Objective: To investigate the epidemiological and spatio-temporal characteristics of influenza in Jiaxing City, Zhejiang Province, so as to provide insights into perfecting the prevention and control strategies of influenza. Methods: Data of influenza in Jiaxing City from 2019 to 2023 were collected from the Chinese Disease Prevention and Control Information System. Population data of the same period were collected from the Zhejiang Health Information Network Reporting System. The epidemiological characteristics of influenza were analyzed using descriptive analysis. Vector map information was collected from the Open Street Map, and the spatio-temporal clustering characteristics of influenza were analyzed using spatial autocorrelation and spatio-temporal scanning. Results: A total of 181 501 cases of influenza were reported in Jiaxing City from 2019 to 2023, with an average annual reported incidence of 653.93/105. The majority of cases were aged 5 to <15 years (59 785 cases, 32.94%). The majority of the occupations were students (78 239 cases, 43.11%) and pre-school children (33 715 cases, 18.58%). The county (city, district) with the highest reported incidence was Haining City (1 451.70/105), and the town (street) with the highest reported incidence was Chang'an Town (1 932.78/105). Spatial autocorrelation analysis showed that the incidence of influenza in Jiaxing City from 2019 to 2023 had positive spatial correlations (all Moran's I>0, all P<0.05), with a high-high clustering in the southern region. Spatio-temporal scanning analysis showed that there was a spatio-temporal clustering of influenza in Jiaxing City from 2019 to 2023, with the southern region being the primary-type clustering area and the period between November and January of the following year being the clustering time. Conclusion There was a significant spatio-temporal clustering of influenza in Jiaxing City from 2019 to 2023, with winter being the peak season and the southern region being the primary area.

Objective: To investigate the epidemiological characteristics of pertussis in Jiaxing City from 2004 to 2023 and spatio-temporal clustering characteristics from 2022 to 2023, so as to provide insights into formulation of pertussis control measures. Methods: Data of pertussis cases in Jiaxing City from 2004 to 2023 were collected through the Infectious Disease Report Information System of Chinese Disease Prevention and Control Information System. The epidemiological characteristics of pertussis cases in Jiaxing City from 2004 to 2023 were descriptively analyzed, and the spatio-temporal clustering characteristics from 2022 to 2023 were analyzed using spatio-temporal scanning. Results: A total of 478 pertussis cases were reported in Jiaxing City from 2004 to 2023, with an average annual reported incidence of 0.53/105. The reported incidence showed an upward trend from 2004 to 2023 (P<0.05), with the highest in 2022 (3.17/105). Higher incidence of pertussis was reported in June to August (149 cases, 31.17%) and November to December (112 cases, 23.43%). There was no statistically significant difference in the reported incidence between males and females (0.56/105 vs. 0.50/105, P>0.05). The cases aged under one year accounted for the highest proportion, with 199 cases (41.63%). Haining City (0.68/105), Jiashan County (0.64/105) and Tongxiang City (0.60/105) ranked the top three in the reported incidence of pertussis. Spatio-temporal scanning analysis showed that from 2022 to 2023, the primary clustering area of pertussis was centered in Daqiao Town of Nanhu District, covering 27 towns (streets) in Nanhu District, Jiashan County, Xiuzhou District and Pinghu City, and the clustering time was from November to December, 2023. Conclusions The reported incidence of pertussis was at a low level in Jiaxing City, but showed an upward trend from 2004 to 2023. The incidence of pertussis was higher among infants under one year of age, peaked in June to August and November to December, and was concentrated in Nanhu District and its surrounding areas.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Objective To explore the characteristics of tumor immune microenvironment of pancreatic ductal adenocarcinoma(PDAC)based on the differentially expressed genes associated with macrophages in early and late tumor tissues of PDAC patients,so as to provide new targets for early diagnosis and treatment of PDAC.Methods Three early-stage and 4 late-stage tumor samples were collected from PDAC patients.Tissue transcriptome data were analyzed by single-cell sequencing technology.With The Cancer Genome Atlas(TCGA)database,macrophage related genes differentially expressed in early and late PDAC related to prognosis were obtained.The prognostic risk scoring model was constructed using the least absolute shrinkage and selection operator(LASSO)-Cox method.The risk genes associated with PDAC prognosis were screened using the Gene Expression Profiling Interaction Analysis 2(GEPIA2)online survival analysis tool.Their immune infiltration was analyzed using the cell-type identification by estimating relative subsets of RNA transcripts(CIBERSORT)method,and their expression in different subpopulations of macrophages at different periods was resolved by t-distributed stochastic nearest-neighbour embedding(tSNE)clustering downscaling and the Monocle package.The protein-protein interactions and immunohistochemistry were further analyzed with the help of STRING database and The Human Protein Atlas(HPA)database.Results A total of 48 differentially expressed macrophage-related genes in early and late PDAC were found to be associated with prognosis.Eleven differentially expressed macrophage genes were screened as PDAC prognostic genes,and they were used to construct a prognostic risk scoring model for PDAC.Two prognostic genes with significant risk indicators were screened:2'-5'-oligoadenylate synthetase 2(OAS2)was mainly expressed in secreted phosphoprotein 1(SPP1)-positive macrophages,and assembly factor for spindle microtubules(ASPM)was mainly expressed in proliferation marker protein Ki-67(MKI67)-positive macrophages.There were significant differences in the expression of OAS2 in PDAC macrophages at different stages.Immune infiltration studies showed that OAS2 and ASPM were highly expressed in regulatory T cells and M2-type macrophages(both P＜0.05).Protein-protein interaction network showed the expression relationship between OAS2 and ASPM and other co-expressed proteins.Immunohistochemistry results showed that the expression of OAS2 was higher in tumor tissues than in normal tissues.Conclusion OAS2 and ASPM are both poor prognostic genes that are specifically expressed and exert negative immune effects in SPP1+macrophages and MKI67+macrophages,respectively,promoting the progression of PDAC and ultimately leading to a poor prognosis,and it is expected to provide new targets for the prevention and treatment of PDAC.

Objective:To analyze the effects and mechanisms of ginseng polysaccharide in myocardial fibrosis and endothelial function in coronary heart disease model rats based on mitogen activated extracellular signal regulated kinase (MEK) and extracellular signal regulated kinase (ERK) signaling pathways.Methods:Totally 60 SD rats were divided into control group (10 rats) and model group (50 rats). A coronary heart disease model was established in modeling rats. The successfully modeled rats were divided into model group, drug control group, ginseng polysaccharide high- and low-dosage groups, with 10 rats in each group. The drug control group was orally administered with 2 mg/kg Lipitor solution, while the ginseng polysaccharide low- and high-dosage groups were orally administered with 100 and 200 mg/kg ginseng polysaccharide solution. The control group and model group were orally administered with equal volumes of physiological saline solution once a day for one week. HE staining and Masson staining were used to observe the morphological changes and pathological morphology of myocardial tissue. ELISA was used to detect the levels of NO, eNOS, ET-1, ADMA, TNF-α, CRP, and IL-6. Immunochemiluminescence was used to detect the expression levels of CK-MB and cTnl. Real time fluorescence quantification was used to identify the expression of MEK and ERK. Western blot was used to detect the expression of MEK, ERK, p-MEK, and p-ERK in myocardial tissue.Results:Compared with the model group, the levels of serum NO and eNOS increased in the drug control group and ginseng polysaccharide low- and high-dosage groups ( P<0.05), while the levels of ET-1, ADMA, TNF-α, CRP, IL-6, CK-MB, and cTnl decreased ( P<0.05), and the mRNA and protein expressions of MEK and ERK in myocardial tissue decreased ( P<0.05). Conclusions:Ginseng polysaccharides can improve the degree of myocardial fibrosis in rats, alleviate endothelial function and myocardial injury. Its mechanism may be related to the inhibition of the MEK/ERK signaling pathway.

Objectives:To evaluate the effect of extended single prone positioning ventilation on survival and weaning rate of acute respiratory distress syndrome (ARDS) patients supported by VV-ECMO.Methods:ARDS patients supported by VV-ECMO admitted to Jinhua Central Hospital, the Fourth Affiliated Hospital of Zhejiang University School of Medicine and the First Hospital of Jiaxing from September 2014 to May 2025 were retrospectively enrolled into the study. The clinical data, ECMO and ventilator related parameters and outcomes of the patients were collected. The patients were divided into the extended prone positioning group and prone positioning group according to whether the duration of prone position ventilation was greater than 24 h. The clinical data of the two groups were compared to explore the effects on 30-day survival in-hospital survival and ECMO withdraw rate of these patients. Multivariate logistic regression analysis was used to explore the relationship between the duration of single prone position ventilation and the success of ECMO weaning, 30-day survival and hospital survival.Results:Total of 163 ARDS patients supported by VV-ECMO receiving prone positioning ventilation were included in study, 64 in extended prone positioning group and 72 in prone positioning group. The 30-day survival (54.7% vs. 52.8%) in-hospital survival (51.6% vs. 48.6%) and ECMO withdraw rate (57.8% vs. 61.1%) between the two groups were not statistically different ( P>0.05) as well as the duration of ECMO support [12(10,15)d vs. 11(10,13)d] the duration of ventilation [16(13,18)d vs. 16(12,18)d] the duration of ICU stay [26(15,32)d vs. 26(19,29)d] and the duration of hospital stay [32(15,42)d vs. 34(28,35)d]. Logistic regression analysis revealed that the duration of each prone position ventilation was not associated with successful weaning ( OR=0.979, 95% CI:0.952-1.006), 30-day survival ( OR=1.015, 95% CI: 0.975-1.056) and hospital survival ( OR=1.014, 95% CI: 0.974-1.055) even after adjusting for the severity of illness, age, and type of pneumonia. Conclusions:For ARDS patients supported by VV-ECMO, extended single prone positioning ventilation for more than 24 hours neither increase 30-day survival in-hospital survival and successful ECMO weaning rate, nor shorten ECMO support duration.

The prevalence of diabetes mellitus in China has recently been increasing year by year,and spontaneous skin ulcers in diabetic patients,as one of the most serious complications,often develop on the patient's extremities represented by foot ulcers.Due to the complexity and variety of its pathogenesis,it leads to poor clinical outcomes and difficulty in healing.Thus,pa-tients often face the risk of amputation and death.Therefore,the exploration of mechanisms of the vascular pathogenesis of diabetic delayed-healing wounds and targeted screening of therapeutic agents has become a current research hotspot.Herein,in this paper,we briefly review the role of impaired angiogenesis and vascular dysfunction in diabetic skin ulcers,and the research progress of classical hypoglycemic and natural compounds against vascular lesions is preliminarily summarized to provide a theoretical basis for effective clinical treatment.

Objective:This study was conducted to investigate the independent risk factors for predicting the occurrence of acute Stanford type A aortic dissection(TAAD), and to construct a nomogram model for predicting the occurrence of TAAD.Methods:The clinical data of patients meeting the diagnostic criteria for TAAD admitted to Tianjin Chest Hospital from June 2016 to December 2021 and healthy people examined by the physical examination center of Tianjin Chest Hospital during the same period were retrospectively collected, and the independent risk factors for TAAD were predicted by propensity matching analysis. Univariate and multivariate Logistic regression were used to analyze the variables with statistical differences, and a nomogram model was constructed to predict the occurrence of TAAD disease according to the screened risk factors. Results:A total of 148 patients in the TAAD group and 5 690 patients in the control group were collected. After bias matching analysis, 148 pairs were successfully matched. Multivariate Logistic regression analysis was performed on the matching results. The results showed that hypertension(HBP), diabetes mellitus(T2DM), Lp(a), very low density lipoprotein(VLDL) and apolipoprotein A1/B(ApoA1/B) were independent risk factors for the development of TAAD. HBP, Lp(a) and ApoA1/B were pathogenic factors( OR 7.267, 1.010 and 2.199, P<0.05, respectively), while T2DM and VLDL were protective factors( OR 0.173 and 0.139, P<0.05). Based on the independent risk factors obtained by multi-factor Logistic regression analysis, a nomogram model of TAAD incidence was constructed. The area under ROC curve( AUC) for predicting the onset of TAAD was 81.6%(95% CI: 0.766-0.863), and the internal calibration curve was close to the standard curve. Conclusion:This model has a good degree of differentiation and calibration, which is helpful for clinicians to guide healthy people to prevent the occurrence of TAAD and provide a theoretical basis for the prevention of TAAD.

Objective To explore the feasibility of automatic segmentation of clinical target volume(CTV)and organs at risk(OARs)for cervical cancer using AccuLearning(AL)based on geometric and dosimetric indices.Methods Seventy-five CT localization images with manual contouring data of postoperative cervical cancer were enrolled in this study.Sixty cases were randomly selected to trained to generate automatic segmentation model by AL,and the CTV and OARs of the remaining 15 cases were automatically contoured.Radiotherapy plans on the automatic segmentation contours were imported on the CT images of manual contours.The efficiency,Dice similarity coefficient(DSC),Hausdorff distance(HD)and dosimetric parameters were compared between the two methods.Results The time of automatic segmentation was significantly shorter than that of the manual contour(P<0.05).The DSC of all structures were≥0.87.The HD of bowel bag and rectum were about 10 mm,and that of the rest of OARs were less than 5 mm.CTV(D98,V90% ,V95% ,Dmean,HI),bowel bag(V50)and bladder(V50)had significant differences in dosimetric comparison(P<0.05).Conclusion The automatic segmentation model based on AL can improve the efficiency of radiotherapy.Automatic segmentation of OARs has the potential of clinical application,while that of CTV still needs to be further modified.

Objective To study the expression and clinical significance of neural Wiskott-Alrdich syndrome protein(N-WASP)in pla-centas with preeclampsia.Methods This study included a total of 65 pregnant women:15 in the early-onset preeclampsia group,15 in the early-onset control group,15 in the late-onset preeclampsia group,and 20 in the late-onset control group.Real-time fluorescence quan-titative PCR(RT-qPCR)was used to detect the relative expression of N-WASP mRNA in placental tissues.Western blotting and immu-nohistochemistry were used to detect the expression and position of N-WASP protein in placental tissues from each group.Results RT-qPCR revealed significantly lower N-WASP mRNA expression levels in the placental tissue of the early-onset preeclampsia group compared to those in the early-onset control group(0.50±0.19 vs.0.93±0.73,P＜0.05).The N-WASP mRNA expression levels in late-onset preeclampsia placenta were significantly lower than those in the late-onset control group(0.83±0.34 vs.1.15±0.34,P＜0.05).Western blotting revealed significantly lower N-WASP protein expression in the placental tissue of early-onset preeclampsia compared to that in the early-onset control group(0.35±0.17 vs.0.72±0.21,P＜0.05).The N-WASP protein expression in late-onset preeclampsia placenta was significantly lower than that in the late-onset control group(0.39±0.16 vs.0.76±0.20,P＜0.05).The N-WASP mRNA expression in the placenta negatively correlated with the occurrence of early-onset(r =-0.37,P = 0.042)and late-onset preeclampsia(r =-0.39,P = 0.019).Immunohistochemistry revealed that N-WASP protein was localized in the cytoplasm of syncytiotrophoblasts,cytotrophoblasts,villous stromal cells,and vascular endothelial cells.Conclusion The low expression of N-WASP may be closely associated with preeclampsia.