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.

ObjectiveTo investigate the correlation between neutrophil-to-lymphocyte ratio （NLR）， platelet-to-lymphocyte ratio （PLR）， systemic immune-inflammation index （SII） and the severity of intrauterine adhesions （IUA）. MethodsThe retrospective study included 380 patients who underwent transcervical resection of adhesions （TCRA） from December 2019 to March 2025. Based on the American Fertility Society （AFS） classification， patients were divided into mild （n=61）， moderate （n=225）， and severe （n=94） groups. NLR， PLR， and SII were calculated from preoperative blood tests. Statistical analyses included Kruskal-Wallis test and ordinal Logistic regression. ResultsNLR， PLR， and SII were significantly higher in the severe IUA group compared to the mild group （P<0.05）， with SII showing the strongest predictive ability （OR=1.004， P=0.001）. The number of intrauterine procedures was an independent risk factor （OR=1.27/level， P=0.016）. The predictive model ［Logit（P）=-0.676+0.241×operation times+0.004×SII］ effectively identified severe IUA cases. ConclusionInflammatory markers （particularly SII） are correlated with IUA severity and may serve as non-invasive tools for clinical assessment.

ObjectiveThe development trend and knowledge structure of the research on human use experience （HUE） of traditional Chinese medicine （TCM） were systematically reviewed， and the core challenges and future directions were identified. This study aims to provide reference for the construction of a scientific and feasible research and development framework and evidence transformation system. MethodsLiterature related to "human use experience" published from January 1， 2019 to July 31， 2025 was retrieved from the China National Knowledge Infrastructure （CNKI）， Wanfang， China Science and Technology Journal Database （VIP）， and PubMed databases. Bibliometric visualization was conducted using Excel， VOSviewer， and CiteSpace， followed by in-depth reading and thematic summarization of core literature. ResultsA total of 181 papers were included for bibliometric analysis， with 45 articles used for in-depth thematic mining. The analysis showed that the number of publications on HUE research has increased in a stepwise manner over the past five years. Yang Zhongqi （24 times） was the core of the author network， the journal with the highest number of publications was China Journal of Chinese Materia Medica， the institutions publishing the most articles were mainly research institutions， regulatory agencies， hospitals， and universities， high-frequency keywords included "new TCM drugs"， "real-world studies"， and "clinical comprehensive evaluation"， keyword clustering analysis formed three major clusters： Policy orientation， application fields， and methodological approaches. Thematic analysis reveals that HUE-based evaluation should be integrated throughout the research and development process， encompassing three dimensions： TCM theory， clinical value， and pharmaceutical fundamentals， with toxic herbs and compatibility contraindications being key foci. Data collection primarily relies on empirical data， while real-world data constitute the primary source for clinical research， with efficacy and safety as the shared core. Data management emphasizes quality control and statistical analysis； however， the management of bias and confounding remains a critical bottleneck in evidence transformation. In practice， HUE-based approaches have successfully supported the registration and evaluation of multiple categories of new TCM drugs. ConclusionThe research on HUE of TCM has formed a policy-driven pattern characterized by， rapid development and close link with regulatory practice. A technical framework covering the whole chain of research and development has been constructed with clinical value as the core， which provides methodological basis and strategy reference for the scientific transformation of HUE of TCM from "experience" to "evidence".

ObjectiveTo analyze the processing mechanism underlying the enhanced effect of invigorating spleen and stopping diarrhea of soil-fried Atractylodis Macrocephalae Rhizoma（AMR） by analyzing the changes of microstructure， chemical composition and anti-ulcerative colitis（UC） activity before and after soil stir-frying. MethodsThe microstructure and elemental composition of AMR before and after soil stir-frying were analyzed by scanning electron microscopy-energy dispersive spectroscopy（SEM-EDS）， to investigate the differences in microstructure and the underlying causes. Ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） coupled with UNIFI 1.9.2 natural product analysis platform were used to analyze and identify the chemical constituents in raw and soil-fried products， and multivariate statistical methods including principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to explore the differences and sources of chemical constituents between them. A dextran sulfate sodium（DSS）-induced UC mouse model was established. The method of disease activity index（DAI） was used to evaluate the severity of intestinal inflammation. Hematoxylin-eosin（HE） staining was used to observe the pathological changes of colon tissue， enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of inflammatory factors， Real-time quantitative polymerase chain reaction（Real-time PCR） and Western blot were used to analyze the expressions of key genes and proteins involved in the intestinal mucosal barrier. The 16S rRNA sequencing was used to evaluate the diversity of intestinal flora， headspace gas chromatography-mass spectrometry（HS-GC-MS） was used to explore the levels of short-chain fatty acids（SCFAs） in feces. Base on the above findings， this paper investigated the effects of raw and soil-fried AMR on the biological， chemical， mechanical and immune barriers of model animals， and the differences in pharmacological effects and underlying mechanisms from the perspective of regulating the intestinal mucosal barrier in UC mice. ResultsSEM observation revealed numerous hearth soil particles on the surface of soil-fried AMR， accompanied by bubble-like bulges. At the same time， there were many cracks and folds on the surface of the hearth soil. EDS analysis revealed that the contents of Si， Al， Mg and Ca in soil-fried AMR were significantly higher than those of raw products， and these elements constituted the primary components of hearth soil. UPLC-Q-TOF-MS combined with database comparison was used to identify the chemical constituents of raw and soil-fried AMR. In positive ion mode， a total of 132 components were identified， primarily comprising three categories of terpenoids， polyphenols and amino acids. In negative ion mode， a total of 40 components were identified， primarily polyphenolic and glycoside compounds. Among them， the contents of sesquiterpenes and polyphenolic acids were changed significantly before and after processing. Soil-fried AMR could reduce the DAI score of UC mice， alleviate the shortening of colon length， reduce the levels of pro-inflammatory factors such as interleukin（IL）-17， IL-18， γ-interferon（IFN-γ） and tumor necrosis factor（TNF）-α in serum， increase the levels of anti-inflammatory factors such as secretory immunoglobulin A（sIgA）， IL-10， IL-4 and transforming growth factor-β（TGF-β） in serum， increase the expressions of key genes and proteins of intestinal mucosal barrier such as tight junction protein-1（ZO-1）， Occludin， Claudin-1 and mucin 2（MUC2） in colonic mucosa， and improve the disorders of intestinal flora diversity and the levels of SCFAs（P<0.05， P<0.01）. The raw and stir-fried products of AMR also exhibited the aforementioned effects， but they were weaker than the soil-fried products. Additionally， the auxiliary material hearth soil also had a certain pharmacodynamic effect. ConclusionSoil-fried AMR can enhance the protective effect on intestinal mucosal barrier in UC mice. These changes or heating-induced alterations in the microscopic structure and chemical composition of AMR may be attributed to the dual effects of adsorption of hearth soil.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

ObjectiveTo analyze the processing mechanism underlying the enhanced effect of invigorating spleen and stopping diarrhea of soil-fried Atractylodis Macrocephalae Rhizoma（AMR） by analyzing the changes of microstructure， chemical composition and anti-ulcerative colitis（UC） activity before and after soil stir-frying. MethodsThe microstructure and elemental composition of AMR before and after soil stir-frying were analyzed by scanning electron microscopy-energy dispersive spectroscopy（SEM-EDS）， to investigate the differences in microstructure and the underlying causes. Ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） coupled with UNIFI 1.9.2 natural product analysis platform were used to analyze and identify the chemical constituents in raw and soil-fried products， and multivariate statistical methods including principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA） were used to explore the differences and sources of chemical constituents between them. A dextran sulfate sodium（DSS）-induced UC mouse model was established. The method of disease activity index（DAI） was used to evaluate the severity of intestinal inflammation. Hematoxylin-eosin（HE） staining was used to observe the pathological changes of colon tissue， enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of inflammatory factors， Real-time quantitative polymerase chain reaction（Real-time PCR） and Western blot were used to analyze the expressions of key genes and proteins involved in the intestinal mucosal barrier. The 16S rRNA sequencing was used to evaluate the diversity of intestinal flora， headspace gas chromatography-mass spectrometry（HS-GC-MS） was used to explore the levels of short-chain fatty acids（SCFAs） in feces. Base on the above findings， this paper investigated the effects of raw and soil-fried AMR on the biological， chemical， mechanical and immune barriers of model animals， and the differences in pharmacological effects and underlying mechanisms from the perspective of regulating the intestinal mucosal barrier in UC mice. ResultsSEM observation revealed numerous hearth soil particles on the surface of soil-fried AMR， accompanied by bubble-like bulges. At the same time， there were many cracks and folds on the surface of the hearth soil. EDS analysis revealed that the contents of Si， Al， Mg and Ca in soil-fried AMR were significantly higher than those of raw products， and these elements constituted the primary components of hearth soil. UPLC-Q-TOF-MS combined with database comparison was used to identify the chemical constituents of raw and soil-fried AMR. In positive ion mode， a total of 132 components were identified， primarily comprising three categories of terpenoids， polyphenols and amino acids. In negative ion mode， a total of 40 components were identified， primarily polyphenolic and glycoside compounds. Among them， the contents of sesquiterpenes and polyphenolic acids were changed significantly before and after processing. Soil-fried AMR could reduce the DAI score of UC mice， alleviate the shortening of colon length， reduce the levels of pro-inflammatory factors such as interleukin（IL）-17， IL-18， γ-interferon（IFN-γ） and tumor necrosis factor（TNF）-α in serum， increase the levels of anti-inflammatory factors such as secretory immunoglobulin A（sIgA）， IL-10， IL-4 and transforming growth factor-β（TGF-β） in serum， increase the expressions of key genes and proteins of intestinal mucosal barrier such as tight junction protein-1（ZO-1）， Occludin， Claudin-1 and mucin 2（MUC2） in colonic mucosa， and improve the disorders of intestinal flora diversity and the levels of SCFAs（P<0.05， P<0.01）. The raw and stir-fried products of AMR also exhibited the aforementioned effects， but they were weaker than the soil-fried products. Additionally， the auxiliary material hearth soil also had a certain pharmacodynamic effect. ConclusionSoil-fried AMR can enhance the protective effect on intestinal mucosal barrier in UC mice. These changes or heating-induced alterations in the microscopic structure and chemical composition of AMR may be attributed to the dual effects of adsorption of hearth soil.

Objective: To understand the epidemiological characteristics of a pertussis outbreak in Guangzhou, so as to provide references for outbreak response and prevention strategies. Methods: From April 5 to June 9, 2024, case screening was conducted among 246 preschool children, 35 staff members, and one full time school nurse in a kindergarten in Guangzhou based on case definition. Field epidemiological investigation methods were employed to collect relevant information, and screening samples were collected from individuals involved in the outbreak. The clinical manifestations, epidemiological characteristics, and risk factors for transmission of the outbreak were analyzed, with rate comparisons performed using the χ 2 test. Results: There were a total of 15 confirmed cases of pertussis in the kindergarten. The main clinical manifestations included intermittent cough in 14 cases ( 93.33 %), sputum production in 5 cases (33.33%), fever in 2 cases (13.33%), paroxysmal spasmodic cough in 1 case (6.67%), and vomiting in 1 case (6.67%). There was no statistically significant difference in the reporting rates of interrupted cough symptoms between pertussis cases (93.33%) and non pertussis cases (92.86%)( χ 2=3.74, P >0.05). The cases were aged 4-5 years, including 5 males and 10 females. The interval between symptom onset and diagnosis ranged from 2 to 25 days, with a median of 10 days. The outbreak involved two classes, with attack rates of 48.28% and 3.45%, respectively. Laboratory testing confirmed 14 close contacts positive for Bordetella pertussisnucleic acid. Among close contacts, only one received prophylactic medication as required. Conclusion The outbreak is a pertussis outbreak in a kindergarten caused by Bordetella pertussis infection, demonstrating distinct temporal and spatial clustering characteristics.

Objective To investigate the causal relationship between gut microbiota and idiopathic pulmonary fibrosis (IPF). Methods Genome-wide association studies (GWAS) data of gut microbiota and IPF were obtained from MiBioGen and IEU OpenGWAS, respectively. Instrumental variables were screened by means of significance, linkage disequilibrium, weak instrumental variable screening, and removal of confounding factors (genetics, smoking, host characteristics). Inverse variance weighted (IVW) was used as the main Mendelian randomization (MR) analysis method, and the weighted median, simple mode, MR-Egger, and weighted mode were used to perform MR to reveal the causal effect of gut microbiota and IPF. The Cochrane's Q, leave-one-out, MR-Egger-intercept, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and Steiger tests were used to analyze the heterogeneity, horizontal pleiotropy, outliers, and directionality, respectively. Results IVW analysis results showed that Actinobacteria [OR=1.773, 95%CI (1.323, 2.377), P<0.001], Erysipelatoclostridium [OR=2.077, 95%CI (1.107, 3.896), P=0.023], and Streptococcus [OR=1.35, 95%CI (1.100, 1.657), P=0.004] could increase the risk of IPF. Bifidobacterium [OR=0.668, 95%CI (0.620, 0.720), P<0.001], Ruminococcus [OR=0.434, 95%CI (0.222, 0.848), P=0.015], and Tyzzerella [OR=0.479, 95%CI (0.304, 0.755), P=0.001] could reduce the risk of IPF. No significant heterogeneity, horizontal pleiotropy, outliers, and reverse causality were found. Conclusion Actinobacteria, Erysipelatoclostridium and Streptococcus may increase the risk of IPF, while Bifidobacterium, Ruminococcus and Tyzzerella may reduce the risk of IPF. Regulation of the above gut microbiota may become a new direction in the study of the pathogenesis of IPF.

Objective: To explore the early effects of birth weight at different gestational ages on blood pressure trajectory among primary school students, so as to provide evidence for incorporating gestational age birth weight into individualized early warning and intervention strategies for childhood hypertension. Methods: From May to November 2023, a purposeful sampling method was used to recruit 1 676 students in grade 1-3 from three primary schools in a certain urban district of Chongqing. Follow up assessments were conducted in May 2024(T1), November 2024(T2), and May 2025(T3). General demographic and birth related information were collected via self administered questionnaires, while height, weight and blood pressure were obtained through physical examinations. Linear mixed effects model was used to analyze the associations between birth weight at different gestational ages and blood pressure trajectories. Results: During the T1-T3 period, the systolic blood pressure of boys were 98.5 (93.0, 104.5 ),98.5 (93.5, 105.0), and 97.5 (92.5, 103.5)mmHg, respectively, while the diastolic blood pressure were 60.5 (56.5, 65.0), 61.5 ( 57.0 , 65.5), and 60.0 (56.0, 64.0)mmHg, respectively. For girls, the systolic blood pressure were 95.5 (90.0, 102.0),95.5 (90.5, 101.5), and 96.0 (90.5, 101.5)mmHg, respectively, and the diastolic blood pressure were 60.5 (56.0, 64.5 ),61.5 (57.5, 65.5), and 59.5 (56.0, 63.0)mmHg, respectively. Through Friedman test within both boys and girls, diostolic blood pressure were statistically significant across three measurements( χ 2=48.85，81.54，both P <0.01). The proportion of normal blood pressure increased , and the proportion of prehypertension and hypertension decreased with time( χ 2=39.72，25.62，both P < 0.01 ). Linear mixed effects model analysis revealed that after adjusting for age, sex, household income monthly, parental education, family history of hypertension and maternal pregnancy complications, large for gestational age had significantly higher trajectories of systolic ( β = 1.50) and diastolic( β =0.94) blood pressure compared to appropriate for gestational age(both P <0.01). Conclusion Large for gestational age is associated with elevated blood pressure trajectories during school age, and it may be considered as an early indicator for individualized screening and intervention for childhood hypertension.