Chronic heart failure （CHF） is a complex clinical syndrome caused by ventricular dysfunction， with mitochondrial energy metabolism disorder being a critical factor in disease progression. Heart-Yang deficiency syndrome， as the core pathogenesis of CHF， persists throughout the disease course. Insufficiency of heart-Yang leads to weakened warming and propelling functions， resulting in the accumulation of phlegm-fluid， blood stasis， and dampness. This eventually causes Qi stagnation with phlegm obstruction and blood stasis with water retention， forming a vicious cycle that exacerbates disease progression. According to the theory of reinforcing Yang， the clinical experience of the traditional Chinese medicine （TCM） master Tang Zuxuan in treating CHF with heart-Yang deficiency syndrome， and achievements from molecular biological studies， this study innovatively proposes an integrated research framework of "TCM syndrome differentiation and staging-mitochondrial metabolism mechanisms-intervention with Yang-reinforcing prescriptions" which is characterized by the integration of traditional Chinese and Western medicine. Heart-Yang deficiency syndrome is classified into mild （Stage Ⅰ-Ⅱ）， severe （Stage Ⅲ）， and critical （Stage Ⅳ） stages. The study elucidates the precise correlations between the pathogenesis of each stage and mitochondrial metabolism disorders from theoretical， pathophysiological， and therapeutic perspectives. The mild stage is characterized by impaired biogenesis and substrate-utilization imbalance， corresponding to heart-Yang deficiency and phlegm-fluid aggregation. Linggui Zhugantang and similar prescriptions can significantly improve the expression of peroxisome proliferator-activated receptor gamma co-activator-1α（PGC-1α）/silent information regulator 2 homolog 1 （SIRT1） and ATPase activity. The severe stage centers on oxidative stress and structural damage， reflecting Yang deficiency with water overflow and phlegm-blood stasis intermingling. At this stage， Zhenwu Tang and Qiangxin Tang can effectively mitigate oxidative stress damage， increase adenosine triphosphate （ATP） content， and repair mitochondrial structure. The critical stage arises from calcium overload and mitochondrial disintegration， leading to the collapse of Yin-Yang equilibrium. At this stage， Yang-restoring and crisis-resolving prescriptions such as Fuling Sini Tang and Qili Qiangxin capsules can inhibit abnormal opening of the mitochondrial permeability transition pore （MPTP）， reduce cardiomyocyte apoptosis rate， and protect mitochondrial function. By summarizing the characteristics of mitochondrial energy metabolism disorders at different stages of CHF， this study explores the application of the theory of reinforcing Yang in treating heart-Yang deficiency syndrome and provides new insights for the clinical diagnosis and treatment of CHF.

ObjectiveTo explore the mechanism of ventricular remodeling mediated by the p38 mitogen-activated protein kinase （MAPK）/nuclear factor kappa B （NF-κB） signaling pathway in the rat model of chronic heart failure （CHF） with heart-blood stasis syndrome， as well as the intervention effect of Danhong injection. MethodsIn vivo experiment： SPF-grade male SD rats were assigned via the random number table method into 4 groups： Sham operation， model， captopril （8.8 mg·kg^-1）， and Danhong injection （6.0 mL·kg^-1）. The model of CHF with heart-blood stasis syndrome was established by abdominal aortic constriction， and the sham operation group only underwent laparotomy without constriction. All the groups were treated continuously for 15 days. The tongue color of rats was observed. Echocardiography， hemorheology， heart mass index （HMI）， and left ventricular mass index （LVMI） were measured. Hematoxylin-eosin （HE） staining and Masson staining were performed to observe the pathological and fibrotic changes of the myocardial tissue. Enzyme-linked immunosorbent assay （ELISA） was employed to quantify the levels of N-terminal pro-B-type natriuretic peptide （NT-proBNP）， interleukin-6 （IL-6）， angiotensin Ⅱ （AngⅡ）， tumor necrosis factor-α （TNF-α）， and Creactive protein （CRP） in the serum， as well as the levels of matrix metalloproteinase-2 （MMP-2） and matrix metalloproteinase-9 （MMP-9） in the myocardial tissue. Western blot was used to quantify the protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 in the myocardial tissue. In vitro experiment： H9C2 cardiomyocytes were treated with 1×10^-6 mol·L^-1 AngⅡ to establish a model of myocardial hypertrophy. H9C2 cardiomyocytes were allocated into normal， model， inhibitor + Danhong injection， Danhong injection （20 mL·L^-1）， and inhibitor （SB203580， 5 μmol·L^-1） groups. CCK-8 assay was used to detect the viability of H9C2 cardiomyocytes. Rhodamine-labeled phalloidin staining was used to reveal the area of cardiomyocytes. Real-time PCR was performed to determine the mRNA levels of atrial natriuretic peptide （ANP） and brain natriuretic peptide （BNP）. Western blot was used to assess the protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65. ResultsIn vivo experiment： Compared with the sham operation group， the model group showed purplish-dark tongue with decreased R， G， B values of the tongue surface （P<0.01）， increased whole blood viscosity （at low， medium， and high shear rates） （P<0.01）， decreased left ventricular ejection fraction （LVEF） and left ventricular fractional shortening （LVFS） （P<0.01）， increased left ventricular end-diastolic diameter （LVIDd）， left ventricular end-systolic diameter （LVIDs）， and left ventricular posterior wall thickness at end-diastole （LVPWd） （P<0.01）， raised LVMI and HMI （P<0.01）， and elevated levels of NT-proBNP， TNF-α， IL-6， and CRP in the serum and MMP-2 and MMP-9 in the myocardial tissue （P<0.01）. The HE and Masson staining of the myocardial tissue showed compensatory myocardial hypertrophy， fibrosis， and massive inflammatory cell infiltration in the model group. Additionally， the model group presented up-regulated protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 in the myocardial tissue （P<0.01）. Compared with the model group， each administration group showed increased R， G， B values of the tongue surface （P<0.05， P<0.01）， decreased whole blood viscosity （at low， medium， and high shear rates） （P<0.05， P<0.01）， increased LVEF and LVFS （P<0.01）， decreased LVIDd， LVIDs， and LVPWd （P<0.05， P<0.01）， declined LVMI and HMI （P<0.05， P<0.01）， and lowered levels of NT-proBNP， TNF-α， IL-6， and CRP in the serum and MMP-2 and MMP-9 in the myocardial tissue （P<0.01）. HE and Masson staining showed alleviated compensatory myocardial hypertrophy， reduced fibrosis， and decreased expression of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 in the myocardial tissue （P<0.01）. In vitro experiment： When the concentration of Danhong injection reached 20 mL·L^-1， the survival rate of H9C2 cardiomyocytes was the highest （P<0.01）. Compared with the normal group， the model group showed up-regulated mRNA levels of ANP and BNP （P<0.01）， increased relative cell surface area （P<0.01）， and raised protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 （P<0.01）. Compared with the model group， each administration group showed down-regulated mRNA levels of ANP and BNP （P<0.01）， reduced relative cell surface area （P<0.05， P<0.01）， and down-regulated protein levels of p-p38 MAPK/p38 MAPK and p-NF-κB p65/NF-κB p65 （P<0.05， P<0.01）. ConclusionDanhong injection can regulate ventricular remodeling through the p38 MAPK/NF-κB pathway， thereby exerting a protective effect on the rat model of CHF with heart-blood stasis syndrome.

Objective: To investigate the current status and related factors of human papillomavirus (HPV) vaccination intention among male college students in Shanghai, so as to provide references for promoting HPV vaccination among males. Methods: From January to February 2025, a stratified random cluster sampling method was used to select 548 male college students in 10 universities from Shanghai for a self questionnaire survey. The survey included socio demographic characteristics, vaccine hesitancy, vaccine beliefs (complacency, confidence, convenience), HPV knowledge level, health status, social support, and information acquisition channels. Latent class analysis (LCA) was used to identify latent classes of vaccine beliefs, and multinomial Logistic regression was used to analyze the related factors of vaccination intentions. Results: The acceptance, hesitancy, and refusal rates of HPV vaccine among college students in Shanghai were 39.4% ( n =216), 35.2% ( n =193), and 25.4% ( n =139), respectively. LCA identified four vaccine belief groups: low complacency high confidence (21.4%), high complacency high confidence (36.1%), low complacency low confidence (18.8%), and high complacency low confidence (23.7%). Multinomial Logistic regression showed that vaccine belief category was an important factor affecting vaccination intentions among college students in Shanghai. Compared with the low complacency high confidence group, high complacency low confidence group had the highest risk of vaccine refusal ( OR =24.80， P <0.05). Medical majors ( OR =0.13), participation in basic medical insurance ( OR =0.37), and recommendations from relatives, friends ( OR =0.39) or healthcare professionals ( OR =0.33) reduced the risk of vaccine refusal among male college students in Shanghai (all P <0.05). The Internet (70.6%) was the main source of HPV related information for male college students, and recommendations from healthcare professionals were associated with more positive vaccination intentions. Conclusions HPV vaccine hesitancy and refusal are common among male college students in Shanghai, with significant heterogeneity in vaccine belief structures. Targeted health education based on belief categories should be conducted to improve the vaccination intentions of male college students.

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.

ObjectiveTo investigate the effect of nicotinamide adenine dinucleotide on vascular endothelial injury in hypertension and its molecular mechanism. MethodsC57BL/6J mice were randomly divided into saline group （Saline） and hypertension group （Ang Ⅱ， which were infused with Ang Ⅱ via subcutaneously implanted osmotic pumps）， and supplemented daily with nicotinamide mononucleotide （300 mg/kg）， a precursor of NAD⁺. Blood pressure， endothelial relaxation function and pulse wave velocity were measured after 4 weeks. Wound healing assay and adhesion assay were used to evaluate the function of endothelial cells in vitro. mtROS levels were detected by immunofluorescence staining. RT-PCR was used to detect the mRNA expression of mtDNA， SIRT3 and isocitrate dehydrogenase 2 （IDH2）. 8-hydroxy-2'-deoxyguanosine levels were detected by enzyme-linked immunosorbent assay. The protein expression levels of p-eNOS， eNOS， SIRT3 and IDH2 were detected by Western blot. ResultsNMN supplementation reduced blood pressure （P<0.001） and improved endothelial function and arterial stiffness （P<0.001） in hypertensive mice. In vitro， NMN improved endothelial function in AngII-stimulated endothelial cells （P<0.05） and attenuated mitochondrial oxidative stress levels （P<0.001）. Mechanistically， NMN elevated SIRT3 activity （P<0.001）， which subsequently enhanced IDH activity （P<0.001） and reduced oxidative stress levels in endothelial cells. Conversely， knockdown of IDH2 would reverse the effect of SIRT3 in improving endothelial function （P<0.001）. ConclusionNAD⁺ lowers blood pressure and enhances vascular function in hypertension by reducing the level of oxidative stress in endothelial cells through activation of the SIRT3/IDH2 signal pathway.

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.

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.

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.