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Front Med (Lausanne)
December 2024
Science and Research Centre, Faculty of Health Sciences, Palacký University Olomouc, Olomouc, Czechia.
Health is one of the Sustainable Development Goals. The importance of health promotion is growing in the context of an aging population and increasing life expectancy. Prevention is often underestimated and neglected by citizens.
View Article and Find Full Text PDFGenet Med Open
April 2024
UCSF Bioethics, University of California, San Francisco, CA.
Purpose: Sharing aggregate results with research participants is a widely agreed-upon ethical obligation; yet, there is little research on communicating study results to diverse populations enrolled in genomics research. This article describes the cocreation of a visual narrative to explain research findings to families enrolled in a clinical genomics research study.
Methods: The design process involved researchers, clinicians, study participants, a physician illustrator, and a health communications expert.
Sample multiplexing is an emerging method in single-cell RNA sequencing (scRNA-seq) that addresses high costs and batch effects. Current multiplexing schemes use DNA labels to barcode cell samples but are limited in their stability and extent of labeling across heterogeneous cell populations. Here, we introduce Nanocoding using lipid nanoparticles (LNPs) for high barcode labeling density in multiplexed scRNA-seq.
View Article and Find Full Text PDFAging results in a progressive decline in physiological function due to the deterioration of essential biological processes, such as transcription and RNA splicing, ultimately increasing mortality risk. Although proteomics is emerging as a powerful tool for elucidating the molecular mechanisms of aging, existing studies are constrained by limited proteome coverage and only observe a narrow range of lifespan. To overcome these limitations, we integrated the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of three brain tissues (cortex, hippocampus, striatum) and kidney in the C57BL/6JN mouse model, achieving quantification of 8,954 to 9,376 proteins per tissue (cumulatively 12,749 across all tissues).
View Article and Find Full Text PDFAs the number of Parkinson's patients is expected to increase with the growth of the aging population there is a growing need to identify new diagnostic markers that can be used cheaply and routinely to monitor the population, stratify patients towards treatment paths and provide new therapeutic leads. Genetic predisposition and familial forms account for only around 10% of PD cases [1] leaving a large fraction of the population with minimal effective markers for identifying high risk individuals. The establishment of population-wide omics and longitudinal health monitoring studies provides an opportunity to apply machine learning approaches on these unbiased cohorts to identify novel PD markers.
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