The effects of xylazine on locomotion and motor behaviour in a planarian model.

In recent years, the recreational use of xylazine has increased dramatically in the USA. Although xylazine has been used as an anesthetic in veterinary medicine for decades, little is known about its behavioral effects. We took advantage of the planarian's innate negative phototaxis, the reliable movement from the light side to the dark side of a Petri dish, to explore the organism's suitability as an animal model for investigating the preclinical pharmacology of xylazine.

Day-case gastrostomy insertion in children: an achievable reality.

Purpose: Recent efforts have sought to streamline gastrostomy insertion care, particularly length of stay (LOS). We report our initial experience with day-case gastrostomy (DCG) insertion.

Method: Retrospective review (April 2018-2024) of all primary gastrostomy insertions.

Gender-Equity Model for Liver Allocation using Artificial Intelligence (GEMA-AI) for waiting list liver transplant prioritization.

Background & Aims: We aimed to develop and validate an artificial intelligence score (GEMA-AI) to predict liver transplant (LT) waiting list outcomes using the same input variables contained in existing models.

Methods: Cohort study including adult LT candidates enlisted in the United Kingdom (2010-2020) for model training and internal validation, and in Australia (1998-2020) for external validation. GEMA-AI combined international normalized ratio, bilirubin, sodium, and the Royal Free Glomerular Filtration Rate in an explainable Artificial Neural Network.

Long-term follow-up of the impact of brief sleep and lifestyle interventions in infancy on BMI z-score at 11 years of age: The POI randomized controlled trial.

Objective: To determine whether BMI differences observed at 5 years of age, from early intervention in infancy, remained apparent at 11 years.

Methods: Participants (n = 734) from the original randomized controlled trial (n = 802) underwent measures of body mass index (BMI), body composition (DXA), sleep and physical activity (24-h accelerometry, questionnaire), diet (repeated 24-h recalls), screen time (daily diaries), wellbeing (CHU-9D, WHO-5), and family functioning (McMaster FAD) around their 11th birthday. Following multiple imputation, regression models explored the effects of two interventions ('Sleep' vs.

Using natural language processing to identify emergency department patients with incidental lung nodules requiring follow-up.

Objectives: For emergency department (ED) patients, lung cancer may be detected early through incidental lung nodules (ILNs) discovered on chest CTs. However, there are significant errors in the communication and follow-up of incidental findings on ED imaging, particularly due to unstructured radiology reports. Natural language processing (NLP) can aid in identifying ILNs requiring follow-up, potentially reducing errors from missed follow-up.