ObjectiveTo explore the possible mechanism of Tongbian Decoction （通便汤， TD） in treating slow transit constipation （STC）. MethodsTwenty-four SD rats were randomly divided into normal group， model group， TD group， and mosapride group， with 6 rats per group. Except for the normal group， STC models were established by intragastric administration of loperamide hydrochloride combined with normal saline. On the day following successful model establishment， rats in the TD group received 18.63 g·kg⁻¹ of TD by gavage， while those in the mosapride group received 1.605 mg·d⁻¹ of mosapride， and those in the normal group and the model group received 10 ml·kg⁻¹ of normal saline by gavage. All treatments were administered once daily for 7 consecutive days. Twenty-four hours after the last administration， fecal pellet number and fecal water content were measured. After intragastric administration of a 10% activated charcoal suspension， the small intestinal transit rate was calculated 30 minutes later. Serum levels of gastrin （GAS） and motilin （MTL） were measured by ELISA. Colonic histopathology was observed by HE staining， and mucus secretion by Alcian blue-periodic acid-Schiff （AB-PAS） staining. Ultrastructure of colon tissue was examined using transmission electron microscopy. Protein expression levels of C-kit， stem cell factor （SCF）， autophagy-related protein 5 （ATG5）， Beclin1， vesicle-associated membrane protein B （VAPB）， and protein tyrosine phosphatase interacting protein 51 （VAPB-PTPIP51） were measured by Western Blot， and the mRNA levels were detected by real-time PCR. Immunohistochemistry was used to detect SCF， C-kit， Beclin1， and ATG5 expression. The calcium content in colon tissue was determined by ELISA. ResultsCompared to the normal group， rats in the model group showed significantly reduced fecal pellet number， fecal water content， small intestinal transit rate， and serum GAS and MTL levels （P＜0.01）； the number of goblet cells decreased， and the mucosal and muscular layers of the colon became thinner； mRNA and protein expression levels of ATG5 and Beclin1 in colon tissue significantly increased， while calcium content decreased （P＜0.05 or P＜0.01）； and electron microscopy revealed vacuolar degeneration and increased autophagosomes in colonic cells. Compared to the model group， both TD group and mosapride group showed increased fecal pellet number， fecal water content， small intestinal transit rate， serum GAS and MTL levels， and colonic calcium content， along with decreased Beclin1 and ATG5 protein levels （P＜0.05 or P＜0.01）； the mucosal thickness and goblet cell number increased significantly， and autophagosomes decreased； in the TD group， ATG5 and Beclin1 mRNA levels decreased； in the mosapride group， SCF， VAPB， and PTPIP51 mRNA levels increased， while Beclin1 mRNA decreased （P＜0.05 or P＜0.01）. Compared to the mosapride group， the TD group showed higher fecal pellet number， fecal water content， serum GAS levels， colonic calcium content， and C-kit expression， along with lower ATG5 and Beclin1 levels （P＜0.05 or P＜0.01）. ConclusionTD may improve constipation symptoms by upregulating the VAPB-PTPIP51 complex during mitochondria-endoplasmic reticulum interactions， reducing autophagy of interstitial cells of Cajal， and promoting intestinal motility.

ObjectiveTo explore the possible mechanism of Tongbian Decoction （通便汤， TD） in treating slow transit constipation （STC）. MethodsTwenty-four SD rats were randomly divided into normal group， model group， TD group， and mosapride group， with 6 rats per group. Except for the normal group， STC models were established by intragastric administration of loperamide hydrochloride combined with normal saline. On the day following successful model establishment， rats in the TD group received 18.63 g·kg⁻¹ of TD by gavage， while those in the mosapride group received 1.605 mg·d⁻¹ of mosapride， and those in the normal group and the model group received 10 ml·kg⁻¹ of normal saline by gavage. All treatments were administered once daily for 7 consecutive days. Twenty-four hours after the last administration， fecal pellet number and fecal water content were measured. After intragastric administration of a 10% activated charcoal suspension， the small intestinal transit rate was calculated 30 minutes later. Serum levels of gastrin （GAS） and motilin （MTL） were measured by ELISA. Colonic histopathology was observed by HE staining， and mucus secretion by Alcian blue-periodic acid-Schiff （AB-PAS） staining. Ultrastructure of colon tissue was examined using transmission electron microscopy. Protein expression levels of C-kit， stem cell factor （SCF）， autophagy-related protein 5 （ATG5）， Beclin1， vesicle-associated membrane protein B （VAPB）， and protein tyrosine phosphatase interacting protein 51 （VAPB-PTPIP51） were measured by Western Blot， and the mRNA levels were detected by real-time PCR. Immunohistochemistry was used to detect SCF， C-kit， Beclin1， and ATG5 expression. The calcium content in colon tissue was determined by ELISA. ResultsCompared to the normal group， rats in the model group showed significantly reduced fecal pellet number， fecal water content， small intestinal transit rate， and serum GAS and MTL levels （P＜0.01）； the number of goblet cells decreased， and the mucosal and muscular layers of the colon became thinner； mRNA and protein expression levels of ATG5 and Beclin1 in colon tissue significantly increased， while calcium content decreased （P＜0.05 or P＜0.01）； and electron microscopy revealed vacuolar degeneration and increased autophagosomes in colonic cells. Compared to the model group， both TD group and mosapride group showed increased fecal pellet number， fecal water content， small intestinal transit rate， serum GAS and MTL levels， and colonic calcium content， along with decreased Beclin1 and ATG5 protein levels （P＜0.05 or P＜0.01）； the mucosal thickness and goblet cell number increased significantly， and autophagosomes decreased； in the TD group， ATG5 and Beclin1 mRNA levels decreased； in the mosapride group， SCF， VAPB， and PTPIP51 mRNA levels increased， while Beclin1 mRNA decreased （P＜0.05 or P＜0.01）. Compared to the mosapride group， the TD group showed higher fecal pellet number， fecal water content， serum GAS levels， colonic calcium content， and C-kit expression， along with lower ATG5 and Beclin1 levels （P＜0.05 or P＜0.01）. ConclusionTD may improve constipation symptoms by upregulating the VAPB-PTPIP51 complex during mitochondria-endoplasmic reticulum interactions， reducing autophagy of interstitial cells of Cajal， and promoting intestinal motility.

Syndrome differentiation and treatment is an integral part of the traditional Chinese medicine （TCM） diagnostic and therapeutic system， whose development exhibits distinct stages. This paper systematically reviews the evolutionary trajectory of syndrome differentiation and treatment， from symptom-based treatment in Inner Canon of Yellow Emperor （《黄帝内经》）， to ZHANG Zhongjing's establishment of the disease-pulse-syndrome-treatment framework， through its application and development in the Ming and Qing dynasties， and finally to its recognition as a fundamental characteristic of TCM in modern times. However， the overemphasis on syndrome differentiation and treatment， coupled with a diminished focus on disease concepts， has led to its gradual alienation as the primary diagnostic and therapeutic model. The alienation mainly manifests as a tendency to prioritize syndrome over disease， resulting in the overgeneralization and limited application of the concept， and causing a lack of specificity in practice. This paper emphasizes that a correct understanding of syndrome differentiation and treatment is a necessary premise for the deve-lopment and improvement of the TCM diagnostic and therapeutic system. By integrating modern medical diagnosis to clarify disease targets and applying TCM thinking to extract common patterns of diseases， precise alignment between syndrome differentiation and treatment and modern clinical demands can be achieved， providing a reference for addressing the contemporary challenges of syndrome differentiation and treatment.

To summarise the clinical experience of Professor TONG Xiaolin in treating prediabetes combined with overweight or obesity using the method of relieving depression and reducing turbidity. It is believed that prediabetes belongs to the category of "spleen-heat syndrome" in traditional Chinese medicine， and its core pathogenesis is center fullness with internal heat， while obesity is the initiating factor for exacerbating center fullness and internal heat， therefore， it is of great significance to reduce the risk of diabetes by interrupting the transformation between overweight， obesity and glucose metabolism abnormality. It is proposed that the main pathogenesis of prediabetes combined with overweight or obesity is qi depression and turbidity obstruction in middle jiao， with qi depression as the root and turbidity obstruction as the cause， forming a treatment idea with the method of relieving depression and reducing turbidity as the core. In clinic， Dahuang Huanglian Xiexin Decoction （大黄黄连泻心汤） is used as the basic prescription， with a primary focus on directing the turbid downward， supplemented by regulating qi， which embodies the concept of "promoting movement through descent， then figuring out the root of spleen-heat syndrome. Furthermore， the treatment is flexibly modified based on the patient's deficiency-excess syndrome to ensure individualized therapy.

Rapid developments in biotechnology have led researchers to seek new method to improve the efficiency and accuracy of biomedical research and drug development,promoting interdisciplinary integration.Recent advancements in artificial intelligence(AI)technologies have brought unprecedented opportunities to this field.The integration of various AI models allows researchers to better utilize multi-omics data,identify disease phenotypes,interpret animal behavior,assess treatment effects,improve experimental designs,reduce the use of experimental animals,enhance animal facility management,and improve animal welfare.This article reviews the advancements in AI biomedical research over the past decade and discusses its contributions to disease phenotype identification,the selection and design of experimental animal models,animal behavior analysis,and animal facility management.It also points out the challenges related to data standardization,AI model selection and interpretability,the extrapolation process from AI models to animal experiments and clinical practice,as well as ethical considerations in using AI in sensitive areas involving human genetics and personalized medicine.This review aims to help researchers and practitioners in relevant fields understand the current state and opportunities of AI development,thus providing support for its broader application.

Environmental pollutants generated by industrialization,characterized by microplastics,are increasingly impairing male fertility in the form of"environmental hidden toxins".Although the concept of environmental toxicity has been proposed for a long time,its practical application remains limited.Therefore,this study innovatively introduces and elaborates on the concept of"environmental hidden toxins",highlighting its pathogenic characteristics,including latency,turbidity,consumptive nature,concurrent nature,and transmutation.Environmental hidden toxin can be classified into five categories based on the properties:stagnation toxins,scorching toxins,turbid toxins,desiccating toxins,and latent toxins.The core pathogenesis of environmental hidden toxins-induced male infertility involves three stages:firstly,invading the lungs and spleen,leading to the gradual depletion of healthy qi;secondly,forming toxin-stasis complexes that obstruct the spermatic pathway;and lastly,penetrating deeply into the seminal chamber,directly damaging the genuine essence.The treatment principle emphasizes"strengthening the foundation and clearing the source,"advocating dual strategies of detoxification and strengthening vital qi.This includes enhancing clarity and lowering turbidity,fortifying the earth to generate metal to replenish healthy qi;resolving stasis,unblocking collaterals,and dispelling toxins to eliminate pathogenic factors;and nourishing the kidneys,replenishing essence,and expelling toxins to preserve the genuine essence.All the above approaches form a holistic traditional Chinese medicine(TCM)strategy that treating both manifestation and root cause of disease.The study provides theoretical foundations and offers novel clinical insights into TCM interventions for male infertility caused by environmental pollutants.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

OBJECTIVE The emergence of evolving variants of Coronavirus disease 2019(COVID-19)has fostered the need for change of newer and adaptive treatments for these infections.During the COVID-19 pandemic and persists,traditional Chinese medicine(TCM)herbs exhibit significant bioactivity and therapeutic effect.This study is aimed to evaluate the efficacy of four TCM preparations on 28-day mortality risk of patients and changes of the laboratory indicators.METHODS The retrospective cohort study included patients with COVID-19 who were admitted to the Jiangsu Province Hospital of Chinese Medicine from December 15,2022 to January 15,2023,and those died within 48 hours of admission or cannot be tracked for outcomes were excluded.The pri-mary outcome was survival status in 28 days(death or survival)starting from the day of admission.The second outcomes were labora-tory indicators,including absolute lymphocyte count,lactate dehydrogenase,creatinine,and blood urea nitrogen.Binary logistic re-gressions were used to estimate the effect of TCM preparations on the primary and secondary outcomes in main analysis.Meanwhile,heterogeneity and robustness of results from main analysis were assessed by subgroup analyses and multiple sensitivity analyses.RESULTS 1 816 eligible patients were included in analysis dataset,including 573 patients received standard care(control group)and 1 243 patients received TCM preparations(hospital preparation group).The 28-day mortality rate of hospital preparation group was lower than that of control group(4.75%vs.14.83%),and the difference was statistically significant(χ2=54.666,P<0.001).The risk of 28-day mortality was 0.535 times lower in the hospital preparation group as compared with the control group(OR=0.46,95%CI:0.305-0.708,P<0.001)showed by multivariable binary logistic regressions.Subgroup analyses showed that taking TCM preparations reduced the 28-day mortality risk.Sensitivity analyses demonstrated that the results of the main analysis for primary outcomes were robust.For secondary outcomes,the risk of abnormal absolute lymphocyte counts at discharge in the hospital prepara-tion group decreased by 0.284 times(OR=0.703,95%CI:0.515-0.961,P=0.027).CONCLUSION Compared with standard of care,taking four hospital preparations including Kanggan Heji,Feining Heji,Qishen Gubiao Keli,and Qianghuo Qushi Qingwen Heji decreased risk of 28-day mortality among hospitalized COVID-19 patients.TCM therapy achieves adequate therapeutic effects in COVID-19.

OBJECTIVE The emergence of evolving variants of Coronavirus disease 2019(COVID-19)has fostered the need for change of newer and adaptive treatments for these infections.During the COVID-19 pandemic and persists,traditional Chinese medicine(TCM)herbs exhibit significant bioactivity and therapeutic effect.This study is aimed to evaluate the efficacy of four TCM preparations on 28-day mortality risk of patients and changes of the laboratory indicators.METHODS The retrospective cohort study included patients with COVID-19 who were admitted to the Jiangsu Province Hospital of Chinese Medicine from December 15,2022 to January 15,2023,and those died within 48 hours of admission or cannot be tracked for outcomes were excluded.The pri-mary outcome was survival status in 28 days(death or survival)starting from the day of admission.The second outcomes were labora-tory indicators,including absolute lymphocyte count,lactate dehydrogenase,creatinine,and blood urea nitrogen.Binary logistic re-gressions were used to estimate the effect of TCM preparations on the primary and secondary outcomes in main analysis.Meanwhile,heterogeneity and robustness of results from main analysis were assessed by subgroup analyses and multiple sensitivity analyses.RESULTS 1 816 eligible patients were included in analysis dataset,including 573 patients received standard care(control group)and 1 243 patients received TCM preparations(hospital preparation group).The 28-day mortality rate of hospital preparation group was lower than that of control group(4.75%vs.14.83%),and the difference was statistically significant(χ2=54.666,P<0.001).The risk of 28-day mortality was 0.535 times lower in the hospital preparation group as compared with the control group(OR=0.46,95%CI:0.305-0.708,P<0.001)showed by multivariable binary logistic regressions.Subgroup analyses showed that taking TCM preparations reduced the 28-day mortality risk.Sensitivity analyses demonstrated that the results of the main analysis for primary outcomes were robust.For secondary outcomes,the risk of abnormal absolute lymphocyte counts at discharge in the hospital prepara-tion group decreased by 0.284 times(OR=0.703,95%CI:0.515-0.961,P=0.027).CONCLUSION Compared with standard of care,taking four hospital preparations including Kanggan Heji,Feining Heji,Qishen Gubiao Keli,and Qianghuo Qushi Qingwen Heji decreased risk of 28-day mortality among hospitalized COVID-19 patients.TCM therapy achieves adequate therapeutic effects in COVID-19.

Rapid developments in biotechnology have led researchers to seek new method to improve the efficiency and accuracy of biomedical research and drug development,promoting interdisciplinary integration.Recent advancements in artificial intelligence(AI)technologies have brought unprecedented opportunities to this field.The integration of various AI models allows researchers to better utilize multi-omics data,identify disease phenotypes,interpret animal behavior,assess treatment effects,improve experimental designs,reduce the use of experimental animals,enhance animal facility management,and improve animal welfare.This article reviews the advancements in AI biomedical research over the past decade and discusses its contributions to disease phenotype identification,the selection and design of experimental animal models,animal behavior analysis,and animal facility management.It also points out the challenges related to data standardization,AI model selection and interpretability,the extrapolation process from AI models to animal experiments and clinical practice,as well as ethical considerations in using AI in sensitive areas involving human genetics and personalized medicine.This review aims to help researchers and practitioners in relevant fields understand the current state and opportunities of AI development,thus providing support for its broader application.