Good practices and common pitfalls of machine learning in nutrition research.

Machine learning is increasingly being utilised across various domains of nutrition research due to its ability to analyse complex data, especially as large datasets become more readily available. However, at times, this enthusiasm has led to the adoption of machine learning techniques prior to a proper understanding of how they should be applied, leading to non-robust study designs and results of questionable validity. To ensure that research standards do not suffer, key machine learning concepts must be understood by the research community.

Dual pathways of concealed gun carrying and use from adolescence to adulthood over a 25-year era of change.

Most homicides in the United States are committed using a handgun, but little research examines gun carrying over critical stages of the life course and changing contexts of violence. Notably, although most of the handgun homicides are committed by adults, most research on concealed gun carrying focuses on adolescents in single cohort studies. Using more than 25 years of longitudinal multicohort data from Chicago, 1994-2021, we show that pathways of concealed gun carrying are distinct between adolescence and adulthood.

Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review.

Purpose: The adoption of artificial intelligence (AI) in health care may afford new avenues for personalized and patient-centered care. This systematic review explored the role of AI in symptom monitoring for adult cancer survivors.

Methods: A comprehensive search was performed from inception to November 2023 in seven bibliographic databases and three clinical trial registries.

Active Probing of a RuO/CZ Catalyst Surface as a Tool for Bridging the Gap Between CO Oxidation Catalytic Tests in a Model and Realistic Exhaust Gas Stream.

Herein, we present a paper that attempts to bridge the gap between CO oxidation catalytic tests performed in a model stream and a more realistic exhaust gas stream by incorporating characterization methods that allow for active probing of the catalyst surface. The results have shown that it is not just the abundance of a given type of species on the surface that impacts the activity of a system but also the ease of extraction of ions from their surface (time-of-flight secondary ion mass spectrometry) and the response of the support to change in the feed composition (dynamic in situ X-ray diffraction (XRD) with variable atmosphere). The study utilizes the method of doping a catalyst (RuO/CZ) with a small amount of alkali-metal (K or Na) carbonates in order to slightly modify its surface to gain insight into parameters that may cause discrepancies between model stream activity and complex stream activity.