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1.
Nat Commun ; 15(1): 1584, 2024 Feb 21.
Artigo em Inglês | MEDLINE | ID: mdl-38383565

RESUMO

Astrocytes, a type of glial cell in the central nervous system (CNS), adopt diverse states in response to injury that are influenced by their location relative to the insult. Here, we describe a platform for spatially resolved, single-cell transcriptomics and proteomics, called tDISCO (tissue-digital microfluidic isolation of single cells for -Omics). We use tDISCO alongside two high-throughput platforms for spatial (Visium) and single-cell transcriptomics (10X Chromium) to examine the heterogeneity of the astrocyte response to a cortical ischemic stroke in male mice. We show that integration of Visium and 10X Chromium datasets infers two astrocyte populations, proximal or distal to the injury site, while tDISCO determines the spatial boundaries and molecular profiles that define these populations. We find that proximal astrocytes show differences in lipid shuttling, with enriched expression of Apoe and Fabp5. Our datasets provide a resource for understanding the roles of astrocytes in stroke and showcase the utility of tDISCO for hypothesis-driven, spatially resolved single-cell experiments.


Assuntos
Astrócitos , Acidente Vascular Cerebral , Camundongos , Animais , Masculino , Astrócitos/metabolismo , Sistema Nervoso Central/metabolismo , Acidente Vascular Cerebral/genética , Acidente Vascular Cerebral/metabolismo , Perfilação da Expressão Gênica , Cromo/metabolismo
2.
Stud Health Technol Inform ; 312: 3-8, 2024 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-38372303

RESUMO

The current corpus of evidence-based information for chronic disease prevention and treatment is vast and growing rapidly. Behavior change theories are increasingly more powerful but difficult to operationalize in the current healthcare system. Millions of Canadians are unable to access personalized preventive and behavior change care because our in-person model of care is running at full capacity and is not set up for mass education and behavior change programs. We propose a framework to utilize data from electronic medical records to identify patients at risk of developing chronic disease and reach out to them using digital health tools that are overseen by the primary care team. The framework leverages emerging technologies such as artificial intelligence, digital health tools, and patient-generated data to deliver evidence-based knowledge and behavior change to patients across Canada at scale. The framework is flexible to enable new technologies to be added without overwhelming providers, patients or implementers.


Assuntos
Inteligência Artificial , Atenção à Saúde , População Norte-Americana , Humanos , Canadá , Doença Crônica
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