Faces of the Mind: Unveiling Mental Health States Through Facial Expressions in 11,427 Adolescents

Mood disorders, including depression and anxiety, often manifest through facial expressions. While previous research has explored the connection between facial features and emotions, machine learning algorithms for estimating mood disorder severity have been hindered by small datasets and limited real-world application. To address this gap, we analyzed facial videos of 11,427 participants, a dataset two orders of magnitude larger than previous studies. This comprehensive collection includes standardized facial expression videos from reading tasks, along with a detailed psychological scale that measures depression, anxiety, and stress. By examining the relationships among these emotional states and employing clustering analysis, we identified distinct subgroups embodying different emotional profiles. We then trained tree-based classifiers and deep learning models to estimate emotional states from facial features. Results indicate that models previously effective on small datasets experienced decreased performance when applied to our large dataset, highlighting the importance of data scale and mitigating overfitting in practical settings. Notably, our study identified subtle shifts in pupil dynamics and gaze orientation as potential markers of mood disorders, providing valuable information on the interaction between facial expressions and mental health. This research marks the first large-scale and comprehensive investigation of facial expressions in the context of mental health, laying the groundwork for future data-driven advancements in this field

CRNDE interference inhibits colorectal cancer cell proliferation, migration, and invasion, and promotes apoptosis

Abstract The aim of this study was to investigate the effect of colorectal neoplasia differentially expressed (CRNDE) interference on the proliferation, migration, invasion, and apoptosis of colorectal cancer (CRC) cells. Lovo, HCT-116, COLO 205, HT-29, SW480, and NCM460 cells were screened by quantitative reverse transcription polymerase chain reaction after transfection with CRNDE-interference vectors or miR-320a mimics. The levels of APPL1, Bax, Bcl-2, and cleaved caspase-3 were determined by western blotting. Cell proliferation was evaluated using Cell Counting Kit-8. Apoptosis was detected using flow cytometry and cell migration and invasion were assessed using a transwell assay. The relationships between CRNDE and miR-320a levels and between APPL1 and miR-320a levels were determined by luciferase reporter assay. The expression levels of CRNDE and APPL1 were significantly higher in HCT-116 cells than in Lovo, COLO 205, HT-29, SW480, or NCM460 cells (P &lt; 0.05). miR-320a overexpression and CRNDE interference significantly decreased cell proliferation, migration, and invasion (P &lt; 0.05), but significantly increased apoptosis (P &lt; 0.05). miR-320a overexpression or CRNDE interference significantly increased the number of cells in the G0-G1 phase, compared to the control treatment and empty vector transfection, while decreasing the number of cells in the G2-M phase. miR-320a overexpression and CRNDE interference significantly increased the expression levels of apoptosis-related proteins (P &lt; 0.05). miR-320a inhibited luciferase activity in HCT-116 cells transfected with the wild-type CRNDE 3′-UTR (P &lt; 0.05) or the APPL1 3′-UTR (P &lt; 0.05). Thus, CRNDE interference inhibited the proliferation, migration, and invasion of CRC cells and promoted apoptosis. The mechanism was related to the CRNDE/miR-320a/APPL1 axis.</jats:p

School-based Evaluation Advancing Response for Child Health (SEARCH): a mixed longitudinal cohort study from multifaceted perspectives in Jiangsu, China

Background Schools play a crucial role in providing mental health services to children and adolescents. However, the vastness of the student population and mental health workforce shortage in China severely limit the capacity for adequate care access and delivery.Objective We propose a large, mixed longitudinal cohort study, ‘School-based Evaluation Advancing Response for Child Health (SEARCH)’, aimed at addressing the increasing demand from individuals seeking access to mental healthcare services.Methods SEARCH uses a digital platform and school-based protocol for comprehensive assessment of the mental well-being of Chinese students in grades 4–12 incorporating individual, caregiver and teacher input, including capture of facial and acoustic features and response times, as well as mental well-being assessments.Findings We completed first wave data collection from nearly 20 000 participants (students, caregivers and teachers) at 11 schools, grades 4–12, in 3 cities in Jiangsu province in Southeast China from September 2022 to February 2023. We intend to conduct follow-up assessments for grades 4 through 12 at the 11 school sites every 6 months for 5 years.Conclusions SEARCH will provide important insight into the developmental trajectory of mental well-being in Chinese children and adolescents. The study protocol does not simply focus on student self-report and incorporates caregiver and teacher viewpoints as well. It also collects objective indicators that may facilitate development of screening tools.Clinical implications We believe future study findings will guide the development and implementation of school-based mental healthcare initiatives to improve the well-being of children and adolescents