ObjectiveTo observe the clinical efficacy of Sanren Runchang formula in treating constipation-predominant irritable bowel syndrome （IBS-C） by regulating the brain-gut axis and the effects of the formula on serum levels of 5-hydroxytryptamine （5-HT）， vasoactive intestinal peptide （VIP）， and substance P （SP）. MethodsA randomized controlled design was adopted， and 72 IBS-C patients meeting Rome Ⅳ criteria were randomized into observation and control groups （36 cases）.The observation group received Sanren Runchang formula granules twice daily， and the control group received lactulose oral solution daily for 4 weeks. IBS Symptom Severity Scale （IBS-SSS）， IBS Quality of Life Scale （IBS-QOL）， and Bristol Stool Form Scale （BSFS） were used to assess clinical symptoms， and bowel movement frequency was recorded. The Self-Rating Anxiety Scale （SAS） and Self-Rating Depression Scale （SDS） were employed to evaluate psychological status. ELISA was employed to measure the serum levels of 5-HT， VIP， and SP. ResultsThe total response rate in the observation group was 91.67% （33/36）， which was higher than that （77.78%， 28/36） in the control group （χ²=4.50， P<0.05）. After treatment， both groups showed increased defecation frequency and BSFS scores， decreased IBS-SSS total score， abdominal pain and bloating scores， IBS-QOL health anxiety， anxiety， food avoidance， and behavioral disorders scores， SAS and SDS scores， serum 5-HT and VIP levels， and increased SP levels （P<0.05， P<0.01）. Moreover， the observation group showed more significant changes in the indicators above than the control group （P<0.05， P<0.01）. The SP level showed no significant difference between the two groups. During the 4-week follow-up， the recurrence rate was 5.88% in the observation group and 31.25% in the control group. No adverse events occurred in observation group， and 2 cases of mild diarrhea occurred in the control group. ConclusionSanren Runchang formula demonstrated definitive efficacy in alleviating gastrointestinal symptoms and improving the psychological status and quality of life in IBS-C patients， with a low recurrence rate. The formula can regulate serum levels of neurotransmitters such as 5-HT and VIP， suggesting its potential regulatory effect on the brain-gut axis through modulating neurotransmitters and neuropeptides. However， its complete mechanism of action requires further investigation through detection of additional brain-gut axis-related biomarkers.

Objective To systematically analyze the literature characteristics of Journal of Organ Transplantation since its inception. Methods Using the China National Knowledge Infrastructure (CNKI) academic journal full-text database as the data source, all articles published in the Journal of Organ Transplantation from January 2010 to August 2025 were retrieved. After excluding non-academic papers, a total of 1 568 research papers were included. R language 4.3.0, Bibliometrix package 3.2.1, and Citespace software were used to analyze the number of publications, publishing institutions, authors, keywords and other aspects. Results The number of publications in Journal of Organ Transplantation increased from an average of 82 articles per year in the early years after its inception to 113 articles per year in recent years, a growth of 37.8%. The geographical distribution of publishing institutions covers 32 provinces, cities and autonomous regions nationwide, mainly concentrated in the South China, East China and North China regions, and has now basically covered the central and western regions in recent years. The author collaboration network includes 45 authors distributed across 7 major collaboration clusters, forming a stable multi-level national research system centered on key university-affiliated hospitals. The high-frequency keywords are dominated by "liver transplantation" (425 times) and "kidney transplantation" (396 times). The theme evolution shows a clear three-stage characteristic: initially focusing on clinical technology application, deepening to immune mechanism exploration in the middle stage, and recently (since 2022) focusing on cutting-edge research areas such as xenotransplantation. Conclusions Journal of Organ Transplantation has witnessed the rapid development of China's organ transplantation cause, fully reflecting the research status and trends in China's organ transplantation field, and has provided an important platform for the future development and international cooperation in China's organ transplantation field.

ObjectiveTo explore effect of Xianlian Jiedu prescription on the recurrence of colorectal cancer （CRC） and investigate the related mechanisms. MethodsA postoperative recurrence model was established in 25 Balb/c mice by injecting CT26 cells subcutaneously into the armpit， followed by surgical removal of 99% of the subcutaneous tumor. The mice were randomly divided into model group， low-dose Xianlian Jiedu prescription （XLJDP-L） group （6.45 g·kg^-1·d^-1）， medium-dose Xianlian Jiedu prescription （XLJDP-M） group （12.9 g·kg^-1·d^-1）， high-dose Xianlian Jiedu prescription （XLJDP-H） group （25.8 g·kg^-1·d^-1）， and 5-fluorouracil （5-FU） group （1×10^-3 g·kg^-1·d^-1）. The mice were euthanized after 14 days of continuous intervention， and recurrent tumor tissue was harvested. Hematoxylin and eosin （HE） staining was used to observe pathological and morphological changes in the recurrent tumor tissue. Immunohistochemistry （IHC） was employed to assess the expression of proliferating cell nuclear antigen （Ki67）， vascular endothelial growth factor （VEGF）， and platelet-endothelial cell adhesion molecule （CD31） in recurrent tumor tissue. The Western blot was used to detect the protein expression levels of angiopoietin-2 （ANG-2）， VEGF， phosphorylated-protein kinase B （p-Akt）， protein kinase B （Akt）， phosphorylated-phosphatidylinositol 3-kinase （p-PI3K）， and phosphatidylinositol 3-kinase （PI3K） in recurrent tumor tissue. ResultsBefore treatment， there were no statistical differences in tumor volume， tumor weight， and body mass among the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group compared to the model group， indicating model stability. After treatment， compared with those in the model group， the tumor volume and tumor weight in the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly reduced （P<0.01）， showing dose dependency. Meanwhile， there were no significant differences in body weight among the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group compared to the model group. HE staining showed that compared with that in the model group， tumor tissue in the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group had loosely arranged cells， increased intercellular spaces， small and shriveled nuclei， light staining， fewer mitotic figures and atypical nuclei， and increased necrotic areas. IHC showed that compared with those of the model group， the positive rates of Ki67， VEGF， and CD31 in the recurrent tumor tissue of the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly reduced （P<0.01） in a dose-dependent manner. Western blot results showed that compared with those of the model group， the protein expression levels of ANG-2 and VEGF in the recurrent tumor tissue of the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly downregulated （P<0.05， P<0.01）， and the p-Akt/Akt and p-PI3K/PI3K ratios were significantly decreased in a dose-dependent manner （P<0.05， P<0.01）. ConclusionXianlian Jiedu prescription significantly inhibits the recurrence of CRC in mice after subcutaneous tumor surgery. The mechanism may involve regulating the PI3K/Akt pathway and downregulating key angiogenic proteins such as ANG-2， VEGF， and CD31.

Objective: To investigate the effect of targeted silencing of DNA methyltransferase 3A(DNMT3A) on collagen deposition, proliferation and migration activity of mouse lung fibroblasts(PFs). Methods: In order to ensure the proliferation and migration activity of primary fibroblasts, the lung tissues of neonatal C57 suckling mice were taken, PFs were extracted after being sheared, and the morphology was observed and identified under the microscope. PFs cells were activated by 5 ng/ml TGF-β1for 24 h after cell attachment, and DNMT3A silencing model was constructed by small interfering RNA; The experiment was divided into control group, TGF-β1group, TGF-β1+ siRNA-NC group and TGF-β1+ siRNA-DNMT3A group. The protein expressions of DNMT3A, α-smooth muscle actin(α-SMA) and Collagen Ⅰ were detected by Western blot; Real time quantitative reverse transcription polymerase chain reaction(RT-qPCR) was used to detect the mRNA expression changes ofDNMT3A,α-SMAandCollagenⅠ. The proliferation ability of PFs was detected by CCK-8 and EdU staining; the migration ability of PFs was detected by scratch test and Transwell migration test. Results: Compared with the control group, TGF-β1induced the increase of DNMT3A in the activated PFs cell group(P<0.01), the protein and mRNA levels of fibrosis and proliferation related indicators α-SMA and Collagen Ⅰ also increased(allP<0.05), and the proliferation and migration ability of PFs increased(allP<0.000 1). Compared with the siRNA-NC group, the protein expression levels of DNMT3A(P<0.000 1) and related indicators α-SMA(P<0.01) and Collagen Ⅰ(P<0.01) significantly decreased in the DNMT3A silencing group by Western blot, and the mRNA levels ofDNMT3A,α-SMAandCollagenⅠby RT-qPCR also decreased(allP<0.001), and the proliferation(P<0.01) and migration ability(P<0.05) of PFs cells decreased compared with the control group. Conclusion Silencing DNMT3A can inhibit the deposition of collagen and the proliferation of PFs. DNMT3A can promote the proliferation and migration of PFs, and then promote the activation of PFs and the development of pulmonary fibrosis. This process may be regulated by DNA methylation modification.

As a new type of model organism， zebrafish is gradually gaining prominence in the field of scientific research. The unique biological characteristics and advantages of zebrafish make them play an increasingly important role in the quality evaluation of traditional Chinese medicine. Compared with other common experimental animals， zebrafish have a fast reproductive and growth speed and high embryo transparency， making them an ideal model for evaluating the quality of traditional Chinese medicine. This provides a new perspective and method for research on traditional Chinese medicine. With the growing global interest in traditional Chinese medicine， it has become crucial to find scientific and accurate methods to evaluate the quality and effectiveness of traditional Chinese medicine. The introduction of the zebrafish model has brought new breakthroughs in the quality evaluation of traditional Chinese medicine. To further promote the application of zebrafish in evaluating the quality of traditional Chinese medicine， this article systematically searched and sorted out the previous studies related to the application of zebrafish for this purpose since 2023. The commonly used disease models and indicators of zebrafish in evaluating the effectiveness of traditional Chinese medicine， as well as the mechanism of zebrafish in exploring the active ingredients of traditional Chinese medicine， were primarily reviewed. The application of zebrafish in evaluating the safety of traditional Chinese medicine and the typical examples in ensuring the quality of traditional Chinese medicine were demonstrated. The limitations encountered by zebrafish models in evaluating the quality of traditional Chinese medicine were highlighted. The resolution of these problems will help further improve the accuracy and reliability of zebrafish in evaluating the quality of traditional Chinese medicine. The article discussed the evaluation of effectiveness， safety， and quality control of zebrafish applied in traditional Chinese medicine， so as to provide a reference for establishing standards for traditional Chinese medicine and promoting its modernization in the future.

ObjectiveBased on the zebrafish model， the hepatotoxicity and anti-osteoporotic activity of evodiamine （EVO） were studied. The mechanism of EVO in treating osteoporosis was explored by using network pharmacology and real-time polymerase chain reaction（Real-time PCR）. MethodsThree days after fertilization （3 dpf）， zebrafish were randomly selected and exposed to different concentrations of EVO solution for 96 hours. The mortality rate of zebrafish at different concentrations was calculated at the exposure endpoint， and a "dose-toxicity" curve was drawn. The 10% lethal concentration （LC₁₀） was calculated. Liver phenotype， acridine orange staining， and pathological tissue sections of liver-transgenic zebrafish ［CZ16 （gz15Tg.Tg （fabp 10a： ds Red； ela31： EGFP））］ were used to confirm hepatotoxicity of EVO. On this basis， prednisolone was used to create a model of osteoporosis in zebrafish. The skull development， area of the skull stained by alizarin red， and cumulative optical density were used as indicators to evaluate the anti-osteoporotic activity of EVO in a safe dose. Based on network pharmacology， the mechanism of action of EVO in the treatment of osteoporosis was predicted and verified through Real-time PCR. ResultsThe LC₁₀ of EVO on zebrafish （7 dpf） was determined to be 0.4 mg·L^-1. Compared with the control group， sublethal concentrations （10=0.36 mg·L^-1 and 1/2LC₁₀=0.18 mg·L^-1） significantly decreased the fluorescence area of zebrafish liver （P<0.05，P<0.01） and increased the number of liver cell apoptosis. The arrangement of liver tissue was disordered and loose， and the vacuole was obvious， especially in the 0.36 mg·L^-1 group. Compared with the control group， under safe dose conditions， 0.08 and 0.02 mg·L^-1 of EVO had no significant effect on the liver. Prednisolone administration significantly reduced the mineralization area and cumulative optical density of zebrafish skulls （P<0.01） compared with the control group. The mineralization area and cumulative optical density of zebrafish skulls in the 0.08 and 0.02 mg·L^-1 groups of EVO were significantly increased compared with the model group （P<0.01）. Network pharmacology prediction suggested that EVO may regulate key targets such as avian sarcoma viral oncogene homolog （SRC）， signal transducer and activator of transcription 3 （STAT3）， interleukin-8 （CXCL8） and tyrosine kinase receptor 2 （ERBB2） to regulate signaling pathways related to lipid and atherosclerosis in diabetic complications， as well as the regulation of inflammatory mediators of tryptophan （TRP） channels. Real-time PCR experiment results indicated that EVO could regulate the above-mentioned targets， as well as genes related to osteoblasts and osteoclasts. ConclusionExcessive doses of EVO can lead to hepatotoxicity in zebrafish. Under safe dosage conditions， EVO can regulate relevant targets to exert anti-osteoporotic activity， providing a reference for the clinical safe use of EVO and ideas for the development of new drugs for osteoporosis.

ObjectiveTo explore the potential mechanism of Huoxue Xiaoyi Formula （活血消异方， HXF） in treating ovarian endometriosis （OEM） from the perspective of T follicular helper （Tfh） cells and the Janus kinase/signal transducer and activator of transcription （JAK/STAT） signaling pathway. MethodsForty-five female SD rats with normal estrous cycles were randomly divided into three groups， HXF group， model group， and normal group， with 15 rats in each group. A rat model of OEM was established by autologous endometrial tissue implantation. After successful modeling， the treatment group received HXF at 5.85 g/（kg·d） by gavage for 14 consecutive days. The model group and normal group received 1 mL/d of normal saline by gavage. RNA-sequencing data from human proliferative-phase endometriotic and normal endometrial tissues were downloaded from the GEO database. Transcriptomic sequencing was used to analyze gene expression in rat ovarian ectopic tissues and normal uterine tissues， and comparisons were made with human data to verify JAK/STAT pathway activation in proliferative-phase ectopic tissues. Immunohistochemistry was used to detect the positive expression of CXC chemokine receptor 5 （CXCR5） and interleukin-21 （IL-21） in rat ovarian ectopic and normal uterine tissues. Western Blotting was performed to detect the protein levels of IL-21， IL-21 receptor （IL-21R）， Janus kinase 1 （JAK1）， signal transducer and activator of transcription 6 （STAT6）， and B-cell lymphoma 2 （Bcl-2）. Tfh cell infiltration was analyzed using immune cell infiltration methods. ResultsGene set enrichment analysis showed that the JAK/STAT pathway was significantly activated in human proliferative-phase endometriotic tissues compared to normal endometrial tissues. Similarly， the JAK/STAT pathway was markedly activated in rat ovarian ectopic tissues in the model group compared to the normal group， but suppressed in the HXF group compared to the model group. Compared with normal uterine tissues， ovarian ectopic tissues in the model group showed increased Tfh cell infiltration scores， higher CXCR5 and IL-21 expression， and elevated levels of IL-21， IL-21R， JAK1， STAT6， and Bcl-2 proteins. Compared with the model group， HXF group showed reduced CXCR5 and IL-21 expression and decreased protein levels of IL-21， IL-21R， JAK1， STAT6， and Bcl-2. ConclusionHXF may suppress activation of the JAK/STAT signaling pathway in ovarian endometriotic tissues by inhibiting IL-21 secretion from Tfh cells.

Objective: To explore the association of screening myopia and sitting posture habits as well as screen viewing distance among primary school students, providing a scientific basis for myopia prevention and intervention among primary school students. Methods: From April to June 2024, a convenient sampling method was used to enroll 1 394 fourth grade students from four primary schools in a district of Beijing for vision examinations and questionnaire surveys. Logistic regression models were employed to analyze the relationship of screening myopia detection and sitting posture habits as well as viewing distance. Results: The screening myopia prevalence among primary school students was 63.8%. About 13.1% of students self reported poor sitting posture, and 47.1% selfreported a viewing distance of ≤20 cm. After adjusting for covariates including age, gender, school, sleep quality, parental myopia status, physical fitness level, daily high intensity physical activity, weekend outdoor activity time and types of after school services, Logistic regression analysis showed that students with poor sitting posture were more likely to have screening myopia than those with normal sitting posture ( OR =1.73,95% CI =1.03-2.92); students with a viewing distance of ≤20 cm were more likely to have screening myopia than those with a viewing distance of >20 cm( OR =1.32, 95% CI =1.02-1.71)( P <0.05). The association between sitting posture and screening myopia was more significant among boys( OR =2.00, 95% CI =1.03-3.88, P < 0.05 ). A multiplicative interaction was observed between sitting posture and viewing distance. Compared to primary school students with normal posture and a viewing distance of >20 cm, those with poor posture and a viewing distance of >20 cm were more likely to have screening myopia ( OR =1.82, 95% CI =1.12-2.96， P <0.05). Conclusions Both sitting posture habits and screen viewing distance are related to screening myopia in primary school students. Poor sitting posture poses a higher risk than screen distance, and the two factors exhibit an interactive effect on myopia risk.

Objective: To explore the safety and feasibility of the disconnection of the left renal artery preferentially during robot-assisted inferior vena cava (IVC) thrombectomy for patients with left renal cell carcinoma and tumor emboli. Methods: Clinical data of 7 patients who underwent robot-assisted IVC thrombectomy and radical nephrectomy in the First Affiliated Hospital of Zhengzhou University during Dec.2021 and Oct.2024 were retrospectively analyzed.Thrombectomy was performed first，followed by nephrectomy. The “IVC-first, kidney-last”robotic technique was developed to minimize chances of IVC thrombus. When patients in left lateral decubitus position, the left renal artery was severed from the right side through the inferior vena cava and abdominal aorta. After removal of thrombus from IVC was completed, patients changed to the right lateral position to complete radical left nephrectomy. Results: Imaging examinations revealed that the median diameter of the renal cell carcinomas was 83(46-99) mm; the median length of the inferior vena cava cancerous emboli was 49(2-91) mm.According to the Mayo classification，the cancerous emboli were gradeⅠ in 2 cases，gradeⅡ in 4 cases，and grade Ⅲ in 1 case.All surgeries were successful.The median operation time was 248(201-331) minutes，blood loss 500(200-1000) mL，and 6 cases required intraoperative blood transfusion.The median time for transition into the intensive care unit was 1(1-4) days，and drainage tube removal 6(5-12) days.Serum creatinine increased significantly in 5 cases，4 of which returned to normal after 1 week，but 1 had renal insufficiency (creatinine 166 μmol/L).Chylous fistula occurred in 1 patient，and lower extremity venous thrombosis developed in 3 patients.Pathological examinations indicated 6 cases of renal cell carcinoma and 1 case of MiT family translocation renal cell carcinoma.During the median follow-up of 17(1-35) months，5 cases were tumor-free，while 2 had lung and retroperitoneal metastases.They received targeted therapy of axitinib combined immunotheraphy and lived with tumors. Conclusion: In the left lateral position for left renal cell carcinoma with cancerous emboli，robot-assisted laparoscopic thrombectomy by crossing the inferior vena cava and abdominal aorta and disconnecting the left renal artery first is safe and feasible.

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.