Can an app designed to reduce repetitive negative thinking decrease depression and anxiety in young people? Results from a randomized controlled prevention trial.

Background And Objectives: Rates of mental health disorders are rising among adolescents and young adults. Therefore, scalable methods for preventing psychopathology in these age groups are needed. As repetitive negative thinking (RNT) is a risk factor for depression and anxiety disorders, targeting RNT via smartphone app promises to be an effective, scalable strategy.

DARPin-induced reactivation of p53 in HPV-positive cells.

Infection of cells with high-risk strains of the human papillomavirus (HPV) causes cancer in various types of epithelial tissue. HPV infections are responsible for ~4.5% of all cancers worldwide.

Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations.

The mutational landscape of TP53, a tumor suppressor mutated in about half of all cancers, includes over 2,000 known missense mutations. To fully leverage TP53 mutation status for personalized medicine, a thorough understanding of the functional diversity of these mutations is essential. We conducted a deep mutational scan using saturation genome editing with CRISPR-mediated homology-directed repair to engineer 9,225 TP53 variants in cancer cells.

Automatic classification of fungal-fungal interactions using deep leaning models.

Fungi provide valuable solutions for diverse biotechnological applications, such as enzymes in the food industry, bioactive metabolites for healthcare, and biocontrol organisms in agriculture. Current workflows for identifying new biocontrol fungi often rely on subjective visual observations of strains' performance in microbe-microbe interaction studies, making the process time-consuming and difficult to reproduce. To overcome these challenges, we developed an AI-automated image classification approach using machine learning algorithm based on deep neural network.