This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

[摘 要] 目的：探讨m6A调控因子在宫颈癌预后评估、免疫微环境特征及治疗反应中的作用，构建基于m6A调控因子的预后风险模型，并分析其与免疫浸润、药物敏感性及细胞间通信的关系。方法：基于TCGA和GEO数据库中宫颈鳞癌及腺癌（CESC）转录组数据，分析22个m6A调控因子的表达与突变情况；采用LASSO‑Cox回归构建m6A相关预后风险模型，并依据风险评分将患者分为高、低风险组。利用CIBERSORT和ESTIMATE算法评估两组免疫细胞浸润及微环境特征；通过oncoPredict预测抗肿瘤药物敏感性。整合单细胞转录组数据（E-MTAB-12305），采用CellChat分析细胞间通信网络。结果：共鉴定出12个在宫颈癌中差异表达的m6A调控因子。高风险组患者总生存期缩短（P < 0.05），免疫评分降低，且对紫杉醇、氟尿嘧啶、多柔比星等抗肿瘤药物敏感性较差（IC50较高）。单细胞分析显示宫颈癌组织中细胞间通信网络发生改变，其中T细胞与内皮/上皮细胞间的相互作用可能主要由CCL5‑ACKR1和MIF‑（CD74 + CXCR4）配体‑受体介导。在临床样本中，对关键的m6A调控因子进行mRNA和蛋白水平的验证，结果显示部分调控因子在宫颈癌组织中的表达水平高于正常宫颈组织（P < 0.05）。结论：m6A调控因子特征可有效预测宫颈癌患者预后，其风险评分与肿瘤免疫浸润、药物敏感性及细胞通信密切相关，为宫颈癌的预后分层及个体化治疗提供了新的分子依据。

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

Objective:To analyze the development trend of medical institution bed allocation in OECD countries and provide insights for optimizing bed resources allocation in China.Methods:Data on indicators of bed allocation and related factors from 1991 to 2022 were collected from the OECD online database.Bed allocation impact dimensions were identified based on health needs and demand theories.The random effect model and correlation analysis were used to explore influencing pathways of bed allocation.Results:The number of beds per 1 000 population and average life expectancy showed a significant positive correlation in countries below the average bed level,while an inverse trend was observed in countries above the average level.The number of long-term care beds per 1000 population showed positive correlation with average life expectancy.Multidimensional factors such as the disease spectrum and bed utilization efficiency were significant correlated with the bed allocation levels.The greater the gap in inpatient and outpatient reimbursement rations,the higher the demand for hospitalization among patients with chronic disease.Conclusions:An optimal number of beds is essential for achieving higher health outcomes.The bed classification planning system should be designed to adapt to demographic changes and strengthen the medical security support system.

Objective To summarize the results of different perioperative anticoagulation protocols for elderly patients with atrial fibrillation(AF)undergoing catheter radiofrequency ablation in our center.Methods A total of 197 elderly AF patients undergoing catheter radiofrequency ablation by a single operator in the First and Sixth Medical Centers of Chinese PLA General Hospital from January 2021 to December 2023 were retrospectively recruited,and the results of relevant exami-nations were collected.Based on the use of different direct oral anticoagulants,they were divided into dabigatran(n=125)and rivaroxaban(n=72)groups.During the procedure,the appropriate dose of unfractionated heparin was administered according to the initial activated clotting time(ACT)with a self-made formula.The time and rate of ACT were recorded,and perioperative ad-verse reactions such as bleeding and thrombosis were observed.Results There were no statistical differences between the two groups in baseline data,including age,gender,BMI,medical history,CHA2DS2-VASc score,HAS-BLED score,and left atrial anteroposterior diameter(P＞0.05).The baseline ACT value was obviously shorter(149.73+23.52 s vs 157.91±24.58 s,P=0.032),the initial heparin dose was significantly higher(0.71±0.12 mg/kg vs 0.65±0.13 mg/kg,P=0.031),and the rate of ACT reaching the target within 15 min was notably lower(60％vs 74％,P＜0.05)in the dabigatran group than the rivaroxaban group.But no significant difference was observed in the rate of ACT reaching the target in 45 min after additional heparin administration according to the formula(86％vs 88％,P＞0.05).The dabigatran group used higher dose of heparin during the procedure than the rivaroxaban group(0.99±0.30 mg/kg vs 0.85±0.31 mg/kg,P=0.009).Peri-cardial effusion was observed in one patient of the rivaroxaban group,and hematoma at the site of femoral vein puncture was seen in one patients of the dabigatran group in 1 d after procedure,which was treated surgically.No other severe complications occurred.Conclusion For elderly pa-tients with AF undergoing catheter ablation therapy,continuous perioperative anticoagulation and individualized application of unfractionated heparin based on initial ACT value can rapidly achieve ACT targets and improve anticoagulation efficacy.

Objective To compare the value of ultrashort echo time(UTE)and T1W sequences for detecting bone erosions of gouty arthritis.Methods Forty-four gouty patients were prospectively enrolled,including 32 cases with affected feet and 12 cases with affected knee.MR UTE and T1W sequence scanning of the affected area were performed,and subjectively scoring of imaging quality of 2 kinds of MRI were evaluated,respectively.Then total number and total score of bone erosions of each case were calculated according to all affected bones.Taken DECT as reference standard,the efficacy of UTE and T1WI for detecting bone erosions was assessed through comparing with DECT using Kappa coefficient.Results The imaging quality score of T1WI was lower than that of DECT(all P＜0.05),while no significant difference was found between UTE and DECT(all P＞0.05).There was high agreement between UTE and DECT for detecting bone erosions(κ=0.949),while the agreement between T1WI and DECT ranged from good to high(κ=0.718 to 0.805).The total number and total score of bone erosions based on T1WI were significantly lower than those based on DECT(all P＜0.05),while no significant difference was found between UTE and DECT(all P＞0.05).Conclusion UTE was better than T1WI for detecting bone erosions of gouty arthritis.

AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.