There is increasing interest in health care organizations functioning as learning health systems (LHSs) to improve the quality and efficiency of health care delivery while generating new knowledge. Individuals must be trained in associated concepts and competencies and subsequently positioned (or embedded) within the delivery system for maximum effect as they perform their scholarship. Potential researchers within LHSs come from many different training backgrounds; therefore, each LHS scholar requires a goal-directed plan tailored to his or her needs. There are few tools available to guide development, training, or evaluation of individuals interested in becoming leaders of research in LHSs. In this paper, we present a newly developed tool for guiding the training of such researchers, the Learning Health Systems Competency Appraisal Inventory (LHS-CAI). The LHS-CAI is modeled after the Clinical Research Appraisal Index (CRAI) used within Clinical and Translational Science Award sites across the United States. The LHS-CAI is a tool for trainees at all levels to use with their mentors in an interactive manner. The tool can then identify areas in which more training is needed and at what level to ensure success as a researcher within LHSs. We further modified the CRAI format to better leverage the LHS-CAI as a key part of an LHS scholar's individual development plan. To implement the LHS-CAI, we have identified key points within the Minnesota Learning Health System Mentored Career Development Program (MN-LHS) at which assessment of expertise for each competency would be useful to LHS scholars, mentors, and program leaders. Scholars in this program come from various clinical and academic backgrounds but are all targeting their career trajectories toward leading embedded LHS research. They will reevaluate their expertise upon completion of the program, with comparison to baseline serving as a key program evaluation tool. The LHS-CAI is currently being implemented with the first cohort of scholars in the MN-LHS program.
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http://dx.doi.org/10.1002/lrh2.10218 | DOI Listing |
HGG Adv
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Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (A) known/plausible links to BE/EAC pathogenesis (n=493) or (B) prior evidence of biological interactions (n=4,196).
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
School of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
β-secretase (BACE1) is instrumental in amyloid-β (Aβ) production, with overexpression noted in Alzheimer's disease (AD) neuropathology. The interaction of Aβ with the receptor for advanced glycation endproducts (RAGE) facilitates cerebral uptake of Aβ and exacerbates its neurotoxicity and neuroinflammation, further augmenting BACE1 expression. Given the limitations of previous BACE1 inhibition efforts, the study explores reducing BACE1 expression to mitigate AD pathology.
View Article and Find Full Text PDFCommun Psychol
January 2025
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
How do people model the world's dynamics to guide mental simulation and evaluate choices? One prominent approach, the Successor Representation (SR), takes advantage of temporal abstraction of future states: by aggregating trajectory predictions over multiple timesteps, the brain can avoid the costs of iterative, multi-step mental simulation. Human behavior broadly shows signatures of such temporal abstraction, but finer-grained characterization of individuals' strategies and their dynamic adjustment remains an open question. We developed a task to measure SR usage during dynamic, trial-by-trial learning.
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January 2025
Department of Computer Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand.
Active transportation, such as cycling, improves mobility and general health. However, statistics reveal that in low- and middle-income countries, male and female cycling participation rates differ significantly. Existing literature highlights that women's willingness to use bicycles is significantly influenced by their perception of security.
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January 2025
Electronics and Communication Engineering Dept. Faculty of Engineering, Horus University, New Damietta, Egypt.
Electric vehicles (EVs) rely heavily on lithium-ion battery packs as essential energy storage components. However, inconsistencies in cell characteristics and operating conditions can lead to imbalanced state of charge (SOC) levels, resulting in reduced capacity and accelerated degradation. This study presents an active cell balancing method optimized for both charging and discharging scenarios, aiming to equalize SOC across cells and improve overall pack performance.
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