promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling.

Summary: We present promor, a comprehensive, user-friendly R package that streamlines label-free quantification proteomics data analysis and building machine learning-based predictive models with top protein candidates.

Availability And Implementation: promor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN) (https://CRAN.R-project.

Five Influential Factors for Clinical Team Performance in Urgent, Emergency Care Contexts.

Introduction: In deployed contexts, military medical care is provided through the coordinated efforts of multiple interdisciplinary teams that work across and between a continuum of widely distributed role theaters. The forms these teams take, and functional demands, vary by roles of care, location, and mission requirements. Understanding the requirements for optimal performance of these teams to provide emergency, urgent, and trauma care for multiple patients simultaneously is critical.

Toward Live Virtual Constructive Simulations in Healthcare Learning.

This article explores the combination of live, virtual, and constructive (LVC) simulations in healthcare. Live, virtual, and constructive simulations have long existed in the military, but their consideration (and deployment) in medical and healthcare domains is relatively new. We conducted a review on LVC- its current application in the military domain -and highlight an approach, challenges, and present suggestions for its implementation in healthcare learning.