Abstract:Quantum dots (QDs), nanoscale semiconductor crystals, have emerged as a revolutionary class of nanomaterials with unique optical and electrochemical properties, making them highly promising for applications in disease diagnosis and treatment. Their tunable emission spectra, long-term photostability, high quantum yield, and excellent charge carrier mobility enable precise control over light emission and efficient charge utilization, which are critical for biomedical applications. This article provides a comprehensive review of recent advancements in the use of quantum dots for disease diagnosis and therapy, highlighting their potential and the challenges involved in clinical translation. Quantum dots can be classified based on their elemental composition and structural configuration. For instance, IB-IIIA-VIA group quantum dots and core-shell structured quantum dots are among the most widely studied types. These classifications are essential for understanding their diverse functionalities and applications. In disease diagnosis, quantum dots have demonstrated remarkable potential due to their high brightness, photostability, and ability to provide precise biomarker detection. They are extensively used in bioimaging technologies, enabling high-resolution imaging of cells, tissues, and even individual biomolecules. As fluorescent markers, quantum dots facilitate cell tracking, biosensing, and the detection of diseases such as cancer, bacterial and viral infections, and immune-related disorders. Their ability to provide real-time, in vivo tracking of cellular processes has opened new avenues for early and accurate disease detection. In the realm of disease treatment, quantum dots serve as versatile nanocarriers for targeted drug delivery. Their nanoscale size and surface modifiability allow them to transport therapeutic agents to specific sites, improving drug bioavailability and reducing off-target effects. Additionally, quantum dots have shown promise as photosensitizers in photodynamic therapy (PDT). When exposed to specific wavelengths of light, quantum dots interact with oxygen molecules to generate reactive oxygen species (ROS), which can selectively destroy malignant cells, vascular lesions, and microbial infections. This targeted approach minimizes damage to healthy tissues, making PDT a promising strategy for treating complex diseases. Despite these advancements, the translation of quantum dots from research to clinical application faces significant challenges. Issues such as toxicity, stability, and scalability in industrial production remain major obstacles. The potential toxicity of quantum dots, particularly to vital organs, has raised concerns about their long-term safety. Researchers are actively exploring strategies to mitigate these risks, including surface modification, coating, and encapsulation techniques, which can enhance biocompatibility and reduce toxicity. Furthermore, improving the stability of quantum dots under physiological conditions is crucial for their effective use in biomedical applications. Advances in surface engineering and the development of novel encapsulation methods have shown promise in addressing these stability concerns. Industrial production of quantum dots also presents challenges, particularly in achieving consistent quality and scalability. Recent innovations in synthesis techniques and manufacturing processes are paving the way for large-scale production, which is essential for their widespread adoption in clinical settings. This article provides an in-depth analysis of the latest research progress in quantum dot applications, including drug delivery, bioimaging, biosensing, photodynamic therapy, and pathogen detection. It also discusses the multiple barriers hindering their clinical use and explores potential solutions to overcome these challenges. The review concludes with a forward-looking perspective on the future directions of quantum dot research, emphasizing the need for further studies on toxicity mitigation, stability enhancement, and scalable production. By addressing these critical issues, quantum dots can realize their full potential as transformative tools in disease diagnosis and treatment, ultimately improving patient outcomes and advancing biomedical science.

Abstract:In recent years, with the large-scale use of plastic products, the degree of plastic pollution has increased, becoming a serious global problem. Microplastics and nanoplastics (MNPs), as emerging environmental pollutants, are widely found in organisms and the environment. These plastic particles enter the human body through 3 exposure pathways: breathing, the food chain’s bioaccumulation and transfer, and skin contact, thereby exerting toxic effects. The physical attributes of MNPs, including their shape, size, and surface characteristics, are not static but rather undergo dynamic transformations in response to changing environmental conditions. These changes can significantly influence their behavior and interactions within different ecosystems. When considering MNPs as carriers of chemicals, two primary mechanisms can be distinguished. (1) MNPs have the capacity to adsorb pollutants from their surrounding environment. These pollutants may encompass a wide range of substances, such as heavy metals, organic compounds, and other contaminants that are commonly found in water, soil, or air. (2) MNPs may also carry chemical agents that are artificially introduced during their commercial production process. For example, flame retardants and pigments are often added to plastics to enhance their performance or appearance. These artificially added chemicals can remain associated with MNPs throughout their lifecycle and may contribute to their overall toxicological impact. Cardiovascular diseases (CVDs) are a general term for diseases of the heart, arteries, veins, and capillaries, and are one of the main causes of disability and death. CVDs have higher incidence, mortality, and recurrence rates, and more complications, which reduce the quality of life and happiness of patients, the phenomenon is gradually showing a trend of early onset, therefore early-stage prevention for CVDs is of critical importance. This article reviews the properties of MNPs and their potential threats to the cardiovascular system, aiming to explore how MNPs cause CVDs through certain physiological effects, toxicity mechanisms, and related pathways. Our review primarily focus on elucidating several critical mechanisms through which MNPs exert their adverse effects. Specifically, the review examines how the enhancement of oxidative stress can trigger the expression of pro-inflammatory factors, which in turn leads to the formation of a chronic inflammatory microenvironment within biological systems. Additionally, MNPs possess the capacity to adsorb toxic metals and organic substances from their surroundings. Furthermore, the review summarizes that sewage irrigation and atmospheric deposition are significant factors contributing to the co-pollution of heavy metals with MNPs in environmental settings. The interaction between heavy metals and MNPs has been shown to have detrimental effects on agricultural productivity, as it can inhibit crop growth and simultaneously increase the absorption rate of heavy metals in plants. When these contaminated plants enter the food chain, the accumulated heavy metals can ultimately be ingested by humans. This process poses a potential risk for inducing acute coronary syndrome and other CVDs, thereby underscoring the importance of understanding and mitigating the impact of MNPs on human health. In addition, our review also gives examples of the long-term effects of MNPs on cardiovascular function and the adverse consequences such as arrhythmia and atherosclerosis, the limitations of the current studies of MNPs affecting cardiovascular system health and future directions are also explored.

Abstract:Alzheimer’s disease (AD) is a chronic, progressive, and irreversible neurodegenerative disorder that typically begins with a subtle onset and progresses slowly. Pathologically, it is characterized by two hallmark features: the extracellular accumulation of amyloid β-protein (Aβ), forming senile plaques, and the intracellular hyperphosphorylation of tau protein, resulting in neurofibrillary tangles (NFTs). These pathological changes are accompanied by substantial neuronal and synaptic loss, particularly in critical brain regions such as the cerebral cortex and hippocampus. Clinically, AD presents as a gradual decline in memory, language abilities, and spatial orientation, significantly impairing the quality of life of affected individuals. With the aging population steadily increasing in China, the incidence of AD is rising, making it a major public health concern that requires urgent attention. The growing societal and economic burden of AD underscores the pressing need to identify effective diagnostic biomarkers and develop novel therapeutic strategies. Among the various molecular signaling pathways involved in neurological disorders, the Notch signaling pathway is especially noteworthy due to its evolutionary conservation and regulatory roles in cell proliferation, differentiation, development, and apoptosis. In the central nervous system, Notch signaling is essential for neurodevelopment and synaptic plasticity and has been implicated in several neurodegenerative processes. Although some studies suggest that Notch signaling may influence AD-related pathology, its precise role in AD remains poorly understood. In particular, the interaction between Notch signaling and non-coding RNAs (ncRNAs)—key regulators of gene expression—has received limited attention. NcRNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), are known to exert extensive regulatory functions at both transcriptional and post-transcriptional levels. Dysregulation of these molecules has been widely associated with various diseases, including cancers, cardiovascular conditions, and neurodegenerative disorders. Notably, interactions between ncRNAs and major signaling pathways such as Notch can produce widespread biological effects. While such interactions have been increasingly reported in several disease models, comprehensive studies investigating the regulatory relationship between Notch signaling and ncRNAs in the context of AD remain scarce. Given the capacity of ncRNAs to modulate signaling cascades and form complex regulatory networks, a deeper understanding of their crosstalk with the Notch pathway could provide novel insights into AD pathogenesis and reveal potential targets for diagnosis and treatment. In this study, we investigated the regulatory landscape involving the Notch signaling pathway and associated ncRNAs in AD using bioinformatics approaches. By integrating data from multiple public databases, we systematically identified significantly dysregulated Notch pathway-related genes and their interacting ncRNAs in AD. Based on this analysis, we constructed a lncRNA-miRNA-mRNA regulatory network to elucidate the potential mechanisms linking Notch signaling to ncRNA-mediated gene regulation in AD pathogenesis. Furthermore, we explored the internal relationships and molecular mechanisms within this network and assessed the feasibility and clinical relevance of these molecules as early diagnostic biomarkers and potential therapeutic targets for AD. This study aims to deepen our understanding of the molecular basis of AD and offer novel strategies for its diagnosis and treatment.

Abstract:Clathrin-mediated endocytosis (CME) is a critical process by which cells internalize macromolecular substances and initiate vesicle trafficking, serving as the foundation for many cellular activities. Central to this process are clathrin-coated structures (CCSs), which consist of clathrin-coated pits (CCPs) and clathrin plaques. While clathrin-coated pits are well-established in the study of endocytosis, clathrin plaques represent a more recently discovered but equally important component of this system. These plaques are large, flat, and extended clathrin-coated assemblies found on the cytoplasmic membrane. They are distinct from the more typical clathrin-coated pits in terms of their morphology, larger surface area, and longer lifespan. Recent research has revealed that clathrin plaques play roles that go far beyond endocytosis, contributing to diverse cellular processes such as cellular adhesion, mechanosensing, migration, and pathogen invasion. Unlike traditional clathrin-coated pits, which are transient and dynamic structures involved primarily in the internalization of molecules, clathrin plaques are more stable and extensive, often persisting for extended periods. Their extended lifespan suggests that they serve functions beyond the typical endocytic role, making them integral to various cellular processes. For instance, clathrin plaques are involved in the regulation of intercellular adhesion, allowing cells to better adhere to one another or to the extracellular matrix, which is crucial for tissue formation and maintenance. Furthermore, clathrin plaques act as mechanosensitive hubs, enabling the cell to sense and respond to mechanical stress, a feature that is essential for processes like migration, tissue remodeling, and even cancer progression. Recent discoveries have also highlighted the role of clathrin plaques in cellular signaling. These plaques can serve as scaffolds for signaling molecules, orchestrating the activation of various pathways that govern cellular behavior. For example, the recruitment of actin-binding proteins such as F-actin and vinculin to clathrin plaques can influence cytoskeletal dynamics, helping cells adapt to mechanical changes in their environment. This recruitment also plays a pivotal role in regulating cellular migration, which is crucial for developmental processes. Additionally, clathrin plaques influence receptor-mediated signal transduction by acting as platforms for the assembly of signaling complexes, thereby affecting processes such as growth factor signaling and cellular responses to extracellular stimuli. Despite the growing body of evidence that supports the involvement of clathrin plaques in a wide array of cellular functions, much remains unknown about the precise molecular mechanisms that govern their formation, maintenance, and turnover. For example, the factors that regulate the recruitment of clathrin and other coat proteins to form plaques, as well as the signaling molecules that coordinate plaque dynamics, remain areas of active research. Furthermore, the complex interplay between clathrin plaques and other cellular systems, such as the actin cytoskeleton and integrin-based adhesion complexes, needs further exploration. Studies have shown that clathrin plaques can respond to mechanical forces, with recent findings indicating that they act as mechanosensitive structures that help the cell adapt to changing mechanical environments. This ability underscores the multifunctional nature of clathrin plaques, which, in addition to their role in endocytosis, are involved in cellular processes such as mechanotransduction and adhesion signaling. In summary, clathrin plaques represent a dynamic and versatile component of clathrin-mediated endocytosis. They play an integral role not only in the internalization of macromolecular cargo but also in regulating cellular adhesion, migration, and signal transduction. While much has been learned about their structural and functional properties, significant questions remain regarding the molecular mechanisms that regulate their formation and their broader role in cellular physiology. This review highlights the evolving understanding of clathrin plaques, emphasizing their importance in both endocytosis and a wide range of other cellular functions. Future research is needed to fully elucidate the mechanisms by which clathrin plaques contribute to cellular processes and to better understand their implications for diseases, including cancer and tissue remodeling. Ultimately, clathrin plaques are emerging as crucial hubs that integrate mechanical, biochemical, and signaling inputs, providing new insights into cellular function and the regulation of complex cellular behaviors.

Abstract:In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Abstract:Tumor immunotherapy has emerged as the fourth major therapeutic modality, following surgery, radiotherapy, and chemotherapy. Unlike traditional treatments that primarily target tumor cells directly, immunotherapy harnesses the body’s immune system to recognize and eliminate cancer cells. Over the past decade, various immunotherapeutic strategies have been developed, including immune checkpoint inhibitors (ICIs), chimeric antigen receptor (CAR) T cell therapy, cancer vaccines, and cytokine-based therapies. However, the immunosuppressive tumor microenvironment (TME) poses a significant obstacle to the effectiveness of these treatments. Polyamines—including putrescine, spermidine, and spermine—are polycationic metabolites that often accumulate abnormally in the TME and act as critical immunoregulatory molecules. T cells play a central role in antitumor immunity, yet their function is frequently influenced by immunoregulatory factors within the TME. Elevated polyamine levels in the TME have been implicated in dampening antitumor T cell responses, thereby facilitating tumor immune evasion. Polyamines in the TME originate from both tumor cells and tumor-associated immune cells. Tumor cells often overexpress the oncogene Myc, which drives the upregulation of polyamine biosynthetic enzymes, resulting in excessive intracellular polyamine production. Additionally, M2-polarized tumor-associated macrophages (M2-TAMs) contribute to polyamine accumulation by upregulating arginase-I (Arg-I), an enzyme that catalyzes the conversion of arginine into ornithine—a key precursor in the polyamine biosynthetic pathway. These combined sources lead to sustained polyamine enrichment in the TME, contributing to immune dysfunction and supporting tumor progression. Moreover, polyamines indirectly affect T cell activity by modulating macrophage polarization and directly suppress tumor cell apoptosis, further promoting an immunosuppressive environment. This review highlights the multifaceted roles of polyamines in modulating tumor-infiltrating T cell function, with a particular focus on their influence on CD4+ T cell differentiation, CD8+ T cell cytotoxicity, and immune checkpoint molecule expression. Recent studies suggest that polyamines suppress CD4+ T cell activation and differentiation by modulating the MAPK/ERK signaling pathway. Additionally, polyamines can impair T cell receptor (TCR) signaling and promote immune evasion through the upregulation of PD-L1 expression on tumor cells. These effects collectively contribute to weakened antitumor T cell responses. Polyamine blocking therapy (PBT), which primarily targets polyamine biosynthesis and transport, has emerged as a novel adjunctive immunotherapeutic strategy in cancer treatment. By reducing polyamine levels in the TME, PBT restores T cell effector functions and alleviates immunosuppression. Notably, studies have demonstrated that combining PBT with ICIs produces synergistic antitumor effects and may overcome resistance to ICI monotherapy. Although research has revealed the inhibitory effects of polyamines on T cell immune function, the underlying regulatory mechanisms remain to be fully elucidated. Moreover, due to compensatory mechanisms employed by tumor cells to maintain polyamine homeostasis, multi-targeted approaches may be necessary to achieve safe and effective therapeutic outcomes. Future PBT strategies may benefit from the integration of multi-omics technologies and the development of nanocarrier-based drug delivery systems, which could collectively enhance their specificity, efficacy, and applicability in cancer immunotherapy. This review systematically elucidates the immunomodulatory effects of polyamines on T cell function within the TME and provides theoretical support and novel insights for the advancement of tumor immunotherapeutic strategies.

Abstract:Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

Abstract:Eukaryotic translation initiation factor 5A (eIF5A) is the only known protein in eukaryotes that contains a hydroxyputrescine lysine modification. Only the modified form of eIF5A is biologically active and is widely involved in protein translation, mRNA degradation, autophagy, and other intracellular processes. Epithelial-mesenchymal transition (EMT) is a process in which epithelial cells transform into mesenchymal phenotype cells through a highly regulated program. It plays a key role in embryonic development, tissue regeneration, and wound healing. Based on its biological functions, EMT can be classified into three types: I, II, and III. Type III EMT is the core mechanism underlying malignant tumor cell invasion and metastasis. This EMT mechanism involves the canonical pathway induced by transforming growth factor-β (TGF-β) and is regulated by various growth factors (TRAF6, EGF, IGF, HGF, VEGF), transcription factors (Twist, Slug, NF-κB, E12/E47, SIP1, ZEB1, etc.), and signaling pathways such as Wnt/β-catenin and PEAK1. eIF5A can influence tumor cell proliferation, invasion, and metastasis by regulating EMT-related signaling pathways. The known signaling pathways through which eIF5A regulates EMT include the canonical Smad signaling pathway and non-canonical pathways such as Rho/Rac1, Twist, STAT3, and MAT1. Additionally, certain miRNA family members, such as miR-30b, miR-599, and miR-203, can bind to the 3"-UTR of eIF5A2, inhibiting its expression and subsequently suppressing the EMT process in cancer cells, including gastric cancer and colorectal cancer. GC7, an inhibitor targeting the key enzyme DHPS involved in eIF5A modification, has been shown to reverse the EMT mechanism in oral squamous cell carcinoma, lung cancer, and breast cancer by regulating cytokine-mediated signaling pathways, including HIF-1α, STAT3/c-MYC, and Twist. However, to date, no inhibitors directly targeting eIF5A have been developed. In recent years, the mechanism of eIF5A activation catalyzed by DHPS and DOHH has become increasingly clear. As the only protein involved in lysine deoxyhydroxymethylation, DHPS may play a more critical role than eIF5A in the overall signal transduction process. Through in-depth analysis of the DHPS protein structure and its active site, researchers have shifted their approach to DHPS inhibitor development from substrate analog inhibitors (such as GC7, CNI-1493, DHSI-15, etc.) to allosteric inhibitors (11g, 26d, 8m, GL-1, etc.). GC7 is not suitable for clinical trials due to its lack of specificity and low bioavailability, and the therapeutic potential of novel allosteric inhibitors has yet to be clarified. Therefore, there is a significant gap in the development of covalent drugs targeting DHPS for cancer treatment in clinical settings. This paper reviews the research progress on eIF5A in regulating EMT, focusing on the molecular mechanisms by which eIF5A influences tumor cell invasion and migration. It also discusses the characteristics and current limitations of inhibitors targeting the hypusine pathway, aiming to provide insights for studying tumor metastasis mechanisms and drug discovery.

Abstract:Age-related sarcopenia is a progressive, systemic skeletal muscle disorder associated with aging. It is primarily characterized by a significant decline in muscle mass, strength, and physical function, rather than being an inevitable consequence of normal aging. Despite ongoing research, there is still no globally unified consensus among physicians regarding the diagnostic criteria and clinical indicators of this condition. Nonetheless, regardless of the diagnostic standards applied, the prevalence of age-related sarcopenia remains alarmingly high. With the global population aging at an accelerating rate, its incidence is expected to rise further, posing a significant public health challenge. Age-related sarcopenia not only markedly increases the risk of physical disability but also profoundly affects patients’ quality of life, independence, and overall survival. As such, the development of effective prevention and treatment strategies to mitigate its dual burden on both societal and individual health has become an urgent and critical priority. Skeletal muscle regeneration, a vital physiological process for maintaining muscle health, is significantly impaired in age-related sarcopenia and is considered one of its primary underlying causes. Skeletal muscle satellite cells (MSCs), also known as muscle stem cells, play a pivotal role in generating new muscle fibers and maintaining muscle mass and function. A decline in both the number and functionality of MSCs is closely linked to the onset and progression of sarcopenia. This dysfunction is driven by alterations in intrinsic MSC mechanisms—such as Notch, Wnt/β-Catenin, and mTOR signaling pathways—as well as changes in transcription factors and epigenetic modifications. Additionally, the MSC microenvironment, including both the direct niche formed by skeletal muscle fibers and their secreted cytokines, and the indirect niche composed of extracellular matrix proteins and various cell types, undergoes age-related changes. Mitochondrial dysfunction and chronic inflammation further contribute to MSC impairment, ultimately leading to the development of sarcopenia. Currently, there are no approved pharmacological treatments for age-related sarcopenia. Nutritional intervention and exercise remain the cornerstone of therapeutic strategies. Adequate protein intake, coupled with sufficient energy provision, is fundamental to both the prevention and treatment of this condition. Adjuvant therapies, such as dietary supplements and caloric restriction, offer additional therapeutic potential. Exercise promotes muscle regeneration and ameliorates sarcopenia by acting on MSCs through various mechanisms, including mechanical stress, myokine secretion, distant cytokine signaling, immune modulation, and epigenetic regulation. When combined with a structured exercise regimen, adequate protein intake has been shown to be particularly effective in preventing age-related sarcopenia. However, traditional interventions may be inadequate for patients with limited mobility, poor overall health, or advanced sarcopenia. Emerging therapeutic strategies—such as miRNA mimics or inhibitors, gut microbiota transplantation, and stem cell therapy—present promising new directions for MSC-based interventions. This review comprehensively examines recent advances in MSC-mediated muscle regeneration in age-related sarcopenia and systematically discusses therapeutic strategies targeting MSC regulation to enhance muscle mass and strength. The goal is to provide a theoretical foundation and identify future research directions for the prevention and treatment of this increasingly prevalent condition.

Abstract:The Golgi apparatus (GA) is a key membranous organelle in eukaryotic cells, acting as a central component of the endomembrane system. It plays an irreplaceable role in the processing, sorting, trafficking, and modification of proteins and lipids. Under normal conditions, the GA cooperates with other organelles, including the endoplasmic reticulum (ER), lysosomes, mitochondria, and others, to achieve the precise processing and targeted transport of nearly one-third of intracellular proteins, thereby ensuring normal cellular physiological functions and adaptability to environmental changes. This function relies on Golgi protein quality control (PQC) mechanisms, which recognize and handle misfolded or aberrantly modified proteins by retrograde transport to the ER, proteasomal degradation, or lysosomal clearance, thus preventing the accumulation of toxic proteins. In addition, Golgi-specific autophagy (Golgiphagy), as a selective autophagy mechanism, is also crucial for removing damaged or excess Golgi components and maintaining its structural and functional homeostasis. Under pathological conditions such as oxidative stress and infection, the Golgi apparatus suffers damage and stress, and its homeostatic regulatory network may be disrupted, leading to the accumulation of misfolded proteins, membrane disorganization, and trafficking dysfunction. When the capacity and function of the Golgi fail to meet cellular demands, cells activate a series of adaptive signaling pathways to alleviate Golgi stress and enhance Golgi function. This process reflects the dynamic regulation of Golgi capacity to meet physiological needs. To date, 7 signaling pathways related to the Golgi stress response have been identified in mammalian cells. Although these pathways have different mechanisms, they all help restore Golgi homeostasis and function and are vital for maintaining overall cellular homeostasis. It is noteworthy that the regulation of Golgi homeostasis is closely related to multiple programmed cell death pathways, including apoptosis, ferroptosis, and pyroptosis. Once Golgi function is disrupted, these signaling pathways may induce cell death, ultimately participating in the occurrence and progression of diseases. Studies have shown that Golgi homeostatic imbalance plays an important pathological role in various major diseases. For example, in Alzheimer’s disease (AD) and Parkinson’s disease (PD), Golgi fragmentation and dysfunction aggravate the abnormal processing of amyloid β-protein (Aβ) and Tau protein, promoting neuronal loss and advancing neurodegenerative processes. In cancer, Golgi homeostatic imbalance is closely associated with increased genomic instability, enhanced tumor cell proliferation, migration, invasion, and increased resistance to cell death, which are important factors in tumor initiation and progression. In infectious diseases, pathogens such as viruses and bacteria hijack the Golgi trafficking system to promote their replication while inducing host defensive cell death responses. This process is also a key mechanism in host-pathogen interactions. This review focuses on the role of the Golgi apparatus in cell death and major diseases, systematically summarizing the Golgi stress response, regulatory mechanisms, and the role of Golgi-specific autophagy in maintaining homeostasis. It emphasizes the signaling regulatory role of the Golgi apparatus in apoptosis, ferroptosis, and pyroptosis. By integrating the latest research progress, it further clarifies the pathological significance of Golgi homeostatic disruption in neurodegenerative diseases, cancer, and infectious diseases, and reveals its potential mechanisms in cellular signal regulation.

Abstract:Optical imaging is highly valued for its superior temporal and spatial resolution. This is particularly important in near-infrared II (NIR-II, 1 000-3 000 nm) imaging, which offers advantages such as reduced tissue absorption, minimal scattering, and low autofluorescence. These characteristics make NIR-II imaging especially suitable for deep tissue visualization, where high contrast and minimal background interference are critical for accurate diagnosis and monitoring. Currently, inorganic fluorescent probes—such as carbon nanotubes, rare earth nanoparticles, and quantum dots—offer high brightness and stability. However, they are hindered by ambiguous structures, larger sizes, and potential accumulation toxicity in vivo. In contrast, organic fluorescent probes, including small molecules and polymers, demonstrate higher biocompatibility but are limited by shorter emission wavelengths, lower quantum yields, and reduced stability. Recently, gold clusters have emerged as a promising class of nanomaterials with potential applications in biocatalysis, fluorescence sensing, biological imaging, and more. Water-soluble gold clusters are particularly attractive as fluorescent probes due to their remarkable optical properties, including strong photoluminescence, large Stokes shifts, and excellent photostability. Furthermore, their outstanding biocompatibility—attributed to good aqueous stability, ultra-small hydrodynamic size, and high renal clearance efficiency—makes them especially suitable for biomedical applications. Gold clusters hold significant potential for NIR-II fluorescence imaging. Atomic-precision gold clusters, typically composed of tens to hundreds of gold atoms and measuring only a few nanometers in diameter, possess well-defined three-dimensional structures and clear spatial coordination. This atomic-level precision enables fine-tuned structural regulation, further enhancing their fluorescence properties. Variations in cluster size, surface ligands, and alloying elements can result in distinct physicochemical characteristics. The incorporation of different atoms can modulate the atomic and electronic structures of gold clusters, while diverse ligands can influence surface polarity and steric hindrance. As such, strategies like alloying and ligand engineering are effective in enhancing both fluorescence and catalytic performance, thereby meeting a broader range of clinical needs. In recent years, gold clusters have attracted growing attention in the biomedical field. Their application in NIR-II imaging has led to significant progress in vascular, organ, and tumor imaging. The resulting high-resolution, high signal-to-noise imaging provides powerful tools for clinical diagnostics. Moreover, biologically active gold clusters can aid in drug delivery and disease diagnosis and treatment, offering new opportunities for clinical therapeutics. Despite the notable achievements in fundamental research and clinical translation, further studies are required to address challenges related to the standardized synthesis and complex metabolic behavior of gold clusters. Resolving these issues will help accelerate their clinical adoption and broaden their biomedical applications.

Abstract:As China accelerates its efforts in deep space exploration and long-duration space missions, including the operationalization of the Tiangong Space Station and the development of manned lunar missions, safeguarding astronauts’ physiological and cognitive functions under extreme space conditions becomes a pressing scientific imperative. Among the multifactorial stressors of spaceflight, microgravity emerges as a particularly potent disruptor of neurobehavioral homeostasis. Dopamine (DA) plays a central role in regulating behavior under space microgravity by influencing reward processing, motivation, executive function and sensorimotor integration. Changes in gravity disrupt dopaminergic signaling at multiple levels, leading to impairments in motor coordination, cognitive flexibility, and emotional stability. Microgravity exposure induces a cascade of neurobiological changes that challenge dopaminergic stability at multiple levels: from the transcriptional regulation of DA synthesis enzymes and the excitability of DA neurons, to receptor distribution dynamics and the efficiency of downstream signaling pathways. These changes involve downregulation of tyrosine hydroxylase in the substantia nigra, reduced phosphorylation of DA receptors, and alterations in vesicular monoamine transporter expression, all of which compromise synaptic DA availability. Experimental findings from space analog studies and simulated microgravity models suggest that gravitational unloading alters striatal and mesocorticolimbic DA circuitry, resulting in diminished motor coordination, impaired vestibular compensation, and decreased cognitive flexibility. These alterations not only compromise astronauts’ operational performance but also elevate the risk of mood disturbances and motivational deficits during prolonged missions. The review systematically synthesizes current findings across multiple domains: molecular neurobiology, behavioral neuroscience, and gravitational physiology. It highlights that maintaining DA homeostasis is pivotal in preserving neuroplasticity, particularly within brain regions critical to adaptation, such as the basal ganglia, prefrontal cortex, and cerebellum. The paper also discusses the dual-edged nature of DA plasticity: while adaptive remodeling of synapses and receptor sensitivity can serve as compensatory mechanisms under stress, chronic dopaminergic imbalance may lead to maladaptive outcomes, such as cognitive rigidity and motor dysregulation. Furthermore, we propose a conceptual framework that integrates homeostatic neuroregulation with the demands of space environmental adaptation. By drawing from interdisciplinary research, the review underscores the potential of multiple intervention strategies including pharmacological treatment, nutritional support, neural stimulation techniques, and most importantly, structured physical exercise. Recent rodent studies demonstrate that treadmill exercise upregulates DA transporter expression in the dorsal striatum, enhances tyrosine hydroxylase activity, and increases DA release during cognitive tasks, indicating both protective and restorative effects on dopaminergic networks. Thus, exercise is highlighted as a key approach because of its sustained effects on DA production, receptor function, and brain plasticity, making it a strong candidate for developing effective measures to support astronauts in maintaining cognitive and emotional stability during space missions. In conclusion, the paper not only underscores the centrality of DA homeostasis in space neuroscience but also reflects the authors’ broader academic viewpoint: understanding the neurochemical substrates of behavior under microgravity is fundamental to both space health and terrestrial neuroscience. By bridging basic neurobiology with applied space medicine, this work contributes to the emerging field of gravitational neurobiology and provides a foundation for future research into individualized performance optimization in extreme environments.

Abstract:Objective Junctophilin-2 (JPH2) is an essential structural protein that maintains junctional membrane complexes (JMCs) in cardiomyocytes by tethering the plasma membrane to the sarcoplasmic reticulum, thereby facilitating excitation-contraction (E-C) coupling. Mutations in JPH2 have been associated with hypertrophic cardiomyopathy (HCM), but the molecular mechanisms governing its membrane-binding properties and the functional relevance of its membrane occupation and recognition nexus (MORN) repeat motifs remain incompletely understood. This study aimed to elucidate the structural basis of JPH2 membrane association and its implications for HCM pathogenesis.Methods A recombinant N-terminal fragment of mouse JPH2 (residues 1-440), encompassing the MORN repeats and an adjacent helical region, was purified under near-physiological buffer conditions. X-ray crystallography was employed to determine the structure of the JPH2 MORN-Helix domain. Sequence conservation analysis across species and junctophilin isoforms was performed to assess the evolutionary conservation of key structural features. Functional membrane-binding assays were conducted using liposome co-sedimentation and cell-based localization studies in COS7 and HeLa cells. In addition, site-directed mutagenesis targeting positively charged residues and known HCM-associated mutations, including R347C, was used to evaluate their effects on membrane interaction and subcellular localization.Results The crystal structure of the mouse JPH2 MORN-Helix domain was resolved at 2.6 ?, revealing a compact, elongated architecture consisting of multiple tandem MORN motifs arranged in a curved configuration, forming a continuous hydrophobic core stabilized by alternating aromatic residues. A C-terminal α-helix further reinforced structural integrity. Conservation analysis identified the inner groove of the MORN array as a highly conserved surface, suggesting its role as a protein-binding interface. A flexible linker segment enriched in positively charged residues, located adjacent to the MORN motifs, was found to mediate direct electrostatic interactions with negatively charged phospholipid membranes. Functional assays demonstrated that mutation of these basic residues impaired membrane association, while the HCM-linked R347C mutation completely abolished membrane localization in cellular assays, despite preserving the overall MORN-Helix fold in structural modeling.Conclusion This study provides structural insight into the membrane-binding mechanism of the cardiomyocyte-specific protein JPH2, highlighting the dual roles of its MORN-Helix domain in membrane anchoring and protein interactions. The findings clarify the structural basis for membrane targeting via a positively charged linker and demonstrate that disruption of this interaction—such as that caused by the R347C mutation—likely contributes to HCM pathogenesis. These results not only enhance current understanding of JPH2 function in cardiac E-C coupling but also offer a structural framework for future investigations into the assembly and regulation of JMCs in both physiological and disease contexts.

Abstract:Objective Repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technique, offers a non-pharmacological therapeutic option for the management of Alzheimer’s disease (AD). Studies have demonstrated that ferroptosis plays a pivotal role in the pathological onset and progression of AD, and the inhibition of neuronal ferroptosis can significantly ameliorate cognitive impairments associated with AD. The imbalance of calcium ion (Ca²⁺) homeostasis is intimately associated with the pathology of AD and serves as a catalyst for the induction of ferroptosis through various pathways. This study is designed to investigate whether rTMS can ameliorate AD by inhibiting neuronal ferroptosis or maintaining calcium homeostasis, ultimately establishing a theoretical and experimental framework for the utilization of rTMS in AD treatment.Methods APP/PS1 AD mice were subjected to both 0.5 Hz low-frequency and 20 Hz high-frequency rTMS treatments, and the efficacy of these treatments was evaluated using novel object recognition and Morris water maze tests. ELISA was employed to quantify the levels of glutathione (GSH), malondialdehyde (MDA), superoxide dismutase (SOD), Fe²⁺ within the hippocampi of mice from each group. HT-22 cells were induced to undergo ferroptosis via Erastin treatment, and subsequent to high- and low-frequency magnetic stimulation, cell viability was assessed using CCK-8 assay, while intracellular calcium ion concentration fluctuations were monitored using Fluo-4 AM.Results The findings revealed that, when compared to normal mice, AD mice displayed a notable decline in cognitive function, accompanied by a substantial increase in ferroptosis levels and intracellular calcium ion concentrations. Both high-frequency and low-frequency applications of rTMS were found to significantly ameliorate cognitive impairments in AD mice, while also effectively mitigating the abnormal augmentation of neuronal ferroptosis and intracellular calcium ion levels.Conclusion The present study underscores that both high-frequency and low-frequency rTMS exhibit efficacy in alleviating cognitive dysfunction in AD mice, potentially through the modulation of ferroptosis and intracellular calcium ion homeostasis.

Abstract:Objective Repetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease (AD), but the neurobiological mechanisms linking synaptic pathology, neural oscillatory dynamics, and brain network reorganization remain unclear. This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments, molecular profiling, and neurophysiological monitoring.Methods In this prospective double-blind trial, 12 AD patients underwent a 14-day protocol of 20 Hz rTMS, with comprehensive multimodal assessments performed pre- and post-intervention. Cognitive functioning was quantified using the mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA), while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living (ADL) scale and combined neuropsychiatric inventory (NPI)-Hamilton depression rating scale (HAMD). Peripheral blood biomarkers, specifically Aβ1-40 and phosphorylated tau (p-tau181), were analyzed to investigate the effects of rTMS on molecular metabolism. Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients, while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization. Furthermore, systematic assessment of correlations between cognitive scale scores, blood biomarkers, and network characteristics was performed to elucidate cross-modal therapeutic associations.Results Clinically, MMSE and MOCA scores improved significantly (P<0.05). Biomarker showed that Aβ1-40 level increased (P<0.05), contrasting with p-tau181 reduction. Moreover, the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores. Post-intervention analyses revealed significant modulations in oscillatory power, characterized by pronounced reductions in delta (P<0.05) and theta bands (P<0.05), while concurrent enhancements were observed in alpha, beta, and gamma band activities (all P<0.05). Network analysis revealed frequency-specific reorganization: clustering coefficients were significantly decreased in delta, theta, and alpha bands (P<0.05), while global efficiency improvement was exclusively detected in the delta band (P<0.05). The alpha band demonstrated concurrent increases in average nodal degree (P<0.05) and characteristic path length reduction (P<0.05). Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181. Additionally, the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band. However, the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands.Conclusion 20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) significantly improves cognitive function and enhances the metabolic clearance of β-amyloid and tau proteins in AD patients. This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation, which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks. These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales, blood biomarkers, and EEG——in understanding and monitoring the progression of AD. This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.

Abstract:Objective Based on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective.Methods According to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity.Results Compared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2.Conclusion Children with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

Abstract:Objective Primary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Abstract:In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.