Publications by authors named "M G Cascio"
Introduction: The Joint United Nations Programme on HIV/AIDS (UNAIDS) Global 2025 targets prioritize action to overcome the collective barriers affecting the people and communities sitting on the outer margins of HIV care. Addressing the social and structural disparities that drive greater HIV prevalence and burden requires well-resourced, community-led responses that are fully integrated into national and global HIV initiatives.
Methods: The HIV Community Council (HCC), composed of 10 leaders from diverse global communities, convened to share their insights, amplify the community's voice, and identify barriers and solutions to empower all to live well with HIV through a dynamic, stepwise process of preparative work, deep discussion, prioritization, and consensus.
Objectives: Patients suffering from chronic pain use online platforms, such as Reddit, to engage in personal exchanges while maintaining anonymity. Analysis of comments and questions posted on these online forums provide unique insight into conversations that patients may be having outside of the physician's office regarding pain-relief procedures, specifically radiofrequency ablation (RFA).
Materials And Methods: Using the Python Reddit Application Programming Interface Wrapper, we identified and screened Reddit users' posts.
Article Synopsis
- Chemical cross-linking coupled with mass spectrometry (CX-MS) effectively identifies distance constraints in macromolecular protein complexes, providing insights into structures under near-native conditions.
- This study focused on the human α1 glycine receptor (α1 GlyR), using a site-specific chemical cross-linking strategy at position 41 to examine its configuration in the apo state.
- The results demonstrated significant cross-linking sites both within and between subunits of α1 GlyR, showcasing CX-MS as a valuable method for understanding the structural dynamics of integral membrane protein assemblies.
Development and Validation of a Natural Language Processing Algorithm for Extracting Clinical and Pathological Features of Breast Cancer From Pathology Reports.
JCO Clin Cancer Inform
August 2024
Purpose: Electronic health records (EHRs) are valuable information repositories that offer insights for enhancing clinical research on breast cancer (BC) using real-world data. The objective of this study was to develop a natural language processing (NLP) model specifically designed to extract structured data from BC pathology reports written in natural language.
Methods: During the initial phase, the algorithm's development cohort comprised 193 pathology reports from 116 patients with BC from 2012 to 2016.