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: To study the clinical efficacy of Wenyang Lishui Formula (WYLSF) in preventing ovarian hyperstimulation syndrome (OHSS) and explore the suitable range of estradiol (E₂) on the human chorionic gonadotropin (HCG) day in patients with OHSS using WYLSF. METHODS: Part I: eligible patients at high risk for OHSS undergoing ovulation induction between January and December, 2023 were randomized into 2 groups based on the actual treatment. The treatment group received 200 mL WYLSF formula twice daily for 5 days after oocyte retrieval in a combination of lifestyle coaching (LC) intervention including regular diet and exercise, whereas the LC group received LC intervention alone. The incidence of OHSS, OHSS self-assessment scales, changes in E₂ levels on HCG day and 5 days after oocyte retrieval, ovarian morphology changes, and menstrual recovery were compared between the two groups. Part II: patients at high risk for OHSS treated with WYLSF were studied. The optimal E₂ threshold on the HCG day was determined using the maximum selection test, and a multivariate analysis was adopted to compare the relationship between different E₂ levels on HCG day and hospitalization rate, incidence of moderate to severe OHSS, and self-assessment scales, to explore the preventive effect of WYLSF on OHSS in patients with varying E₂ levels. RESULTS: A total of 120 patients were included in the Part I analysis. The treatment group (60 cases) showed a significant reduction in the incidence, duration, and severity of abdominal distension, as well as the incidence of vomiting compared with the LC group (P<0.05). The post-retrieval E₂ levels in the treatment group decreased significantly more (P=0.032). Among 1,652 patients treated with WYLSF in the Part II, 90 patients with ⩽ 10092 pmol/L, 159 with >31074 pmol/L, and 1,403 in the middle range group were formed based on E₂ levels on HCG day in Part two analysis. Univariate and regression analyses showed that patients with E₂ levels >31073 pmol/L had a significantly higher incidence of moderate to severe OHSS compared to those with E₂ levels ⩽ 10092 pmol/L (P<0.05). CONCLUSIONS WYLSF can effectively reduce specific symptoms in high-risk OHSS patients after ovulation induction and significantly lower E₂ levels. It may be more suitable for high-risk OHSS patients with E₂ levels <31073 pmol/L on HCG day. (Registration No. MR-11-23-032493, https://www.medicalresearch.org.cn/login ).
Humans ; Ovarian Hyperstimulation Syndrome/blood* ; Female ; Adult ; Prospective Studies ; Drugs, Chinese Herbal/pharmacology* ; Estradiol/blood* ; Ovulation Induction ; Chorionic Gonadotropin

The relationship between gut microbiota and depressive disorder has become a research focus in recent years. Within the microbiota-gut-brain axis, the gut microbiota influences the onset and progression of depressive disorder primarily through the tryptophan metabolic pathway. Tryptophan, an essential amino acid in humans, is subject to dual regulation by intestinal microorganisms, which modulate its metabolic balance via inflammatory stimulation and microbial metabolite production. In depression, excessive activation of the kynurenine branch of tryptophan metabolism leads to the accumulation of proinflammatory and neurotoxic metabolites, thereby exacerbating neuroinflammation in the brain. Intervention studies indicate that the antidepressant-like effects of probiotics and traditional Chinese medicine are associated with remodeling of the gut microbiota, restoration of tryptophan metabolic balance, and alleviation of neuroinflammation. Furthermore, targeted inhibition of kynurenine 3-monooxygenase can mitigate neuroinflammation by regulating microglial activity, thus improving depressive-like behaviors. In summary, the metabolite-inflammation axis represents a central node in the interaction regulation between tryptophan metabolism and the microbiota-gut-brain axis. This provides a theoretical foundation for developing novel therapeutic strategies targeting depression through modulation of gut microbiota-mediated tryptophan metabolism.
Tryptophan/metabolism* ; Gastrointestinal Microbiome/physiology* ; Humans ; Depressive Disorder/microbiology* ; Probiotics/therapeutic use* ; Brain/metabolism* ; Kynurenine/metabolism* ; Metabolic Networks and Pathways ; Animals ; Medicine, Chinese Traditional

Lacking therapeutic targets highlights the crucial roles of chemotherapy and radiotherapy in the clinical management of triple-negative breast cancer (TNBC). To relieve the side effects of the chemoradiotherapy combination regimen, we design and develop a self-assembled micelle nanosystem consisting of perfluorocarbon chain-modified cisplatin prodrug. By incorporating perfluorodecalin, this nanosystem can effectively carry ozone and promote irradiation-derived reactive oxygen species (ROS) production. By leveraging the perfluorocarbon sidechain, the nanosystem exhibits efficient internalization by TNBC cells and effectively escapes from lysosomal entrapment. Under X-ray irradiation, ozone-generated ROS disrupts the intracellular redox balance, thereby facilitating the release of cisplatin in a reduction-responsive manner mediated by reduced glutathione. Moreover, oxygen derived from ozone decomposition enhances the efficacy of radiotherapy by alleviating tumor hypoxia. Notably, the combination of irradiation with ozone-loaded cisplatin prodrug nano system synergistically prompts antitumor efficacy and reduces cellular/systemic toxicity in vitro and in vivo. Furthermore, the combo regimen remodels the tumor microenvironment into an immune-favored state by triggering immunogenic cell death and relieving hypoxia, which provides a promising foundation for a combination regimen of immunotherapy. In conclusion, our nanosystem presents a novel strategy for integrating chemotherapy and radiotherapy to optimize the efficacy and safety of TNBC clinical treatment.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional