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.

Hygroscopicity research has long been a key focus and hot topic in Chinese materia medica（CMM）. Elucidating hygroscopic mechanisms plays a vital role in formulation design， process optimization， and storage condition selection. Hygroscopic models serve as essential tools for characterizing CMM hygroscopic mechanisms， with various types available. The double exponential model is a kinetic mathematical model constructed based on the law of conservation of energy and Fick's first law of diffusion， tailored to the physical properties of CMM extracts. In recent years， this model has been extensively applied to simulate the dynamic moisture absorption behavior of CMM extracts and solid dosage forms under varying humidity conditions. It has revealed the correlation between moisture absorption kinetic parameters and material properties， offering a new perspective for characterizing the moisture uptake behavior of CMM. This paper systematically reviews the application progress of this model in the field of CMM， analyzes its advantages， disadvantages， and challenges in this domain， and explores its potential application trends in other fields. It aims to provide references for elucidating the moisture absorption mechanisms of CMM and researching moisture-proofing technologies， while also offering insights for its broader application in food and polymer materials.

To systematically analyzed the reporting status of core elements in publicly available clinical practice guideline(hereafter referred to as "guideline") protocols published domestically and internationally over the past decade, identified existing problems, and provided evidence to inform the standardized writing and publication of future guideline protocols.

Objective: To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents. Methods: A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model. Results: The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05). Conclusion The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.

Objective: To explore the impact of donor reentry experience, specifically among those with a single reactive serological result who completed the reentry process, on their willingness to return for future blood donation, and to examine the mediating roles of blood donation knowledge and trait anxiety. Methods: A cross-sectional survey was conducted between November and December 2025. A total of 386 blood donors from the Changsha Blood Center were categorized into a reentry group (n=123) and a control group (n=263). Data on demographic characteristics, blood donation knowledge (BDKQ), trait anxiety (STAI-T), and blood donation return intention (BDRIS) were collected via questionnaires. SPSS 27.0 and AMOS 28.0 were used for statistical analyses, including independent-samples t-test, one-way ANOVA, multiple linear regression, and path analysis for mediating effect testing. Results: There were statistically significant differences in age, occupation, education level, monthly income and donation frequency between the reentry group and the control group (all P<0.05). The reentry group scored significantly higher in blood donation knowledge and blood donation return intention than the control group (both P<0.05). The mean BDRIS score was 11.51±3.62, indicating a relatively high intention to return. Blood donation knowledge was significantly negatively correlated with trait anxiety (r=-0.15, P<0.05) and positively correlated with blood donation return intention (r=0.19, P<0.05); trait anxiety was significantly negatively correlated with blood donation return intention (r=-0.33, P<0.05). Significant differences in BDRIS scores were found based on group (reentry vs control), age, and number of previous donations (all P<0.05). Multiple linear regression showed that BDKQ positively predicted BDRIS (β=0.11, P<0.05), while STAI-T negatively predicted BDRIS (β=-0.27, P<0.05). Path analysis further revealed that the reentry experience had no direct effect on the intention to return. However, it exerted a positive influence through two indirect pathways: 1) a simple mediating effect via increased blood donation knowledge (β=0.17, accounting for 25.0% of the total effect), and 2) a chain mediating effect through "increased blood donation knowledge → decreased trait anxiety" (β=0.05, accounting for 8.1% of the total effect). The model fit indices reached the ideal fitting criteria. Conclusion: The donor reentry experience does not directly enhance the intention to return for blood donation. Rather, it may exert an indirect positive influence by increasing blood donation knowledge and through the sequential pathway of "increased knowledge → decreased trait anxiety". Blood collection institutions should leverage the reentry process as an opportunity for education and psychological support to improve donor retention rate.

Objective To apply an artificial intelligence (AI) -based pelvic floor optimization training system using human motion analysis technique in patients undergoing pelvic floor rehabilitation, so as to assist clinicians in providing guidance, improving clinical efficiency, and enhancing the efficacy of patients' independent training. Methods A total of 60 patients with overactive bladder (OAB) complicated with urgent urinary incontinence (UUI) treated in our hospital during Sep. 2024 and Dec. 2025 were enrolled and randomly divided into the routine guidance group (n=30) and AI guidance group (n=30). The routine guidance group received conventional pelvic floor optimization training under clinicians' instruction, while the AI guidance group underwent training with the AI-based pelvic floor optimization system using human motion analysis. After 6 weeks of intervention, outcomes were compared between the two groups, including the international consultation on incontinence questionnaire-short form (ICI-Q-SF), incontinence quality of life scale (I-QoL), overactive bladder symptom score (OABSS), patient's perception of bladder condition (PPBC) score, pelvic floor muscle function (myoelectric values in the preresting, post-resting, type Ⅰ muscle, type Ⅱ muscle, and endurance test phases), urine output, average flow rate (Qavg), and maximum flow rate (Qmax). Results After 6 weeks of treatment, the ICI-Q-SF, I-QoL, OABSS, PPBC score, type I muscle myoelectric value, Qavg and Qmax were significantly improved in both groups compared with baseline (P＜0.05). After 6 weeks of intervention, the I-QoL score was significantly higher in the AI guidance group than in the routine guidance group[81.82 (79.55, 84.38) vs.77.84 (75.00, 79.55) ], with significant difference (P＜0.05). Compared with the routine guidance group, the AI guidance group showed significant improvements in myoelectric values in the pre-resting, post-resting, type I muscle and endurance testing phases (P＜0.05). Conclusion The AI-based pelvic floor optimization training system can effectively assist clinicians in guiding patients to complete pelvic floor optimization training, improve rehabilitation efficiency and efficacy of independent exercise, and reduce dependence on specialized clinicians, which exhibits favorable safety.

Objective: To understand the prevalence and related factors of depressive symptoms among primary and secondary school students in the in depth monitoring counties of China s Rural Compulsory Education Nutrition Improvement Program, so as to provide a basis for prevention and psychological intervention of depressive symptoms among children and adolescents in rural areas. Methods: In November 2022, a stratified random sampling method was adopted to collect height and weight data, basic personal and family information of 7 949 primary and secondary school students from grade three to grade nine through physical measurements and questionnaires in 56 key monitoring schools implementing the Student Nutrition Improvement Program in 7 in depth monitoring counties (Jalaid Banner in Inner Mongolia, Jinzhai County in Anhui, Mao Xian in Sichuan, Tiandeng County in Guangxi, Mian County in Shaanxi, Zhaozhou County in Heilongjiang and Youxi County in Fujian), and to obtain the information related to their depressive symptoms through the self assessment questionnaire on depression. Multivariate Logistic regression analysis was conducted to analyze the prevalence of depressive symptoms among primary and secondary school students, as well as their related factors. Results: The detection rate of depressive symptoms among primary and secondary school students in the in depth monitored counties was 23.5%. Logistic regression analysis showed that the probability of detecting depressive symptoms was higher among female students, middle school students, students whose video screen duration per day was >2 h, and students whose parents marital status was divorced or widowed ( OR =1.40, 1.64, 1.60, 1.24), and students whose sleep duration reached the recommended standard, whose parents usually accompanied them daily for time was 60-<120 min and ≥120 min, and students whose mothers literacy level was middle school graduation had lower probability of detecting depressive symptoms ( OR =0.85, 0.84, 0.71, 0.76) ( P < 0.05 ). Conclusion The detection rate of depressive symptoms among students in the in depth monitoring area is high, and targeted interventions need to be developed for students to reduce the risk of mental health problems.

ObjectiveTo explore the potential mechanisms of Leigongteng （Tripterygium wilfordii Hook. f.） in treating rheumatoid arthritis （RA） using bioinformatics analysis and experimental validation. MethodsBioinformatics approaches， including the Gene Expression Omnibus （GEO）， the traditional Chinese medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Gene Ontology （GO） enrichment analysis， Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment， protein-protein interaction （PPI） network analysis， molecular docking， receiver operating characteristic （ROC） analysis， and immune infiltration analysis， were used to predict the key active components of Leigongteng and its target genes for RA treatment. Experimental validation was conducted using human rheumatoid arthritis fibroblast-like synoviocytes （HFLS-RA） in vitro， with methotrexate as the positive control. A scratch assay was performed to assess cell migration after 24 hours of culture. Western blotting was used to detect protein expression levels， qPCR was used to measure target gene mRNA levels， and ELISA was conducted to evaluate inflammatory cytokine levels， including interleukin-1β （IL-1β）， interleukin-6 （IL-6）， interleukin-10 （IL-10）， and tumor necrosis factor-α （TNF-α）. ResultsA total of 117 target genes of Leigongteng were identified and intersected with RA-related genes， yielding 55 key genes. Further screening identified three core genes： PTGS2， CXCR4， and TIMP1. Based on the correspondence between potential drug targets and key components， triptolide and nobiletin were identified as the primary active compounds. Molecular docking results showed that both triptolide and nobiletin had binding energies lower than -5 kcal/mol with their respective target proteins， indicating strong interactions. In vitro experiments demonstrated that， compared with the blank control group， the triptolide， nobiletin， and positive control groups exhibited reduced cell migration rates after 24 hours of culture （P＜0.01）. The expression levels of PTGS2 and CXCR4 （both mRNA and protein） were significantly downregulated， while TIMP1 expression was upregulated. Levels of IL-1β， IL-6， and TNF-α decreased， whereas IL-10 levels increased （P＜0.01）. Compared with the positive control group， the triptolide and nobiletin groups showed increased cell migration rates， upregulated PTGS2 and CXCR4 expression （mRNA and protein）， downregulated TIMP1 expression （mRNA and protein）， increased IL-1β， IL-6， and TNF-α levels， and decreased IL-10 levels （P＜0.05 or P＜0.01）. ConclusionThe key active components of Leigongteng， triptolide and nobiletin， may alleviate RA by inhibiting PTGS2 and CXCR4 while promoting TIMP1 expression， thereby suppressing inflammatory responses.

Objective:To explore the diagnostic value of combining Ki67, molecular subtyping, and ultrasonographic parameters in predicting axillary lymph node metastasis in breast cancer.Methods:200 breast cancer patients who were admitted to Meizhou People’s Hospital from Jan. 2020 to Dec. 2022 were collected. Based on the presence or absence of axillary lymph node metastasis in breast cancer, the patients were divided into an axillary lymph node metastasis group and a non-axillary lymph node metastasis group. Age, clinical stage, tumor location, tumor size, degree of differentiation, boundary, blood flow, echo, calcification, morphology, vascular invasion, Ki67, molecular typing, resistance index (RI) , shear wave velocity were collected. Multivariate Logistic regression analysis was used to screen the risk factors for axillary lymph node metastasis of breast cancer, and receiver operating characteristic curve (ROC) was used to evaluate the clinical value of ki67, molecular typing combined with ultrasound parameters in the diagnosis of axillary lymph node metastasis of breast cancer.Results:There were no statistically significant differences in age, clinical stage, tumor location, tumor size, differentiation degree, boundary, blood flow, echo or calcification between the axillary lymph node metastasis group and the non-axillary lymph node metastasis group ( t=0.80, χ20.13, χ2=0.14, χ2=0.90, χ2=0.64, χ2=1.03, χ2=0.04, χ2=0.34, χ2=1.2, P>0.05) , while there were statistically significant differences in morphology, vascular invasion, Ki67, molecular classification, RI and shear wave velocity between the two groups ( χ2=12.01, χ2=8.75, χ2=11.36, χ2=11.43, t=6.34, t=7.25, P<0.05) . Multivariate Logistic regression analysis showed that vascular invasion, Ki67 high expression, triple negative breast cancer, RI and shear wave velocity were all risk factors for axillary lymph node metastasis ( OR=5.572,4.026,3.632,107.639,1.936, P<0.05) . ROC curve analysis results showed that the AUC of Ki67, molecular typing, RI and shear wave velocity in the diagnosis of axillary lymph node metastasis of breast cancer was 0.620, 0.594, 0.744 and 0.792, respectively, and the AUC of Ki67, molecular typing, RI and shear wave velocity in the diagnosis of axillary lymph node metastasis of breast cancer was 0.846. The AUC of the combination of Ki67, molecular typing, RI and shear wave velocity in the diagnosis of axillary lymph node metastasis of breast cancer was higher than that of Ki67, molecular typing, RI and shear wave velocity alone ( Z=5.55,7.10,3.44,2.45, P<0.05) . Conclusions:High Ki67 expression, triple-negative breast cancer, lymphovascular invasion,RI, and shear wave velocity are all risk factors for axillary lymph node metastasis in breast cancer. The combined use of Ki67, molecular subtype, RI, and shear wave velocity can improve the diagnostic accuracy for axillary lymph node metastasis in breast cancer.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.