Objective To identify key influencing factors for comorbidity between myopia and depressive symptoms among middle school students, and to construct a nomogram predictive model capable of quantitatively assessing their comorbidity risk. Methods A total of 13 976 middle school students aged 11-20 from 14 counties (cities, districts) in Yichang City were selected as study subjects through cluster random sampling. On-site surveys were conducted using the Student Health Status and Influencing Factors Questionnaire and the Depression Assessment Scale. Chi-square test and multivariate logistic regression analysis were employed to investigate the comorbidity association between myopia and depressive symptoms and their influencing factors, and to construct a nomogram model for risk prediction. Results The myopia screening rate among middle school students was 68.67%, the depression detection rate was 23.31%, and the comorbidity detection rate was 16.59%. Logistic regression analysis revealed that boarding school (OR=1.207), smoking history (OR=1.504), alcohol consumption (OR=2.016), outdoor activity time <1 h (OR=1.293), internet addiction (OR=4.008), school bullying (OR=4.358), school absence due to illness within one year (OR=1.712), and severe injury within one year (OR=1.356) were risk factors for myopia-depression comorbidity. Protective factors included male gender (OR=0.578), junior high school students (OR=0.670), nuclear family (OR=0.862), moderate-to-high intensity exercise ≥1 h/d (OR=0.852), screen time <2h (OR=0.803), adequate sleep duration (OR=0.602), and homework time after school <2 h/d (OR=0.766). The nomogram model constructed based on the above variables exhibited excellent discriminant power (AUC = 0.712) and calibration (Hosmer-Lemeshow test, χ²=3.245, P> 0.05). Conclusion Factors such as boarding school attendance, smoking history, alcohol consumption, less than 1 hour of daily outdoor activity, internet addiction, and school bullying are significantly associated with the comorbidity of screening myopia and depressive symptoms among middle school students in Yichang City. The nomogram model effectively predicts the comorbidity risk in this population, facilitating timely intervention for high-risk individuals.

Objective To identify high-risk factors for healthcare-associated infection(HAI)in patients in inten-sive care units(ICUs),and develop a quick response(QR)code-based APP prediction tool.Methods Information of inpatients in general ICUs of three hospitals in Guizhou Province from January to December 2024 were collected.Risk factors were analyzed with a logistic regression model.QR code-based APP was constructed and validated.Results A total of 1 782 patients in general ICUs of three hospitals in Guizhou Province in 2024 were included in the analysis,out of which 410 were HAI cases,and the incidence of HAI was 23.01％.Multivariate logistic regre-ssion analysis results of HAI in ICU inpatients showed that regional gross domestic product(GDP)≥58 685 Yuan,performing pathogen culture during this hospitalization,history of diabetes mellitus,history of cancer,length of hospital stay ≥7 days before infection,and duration of persistent fever＞5 days before infection were independent risk factors for HAI in ICU patients(all P＜0.05).The discrimination of the model(area under the receiver operating characteristic curve[AUC]of 0.841),calibration(Brier score of 0.129),and clinical effectiveness(net benefit of 11.4％when the risk threshold was 5％-74％)all performed well.Conclusion The QR code-based APP prediction tool is of great significance for scientific research transformation and precise HAI control.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective:To explore the relationship between international collaboration papers and academic impact in global health,using the member universities of the Chinese Consortium of Universities for Global Health(CCUGH)as a case study.Methods:The study focuses on journal articles in global health field published by 31 CCUGH member universities between 2014 and 2024.Descriptive statistical analysis of international and non-international collaboration publication volumes was conducted using Excel.Regression analysis and chi-square tests were performed using R to examine the relationship between international collaboration papers and academic impact,and the correlation between the breadth of collaboration and the academic impact of the papers.Results:From 2014 to 2023,the total number of publications,the number of non-international collaborationpublications,and the number of internationally collaborated publications all showed a consistent annual increase,with average annual growth rates of 56.7%,68.3%,and 41.4%,respectively.By the first half of 2024,the total number of publications had increased to 1.5 times that of the corresponding period in 2023.International collaboration positively influenced academic impact,with broader collaborative networks correlating with higher academic influence.Conclusion:The global health publication output of CCUGH member universities has steadily increased,but the volume of international collaboration papers and their proportion remain relatively low.Therefore,it is necessary for CCUGH member universities to strengthen international collaboration papers in global health.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Objective:To investigate the optimal reconstruction grade of IDream reconstruction technique in reducing image noise,optimizing image quality,and displaying liver cysts through the subjective assessment on the display of computed tomography (CT) image with differently reconstructive grades in IDream reconstruction technique of iterative reconstruction algorithm,and the objective evaluation of image quality of upper abdomen. Methods:The imaging data of CT plain scan of 53 patients with hepatic cysts who underwent plain scans on upper abdomen at Peking Union Medical College Hospital from August to September 2021 were retrospectively collected. All images were reconstructed to standard window images by using 6 kinds of methods that included filtered back projection (FBP) and IDream grades 1 to 5,which resulted in 6 groups of images that included FBP group and IDream grades 1-5. The CT values and standard deviation (SD) values of the liver,abdominal aorta,erector spine muscle,fat and spleen in images of each group were measured and recorded,respectively. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images were calculated. Two CT diagnostic physicians with more than 8 years of experience conducted subjective scoring for the display in the images of hepatic cysts of each group. The objective parameters and the subjective scores of hepatic cysts of reconstructive images with different grades were compared. A one-way analysis of variance was adopted to analyze the objective parameters,and Kruskal-Wallis H test was conducted on the subjective score of the display of hepatic cysts. Results:There were no statistically significant differences in the CT values among different reconstruction grades on the liver,abdominal aorta,fat,erector spine muscle and spleen (P>0.05). In the FBP group and IDream grades 1 to 5 groups,the SD values of images gradually decreased with the increasing of the reconstruction grades,which were respectively (18.11±5.03),(15.37±4.97),(13.26±4.83),(11.68±4.56),(10.99±4.36) and (10.60±4.21) Hu. The SNR and CNR of the liver gradually increased. The differences in SD values,SNR,and CNR among the six groups of images were all statistically significant (F=20.75,17.72,3.15,P<0.05),respectively. The subjective scores for the display of hepatic cysts from the FBP group to IDream grades 1 to 4 were respectively (3.12±0.35),(3.63±0.46),(4.02±0.42),(4.61±0.48) and (4.63±0.48),which were gradually increasing,while the score for the IDream grade 5 group slightly decreased to (4.53±0.47). The subjective scores for hepatic cysts in the images of IDream grades 3 and 4 groups were the highest. The comparison of the average subjective scores of the images of hepatic cysts among the six reconstruction grades showed statistically significant differences (H=192.17,P<0.05). Conclusion:In CT plain scan on the upper abdomen,with the increasing of IDream reconstruction grades,the image noises gradually decrease,and objective parameters of images gradually enhance,and the reconstructions of IDream grades 3 and 4 can obtain the optimal image quality of upper abdomen at the objective score of hepatic cysts.

Artificial intelligence(AI)has emerged as a cutting-edge technology leading the future and is a key engine for China's development.In the innovation and research of medical devices,AI has provided critical support in the areas of intelligent diagnostic assistance,intelligent therapeutic assis-tance,intelligent monitoring,life support,et al.Ma-chine learning-enabled device software functions(ML-DSFs)have become an essential component of many medical devices.Recently,the United States Food and Drug Administration(FDA)released a draft guidance titled"Marketing Submission Rec-ommendations for a Predetermined Change Con-trol Plan for Artificial Intelligence/Machine Learn-ing(AI/ML)-Enabled Device Software Functions(Draft)."that aimed to provide a forward-looking approach to foster the development of ML medical devices.By supporting iterative updates through modifications,this approach ensures the continu-ous safety and effectiveness of the devices.This guidance represents the latest in regulatory direc-tion and is especially beneficial for enhancing the quality and efficiency of clinical trials for AI prod-ucts.Therefore,we plan to provide a detailed intro-duction and interpretation of the guidance,with the aim of learning from international advanced regulatory concepts and experiences to promote the development of ML-DSFs with more profound international influence.

Objective:To investigate the optimal reconstruction grade of IDream reconstruction technique in reducing image noise,optimizing image quality,and displaying liver cysts through the subjective assessment on the display of computed tomography (CT) image with differently reconstructive grades in IDream reconstruction technique of iterative reconstruction algorithm,and the objective evaluation of image quality of upper abdomen. Methods:The imaging data of CT plain scan of 53 patients with hepatic cysts who underwent plain scans on upper abdomen at Peking Union Medical College Hospital from August to September 2021 were retrospectively collected. All images were reconstructed to standard window images by using 6 kinds of methods that included filtered back projection (FBP) and IDream grades 1 to 5,which resulted in 6 groups of images that included FBP group and IDream grades 1-5. The CT values and standard deviation (SD) values of the liver,abdominal aorta,erector spine muscle,fat and spleen in images of each group were measured and recorded,respectively. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the images were calculated. Two CT diagnostic physicians with more than 8 years of experience conducted subjective scoring for the display in the images of hepatic cysts of each group. The objective parameters and the subjective scores of hepatic cysts of reconstructive images with different grades were compared. A one-way analysis of variance was adopted to analyze the objective parameters,and Kruskal-Wallis H test was conducted on the subjective score of the display of hepatic cysts. Results:There were no statistically significant differences in the CT values among different reconstruction grades on the liver,abdominal aorta,fat,erector spine muscle and spleen (P>0.05). In the FBP group and IDream grades 1 to 5 groups,the SD values of images gradually decreased with the increasing of the reconstruction grades,which were respectively (18.11±5.03),(15.37±4.97),(13.26±4.83),(11.68±4.56),(10.99±4.36) and (10.60±4.21) Hu. The SNR and CNR of the liver gradually increased. The differences in SD values,SNR,and CNR among the six groups of images were all statistically significant (F=20.75,17.72,3.15,P<0.05),respectively. The subjective scores for the display of hepatic cysts from the FBP group to IDream grades 1 to 4 were respectively (3.12±0.35),(3.63±0.46),(4.02±0.42),(4.61±0.48) and (4.63±0.48),which were gradually increasing,while the score for the IDream grade 5 group slightly decreased to (4.53±0.47). The subjective scores for hepatic cysts in the images of IDream grades 3 and 4 groups were the highest. The comparison of the average subjective scores of the images of hepatic cysts among the six reconstruction grades showed statistically significant differences (H=192.17,P<0.05). Conclusion:In CT plain scan on the upper abdomen,with the increasing of IDream reconstruction grades,the image noises gradually decrease,and objective parameters of images gradually enhance,and the reconstructions of IDream grades 3 and 4 can obtain the optimal image quality of upper abdomen at the objective score of hepatic cysts.

Objective:To explore the impacts of carnosic acid(CA)on learning and cognitive function in epileptic rats and the mechanism of regulating PKA-CREB signaling pathway in this process.Methods:Epilepsy rat models were prepared by intraperi-toneal injection of 50 mg/kg PTZ.After successful modeling,the rats were randomly grouped into control group,model group,CA low-dose group,CA high-dose group,CA high+PKA inhibitor group(CA high+H-89 group),with 15 rats in each group.The epileptic be-havior of rats in each group was evaluated;Morris water maze experiment was applied to test the cognitive ability of rats;HE staining and Nissl staining were applied to detect the morphology of hippocampal tissue and neurons of rats in each group;ELISA was applied to detect the contents of IL-1β,TNF-α,MDA,and the SOD activity in the hippocampus of rats in each group;and Western blot was applied to detect the protein expressions of PKA,p-PKA,CREB,p-CREB and BDNF in the hippocampus of rats in each group.Results:Compared with control group,the hippocampal neurons of rats in model group were irregularly arranged,with pyknosis of the nuclei,and the number of neurons decreased,the epilepsy frequency,Racine grading,escape latency,time of first platform crossing,and levels of IL-1β,TNF-α and MDA all increased,the frequency of crossing the platform,SOD activity,p-PKA/PKA,p-CREB/CREB,and the expression of BDNF protein all reduced(P<0.05);compared with model group,the arrangement of neuronal cells in hippocampal tissue of rats in CA group gradually became orderly,nuclear pyknosis gradually decreased,and the number of neurons increased,the epilepsy frequency,Racine grading,escape latency,time of first platform crossing,and levels of IL-1β,TNF-α and MDA all reduced,the frequency of crossing the platform,SOD activity,p-PKA/PKA,p-CREB/CREB,and the expression of BDNF protein all increased(P<0.05);further injection of PKA inhibitors on the basis of high-dose CA treatment showed that the improvement effects of high-dose CA on cognitive dysfunction,neuronal damage,inflammation,and oxidative stress in epileptic rats were reversed(P<0.05).Conclusion:CA can improve the learning and cognitive function of epileptic rats by activating the PKA-CREB signaling pathway.

Glycoengineering was carried out in the mammalian cell line CHO for the production of pro-tein-based drugs.Firstly,the genome sequence of the Rosa26 locus of CHO cells was determined,the gRNA sequences were designed,and the landing pad was integrated into the Rosa26 locus of CHO cells by CRISPR/Cas9 technology.Three targeting vectors co-expressed by glycosyltransferases,which are β-1,4 galactosyltransferase(B4GALT1),α-2,6-sialyltransferase 1(ST6GAL1)and N-acetaminoglycosyl-transferase Ⅲ(GnT Ⅲ),were constructed by overlapping PCR and seamless ligation technology,and the three glycosyltransferase genes were integrated into the CHO Rosa26 locus by Cre enzyme-mediated cassette exchange technology.PCR confirmed that three glycosyltransferases had been successfully site-directed integrated into the Rosa26 site.The mRNA expression levels of the three glycosyltransferases were more than 50 000-fold by qRT-PCR,and the protein expression levels of the three glycosyltrans-ferases were more than 4-fold via western blotting(P＜0.001).A CHO-engineered cell line with three glycosyltransferases integrated into Rosa26 site was successfully constructed.