Objective: To analyze the epidemiological characteristics of varicella among nursery children in Shenzhen from 2015 to 2024, and to evaluate the impact of optimizing varicella vaccine (VarV) immunization strategies on varicella incidence. Methods: Varicella incidence data for nursery children in Shenzhen from 2015 to 2024 were obtained from the China Disease Prevention and Control Information System. The study period was divided into three phases:one dose self pay VarV (January 2015 to October 2017), two dose self pay VarV (November 2017 to October 2019), and two dose free VarV (November 2019 to December 2024). Interrupted time series (ITS) analysis was conducted to assess changes in the level and trend of varicella incidence associated with each phase of policy implementation. Results: A total of 27 517 varicella cases was reported among nursery children from 2015 to 2024, with an average annual incidence of 514.01/100 000. During the same period, 136 clustered outbreaks were reported in nursery institutions, involving a cumulative total of 1 091 cases. ITS analysis showed that during the self pay 1 dose stage, the varicella incidence among nursery children showed an upward trend, with an average monthly increase of 2.58/100 000 (95% CI =2.21/ 100 000 -2.95/100 000, P <0.01). After the implementation of the self pay 2 dose strategy, the incidence decreased, with a change in incidence of -26.12/100 000 (95% CI =-37.30/100 000 to -14.94/100 000) and a change in slope of -2.65/100 000 (95% CI = -3.38/100 000 to -1.93/100 000)(all P <0.01). After the implementation of the free 2 dose strategy, the incidence decreased further, with a change in incidence of -40.03/100 000 (95% CI =-50.39/100 000 to -29.66/100 000, P <0.01) and a change in slope of -0.56/100 000 (95% CI =-1.20/100 000-0.08/100 000, P =0.09). Conclusion The gradual optimization of the VarV vaccination strategy in Shenzhen from self pay 1 dose to free 2 dose has significantly reduced the varicella incidence among nursery children, demonstrating good short term control and long term intervention effectiveness.

Objective To investigate the effects of combined exposure to benzene series, dust and noise on occupational high-frequency hearing loss (HFHL) in the electronics manufacturing industry. Methods A total of 740 employees from an electronic manufacturing enterprise were selected as the study subjects. According to the detection of occupational hazard factors, they were divided into noise group, noise benzene group, and noise dust group, with 325, 167, and 248 people, respectively. Occupational health examinations were conducted on the study participants to analyze their HFHL detection status and influencing factors. Results Among all participants (n=740), 456 (61.62%) were male, 284 (38.38%) were female, and 123 (15.62%) were detected with HFHL. The detection rate of HFHL increased with age and length of service (P<0.01). According to the exposure factor grouping, the detection rates of HFHL in the noise group, noise benzene group, and noise dust group were 12.00%, 19.16%, and 20.97%, respectively (P<0.05). Multivariate logistic regression analysis showed that workers aged ≥ 40 years, with 10-20 years of work experience, ≥ 20 years of work experience, exposure to noise and benzene series, and exposure to noise and dust had an increased risk of developing HFHL to 1.734, 1.923, 3.071, 1.706, and 1.527, respectively (P<0.05). Conclusion Combined exposure to noise and benzene series, combined exposure to noise and dust, as well as age and extended length of service may increase the risk of HFHL among workers.

Objective To investigate the risk factors for ICU-acquired weakness (ICU-AW) in patients with sepsis, and to construct a nomogram prediction model. Methods A total of 360 patients with sepsis admitted from January 2020 to December 2025 were enrolled as study subjects. The risk factors for ICU-AW were identified by logistic regression analysis. A nomogram prediction model was constructed, and the model was validated. Results Multivariate logistic regression analysis indicated that age, APACHE II score, duration of mechanical ventilation, duration of immobilization, duration of sedation, and NLR were risk factors for the occurrence of ICU-AW (P<0.05), while ALB was a protective factor (P<0.05). A nomogram model was constructed based on these seven variables. After validation via Bootstrap resampling, ROC curve showed an AUC of 0.949 (0.929–0.969) and a corrected AUC of 0.942 (0.940–0.948), indicating good discrimination degree of the model. Hosmer-Lemeshow test for calibration curve revealed a chi-square value of 10.188 (P=0.252), suggesting that the predicted value of fitting was generally consistent with the actual value. Decision curve analysis demonstrated that when the threshold was in the range of 0.05–0.9, the model had a good net benefit. Conclusion The nomogram prediction model for sepsis ICU-AW based on seven indicators including age, APACHE II score, NLR, ALB, and the durations of mechanical ventilation, immobilization, and sedation exhibits good predictive efficiency and stability. This nomogram prediction model is helpful for the clinical rapid screening of ICU-AW high-risk groups in patients with sepsis, and meets clinical needs for early warning and precise prevention and control.

Tissue repair requires the reconstruction of functional vascular networks to restore oxygen and nutrient delivery, eliminate metabolic waste, and maintain tissue homeostasis. Although biochemical factors such as growth factors and cytokines have been extensively studied in vascular regeneration, increasing evidence indicates that mechanical signals from the extracellular matrix (ECM) are equally important regulators of angiogenesis. Matrix stiffness, as a major biomechanical property of the tissue microenvironment, provides critical information that influences endothelial cell (EC) behavior and vascular remodeling through mechanotransduction. However, the biological effects of matrix stiffness are not universally defined as either pro- or anti-angiogenic, but are highly dependent on tissue context, cellular composition, disease progression, and the dynamic changes occurring during tissue repair. Therefore, understanding how matrix stiffness regulates vascular regeneration is essential for developing more precise strategies for tissue engineering and regenerative medicine. In this review, we summarize recent advances in the regulation of angiogenesis by matrix stiffness during tissue repair from multiple perspectives. First, we discuss the direct effects of matrix stiffness on EC behaviors, including differentiation, morphological remodeling, migration, proliferation, barrier maintenance, and vascular network formation. ECs sense mechanical alterations in the surrounding matrix through various mechanosensitive structures, including integrins, focal adhesion complexes, and mechanosensitive ion channels such as Piezo1 and TRPV proteins. These mechanical signals are subsequently transmitted through intracellular pathways involving FAK, RhoA/ROCK, MAPK, and Hippo-YAP/TAZ signaling, leading to cytoskeletal reorganization and transcriptional regulation. Through these mechanisms, matrix stiffness regulates endothelial functional states and determines the balance between regenerative vascular formation and pathological vascular remodeling. Beyond the direct regulation of ECs, we further highlight the importance of stiffness-mediated intercellular communication within the regenerative microenvironment. Matrix stiffness can regulate the behavior and secretory profiles of vascular-associated cells, including mesenchymal stem cells and macrophages, thereby indirectly affecting endothelial function through paracrine mechanisms. Changes in matrix mechanics influence the secretion of angiogenic factors, inflammatory cytokines, and extracellular vesicles from these cells, creating a mechanical regulation network that coordinates vascular regeneration. This perspective extends the traditional concept of matrix stiffness from a physical support structure to an active regulatory signal that integrates multiple cellular responses during tissue repair. Furthermore, we discuss the tissue-specific effects of matrix stiffness in vascular regeneration across different organs, including the aorta, lung, liver, and heart. Although excessive matrix stiffening is frequently associated with fibrosis and vascular dysfunction, the consequences of mechanical changes vary considerably among tissues. Moderate stiffness alterations may support endothelial activation and vascular stabilization in certain regenerative contexts, whereas persistent pathological stiffening can promote inflammation, endothelial dysfunction, and impaired vascular repair. These findings emphasize that the biological meaning of “soft” and “stiff” microenvironments should be interpreted according to specific tissue and experimental conditions rather than as universal mechanical classifications. Finally, we summarize current challenges and future perspectives in this field. A major limitation is the lack of standardized mechanical characterization among different studies, as stiffness measurements are influenced by material properties, testing methods, and experimental conditions, limiting direct comparison across research systems. Moreover, most existing models fail to fully reproduce the dynamic and viscoelastic properties of native ECM during tissue regeneration. Future studies should combine advanced biomaterials with standardized mechanical analysis, organoid models, and multi-omics approaches to establish more accurate mechanical regulatory maps. Overall, this review proposes that matrix stiffness is not merely a structural feature of tissues, but an active biological signal that regulates vascular regeneration through coordinated mechanotransduction and multicellular interactions. A deeper understanding of stiffness-mediated vascular regulation will provide new theoretical insights and therapeutic opportunities for improving tissue repair outcomes.

Post-stroke cognitive impairment (PSCI) is a common complication of stroke, which seriously affects the quality of life of patients. Therefore, early and accurate prediction of PSCI is crucial for implementing targeted intervention measures. Quantitative electroencephalography (qEEG), as a non-invasive and objective neurophysiological technique, can provide objective basis for early prediction and targeted intervention of PSCI during the critical period of 72 hours to 1 month after stroke onset. This article reviews the current application status of qEEG in predicting PSCI, aiming to provide theoretical basis for early identification of patients with high-risk PSCI.

TCM believes that the main pathogenesis of gastrointestinal dysfunction (GD) after laparoscopic cholecystectomy (LC) is spleen and stomach weakness, liver and stomach disharmony, liver depression and spleen deficiency, and intestinal depression. Moxibustion in the treatment of GD after LC can avoid the aggravation of gastrointestinal burden caused by oral drugs. The intervention methods mainly include suspension moxibustion, umbilical moxibustion, heat sensitive moxibustion, thunder fire moxibustion, warm acupuncture, partition moxibustion, etc. Moxibustion is often performed on the acupoints in liver meridian, spleen meridian, stomach meridian, small intestine meridian, large intestine meridian and Conception Vessel, such as Taichong (LR3), Ganshu (BL18), Yinlingquan (SP9), Zusanli (ST36), Tianshu (ST25), Wangu (SI4), Hegu (LI4), Zhongwan (CV12), Shenque (CV8) and Qihai (CV6). At present, most studies combined with moxibustion on the basis of conventional Western medicine treatment can significantly improve the efficacy, and have certain advantages in improving gastrointestinal motility decline, intestinal flora imbalance, first exhaust time, gastrointestinal hormone level disorder and intestinal mucosal barrier dysfunction. However, there are still some problems in the existing research: small sample size of clinical research, not perfect scoring scale, not unified treatment plan and operation standard, relatively scarce basic research, relatively simple acupoint research, lack of biochemical evaluation indicators, and the research of national moxibustion needs to be explored and improved in the future.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.

Objective To investigate the factors influencing global longitudinal strain(GLS)measured by cardiac magnetic resonance(CMR)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods Clinical data of 315 hospitalized patients diagnosed with acute STEMI who underwent percutaneous coronary intervention(PCI)at the First Medical Center of Chinese PLA General Hospital from June 2016 to September 2021 were retrospectively collected.After analyzing CMR images of all patients,GLS and other strain parameters were obtained,and then the patients were divided into two groups according to the median GLS.In order to balance gender and age differences,1:1 propensity score matching was performed,and 206 patients were eventually included:GLS>-11.3%group(indicating severe GLS impairment,n=103)and GLS≤-11.3%group(n=103).Baseline characteristics,laboratory indicators,coronary angiographic parameters,electrocardiogram(ECG)features,and CMR parameters were compared between the two groups.Variables showing significant differences were analyzed for their correlation with GLS.Multivariate logistic regression and multiple stepwise linear regression analyses were performed to identify factors associated with GLS impairment.Results Compared with GLS≤-11.3%group,GLS>-11.3%group had significantly higher peak levels of creatine kinase-MB(CK-MB)and troponin T(TnT)(P<0.001).A higher proportion of patients in GLS>-11.3%group had the left anterior descending artery(LAD)as the culprit vessel,while a lower proportion had the right coronary artery(RCA)as the culprit vessel(P<0.001).Additionally,GLS>-11.3%group had longer QRS duration(P<0.001)and a higher incidence of pathological Q waves(P=0.001).Regarding CMR parameters,GLS>-11.3%group exhibited larger global circumferential strain(GCS),infarct size(IS),and left ventricular end-systolic volume(LVESV),as well as lower global radial strain(GRS)and left ventricular ejection fraction(LVEF)(P<0.001).Multivariate logistic regression indicated that peak TnT(OR=1.092,P=0.001),LAD culprit vessel(OR=3.744,P<0.001),and QRS duration(OR=1.026,P<0.001)were significantly associated with severely impaired GLS.Multiple stepwise linear regression analysis showed that the logarithmic value of peak TnT,LAD as the culprit vessel,and the square root of QRS duration were linearly correlated with GLS values(adjusted R2=0.301,P<0.001),and these independent variables explained 30.1%of the variation in GLS.Conclusion Elevated peak TnT,prolonged QRS duration,and LAD as the culprit vessel are significantly associated with severe GLS impairment in STEMI patients,indicating more severe myocardial infarction and worse left ventricular function.

Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

Enhancer of zeste homolog 2(EZH2)is a histone methyltransferase It mediates trimethylation of lysine 27 on histone H3,thereby facilitating the epigenetic silencing of downstream genes.In conjunc-tion with SUZ12,EED,and other components,it constitutes the polycomb repressive complex 2(PRC2)complex.While EZH2 is intricately involved in cellular proliferation and cardiac development,the chan-ges in its expression during cardiac terminal differentiation remain elusive.In this study,we employed differential gene expression analysis of embryonic and adult myocardial cells using the GEO database,and found that EZH2 is highly expressed in embryonic myocardium,but is present at very low levels in adult myocardium(P＜0.0001).Conversely,the expression changes of PRC2 members SUZ12 and EED are not as pronounced.Online analysis through the Tabula Muris database indicates that under physiological conditions,various cell subpopulations in the adult mouse heart exhibit negligible expression of EZH2.Immunohistochemical staining of mouse cardiac tissues shows that EZH2 is highly expressed in embryonic and neonatal myocardium but declines progressively from the first day after birth(P＜0.0001),becoming almost undetectable by the third day.Western blotting further confirms the rapid disappearance of EZH2 expression post-birth(P＜0.05),with EZH1 compensating for the downregulation of EZH2 to maintain H3K27me3 modification levels.Additionally,using the P19 teratocarcinoma stem cell model for cardio-myocyte differentiation,it is observed that EZH2 is significantly upregulated during the transition from cardiac progenitor cells to spontaneously beating cardiomyocytes,correlating with the expression of the cardiomyocyte transcription factor Gata4(P＜0.01).Targeted degradation of EZH2 using the small mole-cule drug MS1943 significantly inhibits the proliferation of induced cardiomyocytes,as evidenced by 5-e-thynyl-2'-deoxyuridine(EdU)incorporation assays(P＜0.01),and RT-qPCR reveals a marked in-crease in the expression of the proliferation inhibitor CDKN1A(P＜0.01).In summary,the high expres-sion of EZH2 in embryonic myocardial cells is associated with enhanced cell proliferation.The rapid loss of EZH2 expression postnatally correlates with the loss of proliferative capacity in cardiomyocytes,mark-ing it as a key indicator of cardiac terminal differentiation.