Publications by authors named "Veda Devakumar"
Objectives: Spatially nonresolved transcriptomic data identified several functionally distinct populations of fibroblasts in health and disease. However, in-depth transcriptional profiling in situ at the single-cell resolution has not been possible so far. We thus aimed to profile these populations by single-cell spatial transcriptomics using cyclic in situ hybridisation (cISH).
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- * Researchers identified 13 distinct fibroblast subpopulations, noting an increase in five subpopulations linked to more severe skin fibrosis and a decrease in three associated with milder fibrosis.
- * The findings suggest that certain fibroblast subpopulations, such as S1PR and PI16;FAP-fibroblasts, could serve as potential targets for treatment and may help in assessing the severity of skin fibrosis in patients with SSc.
Article Synopsis
- Systemic sclerosis (SSc) is a disease affecting connective tissues, with microvascular changes being an early sign, but the mechanisms behind these changes are not well understood.
- The study utilized spatial proteomics to analyze skin biopsies from SSc patients and controls, identifying various subpopulations of vascular cells, including a unique group of endothelial cells linked to disease progression.
- Findings suggest that increased levels of a specific endothelial cell population (CD34;αSMA;CD31) correlate with fibrosis progression in SSc and are associated with immune cells and myofibroblasts, indicating a potential mechanism for the vascular complications in the disease.*
Elevated serum creatinine levels and risk of cognitive impairment in older adults with diabetes: a NHANES study from 2011-2014.
Front Endocrinol (Lausanne)
October 2023
Background: The brain and kidney have similar microvascular structure, which makes them susceptible to certain common pathophysiological processes. In this study, we examined several indicators of kidney injury/function associated with cognitive function in older diabetic patients in the hope of finding effective markers for detecting cognitive impairment (CI).
Methods: A total of 2209 older participants (aged ≥60 years) from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) were analyzed for the association between diabetes and CI using a multiple linear regression analysis model.