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 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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.

Abstract: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.