Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

OBJECTIVE To enhance the training quality of anticoagulation specialty clinical pharmacists， address the resource limitations of a single training base， and promote homogenization of training quality. METHODS A multi-base joint training system for anticoagulation specialty clinical pharmacists in the Beijing area was established. A mixed research method was employed， collecting data through performance comparisons， questionnaires， and qualitative interviews to compare the differences between the joint training model （experimental group， n＝16） and traditional teaching model （the control group， n＝17）. RESULTS The established joint training system encompassed a unified joint training teaching plan， the formation of a joint training teaching team， the establishment of joint theoretical teaching courses， the implementation of joint case discussions and literature presentations， as well as strengthening the assessment throughout the joint training process. Compared to the control group [theoretical assessment of （76.44±3.66） points， case assessment of （84.31±3.27） points]， the experimental group students achieved higher scores in theoretical assessment （[ 79.85±4.64） points] and case assessment （[ 88.70±5.51） points] （P＜0.05）. Through questionnaires and qualitative interviews， the trainees in experimental group were highly satisfied with the joint training model in terms of theoretical learning， communication skills， and teaching interaction. CONCLUSIONS The multi-base collaborative training system for anticoagulation specialty clinical pharmacists can integrate advantageous resources and significantly enhance the training effectiveness of anticoagulation specialty clinical pharmacists， offering value for wider promotion.

Humans ; Urinary Bladder Neoplasms/pathology* ; Carcinoma, Transitional Cell/pathology* ; Genetic Markers ; Biomarkers, Tumor/genetics* ; Urothelium/pathology*

Objective To investigate the differences and the immunocompatibility of wild-type (WT), four-gene modified (TKO/hCD55) and six-gene modified (TKO/hCD55/hCD46/hTBM) pig erythrocytes with human serum. Methods The blood samples were collected from 20 volunteers with different blood groups. WT, TKO/hCD55, TKO/hCD55/hCD46/hTBM pig erythrocytes, ABO-compatible (ABO-C) and ABO-incompatible (ABO-I) human erythrocytes were exposed to human serum of different blood groups, respectively. The blood agglutination and antigen-antibody binding levels (IgG, IgM) and complement-dependent cytotoxicity were detected. The immunocompatibility of two types of genetically modified pig erythrocytes with human serum was evaluated. Results No significant blood agglutination was observed in the ABO-C group. The blood agglutination levels in the WT and ABO-I groups were higher than those in the TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups (all P<0.001). The level of erythrocyte lysis in the WT group was higher than those in the ABO-C, TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups. The level of erythrocyte lysis in the ABO-I group was higher than those in the TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups (both P<0.01). The pig erythrocyte binding level with IgM and IgG in the TKO/hCD55 group was lower than those in the WT and ABO-I groups. The pig erythrocyte binding level with IgG and IgM in the TKO/hCD55/hCD46/hTBM group was lower than that in the WT group and pig erythrocyte binding level with IgG was lower than that in the ABO-I group (all P<0.05). Conclusions The immunocompatibility of genetically modified pig erythrocytes is better than that of wild-type pigs and close to that of ABO-C pigs. Humanized pig erythrocytes may be considered as a blood source when blood sources are extremely scarce.

Objective To explore the context and hotspot changes of forensic mixed stain research through bibliometric approach.Methods The literature of forensic mixed stain included in the core col-lection of Web of Science database from 2011 to 2022 were collected as the study object,and the an-nual publication number,countrie(region),institution,journal,keywords,etc.were bibliometrically and visually analyzed using the R-based Bibliometrix 1.1.6 package and VOSviewer 1.6.18 software.Re-sults A total of 732 articles on forensic mixed stain were included from 2011 to 2022,with the an-nual number of articles published and the annual citation frequency showing a steady increase year by year.Among the 59 countries(regions)with the most published articles,the United States ranked first with 246 articles,followed by China with 153 articles.The literature came from 104 journals,and the total number of articles published in the top 10 journals was 633.FORENSIC SCI INT GENET ranked first with 307 articles.Visual analysis using VOSviewer software showed that keywords could be divided into four research clusters,namely the genetic marker development group(blue),the mixed stain typing analysis theory group(red),the sequencing analysis group(yellow),and the case sample research group(green).It can be divided into four development stages in terms of different time peri-ods:early development(2011-2013),middle development(2014-2016),rapid development(2017-2020)and latest development(2021-2022).Conclusion The number of publications by domestic and foreign scholars in the study of mixed stain in forensic science is showing a relatively stable trend.Machine learning,next generation sequencing and other research have been the hottest topics that have attracted the most attention in recent years,which is expected to further develop the theory of mixed stain typing and sequencing analysis in forensic mixed stain research.