Using large language models to estimate features of multi-word expressions: Concreteness, valence, arousal.

This study investigates the potential of large language models (LLMs) to provide accurate estimates of concreteness, valence, and arousal for multi-word expressions. Unlike previous artificial intelligence (AI) methods, LLMs can capture the nuanced meanings of multi-word expressions. We systematically evaluated GPT-4o's ability to predict concreteness, valence, and arousal.

Early region-specific impact of adjuvant radiation therapy on cognition and quality of life in adult patients with primary brain tumors.

Purpose: While treatments for primary brain tumors increase survival, they have cognitive sequelae. Neurocognition's anatomical distribution makes it susceptible to brain damage. This study aims to evaluate the contribution of radiotherapy on short-term cognitive impairment.

Three Years of the Coronavirus Disease 2019 Pandemic in a European Region: A Population-Based Longitudinal Assessment in Madrid Between 2020 and 2022.

Background: Our objective was to assess the health impact of coronavirus disease 2019 (COVID-19) during 2020-2022 in the Madrid region.

Methods: We included all individuals registered in the Madrid Health System Registry as of 31 December 2019, and followed them until 31 December 2022. Using a unique personal identifier, we linked the databases of primary care, hospitals, pharmacies, certified laboratories performing diagnostic tests, vaccines, and mortality.

Development of the aganglionic colon following surgical rescue in a cell therapy model of Hirschsprung disease in rat.

Patients with Hirschsprung disease lack enteric ganglia in the distal colon and propulsion of colorectal content is substantially impaired. Proposed stem cell therapies to replace neurons require surgical bypass of the aganglionic bowel during re-colonization, but there is inadequate knowledge of the consequences of bypass. We performed bypass surgery in Ednrb-/- Hirschsprung rat pups.