ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

The disease-syndrome combination animal model in traditional Chinese medicine （TCM） andrology serves as an important bridge linking TCM theory with modern medical research， providing a key experimental platform for elucidating the 'syndrome-disease' correlation mechanism in male-specific diseases and for screening effective prescriptions. This article reviews recent progress in animal model research on common TCM andrological diseases， including prostatic diseases， sexual dysfunction， and male infertility， with a focus on analyzing the application， advantages， and disadvantages of various modeling strategies， such as immune induction， hormonal intervention， and multi-factor combination across different syndrome types. However， despite breakthroughs in model construction techniques， current research still faces several challenges， including insufficient standardization of syndrome differentiation and difficulties in quantifying TCM-specific indicators. Future studies need to optimize model evaluation systems by integrating modern technologies， in order to promote the standardization and internationalization of TCM andrology research.

The sirtuin 1(SIRT1)is an important NAD+-dependent deacetylase that has attracted much attention in ophthalmic research in recent years. This is because the expression of SIRT1 in ocular tissues and its function are inextricably linked to the pathogenesis and progression of many ocular diseases, including dry eye, glaucoma, cataract and diabetic retinopathy. Through in-depth investigations, we have found that SIRT1, as a key regulatory protein, has a profound impact on the pathophysiological processes of ocular diseases through a variety of mechanisms, such as regulating apoptotic programs, modulating oxidative stress, mediating inflammatory responses and maintaining normal mitochondrial function. These findings indicate that SIRT1 plays an important protective role in ocular diseases. The aim of this article is to comprehensively review the latest research findings on SIRT1 in ophthalmic diseases in recent years, and hopes to provide new ideas and methods for the prevention and treatment of ophthalmic diseases by thoroughly analyzing the mechanism of action of SIRT1.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Objectives:To explore the predictive value of residual Murray's law-based quantitative flow ratio(μQFR)on long-term vessel-oriented composite endpoints(VoCE).Methods:This retrospective study included 3 510 patients from the FAVOR Ⅲ China trial.Offline residual μQFR analysis was performed on all vessels(diameter≥2.5 mm)with 50%-90%stenotic lesions.Patients were stratified into high-,intermediate-,and low-risk groups based on residual μQFR tertiles.The primary endpoint was 3-year VoCE,defined as a composite of cardiac death related to the target vessel,target vessel-related spontaneous myocardial infarction,and ischemia-driven target vessel revascularization.Results:Offline analysis was performed on 5 256 vessels from 3 510 patients.The mean residual μQFR was 0.92±0.75.The high-risk group(residual μQFR≤0.91)with 1 554 patients(1 958 vessels);the intermediate-risk group(residual μQFR 0.92-0.96)with 1 211 patients(1 906 vessels);and the low-risk group(residual μQFR>0.96)with 745 patients(1 392 vessels).Over 3-year follow-up,VoCE occurred in 227 vessels(4.3%).The 3-year VoCE incidence was significantly higher in the high-risk group compared to the intermediate-and low-risk groups(6.2%vs.4.1%vs.2.5%,log-rank P<0.001),primarily driven by ischemia-driven target vessel revascularization(5.0%vs.3.0%vs.1.6%,log-rank P<0.001).Hypertension(OR=0.83,95%CI:0.72-0.96),hypercholesterolemia(OR=0.84,95%CI:0.73-0.97),bifurcation lesions(OR=0.72,95%CI:0.63-0.83),moderate/severe calcification(OR=0.70,95%CI:0.57-0.84),and tandem lesions(OR=0.59,95%CI:0.47-0.75)were independent predictors of lower residual μQFR values.Conclusions:Lower residual μQFR is significantly associated with increased VoCE risk during the 3-year follow up period.

Objective To explore the changes in neural activity in patients with type 2 diabetes mellitus(T2DM)and their corre-lation with executive function,and to analyze the neural mechanisms underlying the decline in executive function in T2DM patients.Methods Thirty-one T2DM patients(T2DM group)and thirty-two healthy controls(HC)(HC group)matched for body mass index(BMI)underwent resting-state functional magnetic resonance imaging(rs-fMRI)scans and N-back task tests were included.Differ-ences in the amplitude of low-frequency fluctuation(ALFF),regional homogeneity(ReHo),and seed-based functional connectivity(FC)between the two groups were compared,and partial correlation analyses were performed between the difference results and N-back task performance.Results The T2DM group showed prolonged reaction time(RT)in the 1-back and 2-back tasks.T2DM patients exhibited increased ALFF in the bilateral caudate nucleus,left medial superior frontal gyrus,and right postcentral gyrus,as well as elevated ReHo in the right putamen.FC analysis revealed significant alterations in FC between the caudate nucleus,putamen,and multiple brain regions in T2DM patients,with some of these FC changes significantly correlated with RT and accuracy(ACC)in the N-back task.Conclusion The decline in executive function in T2DM patients may be associated with abnormal neural activity in brain regions such as the striatum,salience network,and frontoparietal control network.FC further decreases under increased cognitive load.These findings provide evidence for the study of the neural mechanisms of executive function impairment in T2DM patients.

Objective To analyze the epidemiological characteristics of human papillomavirus(HPV)infection in women in the Zhongguancun area of Beijing,and to evaluate the infection rates and genotype distribution between different populations and age groups.Methods A retrospective analysis was conducted on HPV genotyping results of 13,105 women who visited the gynecology outpatient department or underwent routine health check-ups at Zhongguancun Hospital from March 2019 to April 2024.High-risk HPV genotypes(15 types)were detected using a fluorescence PCR assay.Positive cases were classified as single,dual or multiple(≥3)infections based on the number of genotypes.Subjects were stratified into six age groups(≤30,31-40,41-50,51-60,61-70,and≥71 years),and the characteristics of infection by type and age group were analyzed.Results The overall HPV positivity rate was 10.78%(1,413/13,105),with a significantly higher rate in the outpatient group than that in the health check-up group(16.36%vs.6.06%,P<0.01).The three most prevalent genotypes were HPV52(18.83%),HPV58(13.85%),and HPV16(11.28%).Single infections accounted for 79.19%of cases,dual infections for 15.93%and multiple infections for 4.88%.Age distribution showed a U-shaped pattern,with higher infection rate in women aged≤30 years(15.06%)and 61-70 years(13.19%),and the lowest rate in the≥71 years(8.09%).Notably,women aged≤30 years had the highest proportion of multiple infections(31.72%).Conclusion These findings provide a basis for cervical cancer screening strategies,HPV vaccination promotion and individualized prevention of cervical cancer in this region.

Objective To investigate the effect and mechanism of remimazolam on circulatory function in septic shock rats.Methods Seventy-two SPF grade rats were randomly divided into the control group,the model group,the dexamethasone group,the low and high dose remimazolam groups and the high-dose remimazolam+Nrf2 inhibitor(ML385)group,with 12 rats in each group.The septic shock rat model was established by intravenous infusion of 10 mg/kg lipopolysaccharide(LPS).After 6 hours of modeling,the mean arterial pressure(MAP)and heart rate(HR)of rats were measured.Enzyme linked immunosorbent assay(ELISA)method was applied to measure serum levels of lactic acid(Lac),tumor necrosis factor-α(TNF-α),interleukin(IL)-1β,IL-6,nitric oxide(NO),and endothelin-1(ET-1).Hematoxylin-eosin(HE)staining was applied to observe morphological changes in vascular tissue.TUNEL staining was applied to observe the apoptosis of vascular endothelial cells.DHE fluorescent probe was used to detect the level of ROS in vascular tissue.The colorimetric method was applied to detect the contents of MDA and the activity of SOD in vascular tissue.Western blot assay was applied to detect the protein expression of nuclear factor E2-related factor 2(Nrf2)and glutathione peroxidase 4(GPX4)in vascular tissue.Results Compared with the control group,MAP,SOD activity in vascular tissue,Nrf2 and GPX4 protein levels were lower in the model group,while HR,serum Lac,NO,ET-1,TNF-α,IL-1β,IL-6 levels,endothelial cell apoptosis rate,ROS level in vascular tissue and MDA content were higher(P＜0.05).Compared with the model group,MAP,SOD activity in vascular tissue,Nrf2 and GPX4 protein levels were higher in the dexamethasone group and in the low and high dose remimazolam groups,while HR,serum Lac,NO,ET-1,TNF-α,IL-1β,IL-6 levels,endothelial cell apoptosis rate,ROS level in vascular tissue and MDA content were lower(P＜0.05).Nrf2 inhibitor ML385 greatly reduced the protective effect of remimazolam on septic shock rats(P＜0.05).Conclusion Remimazolam may improve circulatory function in septic shock rats by activating the Nrf2/GPX4 pathway,inhibiting inflammatory response and oxidative stress,reducing endothelial cell damage.

Objective To investigate the effect and mechanism of remimazolam on circulatory function in septic shock rats.Methods Seventy-two SPF grade rats were randomly divided into the control group,the model group,the dexamethasone group,the low and high dose remimazolam groups and the high-dose remimazolam+Nrf2 inhibitor(ML385)group,with 12 rats in each group.The septic shock rat model was established by intravenous infusion of 10 mg/kg lipopolysaccharide(LPS).After 6 hours of modeling,the mean arterial pressure(MAP)and heart rate(HR)of rats were measured.Enzyme linked immunosorbent assay(ELISA)method was applied to measure serum levels of lactic acid(Lac),tumor necrosis factor-α(TNF-α),interleukin(IL)-1β,IL-6,nitric oxide(NO),and endothelin-1(ET-1).Hematoxylin-eosin(HE)staining was applied to observe morphological changes in vascular tissue.TUNEL staining was applied to observe the apoptosis of vascular endothelial cells.DHE fluorescent probe was used to detect the level of ROS in vascular tissue.The colorimetric method was applied to detect the contents of MDA and the activity of SOD in vascular tissue.Western blot assay was applied to detect the protein expression of nuclear factor E2-related factor 2(Nrf2)and glutathione peroxidase 4(GPX4)in vascular tissue.Results Compared with the control group,MAP,SOD activity in vascular tissue,Nrf2 and GPX4 protein levels were lower in the model group,while HR,serum Lac,NO,ET-1,TNF-α,IL-1β,IL-6 levels,endothelial cell apoptosis rate,ROS level in vascular tissue and MDA content were higher(P＜0.05).Compared with the model group,MAP,SOD activity in vascular tissue,Nrf2 and GPX4 protein levels were higher in the dexamethasone group and in the low and high dose remimazolam groups,while HR,serum Lac,NO,ET-1,TNF-α,IL-1β,IL-6 levels,endothelial cell apoptosis rate,ROS level in vascular tissue and MDA content were lower(P＜0.05).Nrf2 inhibitor ML385 greatly reduced the protective effect of remimazolam on septic shock rats(P＜0.05).Conclusion Remimazolam may improve circulatory function in septic shock rats by activating the Nrf2/GPX4 pathway,inhibiting inflammatory response and oxidative stress,reducing endothelial cell damage.