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.

Objective To analyze the epidemiological characteristics of hepatitis E (HE) in Huai'an City from 2015 to 2024, and construct and validate the prediction effect of the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, and to provide a scientific basis for HE prevention and control. Methods Data of reported HE cases in Huai'an City from January 2015 to December 2024 were extracted from the National Disease Control and Prevention Information System. Descriptive epidemiological methods were used to analyze the temporal, regional and population distribution characteristics of HE incidence. After data preprocessing, stationarity test and randomness test, the SARIMA model was constructed. The optimal model was selected by minimizing the Akaike Information Criterion (AIC). The model performance was evaluated by adjusted R-squared (Adj R²) and root mean square error (RMSE). The monthly incidence rate of HE in Huai'an City in 2025 was predicted and compared with the actual incidence data to validate the model. Results A total of 1 713 HE cases were reported in Huai'an City from 2015 to 2024, showing a fluctuating upward trend. Huaiyin District (339 cases) and Lianshui County (334 cases) were high-incidence areas. The cases were mainly concentrated in people aged 45 and above (83.3%), males (gender ratio 2.37:1) and farmers (70.8%). The optimal model was SARIMA (1,1,1)×(2,0,1)₁₂, with residual as white noise sequence. There was no statistical difference between the actual incidence and predicted value from January to August 2025 (P>0.05). Conclusion HE incidence in Huai'an has obvious aggregation and temporal fluctuation characteristics. The SARIMA model has a good prediction effect, which can provide reference for formulating targeted prevention and control strategies.

OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

Cremastrae Pseudobulbus Pleiones Pseudobulbus is a Chinese medicinal material used for clearing heat， detoxicifying， resolving phlegm， and dissipating nodules. It is derived from Cremastra appendiculata， Pleione bulbocodioides， or Pleione yunnanensis， as recorded in the 2025 edition of the Pharmacopoeia of the People′s Republic of China， with the former known as Maocigu and the latter two known as Bingqiuzi. Current antitumor studies mainly focus on polysaccharides， water-extracted alcohol-precipitated fractions， and purified extracts of C. appendiculata. Structurally characterized glucomannans suppress breast and liver tumor xenografts and exhibit immunomodulatory effects. The water-extracted alcohol-precipitated fractions inhibit tumor angiogenesis in hepatoma-bearing mice. A purified C. appendiculata extract standardized to five phenanthrene and bibenzyl constituents induces mitochondrial apoptosis in hepatocellular carcinoma cells. Reported pharmacological effects involve cell-cycle regulation， apoptosis， epithelial-mesenchymal transition， angiogenesis， autophagy， and the tumor immune microenvironment， with phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin （PI3K/Akt/mTOR）， Wnt/β-catenin， and Janus kinase 2/signal transducer and activator of transcription 3 （JAK2/STAT3） signaling pathways being the major mechanism links. Quality evaluation of Cremastrae Pseudobulbus Pleiones Pseudobulbus has progressed from single-marker assays to an integrated approach involving botanical authentication， chromatographic fingerprinting， multicomponent analysis， and evaluation of associations between blood-absorbed constituents and antitumor effects. Militarine and dactylorhin A can be used for botanical identification and batch evaluation， and in vivo exposure data from related orchids are concentrated on militarine. Quantitative associations between these constituents and antitumor effects remain to be established. Clinical evidence mainly focuses on formula-based applications and expert experience. Comparative antitumor data in hepatoma models are available for the commercial specifications of Maocigu and Bingqiuzi， whereas parallel evaluations of pharmacological effects， safety windows， and drug interactions among the three official botanical origins remain insufficient. The major limitations are the incomplete standardization of botanical origins and preparations and the lack of quantitative links among quality markers， systemic exposure， antitumor effects， and toxicity endpoints， which constrain reproducible pharmacological evaluation and clinical translation of Cremastrae Pseudobulbus/Pleiones Pseudobulbus.

Objective: o 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 0.17/105 to 1.88/105. There were 20 deaths, with an average annual mortality of 0.03/105, 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.

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.

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.

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*