Patterns and implications of spatial covariation in herbivore functions on resilience of coral reefs.

Persistent shifts to undesired ecological states, such as shifts from coral to macroalgae, are becoming more common. This highlights the need to understand processes that can help restore affected ecosystems. Herbivory on coral reefs is widely recognized as a key interaction that can keep macroalgae from outcompeting coral.

Enhancing end-of-life care practices on the medicine units: perspectives from nurses and families.

Background: Death is a part of life. While most often a sombre event, opportunities exist to optimise the experience both for the dying patient and their loved ones. This is especially true in institutionalised settings, such as acute care hospitals where cure and recovery tend to be paramount.

Enrolment patterns in a randomized controlled trial of probiotics in critically ill patients: a retrospective analysis of the PROSPECT trial.

Background: Understanding site-related factors that influence enrolment within multicenter randomized controlled trials (RCT) may help reduce trial delays and cost over-runs and prevent early trial discontinuation. In this analysis of PROSPECT (Probiotics: Prevention of Severe Pneumonia and Endotracheal Colonization Trial), we describe patient enrolment patterns and examine factors influencing site-based monthly enrolment.

Design: Retrospective analysis of a multicenter RCT.

Longitudinal analysis highlights structural changes in grey- and white-matter within military personnel exposed to blast.

Objective: The purpose of this study was to determine whether gray matter volume and diffusion-based metrics in associated white matter changed in breachers who had neuroimaging performed at two timepoints. A secondary purpose was to compare these changes in a group who had a one-year interval between their imaging timepoints to a group that had a two-year interval between imaging.

Methods: Between timepoints, clusters with significantly different gray matter volume were used as seeds for reconstruction of associated structural networks using diffusion metrics.

Benchmarking the most popular XAI used for explaining clinical predictive models: Untrustworthy but could be useful.

Objective: This study aimed to assess the practicality and trustworthiness of explainable artificial intelligence (XAI) methods used for explaining clinical predictive models.

Methods: Two popular XAIs used for explaining clinical predictive models were evaluated based on their ability to generate domain-appropriate representations, impact clinical workflow, and consistency. Explanations were benchmarked against true clinical deterioration triggers recorded in the data system and agreement was quantified.