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.

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.

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

OBJECTIVE: To investigate whether Buyang Huanwu Decoction (BYHWD) had a good curative effect on the neuroprotection of red nucleus neurons after spinal cord injury (SCI) and the possible molecular mechanism. METHODS: Ninety male Sprague-Dawley rats were divided into 5 groups (n=18 per group) according to a random number table, including the control, model, low- (12.78 g/kg, BL group), medium- (25.65 g/kg, BM group), and high-dose BYHWD groups (51.30 g/kg, BH group). A rubrospinal tract transection model in rats was established, and different doses of BYHWD were intragastrically administrated for 4 weeks. The forelimb locomotor function was recorded using the spontaneous vertical exploration test. Cyclic adenosine monophosphate (cAMP) level in red nucleus was detected through an enzyme-linked immunosorbent assay. The morphology and number of red nucleus neurons were observed using Nissl's staining and axonal retrograde tracing by Fluoro-Gold (FG). The expression of cAMP-dependent protein kinase A (PKA), nuclear factor kappa-B (NF-κB) p65, and brain-derived neurotrophic factor (BDNF) in red nucleus were detected using immunohistochemistry and quantitative real-time polymerase chain reaction. RESULTS: Compared with the control group, the utilization rate of bilateral forelimbs, unilateral right forelimbs, proportion of FG-labeled positive neurons, cAMP level, protein expressions of PKA and BDNF, and BDNF mRNA expression were significantly decreased in the model group (P<0.01), while NF-κB p65 was increased in the model group (P<0.01). Compared with the model group, the utilization rate of bilateral forelimbs and unilateral right forelimbs were significantly higher in the BL, BM and BH groups (P<0.01), the proportion of FG-labeled positive neurons, cAMP level, protein expressions of PKA and BDNF and BDNF mRNA expression in all BYHWD groups were increased (P<0.05 or P<0.01), while NF-κB p65 were decreased in all BYHWD groups (P<0.05 or P<0.01). CONCLUSIONS BYHWD possesses a sound neuroprotective effect on red nucleus neurons after SCI, and the efficacy was dose-related. The mechanism may be related to regulating the cAMP/PKA/NF-κ B p65 signaling pathway, finally promoting expression of BDNF.
Animals ; Spinal Cord Injuries/pathology* ; Drugs, Chinese Herbal/therapeutic use* ; Rats, Sprague-Dawley ; Male ; Cyclic AMP/metabolism* ; Transcription Factor RelA/metabolism* ; Cyclic AMP-Dependent Protein Kinases/metabolism* ; Signal Transduction/drug effects* ; Brain-Derived Neurotrophic Factor/genetics* ; Red Nucleus/metabolism* ; Recovery of Function/drug effects* ; Neurons/metabolism* ; Rats

Immunotherapy has become a pivotal modality in clinical cancer treatment. However, its effectiveness is limited to a small subset of patients due to the low antigenicity, impaired innate response, and various adaptive immune resistance mechanisms of the tumor microenvironment (TME). Accumulating evidence reveals the critical roles of metal elements in shaping immunity against tumor progression and metastasis. The marriage of metalloimmunotherapy and nanotechnology further presents new opportunities to optimize the physicochemical and pharmacokinetic properties of metal ions in a precise spatiotemporal control manner. Several metallodrugs have demonstrated encouraging immunotherapeutic potential in preliminary studies and are currently undergoing clinical trials at different stages, yet challenges persist in scaling up production and addressing long-term biosafety concerns. This review delineates how metal materials modulate biological activities across diverse cell types to orchestrate antitumor immunity. Moreover, it summarizes recent progress in smart drug delivery-release systems integrating metal elements, either as cargo or vehicles, to enhance antitumor immune responses. Finally, the review introduces current clinical applications of nanomedicines in metalloimmunotherapy and discusses potential challenges that impede its widespread translation into clinical practice.

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

Nichrome(NiCr)wire with strong mechanical properties,excellent flexibility,good corrosion resistance and high thermal stability was selected as a promising fiber substrate to replace the fragile fused-silica counterpart.The NiCr layered double hydroxide nanosheets(NiCr LDHs NSs)were in-situ grown on the NiCr fiber substrate.Then,the extraction performance of the NiCr@NiCr LDHs NSs fiber was evaluated using four kinds of chlorophenol(CPs)as model compounds combined with high performance liquid chromatography-ultraviolet detection(HPLC-UV).The results showed that the assembled fibers exhibited superior extraction selectivity and enhanced extraction efficiency for CPs in comparison to commercial PA,PDMS,and PDMS/DVB fibers.Under the optimized experimental conditions,the established method showed good linearity in the range of 0.2-200 μg/L,with coefficient of determination(R2)>0.9989.The limits of detection(LODs)and limits of quantification(LOQs)were 0.050-0.157 μg/L and 0.165-0.502 μg/L,respectively.Relative standard deviations(RSDs)for intra-day and inter-day analyses ranged from 2.85%to 4.05%and from 3.16%to 4.96%,respectively.The developed method with the constructed fiber was applied to preconcentration and detection of different types of CPs in real water samples,showing satisfactory recoveries ranging from 80.0%to 106.9%,with RSDs of 3.12%-7.81%.Moreover,the NiCr@NiCr LDHs NSs fiber could maintain good extraction performance even after 240 extraction-desorption cycles.