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.

Periodontitis is a chronic inflammatory disease, and its occurrence and development are closely related to the imbalance of local innate immune responses. The caspase family plays a crucial role in regulating inflammatory responses and cell death pathways in periodontal innate immune cells (such as gingival epithelial cells, neutrophils, macrophages, dendritic cells, and natural killer cells). These proteases exhibit a dual regulatory effect on cellular functions. On one hand, apoptotic pathways mediated by caspase-3/7/9 enable the programmed clearance of senescent or damaged cells, while pyroptosis pathways mediated by caspase-1/4 contribute to immune defense and pathogen elimination, collectively helping to maintain tissue homeostasis. On the other hand, excessive activation of the caspase-1/gasdermin D pathway, as well as inflammatory amplification pathways involving caspase-4/6/8, promotes the release of inflammatory cytokines such as IL-1β and IL-18, leading to the disruption of the epithelial barrier and exacerbation of periodontal tissue damage. Caspase regulation exhibits both commonality and cell specificity. In gingival epithelial cells, caspase-1 mediates pyroptosis and inflammation activation, caspase-3 regulates apoptosis and proliferation signaling, and caspase-4 participates in differentiation regulation and pathogen-selective immune responses, collectively adapting to physiological and pathological changes. Neutrophils can utilize the caspase-1/gasdermin D signaling pathway to drive the release of neutrophil extracellular traps without triggering typical pyroptosis. In macrophages, caspase-1 and caspase-8 synergistically promote polarization toward the M1 phenotype, while caspase-3 acts as an apoptosis executor to facilitate macrophage transition to the M2 phenotype in specific microenvironments. This article reviews caspase’s specific mechanism of action in periodontal innate immune-related cells, aiming to provide a new theoretical basis for targeted regulation of caspase in the treatment of periodontitis.

Objective To evaluate the performance of lightweight Chinese large language models (LLMs) in answering specialized lung cancer questions, and to explore the impact of retrieval-augmented generation (RAG) on model performance. Methods Eleven lightweight Chinese LLMs with parameter sizes ranging from 7B to 32B were included. A lung cancer-specific evaluation dataset consisting of 200 questions [100 A1-type (basic knowledge) and 100 A2-type (clinical case) questions], constructed based on clinical guidelines and thoracic surgery textbooks, was used for assessment. Model performance was evaluated under two conditions (with and without RAG). Accuracy was used to assess model performance, and response latency was recorded to reflect inference efficiency. An accuracy–latency scatter plot was constructed for descriptive analysis of overall model performance. Results All models successfully completed the evaluation. With the introduction of RAG, the overall average accuracy improved from 61.68% to 76.36%. Smaller models demonstrated the most significant improvement (e.g., the accuracy of DeepSeek-7B increased from 32.50% to 60.00%, P<0.001). The average response latency increased from 12.58 s to 13.80 s. The Qwen3 series showed the best overall performance, and Qwen3-32B achieved the highest accuracy under both conditions (76.50% and 84.00%, respectively). After RAG integration, performance differences among model families were markedly reduced. Based on the accuracy-latency trade-off, Qwen3-32B achieved the best balance between accuracy and response latency under the baseline condition, whereas Qwen3-14B demonstrated superior overall performance in terms of accuracy, latency, and computational cost after RAG integration. Conclusion The integration of RAG technology improves the ability of lightweight Chinese LLMs to answer specialized lung cancer questions. Under the dual practical constraints of limited computational resources and medical data security requirements, the "lightweight model+RAG" technical framework may represent a promising deployment solution.

Objective To describe and analyze the epidemiological characteristics of scrub typhus in Huai'an, Jiangsu Province from 2006 to 2024 and explore the long-term incidence trend and distribution of high-risk areas, and to formulate targeted prevention and control strategies. Methods The scrub typhus case report data of Huai'an from 2006 to 2024 in the Chinese Disease Prevention and Control Information System were extracted for descriptive analysis. Results A total of 898 cases of scrub typhus were reported in Huai'an, with an average annual incidence rate of 0.96 per 100 000 from 2006 to 2024. There was a turning point in the incidence trend of scrub typhus in 2011. From 2006 to 2011, the annual percentage change (APC) was 47.09% (95% CI: 7.53 - 859.39), and the upward trend was statistically significant (P < 0.05). From 2012 to 2024, the APC was -2.12% (95% CI: -29.09 - 3.75), and the downward trend was not statistically significant. October and November were the high-incidence months, and the total concentration from 2006 to 2024 was 0.93, indicating that scrub typhus had strict seasonality. The circular distribution method estimated that the peak period of the epidemic was from October 11th to November 25th, and the peak day of incidence was November 3rd. Jinhu County was a high-incidence area. The ratio of male to female cases was 1.03. The age group with the highest reported incidence was 40 to < 80 years old. The occupation with the highest proportion was farmers, accounting for 78.03%. Conclusion From 2006 to 2024, scrub typhus in Huai'an shows a peak every 3 - 4 years. Middle-aged and elderly farmers are the key population at risk, and Jinhu County is a key area. In the future, targeted health education should be carried out to effectively control the prevalence of scrub typhus.

OBJECTIVES: To explore the promoting effect of ginsenoside Rb3 (Rb3) on osteogenesis in periodontitis environment, and to explain its mechanism. METHODS: Human periodontal ligament stem cells (hPDLSCs) were cultured by tissue block method and identified by flow cytometry. Cell counting kit-8 (CCK8) method and calcein acetoxymethyl ester/propidium iodide staining were used to detect the effect of Rb3 on the viability of hPDLSCs cells. In vitro cell experiments were divided into control group, 10 μg/mL lipopolysaccharides (LPS) group, 10 μg/mL LPS+100 μmol/L Rb3 group and 10 μg/mL LPS+200 μmol/L Rb3 group. Alkaline phosphatase (ALP) staining was used to detect the ALP activity of hPDLSCs in each group after osteogenesis induction. The expression of hPDLSCs interleukin-6 (IL-6), interleukin-8 (IL-8), runt-related transcription factor 2 (RUNX2) and transforming growth factor-β (TGF-β)genes in each group after osteogenesis was detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR) method. Western blot was used to detect the protein expression of hPDLSCs phosphorrylated extracellular signal-regulated kinase (p-ERK) in each group. Sprague-Dawley rats were randomly divided into the control group, ligation group and ligation+Rb3 group. The left molar-maxillary tissue was subjected to micro-computed tomography (micro-CT) scanning. After the scanning, the left molar-maxilla was made into periodontal tissue sections. Hematoxylin-eosin (HE) staining was used to detect the infiltration and loss of adhesion of inflammatory cells. Masson staining was used to detect the destruction of gingival collagen fibers. Immunofluorescence staining was used to detect the protein expression of RUNX2 and p-ERK. The expression of TGF-β in rat gingival tissue was detected by qRT-PCR. The protein expression of IL-6 in peripheral serum of rats was detected by enzyme-linked immunosorbent assay (ELISA). Flow cytometry was used to detect the proportion of Treg cells in rat heart blood. The experimental data were statistically analyzed by Graph Pad Prism10.1.2 software. RESULTS: Rb3 had no effect on the cell activity of hPDLSCs. The results of qRT-PCR and ALP staining showed that Rb3 could inhibit the gene expression of IL-6 and IL-8 in inflammatory hPDLSCs, promote TGF-β gene and promote the osteogenic differentiation of inflammatory hPDLSCs. Western blot showed that Rb3 inhibited the protein expression of inflammatory hPDLSCs p-ERK. The results from micro-CT, Masson staining, and HE staining demonstrated that Rb3 promotes alveolar bone formation in rats with periodontitis, while simultaneously inhibiting the destruction of periodontal fibrous tissue, reducing attachment loss, and suppressing inflammatory cell infiltration. The results of flow cytometry showed that Rb3 could promote the differentiation of Treg cells in peripheral blood of periodontitis rats. The results of ELISA and qRT-PCR showed that Rb3 could inhibit the protein expression of IL-6 and promote the gene expression of TGF-β in periodontitis rats. Immunofluorescence results showed that Rb3 could promote the protein expression of RUNX2 and inhibit the protein expression of p-ERK in periodontitis rats. CONCLUSIONS Rb3 can reduce the inflammatory reaction of periodontal tissues in periodontitis rats, and promote the osteogenic differentiation of hPDLSCs by regulating p-ERK pathways.
Animals ; Ginsenosides/pharmacology* ; Osteogenesis/drug effects* ; Periodontitis/metabolism* ; Rats ; Periodontal Ligament/cytology* ; Humans ; Core Binding Factor Alpha 1 Subunit/metabolism* ; Stem Cells/drug effects* ; Interleukin-6/metabolism* ; Rats, Sprague-Dawley ; Interleukin-8/metabolism* ; Cells, Cultured ; MAP Kinase Signaling System/drug effects* ; Transforming Growth Factor beta/metabolism* ; Signal Transduction ; Male ; Phosphorylation ; Lipopolysaccharides ; Extracellular Signal-Regulated MAP Kinases/metabolism* ; Alkaline Phosphatase/metabolism*

Objective To establish a human monocytic THP-1 macrophage-derived foam cell model and analyze the role of the α subunit of coatomer protein Ⅰ(α-COP)in apolipoprotein A-1(apoA-1)-mediated cholesterol efflux from foam cells.Methods THP-1 cells were induced to adhere using PMA(PMA group),followed by treatment with acetylated low-density lipoprotein(Ac-LDL)to generate macrophage-derived foam cells(Ac-LDL group).Subsequent incubation with apoA-1 formed the apoA-1 group.Cholesterol efflux rates mediated by apoA-1 and intracellular lipid accumulation were quantified through liquid scintillation counting and oil red O staining.The expression patterns of α-COP were systematically analyzed using quantitative real-time PCR(qPCR),Western blotting,and laser scanning confocal microscopy.THP-1 macrophage-derived foam cells mediated by apoA-1 were transduced with scrambled shRNA(Scr group)or α-COP-specific shRNA lentivirus(α-COP shRNA group)to assess the effects of α-COP knockdown on cholesterol efflux efficiency and total cellular cholesterol content.Subcellular localization of adipopoilin(ADFP)and cholesterol probe Fil-ipin Ⅲ staining patterns were visualized via laser scanning confocal microscopy.Bioinformatics analysis of α-COP expression profiles in carotid atherosclerotic plaques was performed using datasets from the GEO data-base.Results Compared with the Ac-LDL group,the cholesterol efflux rate in the apoA-1 group was signifi-cantly increased[(9.77±0.79)%vs.(2.74±0.37)%,P＜0.001].Oil red O staining demonstrated reduced lipid accumulation in foam cells of the apoA-1 group compared with the Ac-LDL group.The relative mRNA expression level of α-COP in the apoA-1 group was significantly higher than that in the Ac-LDL group(P＜0.001),with corresponding elevation in protein expression(P＜0.001).Fluorescence intensity analysis re-vealed increased mean fluorescence intensity of α-COP in the apoA-1 group compared with the Ac-LDL group.Following α-COP knockdown by shRNA,the apoA-1-mediated cholesterol efflux rate was significantly de-creased(P＜0.05)and total intracellular cholesterol levels were increased(P＜0.001)in the α-COP shRNA group compared with the Scr group.The α-COP shRNA group exhibited enhanced red fluorescence intensity of ADFP(P＜0.05)and increased blue fluorescence intensity of Filipin Ⅲ(P＜0.01)compared with the Scr group.Database analysis indicated that α-COP mRNA expression was lower in carotid atherosclerotic plaques than in normal arterial tissues,with reduced expression in advanced-stage plaques compared with early-stage plaques(P＜0.05).Conclusion α-COP participates in apoA-1-mediated cholesterol efflux from foam cells,and interference with α-COP expression results in reduced cholesterol efflux and increased intracellular lipid accumulation.

OBJECTIVE To investigate the epidemiological characteristics of Acinetobacter baumannii,detect the distribution of its β-lactamase genes and efflux pump genes,and analyze the relationship between β-lactamase genes and efflux pump genes and the drug resistance of the strains.METHODS Acinetobacter baumannii strains clinically isolated from Jun.2021 to Jun.2022 in Dujiangyan People's Hospital were collected and tested for anti-microbial resistance.Polymerase chain reaction(PCR)technology was used to amplify the β-lactamase genes as well as the efflux pump genes of Acinetobacter baumannii.PaβN was performed to test the efflux pump pheno-type.RESULTS The drug resistance rates of imipenem-resistant Acinetobacter baumannii(IRAB)to cefopera-zone,ceftazidime,cefepime,imipenem,and meropenem were 14.29％,85.71％,91.43％,100.00％and 100.00％,respectively,significantly higher than those of imipenem-sensitive Acinetobacter baumannii(ISAB)(P＜0.05).The detection rates of OXA-23,OXA-51,and IMP-1 in IRAB strains were 45.71％,62.86％and 65.71％,respectively,higher than those in ISAB strains(P＜0.05).The detection rates of the efflux pump genes adeB,adeS,and adeG in IRAB strains were 60.00％,71.43％and 68.57％,respectively,higher than those in ISAB strains(P＜0.05).In addition,the positive rate of the efflux pump phenotype in the IRAB group was 54.29％,significantly higher than 7.69％in the ISAB group(P＜0.001).CONCLUSION The detection rates of β-lactamase genes(such as OXA-23,OXA-51 and IMP-1 etc.)and efflux pump genes(adeB,adeS and adeG)in IRAB are significantly higher than those in the ISAB,and the positive rate of the efflux pump phenotype in IRAB is higher,which confirms that β-lactamase genes and efflux pump genes are important mechanisms of drug resistance in the bacterium.

BACKGROUND:In recent years,artificial intelligence has been increasingly integrated into the diagnosis and treatment of lumbar disc herniation,enhancing the accuracy and efficiency of diagnostic procedures and diversifying therapeutic approaches.This integration has positioned artificial intelligence as a burgeoning focal point within the field.OBJECTIVE:To provide a comprehensive overview of the current applications of artificial intelligence in the diagnosis and treatment of lumbar disc herniation,to analyze the limitations of the relevant technologies.METHODS:A systematic computer-assisted literature search was performed in PubMed,CNKI,WanFang Database,and VIP Database for relevant publications regarding the application of artificial intelligence in the diagnosis and treatment of lumbar disc herniation from database inception up to August 2024.The search keywords included"lumbar disc herniation,artificial intelligence,machine learning,deep learning,big data,robot,neural network,model,algorithm."A total of 101 articles were selected based on predefined inclusion criteria and were reviewed.RESULTS AND CONCLUSION:Different artificial intelligence technologies have propelled the intelligent treatment of lumbar disc herniation,showing great potential for future development.Deep learning technology,based on advanced algorithms,constructs corresponding learning models to optimize the processing of X-ray,CT,and MRI images,achieving precise localization,identification,and analysis of degenerated intervertebral discs,and improving the accuracy of automated diagnosis.Big data technology utilizes data platforms to analyze vast medical data,simulate disease development trends,and provide a new perspective for disease assessment and prediction.Surgical robots,combined with robotic arms,3D high-definition vision systems,and 5G communication technology,support remote precise surgical operations,demonstrating significant technological advantages.In the future,the diagnosis and treatment of lumbar disc herniation by artificial intelligence will evolve towards standardization,efficiency,and precision through continuous optimization of algorithms and the professional development of data platforms.

OBJECTIVE To investigate the epidemiological characteristics of Acinetobacter baumannii,detect the distribution of its β-lactamase genes and efflux pump genes,and analyze the relationship between β-lactamase genes and efflux pump genes and the drug resistance of the strains.METHODS Acinetobacter baumannii strains clinically isolated from Jun.2021 to Jun.2022 in Dujiangyan People's Hospital were collected and tested for anti-microbial resistance.Polymerase chain reaction(PCR)technology was used to amplify the β-lactamase genes as well as the efflux pump genes of Acinetobacter baumannii.PaβN was performed to test the efflux pump pheno-type.RESULTS The drug resistance rates of imipenem-resistant Acinetobacter baumannii(IRAB)to cefopera-zone,ceftazidime,cefepime,imipenem,and meropenem were 14.29％,85.71％,91.43％,100.00％and 100.00％,respectively,significantly higher than those of imipenem-sensitive Acinetobacter baumannii(ISAB)(P＜0.05).The detection rates of OXA-23,OXA-51,and IMP-1 in IRAB strains were 45.71％,62.86％and 65.71％,respectively,higher than those in ISAB strains(P＜0.05).The detection rates of the efflux pump genes adeB,adeS,and adeG in IRAB strains were 60.00％,71.43％and 68.57％,respectively,higher than those in ISAB strains(P＜0.05).In addition,the positive rate of the efflux pump phenotype in the IRAB group was 54.29％,significantly higher than 7.69％in the ISAB group(P＜0.001).CONCLUSION The detection rates of β-lactamase genes(such as OXA-23,OXA-51 and IMP-1 etc.)and efflux pump genes(adeB,adeS and adeG)in IRAB are significantly higher than those in the ISAB,and the positive rate of the efflux pump phenotype in IRAB is higher,which confirms that β-lactamase genes and efflux pump genes are important mechanisms of drug resistance in the bacterium.

BACKGROUND:In recent years,artificial intelligence has been increasingly integrated into the diagnosis and treatment of lumbar disc herniation,enhancing the accuracy and efficiency of diagnostic procedures and diversifying therapeutic approaches.This integration has positioned artificial intelligence as a burgeoning focal point within the field.OBJECTIVE:To provide a comprehensive overview of the current applications of artificial intelligence in the diagnosis and treatment of lumbar disc herniation,to analyze the limitations of the relevant technologies.METHODS:A systematic computer-assisted literature search was performed in PubMed,CNKI,WanFang Database,and VIP Database for relevant publications regarding the application of artificial intelligence in the diagnosis and treatment of lumbar disc herniation from database inception up to August 2024.The search keywords included"lumbar disc herniation,artificial intelligence,machine learning,deep learning,big data,robot,neural network,model,algorithm."A total of 101 articles were selected based on predefined inclusion criteria and were reviewed.RESULTS AND CONCLUSION:Different artificial intelligence technologies have propelled the intelligent treatment of lumbar disc herniation,showing great potential for future development.Deep learning technology,based on advanced algorithms,constructs corresponding learning models to optimize the processing of X-ray,CT,and MRI images,achieving precise localization,identification,and analysis of degenerated intervertebral discs,and improving the accuracy of automated diagnosis.Big data technology utilizes data platforms to analyze vast medical data,simulate disease development trends,and provide a new perspective for disease assessment and prediction.Surgical robots,combined with robotic arms,3D high-definition vision systems,and 5G communication technology,support remote precise surgical operations,demonstrating significant technological advantages.In the future,the diagnosis and treatment of lumbar disc herniation by artificial intelligence will evolve towards standardization,efficiency,and precision through continuous optimization of algorithms and the professional development of data platforms.