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| http://dx.doi.org/10.1159/000464416 | DOI Listing |
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Machine learning techniques for the prediction of indoor gamma-ray dose rates - Strengths, weaknesses and implications for epidemiology.
J Environ Radioact
December 2024
Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, DHHS, NIH, Bethesda, MD, 20892-9778, USA; Faculty of Health and Life Sciences, Oxford Brookes University, Headington Campus, Oxford, OX3 0BP, UK. Electronic address:
We investigate methods that improve the estimation of indoor gamma ray dose rates at locations where measurements had not been made. These new predictions use a greater range of modelling techniques and larger variety of explanatory variables than our previous examinations of this subject. Specifically, we now employ three types of machine learning models in addition to the geostatistical, nearest neighbour and other earlier models.
View Article and Find Full Text PDFSeed tuber microbiome can predict growth potential of potato varieties.
Nat Microbiol
December 2024
Plant-Microbe Interactions, Institute of Environmental Biology, Department of Biology, Science4Life, Utrecht University, Utrecht, the Netherlands.
Potato vigour, the growth potential of seed potatoes, is a key agronomic trait that varies significantly across production fields due to factors such as genetic background and environmental conditions. Seed tuber microbiomes are thought to influence plant health and crop performance, yet the precise relationships between microbiome composition and potato vigour remain unclear. Here we conducted microbiome sequencing on seed tuber eyes and heel ends from 6 potato varieties grown in 240 fields.
View Article and Find Full Text PDFType 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches.
Sci Rep
December 2024
Department of Clinical and Biomedical Sciences, RILD Building, Royal Devon and Exeter Hospital, University of Exeter, Barrack Road, Exeter, EX2 5DW, UK.
A Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes.
View Article and Find Full Text PDFDescription of Encyonemataceae fam. nov. and Witkowskiaceae fam. nov. (Bacillariophyceae, Cymbellales) based on molecular and morphological analyses.
Sci Rep
December 2024
К.A. Timiryazev Institute of Plant Physiology RAS, IPP RAS, 35 Botanicheskaya St., Moscow, 127276, Russia.
In this study, based on the results of molecular analysis of SSU rRNA and rbcL sequences, we propose the descriptions of two new families in the order Cymbellales. Molecular data demonstrates that diatoms of the genus Encyonema constitute an independent monophyletic clade, which represents a new family described herein - Encyonemataceae fam. nov.
View Article and Find Full Text PDFEPLIN, a prospective oncogenic molecule with contribution to growth, migration and drug resistance in pancreatic cancer.
Sci Rep
December 2024
School of Medicine, Cardiff University, Henry Wellcome Building, Cardiff, CF14 4XN, UK.
Most pancreatic cancer patients are diagnosed at advanced stages, with poor survival rates and drug resistance making pancreatic cancer one of the highest causes of cancer death in the UK. Understanding the underlying mechanism behind its carcinogenesis, metastasis and drug resistance has become an essential task for researchers. We have discovered that a well-established tumour suppressor, EPLIN, has an oncogenic rather than suppressive role in pancreatic cancer.
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