Publications by authors named "E Meadows"

: Breast cancer (BC) is the second most commonly diagnosed cancer worldwide and is accompanied by fatigue during both active disease and remission in the majority of cases. Our lab has measured fatigue in isolated muscles from treatment-naive BC patient-derived orthotopic xenograft (BC-PDOX) mice. Here, we conducted a preclinical trial of pioglitazone in BC-PDOX mice to determine its efficacy in ameliorating BC-induced muscle fatigue, as well as its effects on transcriptomic, metabolomic, and lipidomic profiles in skeletal muscle.

View Article and Find Full Text PDF

Understanding the cellular mechanisms behind diabetes-related cardiomyopathy is crucial as it is a common and deadly complication of diabetes mellitus. Dysregulation of the mitochondrial genome has been linked to diabetic cardiomyopathy and can be ameliorated by altering microRNA (miRNA) availability in the mitochondrion. Long noncoding RNAs (lncRNAs) have been identified to downregulate miRNAs.

View Article and Find Full Text PDF

Traumatic brain injuries are extremely common, and although most patients recover from their injuries many TBI patients suffer prolonged symptoms and remain at a higher risk for developing cardiovascular disease and neurodegeneration. Moreover, it remains challenging to identify predictors of poor long-term outcomes. Here, we tested the hypothesis that preexisting cerebrovascular impairment exacerbates metabolic and vascular dysfunction and leads to worse outcomes after TBI.

View Article and Find Full Text PDF

Unlabelled: Breast cancer (BC) is the most prevalent cancer worldwide and is accompanied by fatigue during both active disease and remission in the majority of cases. Our lab has measured fatigue in isolated muscles from treatment-naive BC patient-derived orthotopic xenograft (BC-PDOX) mice. Here, we conducted a preclinical trial of pioglitazone in BC-PDOX mice to determine its efficacy in ameliorating BC-induced muscle fatigue, as well as its effects on transcriptomic, metabolomic, and lipidomic profiles in skeletal muscle.

View Article and Find Full Text PDF

Purpose: Treatment of non-muscle-invasive bladder cancer (NMIBC) is guided by risk stratification using clinical and pathologic criteria. This study aimed to develop a natural language processing (NLP) model for identifying patients with high-risk NMIBC retrospectively from unstructured electronic medical records (EMRs) and to apply the model to describe patient and tumor characteristics.

Methods: We used three independent EMR-derived data sets including adult patients with a bladder cancer diagnosis in 2011-2020 for NLP model development and training (n = 140), validation (n = 697), and application for the retrospective cohort analysis (n = 4,402).

View Article and Find Full Text PDF