Objective: To explore the association of vegetables and fruits intake with depressive symptoms among multi ethnic first year junior high school students in Yunnan Province, so as to provide data support for preventing and reducing depressive symptoms among first year junior high school students. Methods: From October to December 2022, a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas in Yunnan Province (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County), to investigate with a questionnaire. The Dietary Frequency Questionnaire was used to collect dietary behavior datas, and the Chinese version of Depression Anxiety Stress Scale-21 (DASS-21) was used to assess depressive symptoms. The generalized linear model was used to analyze the association of vegetable and fruit intake with depressive symptoms in students, and stratified analysis was performed according to ethnicity. Results: The detection rate of depressive symptoms among first year junior high school students in Yunnan Province was 29.5%. The detection rates of depressive symptoms in Han and minority first year junior high school students were 26.9% and 31.6%. After controlling for demographic variables such as gender, age, family residence and other confounding factors, the generalized linear model analysis results showed that the intake of leafy vegetables ( β= -0.07 , 95%CI =-0.12 to -0.01), flat fruits ( β=-0.06, 95%CI =-0.12 to -0.00) and hot natured fruits ( β=0.11, 95%CI = 0.04- 0.17) were associated with depressive symptoms in Han first year junior high school students (all P <0.05). The intake of melon and fruit vegetables ( β=-0.06, 95%CI =-0.11 to -0.01) and hot natured fruits ( β=0.06, 95%CI =0.01-0.12) were associated with depressive symptoms in ethnic minority first year junior high school students (both P <0.05). Conclusions The intake of vegetables and fruits among multi ethnic first year junior high school students in Yunnan Province is related to the risk of depressive symptoms. It is suggested to strengthen the consumption guidance and education of vegetables and fruits to prevent depressive symptoms among first year junior high school students.

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

Escherichia coli(E.coli)is a key pathogenic bacterium responsible for postpartum endo-metritis,with its colonization in the reproductive tract closely associated with endometrial damage and disruption of the ovarian cycle.This ultimately leads to infertility,causing significant economic losses to the dairy industry.Macrophages play a pivotal role in the inflammatory response.This study aims to investigate the mRNA expression profile of bovine bone marrow-derived macropha-ges following E.coli infection using RNA sequencing(RNA-seq)technology.Additionally,it seeks to identify the biological functions and signaling pathways of differentially expressed genes(DEGs)through Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses.The results demonstrated that E.coli infection induced differential expression of 4 522 genes,with 2 141 upregulated and 2 381 downregulated.These genes were primarily asso-ciated with inflammatory responses,where TLR2,TLR4,NLRP3,and PTGS2 played pivotal roles.PGD2 synthesis was mediated by TLR2,TLR4,and NLRP3.Transcriptome sequencing of bovine bone marrow-derived macrophages infected with E.coli and treated with a PGD2 inhibitor revealed a marked downregulation of TLR2 and TLR4 gene expression.qPCR validation results were highly consistent with the RNA-seq findings.This study elucidates the interactive regulatory roles of TLR2,TLR4,and NLRP3 in conjunction with PGD2,which collectively modulate bovine endome-tritis.These findings offer significant molecular insights that enhance our understanding of the pathological mechanisms underlying bovine endometritis,thereby informing its prevention and treatment strategies.

Drug repurposing offers a promising alternative to traditional drug development and significantly re-duces costs and timelines by identifying new therapeutic uses for existing drugs.However,the current approaches often rely on limited data sources and simplistic hypotheses,which restrict their ability to capture the multi-faceted nature of biological systems.This study introduces adaptive multi-view learning(AMVL),a novel methodology that integrates chemical-induced transcriptional profiles(CTPs),knowledge graph(KG)embeddings,and large language model(LLM)representations,to enhance drug repurposing predictions.AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning(MVL),matrix factorization,and ensemble optimization techniques to integrate heterogeneous multi-source data.Comprehensive evaluations on benchmark datasets(Fdata-set,Cdataset,and Ydataset)and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art(SOTA)methods,achieving superior accuracy in predicting drug-disease associations across multiple metrics.Literature-based validation further confirmed the model's predictive capabilities,with seven out of the top ten predictions corroborated by post-2011 evidence.To promote transparency and reproducibility,all data and codes used in this study were open-sourced,providing resources for pro-cessing CTPs,KG,and LLM-based similarity calculations,along with the complete AMVL algorithm and benchmarking procedures.By unifying diverse data modalities,AMVL offers a robust and scalable so-lution for accelerating drug discovery,fostering advancements in translational medicine and integrating multi-omics data.We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Drug repurposing offers a promising alternative to traditional drug development and significantly reduces costs and timelines by identifying new therapeutic uses for existing drugs. However, the current approaches often rely on limited data sources and simplistic hypotheses, which restrict their ability to capture the multi-faceted nature of biological systems. This study introduces adaptive multi-view learning (AMVL), a novel methodology that integrates chemical-induced transcriptional profiles (CTPs), knowledge graph (KG) embeddings, and large language model (LLM) representations, to enhance drug repurposing predictions. AMVL incorporates an innovative similarity matrix expansion strategy and leverages multi-view learning (MVL), matrix factorization, and ensemble optimization techniques to integrate heterogeneous multi-source data. Comprehensive evaluations on benchmark datasets (Fdataset, Cdataset, and Ydataset) and the large-scale iDrug dataset demonstrate that AMVL outperforms state-of-the-art (SOTA) methods, achieving superior accuracy in predicting drug-disease associations across multiple metrics. Literature-based validation further confirmed the model's predictive capabilities, with seven out of the top ten predictions corroborated by post-2011 evidence. To promote transparency and reproducibility, all data and codes used in this study were open-sourced, providing resources for processing CTPs, KG, and LLM-based similarity calculations, along with the complete AMVL algorithm and benchmarking procedures. By unifying diverse data modalities, AMVL offers a robust and scalable solution for accelerating drug discovery, fostering advancements in translational medicine and integrating multi-omics data. We aim to inspire further innovations in multi-source data integration and support the development of more precise and efficient strategies for advancing drug discovery and translational medicine.

Standardized training of newly recruited nurses is crucial for enhancing their clinical competencies and facilita-ting rapid adaptation to clinical environments.This approach aims to develop nursing professionals with advanced clinical skills and expertise.This paper reviews and analyzes the training paradigms for new nurses globally,focusing on the challenges faced in the standardized training of new nurses in China,to provide insights and references for future training programs.

Objective To evaluate the effectiveness of WeChat group integrating with BOPPPS instructional model in the standardized training of nurses in an orthopedics department.Methods A total of 56 nurses in orthopedical standardized training from a hospital were selected and divided into a control group(28 nurses from September 2022 to August 2023)and an interven-tion group(28 nurses trained via WeChat groups and the BOPPPS model from September 2023 to August 2024).The two groups were compared in terms of their final assessment scores,critical thinking,and self-directed learning capabilities.Results After training,the intervention group had significantly higher scores in the final assessment,all items of the California Critical Thinking Disposition Inventory,and all dimensions of the Learning Ability Assessment Scale compared to the control group(all P＜0.05).Conclusion WeChat groups combined with the BOPPPS teaching mode effectively improves the self-directed learning ability,critical thinking skills,and assessment results of orthopedic nurses.

Escherichia coli(E.coli)is a key pathogenic bacterium responsible for postpartum endo-metritis,with its colonization in the reproductive tract closely associated with endometrial damage and disruption of the ovarian cycle.This ultimately leads to infertility,causing significant economic losses to the dairy industry.Macrophages play a pivotal role in the inflammatory response.This study aims to investigate the mRNA expression profile of bovine bone marrow-derived macropha-ges following E.coli infection using RNA sequencing(RNA-seq)technology.Additionally,it seeks to identify the biological functions and signaling pathways of differentially expressed genes(DEGs)through Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses.The results demonstrated that E.coli infection induced differential expression of 4 522 genes,with 2 141 upregulated and 2 381 downregulated.These genes were primarily asso-ciated with inflammatory responses,where TLR2,TLR4,NLRP3,and PTGS2 played pivotal roles.PGD2 synthesis was mediated by TLR2,TLR4,and NLRP3.Transcriptome sequencing of bovine bone marrow-derived macrophages infected with E.coli and treated with a PGD2 inhibitor revealed a marked downregulation of TLR2 and TLR4 gene expression.qPCR validation results were highly consistent with the RNA-seq findings.This study elucidates the interactive regulatory roles of TLR2,TLR4,and NLRP3 in conjunction with PGD2,which collectively modulate bovine endome-tritis.These findings offer significant molecular insights that enhance our understanding of the pathological mechanisms underlying bovine endometritis,thereby informing its prevention and treatment strategies.

Objective:To establish a rapid and precise dose measurement method with EBT4 film and ensure its measurement accuracy to be within the required range through strict operational procedures for the purpose of addressing the two essential issues of poor measurement accuracy and timeliness of EBT film under FLASH conditions.Methods:After storing under different humidity conditions for a certain period of time, the film was exposed to radiation for analyzing the influence of air humidity on the intrinsic performance of EBT film. By means of repeated scanning operations and the film angle rotation, the influences of repeated scanning and film placement angle were analuzed. Parabolic correction method was used to reduce the spatial position influence during the scanning process. By analying the relationship between net optical density (netOD) and absorbed dose through the comparison of three fitting method, the optimal fitting curve was selected. After irradiation of the same batch of films for 5 min and 24 h, the film doses were calibrated and then compared with ionization chamber-measured result. The rapid and precise film dosimetry method was used to measure both the percentage depth dose from X-rays at ultra-high dose rate and the dose distribution at a depth of 2 cm in water.Results:Air humidity had the greatest influence on the intrinsic performance of EBT film (approximately 20%). The average deviation of repeated scans is within 0.5%. The angle at which the film is placed significantly affected the readouts of the film with the maximum influence approximately 70%. The net optical density combined with polynomial fitting can control the fitting residuals of 1-16 Gy within 3%. The change rate of light channels at 5 min already mostly met the requirements of the rapid mode (< 0.5%). Compared with the measurement result obtained using the reference ionization chamber, the deviations of the 5 min or 24 h dose calibration curves were all within 2%.Conclusions:The EBT4 film can be employed as a precise dosimeter to quickly measure the FLASH radiation dose. Rapid and precise FLASH dose measurements can meet the stringent requirements of both preclinical and clinical FLASH research.

Objective:To report construction of Evidence-Based Guidelines for the Diagnosis and Treatment of Distal Radius Fractures in Adults (2024) using the Delphi method.Methods:Literature related to the study of adult distal radius fractures was fully searched for and evaluated. An expert group was established from representative experts from all over the nation. The related clinical issues were established by consulting the experts in the form of electronic questionnaires, strictly following the Delphi research method. After the first draft of Evidence-Based Guidelines for the Diagnosis and Treatment of Distal Radius Fractures in Adults (2024) was written, an expert consultation questionnaire was designed for the recommendation opinions to determine the recommendation strength.Results:The clinical issues were determined by 2 rounds of correspondence based on the Delphi method. For the both rounds of correspondence, the questionnaire recovery rates were respectively 88.68% (47/53) and 98.11% (52/53), and the expert authority coefficients >0.7. According to the screening criteria based on the importance of clinical issues (mean importance score <3.5 points or a coefficient of variation ≥0.25 points and a full score ratio <30%) and expert opinions, a total of 40 clinical issues were deleted in the first round of determination of clinical issues, and a total of 5 clinical issues deleted in the second round of determination of clinical issues. The reliability analysis of the results of the 2 rounds of questionnaires showed that the Cronbach α coefficient was >0.9. In the questionnaire to determine the recommendation strength, according to the screening criteria for the consistency of recommendation strength (consistency ≥ 70%) and expert opinions, a total of 26 recommendations were screened in the first round. In the second round when the remaining 4 recommendations were investigated, one recommendation reached the consistency of recommendation strength ≥ 70%. Eventually, 27 recommendations were formed.Conclusion:The Evidence-Based Guidelines for the Diagnosis and Treatment of Distal Radius Fractures in Adults (2024) constructed using the Delphi method shows good scientific validity, authority, and reliability, providing methodological references for guideline development and research.