Mendel established the laws and laid the foundation of modern genetics through his famous hybridization experiments on seven pairs of classic traits in the garden pea (Pisum sativum). However, the molecular bases underlying these traits have only come into sharp focus in recent years. Leveraging advances in traditional map-based cloning, TILLING, long-read resequencing, population genetics, and GWAS, this article synthesizes current knowledge of ten genes governing seven traits—plant height, seed shape, flower color, seed color, pod color, pod morphology, and flower position—by summarizing each gene’s identity, chromosomal localization, and functional pathway. For plant height, the classical Le locus corresponds to PsGA3ox1, which encodes a gibberellin 3β-hydroxylase. Mutations at Le impede the biosynthesis of the bioactive hormone GA₁, and the resulting deficiency leads to a dwarf or reduced-stature phenotype. Seed shape is determined by R, identified as PsSBEI (starch-branching enzyme I). Insertion of a transposable element into R restricts amylopectin synthesis, perturbing endosperm starch architecture and resulting in the wrinkled seeds noted by Mendel. Flower color is specified by the coordinated action of A (a bHLH transcription factor) and A2 (a WD40 scaffold). Together, they assemble the canonical MYB-bHLH-WD40 (MBW) regulatory complex, which co-activates structural genes in the anthocyanin pathway to determine pigment accumulation and floral hue. Seed color is governed by I, which encodes PsSGR (STAY-GREEN), a magnesium dechelatase that catalyzes a key step in chlorophyll catabolism. Loss-of-function alleles at I block chlorophyll degradation, yielding “stay-green” seeds in which chlorophyll persists beyond normal developmental stages. Pod coloration maps to Gp, corresponding to ChlG (chlorophyll synthase). Either direct loss of ChlG function or readthrough-fusion transcriptional interference caused by a large upstream deletion suppresses chlorophyll biosynthesis in developing pods, resulting in the yellow-pod phenotype. Pod morphology depends on two convergent regulatory pathways. The P gene, PsCLE41, signals through the P-PXY-WOX/NAC axis to promote vascular differentiation and secondary-wall programs, while V encodes PsMYB26, a transcription factor that drives secondary wall thickening in fiber cells. Acting in concert, these modules ensure robust secondary-wall deposition in the fiber layer lining the inner pod wall; disruption of either component compromises wall thickening and leads to pleated or wrinkled pods. Flower position (inflorescence determinacy at the shoot apex) is controlled by FA, identified as PsCIK, which participates in the CLAVATA-WUSCHEL (CLV-WUS) feedback circuit that maintains shoot apical meristem homeostasis. Mutations in FA destabilize this self-regulatory loop and promote terminal flowers at the apex. The expressivity of this determinacy phenotype is further modulated by a recessive modifier, Mfa, which fine-tunes the outcome in the fa background. Across these loci, convergent evidence highlights the central role of structural variation in generating the classical Mendelian phenotypes. Building on this clarified molecular landscape, we outline practical implications for quality improvement and the deliberate “design” of traits. Looking ahead, we envisage a next generation of legume genetic improvement anchored on three mutually reinforcing pillars: high-quality reference genomes to deliver contiguous, structurally faithful assemblies; comprehensive pan-genomes to capture presence/absence variation and structural polymorphism across germplasm; and precise gene editing to target coding, regulatory, and structural features alike. Together, these tools chart a path toward mechanism-based breeding, enabling purposeful, design-driven trait improvement in peas and, by extension, other legumes.

Human milk is universally recognized as the optimal and most natural source of nutrition for newborns, offering benefits that extend far beyond basic energy and macronutrient provision. Among its complex constituents, human milk oligosaccharides (HMOs) represent the third most abundant solid component, surpassed only by lactose and lipids. HMOs are distinguished by their exceptionally high structural diversity—over 200 distinct structures have been identified to date. This structural complexity underlies the extensive biological functions HMOs perform within the infant’s body. HMOs play a pivotal role in promoting healthy growth, development, and overall well-being in infants and young children, functioning as indispensable bioactive molecules. Their key physiological activities include: immunomodulation and allergy prevention by promoting immune tolerance and reducing the risk of allergic diseases; potent anti-inflammatory and antioxidant effects that protect vulnerable infant tissues; support for brain development and cognitive enhancement through multiple mechanisms; anti-pathogenic properties, acting as soluble receptor analogs or “decoy” molecules to competitively block viral, bacterial, and other pathogen adhesion, thereby preventing colonization and infection in the gastrointestinal tract; and functioning as blood group substances. At the translational and application level, HMO research is actively driving cross-disciplinary innovation. Building on a deep understanding of their immunological and neurodevelopmental benefits, certain structurally defined HMOs have been successfully incorporated into infant formula. These HMO-supplemented formulas have received regulatory approval and are now commercially available worldwide, providing a nutritional alternative that more closely resembles human milk for infants who are not exclusively breastfed. This represents a significant step toward narrowing the compositional gap between formula and breast milk. Simultaneously, research into the symbiotic relationship between HMOs and the gut microbiota—particularly their role as selective prebiotic substrates promoting the growth of beneficial bacteria—has catalyzed the development of novel functional foods, dietary supplements, and microbiome-targeted therapies. These include advanced synbiotic formulations that combine specific probiotic strains with HMOs to synergistically optimize gut health and function. Furthermore, the intrinsic qualities of HMOs—including their natural origin, safety profile, biocompatibility, and proven antioxidant properties—have attracted growing interest in the emerging field of high-performance cosmetics. They are increasingly being explored as innovative functional ingredients in skincare products aimed at reducing oxidative stress and supporting skin health. This review aims to systematically synthesize recent advancements in HMO research, offering a comprehensive analysis centered on their complex composition and structural diversity; the molecular and cellular mechanisms underlying their diverse biological functions; their translational potential across sectors such as nutrition, medicine, and consumer care (including cosmetics); and the major challenges that persist in the field. It critically examines both foundational discoveries and recent breakthroughs. By integrating these interconnected themes, the review provides a holistic and up-to-date perspective on the scientific landscape of HMOs, highlighting their essential role in early-life nutrition and their expanding relevance across health and wellness applications. It also outlines promising directions for future research, with the goal of advancing evidence-based innovation in infant health and beyond.

Sleep deprivation (SD) has emerged as a significant modifiable risk factor for Alzheimer’s disease (AD), with mounting evidence demonstrating its multifaceted role in accelerating AD pathogenesis through diverse molecular, cellular, and systemic mechanisms. SD is refined within the broader spectrum of sleep-wake and circadian disruption, emphasizing that both acute total sleep loss and chronic sleep restriction destabilize the homeostatic and circadian processes governing glymphatic clearance of neurotoxic proteins. During normal sleep, concentrations of interstitial Aβ and tau fall as cerebrospinal fluid oscillations flush extracellular waste; SD abolishes this rhythm, causing overnight rises in soluble Aβ and tau species in rodent hippocampus and human CSF. Orexinergic neurons sustain arousal, and become hyperactive under SD, further delaying sleep onset and amplifying Aβ production. At the molecular level, SD disrupts Aβ homeostasis through multiple converging pathways, including enhanced production via beta-site APP cleaving enzyme 1 (BACE1) upregulation, coupled with impaired clearance mechanisms involving the glymphatic system dysfunction and reduced Aβ-degrading enzymes (neprilysin and insulin-degrading enzyme). Cellular and histological analyses revealed that these proteinopathies are significantly exacerbated by SD-induced neuroinflammatory cascades characterized by microglial overactivation, astrocyte reactivity, and sustained elevation of pro-inflammatory cytokines (IL-1β, TNF-α, IL-6) through NF-κB signaling and NLRP3 inflammasome activation, creating a self-perpetuating cycle of neurotoxicity. The synaptic and neuronal consequences of chronic SD are particularly profound and potentially irreversible, featuring reduced expression of critical synaptic markers (PSD95, synaptophysin), impaired long-term potentiation (LTP), dendritic spine loss, and diminished neurotrophic support, especially brain-derived neurotrophic factor (BDNF) depletion, which collectively contribute to progressive cognitive decline and memory deficits. Mechanistic investigations identify three core pathways through which SD exerts its neurodegenerative effects: circadian rhythm disruption via BMAL1 suppression, orexin system hyperactivity leading to sustained wakefulness and metabolic stress, and oxidative stress accumulation through mitochondrial dysfunction and reactive oxygen species overproduction. The review critically evaluates promising therapeutic interventions including pharmacological approaches (melatonin, dual orexin receptor antagonists), metabolic strategies (ketogenic diets, and Mediterranean diets rich in omega-3 fatty acids), lifestyle modifications (targeted exercise regimens, cognitive behavioral therapy for insomnia), and emerging technologies (non-invasive photobiomodulation, transcranial magnetic stimulation). Current research limitations include insufficient understanding of dose-response relationships between SD duration/intensity and AD pathology progression, lack of long-term longitudinal clinical data in genetically vulnerable populations (particularly APOE ε4 carriers and those with familial AD mutations), the absence of standardized SD protocols across experimental models that accurately mimic human chronic sleep restriction patterns, and limited investigation of sex differences in SD-induced AD risk. The accumulated evidence underscores the importance of addressing sleep disturbances as part of multimodal AD prevention strategies and highlights the urgent need for clinical trials evaluating sleep-focused interventions in at-risk populations. The review proposes future directions focused on translating mechanistic insights into precision medicine approaches, emphasizing the need for biomarkers to identify SD-vulnerable individuals, chronotherapeutic strategies aligned with circadian biology, and multi-omics integration across sleep, proteostasis and immune profiles may delineate precision-medicine strategies for at-risk populations. By systematically examining these critical connections, this analysis positions sleep quality optimization as a viable strategy for AD prevention and early intervention while providing a comprehensive roadmap for future mechanistic and interventional research in this rapidly evolving field.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β-protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF-κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 to co-regulate antioxidant activity. NF-κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such as α-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder affecting a substantial proportion of women of reproductive age. It is frequently associated with ovulatory dysfunction, infertility, and an increased risk of chronic metabolic diseases. A hallmark pathological feature of PCOS is the arrest of follicular development, closely linked to impaired intercellular communication between the oocyte and surrounding granulosa cells. Transzonal projections (TZPs) are specialized cytoplasmic extensions derived from granulosa cells that penetrate the zona pellucida to establish direct contact with the oocyte. These structures serve as essential conduits for the transfer of metabolites, signaling molecules (e.g., cAMP, cGMP), and regulatory factors (e.g., microRNAs, growth differentiation factors), thereby maintaining meiotic arrest, facilitating metabolic cooperation, and supporting gene expression regulation in the oocyte. The proper formation and maintenance of TZPs depend on the cytoskeletal integrity of granulosa cells and the regulated expression of key connexins, particularly CX37 and CX43. Recent studies have revealed that in PCOS, TZPs exhibit significant structural and functional abnormalities. Contributing factors—such as hyperandrogenism, insulin resistance, oxidative stress, chronic inflammation, and dysregulation of critical signaling pathways (including PI3K/Akt, Wnt/β-catenin, and MAPK/ERK)—collectively impair TZP integrity and reduce their formation. This disruption in granulosa-oocyte communication compromises oocyte quality and contributes to follicular arrest and anovulation. This review provides a comprehensive overview of TZP biology, including their formation mechanisms, molecular composition, and stage-specific dynamics during folliculogenesis. We highlight the pathological alterations in TZPs observed in PCOS and elucidate how endocrine and metabolic disturbances—particularly androgen excess and hyperinsulinemia—downregulate CX43 expression and impair gap junction function, thereby exacerbating ovarian microenvironmental dysfunction. Furthermore, we explore emerging therapeutic strategies aimed at preserving or restoring TZP integrity. Anti-androgen therapies (e.g., spironolactone, flutamide), insulin sensitizers (e.g., metformin), and GLP-1 receptor agonists (e.g., liraglutide) have shown potential in modulating connexin expression and enhancing granulosa-oocyte communication. In addition, agents such as melatonin, AMPK activators, and GDF9/BMP15 analogs may promote TZP formation and improve oocyte competence. Advanced technologies, including ovarian organoid models and CRISPR-based gene editing, offer promising platforms for studying TZP regulation and developing targeted interventions. In summary, TZPs are indispensable for maintaining follicular homeostasis, and their disruption plays a pivotal role in the pathogenesis of PCOS-related folliculogenesis failure. Targeting TZP integrity represents a promising therapeutic avenue in PCOS management and warrants further mechanistic and translational investigation.

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy worldwide, accounting for more than 90% of all oral cancers, and is characterized by high invasiveness and poor long-term prognosis. Its etiology is multifactorial, involving tobacco use, alcohol consumption, and human papillomavirus (HPV) infection. Oral leukoplakia and erythroplakia are the main precancerous lesions lesions, with oral leukoplakia being the most common. Both OSCC and premalignant lesions are closely associated with aberrant activation of multiple signaling pathways. Post-translational modifications (such as ubiquitination and deubiquitination) play key roles in regulating these pathways by controlling protein stability and activity. Growing evidence indicates that dysregulated ubiquitination/deubiquitination can mediate OSCC initiation and progression via aberrant activation of signaling pathways. The ubiquitination/deubiquitination process mainly involves E3 ligases (E3s) that catalyze substrate ubiquitination, deubiquitinating enzymes (DUBs) that remove ubiquitin chains, and the 26S proteasome complex that degrades ubiquitinated substrates. Abnormal expression or mutation of E3s and DUBs can lead to altered stability of critical tumor-related proteins, thereby driving OSCC initiation and progression. Therefore, understanding the aberrantly activated signaling pathways in OSCC and the ubiquitination/deubiquitination mechanisms within these pathways will help elucidate the molecular mechanisms and improve OSCC treatment by targeting relevant components. Here, we summarize four aberrantly activated signaling pathways in OSCC―the PI3K/AKT/mTOR pathway, Wnt/β-catenin pathway, Hippo pathway, and canonical NF-κB pathway―and systematically review the regulatory mechanisms of ubiquitination/deubiquitination within these pathways, along with potential drug targets. PI3K/AKT/mTOR pathway is aberrantly activated in approximately 70% of OSCC cases. It is modulated by E3s (e.g., FBXW7 and NEDD4) and DUBs (e.g., USP7 and USP10): FBXW7 and USP10 inhibit signaling, while NEDD4 and USP7 potentiate it. Aberrant activation of the Wnt/β-catenin pathway leads to β-catenin nuclear translocation and induction of cell proliferation. This pathway is modulated by E3s (e.g., c-Cbl and RNF43) and DUBs (e.g., USP9X and USP20): c-Cbl and RNF43 inhibit signaling, while USP9X and USP20 potentiate it. Hippo pathway inactivation permits YAP/TAZ to enter the nucleus and promotes cancer cell metastasis. This pathway is modulated by E3s (e.g., CRL4^DCAF1 and SIAH2) and DUBs (e.g., USP1 and USP21): CRL4^DCAF1 and SIAH2 inhibit signaling, while USP1 and USP21 potentiate it. Persistent activation of the canonical NF-κB pathway is associated with an inflammatory microenvironment and chemotherapy resistance. This pathway is modulated by E3s (e.g., TRAF6 and LUBAC) and DUBs (e.g., A20 and CYLD): A20 and CYLD inhibit signaling, while TRAF6 and LUBAC potentiate it. Targeting these E3s and DUBs provides directions for OSCC drug research. Small-molecule inhibitors such as YCH2823 (a USP7 inhibitor), GSK2643943A (a USP20 inhibitor), and HOIPIN-8 (a LUBAC inhibitor) have shown promising antitumor activity in preclinical models; PROTAC molecules, by binding to surface sites of target proteins and recruiting E3s, achieve targeted ubiquitination and degradation of proteins insensitive to small-molecule inhibitors, for example, PU7-1-mediated USP7 degradation, offering new strategies to overcome traditional drug limitations. Currently, NX-1607 (a Cbl-b inhibitor) has entered phase I clinical trials, with preliminary results confirming its safety and antitumor activity. Future research on aberrant E3s and DUBs in OSCC and the development of highly specific inhibitors will be of great significance for OSCC precision therapy.

The innate immune system serves as the body’s first line of defense against pathogens and plays a central role in inflammation regulation, immune homeostasis, and tumor immunosurveillance. In recent years, with the growing recognition of the concept “exercise is medicine”, increasing attention has been paid to the immunoregulatory effects of physical activity. Accumulating evidence suggests that regular, moderate-intensity exercise significantly enhances innate immunity by strengthening the skin-mucosal barrier, increasing levels of secretory immunoglobulin A (sIgA), and improving the functional capacity of key immune cells such as natural killer (NK) cells, neutrophils, macrophages, and dendritic cells. It also modulates the complement system and various inflammatory mediators. This review comprehensively summarizes the effects of exercise on each component of the innate immune system and highlights the underlying molecular mechanisms, including activation of AMP-activated protein kinase (AMPK), inhibition of nuclear factor-kappa B (NF-κB), enhancement of mitochondrial function via the PGC-1α/TFAM axis, and initiation of autophagy through the ULK1/mTOR pathway. Emerging mechanisms are also discussed, such as exercise-induced epigenetic modifications (e.g., histone acetylation and miRNA regulation), modulation of the gut microbiota, and metabolite-mediated immune programming (e.g., short-chain fatty acids (SCFAs), β-hydroxybutyrate). The effects of exercise on innate immunity vary considerably among individuals, depending on factors such as age, sex, and comorbidities. For example, adolescents exhibit enhanced NK cell mobilization, whereas older adults benefit from reduced chronic inflammation and immune aging. Sex hormones and metabolic conditions (e.g., obesity, diabetes, chronic obstructive pulmonary disease, cancer) further modulate the immune response to exercise. Based on these insights, we propose a personalized approach to exercise prescription guided by the FITT (frequency, intensity, time, and type) principle, aiming to optimize immune outcomes across diverse populations. Importantly, given the dual role of exercise in immune activation and regulation, caution is warranted: while moderate exercise enhances immune defense, excessive or high-intensity activity may induce transient immunosuppression. In pathological contexts such as infection, autoimmune diseases, or tissue injury, exercise intensity and timing must be carefully adjusted. This review provides practical guidelines for exercise-based immune modulation and underscores the need for dose-response studies and advancements in precision exercise medicine. In conclusion, exercise represents a safe and effective strategy for enhancing innate immune function and mitigating chronic inflammatory diseases.

Objective Cerebral palsy (CP) is a prevalent neurodevelopmental disorder acquired during the perinatal period, with periventricular white matter injury (PWMI) serving as its primary pathological hallmark. PWMI is characterized by the loss of oligodendrocytes (OLs) and the disintegration of myelin sheaths, leading to impaired neural connectivity and motor dysfunction. Neural stem cells (NSCs) represent a promising regenerative source for replenishing lost OLs; however, conventional two-dimensional (2D) in vitro culture systems lack the three-dimensional (3D) physiological microenvironment. Microfluidic chip technology has emerged as a powerful tool to overcome this limitation by enabling precise spatial and temporal control over 3D microenvironmental conditions, including the establishment of stable concentration gradients of bioactive molecules. Catalpol, an iridoid glycoside derived from traditional medicinal plants, exhibits dual antioxidant and anti-apoptotic properties. Despite its therapeutic potential, the capacity of catalpol to drive NSC differentiation toward OLs under biomimetic 3D conditions, as well as the underlying molecular mechanisms, remains poorly understood. This study aims to develop a microfluidic-based 3D biomimetic platform to systematically investigate the concentration-dependent effects of catalpol on promoting NSCs-to-OLs differentiation and to elucidate the role of the caveolin-1 (Cav-1) signaling pathway in this process.Methods We developed a novel multiplexed microfluidic device featuring parallel microchannels with integrated gradient generators capable of establishing and maintaining precise linear concentration gradients (0-3 g/L catalpol) across 3D NSCs cultures. This platform facilitated the continuous perfusion culture of NSC-derived 3D spheroids, mimicking the dynamic in vivo microenvironment. Real-time cell viability was assessed using Calcein-AM/propidium iodide (PI) dual staining, with fluorescence imaging quantifying live/dead cell ratios. Oligodendrocyte differentiation was evaluated through quantitative reverse transcription polymerase chain reaction (qRT-PCR) for MBP and SOX10 gene expression, complemented by immunofluorescence staining to visualize corresponding protein changes. To dissect the molecular mechanism, the Cav-1-specific pharmacological inhibitor methyl-β-cyclodextrin (MCD) was employed to perturb the pathway, and its effects on differentiation markers were analyzed.Results Catalpol demonstrated excellent biocompatibility, with cell viability exceeding 96% across the entire tested concentration range (0-3 g/L), confirming its non-cytotoxic nature. At the optimal concentration of 0-3 g/L, catalpol significantly unregulated both MBP and SOX10 expression (P<0.05, P<0.01), indicating robust promotion of oligodendroglial differentiation. Intriguingly, Cav-1 mRNA expression was progressively downregulated during NSC differentiation into OLs. Further inhibition of Cav-1 with MCD further enhanced this effect, leading to a statistically significant increase in OL-specific gene expression (P<0.05, P<0.01), suggesting Cav-1 acts as a negative regulator of OLs differentiation.Conclusion This study established an integrated microfluidic gradient chip-3D NSC spheroid culture system, which combines the advantages of precise chemical gradient control with physiologically relevant 3D cell culture. The findings demonstrate that 3 g/L catalpol effectively suppresses Cav-1 signaling to drive NSC differentiation into functional OLs. This work not only provides novel insights into the Cav-1-dependent mechanisms of myelination but also delivers a scalable technological platform for future research on remyelination therapies, with potential applications in cerebral palsy and other white matter disorders. The platform’s modular design permits adaptation for screening other neurogenic compounds or investigating additional signaling pathways involved in OLs maturation.

Bispecific antibodies, engineered to simultaneously bind two distinct antigens or two epitopes on the same antigen, are now widely utilized in tumor therapy and various other fields. Depending on their mechanisms of action, bispecific antibodies can be designed into diverse structural formats, including IgG-like bispecific antibodies containing an Fc region. The Fc region mediates immune effector functions by interacting with receptors on immune cells or soluble immune components. However, antibodies containing an Fc region have a relatively high molecular weight, which limits their tissue penetration. They also exhibit slow systemic clearance in vivo and possess pharmacokinetic characteristics marked by a long terminal elimination half-life. Symmetric IgG-like bispecific antibodies feature a symmetric structure and are bivalent for each target antigen. During production, since the two heavy chains carrying the Fc region are identical, issues related to chain mispairing do not arise, thereby simplifying the manufacturing and purification processes. Moreover, the pairing of two identical natural Fc chains allows for correct disulfide bond formation, resulting in a more stable structure. Glycosylation of the Fc region remains in its natural state, preserving Fc-mediated functions. However, as the variable regions of the two antigen-binding sites are linked to the same heavy chain, the design must account for potential steric hindrance when the antibody binds both antigens simultaneously. In contrast, asymmetric IgG-like bispecific antibodies consist of two different heavy chains, each carrying antigen-binding domains that recognize distinct antigens or epitopes, offering greater structural design flexibility. Their development, however, requires addressing challenges related to heavy chain and light chain pairing. Strategies to prevent heavy chain mispairing include engineering the spatial configuration of the Fc region, facilitating Fab arm exchange, applying IgG-IgA chain exchange techniques, and introducing charge modifications in the Fc domain. To ensure correct light chain–heavy chain pairing, approaches such as introducing electrostatic interactions or novel disulfide bonds between the chains, swapping the CH1 and CL domains, or replacing the CH1-CL module with a T-cell receptor-derived structure have been employed. Non-IgG-like bispecific antibodies lack an Fc region. They are characterized by their small size and low molecular weight, which confer enhanced tissue penetration, rapid systemic clearance, and high structural versatility. Unlike IgG-based formats, they do not bind Fc receptors or activate the complement system directly. Different bispecific antibodies exert therapeutic effects through distinct mechanisms, which are largely determined by their structural design and target specificity. Currently recognized mechanisms of action include T cell redirection, dual signaling pathway blockade, immune checkpoint inhibition, formation of ternary complexes by binding two molecules, neutralization of soluble ligands, and acting as cofactors to mimic or enhance biological processes. Bispecific antibodies are extensively applied in cancer therapy. Beyond oncology, they are also being developed for the treatment of autoimmune diseases, infectious diseases, hematological disorders, and other conditions. Different structural designs offer unique advantages across therapeutic areas. This article elaborates on the structural designs of various types of bispecific antibodies and reviews their mechanisms of action and applications in therapeutics.

Objective Non-coding RNA (ncRNA) plays a crucial regulatory role in various biological processes. Numerous studies have shown that the functions of ncRNAs depend not only on their nucleotide sequences but also closely on their spatial conformations, particularly their secondary structures. Traditional methods for predicting RNA secondary structures often have low accuracy, usually around 50 to 70 percent, and their performance further declines when dealing with complex structures or long sequences. Although deep learning methods have improved prediction performance to some extent, they still face challenges such as high model complexity, difficulty in capturing long-range dependencies, and poor generalization in predicting complex structures. Therefore, it is necessary for RNA secondary structure prediction to develop new methods.Methods This study proposed an end-to-end prediction model RMDfold, which employed a feature extraction strategy combining residual Mamba (resMamba) and dense connections (Dense). The model framework consisted of three modules: one-dimensional (1D) modeling, feature mapping, and two-dimensional (2D) modeling. For the 1D modeling module, the model learned contextual dependencies among nucleotides from RNA sequences, providing the foundation for possible base-pairing; for the feature mapping module, the 1D features were projected into a 2D space to form a constraint matrix that represented potential base-pairing relationships; for the 2D modeling module, the model further learned the pairing patterns between nucleotides, and determined the unique pairing of each nucleotide through pairing constraints, to obtain the final secondary structure. For both 1D and 2D modeling modules, a four-layer Dense block composed of batch normalization, ReLU activation, and convolution was used to extract short-range features; and a dual-branch residual structure resMamba based on a state-space model was used to model long-range dependencies, thereby achieving effective integration of short- and long-range features. To validate the effectiveness of the proposed method, it was compared with Ufold, REDfold, TransUfold, and sincfold on the three public datasets RNAStralign, ArchiveII, and bpRNA-new.Results The proposed RMDfold method demonstrates superior performance compared with existing algorithms in structure prediction, pseudoknot prediction, sequence prediction across varying lengths, and model complexity analysis, while requiring fewer parameters and achieving faster inference. For the structure prediction, the method achieved F1, Matthews correlation coefficient (MCC), precision and recall of 0.973 5, 0.973 1, 0.975 6 and 0.972 3 on RNAStralign, 0.854 3, 0.855 6, 0.874 7 and 0.876 2 on ArchiveII, and 0.382 8, 0.401 5, 0.536 5 and 0.318 7 on bpRNA-new, respectively. For the pseudoknot prediction based on ArchiveII, the model achieved F1, MCC, precision and recall of 0.741 4, 0.743 3, 0.752 5 and 0.739 6. For the sequence prediction across different lengths, RMDfold maintained an accuracy of 0.70 for sequences ranging from 200 to 500 nt. In terms of model complexity, RMDfold required 2.886 7 M parameters and achieves an inference speed of 0.026 0 s.Conclusion RMDfold enables highly accurate prediction of RNA secondary structures. It helps to deeply and comprehensively reveal the central roles of RNA molecules in gene expression regulation, molecular recognition, and catalysis. and also provides important structure support for elucidating disease-related variant mechanisms, designing RNA-targeted drugs, and advancing research in evolution and comparative genomics.

Viral membrane fusion proteins facilitate the fusion of viral and host cell membranes by undergoing a transition from a prefusion conformation to a post-fusion conformation, thereby enabling the transfer of viral nucleic acids into the cell interior. This transition process is characterized by peptide exposure, membrane insertion, and structural refolding. The prefusion configuration represents an optimal target for vaccine formulation and antiviral pharmacotherapy. However, the metastable nature of the prefusion conformation makes it prone to spontaneous conversion into the stable post-fusion conformation, thereby complicating structural analysis and vaccine design. Investigating the mechanisms of conformational change in these proteins and developing methods to stabilize their prefusion state remain challenging research topics. This review summarizes the structural and functional differences among three classes of membrane fusion proteins: Class I proteins, which are predominantly composed of α-helices, form trimers, and rely on receptor binding or low pH to trigger fusion peptide release; Class II proteins, which are mainly β-sheet-rich, rearrange from dimers to trimers and activate fusion loops via low pH; and Class III proteins, which combine α-helices and β-structures, with mechanisms involving internal fusion loop insertion and membrane remodeling. It is evident that a comprehensive understanding of the mechanisms underlying viral membrane fusion is crucial for developing effective stabilization strategies for the prefusion conformation of these proteins. This paper presents several such methods that have been successfully employed in this endeavor, including: disulfide bond formation to stabilize domain-domain interactions; hydrophobic cavity filling to enhance core stability; proline substitution to restrict structural transitions in hinge regions; and multimer domains stabilizing the trimeric conformation. The stabilization strategies summarized and discussed herein have been validated in studies of multiple viral membrane fusion proteins and further applied in the design of vaccine antigens. Moreover, this paper highlights the potential applications of novel techniques, such as time-resolved cryo-EM, in capturing conformational intermediates and resolving dynamic transition processes. Such stabilization efforts, informed by structural insights, have yielded promising outcomes—for instance, prefusion-stabilized RSV F antigens that elicit potent neutralizing antibodies in clinical trials. Looking ahead, integrating computational modeling, such as AlphaFold predictions, with experimental data will further refine these approaches. Ultimately, these innovations promise to enable structure-guided therapeutics to combat emerging viral threats. This review provides a theoretical foundation for developing stable viral membrane fusion proteins, offering crucial insights for understanding viral membrane fusion mechanisms and advancing next-generation vaccines and antiviral drugs.

The formation of protein-protein interaction (PPI) networks is a central event in biochemical reactions within organisms. These interactions not only regulate normal physiological functions but are also closely associated with the onset and progression of diseases. PPIs are intricately regulated by proteins, nucleic acids, and their interactions. The complex molecular networks formed between these molecules serve as the foundation for most biochemical reaction events. Moreover, biological information is transmitted through countless molecular interactions within the cellular environment. A wide range of technologies has been developed to study PPIs, among which proximity-dependent biotinylation is a novel technique for labeling proteomes in living cells. This method utilizes engineered biotin ligases to specifically label nearby proteins or RNA molecules, enabling the capture of transient, weak, or stable interactions and facilitating the systematic construction of molecular interaction maps. Through continuous enzyme optimization and refinement, proximity-dependent biotinylation techniques have evolved into diverse systems with improved operational convenience and labeling efficiency. Each proximity-dependent biotinylation technique offers unique advantages: BioID is non-toxic to cells but suffers from low labeling efficiency, requires 18–24 h for labeling, and yields limited biotinylated products. TurboID achieves efficient labeling within 10 min, but its high activity and strong biotin affinity may lead to cytotoxicity. AirID enables low-toxicity labeling under low biotin concentrations but requires several hours to complete. UltraID offers the highest labeling activity with the smallest molecular weight but is prone to over-labeling. APEX provides convenient operation and can resolve protein topology, yet it has concentration-dependent limitations—forming dimers at high concentrations and lacking sensitivity at low concentrations. RNA-BioID is tailored for studying RNA–protein interactions but is limited by non-specific binding. TransitID can capture dynamic protein translocation at the subcellular level, though its temporal resolution still requires improvement. This review systematically summarizes the development, mechanisms, advantages, and disadvantages of proximity-dependent biotinylation techniques such as BioID, TurboID, AirID, UltraID, RNA-BioID, APEX, and TransitID. It also explores their cutting-edge applications in functional regulation and disease research. Proximity-dependent biotinylation techniques are widely used in disease-related studies. In tumor research, they are primarily applied to investigate the transcriptional regulation and chromosomal structural changes of proto-oncogenes and tumor suppressor genes. In the field of neuroscience, they are used to study mechanisms underlying nervous system function and neurological diseases. In viral infection mechanisms, they help elucidate virus–host interaction networks. In immune regulation, they contribute to the study of immune signaling pathways. In stem cell research, they aid in understanding cell differentiation processes. Furthermore, proximity-dependent biotinylation techniques hold promise for integration with spatial biology technologies, enabling more comprehensive and detailed protein studies. These techniques are expected to provide more accurate and efficient tools for life science research and to advance the medical and health fields to a higher level. By comprehensively analyzing the strengths, limitations, and innovative potential of each method, this review also highlights their advantageous applications in molecular interaction studies, aiming to provide methodological guidance and theoretical support for molecular mechanism research in the life sciences.

Chinese hamster ovary (CHO) cells are the most established and versatile mammalian expression system for the large-scale production of recombinant therapeutic proteins, owing to their genetic stability, adaptability to serum-free suspension culture, and ability to perform human-like post-translational modifications. More than 70% of biologics approved by the U.S. Food and Drug Administration rely on CHO-based production platforms, underscoring their central role in modern biopharmaceutical manufacturing. Despite these advantages, CHO systems continue to face three persistent bottlenecks that limit their potential for high-yield, reproducible, and cost-efficient production: excessive metabolic burden during high-density culture, heterogeneity of glycosylation patterns, and progressive loss of long-term expression stability. This review provides an integrated analysis of recent advances addressing these challenges and proposes a forward-looking framework for constructing intelligent and sustainable CHO cell factories. In terms of metabolic regulation, excessive lactate and ammonia accumulation disrupts energy balance and reduces recombinant protein synthesis efficiency. Optimization of culture parameters such as temperature, pH, dissolved oxygen, osmolarity, and glucose feeding can effectively alleviate metabolic stress, while supplementation with modulators including sodium butyrate, baicalein, and S-adenosylmethionine promotes specific productivity (qP) by modulating apoptosis and chromatin structure. Furthermore, genetic engineering strategies—such as overexpression of MPC1/2, HSP27, and SIRT6 or knockout of Bax, Apaf1, and IGF-1R—have demonstrated significant improvements in cell viability and product yield. The combination of multi-omics metabolic modeling with artificial intelligence (AI)-based prediction offers new opportunities for building self-regulating CHO systems capable of dynamic adaptation to environmental stress. Regarding glycosylation uniformity, which determines therapeutic efficacy and immunogenicity, gene editing-based glycoengineering (e.g., FUT8 knockdown or ST6Gal1 overexpression) has enabled the humanization of CHO glycan profiles, minimizing non-human sugar residues and enhancing drug stability. Process-level strategies such as galactose or manganese co-feeding and fine control of temperature or osmolarity further allow rational regulation of glycosyltransferase activity. Additionally, in vitro chemoenzymatic remodeling provides a complementary route to construct human-type glycans with defined structures, though industrial applications remain constrained by cost and scalability. The integration of model-driven process design and AI feedback control is expected to enable real-time prediction and correction of glycosylation deviations, ensuring batch-to-batch consistency in continuous biomanufacturing. Long-term expression stability, another critical challenge, is often impaired by promoter silencing, chromatin condensation, and random genomic integration. Molecular optimization—such as the use of improved promoters (CMV, EF-1α, or CHO endogenous promoters), Kozak and signal peptide refinement, and incorporation of chromatin-opening elements (UCOE, MAR, STAR)—helps maintain durable transcriptional activity, while site-specific integration systems including Cre/loxP, Flp/FRT, φC31, and CRISPR/Cas9 can enable single-copy, position-independent gene insertion at genomic safe-harbor loci, ensuring stable, predictable expression. Collectively, this review highlights a paradigm shift in CHO system optimization driven by the convergence of genome editing, synthetic biology, and artificial intelligence. The transition from empirical optimization to rational, data-driven design will facilitate the development of programmable CHO platforms capable of autonomous regulation of metabolic flux, glycosylation fidelity, and transcriptional activity. Such intelligent cell factories are expected to accelerate the transformation from laboratory-scale research to industrial-scale, high-consistency, and economically sustainable biopharmaceutical manufacturing, thereby supporting the next generation of efficient and customizable biologics manufacturing.

Post-translational modification (PTM) of proteins refers to the covalent addition of functional groups to amino acid residues or structural alterations in proteins during or after translation, primarily mediated by enzymatic reactions and secondarily by non-enzymatic chemical processes. PTM crosstalk denotes interactions between distinct modification sites or different types of modifications on a single protein, which regulate protein functions through synergistic, antagonistic, or cascading mechanisms. Lactylation, phosphorylation, and acetylation are three pivotal types of protein PTMs, involving the covalent attachment of lactic acid, phosphate, and acetyl groups to specific amino acid residues, respectively. These reversible modifications are dynamically regulated by cellular metabolic status and signaling pathways. Phosphorylation primarily facilitates rapid signal transduction; acetylation broadly regulates metabolism and gene expression; and lactylation is closely associated with high-lactate microenvironments and metabolic stress. Through competitive binding at identical or adjacent sites, reciprocal modulation of metabolite levels, and cross-regulation of signaling pathways, these three modifications form an intricate crosstalk network that coordinately regulates cellular adaptive responses to internal and external environmental changes. As a physiological stimulus with broad effects on bodily functions, exercise induces a series of changes in intracellular metabolism and signal transduction, thereby influencing PTMs and their crosstalk. On one hand, exercise activates multiple interconnected cellular systems, including energy metabolism, signal transduction, and molecular interaction networks. Within the energy metabolism system, exercise alters the pattern of cellular ATP production and utilizes metabolic intermediates as signaling molecules to directly or indirectly modulate the activity of enzymes involved in these three modifications. In the signal transduction system, exercise activates pathways such as AMP-activated protein kinase (AMPK) and mitogen-activated protein kinase (MAPK), which precisely regulate the activity and subcellular localization of modification-related enzymes via phosphorylation cascades. In the molecular interaction system, exercise promotes protein-protein and protein-metabolite interactions, thereby remodeling the regulatory network of PTMs. On the other hand, exercise facilitates crosstalk among lactylation, phosphorylation, and acetylation through a multi-level progressive regulatory model: “metabolic initiation → signal transduction → molecular interaction”. At the metabolic level, alterations in metabolites provide the initial driving force for crosstalk; signaling pathways amplify these signals and precisely modulate the direction of crosstalk through cascade reactions; and molecular interactions further integrate signals to establish a refined regulatory network. Ultimately, this multi-system and multi-level crosstalk enables precise regulation of cell proliferation, differentiation, and apoptosis, thereby mediating cellular adaptation to exercise and playing a central role in enhancing exercise capacity and improving metabolic health. This article systematically examines how exercise influences crosstalk among these three key PTMs—lactylation, phosphorylation, and acetylation—and the underlying mechanisms, including the regulation of metabolite levels, modification-related enzyme activity, cellular signaling pathways, metabolic homeostasis, and gene expression. This work provides a novel perspective for gaining deeper insights into how exercise regulates physiological functions.

Obesity has become a major global public health concern, affecting more than one billion individuals worldwide. As a low-grade chronic inflammatory condition, obesity is closely associated with cardiometabolic disorders and gut microbial dysbiosis. Diet-based interventions are recognized as one of the safest and most effective strategies for long-term weight management. Increasing evidence indicates that specific dietary patterns can modulate gut microbiota (GM) composition and metabolic function. However, comparative evidence regarding the effects of different dietary strategies remains limited and inconsistent. This systematic review and meta-analysis comprehensively evaluated the effects of the very-low-calorie ketogenic diet (VLCKD), Mediterranean diet (MD), and intermittent fasting (IF) on gut microbiota in obese populations. Systematic searches of PubMed, EBSCOhost, Cochrane, and Web of Science were conducted up to September 2025. Meta-analyses using R software assessed changes in microbial diversity and characteristic taxa abundance, with subgroup analyses by body mass index (BMI), age, and intervention duration. A total of 42 studies were included. Random-effects meta-analysis revealed that VLCKD significantly increased the Shannon index, observed OTUs, and Faith"s phylogenetic diversity (PD), promoted Akkermansia abundance and the Firmicutes/Bacteroidetes (F/B) ratio, but reduced Bifidobacterium abundance, indicating a bidirectional regulatory effect on gut microbial structure. MD significantly increased the Shannon index as well as the abundance of Akkermansia, Bifidobacterium, and Bacteroidetes, while decreasing Firmicutes abundance and the F/B ratio, suggesting a balanced and sustained improvement in gut microbial composition. In contrast, IF significantly decreased the PD index while increasing Akkermansia and reducing Firmicutes, reflecting partial structural optimization but limited enhancement of phylogenetic diversity; long-term interventions were associated with a decline in Shannon diversity, indicating limited stability. Subgroup analyses revealed distinct moderator effects. Under VLCKD, improvements in microbial diversity were more pronounced among individuals with BMI≤30 kg/m² and those aged 30 years, and meta-regression confirmed that the magnitude of diversity gains increased with age. Regarding BMI, increases in Akkermansia abundance were most evident in individuals with BMI 30–35 kg/m², whereas Bifidobacterium abundance significantly decreased in the same range, suggesting a threshold-dependent microbial response to adiposity. With respect to age, both Akkermansia (increase) and Bifidobacterium (decrease) exhibited significant changes in individuals aged 40 years. In terms of intervention duration, Akkermansia increased significantly within 6 weeks, while Bifidobacterium decreased within 12 weeks. For MD, increases in Shannon diversity were consistently observed across all BMI, age, and duration subgroups; notably, Akkermansia abundance increased significantly among participants with BMI30 kg/m², aged 30–50 years, and during interventions ≤6 months, while Bifidobacterium abundance rose markedly in participants with BMI≤30 kg/m², aged 40–50 years, and during interventions of 6–12 months. Under IF, Shannon diversity increased significantly in individuals with BMI≤30 kg/m² and aged 40 years but declined when the intervention exceeded 4 weeks, suggesting reduced long-term stability. In conclusion, VLCKD, MD, and IF all modulate gut microbiota in obesity but differ in magnitude, direction, and durability. VLCKD exerts strong yet dual effects—enhancing diversity while reducing beneficial taxa; MD shows stable, sustained modulation; whereas IF offers selective improvements but lowers phylogenetic diversity with limited persistence. Future studies should conduct large, multicenter randomized controlled trials to determine optimal intervention duration, confirm the moderating roles of age and BMI, and develop personalized microbiota-based dietary strategies for obesity management and gut health improvement.

The comorbidity of sarcopenia and cognitive impairment constitutes a degenerative syndrome that progresses significantly with age. It has emerged as a critical global health challenge, contributing to functional disability, reduced quality of life, and increased pressure on public healthcare systems. This comorbidity is characterized by a synergistic decline in both physical and cognitive capabilities, manifesting as reduced skeletal muscle mass, diminished muscle strength, impaired physical function, and progressive deterioration in cognitive domains such as memory, executive function, and information processing speed. This dual degeneration not only creates a vicious cycle where each condition exacerbates the other but also substantially increases the risk of falls, fractures, hospitalization, and mortality among older adults. Against the backdrop of rapid global population aging, the prevalence of this comorbidity is anticipated to rise further without effective interventions. Consequently, investigating its underlying mechanisms and developing preventive and therapeutic strategies hold substantial clinical and public health significance. Current evidence indicates that the pathogenesis involves multi-system and multi-level pathophysiological processes, with chronic inflammation, mitochondrial dysfunction, and gut microbiota dysbiosis, identified as three core interacting mechanisms. Age-related chronic low-grade inflammation, termed inflammaging, arises from the senescence-associated secretory phenotype (SASP) and persistent immune cell activation. This inflammatory state inhibits the intramuscular IGF-1/Akt/mTOR anabolic pathway through proinflammatory cytokines (e.g., IL-6, TNF-α), while simultaneously activating protein degradation systems including the ubiquitin-proteasome system (UPS) and autophagy-lysosomal pathway (ALP), ultimately leading to accelerated protein breakdown and muscle atrophy. These circulating inflammatory factors can also compromise blood-brain barrier integrity, activate microglia, trigger neuroinflammation, and consequently damage synaptic structures and neuronal function, thereby accelerating cognitive decline in this comorbidity. Mitochondrial dysfunction presents as impaired oxidative phosphorylation efficiency, excessive reactive oxygen species (ROS) production, and dysregulated mitochondrial quality control. This not only results in inadequate cellular energy supply but also enables mitochondrial-derived factors (e.g., extracellular mtDNA) to activate innate immune pathways such as cGAS-STING, propagating stress signals and amplifying tissue damage in both muscle and brain. Additionally, gut microbiota dysbiosis impairs intestinal barrier function, increases lipopolysaccharide (LPS) translocation into circulation, and reduces short-chain fatty acid (SCFA) production. These changes induce systemic inflammation and metabolic disturbances that further impact muscle metabolism and promote pathological protein accumulation in the brain, thereby establishing a gut-brain-muscle axis that exacerbates the progression of this comorbidity. Exerkines represent a class of biologically active signaling molecules—including cytokines, peptides, metabolites, and exosomes—secreted by various tissues in response to exercise. These exerkines mediate systemic adaptations and protective effects through endocrine and paracrine actions on target organs. Key exerkines such as IL-6, Irisin, brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), fibroblast growth factor 21 (FGF-21), lactate, and cathepsin B (CTSB) play central roles in coordinately ameliorating the comorbidity of sarcopenia and cognitive impairment. The beneficial effects of these exerkines are mediated through multiple mechanisms including inflammation modulation, energy metabolism remodeling, neuroprotection, and enhanced neuroplasticity. As a non-pharmacological intervention, exercise effectively stimulates the production and release of exerkines, thereby targeting the comorbidity through multiple pathways. Aerobic exercise elevates lactate levels and activates the Sirt1/PGC-1α pathway, improving cerebral metabolism and cognitive function. Resistance training significantly upregulates IGF-1, Irisin, and CTSB expression, enhancing muscle anabolism and hippocampal function. Other modalities like high-intensity interval training (HIIT) and traditional practices also help modulate inflammatory status and optimize the neurotrophic environment through the action of various exerkines. Different exercise types work synergistically by engaging distinct signaling pathways and exerkine combinations, collectively alleviating chronic inflammation, correcting mitochondrial dysfunction, and optimizing gut microecology to achieve concurrent musculoskeletal and cognitive protection against this comorbidity. Synthesizing current evidence, this review emphasizes the necessity of transcending a single-organ perspective by recognizing muscle and brain as an integrated functional unit, with exerkines playing a pivotal role in the muscle-brain axis. The field nevertheless faces several challenges: the secretion dynamics of exerkines during aging remain unclear, mechanisms underlying individual differences in exercise response require elucidation, and the compensatory and imbalance characteristics of exercise-induced exerkine networks across disease stages need further characterization. Future research should employ large-sample cohorts and randomized controlled trials integrated with multi-omics technologies to establish personalized exercise interventions based on exerkine profiling for managing this comorbidity. Parallel efforts should focus on developing quantifiable efficacy assessment systems to provide robust theoretical foundation and practical guidance for precise management of the comorbidity of sarcopenia and cognitive impairment and the promotion of healthy aging.

Objective To address the challenge of identifying unknown animal-derived components in the fields of forensic evidence and food safety, this study developed and validated a sensitive and efficient multiplex polymerase chain reaction-capillary electrophoresis (PCR-CE) detection system capable of simultaneously identifying DNA from 13 species—cattle (Bos taurus), mouse (Mus musculus), dog (Canis lupus familiaris), rat (Rattus norvegicus), pig (Sus scrofa), Chinese hamster (Cricetulus griseus), cat (Felis catus), horse (Equus caballus), human (Homo sapiens), chicken (Gallus gallus), duck (Anas platyrhynchos), donkey (Equus asinus), and sheep (Ovis aries)—within a single-tube reaction.Methods Species-specific primers were meticulously designed targeting hypervariable regions of the mitochondrial DNA (including Cytb, COI, 16S rRNA, and ND2 genes), with primer specificity rigorously verified in silico using BLAST analysis against non-target species. A multiplex PCR system was constructed, and critical reaction parameters, including primer concentrations and annealing temperature, were systematically optimized through gradient experiments to ensure balanced amplification of all 13 targets without non-specific products or primer-dimer formation. Amplification products were subsequently separated and detected based on their characteristic fragment lengths and distinct fluorescent labels (6-FAM, HEX) using a capillary electrophoresis platform. The established multiplex PCR-CE system was comprehensively evaluated across several parameters: specificity was tested against 17 species (13 target species and 4 non-target species); sensitivity was determined using serial dilutions of mixed DNA templates; the ability to detect adulteration was assessed using simulated mixed meat samples with known adulteration percentages (10% to 0.1%); and practical applicability was investigated by analyzing 27 commercially available meat products and authentic casework samples from a fatal dog attack incident.Results The optimized multiplex PCR-CE system successfully demonstrated specific and simultaneous amplification for all 13 target species, with zero cross-reactivity observed with 4 non-target species. The system exhibited high sensitivity, with detection limits ranging from 0.05 ng to 0.001 ng of DNA template depending on the species; ten species were detectable at the 0.001 ng level. In simulated adulteration studies, the system reliably detected duck DNA in sheep meat at 0.5%, pork in beef at 0.5%, and horse meat in donkey meat at a remarkably low level of 0.1%. Analysis of commercial meat products revealed an 18.52% (5/27) mislabeling rate. These findings were consistent with validation tests using national and industry standard methods. Furthermore, the system effectively identified human and dog DNA from real forensic case evidence (clothing fragments from bite marks), and even detected trace pig DNA, suggesting the dog"s prior pork consumption.Conclusion This study successfully established a highly specific, sensitive, and practical multiplex PCR-CE system for the simultaneous identification of 13 species. By combining the power of multiplex PCR with capillary electrophoresis, our approach delivers a significant advantage in terms of throughput, resolution, and automation over traditional gel-based methods. The system"s proven effectiveness in detecting low-level adulteration in complex mixtures and processed food products, along with its successful application to genuine forensic specimens, underscores its substantial value and broad potential for routine use in forensic laboratories for evidence analysis and in regulatory settings for ensuring food authenticity and safety monitoring.

Social interaction is central to the development of human cognition and behavior. Studying the neural mechanisms of social interaction helps reveal the neurobiological basis of social functions, such as group cooperation and knowledge transfer. In recent years, social neuroscience research has adopted hyperscanning technology and brain-to-brain coupling (BBC) measurements to reveal the group neural dynamics mechanisms under social interactions. Existing studies have primarily focused on three social contexts highly relevant to social interaction, namely interpersonal communication, task collaboration, and teacher-student instruction. However, the driving factors of BBC across these contexts and their interaction patterns under naturalistic paradigms have not yet been systematically analyzed within a unified framework, and the underlying driving mechanisms remain unclear. To address this limitation, the present review focused on three social contexts with increasing ecological validity in social interaction. It systematically examines the exogenous and endogenous drivers of BBC across these contexts and reveals commonalities and differences across contexts. Exogenous factors provide external conditions and spatiotemporal framework for interaction through sensory input and behavioral patterns. These external conditions induce BBC by guiding individuals to focus on the same target within the same time window, thereby invoking shared attention. However, exogenous drivers can only ensure surface alignment of interactions. Without the support of endogenous drivers, brain-brain coupling is difficult to maintain or deepen. Endogenous factors determine the depth and continuity of interactions through high-level social cognitive processing. Specifically, social closeness enhances trust and empathy between interacting partners, promoting interpersonal multimodal information integration and emotional empathy. Shared attention is the key link for individuals to move from behavioral alignment to initial coupling at the neural level. Shared intentionality led individuals to converge on goals and strategies, forming cognitive predictions during the cooperation process. Shared understanding ensures that individuals can perform high-level cognitive processing based on a common knowledge framework. The above-mentioned endogenous driving factors enhance BBC by engaging higher-order cognitive regions such as the prefrontal cortex, temporoparietal junction, and default mode network. This engagement enables the interaction to shift from transient attention coupling to stable intention alignment and cognitive sharing. Therefore, the formation of BBC can be viewed as a process that evolves "from external to internal, from weak to strong". Exogenous driving factors initiate neural alignment through shared attention. Endogenous driving factors then strengthen BBC via shared understanding and shared intentionality. Together, these processes support the construction of group-level shared cognition. Finally, this article summarized the current challenges in research on the driving mechanisms of BBC and provided an outlook for future development. First, it is necessary to theoretically establish a hierarchical model of brain-brain coupling based on a hierarchy of cognitive complexity, systematically distinguishing between the characteristics of BBC driven by low-level processes and higher-level interpersonal shared cognitive mechanisms. Second, at the methodological and technical level, future development of multimodal hyperscanning systems such as EEG-fNIRS and closed-loop hyper-transcranial alternating current stimulation could comprehensively analyze the dynamic evolution of BBC related to shared cognition in the temporal, spatial, and frequency domains. In summary, this article constructed a theoretical framework for the driving mechanisms of BBC across social contexts, hoping to provide a methodological basis for controlling the driving factors of naturalistic paradigms in social neuroscience research.

This review synthesizes recent advances in prolamin-based multicomponent nanocarriers, with a focus on their physicochemical properties, modification strategies, and potential applications in functional foods, biomedicine, and sustainable agriculture. The abundance of hydrophobic amino acid residues in prolamins facilitates spontaneous self-assembly into nanoparticles, making them promising carriers for poorly water-soluble bioactive compounds such as curcumin and resveratrol. However, native prolamin nanoparticles suffer from limitations including poor colloidal stability, tendency to aggregate under processing or physiological conditions (e.g., pH, ionic strength, enzymatic degradation), and limited functional diversity. To address these drawbacks, extensive research has been devoted to modification strategies aimed at enhancing stability, structural integrity, and cargo protection. Polysaccharide modification enables the formation of stable core-shell structures through electrostatic interactions, hydrogen bonding, and steric hindrance. Coatings with pectin, chitosan, or alginate improve stability across a broad range of pH values and ionic strengths, enhance resistance to gastric digestion, and enable sustained release in the intestine, thereby improving bioavailability. Polyphenol modification introduces hydrogen bonding, hydrophobic interactions, and occasionally covalent cross-linking, which modify nanoparticle structure and surface properties. These composites exhibit improved hydrophilicity, colloidal stability, and resistance to oxidative or UV-induced degradation, along with intrinsic antioxidant activity. Lipid modification leverages hydrophobic interactions with oils or fatty acids to form composite nanoparticles or Pickering emulsions. This approach increases the loading capacity for hydrophobic compounds, creates a protective barrier, and enhances oral bioavailability by promoting emulsification and intestinal absorption. Additional strategies include the incorporation of auxiliary proteins (e.g., casein, whey protein) to improve stability and emulsifying capacity, as well as the use of inorganic nanomaterials (e.g., SiO₂, AuNPs) to impart mechanical reinforcement, antibacterial properties, and stimuli-responsive functions. Genetic engineering further allows molecular-level tailoring of amino acid sequences to fine-tune hydrophobicity, amphiphilicity, and self-assembly behavior. These engineered nanocarriers exhibit advanced functionalities. They enable sustained and stimuli-responsive release triggered by pH, redox potential, enzymes, temperature, or light, facilitating on-demand delivery that maximizes efficacy while minimizing off-target effects. Targeting can be achieved passively through the enhanced permeability and retention (EPR) effect, or actively via conjugation with ligands, antibodies, or peptides that recognize specific receptors. The applications of these systems are broad. In functional foods and nutraceuticals, prolamin-based carriers improve the stability, bioavailability, and controlled release of sensitive bioactive ingredients, supporting personalized nutrition. In biomedicine, they enhance oral drug delivery, enable targeted cancer therapy with reduced systemic toxicity, and serve as scaffolds for tissue engineering. In agriculture, they facilitate the controlled release of pesticides, fertilizers, and growth regulators, helping to reduce environmental contamination and promote sustainable practices; they are also being explored for smart food packaging applications. Despite significant progress, challenges remain in clinical and industrial translation. There is an urgent need for standardized characterization methods, comprehensive in vivo safety and efficacy evaluations, and scalable, regulation-compliant manufacturing processes. Future research should adopt rational design principles to develop multi-stimuli-responsive and sustainable systems. The integration of artificial intelligence and data-driven approaches may further accelerate the development of personalized theranostic platforms and co-delivery systems. Continued innovation is expected to solidify the role of prolamin-based nanocarriers in advancing global health and sustainable development.

Alzheimer"s disease (AD) is a common chronic neurodegenerative disorder of the central nervous system characterized by progressive impairments in memory, cognition, and behavior, eventually leading to severe dementia and loss of self-care ability. Despite decades of investigation, the precise molecular mechanisms underlying AD remain incompletely understood, and effective disease-modifying treatments are still lacking. The traditional pathological hallmarks of AD including amyloid β-protein (Aβ) plaques and neurofibrillary tangles (NFTs) composed of hyperphosphorylated Tau fail to account for the complex biochemical and cellular alterations observed in AD brains. Ferroptosis, a distinct iron-dependent form of non-apoptotic programmed cell death, is increasingly recognized as a contributor to AD pathogenesis. Ferroptosis is driven by excessive accumulation of lipid peroxides and reactive oxygen species (ROS), leading to oxidative destruction of cellular membranes. Unlike apoptosis or necrosis, ferroptosis is morphologically characterized by shrunken mitochondria with condensed membrane densities and biochemically defined by the loss of glutathione peroxidase 4 (GPX4) activity. Disruption of iron homeostasis, a central hallmark of ferroptosis, triggers a cascade that inhibits the cystine/glutamate antiporter (System Xc^-), suppresses glutathione (GSH) synthesis, and impairs GPX4-mediated detoxification of lipid peroxides, leading to uncontrolled lipid peroxidation and oxidative stress that ultimately trigger ferroptotic cell death. This iron-driven cell death exhibits distinct morphological and biochemical characteristics compared with other forms of cell death. Ferroptosis contributes to AD pathogenesis through multiple mechanisms and is closely associated with disease onset and progression. Iron overload can affect early amyloid precursor protein processing, accelerate Aβ production and plaque deposition, reduce Tau protein solubility, and promote Tau hyperphosphorylation and aggregation into NFTs. Therapeutic strategies targeting ferroptosis—such as iron chelation with deferoxamine to reduce labile iron levels and inhibit Fenton reaction-driven oxidative damage; supplementation with antioxidants such as α-tocopherol or α-lipoic acid to neutralize reactive oxygen species (ROS) and scavenge lipid radicals; and administration of selenium or activators of the Nrf2-SLC7A11-GPX4 axis and the SIRT1/Nrf2 signaling pathway to restore glutathione-GPX4 function—can effectively block lipid peroxidation and suppress iron-dependent cell death. By modulating iron metabolism, enhancing antioxidant defenses, and inhibiting lipid peroxidation, these approaches hold promise for mitigating ferroptosis-related neuronal injury. These interventions collectively aim to modulate iron metabolism, strengthen antioxidant defenses, and suppress lipid peroxidation, thereby mitigating neuronal injury and delaying cognitive deterioration. Ferroptosis represents a pivotal intersection of iron metabolism, oxidative stress, and neurodegeneration in AD. Exploring ferroptotic mechanisms not only deepens our understanding of AD pathophysiology but also opens new avenues for therapeutic intervention. This review aims to comprehensively summarize the molecular basis of ferroptosis, elucidate its pathological roles in AD, and propose ferroptosis-centered therapeutic strategies, thereby providing a theoretical framework for future research and drug development in AD.

Parkinson’s disease (PD), the second most common neurodegenerative disorder worldwide, presents significant heterogeneity in clinical manifestations, genetic background, and response to interventions. While conventional exercise therapies demonstrate benefits in alleviating motor and non-motor symptoms through mechanisms such as modulating α-synuclein aggregation, enhancing mitophagy, and reducing neuroinflammation, their efficacy varies considerably among individuals. This variability may stem from endogenous factors such as genetic background, clinical phenotypes, stages of pathological progression, as well as exogenous factors like the type, intensity, and frequency of movement. Thus, this review first discusses the necessity of precise exercise interventions for PD patients, focusing on the epidemiological burden, heterogeneity in disease mechanisms, and differences in intervention response (Why). Next, we systematically explain how to develop precise exercise intervention strategies by stratifying interventions based on genetic background, clinical phenotype, and disease stage, combined with technological aids (How). Genetically, mutations in genes such as GBA1, PRKN, PINK1, and SNCA dictate distinct molecular pathologies—including lysosomal dysfunction, impaired mitophagy, and α-synuclein aggregation—which necessitate tailored exercise regimens. For instance, patients with PRKN/PINK1 mutations may benefit from moderate-intensity endurance training to support mitochondrial biogenesis without exacerbating oxidative stress, whereas carriers of GBA1 mutations might require exercises focusing on enhancing lysosomal function and managing oxidative damage. Clinically, patients are stratified into tremor-dominant (TD) and postural instability/gait difficulty (PIGD) subtypes, which demand divergent exercise priorities: coordinative, rhythm-based activities like dance or Tai Chi for TD-PD to engage cerebellar circuits, versus targeted balance and strength training, potentially aided by virtual reality, for PIGD-PD to mitigate axial symptoms and fall risk. Furthermore, intervention strategies must evolve with disease progression: high-intensity exercise is prioritized in early stages to leverage neuroplasticity and potential disease modification, while mid- and late-stage management focuses on functional maintenance, fall prevention, and compensatory strategies, respectively. Critical to implementing this framework is the adoption of digital biomarkers via wearable technology (e.g., inertial sensors, smartwatches), which enables continuous, objective monitoring of gait, tremor, and physiological responses. This facilitates a closed-loop feedback system, allowing for the remote adjustment of exercise parameters (intensity, frequency, duration) in real-time, thus optimizing efficacy and ensuring safety. Finally, we detail how to configure exercise parameters through personalized adaptation (What), including exercise type, intensity, frequency and dose. Higher volumes of physical activity are associated with reduced PD risk and slower progression, though optimal thresholds remain incompletely defined. Aerobic exercise improves cardiovascular fitness and may aid clearance of pathogenic proteins; resistance training counters sarcopenia and bradykinesia; balance training reduces falls; and mind-body exercises (e.g., Tai Chi) integrate motor and cognitive components. Multimodal regimens are often most beneficial. High-intensity aerobic exercise appears particularly effective in early PD, enhancing neural connectivity and mitigating disease progression in randomized trials. Most evidence supports supervised sessions occurring 3-5 times per week, lasting 30-60 min, adapted to individual tolerance and disease stage. In conclusion, this narrative review outlines a comprehensive precision medicine framework for exercise intervention in PD, moving beyond symptomatic management towards targeting underlying pathophysiology. By stratifying patients based on genetic, phenotypic, and staging characteristics, and by leveraging digital technology for dynamic personalization, exercise therapy can be transformed into a more potent, individualized, and disease-modifying strategy. Future research must validate these biomarker-driven approaches in large-scale trials and establish definitive guidelines for translating precision exercise into clinical practice.

Microorganisms, as one of the Earth"s most abundant genetic resources, demonstrate tremendous application potential in fields such as medicine, energy, and environmental protection. However, natural microorganisms often suffer from poor stability and low catalytic efficiency. The emergence of microorganism-nanomaterial hybrid systems offers novel strategies to overcome these limitations. These systems integrate nanomaterials with microorganisms or their components (e.g., cell membranes, metabolites, or biomacromolecules) through methods such as biomineralization, electrostatic assembly, surface modification, and genetic engineering. This enables programmable design from the nanoscale to the macroscale, demonstrating broad application prospects and attracting extensive research interest. First, microbial-nanomaterial hybrid systems are classified based on the types of nanomaterials (organic, inorganic, organic-inorganic) and microorganisms (bacteria, fungi, viruses, algae, probiotics). Both types of systems leverage the unique catalytic selectivity of microorganisms and the diverse physicochemical properties of nanomaterials to achieve multidimensional synergy. Their synergistic mechanisms involve both the biochemical processes of microorganisms and the surface/interface reactions of nanomaterials, representing a multidisciplinary achievement spanning microbial interface engineering, biomimetic catalysis, controllable nanomaterial fabrication, and interfacial transport and reaction processes. Next, the application progress in biomedical fields (such as anti-infection, intestinal diseases, and cancer therapy) and energy conversion (e.g., light-driven hybrid systems for proton reduction to hydrogen, CO₂ reduction and conversion, and nitrogen fixation) is elaborated in detail, highlighting their significant advantages in functional integration and synergistic performance. Microorganism–nanomaterial hybrid systems combine the specific recognition and precise metabolic capabilities of microorganisms with the catalytic, drug-delivery, and optoelectronic functions of nanomaterials, enabling the construction of various multifunctional synergistic platforms for catalysis, diagnosis, and therapy. These advances have greatly promoted development in nanomedicine, energy, and environmental applications. In medical contexts, such systems utilize the natural chemotaxis of microorganisms for precise targeting, achieve controlled drug release through environmentally responsive delivery and metabolic regulation, and enhance therapeutic efficacy via combined chemical-biological treatments and immune modulation. Improved biosafety can be achieved through attenuated microbial designs and nanomaterial coatings, offering diverse strategies for the precise treatment of various diseases. In the energy sector, the excellent light-harvesting properties of semiconductor materials and the precise catalytic capabilities of biological systems have been integrated to successfully construct light-driven biocatalytic systems, significantly improving light utilization efficiency. Finally, this review discusses the key challenges facing the practical application of these systems. Nanomaterials may exert toxic effects on microorganisms, impairing their activity and raising environmental safety concerns. The potential release of engineered nanomaterials into ecosystems necessitates careful risk assessment and long-term monitoring. In real-world environments, microbial functions are easily compromised, nanostructures are prone to damage, and reactive oxygen species (ROS) tend to accumulate, resulting in insufficient system stability. Stringent culture conditions, costly raw materials, and significant batch-to-batch variability hinder large-scale production and commercialization. The synergistic mechanisms between microorganisms and nanomaterials are not yet fully understood, particularly regarding molecular-level interactions and long-term compatibility. In medical applications, off-target risks persist due to unpredictable microbial colonization and immune responses, while environmental applications lack sufficient selective recognition capabilities, indicating a need for improved targeting and specificity. Furthermore, interdisciplinary barriers between biology, materials science, and engineering complicate collaborative innovation, and the absence of well-established standards for evaluation, regulation, and scalability also constrains further development. Future efforts should focus on enhancing biocompatibility, optimizing fabrication processes, and establishing comprehensive safety and performance standards to accelerate the transition of these promising systems from laboratory research to real-world applications.

Nucleic acid aptamers represent a class of single-stranded oligonucleotides capable of high-affinity and specific binding to diverse targets, including proteins, small molecules, cells, and metal ions. Their advantages over antibodies—such as simpler synthesis, lower immunogenicity, superior stability, and easier modification—have positioned them as powerful tools in therapeutics, diagnostics, and biosensing. This review systematically surveys the integral role of bioinformatics and artificial intelligence (AI) in modern aptamer development, spanning from in silico selection and structural prediction to the generative design of novel aptamer sequences. The application of high-throughput SELEX (HT-SELEX) has greatly accelerated the discovery of aptamers, but also introduced computational challenges in processing large-scale sequencing data. Bioinformatics pipelines now routinely include tools like AptaPLEX and AptaSuite for preprocessing raw reads, including demultiplexing, adapter trimming, and quality filtering. Subsequent analytical steps involve clustering-based tools (e.g., FASTAptamer, AptaCLUSTER) to identify enriched sequences, and motif discovery algorithms (such as AptaTRACE and MPBind) that uncover conserved sequence-structure patterns associated with binding functionality. These approaches allow researchers to move beyond manual curation and extract meaningful candidates from complex selection rounds. Accurate prediction of secondary and tertiary structures is essential for understanding aptamer function and interaction mechanisms. Conventional tools, including RNAfold and Mfold, employ thermodynamics-based models to predict RNA folding, yet often struggle with pseudoknots and non-canonical pairs. Recent advances in deep learning—exemplified by SPOT-RNA, E2Efold, and UFold—have significantly improved prediction accuracy by leveraging neural networks trained on large structural datasets. For tertiary structure, methods range from fragment assembly (Rosetta FARFAR2) and homology modeling (RNAComposer) to deep learning-aided approaches such as AlphaFold-RNA and RoseTTAFoldNA. While these tools offer new insights, predicting structures for short, flexible aptamers remains non-trivial. Predicting aptamer–target interactions draws on both physics-based and data-driven approaches. Molecular docking programs—AutoDock Vina, ZDOCK, and MDockPP—provide initial binding poses, which can be refined using molecular dynamics simulations (with GROMACS, AMBER, or NAMD) and free energy perturbation techniques to estimate binding affinity. Complementarily, machine learning models are increasingly employed to predict interactions from sequence and structural features. Early efforts used hand-engineered features with classifiers like SVM and random forest, while contemporary deep learning models (AptaNet, AptaBERT, PAIR) utilize pre-trained language models to capture intricate sequence-binding relationships with superior generalization. Perhaps the most transformative development is the use of generative AI for de novo aptamer design. Conditional variational autoencoders (e.g., RaptGen), generative adversarial networks (e.g., AptaDesigner), and diffusion models (e.g., AptaDiff) can generate novel aptamer sequences conditioned on target properties or desired binding affinities. Reinforcement learning and evolutionary algorithms, including Monte Carlo tree search (Apta-MCTS) and NSGA-II, support multi-objective optimization toward high specificity, stability, and low immunogenicity. These approaches mark a paradigm shift from selective discovery to intentional design, greatly expanding the functional sequence space. Aptamers designed via these computational strategies are increasingly applied in biomedical and environmental fields, including as targeted therapeutics, diagnostic biosensors, and agents in food safety monitoring. Nonetheless, key challenges persist: data scarcity and heterogeneity, model interpretability, and experimental validation bottlenecks. Future progress will depend on standardized data sharing, improved explainable AI, and the integration of computational design with high-throughput experimental screening—ultimately enabling robust, clinically viable aptamer technologies.

Irisin, a myokine discovered in recent years, has been widely confirmed to exert cardioprotective effects. This review comprehensively elaborates on the molecular mechanisms of Irisin in diabetic cardiomyocytes and its close associations with pathophysiological processes such as disordered glycolipid metabolism, oxidative stress, and autophagy. In terms of regulating glycolipid metabolism, Irisin significantly improves energy metabolism in cardiomyocytes by activating the AMPK signaling pathway, thereby reversing diabetes-induced metabolic abnormalities. It promotes the browning of white adipose tissue (WAT), a process in which subcutaneous fat demonstrates a greater propensity to brown compared to visceral fat, thereby enhancing energy expenditure and exerting anti-inflammatory effects. These browned adipocytes secrete bioactive substances such as FGF and adiponectin, which further contribute to metabolic balance. Meanwhile, Irisin reduces the glucolipotoxic burden on pancreatic β-cells: by modulating signaling pathways including PI3K/AKT and AMPK, it not only inhibits β-cell apoptosis but also improves their function and morphology. It enhances insulin secretion by regulating key proteins including Glut2, Glk, and Pdx1 through the AMPK pathway. Additionally, Irisin accelerates the oxidation of free fatty acids (FFA) via activation of pathways such as PPARα, ameliorates insulin resistance, and thus optimizes the metabolic environment of cardiomyocytes. In the context of cellular stress regulation, Irisin exhibits potent antioxidant properties. It not only directly counteracts the accumulation of reactive oxygen species (ROS) to alleviate oxidative damage but also inhibits ferroptosis by upregulating the MITOL/MARCH5 signaling axis, thereby helping to maintain mitochondrial homeostasis. Regarding endoplasmic reticulum stress (ERS), Irisin downregulates key proteins including GRP78 and PERK, thus mitigating ERS-induced cardiomyocyte apoptosis and fibrosis—a protective mechanism that has also been validated in other diseases such as pancreatitis and osteoporosis. In maintaining the balance between autophagy and cell death, Irisin sustains cellular homeostasis by coordinating both mitochondrial-targeted autophagy and non-selective autophagy. It promotes FUNDC1-mediated mitophagy to support mitochondrial turnover and ensure proper organelle function. At the same time, it suppresses excessive autophagy-induced cell damage through pathways such as PI3K/AKT/mTOR. In terms of apoptosis regulation, Irisin downregulates pro-inflammatory factors (e.g., TNF-α, IL-6) and apoptosis-related proteins such as Caspase-3, while upregulating the anti-apoptotic protein Bcl-2. It inhibits cardiomyocyte apoptosis through multiple signaling pathways, including AMPK/mTOR and miR-19b/PTEN. In summary, Irisin plays a crucial protective role in improving metabolic disorders, reducing cellular stress damage, and regulating cell death in diabetic cardiomyopathy (DCM) through multi-target and multi-pathway synergistic mechanisms. Its diverse actions provide an important theoretical basis and potential therapeutic targets for the clinical prevention and treatment of DCM. However, further research is needed to clarify its systemic effects, the safety of clinical interventions, and optimal treatment strategies to fully realize its therapeutic potential.

Objective This study aims to develop a microwave-induced thermoacoustic and ultrasound dual-modality microscopy system that integrates the advantages of both imaging techniques to investigate the dielectric properties of biological tissues at a microscopic level.Methods This paper first discusses a method to enhance system resolution by combining short-pulse microwave excitation with high-frequency point-focused ultrasonic transducer detection. A three-dimensional microwave-induced thermoacoustic microscopic imaging system was constructed based on this approach and further developed into a dual-modality system capable of both thermoacoustic and ultrasonic imaging. The image reconstruction and dual-modality image fusion strategies are also described. Subsequently, experiments were conducted in the following sequence: imaging of copper wires to evaluate the system"s spatial resolution along the X/Y/Z axes; imaging of tubes containing 3% and 6% saline solutions and tubes filled with coupling agent/vegetable oil to demonstrate the complementary information provided by the two modalities; imaging of brain tissue and bone-cartilage samples to assess the applicability of the technology; and osteoporosis detection to validate the disease diagnostic capability of the dual-modality system. The microwave-induced thermoacoustic and ultrasound microscopic images of these samples were verified against corresponding photographs or micro-CT images.Results The thermoacoustic and ultrasonic images of the copper wire closely matched the physical photograph. The three-dimensional resolutions of the microwave-induced thermoacoustic and ultrasound imaging systems, as estimated from the copper wire experiment, were 178×178×88 μm³ and 177×177×42 μm³, respectively. These measured values align well with theoretical predictions. The dual-modality imaging system successfully combines dielectric property differences captured by thermoacoustic imaging and acoustic impedance variations captured by ultrasound imaging, thereby providing both functional and structural information of the samples. Specifically, the system distinguished between tubes containing saline solutions of different concentrations and those containing vegetable oil, demonstrating strong spatial consistency with physical photographs. The thermoacoustic image contrast among saline solutions corresponded to theoretical dielectric properties, while the ultrasonic contrast between saline and oil reflected their difference in acoustic impedance. The system identified multiple brain tissue structures, including the cortex, hippocampus, superior colliculus, corpus callosum, cingulate cortex, and striatum. The bimodal imaging approach exhibited superior performance, visualizing tissue structures with greater clarity and detail than either modality alone. The brain tissue images were consistent with physical photographs, tissue dielectric properties, and publicly available anatomical atlases. The bimodal system clearly delineated cartilage and epiphyseal lines via thermoacoustic imaging, while ultrasonic imaging revealed bone structures. Thermoacoustic imaging alone differentiated bone sections between normal and osteoporotic groups; however, incorporating prior skeletal contour information from ultrasound significantly enhanced discriminatory power, resulting in intergroup differences with higher statistical significance. The imaging results of bone samples corresponded well with physical photographs, micro-CT images, and theoretical analyses of dielectric properties for cartilage, normal bone, and osteoporotic bone.Conclusion The microwave-induced thermoacoustic and ultrasound dual-modality microscopy system developed in this study demonstrates potential for microscopic detection of complex biological tissues based on dielectric properties. It is expected to provide a new imaging tool for functional assessment of brain tissue and the skeletal system, as well as for studies on disease pathogenesis.

Driven by the construction of "New Medical Sciences" and the educational digitalization strategy, there is an increasingly urgent demand in medical education for compound talents who possess a solid professional foundation, scientific research literacy, and clinical innovation capabilities. To address the problems existing in traditional physiology courses—including insufficient training of high-order thinking, delayed scientific research initiation, and a single evaluation mechanism—this study, with the concept of outcome-based education (OBE) as the guide and supported by constructivist and inquiry-based learning theories, has constructed and implemented a new "Teaching-Learning-Research Integration" blended online-offline curriculum model for physiology. The curriculum promotes reforms systematically from four dimensions. First, in the online dimension, it upgrades resources such as micro-courses and virtual simulation experiments, and optimizes self-directed learning paths. Second, in the offline dimension, it reconstructs flipped classrooms to strengthen the discussion of scientific research cases and interactive inquiry. Third, it expands in-depth scientific research guidance and builds a stepped scientific research training system through SRIP projects and discipline competitions. Fourth, it reforms the multi-dimensional evaluation mechanism by integrating process-oriented assessment and scientific research literacy evaluation. The practical results show that students’ mastery of basic physiology knowledge has been significantly improved; the effectiveness of cultivating their scientific research literacy and professional literacy, as well as their overall course satisfaction, have all been enhanced. Meanwhile, the teaching and research capabilities of the teacher team have been synchronously strengthened, achieving the goal of “mutual promotion between teaching and research”. This study confirms the effectiveness and promotion value of the in-depth integration of “Teaching-Learning-Research” in physiology courses. It provides a replicable and transferable model reference for the reform of basic medical courses under the background of “New Medical Sciences” and holds important practical significance for systematically improving the scientific research literacy and innovation capabilities of medical talents.

Objective This study aimed to comprehensively investigate the potential protective effects and underlying mechanisms of taurine against dihydrotestosterone (DHT)-induced androgenetic alopecia (AGA) in male C57BL/6 mice, with a focus on hair follicle cycle modulation, cellular proliferation/apoptosis, and key related signaling pathways.Methods Six-week-old female C57BL/6 mice were initially used to assess the hair growth-promoting potential of taurine. After acclimatization, they were randomly assigned to three groups (n=8): control (regular drinking water), taurine (drinking water containing 1% taurine), and minoxidil (topical 2% minoxidil, positive control). For the AGA study, male C57BL/6 mice were randomly divided into five groups (n=8): control (physiological saline), DHT (model group, 1 mg/d DHT), DHT+low-dose taurine (1 mg/d DHT+2 mg/d taurine), DHT+high-dose taurine (1 mg/d DHT+10 mg/d taurine), and DHT+minoxidil (positive control, 1 mg/d DHT+topical 2% minoxidil). One day before treatment initiation, dorsal hair was shaved with scissors, and residual hair was removed using a depilatory cream. DHT and taurine were administered via daily intraperitoneal injection. Hair regrowth was assessed by photographing the depilated area at regular intervals and quantified using a four-point grading system (0-3). Dorsal skin samples were collected on day 14 for histological analysis (H&E staining), immunofluorescence staining (Ki67 for proliferation, TUNEL for apoptosis), ELISA (DHT quantification), RT-qPCR, and Western blot analysis to evaluate the expression of key genes and proteins (androgen receptor (AR), transforming growth factor (TGF)-β1, TGF-β2, Dickkopf-1 (DKK1)).Results In female mice, taurine supplementation significantly accelerated hair growth, with effects comparable to minoxidil. This was evidenced by an earlier transition from pink (telogen) to black (anagen) skin and increased hair growth scores. Histological analysis showed that taurine increased hair follicle count and dermal thickness. Immunofluorescence confirmed enhanced keratinocyte proliferation in the hair matrix. In the DHT-induced AGA model, DHT significantly extended the telogen phase, inhibited hair growth, increased skin DHT content, and induced hair follicle miniaturization. Taurine treatment, particularly at the high dose, effectively counteracted these effects: it promoted the telogen-to-anagen transition and improved hair growth scores. Histomorphometric analysis showed that taurine significantly restored DHT-induced reductions in dermal thickness, hair follicle count, hair bulb depth, and follicle size. Taurine treatment also reduced apoptosis and promoted the proliferation of hair follicle cells, as demonstrated by Ki67 and TUNEL assays. Crucially, RT-qPCR and Western blot analyses revealed that DHT significantly up-regulated the expression of AR, TGF-β1, TGF-β2, and DKK1 at both mRNA and protein levels in dorsal skin. Taurine administration markedly down-regulated the expression of these pathogenic factors, bringing them closer to the levels observed in the control group.Conclusion Taurine demonstrates significant efficacy in alleviating DHT-induced AGA in male C57BL/6 mice. Its protective effects are mediated through multi-faceted mechanisms. (1) Promoting hair follicle cycle progression: it accelerates the transition from telogen to anagen, counteracting DHT-induced prolongation of the telogen phase. (2) Modulating cellular dynamics: it stimulates the proliferation of hair matrix keratinocytes and reduces DHT-induced apoptosis within hair follicle cells. (3) Suppressing androgen-driven pathogenic pathways: it downregulates the expression of critical molecules in the AGA pathway, including AR, the cytokines TGF-β1 and TGF-β2, and the Wnt pathway inhibitor DKK1. Given its favorable safety profile and multi-targeted action, taurine emerges as a promising novel therapeutic candidate or adjunct for treating AGA. Further investigation into its clinical potential and precise molecular mechanisms is warranted. This study provides a robust preclinical foundation for considering taurine supplementation or topical application in hair loss management strategies.

Mitochondria are the most crucial energy-generating organelles in eukaryotic cells and serve as signaling hubs that orchestrate metabolism, redox balance, cell-fate decision and multiple forms of cell death. Mitochondria possess their own DNA (mtDNA), which is independent of the nuclear genome, yet encodes only 13 polypeptides, 22 tRNAs, and 2 rRNAs. The remaining >1 150 mitochondrial proteins are encoded by nuclear genes (nDNA), and the two genomes cooperate to preserve cellular homeostasis and proper function. Mitochondrial proteins are localized to the outer mitochondrial membrane (OMM), intermembrane space (IMS), inner mitochondrial membrane (IMM) or matrix, participating in oxidative phosphorylation (OXPHOS), the tricarboxylic acid cycle (TCA), fission-fusion dynamics, and other processes indispensable for mitochondrial integrity. Mitochondrial quality control (MQC) is exerted largely by mitochondrial proteases, which selectively modulate protein activity and degrade misfolded or superfluous proteins. Among them, a group of mitochondrial AAA+ proteases (ATPases associated with diverse cellular activities) couple ATP binding and hydrolysis to protein unfolding and proteolysis, thereby regulating fusion protein maturation, respiratory-chain assembly, and mtDNA replication/transcription. Mutations or aberrant expression of these mitochondrial AAA+ proteases cripple mitochondrial architecture and function, precipitating a spectrum of severe neurological disorders. This review summarizes current knowledge on three paradigmatic mitochondrial AAA+ proteases, LONP1, YME1L1, and AFG3L2. We highlight their conserved Walker A/B motifs in the ATPase domain and hexameric architecture, yet emphasize divergent sub-mitochondrial topologies: LONP1 is soluble in the matrix, whereas YME1L1 and AFG3L2 are embedded in the IMM with catalytic domains facing IMS and matrix, respectively. These positional differences translate into distinct substrates and proteolytic strategies, enabling a division of labor and mutual complementation that cooperatively safeguards mitochondrial proteostasis. Pathogenic mutations linked to common and rare neurological disorders are mapped predominantly to the ATPase and the hydrolase/peptidase domains. Substitutions of the amino acid within these core domains can directly abolish ATP hydrolysis, substrate engagement or peptide cleavage, thereby crippling local MQC networks. Additional variants may disturb transcriptional, translational or post-translational regulation, altering protease stoichiometry and impairing compartmental balance. The subsequent cascade, mtDNA instability, respiratory-chain dysfunction, and aberrant mitochondrial dynamics, propagates stress signals that culminate in neuronal dysfunction and/or neurodegeneration. The mutational and clinical heterogeneity observed across cell types, developmental stages, and genetic backgrounds underscores the context-dependent fine-tuning of these AAA+ proteases. Deciphering how disease-associated variants rewire domain structure, catalytic cycle, and network-level crosstalk will therefore illuminate pathophysiologic mechanisms and guide precision therapeutic strategies.

In recent years, immunotherapy has become an excellent option for cancer patients, but most patients still face problems such as low response or drug resistance. Therefore, researchers conducted extensive studies on the reasons for the poor efficacy of immunotherapy. Eventually, it was found that the regulatory effect of abnormal expression of oncogenes and tumor suppressor genes on the tumor immune microenvironment is one of the important factors leading to the failure of immunotherapy to achieve the expected efficacy. It is well known that cancer is a kind of disease caused by the interaction between environmental and genetic factors, and the occurrence of cancer is mainly related to genetic alteration. Physiologically, the balance between oncogenes and tumor suppressor genes is crucial for DNA replication and proliferation regulation. However, under certain conditions, such as viral infection, chemical carcinogens or radiation, these genes may be mutated and eventually induce cancer. In addition, the combination of different gene mutations can also lead to significant differences among patients. For example, certain gene mutations are associated with the metastasis of cancer cells, while some are associated with the resistance of cancer cells to the attack of immune cells. Therefore, exploring the effects of different genetic alterations on the tumor microenvironment can help us better solve the problems in the process of clinical treatment and provide a theoretical basis for designing gene-targeted and personalized therapies. This review mainly summarizes the effects of common oncogenes and tumor suppressor gene mutations on immunosuppressive cells, anti-tumor immune effector cells and tumor-associated fibroblasts in the tumor microenvironment. Firstly, when the oncogene KRAS, cMyc and EGFR are abnormally activated, cancer cell will secrete various cytokines and chemokines, thereby recruiting various immunosuppressive cells to the TME and causing exhaustion of CD8⁺ T and NK cells. It can also reprogram CAFs and eventually promote the development of cancer. Furthermore, similar phenomena occur after the inactivation of tumor suppressor genes. For example, cancer cells with inactivated PTEN genes will secrete large amounts of IL-33 and LOX to recruit macrophages and induce TAMs. Cancer cells can secrete a variety of microRNAs into the tumor microenvironment after p53 dysregulation. These mircoRNAs can reprogram CAFs and lead to epithelial-mesenchymal transition. Finally, we summarize the reversing effects of therapeutic interventions targeting mutant oncogenes or tumor suppressor genes (such as KRAS inhibitors, overexpression of p53 by mRNA, PI3Kβ inhibitors) on the immunosuppressive tumor microenvironment. Some of the results of their synergistic effects in combination with immunotherapy are also listed. Compared with monotherapy, the combination of either KRAS inhibitor or p53 mRNA nanomedicine with αPD-1 therapy resulted in more durable and potent anti-tumor effects. In summary, this review elucidates the regulatory and remodeling effects of genetic alterations in tumor cells on the tumor immune microenvironment, and analyzes the great potential of gene alteration intervention combined with immunotherapy. We hope it can provide theoretical basis and development strategy for precise cancer immunotherapy.

Neurodegenerative diseases (NDs) are a group of disorders characterized by the progressive loss of neuronal structure and function, leading to clinical manifestations such as cognitive decline, motor dysfunction, and neuropsychiatric abnormalities. NDs encompass a range of conditions, including Alzheimer"s disease (AD), Parkinson"s disease (PD), and amyotrophic lateral sclerosis (ALS), etc. With the intensifying trends of global population growth and aging, the incidence of NDs continues to rise, yet no curative treatments are currently available. The blood-brain barrier (BBB) plays a crucial role in maintaining central nervous system (CNS) homeostasis by blocking harmful substances in the bloodstream from entering brain tissue. More than 98% of small-molecule drugs and nearly 100% of large-molecule therapeutics fail to cross the BBB and reach brain parenchyma. Ultrasound-targeted microbubble destruction (UTMD) is an emerging interdisciplinary technology integrating materials science and bioengineering, which combines the advantages of microbubble carriers with the physical properties of ultrasound. This innovative approach enables transient and reversible opening of the BBB, and enhancing drug delivery efficiency. Microbubbles (MB) are the core component of the UTMD system, consisting of two fundamental structural elements: a gaseous core and a biocompatible outer shell. The drug-loading capacity of MB has been significantly expanded, evolving from traditional chemotherapeutic agents to encompass nucleic acid drugs, macromolecular antibodies, and even traditional Chinese medicines. Concurrently, their drug-loading strategies have advanced from initial passive physical adsorption to active targeted delivery. UTMD possesses the following 4 biological advantages. (1) UTMD can transiently and reversibly enhance the permeability of cell membranes and blood vessels. The biocompatible shells commonly used in microbubbles can be metabolized by the body, posing no risk of long-term accumulation. (2) UTMD not only significantly improves drug delivery efficiency but also simultaneously serves as an ultrasound contrast agent and therapeutic carrier, achieving the integration of diagnosis and treatment. (3) UTMD technology offers dual advantages of spatial targeting and molecular targeting, allowing for precise drug delivery. (4) UTMD only requires conventional ultrasound equipment, and the raw materials for microbubble preparation are readily available with simple synthesis processes. Whether applied in diagnostics or treatment, the cost remains relatively low. The mechanism by which UTMD opens the BBB is primarily associated with cavitation effect and sonoporation effect. The cavitation effect induces mechanical stretching of both cellular membranes and capillary walls, creating transient, reversible channels that facilitate macromolecular drug passage, to enhance BBB permeability. Meanwhile, the sonoporation effect promotes drug penetration through dual mechanisms: (1) augmenting passive diffusion across biological barriers; (2) potentiating active transport processes. This synergistic action significantly elevates both local drug concentrations and therapeutic efficacy at target sites. The permeability of the BBB is predominantly influenced by both microbubble characteristics and ultrasound parameters. Microbubble characteristics and ultrasound parameters are key factors affecting BBB permeability. By adjusting the composition of microbubbles and optimizing ultrasound parameters, effective BBB opening can be achieved while minimizing tissue damage, to regulate the dosage of drugs delivered to the brain parenchyma. Both preclinical investigations and clinical trials have consistently shown that UTMD holds significant therapeutic promise for NDs. This article outlines the fundamental properties of microbubbles and elucidates the potential mechanisms underlying UTMD mediated BBB opening. Furthermore, it systematically reviews recent advances in UTMD technology for the treatment of treating various NDs, aiming to provide a theoretical foundation and future directions for developing novel therapeutic strategies and drugs for NDs.

Objective In the clinical diagnosis and grading of brain glioma from histopathological slides, whole-slide cell nucleus density estimation is a critical task. This metric is a key biomarker directly correlated with tumor malignancy, proliferative activity, and patient prognosis, as defined by the World Health Organization (WHO) classification system. Glioma density estimation typically relies heavily on the performance of underlying nucleus segmentation. However, segmentation accuracy is challenged by substantial heterogeneity in nucleus morphology and significant staining variations both across slides and within individual specimens. This variability often causes standard semantic segmentation models to overfit the training data, leading to considerable errors in density estimation. Such inaccuracies can compromise downstream pathological assessments, particularly the subjective and time-consuming manual selection of regions of interest (ROI) for grading. To address these limitations, this study aims to develop a precise and robust whole-slide nucleus density estimation method that enhances model generalization and mitigates overfitting, thereby providing an objective, automated tool for glioma analysis.Methods We propose a systematic three-stage pipeline. (1) Preprocessing: whole-slide images (WSIs) of glioma undergo comprehensive preprocessing, including automated data cleaning to discard blurry or artifact-contaminated patches, data augmentation through geometric transformations (e.g., rotation, flipping) to increase dataset diversity, and color normalization. The latter, based on RGB channel ratios, remaps the color space of all patches to a standardized target, reducing domain shifts caused by staining inconsistencies and improving model robustness. A rigorous semi-automated ground-truth annotation protocol is also implemented, where initial binarization assists annotators in accurately labeling even faint or blurry nuclei, ensuring high-quality training data. (2) Segmentation: using the preprocessed patches, we construct a U-net-based segmentation model that incorporates the DropBlock regularization module—here termed U-net+DropBlock. Unlike standard Dropout, which removes individual neurons, DropBlock eliminates contiguous, spatially correlated regions within feature maps. This structural regularization disrupts undesirable spatial dependencies, forcing the network to learn a more distributed and robust feature representation, thereby reducing overfitting. (3) Quantitative analysis: for each segmented patch, density is computed as the ratio of the total nucleus area to the total patch area—a more robust approach than simple nucleus counting, as it accounts for variations in nucleus size. Patch-wise density values are then assembled into a whole-slide density heatmap, offering an intuitive, global overview of tumor cellularity.Results The U-net+DropBlock model was evaluated both quantitatively and qualitatively against state-of-the-art nucleus segmentation methods, including standard U-net and Hover-net. Quantitatively, our model achieved an F1 score of 90.1%, outperforming U-net and Hover-net, which both scored 87.6%. Qualitative analysis confirmed that our method effectively balances precision and recall, substantially reducing the over-segmentation artifacts common with U-net and the under-segmentation issues observed with Hover-net. This enhanced segmentation quality directly improved the accuracy and reliability of the proposed density estimation approach.Conclusion The proposed whole-slide nucleus density estimation method provides a powerful tool for improving the precision and efficiency of glioma diagnosis. By enabling automated, rapid, and objective analysis of cellular density, it overcomes key limitations of manual pathological review. The generated heatmaps allow pathologists to rapidly identify high-density “hotspots” critical for accurate grading and prognostic evaluation, supporting a more standardized and reproducible ROI selection process. This work lays a solid foundation for developing advanced AI-assisted diagnostic systems, paving the way for more precise, efficient, and reproducible glioma assessments in clinical practice.

Spores and pollen, as ubiquitous organisms found in nature, possess a remarkable core-shell structure and intricate surface morphology. These tiny particles are notable for their dimensional uniformity, sustainable utilization, environmental friendliness, porosity, amphiphilicity, and strong adhesive properties. In addition, they display excellent biocompatibility and biodegradability, which significantly enhances the stability and targeting of drugs within the body. Spores and pollen can be extracted using methods such as acidic solutions, alkaline solutions, or enzyme treatments to obtain sporopollenin, which is an extremely resilient and chemically inert complex biopolymer. The sporopollenin extracted through this process removes the original bioactive substances, such as cell nuclei, enzymes, and DNA, providing greater drug loading capacity and containing no potential allergens or immunogens, thus further enhancing its drug loading capacity and improving safety in therapeutic applications. Due to these beneficial attributes, spores, pollen and sporopollenin have gained widespread use in a variety of drug delivery systems, such as targeted delivery, sustained drug delivery, toxicity mitigation, flavor masking, vaccine delivery, delivery of labile substances, and other applications. This review introduces the types of natural spores and pollen commonly used in drug delivery systems, including their main components, common effects, and uses in drug delivery systems, and so on. It subsequently summarizes novel optimization methods in their processing, such as physical treatment, surface modification, and chemical modification, which enable higher drug loading efficiency, stability, and targeting, among other benefits. Additionally, this paper reviews the research progress and applications of natural spores, pollen, and sporopollenin in drug delivery systems, while also touching on some innovative research content, such as novel nanomotor microcarriers developed based on pollen. Based on these research findings, we further elaborate on the advantages of spores, pollen, and sporopollenin in drug delivery systems. For example, they have high stability and drug loading capacity, good adhesion, excellent targeting, and are easy to modify functionally. Currently, they show promising prospects in the fields of targeted drug delivery, sustained-release drug delivery, as well as the delivery of drugs that are effective but slightly toxic, and are often used in research on the treatment of diseases such as cancer and inflammation. We have also highlighted the challenges they face in various applications and identified some issues that need to be addressed, including difficulties in large-scale production, the need to improve extraction and purification processes, and the existence of a low but still noteworthy risk of allergies, in order to fully leverage their potential in drug delivery applications. According to current research, although spores, pollen, and sporopollenin face some unresolved issues in clinical drug delivery, they still have great potential overall and are expected to become a new generation of green drug delivery platforms. In the future, further research into their unique physical and chemical properties and structural characteristics will help develop more efficient and stable drug delivery systems to meet diverse treatment needs. We believe that continued exploration of natural spores, pollen, and sporopollenin will drive this emerging field to achieve continuous breakthroughs and progress, ultimately making an important contribution to the cause of human health.

Objective With the continuous evolution of severe acute respiratory syndromes-coronary virus 2 (SARS-CoV-2) Omicron subvariants, particularly the emergence of BA.2.86 and its descendant JN.1, the efficacy of current neutralizing antibodies has faced substantial challenges. The JN.1 variant, noted for its pronounced immune evasion capacity, has rapidly become the globally dominant strain. Elucidating its escape mechanisms is therefore essential to guide the development of next-generation broad-spectrum vaccines and neutralizing antibody therapeutics. This study aimed to investigate the immune evasion mechanisms of JN.1 against broadly neutralizing antibodies, focusing on the effects of key receptor-binding domain (RBD) mutations on antibody binding and neutralization, thereby providing theoretical support for countering ongoing viral evolution.Methods We employed a multidisciplinary approach to systematically assess the binding and neutralizing activities of three broad-spectrum neutralizing antibodies (XGv074, XGv302, and XGv303) against BA.2.86 and JN.1. Binding affinities (K_D values) of antibodies to variant RBDs were determined using bio-layer interferometry (BLI). Cryo-electron microscopy (cryo-EM) was used to resolve the structure of the BA.2.86 Spike trimer in complex with antibody antigen-binding fragments (Fabs), achieving a resolution of 3.47 ? for the BA.2.86 S-trimer bound to XGv302. Molecular dynamics simulations and binding free-energy decomposition were conducted to quantify the contributions of key mutations at the antibody-RBD interface. Additionally, sequence alignment and structural modeling were performed to evaluate the role of conformational flexibility in the antibody heavy-chain complementarity-determining region 3 (HCDR3) in mediating tolerance to mutations.Results Experimental data showed that XGv074, XGv302, and XGv303 retained neutralizing activity against BA.2.86 but exhibited markedly reduced binding to JN.1, with only XGv074 maintaining weak neutralization (IC₅₀=2.3 mg/L). Cryo-EM structures revealed that all three antibodies targeted the RBD tip, overlapping with the ACE2-binding region. The JN.1-specific L455S mutation disrupted the hydrophobic interaction network between XGv302 and the RBD (involving key residues such as Y421 and L455), resulting in complete loss of neutralization. Binding free-energy decomposition further identified L455 and Y421 as energetic hotspots (ΔG<-3 kcal/mol), with the L455S mutation directly impairing antibody binding. XGv074, owing to greater conformational flexibility in its HCDR3 region, partially tolerated the mutation and retained weak binding. Molecular dynamics simulations showed that the L455S mutation not only eliminated the energetic contribution of this residue but also caused a concurrent decrease in binding free energy of neighboring residues, thereby reducing overall interface stability.Conclusion The JN.1 variant escapes broad-spectrum neutralizing antibodies primarily through the L455S mutation in the RBD, which disrupts energetic hotspots and remodels the antibody-binding interface. Antibody conformational flexibility enhances adaptability to such mutations, providing new insights for broad-spectrum antibody design. These findings highlight the critical roles of epitope energy distribution and antibody flexibility in maintaining neutralization breadth, offering essential guidance for the rational design of next-generation vaccines and antibody therapeutics: specifically targeting conserved energetic hotspots while enhancing CDR flexibility to counter immune evasion driven by viral evolution.

Objective N6-methyladenosine (m6A), the most prevalent epigenetic modification in eukaryotic RNA, plays a pivotal role in regulating cellular differentiation and developmental processes, with its dysregulation implicated in diverse pathological conditions. Accurate prediction of m6A sites is critical for elucidating their regulatory mechanisms and informing drug development. However, traditional experimental methods are time-consuming and costly. Although various computational approaches have been proposed, challenges remain in feature learning, predictive accuracy, and generalization. Here, we present m6A-PSRA, a dual-branch residual-network-based predictor that fully exploits RNA sequence information to enhance prediction performance and model generalization.Methods m6A-PSRA adopts a parallel dual-branch network architecture to comprehensively extract RNA sequence features via two independent pathways. The first branch applies one-hot encoding to transform the RNA sequence into a numerical matrix while strictly preserving positional information and sequence continuity. This ensures that the biological context conveyed by nucleotide order is retained. A bidirectional long short-term memory network (BiLSTM) then processes the encoded matrix, capturing both forward and backward dependencies between bases to resolve contextual correlations. The second branch employs a k-mer tokenization strategy (k=3), decomposing the sequence into overlapping 3-mer subsequences to capture local sequence patterns. A pre-trained Doc2vec model maps these subsequences into fixed-dimensional vectors, reducing feature dimensionality while extracting latent global semantic information via context learning. Both branches integrate residual networks (ResNet) and a self-attention mechanism: ResNet mitigates vanishing gradients through skip connections, preserving feature integrity, while self-attention adaptively assigns weights to focus on sequence regions most relevant to methylation prediction. This synergy enhances both feature learning and generalization capability.Results Across 11 tissues from humans, mice, and rats, m6A-PSRA consistently outperformed existing methods in accuracy (ACC) and area under the curve (AUC), achieving >90% ACC and >95% AUC in every tissue tested, indicating strong cross-species and cross-tissue adaptability. Validation on independent datasets—including three human cell lines (MOLM1, HEK293, A549) and a long-sequence dataset (m6A_IND, 1 001 nt)—confirmed stable performance across varied biological contexts and sequence lengths. Ablation studies demonstrated that the dual-branch architecture, residual network, and self-attention mechanism each contribute critically to performance, with their combination reducing interference between pathways. Motif analysis revealed an enrichment of m6A sites in guanine (G) and cytosine (C), consistent with known regulatory patterns, supporting the model"s biological plausibility.Conclusion m6A-PSRA effectively captures RNA sequence features, achieving high prediction accuracy and robust generalization across tissues and species, providing an efficient computational tool for m6A methylation site prediction.

Endometriosis (EM) and adenomyosis (AM) are chronic, estrogen-dependent gynecological disorders that significantly impair the quality of life and reproductive health of millions of women worldwide. Clinically, both conditions are characterized by dysmenorrhea, abnormal uterine bleeding, infertility, and high recurrence rates. Despite decades of research, their pathogenesis remains incompletely understood, and current therapeutic options are limited in both efficacy and long-term safety. Emerging studies have identified glycolytic metabolic reprogramming (GMR)—a shift from mitochondrial oxidative phosphorylation (OXPHOS) to aerobic glycolysis—as a unifying and critical feature in the development and progression of EM and AM. In ectopic lesions, enhanced glycolysis supports cellular proliferation, survival, and adaptation to hypoxic microenvironments. Key glycolytic enzymes, including hexokinase 2 (HK2), phosphofructokinase-1 (PFK1), pyruvate dehydrogenase kinase (PDK), and lactate dehydrogenase A (LDHA), are markedly upregulated, whereas oxidative metabolism is suppressed, reflecting a Warburg-like metabolic phenotype. Notably, single-cell and spatial transcriptomic analyses reveal significant heterogeneity between EM and AM lesions. EM lesions often contain cell clusters co-expressing glycolytic and OXPHOS-related genes, suggesting metabolic flexibility. In contrast, AM tissues exhibit a more uniform, glycolysis-dominant profile, with preferential HK2 expression over HK1—potentially linked to defective repair of the endometrial basal layer. Multiple regulatory layers contribute to this glycolytic shift. Hypoxia-inducible factors (HIFs) act as upstream transcriptional activators in response to oxygen deprivation. Kinase cascades, such as those involving PIM2 and AURKA, enhance glycolytic enzyme activity via phosphorylation. Epigenetic mechanisms—including N6-methyladenosine (m6A) RNA modification and histone H3K18 lactylation—further stabilize glycolytic gene expression and reinforce metabolic reprogramming. These alterations form an integrated regulatory network that sustains high glycolytic flux in ectopic cells. Importantly, GMR profoundly affects the immune microenvironment. Lactate produced by glycolytic stromal cells promotes M2 macrophage polarization and impairs the function of cytotoxic T cells and dendritic cells, leading to immune evasion and chronic inflammation. Meanwhile, immune cells themselves undergo metabolic reprogramming, exhibiting increased dependence on glycolysis and diminished oxidative capacity. This bidirectional metabolic-immune feedback loop facilitates lesion persistence and disease progression. GMR is also closely linked to infertility in EM and AM. In the ovarian microenvironment, glycolytic imbalance leads to lactate accumulation in follicular fluid, negatively affecting oocyte quality and embryo development. In the endometrium, excessive glycolysis disrupts decidualization, angiogenesis, and immune tolerance—processes essential for implantation and pregnancy. Targeting glycolysis offers promising therapeutic potential. Small-molecule inhibitors such as dichloroacetate and meclozine target PDK and HK2, respectively. Natural compounds like cinnamic acid and protoberberine derivatives exhibit both anti-glycolytic and anti-inflammatory effects. Traditional Chinese medicine formulations, including Guizhi Fuling Wan, have shown efficacy in modulating metabolism, vascular remodeling, and fibrosis. Combination therapies, such as atorvastatin with resveratrol, may provide synergistic benefits by inhibiting both glucose uptake and lactate export. In conclusion, glycolytic metabolic reprogramming is a central mechanism linking inflammation, immune dysfunction, lesion progression, and reproductive failure in endometriotic diseases. Future research should focus on identifying metabolic subtypes, developing combined metabolic-immune therapies, and evaluating the safety of these treatments in reproductive-age women. These insights may pave the way toward personalized, mechanism-driven interventions for EM and AM.

Neurodegenerative diseases (NDs) are a wide variety of disorders characterized by the progressive and irreversible loss of neuronal structure and functions leading to cognitive impairments. The common types of NDs include Alzheimer"s disease, amyotrophic lateral sclerosis, Huntington"s disease, and Parkinson"s disease. The sharing pathological hallmarks of these diseases are the aberrant aggregation and amyloid deposition. However, the underlying molecular mechanisms of protein misfolding and aberrant aggregation remain elusive. Amyloid protein is prone to aggregate from its native disordered monomeric state into well-ordered amyloid fibril state via nucleation-dependent polymerization mechanism, in which follows sigmoidal growth kinetics with three steps: lag phase, growth phase, and plateau phase. The formation and subsequent distribution of these pathological amyloid fibrils are closely related to the onset and progression of NDs. Additionally, the aberrant aggregation of these disease-associated proteins proceeds via liquid-liquid phase separation (LLPS) and liquid-to-solid phase transition (LSPT) leading to amyloid fibril formation in the condensed phase. The phase transition from liquid-like droplets or dynamic condensates to solid-like hydrogel or amyloids is intimately linked to the pathogenesis of several NDs. In this review, we discuss two typical pathways of amyloid fibrils formation. One route involves aggregation in the bulk solution environment, proceeding via nucleation and elongation steps to form amyloid fibrils. In this scenario, protein aggregation initiates with the nucleation step to form oligomeric nuclei. Then the nuclei serve as templates for the subsequent elongation step ultimately leading to the formation of amyloid fibrils. When sufficient fibrils have formed during self-assembly, the secondary nucleation is triggered to generate new species of oligomers and fibrillar aggregates. The other route of fibril formation occurs in the condensed phase through LLPS and LSPT to form amyloid aggregates and deposits. The occurrence of a phase separation leads to the liquid-like droplets formation during the early stage of aggregation. Over time, these dynamic biomolecular condensates gradually solidify and ultimately evolve into a hydrogel state enriched by amyloid aggregates through a phase transition process. Evidence indicates that pathological phase transitions are early events in the pathogenesis of several NDs. It should be noted that these two routes are not independent or mutually exclusive. They are interconnected and function cooperatively during aberrant aggregation. The pathological progression of NDs is closely related to the dominant aggregation pathway involved in aberrant aggregation. Moreover, the molecular mechanisms underlying the formation of pathogenic amyloid deposits are intricately linked to the structural and functional characteristics of aggregates. These aggregates may not only directly participate in fibrillization, but also indirectly promote the development of NDs by affecting the normal physiological cellular functions. Therefore, in-depth research on the structural and functional properties of both intermediates and fibrils is of great significance for understanding the molecular mechanisms of protein misfolding and aberrant aggregation. Overall, this paper reviews the amyloid deposition and pathological phase transitions in NDs. By delving into the molecular mechanisms of amyloid fibrillization, the aim is to better understand the pathogenesis of NDs, and to provide valuable insights into the development of therapeutic strategies targeting amyloid aggregation and aberrant phase transition.

Schizophrenia is a severe psychiatric disorder characterized by positive symptoms (e.g., hallucinations), negative symptoms (e.g., social withdrawal), and cognitive impairments. Among these, cognitive impairment is a core feature that severely compromises patients’ social functioning and long-term prognosis. Antipsychotics, the first-line treatment for schizophrenia, are generally effective in managing positive symptoms. However, their efficacy in alleviating negative symptoms and cognitive deficits remains limited. Moreover, long-term use may lead to metabolic syndrome and extrapyramidal side effects. Consequently, non-pharmacological interventions have garnered increasing attention as alternative or adjunctive strategies for cognitive remediation in schizophrenia. In recent years, techniques grounded in neuroplasticity theory have advanced rapidly. These interventions aim to alleviate cognitive impairments by modulating neural circuits (e.g., enhancing prefrontal-hippocampal connectivity) and synaptic plasticity (e.g., modulating the BDNF/TrkB pathway) from multiple dimensions. Such approaches not only enhance cognitive function but also reduce medication-related adverse effects and improve treatment compliance. This article comprehensively reviews the clinical evidence and recent technological advances in non-pharmacological interventions targeting cognitive impairments in schizophrenia. The interventions discussed include cognitive remediation therapy (CRT), repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), electro-acupuncture (EA), aerobic exercise (AE), and light therapy (LT). CRT, the most extensively studied and evidence-based intervention, uses structured cognitive training tasks to enhance neuroplasticity and has consistently demonstrated efficacy in improving executive function and social cognition. Both rTMS and tDCS are non-invasive brain stimulation techniques that modulate cortical excitability and neural network connectivity. While rTMS has shown promise in improving working memory and attention—particularly in patients with prominent negative symptoms—its clinical efficacy remains inconsistent, likely due to variability in stimulation parameters and patient heterogeneity. In contrast, tDCS has demonstrated encouraging effects on working memory and attention with a relatively rapid onset, although optimal stimulation protocols have yet to be standardized. EA, which combines traditional acupuncture with electrical stimulation, has been shown to improve memory function, possibly through upregulation of brain-derived neurotrophic factor (BDNF) and enhanced cerebral blood flow. It may be especially useful in treatment-resistant cases. AE is a low-cost and widely accessible intervention that promotes hippocampal neuroplasticity and BDNF expression, thereby improving memory and attention. It is recommended as a foundational adjunctive therapy, particularly for patients with chronic schizophrenia. LT, although still experimental, has yielded promising results in animal models by modulating neuroinflammation and enhancing neurogenesis via the BDNF/CREB signaling pathway. However, clinical evidence remains limited, necessitating further large-scale trials to validate its efficacy and safety. In addition to reviewing individual interventions, this article highlights the potential of combination strategies—such as CRT combined with AE or rTMS—to produce synergistic cognitive benefits. Future directions include the development of personalized treatment protocols, early intervention during neurodevelopmental windows (e.g., adolescence), and the integration of biomarkers and neuroimaging to guide therapeutic decisions. This synthesis aims to provide clinicians and researchers with a comprehensive framework for advancing non-pharmacological cognitive rehabilitation in schizophrenia.

Objective This study proposes a fatigue detection method for police extreme training based on electrical impedance imaging technology to prevent muscle damage caused by overstrain during intense physical training.Methods First, based on the mechanism of human anaerobic exercise, lactic acid was identified as a key indicator of muscle fatigue, demonstrating that measuring muscle lactic acid effectively reflects localized fatigue. Second, a numerical simulation model of the human calf was established, and the internal tissue structure of the calf was analyzed to determine the stages of lactic acid diffusion and change. Then, the reconstruction performance of electrical impedance tomography (EIT) in visualizing lactic acid diffusion was compared under three different regularization algorithms, and the most suitable regularization method for subsequent experiments was selected. Finally, a controlled experiment simulating lactate diffusion was conducted to verify the imaging capability of the TK-Noser regularization algorithm in complex imaging fields.Results Simulation results indicate that both the TK-Noser and TV regularization algorithms achieve superior imaging performance, effectively suppressing artifacts in the visualization of lactic acid diffusion inside muscle tissue. The average ICC/RMSE values reached 0.754/0.303 and 0.772/0.320, respectively, while the average SSIM/PSNR values were 0.677/61 dB and 0.488/60 dB, respectively. In the lactate diffusion experiment, the average ICC/SSIM of the EIT reconstruction results based on the TK-Noser regularization algorithm reached 0.701 and 0.572, respectively. Additionally, compared with the TV regularization algorithm, the TK-Noser algorithm better preserved the shape and structural integrity of the imaging target, with an SSIM value 21.2% higher than that of the TV regularization results. This enhancement ensures the stability of the experimental results and significantly improves the capability of electrical impedance imaging technology in monitoring lactate diffusion within complex fields.Conclusion The proposed method offers real-time convenience and non-invasiveness, making it a promising approach for dynamic monitoring of muscle lactate levels in police officers during extreme physical training.