Purpose: Leptin interacts not only with leptin receptor (LEPR) but also engages with other receptors. While the pro-oncogenic effects of the adrenergic receptor β2 (ADRB2) are well-established, the role of leptin in activating ADRB2 in triple-negative breast cancer (TNBC) remains unclear. Materials and Methods: The pro-carcinogenic effects of LEPR were investigated using murine TNBC cell lines, 4T1 and EMT6, and a tumor-bearing mouse model. Expression levels of LEPR, NADPH oxidase 4 (NOX4), and ADRB2 in TNBC cells and tumor tissues were analyzed via western blot and quantitative real-time polymerase chain reaction. Changes in reactive oxygen species (ROS) levels were assessed using flow cytometry and MitoSox staining, while immunofluorescence double-staining confirmed the co-localization of LEPR and ADRB2. Results: LEPR activation promoted NOX4-derived ROS and mitochondrial ROS production, facilitating TNBC cell proliferation and migration, effects which were mitigated by the LEPR inhibitor Allo-aca. Co-expression of LEPR and ADRB2 was observed on cell membranes, and bioinformatics data revealed a positive correlation between the two receptors. Leptin activated both LEPR and ADRB2, enhancing intracellular ROS generation and promoting tumor progression, which was effectively countered by a specific ADRB2 inhibitor ICI118551. In vivo, leptin injection accelerated tumor growth and lung metastases without affecting appetite, while treatments with Allo-aca or ICI118551 mitigated these effects. Conclusion This study demonstrates that leptin stimulates the growth and metastasis of TNBC through the activation of both LEPR and ADRB2, resulting in increased ROS production. These findings highlight LEPR and ADRB2 as potential biomarkers and therapeutic targets in TNBC.

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.

Purpose: Leptin interacts not only with leptin receptor (LEPR) but also engages with other receptors. While the pro-oncogenic effects of the adrenergic receptor β2 (ADRB2) are well-established, the role of leptin in activating ADRB2 in triple-negative breast cancer (TNBC) remains unclear. Materials and Methods: The pro-carcinogenic effects of LEPR were investigated using murine TNBC cell lines, 4T1 and EMT6, and a tumor-bearing mouse model. Expression levels of LEPR, NADPH oxidase 4 (NOX4), and ADRB2 in TNBC cells and tumor tissues were analyzed via western blot and quantitative real-time polymerase chain reaction. Changes in reactive oxygen species (ROS) levels were assessed using flow cytometry and MitoSox staining, while immunofluorescence double-staining confirmed the co-localization of LEPR and ADRB2. Results: LEPR activation promoted NOX4-derived ROS and mitochondrial ROS production, facilitating TNBC cell proliferation and migration, effects which were mitigated by the LEPR inhibitor Allo-aca. Co-expression of LEPR and ADRB2 was observed on cell membranes, and bioinformatics data revealed a positive correlation between the two receptors. Leptin activated both LEPR and ADRB2, enhancing intracellular ROS generation and promoting tumor progression, which was effectively countered by a specific ADRB2 inhibitor ICI118551. In vivo, leptin injection accelerated tumor growth and lung metastases without affecting appetite, while treatments with Allo-aca or ICI118551 mitigated these effects. Conclusion This study demonstrates that leptin stimulates the growth and metastasis of TNBC through the activation of both LEPR and ADRB2, resulting in increased ROS production. These findings highlight LEPR and ADRB2 as potential biomarkers and therapeutic targets in TNBC.

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.

Purpose: Leptin interacts not only with leptin receptor (LEPR) but also engages with other receptors. While the pro-oncogenic effects of the adrenergic receptor β2 (ADRB2) are well-established, the role of leptin in activating ADRB2 in triple-negative breast cancer (TNBC) remains unclear. Materials and Methods: The pro-carcinogenic effects of LEPR were investigated using murine TNBC cell lines, 4T1 and EMT6, and a tumor-bearing mouse model. Expression levels of LEPR, NADPH oxidase 4 (NOX4), and ADRB2 in TNBC cells and tumor tissues were analyzed via western blot and quantitative real-time polymerase chain reaction. Changes in reactive oxygen species (ROS) levels were assessed using flow cytometry and MitoSox staining, while immunofluorescence double-staining confirmed the co-localization of LEPR and ADRB2. Results: LEPR activation promoted NOX4-derived ROS and mitochondrial ROS production, facilitating TNBC cell proliferation and migration, effects which were mitigated by the LEPR inhibitor Allo-aca. Co-expression of LEPR and ADRB2 was observed on cell membranes, and bioinformatics data revealed a positive correlation between the two receptors. Leptin activated both LEPR and ADRB2, enhancing intracellular ROS generation and promoting tumor progression, which was effectively countered by a specific ADRB2 inhibitor ICI118551. In vivo, leptin injection accelerated tumor growth and lung metastases without affecting appetite, while treatments with Allo-aca or ICI118551 mitigated these effects. Conclusion This study demonstrates that leptin stimulates the growth and metastasis of TNBC through the activation of both LEPR and ADRB2, resulting in increased ROS production. These findings highlight LEPR and ADRB2 as potential biomarkers and therapeutic targets in TNBC.

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.