Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone.

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK).

Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning.

Introduction And Objectives: Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk prediction model specific for Sri Lankans using machine learning (ML) of data of a population-based, randomly selected cohort of Sri Lankans followed up for 10 years and to validate it in an external cohort.

Material And Methods: The cohort consisted of 2596 individuals between 40-65 years of age in 2007, who were followed up for 10 years.

Do National Nutrition Policies Relevant to Sri Lankan Adolescents Effectively Uplift Their Development and Well-Being? A Qualitative Study.

Adolescence is a crucial phase of growth and development in the life course, and healthy nutrition is essential during this period. The objective of this study was to explore the perceptions regarding the implementation of relevant nutrition policies for adolescents in Sri Lanka. The study is qualitative, employing a "phenomenology" approach.

Exploring the Temporal Patterns of Right Ventricular Pacing Burden.

Elevated right ventricular pacing (RVP) burdens are associated with the development of pacing-induced cardiomyopathy. This association is alluded to in the recent European and American pacing guidelines where anticipated pacing burden forms part of the indications for conduction system pacing. Understanding the temporal pattern of RVP burden is important with respect to anticipating future burden and ensuring that the most appropriate pacing modality is selected for patients.

The Determination of the Spatial Distribution of Indigenous Lipid Biomarkers in an Immature Jurassic Sediment Using Time-of-Flight-Secondary Ion Mass Spectrometry.

The ability to detect and map lipids, including potential lipid biomarkers, within a sedimentary matrix using mass spectrometry (MS) imaging may be critical to determine whether potential lipids detected in samples returned from Mars are indigenous to Mars or are contaminants. Here, we use gas chromatography-mass spectrometry (GC-MS) and time-of-flight-secondary ion mass spectrometry (ToF-SIMS) datasets collected from an organic-rich, thermally immature Jurassic geologic sample to constrain MS imaging analysis of indigenous lipid biomarkers in geologic samples. GC-MS data show that the extractable fractions are dominated by C-C steranes and sterenes as well as isorenieratene derivatives.