its modulation of BDNF/MeCP2/PTEN signaling and has been consistently downregulated in ASD prefrontal cortex; miR-34a functions as a pro-apoptotic factor that suppresses Bcl-2-mediated neuronal survival pathways and is upregulated in ASD cerebellum; and miR-146a serves as a key brake on neuroinflammation <i>via</i> TLR7/IRAK1 signaling and shows region-specific dysregulation in ASD temporal lobe. We first summarize evidence from human post-mortem brain tissues and ASD animal models demonstrating the consistent dysregulation of these three miRNAs. Notably, the pathological consequences of these miRNA alterations—impaired synaptic plasticity, excessive neuronal apoptosis, and sustained neuroinflammation—are interconnected and collectively contribute to the heterogeneous symptomatology of ASD. We then present a synthesis of emerging evidence demonstrating that various exercise modalities, including swimming, treadmill running, and voluntary wheel running, can concurrently reverse these ASD-like behavioral phenotypes and normalize the expression of the three key miRNAs. These data provide the first direct experimental evidence linking exercise-induced miRNA modulation to ASD symptom improvement. On the basis of these findings, we propose an integrative “exercise-miRNA-ASD” framework wherein exercise functions as a multi-targeted modulator—simultaneously enhancing synaptic plasticity, promoting neuronal survival, and attenuating neuroinflammation—through coordinated regulation of the three miRNAs. Importantly, this framework is not merely descriptive but offers testable predictions: exercise-induced miRNA changes should be dose-dependent, show temporal correlation with behavioral improvements, and be blunted by miRNA-specific antagonists or CRISPR/Cas9-mediated knockout. Beyond its specific application to ASD, this framework has broader implications. The miR-132/BDNF, miR-34a/Bcl-2, and miR-146a/TLR7 pathways are not ASD-specific but represent fundamental neural stress and repair mechanisms that are dysregulated across Alzheimer’s disease (AD), traumatic brain injury, Parkinson’s disease (PD), and major depressive disorder. Exercise has been shown to modulate these same miRNAs in several of these conditions, suggesting that the “exercise-miRNA-neural function” axis may represent a conserved neuroprotective mechanism that transcends diagnostic boundaries. Thus, we propose that ASD serves as an ideal model disease for elucidating this universal mechanism, with findings potentially generalizable to other neurological disorders. We also critically evaluate current translational barriers: the near-absence of human clinical trials with serial miRNA profiling; the undefined dose-response relationships between exercise parameters and miRNA expression; the unresolved causality issue (current evidence demonstrates association, not causation); and the uncertain correlation between peripheral exosomal miRNA levels and brain miRNA dynamics. We argue that future research must prioritize CRISPR/Cas9-based miRNA manipulation in animal models combined with longitudinal exercise interventions to establish causality, and that cross-disease validation studies are essential to determine whether exercise-induced miRNA changes represent a shared neuroprotective signature or disease-specific responses. Ultimately, we envision a paradigm where a simple blood test measuring exosomal miR-132, miR-34a, and miR-146a levels could guide personalized exercise prescriptions, enabling precision rehabilitation for individuals with ASD and potentially other neurological conditions.

Peripheral nerve injury (PNI) severs peripheral connections and induces profound reorganization of primary somatosensory (S1) and motor (M1) cortical maps, a dynamic process that critically shapes the extent and quality of functional recovery. Brain-derived neurotrophic factor (BDNF) has emerged as a central molecular hub linking the initial peripheral insult to subsequent central plastic changes. This review systematically examines BDNF-mediated cortical remodeling following PNI, with a particular emphasis on its spatiotemporally specific regulatory mechanisms and the therapeutic opportunities they present. Immediately after PNI, deafferented cortical territories undergo rapid functional silencing and, over time, become progressively encroached upon by adjacent intact representations. This maladaptive reorganization—characterized by sensory map fusion and motor compensatory invasion—actively impedes successful reinnervation and optimal recovery. Such phenomena have been consistently documented in both non-human primate models and human fMRI studies, spanning sensory and motor modalities. Motor remapping is also prominently observed in facial nerve injury and chronic nerve compression models, underscoring the universality of these plastic changes. Notably, a range of interventions including regional local anesthesia, auditory-tactile substitution, and guided tactile imagery can effectively mitigate this aberrant remodeling, revealing promising avenues for the therapeutic modulation of cortical plasticity during critical post-injury windows. BDNF coordinates post-PNI cortical remodeling through three mechanistically interconnected pathways. First, BDNF drives dendritic and axonal growth <i>via </i>TrkB receptor signaling: retrogradely transported axonal signaling endosomes integrate CREB-dependent transcriptional programs with mTOR-mediated local protein synthesis to bolster dendritic arborization and axonal elongation, while BDNF-induced Limk1 translation precisely fine-tunes actin cytoskeletal dynamics, thereby stabilizing dendritic spine morphology. Second, BDNF governs GABAergic interneuron maturation and perineuronal net formation through the JNK signaling cascade, thereby acting as a “plasticity brake” that preserves the delicate excitatory/inhibitory balance and constrains indiscriminate, maladaptive rewiring. Third, BDNF robustly potentiates NMDAR-dependent long-term potentiation (LTP) by elevating NMDA channel open probability and increasing synaptic receptor density, thus tightly coupling structural remodeling with functional synaptic strengthening. Concurrently, long-term depression pathways are subject to modulation, with NMDAR antagonism exerting time-dependent, bidirectional effects that vary with the post-injury phase. Superimposed on these mechanisms, the functionally antagonistic actions of proBDNF/p75NTR (favoring pruning and growth cone collapse) and mature BDNF/TrkB (promoting survival and stabilization) add further layers of regulatory complexity, highlighting the absolute necessity for precise spatiotemporal control in any therapeutic strategy. Extending our previous experimental findings, we introduce a “cortical reclamation threshold” model. In this framework, early upregulation of BDNF-TrkB signaling enhances inhibitory tone to restrict cortical encroachment by neighboring intact regions, whereas delayed but precisely timed BDNF delivery following surgical nerve repair actively facilitates the reclamation of the original, deafferented cortical maps by regenerating afferent fibers. Importantly, the common BDNF Val66Met polymorphism may significantly modulate individual thresholds, providing a biologically grounded rationale for patient stratification and personalized timing of intervention. Despite this mechanistic promise, clinical translation faces considerable hurdles. These include inherently poor pharmacokinetics of BDNF, severely limited penetration across the blood-brain barrier, dose-dependent neurotoxicity mediated through the p75NTR receptor, and the overarching dual-edged nature of BDNF signaling, which can simultaneously promote both adaptive and maladaptive plasticity. Emerging delivery platforms——including engineered exosomes, polymeric nanoparticles, cryogel microcarriers, and adeno-associated virus (AAV)-based gene therapy——offer potential solutions, but all require rigorous pharmacokinetic, toxicological, and functional validation. Future research priorities should encompass: (1) comprehensive single-cell and spatial transcriptomic mapping to resolve BDNF cellular sources and real-time signaling dynamics across distinct cortical layers and cell types; (2) genotype-stratified dose-response studies to establish safe, effective, and personalized delivery protocols; and (3) large-scale multicenter clinical trials that seamlessly integrate BDNF-targeted interventions with multimodal rehabilitation strategies, such as repetitive transcranial magnetic stimulation and mirror therapy, with longitudinal neuroimaging serving as a biomarker for cortical reclamation. By systematically addressing these priorities, we aim to transform BDNF from a critical endogenous regulator into a precisely controllable and titratable therapeutic target, ultimately enabling a paradigm shift from mere structural repair to true functional neural reconstruction following PNI.

Bone metastases are a common and serious complication of solid tumors such as breast cancer, prostate cancer, lung cancer, and kidney cancer, and occur at a high rate in patients with advanced cancer. This pathological process not only frequently leads to skeletal-related events such as severe bone pain, pathological fractures, spinal cord compression, and hypercalcemia—conditions that severely impact patients’ quality of life—but may also significantly increase the risk of death. Cancer bone metastasis is a complex, multistage cascade involving key steps such as the detachment of tumor cells from the primary tumor, their invasion and entry into the bloodstream, and their colonization, dormancy, and reactivation within the bone microenvironment. In recent years, exercise—as a safe and easily implementable non-pharmacological intervention—has demonstrated significant potential in inhibiting bone metastasis, improving the bone microenvironment, and alleviating related clinical symptoms. Its mechanisms of action may involve multiple levels. First, at the mechanical load level, mechanical signals generated by exercise can directly act on bone cells, inhibiting tumor cell infiltration and colonization by regulating endothelial cell permeability and osteoclast activity. Second, at the endocrine and paracrine levels, exercise can alter the expression profiles of microRNAs (such as miR-486 and miR-34b) carried by extracellular vesicles and particles (EVPs) in the circulation, thereby inhibiting tumor cell proliferation and migration by targeting cell cycle-related genes. Furthermore, exercise can remodel the immune microenvironment, enhance the cytotoxic activity of antitumor immune cells, and improve oxygen supply to tumor tissues, thereby alleviating hypoxia-induced immunosuppression. Finally, at the metabolic intervention level, exercise can induce systemic metabolic reprogramming, increasing the nutritional demands of normal tissues, thereby competing with tumor cells for nutrients and forming a “metabolic barrier” in distal organs such as bones. This article reviews the pathogenesis and classification of bone metastases, including osteolytic, osteogenic, and mixed types, and elaborates in detail on the complex processes by which tumor cells undergo colonization, dormancy, and reactivation within the bone microenvironment. Furthermore, based on a comprehensive analysis of human and animal studies on exercise interventions for bone metastases, this paper highlights the mechanisms by which exercise inhibits tumor formation, growth, and spread through the regulation of mechanical loading, extracellular vesicles and granules, as well as via immune and metabolic pathways, thereby interfering with bone metastasis. However, the array of exercise modalities and intensities available for patients grappling with the challenges of cancer-related bone metastases remains markedly constrained, and the formulation of tailored exercise prescriptions continues to be devoid of robust, evidence-based medical backing. This review aims to explore the effects of exercise on bone health in patients with bone metastases, analyze the factors and considerations that should be taken into account in exercise prescriptions, and provide new theoretical support and insights for developing personalized exercise programs for these patients and further advancing relevant clinical research. Future research directions should include the development of evidence-based, personalized exercise prescriptions and further clarification of the safety boundaries and best practice standards for exercise interventions, thereby promoting the advancement of relevant clinical research and ultimately improving patients’ clinical outcomes and quality of life.

Intraflagellar transport (IFT) is a core mechanism for ciliary assembly, length maintenance, ciliary proteome homeostasis and signal transduction. Most proteins required for ciliary structure and function are synthesized in the cytoplasm. Because the ciliary compartment is separated from the cell body by the selective barrier of the transition zone, these proteins cannot freely equilibrate between the cytoplasm and the cilium. Consequently, axonemal components, membrane proteins and signaling molecules must be actively imported into cilia, retrieved from the ciliary compartment, and recycled or degraded through highly ordered transport and sorting pathways. The IFT system is mainly composed of the IFT-A complex, IFT-B complex, kinesin-2, dynein-2 and the Bardet-Biedl syndrome protein complex (BBSome). Through coordinated anterograde and retrograde transport, these modules mediate the dynamic trafficking of different classes of ciliary cargoes. Anterograde transport delivers structural and membrane-associated components from the ciliary base toward the ciliary tip, whereas retrograde transport retrieves IFT components and selected cargoes back toward the ciliary base and cytoplasm. In this way, IFT not only supports the construction of the axoneme but also contributes to the maintenance of ciliary composition and the regulation of ciliary signaling activity. In recent years, advances in cryo-electron microscopy, in situ cryo-electron tomography and single-molecule imaging have greatly improved our understanding of the molecular mechanisms underlying IFT. These approaches have revealed how IFT trains are assembled at the ciliary base, how they move along axonemal microtubule tracks, how they undergo directional switching at the ciliary tip, and how cargoes are retrieved and recycled. Among the IFT modules, IFT-B acts as the major scaffold of IFT trains. It participates in cargo loading, motor coupling and initiation of anterograde transport. IFT-A is involved in retrograde transport, membrane protein adaptor function and train remodeling. The BBSome, through reversible association with the IFT system, regulates ciliary membrane protein sorting, signaling receptor clearance and renewal of the ciliary proteome. These functions indicate that the IFT machinery is not a simple linear transport pathway, but rather a dynamic and reconfigurable transport system. The conversion of transport direction is a key step in the IFT cycle. This process is closely associated with disassembly of anterograde trains, dissociation of kinesin-2, activation of dynein-2 at the ciliary tip and reassembly of retrograde trains. In terms of pathogenic mechanisms, IFT abnormalities may cause ciliopathies through four major pathways: defects in ciliary assembly and structure, abnormal localization of ciliary cargoes, dysregulation of signaling pathways, and impaired cargo unloading and retrieval. These defects can affect multiple organ systems, including the retina, kidney, skeleton, respiratory tract, reproductive system, and neuro-metabolic system. Current therapeutic strategies are still mainly based on symptomatic support and maintenance of organ function. Overall, IFT is a dynamic transport system jointly regulated by axonemal structure, motor activity, cargo selection and cellular signaling. It links ciliary architecture with protein turnover and signaling regulation, thereby playing a fundamental role in both ciliary homeostasis and ciliopathy pathogenesis. Further elucidation of IFT regulatory mechanisms and their relationships with disease phenotypes will help promote mechanism-based classification, genetic diagnosis and precision intervention for ciliopathies.

<b>Objective</b> Accurate prediction of anticancer drug response plays an important role in precision medicine and drug discovery. However, existing computational approaches often suffer from insufficient integration of heterogeneous biological data and limited generalization to unseen drugs. To address these challenges, this study proposes DeepFusion-CDR, a multimodal deep learning framework that integrates drug-target interaction information with multi-omics characteristics of cancer cell lines to improve the accuracy and generalization of anticancer drug response prediction.<b>Methods</b> A drug-target interaction (DTA) prediction model based on the Kolmogorov-Arnold Network (KAN) was first developed to capture complex nonlinear relationships between drugs and target proteins. The pretrained model was then used to generate drug target activity profiles, which provide biologically meaningful representations of drug mechanisms of action. On the drug side, molecular fingerprints, molecular graph structures, and drug target activity profiles were integrated as complementary multi-view features to comprehensively characterize the chemical and biological properties of drugs. On the cell-line side, multi-omics data, including genomic mutations, gene expression profiles, and DNA methylation information, were incorporated to describe the molecular heterogeneity of cancer cells. Subsequently, a multimodal deep fusion architecture was designed to jointly model the interactions between drug features and cell-line features, enabling accurate prediction of drug responses. The proposed framework was evaluated on the Genomics of Drug Sensitivity in Cancer (GDSC) dataset under different experimental settings, and its robustness and generalization capability were further assessed using the independent Cancer Therapeutics Response Portal version 2 (CTRPv2) dataset.<b>Results</b> Experimental results on the GDSC dataset demonstrated that DeepFusion-CDR consistently outperformed several state-of-the-art baseline methods and achieved superior predictive performance across multiple evaluation scenarios. The model demonstrated strong generalization capability, particularly in challenging settings involving unseen drugs. Validation on the independent CTRPv2 dataset further confirmed the model’s ability to generalize across different datasets. In addition, ablation studies revealed that both drug target activity profiles and multi-omics features made significant contributions to prediction performance. Removing any major feature modality led to a measurable decrease in model accuracy, indicating that different data sources provide complementary information for drug response prediction. These findings highlight the importance of multimodal collaborative learning and demonstrate the effectiveness of incorporating drug-target interaction knowledge into predictive modeling.<b>Conclusion</b> DeepFusion-CDR achieves accurate prediction of anticancer drug responses by integrating drug mechanism-related information with multi-omics characteristics of cancer cell lines. The incorporation of drug target activity profiles provides complementary biological information beyond traditional chemical structure descriptors and enhances the predictive capability of the model for unseen drugs. By combining drug-target interaction knowledge with heterogeneous biological data within a unified deep learning framework, DeepFusion-CDR offers a promising computational approach for precision medicine, drug repurposing, and anticancer drug discovery.

Objective To address the key challenges in breast electrical impedance tomography (EIT) reconstruction including the severe ill-posedness of the inverse problem, limited measurement information from the electrodes, low contrast of small lesions, as well as the common drawbacks of traditional reconstruction methods such as boundary blurring, low spatial resolution, and weak small-target detection capability, and to overcome the limitations of existing deep learning approaches namely low training efficiency, insufficient physical consistency, and substantial information loss during the low-to-high dimensional mapping process, this study proposes a multi-scale attention and dynamic sparse mask fusion network (MADS-Net). The proposed method aims to enhance high-resolution reconstruction accuracy, small-lesion detectability, noise robustness, and computational efficiency in breast-screening-oriented EIT, thereby providing a feasible solution for the application of EIT in breast functional imaging.Methods The proposed network adopts a strategy of "locate first, reconstruct later". It realizes adaptive allocation of computational resources through a dynamic mask module, alleviates information loss in the low-to-high dimensional mapping process via a multi-scale attention mechanism, and embeds physical constraints to improve the physical rationality of reconstruction results. The performance of the proposed method was validated through systematic numerical simulations, agar phantom experiments, and porcine tissue experiments. Comparisons were made with mainstream methods including the Gauss-Newton algorithm, convolutional neural networks, U-Net, and Deep D-Bar. The image correlation coefficient (ICC), root mean square error (RMSE), and peak signal-to-noise ratio (PSNR) were adopted as quantitative evaluation metrics. Furthermore, lesion-level evaluation metrics were introduced to assess the capability of different methods in reconstructing abnormal target boundaries and small-sized target regions.Results Experimental results demonstrate that MADS-Net outperforms all comparison methods across all test scenarios. In numerical simulations, it achieves higher accuracy in target morphology and spatial location recovery as well as better background suppression. In agar phantom experiments, its detection and imaging reliability for small targets is significantly superior to the comparison methods. In porcine tissue experiments, the model maintains good generalization performance and can adapt to complex biological tissue imaging scenarios. Quantitative results show that MADS-Net achieves an average ICC of 0.917 6±0.048 8, an RMSE as low as 0.060 6±0.031 6, and a PSNR of 23.893 9±2.685 3 dB. It successfully detects tiny targets as small as 5 mm within a 100 mm diameter sensing field, reduces the total training duration by 23.5% compared with the baseline method, and maintains stable reconstruction performance even under strong noise interference.Conclusion The results demonstrate that MADS-Net achieves favorable EIT reconstruction performance in numerical simulations, agar phantom experiments, and porcine tissue experiments, even under common practical imaging challenges including low signal-to-noise ratio and blurred tissue boundaries. This study provides a methodological reference for further research on EIT in breast-screening-related scenarios and other medical functional imaging tasks, and also offers a low-cost, radiation-free alternative for breast lesion screening that aligns with the clinical demand for non-invasive diagnostic tools. It should be noted that real clinical breast data have not yet been used for validation in this study, and the clinical applicability of the proposed method requires further investigation. Future work will prioritize collecting multi-center real clinical breast datasets, and further optimize the model""s generalization ability to adapt to individual differences in breast tissue composition to promote its clinical application.

Regulated cell death (RCD) has long been conceptualized as an elaborate program orchestrated by the nucleus and mitochondria in eukaryotic cells. However, this paradigm was fundamentally changed in 2025 by two independent studies published in<i> Cell</i>. One revealed that mature, enucleated erythrocytes execute a cytoskeletal disintegration-driven lysis<i> via</i> a miniNLRP3-ASC-caspase-8-β-spectrin axis, termed spectrin-dependent death (spectosis), wherein caspase-8 undergoes a functional switch from an initiator to an executioner, reflecting an evolutionary adaptation in protein economy. The other uncovered mitoxypterilysis, a modality in which metabolic distress and innate immune signals converge to trigger mTORC2-mediated aberrant mitochondrial-plasma membrane contacts, culminating in localized lipid peroxidation and membrane rupture. Mitoxypterilysis shows a logic defined by dual metabolic-immune regulation. This paper systematically dissects the molecular architectures of both modalities, and through comparative analysis, delineates their distinctions from classical RCD pathways as well as their divergent dependencies on organellar integrity, triggering contexts, and executional programs. In parallel, we integrate the recent discovery of reductive death, which underscores a central metabolic checkpoint to contextualize these findings within an emerging framework. Finally, we evaluate their therapeutic implications in hemolytic diseases, oncology, and inflammatory pathologies, while critically reflecting on current limitations and future directions, with the aim of providing a renewed conceptual foundation for targeted intervention strategies.

Mammalian male germline development depends on a specialized gonadal somatic microenvironment. However, its <i>in vitro</i> reconstruction remains challenging. Major barriers include the generation of appropriate supporting-cell lineages, organized tissue architecture, and culture conditions that sustain germ-cell maturation. Yoshino <i>et al</i>. established a mouse pluripotent stem cell-derived testicular organoid model. This model reconstitutes the sex-determining region Y (Sry)-SRY-box transcription factor 9 (Sox9)-mediated sex-determination program and generates testicular somatic cell-like cells (TesLCs). When assembled with primordial germ cell-like cells (PGCLCs), TesLCs formed seminiferous tubule-like structures and supported male germline progression toward prospermatogonia and germline stem cell-like cells (GSCLCs). After transplantation into infertile recipient testes, organoid-derived GSCLCs produced fertilization-competent sperm and generated fertile offspring. The major significance of this work extends beyond sperm production. It integrates sex determination, germ-cell fate transition, and testicular niche self-organization into an experimentally tractable organoid system. This commentary discusses the technical strategy, sex-determination mechanism, value of testicular niche reconstruction, and translational limitations of this study. It also highlights its implications for <i>in vitro</i> gametogenesis, male infertility modeling, and reproductive medicine.

Diabetic tendinopathy is a common and disabling musculoskeletal complication of diabetes, clinically characterized by tendon thickening, pain, impaired healing capacity and compromised biomechanical performance, collectively undermining joint function and quality of life. Its pathogenesis is multifactorial. On the one hand, chronic hyperglycaemia promotes the abnormal accumulation of advanced glycation end products (AGEs) within tendon collagen, leading to non-enzymatic crosslinking and engagement of the receptor for AGEs (RAGE), which in turn triggers inflammasome activation and sustains inflammatory responses. On the other hand, the diabetic milieu disrupts collagen metabolic homeostasis, impairs microvascular function and induces peripheral neuropathy; together, these alterations drive extracellular matrix degeneration and weaken the mechanical properties of tendon. Exercise, as a non-pharmacological intervention, can ameliorate these pathological changes through multiple integrated mechanisms. First, exercise attenuates tendon inflammation and restores microenvironmental homeostasis. Regular physical activity reduces AGE-RAGE signalling, thereby suppressing downstream expression of tumour necrosis factor (TNF) and interleukin-1β (IL-1β), while upregulating the anti-inflammatory cytokine interleukin-10 (IL-10). This shift from a pro-inflammatory to a pro-resolving milieu not only restrains chronic inflammation but may also limit excessive inflammasome activation in tenocytes and tissue-resident immune cells. Second, exercise enhances local expression of insulin-like growth factor 1 (IGF-1), thereby activating the phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt) signalling pathway. This axis stimulates tenocyte proliferation, augments synthesis of type I collagen —— the principal load-bearing component of tendon —— and thereby promotes tissue repair, preserves tensile strength and supports matrix synthesis and structural integrity. In addition, exercise improves blood supply and nutrient delivery to tendon by increasing the expression of vascular endothelial growth factor (VEGF), connective tissue growth factor (CTGF) and the small leucine-rich proteoglycan decorin (DCN), thereby enhancing capillary growth, coordinating collagen fibrillogenesis and actively suppressing pathological vascular calcification. Exercise also increases the expression of angiopoietin-like 4 (ANGPTL4), fibroblast growth factor 2 (FGF-2) and CD34. Through the concerted actions of these factors, exercise promotes angiogenesis, restores the microvascular network and ensures adequate oxygen and nutrient supply to relatively ischaemic tendon tissue. Finally, exercise elevates levels of brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF), supporting neuronal survival, axonal growth and the function of sensory and sympathetic nerve endings within tendon, thereby exerting neurotrophic and neuromodulatory effects and improving tendon innervation and neuromuscular control. Moreover, exercise upregulates collapsin response mediator protein 2 (CRMP-2), a molecule involved in axonal guidance and regeneration, and moderately increases the activity of substance P (SP), thereby helping to regulate neurogenic inflammation, pain perception and trophic support for tenocytes. Drawing together current evidence, this review systematically summarizes the mechanisms underlying diabetic tendinopathy and examines the mechanistic basis of exercise intervention, with the aim of providing a theoretical framework for the development of precise exercise strategies for affected individuals. However, several key issues remain unresolved: the therapeutic efficacy and mechanistic specificity of different exercise modalities in diabetic tendinopathy have yet to be defined, and early diagnostic biomarkers remain insufficiently characterized. Future studies should apply multi-omics approaches to profile AGE subtypes, miRNA signatures and collagen metabolic products, and should also clarify the adverse effects and underlying mechanisms of excessive exercise or mechanical overloading in diabetic tendinopathy. Such efforts will further elucidate the therapeutic effects and mechanisms of exercise in diabetic tendinopathy and provide a stronger basis for precision exercise prescription and fitness guidance in patients with diabetes.

Objective Multi-omics integration and analysis remain a major challenge in biomedical research. These tasks often require extensive coding skills and specialised bioinformatics expertise, which many biological and medical researchers do not have. Deep learning has emerged as a powerful approach for predictive modelling and data-driven discovery. However, most existing platforms focus only on traditional statistical analysis or basic machine learning. They do not combine deep learning support with standard statistical workflows. Moreover, none of them provide intelligent assistance to help with parameter tuning, error diagnosis, or result interpretation. To address this gap, we introduce AutoMATA, a fully code-free platform that streamlines multi-omics analysis from expression data to predictive modelling. AutoMATA is designed to lower the technical barrier for experimental biologists and clinical researchers who want to use advanced deep learning methods but lack programming experience.Methods AutoMATA's architecture is built around three core modules. The data processing and normalisation module automates essential steps such as gene and protein ID conversion and data normalisation. This module also allows users to integrate multi-omics data. The statistical analysis and visualisation module offers important and commonly used functions including differential expression analysis, principal component analysis, correlation analysis, and pathway enrichment for both GO and KEGG. Users can adjust thresholds and choose output formats for publication. The deep learning module provides twelve neural network architectures covering supervised, unsupervised, and semi-supervised learning. These include Multilayer Perception (MLP), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Transformer, Autoencoder, Variational Autoencoder (VAE), Radial Basis Function Neural Network (RBFNN), Self-Organising Map (SOM), DeepCluster, Pseudo-Labeling, and Ladder Network. Users can customise key settings including epoch, regularisation method, regularisation weight, dropout rate, and feature selection method. Two training strategies (train-validation-test split and stratified K-fold) are available. In addition, two Artificial Intelligence (AI) agents, DeepSeek and Qwen, are integrated into the platform. These agents answer user questions about parameter suggestion, task failure diagnosis, and result interpretations based on the actual task context and platform logic.Results We demonstrate AutoMATA in three case studies using public datasets. First, for colon adenocarcinoma data, AutoMATA reproduces gold-standard differential expression and clustering results. It correctly identifies known upregulated genes such as CXCL3 and CXCL8, and visualises enriched pathways. This confirms that AutoMATA's statistical module works as reliably as existing tools. Second, using multi-omics data for bladder, pancreatic, and stomach cancers, AutoMATA's deep learning module predicts cancer recurrence with good performance. Recurrent neural networks achieve the best results, with accuracy above 79% for stomach cancer. The platform also reproduces known biomarkers such as CDK6 in bladder cancer. Third, for breast cancer subtype classification, AutoMATA achieves 88.2% accuracy using a tuned RNN model. This performance is better than traditional machine learning methods like logistic regression and random forest. The AI agents provide on-demand assistance, helping users understand why certain models perform better, suggest parameter adjustments, and explain the biological meaning of the output. This makes the platform especially useful for non-experts.Conclusion By offering advanced multi-omics integration, comprehensive statistical analysis, flexible deep learning modelling options, and built-in AI agents, AutoMATA empowers researchers to extract meaningful biological insights and build robust predictive models without writing any code. The platform and source code are freely accessible athttps://github.com/ABILiLab/AutoMATA.

The establishment of endometrial receptivity is a critical prerequisite for successful embryo implantation and early pregnancy. However, current clinical methods for assessing receptivity are insufficiently validated, and their reliability is inadequate for guiding precision medicine. Although microfluidic organ-on-a-chip models have emerged as promising <i>in vitro</i> platforms garnering significant academic interest, their practical clinical translation has been hindered by challenges in accurately replicating patient-specific microenvironments and the lack of standardized quantitative evaluation systems. Recently, Lee <i>et al</i>. published a groundbreaking study in <i>Nature Communications</i>, which effectively addresses these critical limitations by integrating a patient-derived vascularized endometrium-on-a-chip (EoC) with a newly developed endometrial receptivity scoring system (ERS²). This commentary offers a comprehensive analysis of the key findings from this work, systematically examining the design, construction, dynamic simulation validation, and translational potential of the EoC-ERS² platform. This innovative approach successfully transforms conventional subjective assessments of endometrial receptivity into a digitized, objective, and quantitative evaluation framework. As a result, it establishes a robust foundation for a paradigm shift toward personalized infertility management and precision medicine in reproductive health.

<b>Objective</b> Type 2 diabetes mellitus (T2DM) often causes severe hepatic metabolic complications, dominated by metabolic dysfunction-associated steatotic liver disease (MASLD). Persistent hepatic steatosis and oxidative stress further trigger steatohepatitis and progressive liver damage, increasing the mortality risk of diabetic patients. Aerobic exercise effectively improves hepatic lipid metabolism and antioxidant capacity, but poor patient adherence restricts its long-term clinical application. Mitochondrial-derived mitochondrial open reading frame of the 12S rRNA type-c (MOTS-c) is a key peptide regulating insulin sensitivity and hepatic redox homeostasis. This study aimed to explore the protective mechanism of MOTS-c against T2DM-related liver injury and its combined beneficial effect with aerobic exercise <i>via</i> the NRF2/PPARγ signaling axis. This study aimed to investigate whether MOTS-c cooperates with aerobic exercise to alleviate T2DM-associated hepatic oxidative stress and metabolic dysfunction by activating the NRF2/PPARγ axis, and to clarify the molecular and transcriptomic characteristics of their combined intervention.<b>Methods</b> Stable MOTS-c overexpression and knockdown HepG2 cell lines were constructed using lentiviral transfection. An oleic acid-induced cellular lipid accumulation model and Nrf2-knockout cell model were applied to verify the NRF2-dependent mechanism of MOTS-c. Intracellular lipid deposition, triglyceride levels, antioxidant enzyme activities, and the expression of NRF2/PPARγ pathway-related genes and proteins were detected. <i>In vivo,</i> a T2DM rat model with obvious hepatic steatosis was established <i>via</i> a high-fat and high-sucrose diet combined with streptozotocin injection. Model rats received aerobic exercise, MOTS-c intraperitoneal injection, or combined intervention. We detected systemic glycolipid metabolic indicators, hepatic histopathological changes, and the expression of core proteins in the hepatic NRF2/PPARγ axis. Hepatic transcriptomic sequencing was performed to screen differentially expressed genes (DEGs) and enrich key pathways co-regulated by MOTS-c and aerobic exercise.<b>Results</b> Cellular results showed that MOTS-c overexpression significantly reduced oleic acid-induced lipid deposition, enhanced antioxidant enzyme activity, and upregulated NRF2 and PPARγ expression. Conversely, MOTS-c knockdown aggravated hepatic lipid accumulation and oxidative damage and inhibited NRF2/PPARγ pathway activation. Nrf2 knockout completely eliminated the protective effects of MOTS-c on lipid metabolism and redox balance, confirming its NRF2-dependent regulatory mechanism. In T2DM rats, both MOTS-c supplementation and aerobic exercise effectively improved insulin resistance, corrected glycolipid metabolic disorders, and alleviated hepatic steatosis, while consistently activating the hepatic NRF2/PPARγ axis. Compared with single intervention, the combined treatment showed a better improvement trend in hepatic metabolic and oxidative injury, without definitive synergistic effects. Transcriptomic analysis revealed that the co-regulated DEGs of MOTS-c and aerobic exercise were primarily enriched in lipid metabolism and PPAR signaling pathways, with multiple antioxidant and lipid-regulating genes significantly modulated by combined intervention.<b>Conclusion</b> MOTS-c exhibits obvious exercise-mimetic hepatoprotective effects in T2DM. It activates the hepatic NRF2/PPARγ axis to strengthen antioxidant defense, stabilize lipid metabolism, and relieve T2DM-associated hepatic steatosis and oxidative damage. Furthermore, MOTS-c produces additive beneficial effects with aerobic exercise, showing a superior intervention trend on diabetic liver dysfunction. This study identifies the NRF2/PPARγ axis as the core mechanism of MOTS-c-regulated hepatic protection, elucidates the transcriptomic basis of combined intervention, and provides a reliable theoretical basis and potential therapeutic target for clinical intervention in T2DM-complicated MASLD.

While pooled CRISPR screens have revolutionized functional genomics by enabling genome-scale interrogation, they have long faced a fundamental compatibility challenge with high-resolution microscopy-based phenotypes. The core issue lies in the technical disconnect between pooled screening formats, where cells are typically analyzed in bulk populations, and microscopy approaches that require spatial resolution and single-cell visualization. This limitation has created a significant blind spot in functional genomics, preventing researchers from systematically linking genetic perturbations to detailed subcellular architectural changes. To bridge this critical technological gap, a recent landmark study published in <i>Developmental Cell</i> has unveiled an integrated microscopy-based CRISPR screening platform that represents a paradigm shift in the field. The most innovative breakthrough of the platform involves extending photoactivation-based labeling techniques to fixed, immunostained cells, thereby overcoming a key limitation of prior approaches that were restricted exclusively to live-cell reporter systems. This methodological advancement allows researchers to capture transient cellular states and preserve delicate subcellular structures that would otherwise be lost in live-cell imaging scenarios. By seamlessly integrating this enhanced labeling approach with sophisticated automated imaging workflows and high-content analysis pipelines, the system enables unprecedented high-throughput, organelle-level phenotypic profiling at true single-cell resolution. The platform’s capabilities were demonstrated through its application to a comprehensive genome-wide screen for regulators of cilium assembly, a complex cellular process involving intricate cytoskeletal dynamics and membrane remodeling events. The screening results validated the platform’s robustness by successfully recapitulating known ciliary machinery components while simultaneously uncovering novel regulatory factors. Most notably, the study identified SMIM27/TZMP1, a conserved transition zone microprotein, as a previously unrecognized regulator of ciliary function. This discovery provides crucial insights into the molecular mechanisms governing ciliary transition zone barrier formation and selectivity. This accessible and versatile framework effectively overcomes longstanding bottlenecks in microscopy-based screening technologies, offering a generalizable strategy for dissecting organelle biology and cellular architecture at scale. The platform’s ability to combine genome-wide screening power with detailed morphological analysis opens new avenues for investigating cellular responses to genetic perturbations across diverse biological contexts.

Platelets play a crucial role in hemostasis and thrombosis. They have a complex and active metabolic system, particularly regarding lipid metabolism. The active and intricate lipid metabolism within platelets plays a central role in platelet activation, signal transduction, and functional regulation, making it crucial for studying the pathophysiological mechanisms of diseases. The platelet membrane structure is highly complex and it contains various lipids, including phospholipids, sphingolipids, cholesteryl esters, and triglycerides, etc. Current research has elucidated multiple metabolic pathways in platelets, such as phospholipid and sphingolipid metabolism, which profoundly influence platelet aggregation, release, and inflammatory responses. Upon activation, platelets release various lipids that interact with inflammatory cells in a paracrine manner. This review systematically describes the key lipid metabolism and its dynamic functional regulation. Lipid metabolism regulates processes such as platelet production, aging, and activation. This review emphasizes the interaction between lipid droplets and mitochondria, which is closely related to platelet activation. For instance, platelet-derived extracellular vesicles can transfer dysfunctional mitochondria from platelets to hepatocytes, leading to the dysfunction of lipid droplet-bound mitochondria and abnormal lipid droplet metabolism, thereby affecting hepatic lipid metabolism. The review summarizes interactions between platelet lipid metabolism and other cells, including leukocytes, erythrocytes, and lymphocytes. However, there are few studies on the interactions between platelets and cells through lipid metabolism, and the direct evidence is scarce. Further research is recommended in the future. It further explores the relationships between platelet lipid metabolism and the reproductive system, musculoskeletal system, the central nervous system, and the gut microbiota. Additionally, it reviews the close associations between platelet lipid metabolism and diseases such as diabetes, metabolic dysfunction-associated steatotic liver disease, immune thrombocytopenia, metabolic syndrome, and thrombotic disorders (thromboembolic diseases). For example, antiphospholipid syndrome (APS), typically characterized by reproductive impairment, may be associated with enhanced platelet activation and elevated phospholipase A2 activity in patients with APS. Moreover, lipid metabolism in the bone marrow microenvironment can promote platelet production. Under cellular stress, platelets transfer mitochondria to macrophages; in the spinal cord injury model, this process can regulate energy and lipid metabolism, leading to nerve and myelin regeneration and ultimately promoting the recovery of motor function. These findings indicate that modulating energy and lipid metabolism can influence platelet function, suggesting that targeting platelet lipid metabolism may provide a direction for disease treatment. Furthermore, the review covers the research on platelet lipid metabolism and related drugs, including traditional Chinese medicines and natural products. As the first selective 12-lipoxygenase (12-LOX) inhibitor to enter clinical trials, ML355 will facilitate future research on the biology of 12-LOX and its effects on regulation of platelet activity, hemostasis, and thrombosis, and promote the discovery of structure-based drugs. However, research on platelets and lipid metabolism still faces numerous challenges. For example, lipid droplet-mitochondria interaction in the liver regulates lipid metabolism. Meanwhile, there is controversy over whether autophagy serves a protective function or promotes the occurrence of liver disease. It is speculated that the interaction between mitochondrial autophagy and lipid droplets may be a future research direction. The precise regulatory mechanism of lipid metabolism and how to develop novel antithrombotic and anti-inflammatory drugs with high specificity and low side effects by targeting lipid metabolism remain current challenges. In summary, this review provides a comprehensive overview of platelet lipid metabolism, its interactions with other cells, and its roles in organ function and diseases. This contributes to the discovery of new disease-specific lipid biomarkers and drug targets. Future research could focus on structural modifications of drugs targeting lipid metabolism to enhance selectivity, offering directions for improving safety and efficacy, and developing the most effective individualized treatment plans for patients.

Core fucosylation, catalyzed exclusively by α-1,6-fucosyltransferase 8 (FUT8), is an evolutionarily conserved post-translational modification that has emerged as a central regulatory hub linking liver homeostasis, chronic disease progression, and malignant transformation. Liver diseases, particularly hepatocellular carcinoma, remain a leading global health burden characterized by late diagnosis, limited therapeutic options, and poor overall survival. While aberrant glycosylation is now recognized as a hallmark of cancer and inflammatory disorders, existing research on FUT8-mediated core fucosylation in liver diseases remains fragmented: the dynamic functional switch of FUT8 from a homeostatic regulator to a pathological driver across the full disease continuum has not been systematically delineated, and the integrated mechanisms by which core fucosylation modulates oncogenic signaling, metabolic reprogramming, and immune evasion remain poorly understood. This review synthesizes recent advances to establish a unified framework for understanding the dual role of core fucosylation in liver physiology and pathology, and evaluates its translational potential for precision medicine. At the molecular level, FUT8""s unique catalytic specificity makes core fucosylation an irreplaceable modification, as evidenced by the perinatal lethality and severe organ dysfunction in <i>Fut8</i> knockout mice. In hepatocellular carcinoma, genomic amplification of guanosine 5""-diphosphate-fucose biosynthetic enzymes provides metabolic support for aberrant core fucosylation. FUT8 expression is tightly regulated by a multi-layered network: transcriptional activation <i>via</i> Wnt/β-catenin and wild-type p53, epigenetic upregulation by lncRNAs, post-transcriptional repression by miR-122-5p and miR-34a, and virus-specific induction by hepatitis B virus/hepatitis C virus. Physiologically, core fucosylation maintains liver homeostasis through four core mechanisms: it acts as a molecular switch for epidermal growth factor receptor/hepatocyte growth factor receptor signaling to enable liver regeneration; directs polarized secretion of hepatocyte-derived glycoproteins into bile ducts; modulates cholesterol metabolism <i>via</i> the hepatocyte nuclear factor 1α-proprotein convertase subtilisin/kexin type 9-low density lipoprotein receptor axis; and regulates aging through Insulin-Like Growth Factor 1 Receptor signaling. Pathologically, core fucosylation exhibits context-dependent dual functions: in liver fibrosis, FUT8 upregulation in hepatic stellate cells forms a negative feedback loop that limits excessive fibrogenesis; in hepatocellular carcinoma, however, aberrant FUT8 overexpression drives cell-autonomous malignancy by constitutively activating epidermal growth factor/hepatocyte growth factor receptor, transforming growth factor-β/Smad, and Wnt/β-catenin pathways, while simultaneously establishing a multi-layered immune evasion network by stabilizing programmed cell death ligand 1 and cluster of differentiation 47, and impairing natural killer cell homeostasis <i>via </i>interleukin-2 receptor β glycosylation. Clinically, stage-specific core fucosylation biomarkers enable non-invasive monitoring of liver disease progression: low molecular weight kringle-Fc fusion protein outperforms conventional markers for early fibrosis detection, while alpha-fetoprotein-L3 and novel glycopeptides (α-2-macroglobulin N-linked glycosylation site 1424, lumican core fucosylated peptide) significantly improve early hepatocellular carcinoma diagnosis, especially in alpha-fetoprotein-negative patients. Next-generation detection technologies (chemoenzymatic labeling, site-specific mass spectrometry) overcome the specificity limitations of traditional lectin assays. Therapeutically, four promising strategies are emerging: small-molecule FUT8 inhibitors, afucosylated antibodies with enhanced antibody-dependent cellular cytotoxicity, Fuc-modified targeted drug delivery systems, and core fucose-specific lectins for NASH treatment. The core challenge for clinical translation lies in FUT8’s inherent “double-edged sword” effect, as systemic inhibition disrupts its essential physiological functions beyond pathological roles. Long-term systemic FUT8 blockade not only impairs post-injury liver regeneration by abrogating epidermal growth factor/hepatocyte growth factor receptor signaling but also disrupts cholesterol homeostasis <i>via</i> the hepatocyte nuclear factor 1α-proprotein convertase subtilisin/kexin type 9-low density lipoprotein receptor axis, leading to dyslipidemia and altered bile secretion. Critically, it compromises immune surveillance by destabilizing interleukin-2 receptor β on natural killer cells, reducing their cytotoxic activity against malignant and virally infected cells, and impairs IgG Fc-mediated effector functions, increasing susceptibility to infections. This fundamental trade-off between therapeutic efficacy and systemic toxicity necessitates a paradigm shift from non-specific global inhibition to precision modulation of pathological core fucosylation. By addressing these critical challenges, FUT8-mediated core fucosylation has the potential to transform liver disease management from late-stage intervention to early detection and precision therapy, ultimately improving patient outcomes and reducing the global burden of liver diseases.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Objective In order to address the challenge of rapid diagnosis in pulmonary diseases, this paper proposes a cross-modal fusion method based on the Cross-modal Transformer (CMT) that integrates respiratory sounds (RS) and electrical impedance tomography (EIT), with the aim of improving the accuracy and robustness of multi-classification tasks. RS encodes the acoustic characteristics of the airways via the Meyrieh spectrogram, whilst EIT depicts regional lung ventilation distribution through spatio-temporal image sequences. The two modalities are naturally complementary in terms of functional and spatial information, providing a physiological basis for multimodal fusion diagnosis.Methods A dual-branch feature extraction framework was constructed, employing Convolutional Neural Networks (CNNs) to extract local features from RS time-frequency spectra and EIT ventilation images, whilst utilising Bidirectional Long Short-Term Memory Networks (BiLSTMs) to model the temporal dependencies across modalities. The development of a transformer-based cross-modal attention fusion module represents a significant advancement in the field. The module utilises a multi-head self-attention mechanism and gated convolutional units to achieve deep semantic alignment and complementary information fusion between RS acoustic features and EIT spatial ventilation features. The model employs an end-to-end joint optimisation strategy, with a cross-entropy loss function supervising the overall training process, and utilises a time-synchronisation mechanism to ensure strict alignment of the dual-modal inputs within the respiratory cycle. The proposed CMT method was subjected to systematic experimental validation on two datasets: The BRACETS dataset (three-class classification, 795 samples) and the CleftPalate dataset (two-class classification, 549 samples) are the focus of this study. Quantitative evaluation was performed using accuracy, balanced accuracy (BAcc) and macroF1 score.Results On the BRACETS dataset, the CMT method achieved an accuracy of 87.21%, a balanced accuracy (BAcc) of 88.24%, and a macroF1 score of 87.40%. In comparison to the optimal baseline method, DCNN, the macroF1 score exhibited an enhancement of 8.73 percentage points, thereby substantiating a substantial performance superiority. The findings of the ablation experiments suggest that the three core modules – CNN, BiLSTM and Transformer – all contribute to performance enhancements. Upon the removal of these modules, the MacroF1 score decreased by 1.84%, 1.13% and 2.20%, respectively. Among these, the Transformer cross-modal fusion module had the most significant impact, validating its crucial role in the interaction of heterogeneous modal information. Hyperparameter sensitivity analysis indicates that the optimal parameter configuration is a sequence length of T=128 and a feature dimension of d=128, achieving a good balance between classification performance and computational efficiency. Sequences that are insufficiently extensive or dimensions that are unduly limited impede the capacity to adequately represent temporal dynamics, whilst excessively protracted sequences may engender superfluous information. On the CleftPalate dataset, the CMT method achieved an accuracy of 96.58%, a BAcc of 96.60%, and a MacroF1 of 96.56%, representing a further improvement of 2.51 percentage points compared to the DCNN. This result validates the model's generalisation capability across different data distributions and task scenarios. The fusion representation learned by CMT has been shown to exhibit tighter intra-class cohesion and clearer inter-class separation boundaries, as evidenced by feature visualisation and case studies (Smith et al., 2022). The system has the capacity to adaptively aggregate effective features when the reliability of multimodal information is uneven, and can maintain correct classification even when ambiguity exists in a single modality.Conclusion The proposed method effectively achieves deep fusion of heterogeneous modal information from RS and EIT, fully exploiting the physiological complementary relationship between respiratory airflow acoustic features and regional lung ventilation distribution. The model displays excellent classification performance and stability across various data distributions and task scenarios, thus providing a novel technical pathway for the non-invasive intelligent diagnosis of pulmonary diseases.

Objective Frozen shoulder (FS) is a debilitating musculoskeletal disorder characterized by persistent inflammation and progressive fibrosis of the glenohumeral joint capsule, leading to pain and severely restricted range of motion. Given the limited efficacy of current pharmacotherapies, there is an urgent need for novel anti-fibrotic agents. Guyanxiao Tincture (GYX), a traditional Chinese herbal formula, has shown clinical benefits in alleviating FS symptoms. However, its bioactive constituents and the molecular mechanisms underlying its therapeutic effects remain poorly defined. This study aimed to systematically evaluate the therapeutic efficacy of GYX against FS and to elucidate the mechanisms by which GYX attenuates capsular fibrosis.Methods A Sprague-Dawley (SD) rat model of FS was established by immobilizing the unilateral shoulder with a plaster cast for 21 d. Following model induction, animals were administered with GYX or its serum-identified bioactive component, icariside F2. The absorbed prototype compounds of GYX in FS rat serum were profiled using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Therapeutic effects were assessed by measuring shoulder range of motion (ROM), histopathological evaluation of the capsule via hematoxylin-eosin staining, and quantification of transforming growth factor-β1 content by ELISA. To explore the underlying mechanisms, transcriptomic profiling of the shoulder capsule was performed using RNA sequencing, and differentially expressed genes were validated by real-time quantitative PCR. Protein expression and localization were examined through immunohistochemistry, immunofluorescence, and Western blot. Protein-protein interaction networks were constructed to identify key regulatory hubs. In vitro, primary shoulder capsule fibroblasts were stimulated with TGF-β1 to induce a fibrotic phenotype and then treated with icariside F2. The expression of ACTC1, α-smooth muscle actin, and collagen I was subsequently measured.Results Serum pharmacochemistry analysis identified icariside F2 as the predominant circulating bioactive component of GYX in FS rats. Both GYX and icariside F2 treatment significantly improved the ROM and ameliorated histopathological lesions, including the attenuation of synovial hyperplasia, inflammatory infiltration, and excessive collagen deposition in the shoulder capsule. Consistently, elevated TGF-β1 levels in the model group were markedly reduced after the interventions. RNA sequencing revealed that actin alpha cardiac muscle 1 (ACTC1) was dramatically upregulated in the fibrotic capsule, accompanied by the enrichment of fibrosis-associated pathways such as TGF-β signaling, focal adhesion, and ECM-receptor interaction. Protein-protein interaction network analysis demonstrated that ACTC1 directly interacts with core fibrotic genes, including Col1a1, Col1a2, Thbs2, and Fn1. Critically, icariside F2 administration significantly reversed the aberrant overexpression of ACTC1 and suppressed the activation of the aforementioned fibrosis-related pathways in vivo. In TGF-β1-stimulated fibroblasts, icariside F2 dose-dependently downregulated ACTC1 at both the mRNA and protein levels and concurrently decreased the expression of the fibrotic markers α-smooth muscle actin and collagen I. Immunofluorescence and Western blot further confirmed that icariside F2 attenuated stress fiber formation and collagen production in vitro.Conclusion GYX and its bioactive component icariside F2 effectively alleviate the progression of frozen shoulder by inhibiting capsular fibrosis. Mechanistically, the therapeutic action is functionally linked to the suppression of ACTC1 and its downstream profibrotic signaling cascade, highlighting ACTC1 as a promising therapeutic target for the management of frozen shoulder.

Small-molecule therapeutics and chemical probes remain indispensable in modern biomedical research and drug discovery. However, with the rapid expansion of chemical space and the increasing diversification of biological target classes, high-throughput and material-efficient screening technologies are facing growing demands. Small-molecule microarrays (SMMs) provide a miniaturized and spatially addressable platform in which thousands to tens of thousands of compounds are immobilized on a solid surface and screened in parallel against proteins, cell lysates, or nucleic acid structures. Since the last comprehensive review of this field in 2014, SMM technology has undergone substantial methodological and application-oriented development; however, these advances have often been reported in a fragmented manner and still require systematic integration. This review therefore clarifies the terminology and scope of SMM and systematically summarizes its recent advances, with particular attention paid to four interconnected dimensions: surface chemistry, interface microenvironment modulation, signal detection, and applications. Regarding surface chemistry, immobilization methods are organized into tag-based and broad-spectrum strategies. Tag-based strategies use reactive handles or affinity tags, such as covalent tags, biotin, or fluorous tags, to achieve defined attachment and controllable molecular display, but require prior modification and may mask key pharmacophores. Broad-spectrum strategies exploit intrinsic functional groups or physicochemical properties, including isocyanate coupling, ultraviolet-activated photo-capture, and polymer-based immobilization. They show broader compatibility with diverse libraries, natural products, and approved drugs, but may increase ligand heterogeneity and nonspecific background. This classification provides references for selecting suitable surface construction strategies in SMM studies. Interface microenvironment modulation is another factor affecting the SMM performance. Because immobilized small molecules are displayed on solid substrates, steric hindrance and restricted conformational freedom may reduce target accessibility. Flexible linkers, polyethylene glycol spacers, oligonucleotide tethers, and quasi-three-dimensional polymer layers have therefore been introduced to increase ligand-substrate distance, alleviate steric constraints, and preserve solution-like binding behavior. This review also summarizes signal detection strategies, including fluorescence-based labeling, HaloTag-assisted readouts, and label-free technologies such as oblique-incidence reflectivity difference and surface plasmon resonance imaging. In applications, SMM has expanded from purified protein screening to more diverse biological contexts. Cell lysate-based screening enables interrogation of unstable, difficult-to-purify, or context-dependent targets, whereas structure-oriented screening against RNA/DNA motifs has extended SMM into nucleic acid-targeted discovery. These advances allow SMM to address challenging target classes, including transcription factors, intrinsically disordered proteins, membrane-associated proteins, and protein-protein interactions, targeted protein degradation systems, and higher-order nucleic acid structures. Compared with activity-based high-throughput screening or DNA-encoded library selection, SMM provides a direct, amplification-free binding readout and can capture weak interactions, although rigorous validation remains essential. Finally, this review discusses SMM in fragment-based drug discovery (FBDD) and artificial intelligence-assisted drug design (AIDD). In FBDD, SMM offers a parallel, low-consumption format for detecting weak fragments–target interactions and identifying fragment hits for validation and optimization. In AIDD, SMM can generate binding fingerprints, including fluorescence intensities, signal-to-noise ratios, Z-scores, and apparent affinity parameters in concentration-gradient designs. These datasets may support virtual screening, hit prioritization, binding landscape construction, functional group clustering, and structure–activity relationship inference. Overall, SMM has evolved into a versatile screening and data-generation platform, providing a methodological engine for expanding the druggable target space and accelerating early-stage discovery of chemical probes and lead compounds.

Adipose tissue macrophages (ATMs) are crucial immunomodulatory factors in the adipose tissue (AT) microenvironment, playing an irreplaceable role in maintaining the balance of the local immune system and regulating metabolic homeostasis. Under obese conditions, the excessive accumulation of lipids leads to abnormal expansion of adipose tissue, which further disrupts the homeostasis of the local microenvironment, including the imbalance of inflammatory factors, the occurrence of oxidative stress, and the damage of microcirculation. As an essential immune cell population in adipose tissue, ATMs are deeply involved in the occurrence and progression of metabolic disorders and multiple obesity-related diseases, and their functional abnormalities are closely related to the initiation and development of adipose tissue inflammation and systemic metabolic disorders. The interaction between ATMs and adipokines, including adiponectin, leptin, resistin and retinol-binding protein 4 (RBP4), acts as the core immunological and molecular mechanism linking adipose tissue inflammation to continuous disease deterioration, and this interaction is also a key research focus in the field of obesity-related diseases in recent years. This review discusses in detail the facilitating effect of the AT inflammatory microenvironment on the differentiation of peripheral monocytes into ATMs, elaborating on the specific molecular mechanisms by which various inflammatory mediators and abnormal metabolic products in the inflammatory microenvironment induce the differentiation of peripheral monocytes into functional ATMs. It also focuses on the regulatory mechanisms of chemokine-mediated ATM polarization and recruitment, including the specific roles of key chemokines like MCP-1 and CXCL10 in mediating the recruitment of ATMs to adipose tissue, as well as the molecular pathways that regulate the switch between M1 pro-inflammatory phenotype and M2 anti-inflammatory phenotype of ATMs. In addition, this review explores the specific process by which ATMs trigger AT inflammation by secreting various pro-inflammatory factors such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β), which further amplify the local inflammatory response and disrupt the metabolic homeostasis of adipose tissue. Furthermore, it analyzes the specific binding patterns and molecular characteristics of adiponectin, leptin, resistin and RBP4 with ATM surface receptors, and clarifies how the activation of downstream immune signaling pathways, such as JAK-STAT, NF-κB, and PI3K-AKT, triggered by these binding processes, induces the occurrence and development of various obesity-related diseases, including insulin resistance, cancer, metabolic-associated steatohepatitis (MASH) and cardiovascular diseases. This paper highlights the unique and crucial role of the interaction between ATMs and adipokines in the occurrence and progression of obesity-related diseases, emphasizing that this interaction is a key link connecting local adipose tissue inflammation to systemic metabolic disorders. It further summarizes the potential therapeutic strategies targeting the ATM-adipokine axis, and comprehensively illustrates three major clinical application barriers, namely biological complexity, technical bottlenecks, and clinical translation obstacles, in the process of applying these therapeutic strategies. For each barrier, this review puts forward corresponding feasible solutions and clear research directions, which not only enrich the theoretical system of the ATM-adipokine axis in the field of obesity research, but also provide a solid theoretical basis and practical ideas for the clinical intervention, prevention and treatment of obesity and its related diseases.