ArticleMicroorganisms2021
Consequences of Both Coxsackievirus B4 and Type 1 Diabetes on Female Non-Obese Diabetic Mouse Kidneys.
Article in Microorganisms, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Coxsackievirus Infection and Associated Diseases.Microorganisms · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Despite the 2019 Executive Order on Advancing American Kidney Health Initiative, kidney disease has moved up in rank from the 9th to the 8th leading cause of death in the United States. A recent push in the field of nephrology has been to identify molecular markers and/or molecular profiles involved in kidney disease process or injury that can help identify the cause of injury and predict patient outcomes. While these studies have had moderate success, they have not yet considered that many of the health conditions that cause kidney disease (diabetes, hypertension, etc.) can also be caused by environmental factors (such as viruses), which in and of themselves can cause kidney disease. Thus, the goal of this study was to identify molecular and phenotypic profiles that can differentiate kidney injury caused by diabetes (a health condition resulting in kidney disease) and coxsackievirus B4 (CVB4) exposure (which can cause diabetes and/or kidney disease), both alone and together. Non-obese diabetic (NOD) mice were used for this study due to their susceptibility to both type 1 diabetes (T1D)- and CVB4-mediated kidney injury, in order to glean a better understanding of how hyperglycemia and viral exposure, when occurring on their own and in combination, may alter the kidneys' molecular and phenotypic profiles. While no changes in kidney function were observed, molecular biomarkers of kidney injury were significantly up- and downregulated based on T1D and CVB4 exposure, both alone and together, but not in a predictable pattern. By combining individual biomarkers with function and phenotypic measurements (i.e., urinary albumin creatinine ratio, serum creatinine, kidney weight, and body weight), we were able to perform an unbiased separation of injury group based on the type of injury. This study provides evidence that unique kidney injury profiles within a kidney disease health condition are identifiable, and will help us to identify the causes of kidney injury in the future.
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