Publications by authors named "M A Gainey"
Bacteriophage Evcara is a podovirus isolated on NRRL B-24275. Its genome is 16,285 bp in length and contains 22 predicted protein-coding genes. Evcara, has been assigned to cluster GI with phages PineapplePizza and Curie that share 10 homologues with the well-characterized phage phi29.
View Article and Find Full Text PDFThe professional identity of scientists has historically been cultivated to value research over teaching, which can undermine initiatives that aim to reform science education. Course-Based Research Experiences (CRE) and the inclusive Research and Education Communities (iREC) are two successful and impactful reform efforts that integrate research and teaching. The aim of this study is to explicate the professional identity of instructors who implement a CRE within an established iREC and to explore how this identity contributes to the success of these programs.
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- Over two decades, initiatives have aimed to enhance STEM undergraduate outcomes, with the inclusive Research Education Community (iREC) emerging as a scalable reform model that supports STEM faculty in implementing course-based research to improve student learning.
- This study utilized pathway modeling to describe the HHMI Science Education Alliance (SEA) iREC, identifying how faculty engagement leads to sustainable adoption and improvement of new teaching strategies through feedback from over 100 participating faculty members.
- The findings indicate that iREC fosters a collaborative environment where STEM faculty can share expertise and data, thereby enhancing their teaching practices and contributing to the overall evolution of undergraduate science education.
Article Synopsis
- TG-43 dose calculations in HDR brachytherapy often overlook variations in tissue density and scattering effects, leading to inaccuracies.
- Model-based dose calculation algorithms (MBDCAs) were introduced to enhance precision in high-dose-rate (HDR) treatments, especially for extended scalp lesions.
- This study found that MBDCAs provided more accurate dose estimations compared to TG-43, with discrepancies reduced to 2%-6% versus the 10%-23% overestimations seen with TG-43 at greater distances from the implant.
Sepsis is the leading cause of child death globally with low- and middle-income countries (LMICs) bearing a disproportionate burden of pediatric sepsis deaths. Limited diagnostic and critical care capacity and health worker shortages contribute to delayed recognition of advanced sepsis (severe sepsis, septic shock, and/or multiple organ dysfunction) in LMICs. The aims of this study were to 1) assess the feasibility of a wearable device for physiologic monitoring of septic children in a LMIC setting and 2) develop machine learning models that utilize readily available wearable and clinical data to predict advanced sepsis in children.
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