Publications by authors named "J F POWELL"

Background: Traumatic injuries have increased risks for infection and progression to difficult-to-heal wounds. Often, they are inadequately treated with single-purpose dressings. Involving wound care specialists allows for integrating various advanced wound treatments.

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Context: Surrogate decision-makers have expressed the need for better preparation around communication and medical decision-making.

Objectives: This mixed-methods feasibility study aimed to assess the feasibility and usability of an online program to prepare surrogates for their role.

Methods: We developed a 2-part program for surrogates called PREPARE For THEIR Care with a diverse group of Community Advisory Board members and caregivers recruited from the National Patient Advocacy Foundation.

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An abnormal expansion of a GGGGCC (GC) hexanucleotide repeat in the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), two debilitating neurodegenerative disorders driven in part by gain-of-function mechanisms involving transcribed forms of the repeat expansion. By utilizing a Cas13 variant with reduced collateral effects, we develop here a high-fidelity RNA-targeting CRISPR-based system for C9ORF72-linked ALS/FTD. When delivered to the brain of a transgenic rodent model, this Cas13-based platform curbed the expression of the GC repeat-containing RNA without affecting normal C9ORF72 levels, which in turn decreased the formation of RNA foci, reduced the production of a dipeptide repeat protein, and reversed transcriptional deficits.

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Mechanical force orchestrates a myriad of cellular events including inhibition of axon regeneration, by locally activating the mechanosensitive ion channel Piezo enriched at the injured axon tip. However, the cellular mechanics underlying Piezo localization and function remains poorly characterized. We show that the RNA repair/splicing enzyme Rtca acts upstream of Piezo to modulate its expression and transport/targeting to the plasma membrane via Rab10 GTPase, whose expression also relies on Rtca.

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Background: The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opinions on novel psychoactive substances. However, due to the large volume of data, obtaining useful insights through natural language processing technologies such as large language models is challenging.

Objective: This paper aims to develop a retrieval-augmented generation (RAG) architecture for medical question answering pertaining to clinicians' queries on emerging issues associated with health-related topics, using user-generated medical information on social media.

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