Objective: To investigate the epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome (SFTS) in Huai'an City, Jiangsu Province from 2011 to 2024, so as to provide a basis for optimizing local SFTS prevention and control strategies, and identifying high-risk areas and key populations. Methods: Data on SFTS incidence and deaths in Huai'an City from 2011 to 2024 were collected from the Infectious Disease Reporting Information System of the Chinese Disease Prevention and Control Information System. The reported incidence, mortality, and fatality rates were calculated. Descriptive analysis was performed on temporal, population, and regional distribution. The average annual percent change (AAPC) was used to analyze the trend in the reported incidence of SFTS. Global and local spatial autocorrelation analyses were employed to examine the spatial distribution patterns and spatial association patterns of SFTS incidence while spatio-temporal scanning analyses was used to assess the spatial-temporal clustering of SFTS. Results: A total of 337 SFTS cases were reported in Huai'an City from 2011 to 2024, with the reported incidence rising from 0.17/100 000 to 1.88/100 000. There were 20 deaths, with an average annual mortality of 0.03/100 000, and a fatality rate of 5.93%. The incidence showed obvious seasonality, with a peak in May and June (148 cases, accounting for 43.92%). Spring and summer accounted for 107 cases (31.75%) and 159 cases (47.18%), respectively. The reported SFTS cases were mainly male, farmers, and individuals aged ≥41 years, accounting for 56.38%, 79.23%, and 96.74%, respectively. The population distribution of death cases was basically consistent with that of incident cases. Xuyi County was a high-incidence area, with a total of 332 reported cases, accounting for 98.52%. All death cases were reported in this county. Spatial autocorrelation analyses revealed a positive spatial correlation in SFTS incidence from 2019 to 2024, with Moran's I values ranging from 0.214 to 0.336 (all P<0.05). Heqiao Town, Tianquanhu Town, and Guiwu Town in Xuyi County were identified as high-high clustering areas. Spatio-temporal scanning analyses showed that cluster 1 was consistent with the high-high clustering areas, with an aggregation time from the second quarter of 2019 to the second quarter of 2022. Conclusions From 2011 to 2024, the reported incidence of SFTS in Huai'an City showed an upward trend, with a high incidence in spring and summer. Males, farmers, and the middle-aged and elderly population were the key populations for prevention and control. Xuyi County was the key area for prevention and control.

Objective To explore the application value of three mainstream large language models in the diagnosis, differential diagnosis, and treatment decision support of the primary diseases related to pediatric liver transplantation. Methods Seventy-nine cases of pediatric liver transplantation-related diseases diagnosed through pathological or clinical follow-up data were collected from Renji Hospital, Shanghai Jiao Tong University School of Medicine or published high-quality case reports. These cases covered 25 types of primary diseases such as cholestatic liver disease, metabolic diseases, and tumors. Standardized prompts were used to input the case information into the DeepSeek-R1, ChatGPT-4o and Grok-3 models, and the accuracy of their preliminary diagnosis and differential diagnosis based on basic clinical data was evaluated. The final diagnosis accuracy and the response time after supplementary examination were also assessed, as well as the completeness and rationality of their analysis of disease treatment principles. Results In the initial diagnosis and differential diagnosis stage, the comprehensive accuracy of DeepSeek-R1 was the highest [72.1%, 95% confidence interval (CI) 61.4% - 80.8%], and there was a statistically significant difference in the comprehensive accuracy of the three models for initial diagnosis (P = 0.008). After adding further examination information, the final diagnosis accuracy of the three models increased, with DeepSeek-R1 at 88.6% (95% CI 79.7% - 93.9%), ChatGPT-4o at 87.3% (95% CI 78.2% - 93.0%), and Grok-3 at 78.5% (95% CI 68.2% - 86.1%). There was no statistically significant difference among the three models (P = 0.05). The scores given by experts for the treatment principles showed good consistency (Kappa = 0.769). In addition, the response time of ChatGPT-4o is shorter than that of the other two models [(24 ± 7) s]. Conclusions Large language models demonstrate good efficacy in the diagnosis and treatment decision-making process of various pediatric liver diseases, have a good application prospect for auxiliary diagnosis and decision support, and are expected to help improve the accuracy and efficiency of clinical diagnosis and treatment of pediatric liver transplantation-related primary diseases.

ObjectiveTo explore the mechanism of Yishen Qubi Tongluo Formula （益肾祛痹通络方， YQTF） in the treatment of rheumatoid arthritis（RA）. MethodsNetwork pharmacology was employed to retrieve and screen the active components and potential targets of YQTF as well as RA-related targets using databases including TCMSP， BATMAN， ETCM and GEO. The intersection of targets related to active components and RA-related targets was identified， and a protein-protein interaction （PPI） network was constructed. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed， and a drug-active component-common target network of YQTF in the treatment of RA was established. The core components of YQTF were molecularly docked with key targets. Human rheumatoid arthritis synovial fibroblast cell line MH7A was divided into blank group， model group， methotrexate group and YQTF group. The blank group was cultured with 10% fetal bovine serum， while the other three groups were stimulated with 10 μg/L of recombinant human tumor necrosis factor-α （TNF-α） for 24 h to establish the RA cell model. On this basis， the methotrexate group was treated with methotrexate suspension at a concentration of 20 μmol/L， and the YQTF group was treated with 10% YQTF-medicated serum. After 48 h of intervention， the levels of TNF-α and interleukin-17A（IL-17A）contents in cell supernatants were detected by enzyme-linked immunosorbent assay （ELISA）， and mRNA expressions of phosphatidylinositol 3-kinase（PI3K）， protein kinase B（AKT） and mammalian target of rapamycin（mTOR） were detected by real-time quantitative polymerase chain reaction （RT-qPCR）. ResultsNetwork pharmacological analysis identified 209 active components and 583 potential target genes of YQTF， as well as 818 RA-related targets. A total of 29 common targets were obtained from the intersection of drug-related targets and RA-related targets. Quercetin，β-sitosterol， kaempferol， stigmasterol and luteolin were the core active components of YQTF for the treatment of RA， while matrix metalloproteinase-9 （MMP9）， prostaglandin-endoperoxide synthase 2 （PTGS2）， Toll-like receptor 4 （TLR4）， tumor protein p53 （TP53） and transcription factor AP-1 subunit JUN were the key targets. The GO and KEGG pathway enrichment analysis showed that the involved biological processes and pathways were mainly associated with antioxidant responses， PI3K-AKT signaling pathway and Toll-like receptor （TLR） signaling pathway. Molecular docking results showed that MMP9 and PTGS2 exhibited high binding affinities with quercetin， β-sitosterol， kaempferol， stigmasterol and luteolin； TLR4 exhibited high binding activities with β-sitosterol， stigmasterol and luteolin； and TP53 showed high binding affinity with luteolin. The results of cell experiments showed that compared with the control group， the contents of TNF-α and IL-17A as well as the mRNA expressions of AKT and mTOR in the model group significantly increased （P＜0.05 or P＜0.01）. Compared with the model group， all the above indicators significantly decreased in the YQTF group， while the contents of TNF-α and the mRNA expression of AKT significantly decreased in the methotrexate group （P＜0.05 or P＜0.01）. ConclusionThe mechanism of YQTF in the treatment of RA may be associated with reducing inflammatory cytokine secretion and inhibiting the activation of the PI3K-AKT-mTOR signaling pathway.

With the rapid development of sequencing technologies, the detection of alternative polyadenylation (APA) in mammals has become more precise. APA precisely regulates gene expression by altering the length and position of the poly(A) tail, and is involved in various biological processes such as disease occurrence and embryonic development. The research on APA in mammals mainly focuses on the following aspects:(1) identifying APA based on transcriptome data and elucidating their characteristics; (2) investigating the relationship between APA and gene expression regulation to reveal its important role in life regulation;(3) exploring the intrinsic connections between APA and disease occurrence, embryonic development, differentiation, and other life processes to provide new perspectives and methods for disease diagnosis and treatment, as well as uncovering embryonic development regulatory mechanisms. In this review, the classification, mechanisms and functions of APA were elaborated in detail and the methods for APA identifying and APA data resources based on various transcriptome data were systematically summarized. Moreover, we epitomized and provided an outlook on research on APA, emphasizing the role of sequencing technologies in driving studies on APA in mammals. In the future, with the further development of sequencing technology, the regulatory mechanisms of APA in mammals will become clearer.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Kidney stones are a urinary system disease with a high incidence,among which calcium oxalate stones are the most common.Metabolic disorders such as hypertension,diabetes,obesity,hyperlipidemia,and hyperuricemia can cause changes in oxalate,uric acid,and pH and calcium ion concentrations in the urine through multiple pathways including inducing oxidative stress and inflammatory responses by generating reactive oxygen species,ultimately affecting the formation of calcium oxalate stones.This article reviews the possible pathways and mechanisms by which metabolic diseases influence the formation of calcium oxalate stones,providing new ideas for the clinical prevention and treatment of calcium oxalate stones.
Humans ; Calcium Oxalate/metabolism* ; Kidney Calculi/etiology* ; Metabolic Diseases/complications*

Hydronephrosis is a common urological disease,and pregnancy with hydronephrosis is also common.However,it is extremely rare that patients suffering from hydronephrosis after delivery cannot recover on their own.Moreover,due to the no specificity of clinical manifestations,it is easy to be ignored by clinicians.This paper reports a solitary kidney patient with severe dilatation and hydronephrosis of the kidney and ureter that were caused by late pregnancy,and the hydrops could not recover spontaneously after delivery.In addition,the methods of open surgery,ureteroscopy,and ureteral stent placement for many times in other hospital were ineffective for her.The purpose of this study is to improve the attention of clinicians to hydronephrosis during pregnancy and after delivery and provide the reference for clinical treatment.
Humans ; Female ; Hydronephrosis/etiology* ; Adult ; Pregnancy ; Solitary Kidney/complications* ; Pregnancy Complications ; Ureter

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective:It is of great significance to analyze the expression characteristics of immune-related genes in pancreatic cancer and their relationship with prognosis,construct and verify a reliable prognostic model,and explore prognostic methods of pancreatic cancer from the perspective of immune microenvironment.Methods:GSEA enrich-ment analysis of differentially expressed genes in pancreatic cancer was performed to identify key immune-related pathways and genes.The genes involved in the immune pathway were screened through the STRING database and combined with univariate Cox regression and LASSO regression analysis.Three key genes,RIPK2,IRAK2 and CXCL11,were finally identified to construct the prognostic model.The accuracy of the model was evaluated using ROC curves and calibration curves,and verified in an independent verification set(GSE57495).At the same time,the expression pat-terns of key genes in the immune microenvironment were analyzed by single-cell RNA sequencing,and the expression levels of these genes were verified in pancreatic cancer cell lines by RT-qPCR.Results:The expressions of RIPK2,IRAK2 and CXCL11 in pancreatic cancer cell lines were higher than those in normal pancreatic cancer cells(P<0.05).The model based on these three genes divided the patients into a high-risk group(n=87)and a low-risk group(n=89),and the difference in survival time between the high-risk group and the low-risk group was statistically significant(P<0.001).Risk score was correlated with G stage,N stage and tumor residue(P<0.01).Single-cell analysis showed that the ex-pression of these genes was highest in tumor-associated macrophages(mean>0.5)and correlated with regulatory T cells and macrophage infiltration(P<0.05).Multivariate analysis showed that risk score was correlated with overall sur-vival after adjusting for clinical factors(P=0.0014).Conclusion:Based on three key immune-related genes(RIPK2,IRAK2 and CXCL11),we successfully constructed a model to accurately predict the prognosis of pancreatic cancer pa-tients,revealing the important role of these genes in the tumor immune microenvironment,and providing new insights and theoretical basis for pancreatic cancer prognosis assessment and immunotherapy research.

Objective:To evaluate the value of spectral CT quantitative parameters in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Methods:A total of 100 HCC patients who underwent surgical resection and were pathologically diagnosed in the Affiliated Cancer Hospital of Xiangya Medical College of Central South University from January 2020 to January 2023 were retrospectively enrolled. According to pathological grading, the patients were divided into the microvascular invasion group (invasion group, n=60) and the non-vascular invasion group (non-invasion group, n=40). Serological indicators and spectral CT quantitative parameters were compared between the two groups. Receiver operating characteristic (ROC) curve was used to analyze the value of spectral CT quantitative parameters in predicting MVI of HCC. Results:The serum alpha-fetoprotein (AFP) level in the invasion group was higher than that in the non-invasion group, with a statistically significant difference ( P<0.05). There were no statistically significant differences in serum carcinoembryonic antigen (CEA) and carbohydrate antigen 199 (CA-199) levels between the two groups (all P>0.05). In the invasion group, arterial phase iodine concentration, arterial phase normalized iodine concentration, venous phase iodine uptake reduction rate, arterial phase effective atomic number, and energy spectrum curve slope were all higher than those in the non-invasion group, with statistically significant differences (all P<0.05); there were no statistically significant differences in venous phase iodine concentration, venous phase normalized iodine concentration, and venous phase effective atomic number between the two groups (all P>0.05). The rates of peritumoral enhancement in the arterial phase and irregular tumor margin in the invasion group were higher than those in the non-invasion group, with statistically significant differences (all P<0.05); there was no statistically significant difference in tumor capsule between the two groups ( P>0.05). ROC curve analysis showed that the areas under the curve (AUC) of arterial phase iodine concentration, arterial phase normalized iodine concentration, venous phase iodine uptake reduction rate, arterial phase effective atomic number, and energy spectrum curve slope for predicting MVI in HCC were 0.812, 0.885, 0.726, 0.823, and 0.788, respectively. Conclusions:Spectral CT quantitative parameters are helpful to improve the preoperative diagnostic efficiency of MVI in HCC and can effectively predict MVI in HCC. Especially, arterial phase normalized iodine concentration has high application value in judging whether there is MVI in HCC.