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Endocrine
January 2025
Department of Health Management, Chronic Health Management Laboratory, Henan Provincial People's Hospital, Zhengzhou, 450003, China.
Background: The impact of fatty liver disease on lumbar bone mineral density (BMD) represents an intriguing area of study, particularly in light of established research linking obesity to bone metabolism. However, there remains limited investigation into the correlation between quantifying liver fat content (LFC) and lumbar BMD among overweight and obese populations, particularly within the Chinese demographic. This study aims to accurately quantify LFC and investigate its association with lumbar BMD in overweight or obese individuals.
View Article and Find Full Text PDFOecologia
January 2025
Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, 80523, USA.
Immigration and emigration are key demographic processes of animal population dynamics. However, we have limited knowledge on how fine-scale movement varies over space and time. We developed a Bayesian integrated population model using individual mark-recapture and count data to characterize fine-scale movement of stream fish at 20-m resolution in a 740-m study area every two months for 28 months.
View Article and Find Full Text PDFIr J Med Sci
January 2025
Unidad de Investigación Biomédica, Delegación Durango, Instituto Mexicano del Seguro Social, Predio Canoas 100, Col. Los Angeles, Durango, 34077, México.
Background: It has been revealed that the potential utility of the triglycerides and glucose (TyG) index as an effective option for assessing glycemic control; however, evidence in this field is still scarce.
Aims: The goal of this study was to investigate the diagnostic accuracy of the TyG index, as an alternative option, to detect inadequate glycemic control in patients with type 2 diabetes (T2D).
Methods: Men and women between 30 and 60 years of age diagnosed with type 2 diabetes were included in a cross-sectional study.
J Intern Med
January 2025
Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Harvard Institutes of Medicine (HIM), Boston, Massachusetts, USA.
Background: Steatotic liver disease (SLD) is a potentially reversible condition but often goes unnoticed with the risk for end-stage liver disease.
Purpose: To opportunistically estimate SLD on lung screening chest computed tomography (CT) and investigate its prognostic value in heavy smokers participating in the National Lung Screening Trial (NLST).
Material And Methods: We used a deep learning model to segment the liver on non-contrast-enhanced chest CT scans of 19,774 NLST participants (age 61.
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