Readiness planning: how to go beyond "buy-in" to achieve curricular success and front-line performance.

Simulation program staff and leadership often struggle to partner with front-line healthcare workers, their managers, and health system leaders. Simulation-based learning programs are too often seen as burdensome add-ons rather than essential mechanisms supporting clinical workforce readiness. Healthcare system leaders grappling with declining morale, economic pressure, and too few qualified staff often don't see how simulation can help them, and we simulation program leaders can't seem to bridge this gap.

Heteroaryl Glutarimides and Dihydrouracils as Cereblon Ligand Scaffolds for Molecular Glue Degrader Discovery.

Stabilization of cereblon (CRBN)/neosubstrate complexes with molecular glues followed by degradation of those neosubstrates is an emerging strategy in drug discovery with compelling potential to target certain proteins that were previously considered to be undruggable. In this context, the discovery of novel CRBN ligands is an important area of ongoing research that holds promise to expand the scope of proteins that can be targeted through this mode of action. Herein, we describe the synthesis and evaluation of CRBN ligands featuring heteroaryl glutarimide and dihydrouracil scaffolds.

Gastric Neuroendocrine Tumors and Pernicious Anemia: A Case Report and Literature Review.

Gastrointestinal neuroendocrine tumors (GI-NETs) are rare neoplasms, with the gastric (stomach) subtype (G-NETs) representing a significant clinical focus. Type 1 G-NETs are particularly noteworthy due to their relationship with autoimmune atrophic gastritis (AAG) and pernicious anemia (PA), conditions that impact vitamin B12 absorption. This report presents the case of a patient with a type 1 G-NET identified at the initial diagnosis of PA, demonstrating the connection between these conditions.

Artificial intelligence-based rapid brain volumetry substantially improves differential diagnosis in dementia.

Introduction: This study evaluates the clinical value of a deep learning-based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age- and sex-adjusted percentile comparisons.

Methods: Fifty-five patients-17 with Alzheimer's disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls-underwent cranial magnetic resonance imaging scans. Two board-certified neuroradiologists (BCNR), two board-certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance.