ObjectiveTo establish an animal model of atrial fibrillation（AF） that accurately reflects the phlegm-heat and blood stasis（TRYZ） pathogenesis in traditional Chinese medicine. MethodsForty SPF-grade SD rats were randomly assigned using a random number table to the following groups：the control group， the TRYZ+AF group，the AF group and the TRYZ group， with ten rats in each group. The TRYZ+AF and TRYZ groups underwent a high-fat diet combined with intraperitoneal lipopolysaccharide（LPS） injection to simulate the pathological alterations of TRYZ syndrome. Groups TRYZ+AF and AF were induced with acetylcholine-calcium chloride（Ach-CaCl₂） via caudal vein injection to induce AF. The control group received no intervention and was maintained under normal conditions. The modeling period lasted 3 weeks. Electrocardiography was used to assess AF episodes and duration， echocardiography evaluated left atrial dimensions and cardiac function， fully automated biochemical analyzer measured the levels of total cholesterol（TC）， triglycerides（TG）， high-density lipoprotein cholesterol（HDL-C） and low-density lipoprotein cholesterol（LDL-C）， hemoreometer analyzed the whole blood viscosity， plasma viscosity， and whole blood reduced viscosity， a coagulation analyzer assessed prothrombin time（PT）， activated partial thromboplastin time（APTT）， thrombin time（TT）， and fibrinogen（FIB）， enzyme-linked immunosorbent assay（ELISA） was used to determine the levels of C-reactive protein（CRP）， interleukin（IL）-1β， IL-6， IL-17， tumour necrosis factor（TNF）-α， matrix metalloproteinase-9（MMP-9）， galectin-3（Gal-3）， Collagen Ⅰ， and α-smooth muscle actin（α-SMA）. Hematoxylin-eosin（HE） staining and Masson's trichrome staining were used to analyze pathological changes in atrial myocardium， Western blot was employed to detect MMP-9， Collagen Ⅰ and α-SMA protein expression in myocardial tissue， real-time quantitative polymerase chain reaction（Real-time PCR） evaluated fibrous factor gene expression levels. Changes in the TRYZ syndrome were assessed via body weight， tongue color［red（R）， green（G）， and blue（B）］， and rectal temperature. Ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was employed to detect differential metabolites between the control group and the TRYZ+AF group. ResultsFollowing three weeks of sustained modeling， compared with the control group， rats in the TRYZ+AF and the TRYZ groups exhibited reduced body weight， dry faeces， elevated rectal temperature， dark red tongue， decreased RGB values on the tongue surface， and markedly elevated TC and LDL-C levels（P<0.05， P<0.01）. The TRYZ+AF， TRYZ， and AF groups exhibited significantly decreased TT， APTT and PT， along with markedly elevated whole blood viscosity and FIB（P<0.05， P<0.01）. Rats in the TRYZ+AF and AF groups exhibited AF rhythm， markedly decreased heart rate， prolonged RR intervals， enlarged left atrium， and significantly reduced ejection fraction and shortening fraction（P<0.05， P<0.01）. Serum levels of CRP， IL-1β， IL-6， IL-17， TNF-α， MMP-9， Gal-3， Collagen Ⅰ， and α-SMA were elevated in rats from the TRYZ+AF， TRYZ， and AF groups compared to the control group， with the most pronounced increase observed in the TRYZ+AF group（P<0.05， P<0.01）. Histopathology revealed that the collagen fiber deposition in the atrial of rats in the TRYZ+AF， TRYZ and AF groups was higher than that in the control group（P<0.05， P<0.01）. Western blot and Real-time PCR results further demonstrated that the protein and mRNA expression levels of MMP-9， Collagen Ⅰ and α-SMA in the myocardial tissue of the TRYZ+AF group were higher than those in the other three groups（P<0.05， P<0.01）. Metabolomic analysis revealed 173 differentially expressed metabolites in the TRYZ+AF group and the control group， primarily enriched in pathways such as glycerophospholipid metabolism and glycolysis/gluconeogenesis. ConclusionThis study successfully establishes a rat model of AF integrated with the TRYZ syndrome， demonstrating the pathological process where the interactions of phlegm， heat and stasis jointly trigger tremor， this provides a reliable experimental tool for in-depth research into the biological basis of this disease syndrome.

To thoroughly implement the strategic deployment outlined in the Opinions of the Central Committee of the Communist Party of China and the State Council on Promoting the Inheritance and Innovative Development of Traditional Chinese Medicine regarding research on dominant diseases of traditional Chinese medicine and to uphold the development philosophy of equal emphasis on traditional Chinese medicine and western medicine，the China Association of Chinese Medicine has fully played a leading academic role by systematically organizing and conducting a series of academic youth salons on clinical dominant diseases of traditional Chinese medicine. On September 13，2024，the 36^th Youth Salon on Clinical Dominant Diseases was successfully held in Nanjing，focusing on the advantages of traditional Chinese medicine and the integrative traditional Chinese medicine and western medicine in the diagnosis and treatment of erectile dysfunction （ED）. The conference brought together leading experts from traditional Chinese medicine，western medicine，and interdisciplinary fields，facilitating in-depth multidisciplinary discussions that led to key consensus on optimizing traditional Chinese medicine treatment protocols for ED，researching and developing new drugs of traditional Chinese medicine，and advancing interdisciplinary development in traditional Chinese medicine. This salon systematically sorted out the clinical strengths and distinctive features of traditional Chinese medicine in the diagnosis and treatment of ED. Based on current research foundations and clinical needs，it identified key directions for future scientific layout and scientific research tackling： （1） Standardization of syndrome differentiation system of traditional Chinese medicine for ED. （2） Optimization and standardization of intervention methods of integrated traditional Chinese medicine and western medicine. （3） High-quality clinical research guided by evidence-based medicine. （4） In-depth analysis of the pharmacological mechanisms of traditional Chinese medicine in the treatment of ED. （5） Clinical translation and application promotion of new drugs of traditional Chinese medicine. （6） Interdisciplinary integration and innovation in traditional Chinese medicine. For each research direction，key focus areas，expected objectives，and clinical value were further refined，along with the establishment of a scientifically sound priority funding level evaluation system. Therefore，building on the series of salons on the ED-focused dominant diseases of traditional Chinese medicine，this paper provides standardized guidance for clinical practice of traditional Chinese medicine in ED management，effectively contributing to the high-quality development of traditional Chinese medicine. It serves as a valuable reference for national scientific and technological strategic layout， research and development decision-making in new drugs of traditional Chinese medicine，research topic planning，and clinical guideline formulation.

Health economics evidence plays an important role in linking clinical value evidence with health resource allocation decisions in the development of clinical practice guidelines. It can not only effectively balance clinical effectiveness and economic feasibility but also avoid forming "idealized" recommendations that are detached from the affordability of the healthcare system or the burden-bearing capacity of patients. To promote guideline developers to use health economics evidence more standardizedly and fully, this paper conducts an in-depth analysis of the current application status, existing challenges, access channels, and application processes of health economics evidence in current guidelines, and on this basis, puts forward considerations and suggestions for strengthening and standardizing the application of health economics evidence in China's clinical practice guidelines.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Background: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Background: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.

Background: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.