Depression is a major psychological disorder with a growing impact worldwide. Traditional methods for detecting the risk of depression, predominantly reliant on psychiatric evaluations and self-assessment questionnaires, are often criticized for their inefficiency and lack of objectivity. Advancements in deep learning have paved the way for innovations in depression risk detection methods that fuse multimodal data. This paper introduces a novel framework, the Audio, Video, and Text Fusion-Three Branch Network (AVTF-TBN), designed to amalgamate auditory, visual, and textual cues for a comprehensive analysis of depression risk. Our approach encompasses three dedicated branches—Audio Branch, Video Branch, and Text Branch—each responsible for extracting salient features from the corresponding modality. These features are subsequently fused through a multimodal fusion (MMF) module, yielding a robust feature vector that feeds into a predictive modeling layer. To further our research, we devised an emotion elicitation paradigm based on two distinct tasks—reading and interviewing—implemented to gather a rich, sensor-based depression risk detection dataset. The sensory equipment, such as cameras, captures subtle facial expressions and vocal characteristics essential for our analysis. The research thoroughly investigates the data generated by varying emotional stimuli and evaluates the contribution of different tasks to emotion evocation. During the experiment, the AVTF-TBN model has the best performance when the data from the two tasks are simultaneously used for detection, where the F1 Score is 0.78, Precision is 0.76, and Recall is 0.81. Our experimental results confirm the validity of the paradigm and demonstrate the efficacy of the AVTF-TBN model in detecting depression risk, showcasing the crucial role of sensor-based data in mental health detection.

The prognostic role of neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) in patients with prostate cancer (PCa) remains inconsistent. Here we quantify the prognostic impact of these biomarkers and assess their consistency in PCa. We systematically searched PubMed, Web of Science, and Embase for eligible studies embracing multivariate results. The Newcastle-Ottawa Scale were used to assess the study quality. Pooled hazard ratios (HRs), and 95% confidence intervals (CIs) were calculated. A total of 7228 patients from 18 studies were included in the meta-analysis. Overall, elevated pretreatment NLR was associated with poor overall survival (OS, HR 1.58, 95% CI 1.41-1.78, P < 0.001), progression-free survival (PFS, HR 1.95, 95% CI 1.53-2.49, P < 0.001) and biochemical recurrence-free survival (BRFS, HR 1.37, 95% CI 1.07-1.75, P = 0.011). And high pretreatment PLR was correlated with more inferior PFS (HR 1.62, 95% CI 1.20-2.19, P = 0.002), OS (HR 1.70, 95% CI 1.34-2.15, P < 0.001) and cancer-specific survival (CSS, HR 2.02, 95% CI 1.24-3.29, P = 0.005). Moreover, the subgroup analyses did not alter the direction of results for OS and PFS. Based on these findings, elevated NLR and PLR was associated with poor oncologic outcomes, and they can serve as prognostic factors in PCa patients.

Background: COVID-19 outbreak have a long-term negative impact on mental health. Meanwhile, it may also provide opportunities for positive outcomes (e.g., post-traumatic growth). Resilience and social support could serve as psychological resources to protect individuals against the detrimental effects of the COVID-19 crisis and enable people to develop positive changes during challenging times.Objective: By testing the roles of resilience and social support in the relationship between COVID-19 related stress and negative mental health outcomes (depression and anxiety), as well as the relationship between COVID-19 related stress and positive mental health outcomes (post-traumatic growth, PTG), this study aimed to investigate the psychological mechanisms involved in different mental health outcomes induced by COVID-19.Methods: An online survey was conducted 1 year after the peak of the COVID-19 outbreak (from April to August 2021) in China. The survey includes demographic questionnaires and six scales: the Impact of Event Scale-Revised for COVID-19 (IES-RC), the 10-item Connor-Davidson Resilience Scale (CD-RISC-10), the Perceived Social Support Scale (PSSS), the Center for Epidemiological Studies Depression Scale (CES-D), the Generalized Anxiety Disorder scale (GAD-7) and the Posttraumatic Growth Inventory (PTGI). The structural equation model (SEM) was used to evaluate the relations and mechanisms between COVID-19 related stress and resilience, social support in depression, anxiety, and PTG.Results: A total of 771 Chinese subjects completed the questionnaire, including 416 (54%) females. COVID-19 related stress was associated with anxiety (P < 0.001), PTG (P < 0.001), and depression (P < 0.001). Resilience was related to depression (P < 0.001), anxiety (P < 0.001), and PTG (P < 0.001). Social support was associated with depression (P < 0.001), anxiety (P < 0.001), and PTG (P < 0.001). Under SEM analysis, resilience mediated the effects of COVID-19 related stress on depression and post-traumatic growth. Social support mediated the impacts of COVID-19 related stress on post-traumatic growth, depression, and anxiety. The path coefficients of the mediation effects were statistically significant.Conclusions: The current findings suggest that COVID-19 related stress has a double-edged effect on mental health. Depression, anxiety, and PTG coexist in Chinese individuals 1 year after the peak of the pandemic. Resilience and social support serve as important protective factors of mental health, safeguard people from the negative mental health outcomes of the COVID-19, and promote PTG.

Targeted protein degradation (TPD) is an emerging therapeutic strategy with the potential to modulate disease-associated proteins that have previously been considered undruggable, by employing the host destruction machinery. The exploration and discovery of cellular degradation pathways, including but not limited to proteasomes and lysosome pathways as well as their degraders, is an area of active research. Since the concept of proteolysis-targeting chimeras (PROTACs) was introduced in 2001, the paradigm of TPD has been greatly expanded and moved from academia to industry for clinical translation, with small-molecule TPD being particularly represented. As an indispensable part of TPD, biological TPD (bioTPD) technologies including peptide-, fusion protein-, antibody-, nucleic acid-based bioTPD and others have also emerged and undergone significant advancement in recent years, demonstrating unique and promising activities beyond those of conventional small-molecule TPD. In this review, we provide an overview of recent advances in bioTPD technologies, summarize their compositional features and potential applications, and briefly discuss their drawbacks. Moreover, we present some strategies to improve the delivery efficacy of bioTPD, addressing their challenges in further clinical development.

Objectives: To investigate the prevalence of depression and anxiety symptoms among older adults in an urban district in China, as well as their associated factors. Design: Cross-sectional study. Setting: General communities in Shenzhen, Guangdong, China. Participants: A total of 5372 community-dwelling older adults aged 65 years or older were initially recruited. Ultimately, 5331 participants met the inclusion criteria and were included in this study. Methods: Participants completed a sociodemographic questionnaire, along with assessments including the Patient Health Questionnaire-9, Generalised Anxiety Scale-7, UCLA Loneliness Simplification Scale, Insomnia Severity Index Scale (ISI), Community Dementia Brief Screening Scale and the 8-item Dementia Screening Questionnaire. Statistical analyses included the Shapiro-Wilk test, independent t-test, Wilcoxon rank test, χ ² test and univariate and multivariate linear regression analysis. Results: The prevalence of depression and anxiety symptoms among older adults in Shenzhen communities was 10.4% and 11.3%, respectively. In multivariate analysis, age (B=−0.01, p<0.05), relatively poor health status in the past year (B=1.00, p<0.01), poor health status in the past year (B=2.40, p<0.01), ISI score (B=0.21, p<0.01), -item Ascertain Dementia Questionnaire (AD8) score (B=0.22, p<0.01), UCLA Loneliness Scale (ULS) score (B=0.24, p<0.01) were significantly associated with the severity of depression symptom, Compared with their respective reference categories, relatively poor health status in the past year (B=0.50, p<0.01), poor health status in the past year (B=1.32, p<0.01), ISI score (B=0.23, p<0.01), sleep duration (B=0.05, p<0.01), AD8 score (B=0.21, p<0.01), Community Screening Instrument for Dementia score (B=0.13, p<0.01), ULS score (B=0.22, p<0.01) were significantly associated with the severity of anxiety symptom. Conclusions: We observed a high prevalence of depression and anxiety symptoms among older adults in this study. The existing welfare system and infrastructure should remain and targeted mental health programmes addressing the identified risk factors should be proposed.