ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

The innate immune system detects cellular stressors and microbial infections, activating programmed cell death (PCD) pathways to eliminate intracellular pathogens and maintain homeostasis. Among these pathways, pyroptosis, apoptosis, and necroptosis represent the most characteristic forms of PCD. Although initially regarded as mechanistically distinct, emerging research has revealed significant crosstalk among their signaling cascades. Consequently, the concept of PANoptosis has been proposed—an inflammatory cell death pathway driven by caspases and receptor-interacting protein kinases (RIPKs), and regulated by the PANoptosome, which integrates key features of pyroptosis, apoptosis, and necroptosis. The core mechanism of PANoptosis involves the assembly and activation of the PANoptosome, a macromolecular complex composed of three structural components: sensor proteins, adaptor proteins, and effector proteins. Sensors detect upstream stimuli and transmit signals downstream, recruiting critical molecules via adaptors to form a molecular scaffold. This scaffold activates effectors, triggering intracellular signaling cascades that culminate in PANoptosis. The PANoptosome is regulated by upstream molecules such as interferon regulatory factor 1 (IRF1), transforming growth factor beta-activated kinase 1 (TAK1), and adenosine deaminase acting on RNA 1 (ADAR1), which function as molecular switches to control PANoptosis. Targeting these switches represents a promising therapeutic strategy. Furthermore, PANoptosis is influenced by organelle functions, including those of the mitochondria, endoplasmic reticulum, and lysosomes, highlighting organelle-targeted interventions as effective regulatory approaches. Cardiovascular diseases (CVDs), the leading global cause of morbidity and mortality, are profoundly impacted by PCD. Extensive crosstalk among multiple cell death pathways in CVDs suggests a complex regulatory network. As a novel cell death modality bridging pyroptosis, apoptosis, and necroptosis, PANoptosis offers fresh insights into the complexity of cell death and provides innovative strategies for CVD treatment. This review summarizes current evidence linking PANoptosis to various CVDs, including myocardial ischemia/reperfusion injury, myocardial infarction, heart failure, arrhythmogenic cardiomyopathy, sepsis-induced cardiomyopathy, cardiotoxic injury, atherosclerosis, abdominal aortic aneurysm, thoracic aortic aneurysm and dissection, and vascular toxic injury, thereby providing critical clinical insights into CVD pathophysiology. However, the current understanding of PANoptosis in CVDs remains incomplete. First, while PANoptosis in cardiomyocytes and vascular smooth muscle cells has been implicated in CVD pathogenesis, its role in other cell types—such as vascular endothelial cells and immune cells (e.g., macrophages)—warrants further investigation. Second, although pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) are known to activate the PANoptosome in infectious diseases, the stimuli driving PANoptosis in CVDs remain poorly defined. Additionally, methodological challenges persist in identifying PANoptosome assembly in CVDs and in establishing reliable PANoptosis models. Beyond the diseases discussed, PANoptosis may also play a role in viral myocarditis and diabetic cardiomyopathy, necessitating further exploration. In conclusion, elucidating the role of PANoptosis in CVDs opens new avenues for drug development. Targeting this pathway could yield transformative therapies, addressing unmet clinical needs in cardiovascular medicine.

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.

Objective To explore the application value of combining the ultrasound breast imaging reporting and data system(BI-RADS)classification with serum fibroblast growth factor receptor 1(FGFR1)and growth differentiation factor 3(GDF3)in the differential diagnosis of benign and malignant breast masses.Methods A total of 159 patients with breast masses were selected and divided into the benign mass group(n=83)and the malignant mass group(n=76)based on postoperative pathological diagnosis.All patients underwent ultrasound examination,and enzyme-linked immunosorbent assay(ELISA)was applied to detect serum levels of FGFR1 and GDF3.Receiver operating characteristic(ROC)curve was applied to analyze the diagnostic value of ultrasound BI-RADS classification and serum FGFR1 and GDF3 levels for benign and malignant breast masses.Kappa test was applied to analyze the consistency between various diagnostic methods and pathological diagnosis.Results The serum levels of FGFR1 and GDF3,the proportions of irregular morphology,unclear boundaries,spiculation,microcalcifications,blood flow grade Ⅱ-Ⅲ and posterior echo attenuation,RI and PI were higher in the malignant tumor group than those in the benign tumor group(P＜0.05).The area under the curve(AUC)of FGFR1,GDF3 and ultrasound BI-RADS classification in the differential diagnosis of benign and malignant breast masses separately and in combination was 0.802(95%CI:0.732-0.871),0.817(95%CI:0.751-0.884),0.848(95%CI:0.784-0.912)and 0.956(95%CI:0.918-0.993),respectively.The combined diagnosis was more effective than that of the individual diagnosis of each indicator.The consistency between the individual and combined diagnosis of benign and malignant breast masses and pathological diagnosis showed that the Kappa values were 0.517,0.514,0.688 and 0.912,respectively,with the highest consistency observed in the combined diagnosis(P＜0.05).Conclusion Ultrasound BI-RADS classification combined with serum FGFR1 and GDF3 has high application value in the differential diagnosis of benign and malignant breast masses.

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.

OBJECTIVE: To investigate the expression levels and combined detection efficiency of serum mean corpuscular volume (MCV), mean platelet volume (MPV), and tumor gene ( WT-1) in elderly patients with myelodysplastic syndrome (MDS). METHODS: One hundred elderly MDS patients admitted to our hospital from January 2020 to January 2021 were selected as observation group, and eighty healthy subjects during the same period were selected as control group. The levels of MCV, MPV and WT-1 were detected, and receiver operating characteristic (ROC) curve was drawn to analyze the value of combined detection of the three indicators in the prediction of MDS. The expression and correlation of MCV, MPV and WT-1 in elderly patients with MDS were analyzed and evaluated. RESULTS: The levels of MCV, MPV, and WT-1 in the observation group were higher than those in the control group (all P <0.001). Pearson correlation analysis showed that MCV was positively correlated with MPV and WT-1 (r =0.724, 0.733), while MPV was positively correlated with WT-1 (r =0.731). MCV, MPV, and WT-1 were independent influencing factors for elderly MDS (all P <0.05). The combined detection of the three indicators had the largest area under the curve (AUC) (0.873, 95%CI : 0.776-0.893) in the diagnosis of elderly MDS, with a sensitivity of 95.00%, a specificity of 90.00%, and Youden index of 0.850. The diagnostic value was significantly higher than that of a single indicator (both P <0.05). The levels of MCV, MPV, and WT-1 in severe patients were significantly higher than those in mild patients (all P <0.01). Logistic regression analysis showed that high expression of MCV, MPV, and WT-1 were influencing factors of severe elderly MDS. The ROC curve analysis showed that the combined diagnosis of MCV, MPV and WT-1 had the largest AUC for predicting severe MDS in elderly patients (0.897, 95%CI : 0.709-0.926), and the sensitivity and specificity were 93.18% and 91.07%, respectively (P <0.05). CONCLUSION MCV, MPC, and WT-1 are highly expressed in elderly patients with severe MDS. These three indicators can reflect the bone marrow hematopoietic function status of the subjects. However, compared with single indicator detection, the combined detection of the three indicators is more effective in diagnosis. It has certain advantages in elderly MDS and disease staging, and its promotion and application value is higher.
Humans ; Myelodysplastic Syndromes/blood* ; Aged ; WT1 Proteins/blood* ; Mean Platelet Volume ; Erythrocyte Indices ; ROC Curve ; Male ; Female

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

To address the challenges associated with traditional medical treatment modalities that hinder the efficiency of healthcare delivery,and to facilitate the sharing of medical service information across multiple campuses via mobile platforms,the First Affiliated Hospital to Zhejiang University School of Medicine has proactively leveraged digital intelligence to innovate its medical service model.This program involved the development of a comprehensive process guidance service applet on the Alipay platform specifically for outpatient services.The applet offers intelligent support services,standardizes electronic authentication processes,coordinates medical resources across various hospital locations,and establishes an integrated service delivery system that seamlessly combines online and offline interactions.This approach has optimized the outpatient treatment process,enhanced the patient experience,and fostered standardized management of medical services across multiple campuses.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.