Abstract: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.

Abstract: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, c-Myc 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.

Abstract: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.

Abstract: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 (TCA) cycle, 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 ATPases associated with diverse cellular activities (AAA+ proteases) 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 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.

Abstract: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.

Abstract: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 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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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 using these computational strategies are increasingly used across biomedical and environmental applications, including targeted therapeutics, diagnostic biosensors, and 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.

Abstract: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 upregulated 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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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 Student Research and Innovation Program (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.