Introduction: The growing interest in knowledge translation and implementation science, both in clinical practice and in health professions education (HPE), is reflected in the number of studies that have sought to address what are believed to be evidence-practice gaps. Though this effort may be intended to ensure practice improvements are better aligned with research evidence, there is a common assumption that the problems researchers explore and the answers they generate are meaningful and applicable to practitioner needs.
Methods: This Mythology paper considers the nature of problems from HPE as the focus of HPE research and the ways in which they may or may not be aligned. The authors argue that, in an applied field such as HPE, it is vital that researchers better understand how their research problems relate to practitioner needs and what the limitations on evidence uptake might be. Not only can this establish clearer paths between evidence and action, but it also requires a rethink of much of knowledge translation and implementation science thinking and practice.
Results: The authors explore five myths: whether everything in HPE is a problem; whether practitioner needs involve problem solving; whether practitioner problems are resolvable with sufficient evidence; whether researchers effectively target practitioner problems; and whether studies that focus on solving practitioner problems make significant contributions to the literature.
Conclusions: To advance the conversation on the connections between problems and HPE research, the authors propose ways in which knowledge translation and implementation science might be approached differently.
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http://dx.doi.org/10.1111/medu.15067 | DOI Listing |
Sci Immunol
January 2025
Irving Institute for Cancer Dynamics, Columbia University, New York, NY 10027, USA.
Understanding how intratumoral immune populations coordinate antitumor responses after therapy can guide treatment prioritization. We systematically analyzed an established immunotherapy, donor lymphocyte infusion (DLI), by assessing 348,905 single-cell transcriptomes from 74 longitudinal bone marrow samples of 25 patients with relapsed leukemia; a subset was evaluated by both protein- and transcriptome-based spatial analysis. In acute myeloid leukemia (AML) DLI responders, we identified clonally expanded CD8 cytotoxic T lymphocytes with in vitro specificity for patient-matched AML.
View Article and Find Full Text PDFSci Adv
January 2025
Department of Biomedical Engineering, Northwestern University, Evanston, IL 60208, USA.
Understanding chromatin organization requires integrating measurements of genome connectivity and physical structure. It is well established that cohesin is essential for TAD and loop connectivity features in Hi-C, but the corresponding change in physical structure has not been studied using electron microscopy. Pairing chromatin scanning transmission electron tomography with multiomic analysis and single-molecule localization microscopy, we study the role of cohesin in regulating the conformationally defined chromatin nanoscopic packing domains.
View Article and Find Full Text PDFPLoS One
January 2025
Center for Innovation in Brain Science, University of Arizona Health Sciences, Tucson, Arizona, United States of America.
Translational validity of mouse models of Alzheimer's disease (AD) is variable. Because change in weight is a well-documented precursor of AD, we investigated whether diversity of human AD risk weight phenotypes was evident in a longitudinally characterized cohort of 1,196 female and male humanized APOE (hAPOE) mice, monitored up to 28 months of age which is equivalent to 81 human years. Autoregressive Hidden Markov Model (AHMM) incorporating age, sex, and APOE genotype was employed to identify emergent weight trajectories and phenotypes.
View Article and Find Full Text PDFTransl Vis Sci Technol
January 2025
Glaucoma Service, Wills Eye Hospital, Philadelphia, PA, USA.
Purpose: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant opportunities in the diagnosis and management of glaucoma. This article explores the application of various DL models in enhancing OCT capabilities and addresses the challenges associated with their clinical implementation.
Methods: A review of articles utilizing DL models was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), autoencoders, and large language models (LLMs).
FEBS J
January 2025
Department of Neurosurgical Engineering and Translational Neuroscience, Tohoku University Graduate School of Medicine, Sendai, Japan.
Alternative splicing (AS) plays an important role in neuronal development, function, and disease. Efforts to analyze the transcriptome of AS in neurons on a wide scale are currently limited. We characterized the transcriptome-wide AS changes in SH-SY5Y neuronal differentiation model, which is widely used to study neuronal function and disorders.
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