A Personalized, Transdiagnostic Smartphone App (Mello) Targeting Repetitive Negative Thinking for Depression and Anxiety: Qualitative Analysis of Young People's Experience.

Background: The increasing rates of mental health challenges among young people highlight an urgent need for accessible and effective treatment. However, current mental health systems face unprecedented demand, leaving most young people globally with unmet mental health needs. Smartphones present a promising solution to this issue by offering in-the-moment support through innovative just-in-time adaptive interventions, which provide support based on real-time data.

System transferability of Raman-based oesophageal tissue classification using modern machine learning to support multi-centre clinical diagnostics.

Background: The clinical potential of Raman spectroscopy is well established but has yet to become established in routine oncology workflows. One barrier slowing clinical adoption is a lack of evidence demonstrating that data taken on one spectrometer transfers across to data taken on another spectrometer to provide consistent diagnoses.

Methods: We investigated multi-centre transferability using human oesophageal tissue.

Characterization of Collaborative Cross mouse founder strain CAST/EiJ as a novel model for lethal COVID-19.

Mutations in SARS-CoV-2 variants of concern (VOCs) have expanded the viral host range beyond primates, and a few other mammals, to mice, affording the opportunity to exploit genetically diverse mouse panels to model the broad spectrum of responses to infection in patient populations. Here we surveyed responses to VOC infection in genetically diverse Collaborative Cross (CC) founder strains. Infection of wild-derived CC founder strains produced a broad range of viral burden, disease susceptibility and survival, whereas most other strains were resistant to disease despite measurable lung viral titers.