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.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Objective: To understand the correlation between autistic traits in children with autism spectrum disorder(ASD) and their parental behaviors, so as to provide evidence for improving social behavior in children with ASD. Methods: A total of 62 children aged 4-7 years diagnosed with ASD at Guangdong Provincial Work Injury Rehabilitation Hospital and Guangzhou Yuexiu District Children s Hospital from October 2021 to May 2025 were selected as the ASD group. A random number table method was used to select 62 healthy children of the same age from 3 ordinary kindergartens in Guangzhou as the control (typically developing,TD) group. The Parental Behavior Inventory and Social Responsiveness Scale were used to evaluate parental behaviors and autistic traits in both groups. The t-test and multiple linear regression were used to analyze the relationship between autistic traits in children with ASD and parental behaviors. Results: Compared with the TD group, the ASD group had significantly higher scores in social awareness, social cognition, social communication, social motivation, autistic behavior patterns, and the total score of social responsiveness, with statistically significant differences ( t =35.83, 46.17, 64.36, 41.45, 49.46,101.15, all P <0.01). The score of parental support/participation in the ASD group (24.61±4.30) was lower than that in the TD group (31.27±4.58), while the score of parental hostility/coercion in the ASD group (25.51±2.72) was higher than that in the TD group (12.75±2.72), with statistically significant differences ( t = -8.34, 26.14, both P <0.01). The total score of the Social Responsiveness Scale was negatively correlated with the dimension score of parental support/participation behaviors, and positively correlated with the dimension score of parental hostility/coercion behaviors ( r =-0.60, 0.91,both P <0.05). After adjusting for covariates such as children s age, gender, and primary caregiver, ASD children with exclusive breastfeeding ( β =-8.79) and parental support/participation behaviors ( β = -0.79 ) had a lower risk of autistic traits, while children with parental hostility/coercion behaviors ( β =4.62) had a higher risk of autistic traits (all P <0.05). Conclusion Autistic traits in children with ASD may be related to their parental behaviors and early feeding mode.

Objective To observe the value of dual-energy CT(DECT)for diagnosing knee gouty arthritis(GA)complicated with knee osteoarthritis(KOA).Methods Forty-eight cases of GA(GA group),30 cases of KOA(KOA group)and 60 cases of GA complicated with KOA(GA+KOA group)were retrospectively enrolled.Clinical and imaging data were compared among 3 groups and between each 2 groups,and the efficacy of DECT for diagnosing knee GA complicated with KOA was analyzed.Results Significant differences of detection rate and CT value of bone marrow edema(BME)were found among 3 groups and between each 2 groups(all P＜0.05),also of the course of disease,serum uric acid(SUA),monosodium urate(MSU)volume,bone erosion score and CT value between GA group and GA+KOA group(all P＜0.05).The area under the curve(AUC)of bone erosion score and CT value for diagnosing knee GA complicated with KOA was 0.779 and 0.824,respectively,and of the combination of the above 5 indexes was 0.898,higher than that of each parameter alone(all P＜0.05).Conclusion DECT was helpful for diagnosing knee GA complicated with KOA,and further combining with clinical parameters could improve its diagnostic efficacy.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To observe the value of dual-energy CT(DECT)for diagnosing knee gouty arthritis(GA)complicated with knee osteoarthritis(KOA).Methods Forty-eight cases of GA(GA group),30 cases of KOA(KOA group)and 60 cases of GA complicated with KOA(GA+KOA group)were retrospectively enrolled.Clinical and imaging data were compared among 3 groups and between each 2 groups,and the efficacy of DECT for diagnosing knee GA complicated with KOA was analyzed.Results Significant differences of detection rate and CT value of bone marrow edema(BME)were found among 3 groups and between each 2 groups(all P＜0.05),also of the course of disease,serum uric acid(SUA),monosodium urate(MSU)volume,bone erosion score and CT value between GA group and GA+KOA group(all P＜0.05).The area under the curve(AUC)of bone erosion score and CT value for diagnosing knee GA complicated with KOA was 0.779 and 0.824,respectively,and of the combination of the above 5 indexes was 0.898,higher than that of each parameter alone(all P＜0.05).Conclusion DECT was helpful for diagnosing knee GA complicated with KOA,and further combining with clinical parameters could improve its diagnostic efficacy.

Objective To investigate the clinical characteristics of preoperative intestinal symptoms in patients with bowel endometriosis and to compare the effects of shaving versus segmental bowel resection on postoperative intestinal function.Methods A total of 105 patients diagnosed with bowel endometriosis and treated by the same surgical team at the Obstetrics and Gynecology Hospital,Fudan University between Aug 1,2013 and Dec 30,2017 were prospectively enrolled in this study.Clinical data were collected via outpatient visits and telephone follow-ups at four time points:preoperative(T0)and postoperative(T1:Nov 2018;T2:Nov 2020;T3:Apr 2024).The primary outcome was bowel symptoms and gastrointestinal function scores;secondary outcome was pain scores.A generalized estimating equation(GEE)model was used to analyze the interaction effect of surgical approach and follow-up time on outcomes.Results Ultimately,a total of 89 patients were included(15.24%loss to follow-up),among whom 79 patients(88.76%)underwent shaving excision.Preoperatively,46 patients(51.68%)presented with bowel symptoms,primarily anus bulge(21 cases,46.65%)and diarrhea(15 cases,32.61%)during menstruation.Postoperatively,there was a significant increase in constipation rates(T1:71.43%;T2:50.00%;T3:72.00%).Both surgical groups exhibited significant improvements in dysmenorrhea,gastrointestinal discomfort scores as well as gastrointestinal quality of life index(P<0.000 5).However,the segmental resection group had significantly higher scores for low anterior resection syndrome,constipation compared with the shaving excision group(P=0.02 and P=0.05).Conclusion Approximately half of the patients with bowel endometriosis exhibit typical bowel symptoms preoperatively,such as anus bulge and diarrhea.Both shaving excision and segmental resection effectively alleviate pain;however,shaving excision demonstrates an advantage regarding preservation of bowel function,whereas segmental resection may elevate risks associated with postoperative constipation or altered defecation patterns due to structural changes.The selection of surgical approach should carefully balance lesion removal and functional preservation,moreover,be sure that potential risks are thoroughly informed to patients prior to surgery.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To investigate the clinical characteristics of preoperative intestinal symptoms in patients with bowel endometriosis and to compare the effects of shaving versus segmental bowel resection on postoperative intestinal function.Methods A total of 105 patients diagnosed with bowel endometriosis and treated by the same surgical team at the Obstetrics and Gynecology Hospital,Fudan University between Aug 1,2013 and Dec 30,2017 were prospectively enrolled in this study.Clinical data were collected via outpatient visits and telephone follow-ups at four time points:preoperative(T0)and postoperative(T1:Nov 2018;T2:Nov 2020;T3:Apr 2024).The primary outcome was bowel symptoms and gastrointestinal function scores;secondary outcome was pain scores.A generalized estimating equation(GEE)model was used to analyze the interaction effect of surgical approach and follow-up time on outcomes.Results Ultimately,a total of 89 patients were included(15.24%loss to follow-up),among whom 79 patients(88.76%)underwent shaving excision.Preoperatively,46 patients(51.68%)presented with bowel symptoms,primarily anus bulge(21 cases,46.65%)and diarrhea(15 cases,32.61%)during menstruation.Postoperatively,there was a significant increase in constipation rates(T1:71.43%;T2:50.00%;T3:72.00%).Both surgical groups exhibited significant improvements in dysmenorrhea,gastrointestinal discomfort scores as well as gastrointestinal quality of life index(P<0.000 5).However,the segmental resection group had significantly higher scores for low anterior resection syndrome,constipation compared with the shaving excision group(P=0.02 and P=0.05).Conclusion Approximately half of the patients with bowel endometriosis exhibit typical bowel symptoms preoperatively,such as anus bulge and diarrhea.Both shaving excision and segmental resection effectively alleviate pain;however,shaving excision demonstrates an advantage regarding preservation of bowel function,whereas segmental resection may elevate risks associated with postoperative constipation or altered defecation patterns due to structural changes.The selection of surgical approach should carefully balance lesion removal and functional preservation,moreover,be sure that potential risks are thoroughly informed to patients prior to surgery.