BACKGROUND:Liver carcinoma, as a major global health concern due to its high incidence and mortality rates. Despite advancements in diagnostic and treatment methodologies, outcomes for hepatocellular carcinoma remain unsatisfactory. In response to these limitations, patients increasingly turn to alternative therapies such as traditional Chinese medicine, which has demonstrated potential in enhancing quality of life and prolonging survival in combination with conventional treatments. Triptolide (TP) and quercetin, as two broad-spectrum antitumor activities, act through multiple mechanisms, and whether the combination of them can provide a synergistic effect to improve the treatment effect. To optimize the dosage combination of TP and quercetin to maximize their therapeutic benefits in treating liver cancer, potentially advancing the field of drug combination therapy. This approach seeks to explore new treatment strategies and elucidate the underlying mechanisms that could lead to improved outcomes for hepatocellular carcinoma patients facing limited effective treatment options. AIM:To investigate the synergistic anti-hepatoma effect of TP and quercetin and elucidate the underlying molecular mechanism involving the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and mammalian target of rapamycin (mTOR) signaling pathways. METHODS:The study utilized 5-week-old female BALB/c-nu mice for establishing a liver cancer subcutaneous transplant tumor model. TP and quercetin were administered intraperitoneally over 21 days to evaluate the effectiveness of the combination, with monitoring of tumor growth. IncuCyte Zoom and CompuSyn software were employed to analyze drug effects for different dose combination on cell proliferation and synergy. Various assays such as CCK-8 cell proliferation analysis, plate cell clone formation, cell scratch experiments, Transwell migration and invasion assays, Annexin V-FITC flow cytometry, and western blotting using specific antibodies were employed to assess cell apoptosis, migration, invasion. Then transcriptome analysis was used RNA sequencing to find the potential synergistic mechanisms and proved by western blotting. RESULTS:In vivo, the combination therapy significantly slowed down tumor growth compared to the control group, quercetin alone group, and TP alone group. The tumor inhibition rates were 28.91% (quercetin), 28.8% (TP), and 59.3% (combination therapy), respectively. The determination of IncuCyte Zoom and CCK-8 confirmed that there is a concentration gradient and time gradient effect on tumor inhibition, with the synergistic effect of 25 nmol/L TP and 100 μmol/L quercetin being the best. Platelet cell clone formation and cell wound scratch assay showed that the combination group had better inhibitory effects. Transwell analysis showed a decrease in migration and invasion in the combination therapy group. Flow cytometry showed that over time, cell apoptosis increased after combination therapy. Transcriptome analysis emphasizes unique pathways influenced by the combination (JAK-STAT and mTOR signaling pathways) and has been validated at the protein level. CONCLUSION:Compared with a single drug, the specific metering combination of TP and quercetin has enhanced anti-tumor effects, mediated by inhibition of cell proliferation, inducing cell apoptosis and inhibiting migration/invasion. This synergistic effect is closely related to the simultaneous inhibition of signaling pathways JAK-STAT and mTOR concurrently.

BackgroundRecurrent angina pectoris following coronary revascularization via percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) poses significant clinical challenges, associated with reduced quality of life and increased healthcare burden. Traditional risk tools have limitations in predicting short-term recurrence. This study aimed to develop and validate a machine learning (ML) predictive model for post-revascularization angina (PRA).MethodsThis study used patient data from 38 clinical research centers in 23 provinces of China from 2016 to 2018. Data from 626 patients in a derivation cohort recruited from 28 centers across 16 Chinese provinces and 127 in an external validation cohort from another 10 centers across 10 provinces were analyzed. The Boruta algorithm selected key features, and eight ML models were trained on 70% of the derivation cohort, internally validated on 30%, and externally validated. Performance metrics included area under the curve (AUC), decision curve analysis (DCA), accuracy, sensitivity, specificity, and F1 score. The Shapley Additive explanation (SHAP) values provided model interpretability.ResultsThe Boruta algorithm selected six features: New York Heart Association (NYHA) classification, cardiac troponin T (cTnT), prothrombin time (PT), depression severity, abdominal circumference, and diastolic blood pressure (DBP). The Random forest (RF) model outperformed others, achieving an AUC of 0.90 (accuracy 0.88, sensitivity 0.77, specificity 0.92, F1 0.78) in internal validation and 0.87 in external validation. The SHAP algorithm confirmed the features’ predictive importance, with higher NYHA class, elevated cTnT, and depression severity positively influencing PRA risk.ConclusionsThis RF model offers a robust, interpretable tool for early PRA risk stratification, integrating cardiac, hemostatic, psychological, and metabolic factors. It supports personalized post-revascularization care, though prospective, multi-ethnic validation is needed to enhance generalizability.

BackgroundThe association between air temperature and angina has been confirmed by several studies, which show that some patients with cardiovascular disease are “heat sensitive” and experience angina more frequently in high-temperature environments. Although several predictive models for cardiovascular risk stratification and angina-related outcomes have been reported, predictive tools specifically designed to identify susceptibility to heat-sensitive angina (HSA) exacerbation under hot weather conditions remain limited.MethodsThe derivation cohort consisted of 1,246 individuals with stable angina treated at 43 clinical research centers in China. Variable selection was performed using the Boruta algorithm. Seven machine learning algorithms were developed and evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, F1 score, calibration analysis, and decision curve analysis. An independent external validation cohort comprising 120 patients from 5 additional clinical research centers was used to assess model generalizability. Furthermore, we conducted a post hoc analysis of a multi-center clinical trial to validate the value of the model in guiding clinical strategies.ResultsThrough variable selection, 14 predictors were included as the risk factors to develop ML model. A random forest (RF) model demonstrated strong performance during the training and internal validation cohorts. External validation further supported the RF model's predictive performance and robustness. Exploratory post hoc analysis suggested that patients identified by the RF model as having high HSA probability exhibited increased angina frequency during summer months.ConclusionsThis study innovatively employs region, MPA, DBP, BMI, constipation, body fat distribution indicators, and seven serological markers related to inflammation, lipid metabolism to construct an RF model. The proposed RF model demonstrated promising predictive performance for identifying patients with potential susceptibility to HSA. The model may serve as an exploratory decision-support tool for individualized heat-related cardiovascular risk assessment, although further prospective multicenter validation is required before routine clinical application.Clinical Trial Registrationhttps://www.chictr.org.cn/showproj.html?proj=166685, identifier ChiCTR2200060267 and https://clinicaltrials.gov/study/NCT02967718?term=NCT02967718&rank=1, identifier NCT02967718.

ETHNOPHARMACOLOGICAL RELEVANCE:Chronic hepatitis B virus (HBV) infection is still a widespread global health issue. HuaganJiedu Decoction (HGJDD) is a common prescription for treating HBV in China, which has the effect of enhancing antiviral efficacy and improving clinical efficacy. However, its precise mechanism of action remains unclear, warranting further investigation to elucidate its therapeutic potential and integration into standard medical practices. AIM OF THE STUDY:This study aims to explore the therapeutic mechanism of HuaganJiedu Decoction (HGJDD) in HBV. MATERIALS AND METHODS:We investigated the therapeutic potential of HGJDD, and LC-MS analysis characterized the chemical profile of HGJDD. In vitro, we utilized HepG2.2.15 cell line to assess cytotoxicity and treatment efficacy of HGJDD compared to Entecavir controls. In vivo, assessments included monitoring HBV-related biomarkers and viral load. Network pharmacology and RNA-seq analyses identified molecular pathways and targets influenced by HGJDD treatment. Immunofluorescence and Western blotting provided further insights into the therapeutic mechanisms underlying HGJDD for HBV. RESULTS:HGJDD showed no toxicity on HepG2.2.15 cells at 10%, 20%, 40%, and 80% serum concentrations. In vitro, HGJDD reduced HBsAg, HBeAg, and HBV DNA levels by dose-dependently and time-dependently. HGJDD can decrease the levels of HBsAg, HBeAg, and HBV DNA in serum and liver levels, meanwhile the therapeutic effect of high-dose HGJDD approach to EVT's in HBV Tg mice. According to intersection of network pharmacology and transcriptome, FOXO signal pathway was highlighted as potential targets and Immunofluorescence find that FOXO4D protein expression lever was increased in three HGJDD group, especially in high-dose HGJDD group. Western blotting confirmed increased level of FOXO4, ERK, and p-ERK and decreased levels of HNF4α, which reflected that the therapeutic effect was closely to FOXO4/ERK/HNF4α signal pathway. CONCLUSIONS:Traditional Chinese medicine (TCM) offers diverse herbal treatments for HBV, with HGJDD showing efficacy in reducing HBsAg, HBeAg, and HBV DNA levels at cellular and animal levels. This study identified that FOXO4/ERK/HNF4α signal pathway played an important role in HGJDD's therapeutic effects. These findings support HGJDD's potential in HBV treatment, providing a scientific basis for clinical use.

OBJECTIVE:To develop a core outcome set (COS) for clinical trials on post COVID-19 condition (PCC), that is, what, when, and how to measure PCC. METHOD:A comprehensive collection of outcomes (including their measurement methods and phases) was launched via literature review and clinician and patient surveys. Two rounds of Delphi surveys were conducted under the predefined criteria for rating, followed by a consensus meeting to finalize the COS for PCC (COS-PCC). RESULTS:Fifty-two outcomes within 7 categories and 206 measurement methods were identified. Sixty participants from five stakeholder groups completed the first round of the Delphi survey and 41 the second. Consensus was reached among 36 representatives on four domains of respiratory, physical, neuropsychological, and health conditions, including nine core outcomes and their respective measurement methods of priority: dyspnea (modified Medical Research Council scale), cough (Leicester Cough Questionnaire), exercise capacity (6-min walk test), fatigue (Fatigue Severity Scale), pain (Numerical Rating Scale), sleeping disturbance (Pittsburgh Sleep Quality Index), anxiety (Generalized Anxiety Disorder Scale-7), depression (Patient Health Questionnaire-9), and health status (36-item Short Form Health Survey); 16 optional measurement methods achieved consensus for supplement. Measuring phases of each core outcome were prioritized by importance through short and long terms of PCC. CONCLUSIONS:The COS-PCC highlights the key PCC concerns and provides an essential outcome set for PCC assessment in clinical trials and evidence synthesis. With improving the understanding of PCC and accumulating research evidence, the COS-PCC needs to be continuously updated and improved in practice.

Objective:The objective of the study was to investigate the situation of depression/anxiety in patients with coronary heart disease(CHD)at different stages of the disease and to analyze the influencing factors and the evolution characteristics of traditional Chinese medicine(TCM)syndromes.Materials and Methods:From October 2016 to April 2018,a cross-sectional survey was conducted at 48 clinical research centers in 23 provinces,cities,and autonomous regions across China.A total of 11383 cases were collected by outpatient or inpatient cases,including healthy individuals(n=1754),low-risk individuals(n=2339),metabolic syndrome(n=1475),stable CHD(n=3366),acute coronary syndrome(n=704),perioperative intervention treatment(n=753),and heart failure(n=992).Survey demographic data,lifestyle habits,disease and health status,TCM symptoms and signs,and other information were collected.Results:The prevalence rates of depression/anxiety in surveyed patients with CHD were 35.7%and 21.0%,respectively,and were higher than those in patients with metabolic syndrome(18.8%and 10.3%,respectively),low-risk individuals(11.7%and 7.5%),and healthy individuals(9.7%and 5.7%,respectively).The significant risk factors for CHD combined with depression analyzed by the generalized linear mixed model included age(odds ratio[OR]=0.019),gender(OR=0.632),hypertension(OR=0.306),course of CHD(OR=0.022),stent placement(OR=-0.284),heart function level(OR=-4.151/-3.336/-2.118),and phlegm stasis syndrome score(OR=0.129).The significant risk factors for CHD combined with anxiety included gender(OR=0.581),heart function level(OR=-1.856),and phlegm stasis syndrome score(OR=0.094).Factor analysis was conducted on the symptoms and signs of patients with CHD combined with depression/anxiety,and 16 common factors were obtained with cumulative contribution rates of 62.83%and 66.13%,respectively.Disease syndromes included liver and kidney deficiency syndrome,liver stagnation and discomfort syndrome,Qi deficiency syndrome,liver meridian fire heat syndrome,kidney deficiency syndrome,phlegm dampness syndrome,heart and gallbladder Qi deficiency syndrome,blood stasis syndrome,lung Qi inversion syndrome,Yang deficiency syndrome,and three symptoms named diseases,including chest tightness,chest pain,insomnia,and head discomfort.Conclusions:Through cross-sectional design,the data obtained in this study revealed the actual situation of CHD patients with anxiety or depression at different stages.The influencing factors of CHD patients with depression or anxiety were analyzed through the collected cross-sectional information and further revealed the syndromic characteristics of CHD patients with depression or anxiety at different stages from the perspective of TCM syndromes.The data obtained provide a practical basis for further understanding the clinical characteristics of bicardiac diseases and for proposing treatment strategies in stages.

Background:Extensive research has demonstrated that gut microbiota and its metabolites-including short-chain fatty acids, trimethylamine N-oxide (TMAO), and bile acids-play a crucial role in the pathophysiology of coronary artery disease (CAD).The bidirectional interaction between the gut microbiota and the cardiovascular system significantly influences host metabolic and inflammatory homeostasis. As a result, targeted modulation of the gut microbiota emerges as a promising adjunctive therapeutic strategy for CAD, offering potential benefits with minimal side effects. Purpose:This study aims to elucidate the therapeutic mechanisms of the clinically validated Chinese medicine formula HJ11 in mitigating coronary heart disease (CHD), with a particular focus on its regulation of the heart-gut axis and associated atherosclerotic processes. Study Design and Methods:This study established an ApoE-/- mouse model of atherosclerosis and treated with HJ11 via gavage.We investigated the effects of HJ11 on the gut microenvironment in these atherosclerotic mice. Gut microbial composition and faecal metabolite profiles were analyzed using 16S rDNA sequencing and metabolomics. Additionally, an in vitro model of atherosclerosis was used to examine whether HJ11 exerts anti-inflammatory effects by modulating the TLR4/MYD88/IκB-α signaling pathway. Results:HJ11 exerted protective effects on coronary atherosclerosis by reducing systemic serum lipid levels and inhibiting plaque formation, vascular inflammation, and collagen deposition, while also alleviating aortic injury. It suppressed endothelial inflammation and inhibited the proliferation of vascular smooth muscle cells. In the gut, HJ11 alleviated intestinal structural damage and enhanced barrier integrity. Notably, it promoted the function of Akkermansia, a beneficial bacterium known to influence TLR4 expression. Finally, in an in vitro atherosclerosis model, HJ11 decoction inhibited cell proliferation and migration by inactivating the TLR4/MYD88/IκB-α signaling pathway-an effect that was abolished by TLR4 overexpression.

Traditional Medicine(TM),particularly Traditional Chinese Medicine(TCM),is an indispensable compo-nent of the global healthcare system,offering unique insights to modern medical science.Clinical efficacy is the bedrock for the inheritance and development of TM.To meet the growing demand for high-quality healthcare,it is imperative to integrate TM with mod-ern technology to address the issue of insufficient evi-dence for the efficacy of TM.To evaluate the clinical efficacy of TM,clinical trials are necessary,especially good clinical trials,which conform to the general prin-ciples of scientific research and also take into account the characteristics of traditional therapies.To promote the development of high-quality clinical trials that are in line with the features of TM,the attending experts held an in-depth discussion and reached the Rome con-sensus on"Good Clinical Trials for TM(GCT-TM),"at the 18th Academic Annual Meeting of the Clinical Efficacy Evaluation Committee of the World Federation of Chinese Medicine Societies and the 8th International Forum on Evidence-Based Chinese Medicine,held in Rome on June 26,2025.

Large language models (LLMs) show promise in medical knowledge representation but struggle with dynamic clinical workflows and personalized treatment in complex systems like Traditional Chinese Medicine (TCM). We propose an efficient and novel LLM framework for TCM mechanism exploration and clinical application, combining incremental domain-specific pre-training, multi-task supervised fine-tuning, and Chain-of-Thought (CoT) reasoning. Our two-stage approach-"Understanding and Inheritance" followed by "Exploration and Innovation"-uniquely leverages a heterogeneous database of 100,538 records from 19 TCM physicians to model the core TCM principle of "different treatments for the same disease". Six downstream tasks assess clinical capabilities, including personalized prescription generation (Task 3). After incremental pre-training, the model improves BLEU-4 by 1,313% over baseline, reaching 41.26-43.21 after fine-tuning. We quantify physician-specific variations and formally validate the decisive role of basic formulas-removing them causes a 23.9% performance drop. Cross-school evaluations confirm robust generalization, with 22.8 BLEU-4 on external data. CoT annotation boosts performance by 20% using only 10% labeled data, demonstrating high data efficiency. The model captures TCM's "different treatments for the same disease" principle and preserves school-specific diagnostic logic. This work advances intelligent TCM inheritance and paves the way for AI-driven personalized medicine.

Background:Abnormal circadian rhythm of blood pressure is recognized as an independent risk factor for target organ damage in the heart, brain, and kidneys. Eucommia ulmoides Oliv [Eucommiaceae, Eucommiae cortex], a traditional Chinese medicine, has been reported to exhibit antihypertensive effects and may regulate blood pressure variability. This study aimed to evaluate the efficacy and safety of Quanduzhong capsules in regulating the circadian rhythm of blood pressure in patients with essential hypertension. Methods:We designed a randomized controlled clinical trial. A total of 136 participants who had essential hypertension and abnormal circadian rhythm of blood pressure were randomly assigned to the test or control group, each comprising 68 individuals, using the random number table method. Both groups maintained their original Western antihypertensive medicine regimen, with the test group receiving additional treatment of Quanduzhong capsules (administered twice daily, 1.48 g each time). The treatment duration for both groups was 12 weeks. The patients were visited at baseline and at the end of the 4th, 8th, and 12th weeks of the intervention. Their 24-h ambulatory blood pressure and clinic blood pressure were measured at baseline and the end of 12th weeks. Primary outcomes included the recovery rate of dipper blood pressure rhythm, the standard deviation of blood pressure (SD), and the coefficient of variation of blood pressure (CV). Results:After 12 weeks of treatment, the results in the full analysis set and in the per-protocol set showed no statistically significant differences between the treatment group and the control group in SD and CV. However, among the subjects who did not use calcium channel blockers, the treatment group demonstrated significantly better improvements in 24-h standard deviation of diastolic blood pressure (P < 0.05) than the control group. Conclusion:Our findings suggest that Quanduzhong capsules can effectively improve the circadian rhythm of blood pressure without calcium channel blockers. Clinical Trial Registration:https://www.chictr.org.cn/showproj.html?proj=127240, identifier ChiCTR2100046830.

Non-alcoholic fatty liver disease (NAFLD) has emerged as a global public health concern, affecting over one-quarter of the global population. It is closely associated with the prevalence of obesity and metabolic syndrome. Current treatment options for NAFLD are limited and often have side effects. Traditional Chinese medicine (TCM) offers a promising alternative with its holistic approach and use of multi-component herbal formulations. A recent study explored the potential of the TCM formula, "Fanlian Huazhuo Formula (FLHZF)", to alleviate high-fat diet-induced NAFLD by regulating autophagy and lipid synthesis signaling pathways. TCM has shown advantages in the prevention and treatment of NAFLD due to its efficacy and minimal side effects. However, the complex multicomponent and multitarget characteristics of formulas such as FLHZF present challenges in research. Future studies should focus on utilizing modern techniques to deepen our understanding of the mechanisms of action and active ingredients of Chinese herbal medicines, thereby promoting their modernization.

BACKGROUND:Acute Coronary Syndrome (ACS), as the most critical pathological type of coronary atherosclerotic heart disease, has a high morbidity and lethality, and the long-term treatment of modern medicine is still faced with the problems of restenosis, microcirculation obstruction and drug resistance. The addition of Traditional Chinese Medicine provides new ideas for ACS treatment. Our previous study found that Jia-Wei-Si-Miao-Yong-An decoction (HJ11) can improve the inflammatory response and cardiac function in ACS. However, its mechanism of action needs to be studied in depth. PURPOSE:This study aimed to combine transcriptomics and network pharmacology based on the study of HJ11 components, elucidate the mechanism of HJ11 in ameliorating ACS by experimental validation. METHODS:UPLC-QE-Orbitrap-MS was utilized for the preliminary identification of HJ11 decoction and blood-entry components. And based on the results of the compositional studies, combining with the transcriptomic results of ACS rat model, network pharmacological analysis was performed to identify the potential targets of HJ11 action. The ACS rat model and LPS-induced endothelial cells were further used for experimental validation using RT-PCR, Western blot techniques, immunofluorescence and other techniques. RESULTS:UPLC-QE-Orbitrap-MS analysis preliminarily identified 212 chemical constituents of HJ11 decoction, of which 49 were consistent with the blood-entered constituents, including organic acids, flavonoids, and amino acids. Combining the compositional studies and transcriptomics results with network pharmacology analysis, HJ11 may ameliorate ACS through various mechanisms (including inflammatory response, oxidative stress, etc.). We verified the mechanisms using rats and endothelial cells and found that HJ11 modulates eNOS levels; reduces inflammation-induced oxidative stress; reduces ADMA levels, which are closely related to inflammation, oxidative stress, and endothelial function and modulates DDAH/ADMA/NO pathway. CONCLUSION:HJ11 exhibits a comprehensive multi-target mechanism against ACS, acting through the DDAH/ADMA/NO pathway, reducing inflammation, and attenuating oxidative stress. These findings highlight HJ11 as a promising, holistic therapeutic strategy for ACS, illustrating the potential of Chinese herbal formulas in addressing complex cardiovascular diseases.

Background: HJ11 (HJ11 decoction), which is based on the traditional prescription Si-Miao-Yong-An decoction, has exerted a remarkable effect on atherosclerosis (AS). Nevertheless, the main components and underlying mechanisms of HJ11 for treating AS remain unclear. Aim of the Study: This study was designed to elucidate the mechanism of HJ11 in the treatment of AS through network pharmacology and in vivo experimental validation. Methods: Network pharmacology was employed to explore the primary bioactive components and targets of HJ11. AS-related genes were obtained from the GeneCards and DisGeNET databases and screened for intersections with HJ11. A herb-compound-target interaction network was constructed by Cytoscape 3.9.1, and molecular docking analyses were constructed on key targets. By using a mouse model, the mechanism of action of HJ11 was further confirmed. Results: A total of 231 active components of HJ11, 1681 AS-related genes, and 156 common targets were identified. Through the establishment of numerous networks, it was discovered that the main association of the mechanism of HJ11 in AS therapy pertained to anti-inflammation. Important substances included quercetin, kaempferol, and luteolin, while TNF-α, AKT1, IL-6, and VEGFA were the main targets. Molecular docking demonstrated that there were favorable binding interactions between active drugs (quercetin, kaempferol, and luteolin) and targets (TNF-α, AKT1, IL-6, and VEGFA). In the in vivo study, HJ11 reduced the expression of TNF-α, AKT1, IL-6, and VEGFA at both the mRNA and protein levels, inhibited atherosclerotic lesions in AS mouse models, and retarded the development of retroarterioid sclerosis. Conclusions: HJ11 can inhibit inflammation and the progression of AS, and the mechanism might involve downregulating the expression of TNF-α, AKT1, IL-6, and VEGFA.

With the development of deep learning technology, the autonomous analytical performance of Traditional Chinese Medicine (TCM) inspections has greatly advanced in recent decades, particularly in the areas of tongue and face diagnosis. To improve the effectiveness of diagnosis and treatment in clinical practice, TCM doctors typically differentiate between TCM-based deficiency and excess based on patterns. Therefore, an accurate TCM-based deficiency and excess pattern differentiation system is required to support TCM doctors in their work, including online diagnosis and treatment, applications on major health platforms, and other situations. This study aimed to develop a TCM-based inspection characteristic extraction model based on convolutional neural networks to extract significant characteristics from the face, lips, tongue, and other areas. Based on TCM theory and the clinical expertise of doctors, mapping modules were created for TCM-based deficiency and excess. These two modules were combined to provide a thorough TCM-based deficiency and excess pattern differentiation system. The experimental results showed that the average accuracy for inspection characteristics, such as tongue body color, coating color, and coating thickness, as well as lip color reached 90% in tests on the gathered facial dataset. In addition, the average accuracy attained 81.67%.for the trained TCM-based deficiency and excess pattern differentiation system.

Objectives:This study aimed to clarify the short-term symptoms, duration, and influencing factors in people recovering from coronavirus disease 2019 (COVID-19) after China's dynamic zero-COVID-19 policy was implemented in December 2022.Methods:We included data from a large-scale on-line survey conducted in China between January 14 and February 1, 2023. Participants were individuals of all ages. Chi-squared tests and multivariate logistic regression analyses were performed to identify factors associated with different symptoms.Results:Overall, 21,012 patients from seven regions of China were included in this study (female: 71.22%). For most patients, the period from symptom onset to a negative nucleic acid test result was <= 10 days (72.33%). The distribution of symptoms varied at different times, with respiratory (1-4 weeks) and psychocardiology (5-8 weeks) symptoms being the most common. Multivariate analysis identified male sex, no comorbidity, and living in northeast and northwest China (compared with central China) as independent factors associated with a lower risk of symptoms, while age (41-60 years) was a possible risk factor (compared with 18-40 years).Conclusions:Short-term respiratory and psychocardiology symptoms were the most common after COVID-19 recovery. Sex, age, geographical region, and comorbidities were potential influencing factors for the development of short-term symptoms.

Honeysuckle is a conventional Chinese medicine with several therapeutic applications. With the advancement of modern scientific technologies, Honeysuckle's pharmacological effects and medicinal properties have been investigated more thoroughly. Studies demonstrate that the bioactive compounds in Honeysuckle possess anti-inflammatory effects via several mechanisms, protecting the cardiovascular system. This article provides a reference for the clinical use of Honeysuckle by reviewing research on the therapeutic impact of Honeysuckle and its active constituents on cardiovascular diseases, such as coronary atherosclerotic heart disease (CHD), myocardial ischemia-reperfusion (MI/R), acute myocardial infarction (AMI), hypertension, arrhythmia, and heart failure, through the inhibition of inflammatory responses.

Anxiety disorders are one of the most prevalent mental health conditions worldwide, imposing a significant burden on individuals affected by them and society in general. Current research endeavors aim to enhance the effectiveness of existing anxiolytic drugs and reduce their side effects through optimization or the development of new treatments. Several anxiolytic novel drugs have been produced as a result of discovery-focused research. However, many drug candidates that show promise in preclinical rodent model studies fail to offer any substantive clinical benefits to patients. This review provides an overview of the diagnosis and classification of anxiety disorders together with a systematic review of anxiolytic drugs with a focus on their targets, therapeutic applications, and side effects. It also provides a concise overview of the constraints and disadvantages associated with frequently administered anxiolytic drugs. Additionally, the study comprehensively reviews animal models used in anxiety studies and their associated molecular mechanisms, while also summarizing the brain circuitry related to anxiety. In conclusion, this article provides a valuable foundation for future anxiolytic drug discovery efforts.

Non-alcoholic fatty liver disease (NAFLD) is a chronic liver condition closely associated with metabolic syndrome, with its incidence rate continuously rising globally. Recent studies have shown that the development of NAFLD is associated with insulin resistance, lipid metabolism disorder, oxidative stress and endoplasmic reticulum stress. Therapeutic strategies for NAFLD include lifestyle modifications, pharmacological treatments, and emerging biological therapies; however, there is currently no specific drug to treat NAFLD. However Chinese herb medicine (CHM) has shown potential in the treatment of NAFLD due to its unique therapeutic concepts and methods for centuries in China. This review aims to summarize the pathogenesis of NAFLD and some CHMs that have been shown to have therapeutic effects on NAFLD, thus enriching the scientific connotation of TCM theories and facilitating the exploration of TCM in the treatment of NAFLD.

Background: This study aimed to assess the prevalence and identify risk factors associated with depression among coronary heart disease (CHD) patients at different stages in China. Methods: Conducted as a hospital-based, cross-sectional study across 48 hospitals in 23 provinces, the research spanned from October 2016 to April 2018. A total of 9044 patients were initially recruited, with 8353 deemed eligible for participation. Depression was assessed using the nine-item Patient Health Questionnaire-9 (PHQ-9) Scale. Univariate analysis identified predictors of postoperative depression, and binary logistic regression analysis was employed to ascertain risk factors associated with depressive symptoms. The predictive model was constructed using the "rms" package in R software, demonstrating robust predictive capabilities according to the ROC curve. Results: In general, both the degree and overall score based on the PHQ-9 revealed a trend: as the severity of the disease increased, so did the severity of patient depression. Univariate analysis indicated statistical differences concerning general situations and lifestyles. The binary logistic regression model highlighted the proximity of depression to risk factors such as gender, nationality, marital status, education, drinking, BMI, sleep disturbance, and disease status. Utilizing these findings, a predictive nomogram for depression was developed. The model exhibited excellent predictive ability, with an AUC of 0.768 (95% CI = 0.757–0.780). Conclusions: This study systematically investigated the prevalence of depression among coronary heart disease patients at various stages. As coronary heart disease advanced, the level of depression intensified. The nomogram developed in this study proves valuable in predicting the incidence of depression in coronary heart disease patients.