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| http://dx.doi.org/10.1503/cmaj.090361 | DOI Listing |
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The Causal Effects of Lifestyle Factors on Osteoarthritis: A Two-sample Mendelian Randomisation Study.
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Division of Trauma and Orthopaedics, Department of Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
Background: Modern sedentary lifestyles are prevalent among individuals with osteoarthritis. However, direct evidence linking such behaviours as causative factors of osteoarthritis remain limited due to the presence of confounding variables.
Objective: This study aims to determine the extent to which lifestyle factors have causal effects on osteoarthritis through a two-sample Mendelian randomisation (MR) study.
Toward the elimination of NTDs: application of cost-effective and sensitive molecular environmental surveillance tools-a pilot study.
Front Parasitol
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Biomedical and Public Health Research Unit, Council for Scientific and Industrial Research -Water Research Institute, Accra, Ghana.
Neglected tropical diseases (NTDs) affect over a billion people worldwide. The 2021-2030 NTD road map calls for innovative and highly efficient interventions to eliminate or significantly reduce the burden of NTDs. These include sensitive and cost-effective diagnostic techniques for disease surveillance.
View Article and Find Full Text PDFDistinct population-wide differences in contaminants and blood parameters in foraging green sea turtles.
Mar Pollut Bull
January 2025
School of Science, Technology and Engineering, University of the Sunshine Coast, Hervey Bay, Queensland 4655, Australia.
The rising diversity and concentration of contaminants have surpassed ecological thresholds, threatening marine ecosystems. The effects of pollutants on marine animals, particularly sea turtles, are receiving increased attention due to their role as indicators of human impacts. This study examined the health implications of contaminant exposure in three green turtle (Chelonia mydas) foraging sites in the southern Great Barrier Reef, Australia.
View Article and Find Full Text PDFMachine learning analysis of population-wide plasma proteins identifies hormonal biomarkers of Parkinson's Disease.
medRxiv
December 2024
Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
As the number of Parkinson's patients is expected to increase with the growth of the aging population there is a growing need to identify new diagnostic markers that can be used cheaply and routinely to monitor the population, stratify patients towards treatment paths and provide new therapeutic leads. Genetic predisposition and familial forms account for only around 10% of PD cases [1] leaving a large fraction of the population with minimal effective markers for identifying high risk individuals. The establishment of population-wide omics and longitudinal health monitoring studies provides an opportunity to apply machine learning approaches on these unbiased cohorts to identify novel PD markers.
View Article and Find Full Text PDFEvaluation of self-collected dried blood spots for detection of SARS-CoV-2 nucleocapsid antibodies shows low sensitivity.
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Background And Aims: Dried blood spots (DBS) have been proposed as a cost-effective surveillance method for population-wide screening of SARS-CoV-2 immunity but sensitivity of DBS based on self-collected DBS samples is unknown. To evaluate the success of vaccination strategies, it is necessary to differentiate vaccination from natural infection. Therefore, a test for antibodies against the viral nucleocapsid protein (anti-N) is desirable.
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