Artificial intelligence, recessionary pressures and population health.

Economic and labour policies have a considerable influence on health and well-being through direct financial impacts, and by shaping social and physical environments. Strong economies are important for public health investment and employment, yet the rapid rise of generative artificial intelligence (AI) has the potential to reshape economies, presenting challenges beyond mere temporary market disruption. Generative AI can perform non-routine cognitive tasks, previously unattainable though traditional automation, creating new efficiencies.

Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework.

Introduction: Genomic medicine has features that make it preference sensitive and amenable to model-based health economic evaluation. Preferences of patients, caregivers, and clinicians related to the uptake and delivery of genomic medicine technologies and services that are not captured in health state utility weights can affect the intervention's cost-effectiveness and budget impact. However, there is currently no established or agreed-on approach for integrating preference information into economic evaluations.

2024 Scholars' Research Symposium Abstract: Retrospective Cohort Study of Pediatric COVID-19 in a Rural Integrated Health System.

Introduction: The spread of the SARS-CoV-2 virus, which caused Coronavirus Disease 2019 (COVID-19), led to a global pandemic and public health crisis, which affected the physical health and mental well-being of Americans in every part of the country. Although the effect of the pandemic was ubiquitous, it has been more extensively studied in urban areas, which leads to an underscoring of the burden of COVID-19 in rural US. Health disparities adversely affect children in rural communities, each of which is unique and requires interventions based on regional needs.

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina.

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells.