ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Liver cancer is one of the most common malignant tumors in the digestive system and ranks sixth among newly diagnosed malignant tumors worldwide. Transforming growth factor-β （TGF-β） regulates cell differentiation， proliferation， apoptosis， and other physiological and pathological mechanisms and exerts cancer-suppressive and pro-cancerous dual effects in the process of tumor development. In recent years， with the continuous exploration of the mechanism of liver cancer， it has been found that the conversion of the cancer-suppressive effect into a pro-cancerous effect of this pathway plays a key role in the development of liver cancer. Traditional Chinese medicine （TCM） provides a unique perspective for the classification， diagnosis， and treatment of liver cancer with its comprehensive regulatory effects of multi-components， multi-targets， and multi-pathways. This paper summarized that the cancer-suppressive mechanisms of the TGF-β signaling pathway included promoting cancer cell cycle arrest， apoptosis， autophagy， et al， while the pro-cancerous mechanisms included promoting cancer cell proliferation， invasion and metastasis， immunosuppression， angiogenesis， et al. The TCM compounds intervening this pathway were sorted out， including Jianpi Huayu compound， Fuyang Baoyuan compound， Yipi Yanggan compound， Fuzheng Jiedu compound， compound Astragalus and Salvia， Biejia Jianwan， Dahuang Zhechong pill， and Qingxiang powder. The single TCMs mainly included Schizocapsa plantaginea， Dendrobii Caulis， Gleditsia sinensis， and Dracaena cochinchinensis. The active ingredients of TCM are mainly concentrated on flavonoids， alkaloids， glycosides， phenolics， terpenoids， polysaccharides， and other kinds of compounds. At the same time， it summarized that the liver cancer inhibition mechanism of TCM by regulating this pathway mainly included promoting apoptosis of liver cancer cells， blocking the cell cycle， and inhibiting liver cancer cell proliferation， migration， invasion， angiogenesis， immune escape， etc. The mechanism aims to give full play to the advantages of TCM and precisely regulate the TGF-β signal， thereby exerting positive anti-tumor effects， opening up a new direction for the precise targeted treatment of liver cancer， and providing a scientific basis and a new strategy for the application of TCM in the treatment of liver cancer.

Liver cancer is one of the most common malignant tumors in the digestive system and ranks sixth among newly diagnosed malignant tumors worldwide. Transforming growth factor-β （TGF-β） regulates cell differentiation， proliferation， apoptosis， and other physiological and pathological mechanisms and exerts cancer-suppressive and pro-cancerous dual effects in the process of tumor development. In recent years， with the continuous exploration of the mechanism of liver cancer， it has been found that the conversion of the cancer-suppressive effect into a pro-cancerous effect of this pathway plays a key role in the development of liver cancer. Traditional Chinese medicine （TCM） provides a unique perspective for the classification， diagnosis， and treatment of liver cancer with its comprehensive regulatory effects of multi-components， multi-targets， and multi-pathways. This paper summarized that the cancer-suppressive mechanisms of the TGF-β signaling pathway included promoting cancer cell cycle arrest， apoptosis， autophagy， et al， while the pro-cancerous mechanisms included promoting cancer cell proliferation， invasion and metastasis， immunosuppression， angiogenesis， et al. The TCM compounds intervening this pathway were sorted out， including Jianpi Huayu compound， Fuyang Baoyuan compound， Yipi Yanggan compound， Fuzheng Jiedu compound， compound Astragalus and Salvia， Biejia Jianwan， Dahuang Zhechong pill， and Qingxiang powder. The single TCMs mainly included Schizocapsa plantaginea， Dendrobii Caulis， Gleditsia sinensis， and Dracaena cochinchinensis. The active ingredients of TCM are mainly concentrated on flavonoids， alkaloids， glycosides， phenolics， terpenoids， polysaccharides， and other kinds of compounds. At the same time， it summarized that the liver cancer inhibition mechanism of TCM by regulating this pathway mainly included promoting apoptosis of liver cancer cells， blocking the cell cycle， and inhibiting liver cancer cell proliferation， migration， invasion， angiogenesis， immune escape， etc. The mechanism aims to give full play to the advantages of TCM and precisely regulate the TGF-β signal， thereby exerting positive anti-tumor effects， opening up a new direction for the precise targeted treatment of liver cancer， and providing a scientific basis and a new strategy for the application of TCM in the treatment of liver cancer.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

The genome tagging project (GTP) plays a pivotal role in addressing a critical gap in the understanding of protein functions. Within this framework, we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411 (HA-tagged Ssp411) mouse model. This model is instrumental in probing the expression and function of Ssp411. Our research revealed that Ssp411 is expressed in the round spermatids, elongating spermatids, elongated spermatids, and epididymal spermatozoa. The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis. Nevertheless, rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions. Ssp411 is not detectable in metaphase II (MII) oocytes, zygotes, or 2-cell stage embryos, highlighting its intricate role in early embryonic development. These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP, fostering groundbreaking advancements in the fields of spermiogenesis and reproductive biology.
Animals ; Female ; Humans ; Male ; Mice ; Spermatids/metabolism* ; Spermatogenesis/physiology* ; Spermatozoa/metabolism* ; Thioredoxins/genetics*

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

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.

Objective To evaluate the influence of the wearing position of dosimeters outside lead aprons on effective dose estimation for interventional radiology workers, analyze the differences between single and double dosimeter methods in effective dose estimation, and provide a reference for the personal dose monitoring of interventional radiology workers. Methods This study employed a combined approach of on-site monitoring and Monte Carlo simulation to evaluate the impact of the wearing position of dosimeters outside lead aprons on effective dose estimation, as well as the differences between effective doses measured using single and double dosimeters. Interventional radiology workers wore dosimeters at three positions: the neck outside the lead collar, the left chest outside the lead apron, and inside the lead apron. Effective doses were estimated using the single and double dosimeter methods specified in GBZ 128-2019 Specifications for individual monitoring of occupational external exposure, and the impact of different wearing positions on the estimation results was compared. Geant4 Monte Carlo simulations were used to model dose distributions at the neck outside the lead collar and at the left chest outside the lead apron for operators performing cardiovascular interventions under tube voltages of 70, 80, 90, and 100 kVp and exposure angles of posteroanterior (PA), anteroposterior (AP), and left anterior oblique 45° (LAO45°) positions. The study assessed the impact of dosimeter wearing position on effective dose estimation. Results Monte Carlo simulations demonstrated that neck doses consistently exceeded left chest doses across different tube voltages and exposure angles, with neck-to-chest dose ratios of 0.80-0.90. Under identical tube voltage conditions, AP showed the highest doses, followed by LAO45°, and PA demonstrated the lowest doses. The single and double dosimeter methods exhibited consistent patterns in effective dose estimation. Single dosimeter method generally yielded higher effective doses with relative deviations of 9.9% to 83%, though these deviations decreased under high tube voltages. Field monitoring data indicated that most interventional radiology workers maintained relative deviations between single and double dosimeter calculations below 6%, with neck-to-chest dose ratios of 0.95-1.1. The estimation patterns remained consistent across both methods, though single dosimeter method showed slightly higher results. Conclusion Under PA, AP, or LAO45°, the doses at the neck consistently exceeded those at the left chest. Therefore, when wearing lead protective equipment, the dosimeter should be properly positioned at the neck outside the lead collar to accurately reflect the radiation doses of surgeons. Some interventional radiology workers improperly positioned the dosimeter (intended at the neck outside the lead collar) at the left chest outside the lead apron, and this may result in an underestimation of the effective dose.

This study aims to explore the role and mechanism of berberine in promoting the expression of aquaporin 4(AQP4) in astrocytes by regulating the expression of miR-383-5p in HepG2 cell-derived exosomes under insulin resistance(IR). The IR-HepG2 cell model was established with 1×10~(-6) mol·L~(-1) insulin. With metformin as the positive control, the safe concentrations of berberine and metformin were screened by cell counting kit-8(CCK-8) and lactate dehydrogenase(LDH) leakage assays, and the effect of berberine on the IR of HepG2 cells was evaluated by glucose consumption. NanoSight was used to measure the particle size and concentration of exosomes secreted by HepG2 cells in each group. HepG2 cell-derived exosomes in each group were incubated with astrocytes for 24 h, and the protein and mRNA levels of AQP4 in HA1800 cells were determined by Western blot and qRT-PCR, respectively. qRT-PCR was performed to determine the expression of miR-383-5p in HepG2 cell-derived exosomes and HA1800 cells after co-incubation. Western blotting was employed to determine the expression levels of miRNAs and proteins associated with exosome production and release in HepG2 cells. The results showed that 10 μmol·L~(-1) berberine and 1 mmol·L~(-1) metformin significantly alleviated the IR of HepG2 cells and reduced the concentration of exosomes in HepG2 cells. The exosomes of HepG2 cells treated with berberine and metformin significantly up-regulated the protein and mRNA levels of AQP4 in HA1800 cells. The mRNA level of miR-383-5p in HepG2 cell exosomes and HA1800 cells co-incubated with berberine and metformin decreased significantly. The intervention with berberine and metformin significantly down-regulated the expression of proteins associated with the production of miRNAs(Dicer, Drosha) as well as the production(Alix, Vps4A) and release(Rab35, VAMP3) of exosomes in IR-HepG2 cells. In conclusion, berberine can promote the expression of AQP4 in astrocytes by inhibiting the production and release of miR-383-5p in HepG2-derived exosomes under IR.
Humans ; MicroRNAs/metabolism* ; Berberine/pharmacology* ; Hep G2 Cells ; Exosomes/genetics* ; Aquaporin 4/metabolism* ; Insulin Resistance ; Astrocytes/drug effects*