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Interaction between genetic risk score and dietary carbohydrate intake on high-density lipoprotein cholesterol levels: Findings from the study of obesity, nutrition, genes and social factors (SONGS).

Clin Nutr ESPEN

January 2025

Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK; Institute for Food, Nutrition, and Health (IFNH), University of Reading, Reading, RG6 6AP, UK. Electronic address:

Background & Aims: Cardiometabolic traits are complex interrelated traits that result from a combination of genetic and lifestyle factors. This study aimed to assess the interaction between genetic variants and dietary macronutrient intake on cardiometabolic traits [body mass index, waist circumference, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triacylglycerol, systolic blood pressure, diastolic blood pressure, fasting serum glucose, fasting serum insulin, and glycated haemoglobin].

Methods: This cross-sectional study consisted of 468 urban young adults aged 20 ± 1 years, and it was conducted as part of the Study of Obesity, Nutrition, Genes and Social factors (SONGS) project, a sub-study of the Young Lives study.

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In Silico Bioinformatics Analysis on the Role of Long Non-Coding RNAs as Drivers and Gatekeepers of Androgen-Independent Prostate Cancer Using LNCaP and PC-3 Cells.

Curr Issues Mol Biol

September 2023

SAMRC Precision Oncology Research Unit (PORU), DSI/NRF SARChI Chair in Precision Oncology and Cancer Prevention (POCP), Pan African Cancer Research Institute (PACRI), University of Pretoria, Hatfield 0028, South Africa.

Prostate cancer (PCa) is the leading cancer in men globally. The association between PCa and long non-coding RNAs (lncRNAs) has been reported. Aberrantly expressed lncRNAs have been documented in each of the cancer "hallmarks".

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Oxygenation during the Cambrian Radiation progressed via a series of short-lived pulses. However, the metazoan biotic response to this episodic oxygenation has not been quantified, nor have the causal evolutionary processes been constrained. Here we present ecological analyses of Cambrian archaeocyath sponge reef communities on the Siberian Platform (525-514 Ma).

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Network data is composed of nodes and edges. Successful application of machine learning/deep learning algorithms on network data to make node classification and link prediction have been shown in the area of social networks through which highly customized suggestions are offered to social network users. Similarly one can attempt the use of machine learning/deep learning algorithms on biological network data to generate predictions of scientific usefulness.

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Convergence of Machine Vision and Melt Electrowriting.

Adv Mater

July 2021

Institute of Health and Biomedical Innovation, Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, 4059, Australia.

Melt electrowriting (MEW) is a high-resolution additive manufacturing technology that balances multiple parametric variables to arrive at a stable fabrication process. The better understanding of this balance is underscored here using high-resolution camera vision of jet stability profiles in different electrical fields. Complementing this visual information are fiber-diameter measurements obtained at precise points, allowing the correlation to electrified jet properties.

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