Journal of Medicine and Life Sciences (JMLS) is a peer-reviewed academic journal dedicated to interdisciplinary research in the fields of medicine, life sciences, and healthcare. It publishes original research articles on topics such as medical innovations, molecular biology, pharmacology, public health, healthcare systems, and environmental health. The journal aims to foster academic dialogue, advance scientific understanding, and contribute to the improvement of global health and well-being.
Meridian-GAT: Modeling Meridian System Mechanisms Using Graph Attention Networks
The meridian system is a central theoretical component of traditional Chinese medicine (TCM), describing functional pathways through which acupuncture stimulation is transmitted to regulate physiological states. Despite its extensive clinical use, the meridian system lacks a unified computational framework capable of quantitatively modeling its network structure and transmission mechanisms. In this study, we formulate the meridian system as a complex graph, where acupoints are represented as nodes and meridian-based and functional relationships are represented as edges, and propose Meridian-GAT, a graph attention network-based model for modeling meridian system mechanisms. By leveraging attention mechanisms in graph neural networks, the proposed model captures heterogeneous and non-uniform transmission strengths among acupoints, enabling data-driven exploration of meridian connectivity and information propagation patterns. Multi-dimensional acupoint features, including spatial attributes, meridian affiliations, and functional indications, are integrated into a unified graph representation to support mechanism-oriented learning tasks. Meridian-GAT is evaluated on acupoint representation learning and acupuncture efficacy prediction tasks using a curated meridian knowledge dataset. Experimental results demonstrate that Meridian-GAT outperforms baseline graph neural network models, achieving an improvement of 8.7% in prediction accuracy compared with the standard GCN model. Furthermore, the learned attention weights provide interpretable insights into key acupoints and dominant transmission pathways, which are consistent with classical meridian theory. This work offers a novel graph-based computational framework for quantitatively modeling meridian system mechanisms and contributes to the scientific interpretation and modernization of acupuncture theory.
Copyright (c) 2026 Xueqi Tang, Lixian Li (Author)
MSA-TransUNet: A Multi-Scale Attention Enhanced Transformer-UNet Architecture for Accurate Vessel Segmentation and Visualization in Medical Imaging
Accurate segmentation of vascular structures is critical for computer-aided diagnosis, surgical planning, and quantitative vascular analysis. Nevertheless, vessel segmentation remains a formidable challenge due to low contrast, high noise, intricate topology, and the pervasive presence of thin and tortuous vascular branches. To overcome these obstacles, we propose MSA-TransUNet, a novel hybrid architecture that combines convolutional neural networks (CNNs) with Transformer-based global modeling, augmented by a Multi-Scale Attention Module (MSAM) and a Vessel Enhancement Module (VEM) to enhance vessel representation. The MSAM selectively emphasizes vascular features across multiple receptive fields and strengthens both channel-wise and spatial responses, while the VEM introduces a learnable vascular enhancement mechanism inspired by traditional vesselness filtering techniques. In addition, a connectivity-aware loss function (clDice) is incorporated to preserve delicate vascular topology and minimize branch discontinuities. Experiments conducted on three publicly available vascular datasets, including DRIVE, STARE, and CHASE_DB1, demonstrate that MSA-TransUNet outperforms state-of-the-art segmentation models such as UNet, Attention-UNet, and TransUNet. The proposed approach achieves notable improvements in Dice coefficient, connectivity accuracy, and small-vessel recall. These results indicate that MSA-TransUNet offers a robust and effective solution for medical vascular segmentation and has potential to support clinical vessel visualization and diagnosis.
Copyright (c) 2025 Yilin Yao, Yinghan Li, Shirong Zheng, Taoyu Zhu (Author)
Exploration on the Construction of a Deeply Integrated "Medical-Research-Enterprise" Sci-Tech Innovation Model System in Monodisease Oncology Research Centers
Objective: To enhance the overall scientific and technological innovation capability and conversion rate of scientific and technological achievements of hospitals by constructing a scientific and comprehensive "medical research enterprise" deep integration technology innovation model system for tumor single disease research centers. Methods: Based on the typical case study method and literature study method, the "medical research enterprise" deep integration scientific and technological innovation model system of the tumor single disease research center built by the Chinese Academy of Sciences Hefei Cancer Hospital was elaborated from six fusion aspects, including organization, system, platform, personnel, project support and achievements, and achievements transformation and sharing. At the same time, the scientific and technological achievements obtained from the publication of paper achievements, patent achievement approval, patent achievement transformation, and project approval showed the role of the "medical research enterprise" deep integration scientific and technological innovation model system of the tumor single disease research center in improving the scientific and technological innovation ability of the hospital. Results: The "medical research enterprise" deep integration scientific and technological innovation system of the cancer single disease research center built by the Chinese Academy of Sciences Hefei Cancer Hospital has made remarkable achievements in the important aspects of scientific and technological achievements such as the publication of papers and books, the publication of patents and software works, the approval of projects, and the transformation of patent achievements. Conclusion: The "medical research enterprise" deep integration of scientific and technological innovation model system of the Research Center for Single Disease of Tumor in Hefei Cancer Hospital, Chinese Academy of Sciences can significantly improve the overall scientific and technological innovation capability of the hospital and the transformation rate of scientific and technological achievements, which is of great significance for improving the theory of hospital integration of scientific and technological innovation and guiding the practice of hospital scientific and technological innovation.
scientific and technological innovation framework
Copyright (c) 2025 Mengfei Sheng, Jiangping Zhou, Enjun Wang, Xueran Chen, Peng Wang, Ying Wang, Haoxiang Wang (Author)
Biliary Preservation Surgery vs. Cholecystectomy: A Re-Evaluation of the Era of Precision Medicine
In the management of biliary diseases, gallbladder-preserving surgery and cholecystectomy are two primary surgical strategies that have attracted considerable attention. With the advent of precision medicine, the development of advanced diagnostic tools and personalized treatment approaches necessitates a re-evaluation of their clinical applications. Gallbladder-preserving surgery, including procedures such as partial cholecystectomy and gallbladder-preserving lithotomy, aims to remove pathological lesions while retaining as much functional gallbladder tissue as possible, whereas cholecystectomy involves complete removal of the diseased gallbladder to prevent recurrence. Each approach has distinct advantages and limitations: gallbladder-preserving surgery maintains gallbladder function and supports normal biliary physiology, while cholecystectomy provides definitive resolution of gallbladder pathology with a lower recurrence risk. However, gallbladder-preserving procedures carry the potential for disease recurrence, and cholecystectomy may result in loss of gallbladder function and associated complications. Recent studies have explored the indications, surgical outcomes, and long-term prognosis of these procedures across diverse patient populations. Guided by precision medicine, the integration of genetic testing, advanced imaging modalities, and biomarker assessments enables more accurate risk stratification and individualized treatment planning, enhancing both surgical safety and efficacy. This article systematically reviews recent literature on gallbladder-preserving surgery and cholecystectomy, providing a comprehensive evaluation of indications, therapeutic effects, complications, and postoperative recovery, with the aim of offering clinicians evidence-based guidance for selecting the most appropriate surgical approach for each patient.
Copyright (c) 2025 Yingbing Yan (Author)
Selected Case Studies of Moving Qi Acupuncture for Pain Relief
This paper provides a comprehensive overview of the origin, theoretical foundation, operational principles, and clinical efficacy of Dong's "Moving Qi" acupuncture technique in pain management. Rooted in the classical theory that "where Qi flows smoothly, there is no pain," this method integrates the principles of meridian regulation, dynamic balance of Yin and Yang, and neuromuscular coordination. The technique involves inserting needles at distant or contralateral acupoints while guiding the patient to actively move or gently massage the affected area. This process enhances Qi circulation and blood flow, promotes neuromuscular activation, and facilitates the body's self-regulation mechanisms. Drawing upon both ancient medical texts such as Lingshu·Guanzhen and modern research on acupuncture analgesia, this study elucidates how movement synergizes with needling stimulation to produce dual effects on sensory and motor pathways. By activating motor output, movement suppresses excessive nociceptive input and enhances the brain's endogenous pain control system, thus amplifying acupuncture's therapeutic impact. Clinical observations demonstrate that Moving Qi acupuncture achieves rapid and sustained pain relief in conditions such as cervical spondylosis, shoulder periarthritis, lumbar disc herniation, knee osteoarthritis, and ankle sprain. Through detailed case analyses, the paper highlights the technique's operational features, including point selection, manipulation methods, and movement coordination strategies, offering insights into its integration with modern rehabilitation and pain medicine. Dong's Moving Qi acupuncture represents a unique synthesis of traditional meridian theory and modern physiological mechanisms, providing a valuable model for the future development of dynamic acupuncture therapies.
Copyright (c) 2025 Tingting Zhu, Chengbo Zhen (Author)
Enzymatic Activity Suppression Mechanisms in Agricultural Soil Systems: Coordination Polymer Intervention Strategies
Agricultural soil systems rely on complex enzymatic processes that regulate nutrient cycling, organic matter decomposition, and microbial community dynamics. However, intensive farming practices and environmental stressors often lead to uncontrolled enzymatic activity that can result in nutrient loss, soil degradation, and reduced agricultural productivity. This paper examines the mechanisms of enzymatic activity suppression in agricultural soils, with particular emphasis on coordination polymer intervention strategies. The research synthesizes current understanding of soil enzyme dynamics, explores the role of metal-based coordination polymers as selective enzyme inhibitors, and evaluates their applications in sustainable agriculture. Various factors affecting soil enzymatic activity are analyzed, including fertilization treatments, contamination effects, and microbial community interactions. The study reveals that copper-based and zinc-based coordination polymers demonstrate significant potential as urease inhibitors and broader enzymatic activity modulators. These novel materials offer precision control over soil biochemical processes while maintaining ecological balance. The findings suggest that coordination polymer technologies can optimize nutrient retention, reduce environmental losses, and enhance crop productivity through targeted enzymatic intervention. This approach represents a paradigm shift from traditional soil management practices toward molecularly-designed agricultural systems. The implications extend beyond immediate agricultural applications to encompass broader environmental sustainability and food security challenges in modern agriculture.
Copyright (c) 2025 Ayesha Malik (Author)
Graph Neural Network-Based Prediction Framework for Protein-Ligand Binding Affinity: A Case Study on Pediatric Gastrointestinal Disease Targets
Accurate prediction of protein-ligand binding affinity is a fundamental step in drug and vaccine development, particularly for pediatric gastrointestinal diseases such as peptic ulcers, Crohn's disease, and ulcerative colitis. Traditional computational methods, including molecular docking and physics-based simulations, often suffer from limited accuracy and high computational costs. To address these limitations, this study proposes a prediction framework based on Graph Neural Networks (GNNs), which naturally represent the structural and relational characteristics of protein-ligand complexes. Using publicly available datasets derived from PDBbind and BindingDB, a subset of protein targets highly relevant to pediatric gastrointestinal disorders was curated. Protein-ligand complexes were preprocessed to construct heterogeneous molecular graphs, with atoms as nodes and bonds or intermolecular interactions as edges. Multiple GNN architectures-including Graph Convolutional Networks (GCN), Graph Attention Networks (GAT), and Graph Isomorphism Networks (GIN)-were compared to evaluate prediction performance. Experimental results demonstrate that the GIN-based model achieved the best performance, with a mean squared error (MSE) of 2.05 and a Mean Absolute Error (MAE) of 1.05, outperforming traditional baselines such as RNN-based methods. These findings highlight the potential of graph-based deep learning approaches for accelerating drug discovery in pediatric gastroenterology by providing accurate, scalable, and generalizable predictions of binding affinity.
Copyright (c) 2025 Jiawei Jin, Taoyu Zhu, Caifeng Li (Author)
Generative AI for Advances in Biomedicine
The rapid advancement of Generative Artificial Intelligence (GenAI) has sparked widespread interest in the field of medical imaging, revealing unprecedented potential in diverse biomedical applications. Recent developments have enabled GenAI systems to perform at a level comparable to experienced clinicians, capable of generating highly accurate and structured medical reports, providing auxiliary diagnostic suggestions, and supporting complex clinical decision-making processes. By automating routine documentation, analyzing imaging data, and integrating multimodal patient information, GenAI can significantly reduce physician workload, minimize diagnostic errors, and improve the efficiency and clarity of doctor-patient communication. Beyond immediate clinical utility, these technologies hold promise for personalized medicine, predictive diagnostics, and large-scale epidemiological studies, offering transformative opportunities to enhance healthcare delivery and optimize clinical workflows. As research continues, the integration of GenAI into standard medical practice may redefine the role of clinicians, promoting more informed, data-driven, and patient-centered care.
Bioethics: To What Extent Should Terminal Illnesses Be Concealed?
This paper will delve into the idea of concealment of terminal illness, a common practice in the past and in many countries today. I will explore Eastern and Western cultural roots and history for the concealment of terminal illness, followed by an analysis of the impacts of historical factors on this norm. I will then contextualize this issue in today's world, with relevant case studies that highlight the complexity and ethical dilemma of the problem. Then, I will compare the Western and Eastern perspectives on the concealment of terminal illness today, with a focus on the US and China as representatives of the West and the East. Finally, I will put together different perspectives and explore my perspective on this issue.
Sleep Disruption During Adolescence: Effects on BMAL1 Gene Expression and Psychiatric Vulnerability
Sleep disruption (SD) is an increasingly alarming public health crisis with profound implications for psychiatric disorders. Particularly vulnerable are adolescents, who are in a critical period for brain development; insufficient sleep exacerbates neuro-developmental risks and predisposes to long-term cognitive and emotional deficits. A growing population with insomnia and other sleep disorders worldwide indicates the importance of understanding the underlying molecular mechanisms to develop targeted interventions. This study integrates clinical data, neurological studies, and molecular evidence from animal models to investigate the topic. Our analysis shows how the impacts of SD on circadian regulator BMAL1 impair prefrontal cortex (PFC) and hippocampus development, and how they are linked to common mood disorders such as depression and anxiety. Notably, key findings from the previous studies demonstrate that circadian misalignment in mice disrupts BMAL1 rhythms in prefrontal and hippocampal regions; in particular, it suppresses oligodendrocyte maturation genes and reduces myelination. Human clinical studies consistently link SD to mood disorders, while neurobiological evidence reveals the adolescent brain’s heightened vulnerability—a consequence of the ongoing maturation of the PFC, which governs emotional regulation and cognitive control. This developmental immaturity explains why teenagers are uniquely susceptible to sleep-related disruptions, often manifesting as heightened emotional reactivity and increased risk of mood disorders. Integrating these findings, this analysis identifies BMAL1-mediated oligodendrocyte dysfunction as a plausible pathway connecting sleep disruption to psychiatric risk. However, while animal models provide compelling evidence, the translational relevance to human adolescents requires further validation through longitudinal clinical studies and mechanistic investigations. Future research should prioritize direct targeting of SD-induced BMAL1 dysregulation and its downstream effects, with particular emphasis on developing personalized interventions tailored to individual circadian profiles and novel precision therapies optimized for adolescent neurodevelopmental windows.
Copyright (c) 2025 Wei Xing, Guangyao Wu (Author)
EGNN-CMutPred: Predicting Protein Mutational Effects by Integrating Primary and Tertiary Protein Structures
The study proposed the EGNN-CMutPred, Equivariant Graph Neural Network based Comprehensive Protein Mutational Effect Predictor, a novel approach for predicting the effects of protein mutations by integrating both primary and tertiary protein structures. By combining Evolutionary Scale Modeling 2 (ESM-2) for semantic embedding with Equivariant Graph Neural Network (EGNN) for structural encoding, the model improves its accuracy in predicting how mutations impact protein function and stability. The study aims to address the limitations of traditional sequence and structure-based prediction methods by incorporating both semantic and topological embeddings of proteins, allowing the model to capture a comprehensive understanding of each protein. EGNN-CMutPred was trained on non-redundant protein sequences from the CATH v4.3.0 database and evaluated against benchmarks, including ProteinGym (DMS) and the ProThermDB database, which measure changes in melting temperature (△Tm) and change in the variation of Gibbs free energy (△△G). The model effectively simulates mutations and predicts changes in protein stability, as demonstrated by strong performance in metrics such as Spearman’s Correlation and True Positive Rate. These results suggest that EGNN-CMutPred is a valuable tool for precision medicine and protein engineering, offering enhanced prediction capabilities over existing methods. Future research will refine the model’s computational techniques and expand its applicability to larger, more diverse datasets, furthering its potential in understanding protein mutations and their implications for disease and therapeutic development.
Exploration and Clinical Practice of the Optimization Path of Sports Rehabilitation Technology
With the continuous development of sports rehabilitation technology, the combination of sports science and physical therapy provides patients with personalized and effective rehabilitation plans. However, there are some problems with sports rehabilitation technology in terms of individualized treatment plans and the popularization of equipment. This paper conducts in-depth discussions on these issues and proposes optimization paths, including the optimization of personalized training programs, the innovation and popularization of equipment, as well as the improvement of rehabilitation monitoring and feedback mechanisms. This paper provides an in-depth discussion on the clinical applications of sports rehabilitation in treating sports injuries and elderly patients, as well as implementing personalized rehabilitation interventions, offering theoretical and practical support for future development.
AI-Driven Clinical Decision Support Optimizes Treatment Accuracy for Mental Illness
This paper focuses on exploring the application of AI-based clinical decision support systems in the precise treatment of mental disorders, and analyzes their mechanisms of action, key techniques, and technical solutions. This paper proposes a series of system architecture methods, including unstructured data processing, multi-modal feature fusion, individualized treatment modeling, and interpretable process design, to improve the efficiency and individualization of precise treatment for mental disorders. Meanwhile, an experimental verification system was proposed to comprehensively verify the functional performance and practical value of the system, providing good technical support for the intelligent diagnosis and treatment of clinical mental disorders by this system.
Copyright (c) 2025 Danyating Shen (Author)
Research on Improving the Matching Efficiency between Cancer Patients and Clinical Trials Based on Machine Learning Algorithms
Clinical trials offer critical opportunities for cancer patients to access novel treatments. However, the current trial matching process is often time-consuming, labor-intensive, and limited by fragmented data and manual screening. This study explores the application of machine learning algorithms to optimize the matching of cancer patients to clinical trials. By constructing structured representations of both patient profiles and trial eligibility criteria, and applying a combination of classification and similarity models, the system efficiently estimates match probabilities. Supplemented by natural language processing, feature extraction, and physician feedback mechanisms, the approach integrates automated recommendations with expert validation in a "model-assisted, human-in-the-loop" workflow. Case analyses demonstrate that this framework achieves high accuracy and significantly improves matching speed, providing effective support for personalized oncology care.
Copyright (c) 2025 Xiangtian Hui (Author)
Research Progress on the Correlation between Obstructive Sleep Apnea Hypopnea Syndrome and Metabolic Related Fatty Liver Disease
Metabolic dysfunction-associated fatty liver disease (MAFLD), a newly named term for fatty liver disease, offers clearer diagnostic criteria compared to the traditional non-alcoholic fatty liver disease (NAFLD). This helps identify high-risk individuals earlier and improves diagnostic accuracy. The introduction of MAFLD not only reduces the need to rule out other liver diseases but also decreases the social stigma associated with the disease, making it widely accepted by multiple international societies. Obstructive sleep apnea hypopnea syndrome (OSAHS) is significantly linked to MAFLD. Chronic intermittent hypoxia (CIH), caused by OSAHS, promotes the development and progression of MAFLD through mechanisms such as excessive sympathetic nervous system activity, oxidative stress, and insulin resistance. This review aims to summarize and connect existing research findings to deepen the understanding of the relationship, diagnosis, and management of OSAHS and MAFLD patients.
Copyright (c) 2025 Yuanguo Chen, Lu Chen (Author)
Challenges and Future Development of Neural Signal Decoding and Brain-Computer Interface Technology
Brain-computer interface technology can decode neural signals and realize two-way information exchange between brain and computer. The development of brain-computer interface technology is gradually becoming the mainstream direction of neuro-engineering and intelligent control research. In this paper, the structural characteristics and decoding methods of BCI system are described in detail, and the key challenges of neural signal stability and individual model design, real-time performance and security are discussed, as well as the technological development of low invasive acquisition, multi-modal fusion, adaptive algorithms and brain-computer interactive intelligence, comprehensive simulation and comparative analysis. It is expected to provide theoretical reference for the practical application and intelligent research of BCI system.
What Happens if Someone Doesn't Clean Male Masturbator? A Study Based on in Vitro Microbial Culture
The study investigated hygiene issues associated with the lack of cleaning in male masturbators through in vitro microbial culture. The experiment used 24 masturbators simulating human use scenarios, with pig semen serving as a potential microbial culture medium. The results showed that in YPD media, the colony-forming units (CFU) of the no-clean group increased from 11,600 ± 1249 mL⁻¹ at 0 hours to 41,000 ± 8641 mL⁻¹ at 48 hours, representing a 3.53-fold increase. In PDA media, the fungal colony area of the water-cleaned group at 48 hours was 328.01 ± 144.00 mm², while the special cleaning fluid group exhibited only 14.12 ± 3.55 mm². The special cleaning fluid achieved a 97.8% inhibition effect on fungi (PDA media, 48 hours) and a 90.6% cleaning effect on bacteria (BPA media, 48 hours). These findings suggest that the use of GXP special cleaning fluid significantly reduces the risk of microbial growth, ensuring improved hygiene and safety.
Copyright (c) 2025 Ao Wang, Zhe Wang, Guannan Li, Quanming Liu, Libo Huang, Junru Jiang (Author)
Computational and Experimental Drug Discovery Targeting the Glycolytic Pathway in Methicillin-Resistant Staphylococcus Aureus
This dissertation studies the metabolic pathways of methicillin-resistant Staphylococcus aureus (MRSA), focusing on the enzyme MRSaFBA. It highlights the enzyme's potential as a therapeutic target for antibacterial strategies. By employing biophysical techniques including Dynamic Light Scattering (DLS) and Thermal Denaturation Analysis (TDA), the study provides new insights into the structural stability and aggregation behavior of MRSaFBA under various conditions. The research also demonstrates improvements in protein production and purification processes, enhancing the yield and purity of MRSaFBA and enabling more precise biochemical characterization. Furthermore, enzymatic assays confirm the enzyme's sensitivity to environmental factors and inhibitors, underscoring its potential as a drug target. The study also incorporates molecular docking to understand the interaction mechanisms of potential inhibitors, laying a foundation for the development of MRSaFBA-HCA site.
methicillin-resistant Staphylococcus aureus
Optimization of Medical Device Software Lifecycle Management Based on DevOps
As more and more technological advances affect medical equipment, the importance of software for medical equipment is becoming more and more significant, and it is crucial to effectively manage and control the life cycle of software. This paper proposes a software improvement scheme with DevOps as the core, including adopting agile development mode, refining test management and optimizing operation and maintenance process, so as to improve the efficiency of software development, test and operation and maintenance, shorten the delivery cycle and reduce compliance risks. The core philosophy of DevOps is continuous integration, continuous delivery and cross-team collaboration, providing a new approach to the development and management of medical device software, the implementation of this strategy to achieve the goal of improving software quality, improving system reliability, and meeting stringent industry standards.
Copyright (c) 2025 Minkang Zhang (Author)
Exploration and Practice of Artificial Intelligence Empowering Diagnosis and Treatment of Hematological Diseases
Artificial intelligence technology has made great progress in the clinical treatment of blood diseases. This paper comprehensively discusses the core application of artificial intelligence in the diagnosis and treatment of blood diseases, summarizes the existing problems, such as non-standard data standards, small sample size, insufficient model interpretability and disconnection between the system and clinical process, and puts forward solutions, such as the establishment of high-quality data platform. Optimize convenient clinical decision assistance, strengthen the combination of model and procedure, and increase the training of compound talents to promote the intelligent and standardized direction of blood disease diagnosis and treatment.
Copyright (c) 2025 Qing Yuan, Qiaoling Wang, Yanwu Liu, Jiayu Liu, Mingxia Tang, Jian Yang (Author)
Pathogenetic and Therapeutic Insights of Depression
Depression has become one of the major diseases that endanger public health and safety. With the march of society, people have become more aware of the dangers of depression, and scientists have made extensive research on depression. Now scientists have put forward some hypotheses recognized widely by the academic world about the pathogenesis of depression, while the exact pathogenesis of depression remains to be studied. Although some clinical treatments for depression have been explored, effective therapies to completely cure depression haven't been found. This thesis mainly concludes the progress of previous research on the symptoms, pathogenesis, diagnosis and treatments of depression, and gives a detailed and full introduction of depression. I hope that this paper can provide a multi-faceted knowledge for people who want to understand and do research on depression, and give a reference to future research on depression.
Restoring Glycemic Control in Type 2 Diabetes through Fiber-Induced Microbial Remodeling
Dietary composition plays a vital role in the intervention and management of chronic metabolic diseases. This study evaluated the effects of a high-fiber diet on gut microbiota and glucose regulation in patients with type 2 diabetes through a rigorously designed clinical intervention trial. Participants in the intervention group followed a personalized high-fiber diet continuously for 12 weeks. The results showed a 16.8% reduction in fasting blood glucose and a 1.4% decrease in glycated hemoglobin (HbA1c). Additionally, the relative abundance of beneficial gut bacteria, such as Bifidobacterium, significantly increased. These findings indicate that a high-fiber diet can improve glucose metabolism by altering the composition of the gut microbiota. The study provides solid scientific evidence to support the refinement of nutritional strategies for diabetes management.
Copyright (c) 2025 Emily C. Cartwright, Michael T. Hughes, Sophie Lennox, Oliver Jameson, Rachel Winstone (Author)
Precise Design and Application Progress of Nanodelivery Systems in Targeted Therapy for Hepatic Fibrosis
Hepatic fibrosis is a chronic disease with global prevalence and the development of targeted therapeutic strategies remains essential. This study presents a nanocarrier platform developed through precise engineering, incorporating Vitamin A modification to achieve effective targeting of hepatic stellate cells (HSCs). The carrier utilizes a pH-responsive mechanism to control drug release accurately. In mouse models, the system showed good biocompatibility and significant antifibrotic effects. Experimental results showed a 68.9% reduction in transforming growth factor-beta 1 (TGF-β1) expression and a 40.7% decrease in collagen deposition area. These findings indicate that such responsive nanodelivery systems may offer a practical approach for the targeted treatment of hepatic fibrosis.
Copyright (c) 2025 Fang Lin, Mauro Ferrari, Leaf Huang, Omid Farokhzad, Pei Gu, Tatiana Segura (Author)
Neuromodulation in Pain Management for Rehabilitation: Current Status and Future Perspectives
Neuromodulation techniques have gained significant attention in pain management, particularly in the rehabilitation of chronic pain conditions. These therapies target the nervous system to alter pain perception and promote recovery by modulating neural activity. This review provides an overview of the current state of neuromodulation in pain management, highlighting key techniques such as spinal cord stimulation, peripheral nerve stimulation, transcranial magnetic stimulation, and deep brain stimulation. We also explore the underlying neurophysiological mechanisms, clinical applications, and challenges associated with these therapies. The future of neuromodulation in rehabilitation is promising, with advancements in bioelectronic medicine and personalized, AI-driven approaches offering new opportunities for more effective and tailored treatments. However, challenges such as device accessibility, patient variability, and long-term efficacy need to be addressed to optimize their clinical use. This review concludes by discussing the potential directions for future research and the clinical implications for integrating neuromodulation into comprehensive pain management strategies.
Copyright (c) 2025 Hao Hu, Fang Liu, Wenjuan Wu, Yun Luo, Yanbiao Zhong, Maoyuan Wang (Author)
Quality Control and Regulatory Standards for Controlled-Release Tablets: A Global Perspective
Controlled-release (CR) tablets play a crucial role in modern pharmaceutical formulations by enhancing therapeutic efficacy, reducing dosing frequency, and improving patient compliance. However, ensuring the quality and regulatory approval of these formulations remains a complex challenge due to variations in manufacturing processes, quality control parameters, and global regulatory requirements. This review provides a comprehensive analysis of CR tablet development, focusing on key formulation principles, quality control methodologies, and regional regulatory frameworks. It explores critical aspects such as dissolution testing, in vitro–in vivo correlation (IVIVC), and stability studies, highlighting the evolving role of artificial intelligence (AI) and emerging formulation technologies in optimizing drug release profiles. Furthermore, the review compares regulatory expectations across major regions, including the United States, European Union, China, and Japan, emphasizing the need for harmonized global standards. Addressing these challenges requires interdisciplinary collaboration to align regulatory requirements, enhance quality control precision, and foster innovation in controlled-release drug delivery.
Copyright (c) 2025 Lei Zhao, Na Chen, Lei Wang (Author)
The Clinical Application Value Assessment of Enhanced CT in the Diagnosis of Gastrointestinal Stromal Tumors
Objective: To evaluate the clinical application value of enhanced CT in the diagnosis of gastrointestinal stromal tumors (GISTs). Methods: This study selected clinical and CT scan data from 62 patients with gastrointestinal stromal tumors between January 2023 and May 2024. The detection efficacy of different diagnostic methods was compared, and the CT imaging characteristics based on risk classification and tumor location were analyzed. Patients were divided into two groups: gastric GIST and small intestine GIST, and the CT features and CT values were analyzed. Results: Enhanced CT scanning was superior to conventional CT in detecting gastrointestinal stromal tumors (p < 0.05). There were significant differences in tumor risk, morphology, calcification, necrosis, boundaries, vascularity, and size (p < 0.05), but no significant differences in calcification, necrosis, and tumor internal features between the two groups (p > 0.05). Significant differences were observed in tumor morphology and growth characteristics between the gastric GIST group and the small intestine GIST group (p < 0.05), and the CT values in the gastric GIST group were consistently lower than those in the small intestine GIST group (p < 0.05). Conclusion: Enhanced CT scanning improves the detection rate of gastrointestinal stromal tumors, reduces the risk of missed diagnoses and misdiagnoses, helps determine pathological grade and tumor nature, and shows differences in malignancy between tumors in different locations, providing a reliable basis for clinical decision-making.
Copyright (c) 2025 Gaoli Xiao, Jianxin Liu (Author)
The Integration of Acupuncture and Mindfulness in Depression Treatment: Development of the Mindfulness-Acupuncture (MA) Protocol
Depression remains a leading cause of disability worldwide, with up to 40% of patients failing to achieve adequate response with conventional treatments. This paper introduces the Mindfulness-Acupuncture (MA) protocol, a pioneering 12-week intervention that systematically integrates acupuncture and mindfulness practices to address the multifaceted nature of depression. The theoretical framework underpinning this protocol posits that acupuncture and mindfulness operate through complementary neurobiological mechanisms that, when combined, yield synergistic therapeutic effects. Acupuncture modulates neurotransmitter systems, reduces inflammation, and normalizes HPA axis function, while mindfulness decreases default mode network hyperactivity, strengthens executive function, and enhances emotional regulation. The MA protocol features concurrent delivery of acupuncture with guided mindfulness practice during clinical sessions, complemented by structured home practice incorporating self-administered acupressure and progressive mindfulness training. Preliminary observations from pilot implementations (n = 15) indicate promising outcomes, with 73% of participants meeting criteria for clinical response and 40% achieving remission. Patients report deeper relaxation, accelerated mindfulness skill development, and sustained benefits between sessions. The protocol demonstrates excellent retention rates (>80%) and safety profile, with minimal adverse events. This paper details the protocol's methodology, implementation requirements, clinical considerations, and future research directions. The MA protocol represents a significant advancement in integrative depression treatment — offering a comprehensive approach that simultaneously addresses neurobiological dysregulation and maladaptive psychological processes while empowering patients with sustainable self-management skills.
Copyright (c) 2025 Yuhang Qi, Bruce Park, Jian Madesen (Author)
Combined Application of Ultrasound and Coagulation Indicators in Risk Assessment of Lower Extremity Deep Vein Thrombosis During the Perioperative Period of Hip Fracture
This study investigates the effectiveness of the combined application of ultrasound and coagulation indicators in assessing the risk of lower extremity deep vein thrombosis (DVT) during the perioperative period of hip fracture. Patients with hip fractures, particularly the elderly, face a high risk of DVT due to surgical trauma, prolonged immobilization, and hypercoagulability. Ultrasound, as a non-invasive imaging technique, provides real-time visualization of venous blood flow abnormalities, while coagulation indicators (such as D-dimer and fibrinogen) reflect the biological processes of thrombosis. This prospective cohort study performed ultrasound examinations and coagulation tests on perioperative patients and analyzed their combined diagnostic efficacy for DVT. The results demonstrate that integrating ultrasound with coagulation indicators enhances early DVT detection, optimizes individualized anticoagulation therapy, and reduces thrombotic complications. These findings contribute to refining perioperative DVT risk assessment systems and provide a more precise prevention and management strategy for clinical practice.
Copyright (c) 2025 Yupeng Zhang, Xin Wang, Zhiwen Hou (Author)
Comprehensive Analysis of GLP-1 Receptor Agonists in Regulating Inflammatory Pathways and Gut Microbiota
In addition to their well-established function in regulating blood glucose, GLP-1 receptor agonists (GLP-1RAs) also contribute significantly to mitigating inflammation and promoting the balance of gut microbiota. This investigation utilizes a multi-omics approach — incorporating transcriptomics, metabolomics, and metagenomics — to assess the impact of GLP-1RAs on inflammatory signaling pathways and gut microbial composition. The findings indicate that GLP-1 receptor agonists (GLP-1RAs) mitigate inflammation by regulating the NF-κB pathway and stimulate the growth of beneficial bacteria, such as Bacteroides and Lactobacillus, which are essential for sustaining metabolic harmony. These results provide new scientific support for the clinical use of GLP-1RAs in treating diabetes and associated metabolic conditions, while highlighting their role in inflammation control and microbiome modulation.
Copyright (c) 2025 Daniel J. Carter, James R. Fletcher, Emily K. Thompson, Sophie L. Harris (Author)
Application of Nanocarrier-Based Targeted Drug Delivery in the Treatment of Liver Fibrosis and Vascular Diseases
Liver fibrosis and vascular diseases are often accompanied by chronic inflammation and excessive extracellular matrix deposition, posing significant clinical challenges. In this study, we developed a poly (lactic-co-glycolic acid) (PLGA)-based nanocarrier system for targeted delivery of anti-inflammatory and antifibrotic agents. The nanocarriers were fabricated via a nanoprecipitation method and functionalized with α-smooth muscle actin (α-SMA) antibodies and vascular cell adhesion molecule-1 (VCAM-1) aptamers to enhance cell-specific targeting. Characterization revealed uniform spherical morphology with a mean particle size of 150 ± 20 nm, increasing to 165 ± 25 nm after ligand modification, and a stable zeta potential of -20 ± 5 mV. Flow cytometry confirmed a conjugation efficiency of 85 ± 5%. Confocal imaging showed 2.3-fold and 2.5-fold increases in uptake by hepatic stellate and vascular endothelial cells, respectively. ELISA results demonstrated significant reductions in TNF-α, IL-6, Collagen I, and Fibronectin levels following treatment with drug-loaded nanocarriers. In vivo studies using C57BL/6 mouse models of liver fibrosis and vascular injury confirmed improved therapeutic efficacy. The nanocarrier group showed marked reductions in ALT (60 ± 6 U/L), AST (80 ± 8 U/L), liver fibrosis area (15 ± 3%), and atherosclerotic plaque (12 ± 2%) compared to controls. No significant adverse effects were observed. These results suggest that ligand-modified PLGA nanocarriers provide a promising strategy for targeted therapy of fibrosis-related diseases improved efficacy and safety profiles.
Copyright (c) 2025 Yan Wen, Xiaofeng Wu, Lilu Wang, Hongwei Cai, Yawen Wang (Author)