Ready, Set, Move! Tracking Children's Modified Ride-On Car Use With a Custom Data Logger.

PURPOSE: To create and implement a next-generation, custom data logger to automatically track modified ride-on car (MROC) use in home and community settings, establish feasibility of long-term remote collection of community MROC use data, describe trends of MROC use, and explore parent perception of the MROC. METHODS: In this descriptive study, a custom data logger was constructed and integrated into MROCs using an Arduino Pro-Mini microprocessor to capture real-time use data remotely. RESULTS: It is feasible to automatically track MROC use in home and community settings. On average, MROC use trends appear consistent with caregiver reports and show higher initial use with steadily decreasing frequency over time, and varying bout duration and play session length, despite favorable caregiver perceptions of the cars. CONCLUSIONS: Remote tracking of MROC use may decrease burden on busy families and provide clinicians with valuable technology use data.

An Introduction to Generative Artificial Intelligence in Mental Health Care: Considerations and Guidance.

PURPOSE OF REVIEW: This paper provides an overview of generative artificial intelligence (AI) and the possible implications in the delivery of mental health care. RECENT FINDINGS: Generative AI is a powerful technology that is changing rapidly. As psychiatrists, it is important for us to understand generative AI technology and how it may impact our patients and our practice of medicine. This paper aims to build this understanding by focusing on GPT-4 and its potential impact on mental health care delivery. We first introduce key concepts and terminology describing how the technology works and various novel uses of it. We then dive into key considerations for GPT-4 and other large language models (LLMs) and wrap up with suggested future directions and initial guidance to the field.

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia.

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia.

Mutations in SF3B1, which encodes a spliceosome component, are associated with poor outcome in chronic lymphocytic leukemia (CLL), but how these contribute to CLL progression remains poorly understood. We undertook a transcriptomic characterization of primary human CLL cells to identify transcripts and pathways affected by SF3B1 mutation. Splicing alterations, identified in the analysis of bulk cells, were confirmed in single SF3B1-mutated CLL cells and also found in cell lines ectopically expressing mutant SF3B1. SF3B1 mutation was found to dysregulate multiple cellular functions including DNA damage response, telomere maintenance, and Notch signaling (mediated through KLF8 upregulation, increased TERC and TERT expression, or altered splicing of DVL2 transcript, respectively). SF3B1 mutation leads to diverse changes in CLL-related pathways.