Little is known about the neural substrates underlying early memory functioning. To gain more insight, we examined how toddlers remember newly learned words. Hippocampal and anterior medial-temporal lobe (MTL) processes have been hypothesized to support forming and retaining the association between novel words and their referents, but direct evidence of this connection in early childhood is lacking. We assessed 2-year-olds (n = 38) for their memory of newly learned pseudowords associated with novel objects and puppets. We tested memory for these associations during the same session as learning and after a 1-week delay. We then played these pseudowords, previously known words, and completely novel pseudowords during natural nocturnal sleep, while collecting functional magnetic resonance imaging data. Activation in the left hippocampus and the left anterior MTL for newly learned compared to novel words was associated with same-session memory for these newly learned words only when they were learned as puppet names. Activation for known words was associated with memory for puppet names at the 1-week delay. Activation for newly learned words was also associated with overall productive vocabulary. These results underscore an early developing link between memory mechanisms and word learning in the medial temporal lobe.
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http://dx.doi.org/10.1016/j.cub.2021.09.058 | DOI Listing |
J Dent Educ
January 2025
Department of Conservative and Prosthetic Dentistry, Complutense University, Madrid, Spain.
Purpose: A properly designed rubric for oral presentations should be useful both to assess students' performance and to help them prepare for the task. However, its use and perceptions might be influenced by scholars' previous familiarization with rubrics during pre-university courses. The aim of this study was to evaluate how the previous experience of students in the use of rubrics can influence their assessment of oral presentations and to compare their ratings with those assigned by educators.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 5/6, Bonn D-53115, Germany.
Explaining the predictions of machine learning models is of critical importance for integrating predictive modeling in drug discovery projects. We have generated a test system for predicting isoform selectivity of phosphoinositide 3-kinase (PI3K) inhibitors and systematically analyzed correct predictions of selective inhibitors using a new methodology termed MolAnchor, which is based on the "anchors" concept from explainable artificial intelligence. The approach is designed to generate chemically intuitive explanations of compound predictions.
View Article and Find Full Text PDFLearn Health Syst
January 2025
Northwell New Hyde Park New York USA.
Introduction: Learning health networks (LHNs) improve clinical outcomes by applying core tenets of continuous quality improvements (QI) to reach community-defined outcomes, data-sharing, and empowered interdisciplinary teams including patients and caregivers. LHNs provide an ideal environment for the rapid adoption of evidence-based guidelines and translation of research and best practices at scale. When an LHN is established, it is critical to understand the needs of all stakeholders.
View Article and Find Full Text PDFNurse Educ
January 2025
Author Affiliations: Division of Simulation and Clinical Learning (Dr Sandiford), Division of Nursing Science (Dr Birnbaum), Center for Health Equity and Systems Research and Rutgers University School of Nursing, Newark, New Jersey.
Background: Resilience plays a role in workforce retention and has been linked to job satisfaction, quality of life, and organizational commitment in nursing faculty. Research on the nature of faculty resilience, however, remains sparse.
Purpose: The purpose of this study was to contribute to the understanding of nurse faculty resilience by describing examples of specific ways that a group of newly hired nursing faculty enacted resilience during their first few years on the job.
BMC Med Res Methodol
January 2025
Center for Medical Data Science, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Background: Platform trials are innovative clinical trials governed by a master protocol that allows for the evaluation of multiple investigational treatments that enter and leave the trial over time. Interest in platform trials has been steadily increasing over the last decade. Due to their highly adaptive nature, platform trials provide sufficient flexibility to customize important trial design aspects to the requirements of both the specific disease under investigation and the different stakeholders.
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