Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective: To analyze the relationship between the risk of tuberculosis outbreaks in schools and the visit interval of index cases, so as to provide a scientific reference for predicting the risks of tuberculosis outbreak and making preventive measures. Methods: A total of 630 index cases from school tuberculosis outbreaks were studied during January, 2015 to December, 2022. Data on demographics, consultation history, etiological diagnosis, and methods of detection were collected. Restricted Cubic Splines (RCS), unconditional Logistic regression, and the receiver operating characteristic curve (ROC curve) were used for analysis. Results: The RCS fitted curve showed that the risk of a tuberculosis outbreak linearly increased when the consultation interval for etiologically negative patients exceeded 5.79 days, or for etiologically positive patients exceeded 8.37 days. After multi factor adjustment, for every additional day in the visit interval of the index case, the odds ratio ( OR ) value for a high risk outbreak was 1.10 (95% CI =1.07-1.13)( P <0.05). When analyzed by tertiles of visit intervals, compared to an interval of <14 days, the OR values (95% CI ) for high risk outbreaks in schools with intervals of 14-<28 days and ≥28 days were 10.32(3.04-35.10) and 82.58( 28.42 -239.95), respectively( P <0.01), indicating a trend of increasing outbreak risk with longer visit intervals. Based on the ROC curve analysis, the optimal threshold for predicting a high risk school tuberculosis outbreak was 23.5 days, with an area under the curve ( AUC ) of 0.93 (95% CI =0.89-0.98). Conclusion An extended visit interval of index cases is a good early warning indicator for high risk tuberculosis outbreaks in schools and could be considered a key factor in early intervention and risk control strategies.

Objective To establish a method for the simultaneous determination of DOX·HCl and LND. Methods HPLC was performed on Agilent 5 HC-C₁₈（2） （4.6 mm × 250 mm, 5 µm） column. The mobile phase was methanol-0.1% TFA aqueous solution, and the gradient elution procedure were: 0 to 3 min, 65% methanol; 3 to 7 min, 65%→90% methanol; 7 to 13 min, 90% methanol; 13 to 15 min, 90%→65% methanol; 15 to 20 min, 65% methanol. The collection time was 20 min, the balance time was 3 min, the UV detection wavelengths were 205 nm and 253 nm. The flow rate was 1.0 ml/min and the column temperature was 35℃. The amount of inlet was 10 µl. Results The method was highly specific, and both DOX·HCl and LND exhibited good linearity in the concentration range of 1-40 µg/ml and 6-240 µg/ml, respectively. The two compounds’ precision, stability, and recovery satisfied the requirements of the method. Conclusion This study established a HPLC method that was suitable for the simultaneous detection of DOX·HCl and LND. This method’s high level of specificity, accuracy, and reliability .

Objective: To explore the intervention effect of different intensity of classroom physical exercise on cardiorespiratory fitness and executive function of Tibetan first grade students at high altitude, so as to provide reference for improving the level of cardiorespiratory fitness and executive function of Tibetan adolescents. Methods: From September to December 2020, 184 Tibetan students from five first grade classes in a middle school in Lhasa, Tibet, were randomly assigned into a control group (81 students in two classes) and an intervention group (103 students in three classes). Both groups followed the same teaching programme, but the intervention group received 36 sessions of moderate to high intensity classroom physical activity, one session per day, Monday,Wednesday and Friday, for 12 weeks. Before and after the intervention, cardiorespiratory fitness and executive function were tested by 20m round trip running and Flanker s experimental paradigm, 2-back s experimental paradigm, and More odd shifting experimental paradigm for inhibitory control, refreshing memory, and switching flexibility, and the results were analysed by analysis of covariance (ANCOVA) to compare the results of the pre and post intervention periods. Results: The maximum oxygen uptake (VO 2max ) of Tibetan first grade students in the intervention group increased by 2.25 mL/(kg〖WW）〗·〖WW(〗min) compared with the control group after the intervention ( t =-3.89, P <0.01); the response time of the inhibitory function was reduced by 4.40 ms, that of the refreshing function by 196.06 ms, and that of the switching function by 92.72 ms in the intervention group compared with the control group ( t =2.98, 4.82 ,3.21, P <0.05). Conclusion The 12 week moderate to high intensity classroom physical activity intervention has different degrees of improvement effects on cardiorespiratory fitness and executive function in Tibetan adolescents.

Aim To explore the effects of Lycium berry seed oil on Nrf2/ARE pathway and oxidative damage in testis of subacute aging rats. Methods Fifty out of 60 male SD rats, aged 8 weeks, were subcutaneously injected with 125 mg • kg"D-galactosidase in the neck for 8 weeks to establish a subacute senescent rat model. The presence of senescent cells was observed using P-galactosidase ((3-gal), while testicular morphology was examined using HE staining. Serum levels of testosterone (testosterone, T), follicle-stimulating hormone ( follicle stimulating hormone, FSH ) , luteinizing hormone ( luteinizing hormone, LH ) , superoxide dis-mutase ( superoxide dismutase, SOD ) , glutathione ( glutathione, GSH) and malondialdehyde ( malondial-dehyde, MDA) were measured through ELISA, and the expressions of factors related to aging, oxidative damage, and the Nrf2/ARE pathway were assessed via immunohistochemical analysis and Western blotting. Results After successfully identifying the model, the morphology of the testis was improved and the intervention of Lycium seed oil led to a down-regulation in the expression of [3-gal and -yH2AX. The serum levels of SOD, GSH, T, and FSH increased while MDA and LH decreased (P 0. 05) . Additionally, there was an up-regulated expression of Nrf2, GCLC, NQOl, and SOD2 proteins in testicular tissue ( P 0. 05 ) and nuclear expression of Nrf2 in sertoli cells. Conclusion Lycium barbarum seed oil may reduce oxidative damage in testes of subacute senescent rats by activating the Nrf2/ARE signaling pathway.

Objective To study the correlation between traditional Chinese medicine(TCM)constitution and pathogenic factors in patients with ankylosing spondylitis(AS).Methods One hundred patients of AS and their family members who had medical consultation in the Fifth Hospital of Xi'an(i.e.,Shaanxi Hospital of Integrated Traditional Chinese and Western Medicine)in August 2019 and September 2020 were selected as the study subjects.The guidelines of Classification and Determination of Traditional Chinese Medicine Constitution issued by the China Association of Chinese Medicine were adopted to determine the traditional Chinese medicine(TCM)constitution types of the study subjects.The sociodemographic information,living habits,clinical symptoms,and TCM constitution types of the AS patients and their family members were collected by means of questionnaires and clinical investigations,and then the pathogenic factors of the patients with AS were investigated.The binomial Logistic regression model was used to analyze the correlation between TCM constitution types and pathogenic factors in patients with AS.Results(1)Among the 100 AS patients,the majority of them had the biased constitutions,and the biased constitutions with the occurrence frequency in descending order were yang deficiency constitution,qi deficiency constitution,and damp-heat constitution,which accounted for 33.00%,14.00%,and 18.00%,respectively.(2)The prevalence rates of AS in the first-,second-,and third-degree relatives of AS patients were 56.25%,40.00%and 25.00%,respectively.For the positive rates of human leukocyte antigen B27(HLA-B27)in AS patients and their family members,HLA-B27 in AS patients was all positive,while the positive rates of HLA-B27 in the first-,second-,and third-degree relatives of AS patients were 44.31%,30.67%and 15.63%,respectively.(3)The results of regression analysis showed that the disease duration of AS patients was significantly correlated with qi deficiency constitution,the grading of sacroiliac arthritis was correlated with qi stagnation constitution,and age was correlated with blood stasis constitution(P＜0.05 or P＜0.01).The results indicated that disease duration and age were the important factors affecting the constitution types of AS patients,and disease duration was closely related to qi deficiency while age was closely related to blood stasis.Conclusion AS is a highly hereditary autoimmune disease,and its onset is associated with HLA-B27.Yang deficiency is the basic constitution type of AS,and damp-heat constitution is the main constitution type in the progression of AS(especially in the active stage of the disease).The prolongation of the disease will exacerbate the illness condition of AS and then the manifestations of qi deficiency will be more obvious.

Objective By analyzing relevant literature of long COVID,we aimed to understand the current research status,hotspots and trends in this field.Methods Based on Web of Science core collection data,bibliometric analysis was used as the main research method.The results were visualized with VOSviewer.A comprehensive analysis was performed from various perspectives including trends in publication,journal distribution,highly cited papers,international research collaboration networks,and clusters of keywords,etc.Results The field of long COVID has garnered significant global academic attention.A total of 7 877 related articles were retrievable,with a total citation count of 103 389 and an average citation count of 13.13 per article.Among them,the United States published the most articles(1 780 articles,22.59%),while China ranked fifth in publication volume(686 articles,8.71%).The international scientific cooperation network reflected the close collaborative relationships between countries in long COVID research,predominantly involving the United States,the United Kingdom,Italy,India,and China.Keywords clustering indicated that the current main research focuses in the long COVID field include:clinical manifestations,epidemiological characteristics,risk factors,and mechanisms of occurrence,treatment and rehabilitation measures of long COVID,and its impact on public and social life.Conclusion This article reveals the current state,research hotspots and trends in the long COVID field,providing valuable references for related research institutions,scholars as well as health administrative office.