Microenhancement as a Biomarker for Cerebral Microbleed in Inflammatory Cerebral Amyloid Angiopathy: Insights From 3D T1 Black-Blood MR Imaging.

Objectives: Cerebral microbleeds (cMBs) are common imaging findings in conditions related to cerebral amyloid angiopathy (CAA). Blood-brain barrier (BBB) leakage is considered pivotal in their pathogenesis. This study investigates the potential role of cerebral microenhancement (cME) as an imaging biomarker on 3D T1 black-blood MRI (BB-MRI) for BBB rupture, predicting the formation of cMBs in inflammatory CAA variants.

Family-Reflections.com: Creating a parent-to-parent web-based tool regarding pediatric home ventilation.

Background: The decision to initiate pediatric mechanical ventilation via tracheostomy ("home ventilation") is complex and parents often desire information from other parents who have faced this decision. However, parent-to-parent communication is challenging as it is difficult to connect new families to experienced families in ways that optimize informed, balanced decision-making.

Objective: Create a parent-to-parent web-based tool to support decision-making about pediatric home ventilation.

"What Would Give Her the Best Life?": Understanding Why Families Decline Pediatric Home Ventilation.

Families who must decide about pediatric home ventilation rely on the clinicians who counsel them for guidance. Most studies about pediatric home ventilation decisions focus on families who opt for this intervention, leaving much unknown about the families who decline. To describe the rationales of families who decline home ventilation.

Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces.

Estimates of future climate change impacts using numerical impact models are commonly based on a limited selection of projections of climate and other key drivers. However, the availability of large ensembles of such projections offers an opportunity to estimate impact responses probabilistically. This study demonstrates an approach that combines model-based impact response surfaces (IRSs) with probabilistic projections of climate change and population to estimate the likelihood of exceeding pre-specified thresholds of impact.