Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

Chronic pain is a complex condition shaped by long-standing alterations in both physiological and psychological processes. Rather than representing a simple continuation of acute nociceptive signaling, chronic pain is increasingly understood as the outcome of progressive dysregulation within distributed neural systems that govern sensation, affect, motivation, and cognitive control. Neuroimaging and electrophysiological studies indicate that this state is accompanied by extensive plastic changes in deep brain structures and large-scale networks. Beyond well-described central sensitization processes, chronic pain is characterized by disrupted oscillatory rhythms and altered connectivity within large-scale brain networks, including thalamo-cortical circuits and prefrontal-limbic-reward networks. These findings support a conceptual shift from viewing chronic pain as a focal, lesion-driven phenomenon toward recognizing it as a disorder of distributed network pathology. Pharmacological treatments remain central to clinical practice, yet their long-term efficacy is often limited and frequently accompanied by substantial side effects. The ongoing concerns about opioid-related risks and the inadequate therapeutic response in a subset of patients highlight the need for safe, non-pharmacological approaches that can address not only pain but also comorbid disturbances in mood, sleep, and social functioning. Neuromodulation provides a promising path toward mechanism-based and non-pharmacological management of chronic pain by employing physical or chemical stimulation to alter the excitability and synchrony of specific neural populations within central, peripheral, and autonomic systems. While invasive deep brain stimulation demonstrates that targeting deep brain structures can be effective, its clinical application is restricted by surgical risks and cost, highlighting the importance of non-invasive techniques capable of reaching deep targets. Current non-invasive approaches, such as transcranial electric stimulation, are constrained by limited penetration depth and insufficient spatial precision. These limitations hinder reliable engagement of deep regions implicated in pain, including the thalamus and nucleus accumbens, and tend to produce broad, non-specific modulation of cross-network oscillatory activity. Temporal interference (TI) stimulation has emerged as a means of overcoming these obstacles. By delivering interacting high-frequency currents that generate a low-frequency envelope within the head, TI enables focal stimulation of deep targets while minimizing superficial current delivery. Recent multiscale modeling and animal studies indicate that TI exploits the nonlinear rectification properties of neuronal membranes in response to high-frequency carriers, as well as their phase-locked responses to low-frequency envelopes, to generate “peak-focused” electric fields in deep regions under relatively low superficial current loads. Moreover, TI appears to exhibit potential advantages in terms of cell-type selectivity and rhythm-specific engagement, including differential responses across neuronal subtypes and distinct coupling to θ-, β-, and γ-band oscillations. These features suggest a promising avenue for correcting abnormal rhythms and network dynamics that contribute to chronic pain. This review summarizes current knowledge of the neural mechanisms underlying chronic pain and recent advances in TI research. It examines functional disturbances across key pain-related regions and networks, outlines the principles and technical characteristics of TI, and discusses potential deep-brain targets and stimulation strategies relevant to chronic pain. Evidence to date indicates that TI, with its non-invasiveness, tolerability, and capacity for precise deep brain modulation, holds great promise for the management of treatment-resistant chronic pain and may evolve into a new generation of precise and efficient non-pharmacological analgesic strategies.

The development of bone in human body and the maintenance of bone mass in adulthood are regulated by a variety of biological factors. Myocyte enhancer factor 2C (MEF2C), as one of the many factors regulating bone tissue development and balance, has been shown to play a key role in bone development and metabolism. However, there is limited systematic analysis on the effects of MEF2C on bone tissue. This article reviews the role of MEF2C in bone development and metabolism. During bone development, MEF2C promotes the development of neural crest cells (NC) into craniofacial cartilage and directly promotes cartilage hypertrophy. In terms of bone metabolism, MEF2C exhibits a differentiated regulatory model across different types of osteocytes, demonstrating both promoting and other potential regulatory effects on bone formation, with its stimulating effect on osteoclasts being determined. In view of the complex roles of MEF2C in bone tissue, this paper also discusses its effects on some bone diseases, providing valuable insights for the physiological study of bone tissue and strategies for the prevention of bone diseases.
Humans ; MEF2 Transcription Factors/physiology* ; Bone and Bones/metabolism* ; Animals ; Bone Development/physiology* ; Osteogenesis/physiology* ; Myogenic Regulatory Factors/physiology*

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Sishen Pills and its separated prescriptions are classic prescriptions of traditional Chinese medicine to treat intestinal diseases. In this study, a high-performance liquid chromatography-electrospray ionization tandem mass spectrometry(HPLC-ESI-MS/MS) technology was used to identify the components of Sishen Pills, Ershen Pills, and Wuweizi Powder. The positive and negative ion sources of electrospray ionization were simultaneously collected by mass spectrometry. A total of 11 effective components were detected in Sishen Pills, with four effective components detected in Ershen Pills and eight effective components detected in Wuweizi Powder, respectively. To explore the effects of Sishen Pills and its separated prescriptions on the human intestinal flora, an in vitro anaerobic fermentation model was established, and the human intestinal flora was incubated with Sishen Pills, Ershen Pills, and Wuweizi Powder in vitro. The 16S rDNA sequencing technology was used to analyze the changes in the intestinal flora. The results showed that compared with the control group, Sishen Pills, and its separated prescriptions could decrease the intestinal flora abundance and increase the Shannon index after fermentation. The abundance of Bifidobacterium was significantly increased in the Sishen Pills and Ershen Pills groups. However, the abundance of Lactobacillus, Weissella, and Pediococcus was significantly increased in the Wuweizi Powder group. After fermentation for 12 h, the pH of the fermentation solution of three kinds of liquids with feces gradually decreased and was lower than that of the control group. The decreasing amplitude in the Wuweizi Powder group was the most obvious. The single-bacteria fermentation experiments further confirmed that Sishen Pills and Wuweizi Powder had inhibitory effects on Escherichia coli, Staphylococcus aureus, and Enterococcus faecalis, and the antibacterial activity of Wuweizi Powder was stronger than that of Sishen Pills. Both Sishen Pills and Ershen Pills could promote the growth of Lactobacillus brevis, and Ershen Pills could promote the growth of Bifidobacterium adolescentis. This study provided a more sufficient theoretical basis for the clinical application of Sishen Pills and its separated prescriptions.
Humans ; Gastrointestinal Microbiome/drug effects* ; Drugs, Chinese Herbal/chemistry* ; Fermentation/drug effects* ; Bacteria/drug effects* ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Intestines/microbiology*

Objective This study aimed to explore the correlation between abnormal hand features and coronary atherosclerotic heart disease(CHD)to provide clinical data support for digitalized traditional Chinese medicine(TCM)hand diagnosis.Methods A palm key point prediction algorithm was used to automatically capture and collect detailed features of the palm and nails through image analysis and data mining using the hand diagnosis information collection technology based on the NVIDIA Jetson platform and Qt framework.A total of 438 cardiac patients who underwent coronary artery computed tomography angiography(CACTA)in the Department of Cardiology,Dongzhimen Hospital,Beijing University of Chinese Medicine,from December 2023 to April 2024 were included and divided into CHD(148 cases)and non-CHD groups(290 cases)based on the CACTA results.The hand features of the two groups were compared,and abnormal hand features associated with CHD were screened using random forest analysis as well as univariate and multivariate logistic regression analyses.Results Based on the results of univariate logistic regression and random forest analyses,a set of hand-related features associated with CHD were identified and subsequently included in the multivariate logistic regression analysis.These features included the morphology of the thenar eminence,the wrinkles of the thenar eminence,nail shape,nail texture,and the length of the blood vessel in the middle finger.Multivariate logistic regression analysis revealed that hypertrophic thenar eminence[odds ratio(OR):3.049,95%confidence interval(CI):1.430-6.503,P=0.004],presence of wrinkles on the thenar eminence(OR:2.206,95%CI:1.119-4.348,P=0.022),presence of gray-black vertical stripes on the nails(OR:1.981,95%CI:1.173-3.347,P=0.011),uneven nail surface(OR:3.130,95%CI:1.822-5.378,P<0.001),and inward-bending nail surface(OR:5.727,95%CI:1.812-18.102,P=0.003)were positively associated with CHD.In contrast,the blood vessel in the middle finger longer than 1/3 of the phalanx was negatively associated with CHD(OR:0.405,95%CI:0.234-0.702,P=0.001).Conclusion Certain hand features are significantly associated with CHD,providing the valuable clinical data to support for the digitalization of TCM hand diagnosis.

Miao medicine is guided by the medical theories of the Miao ethnic group,and the drugs used by the Miao people are derived from natural plants and animals for the prevention and treatment of diseases and protection of health.In recent years,a large number of clinical studies have shown good clinical efficacy of traditional Miao medicine in the treatment of prostatic diseases,with the advantages of easy availability,low price,and minimal adverse reactions.However,currently no systematic literature review has been reported on the treatment of prostatic diseases with Miao medicine.This article focuses on the commonly used Miao drugs recorded in the Chinese Materia Medica-Miao Medicine,with a systematic review of relevant literature retrieved on the treatment of prostate disea-ses with Miao medicine in recent years and a summarization of the advances in the studies of its pharmacological effects,mechanisms of action and clinical application,aiming to provide some new perspectives and ideas for further academic research and clinical develop-ment of Miao medicine.

Objective:To investigate the impact of regional innovation on medical security and its spatial effects across 31 provinces in China,providing scientific evidence for synergizing the"Healthy China"strategy with regional coordinated development.Methods:Based on provincial panel data from 2007 to 2023,the medical insurance fund expenditure was employed as a proxy for medical security.Methodologies include Moran's I tests,dual-way fixed effects models,Spatial Durbin Models(SDM)with adjacency and inverse-distance matrices,and spatial mediation models were applied to comprehensively analyze the direct effects,spatial spillover effects,and mediating pathways of regional innovation on medical security.Results:During the observation period,medical security levels in all provinces showed a fluctuating upward trend with significant regional disparities,where eastern provinces outperformed central and western regions.Regional innovation exhibited significant positive direct effects and spatial spillover effects on medical security.Regional innovation can improve medical insurance coverage by promoting growth in medical financial expenditure and the conversion of medical patents.Conclusion:Policy recommendations include deepening the synergy between regional innovation and medical security,optimizing the allocation of medical fiscal resources,accelerating the transformation of technological innovations,and narrowing regional development gaps.

Objective To assess the effectiveness of the evaluation of military physical function(EMPF)system in predicting the occurrence of military training injuries among new recruits to provide scientific guidance and methodological choice for military training.Methods A total of 527 new recruits from 5 grassroots units from July 2016 to February 2018 were selected for the study.The recruits underwent EMPF testing,and their military training injuries were monitored over a 2-year follow-up period.Those who sustained injuries during training were divided into injury group(n=163),while the remaining recruits were placed in healthy group(n=364).The predictive ability of the total EMPF score for training injuries was assessed using the receiver operating characteristic curve(ROC),and the correlation between the total EMPF score,individual test scores,and military training injuries were analyzed using binary logistic regression.Results The total EMPF score of new recruits in injury group(19.52±1.97)was significantly lower than that of healthy group(24.31±1.54)(P<0.001),which also demonstrated a high diagnostic value in predicting the risk of military training injuries,with an area under the curve(AUC)of ROC of 0.971(P<0.001).A cut-off value of 22 scores was found to have the highest accuracy in predicting future training injuries,with an odds ratio(OR)of 25.63,sensitivity of 0.939,specificity of 0.879,positive likelihood ratio of 7.76,and a post-test probability of 0.67.Binary logistic regression analysis revealed that 6 EMPF tests,including holding the ball over and leaning back,bending forward and touching the ground with the ball,lunge squat and twist,swallow balance with holding the ball afterward,vertical jump,and respiratory pattern assessment,were negatively associated with the risk of military training injuries(P<0.0001).Conclusion The EMPF system can effectively predict the risk of military training injuries,with military personnel whose total EMPF score is less than 22 being at higher risk of sustaining such injuries.

Aim To study the correlation between es-trogen metabolism function of intestinal flora and liver fibrosis disease phenotype and differential intestinal bacteria by fecal microbiota transplantation(FMT).Methods C57BL/6J male mice were divided into normal group(Control-M),liver fibrosis Model group(Model),FMT-1 group(normal mice fecal microbiota transplantation from liver fibrosis mice),and FMT-2 group(liver fibrosis mice fecal microbiota transplanta-tion from female mice).The model group was induced by high fat and high glucose combined with low dose of CCl4 for 16 weeks.In the FMT group,the bacteria were destroyed by mixed antibacterial solution and then the corresponding fecal microbiota solution was given.The model group was established in the FMT-2 group and the model group at the same time.Liver function(ALT,AST)was detected by biochemical methods;liver inflammation(IL-1α,IL-6)was detected by ELISA;liver pathology was detected by HE and Mas-son methods;the expressions of α-SMA,collagen Ⅰ,estrogen receptor ERα,ERβ and GPER were detected by Western blot;estrogen metabolic enzymes β-glucu-ronidase and β-glucosidase in intestinal flora were de-tected by double antibody sandwich assay;gut microbi-ota was detected by 16S rDNA method;the correlation between estrogen metabolic enzymes,estrogen receptors and disease phenotypes and disease-related differential bacteria was analyzed by Pearson correlation analysis.Results Liver function,inflammation and fibrosis in-dices were significantly higher in the model group than those in the control-M group and significantly lower in the FMT-2 group than in the model group;estrogen metabolic enzymes of the intestinal flora significantly increased in the model group compared to the control-M group and significantly decreased in the FMT-2 group compared to the model group;the model group showed a significant increase in ERβ and GPER and a significant decrease in ERα compared to the control-M group,while the FMT-2 group showed a significant de-crease in ERβ and GPER and a significant increase in ERα compared to the model group;the FMT-2 group increased the enterobacterial abundance and diversity reduced by modelling;estrogen metabolic enzymes,es-trogen receptor ERβ and GPER were all positively cor-related with the disease phenotype,while the opposite was true for ERα;estrogen metabolic enzymes were positively correlated with Allobaculum,Ruminococcus and Alistipes,and negatively correlated with Akkerman-sia,Lactobacillus and Prevotella.Conclusions Fecal microbiota transplantation in female mice can alleviate liver fibrosis in male mice,which is related to the im-provement of estrogen metabolism of intestinal flora.