Objective: To validate GE PIXImus2 DXA fat mass (FM) estimates by chemical analysis, to compare previously published correction equations with an equation from our machine, and to determine intermachine variation.
Research Methods And Procedures: C57BL/6J (n = 16) and Aston (n = 14) mice (including ob/ob), Siberian hamsters (Phodopus sungorus) (n = 15), and bank voles (Clethrionomys glareolus) (n = 37) were DXA scanned postmortem, dried, then fat extracted using a Soxhlet apparatus. We compared extracted FM with DXA-predicted FM corrected using an equation designed using wild-type animals from split-sample validation and multiple regression and two previously published equations. Sixteen animals were scanned on both a GE PIXImus2 DXA in France and a second machine in the United Kingdom.
Results: DXA underestimated FM of obese C57BL/6J by 1.4 +/- 0.19 grams but overestimated FM for wild-type C57BL/6J (2.0 +/- 0.11 grams), bank voles (1.1 +/- 0.09 grams), and hamsters (1.1 +/- 0.13 grams). DXA-predicted FM corrected using our equation accurately predicted extracted FM (accuracy 0.02 grams), but the other equations did not (accuracy, -1.3 and -1.8 grams; paired Student's t test, p < 0.001). Two similar DXA instruments gave the same FM for obese mutant but not lean wild-type animals.
Discussion: DXA using the same software could use the same correction equation to accurately predict FM for obese mutant but not lean wild-type animals. PIXImus machines purchased with new software need validating to accurately predict FM.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1038/oby.2005.191 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Effects of Food Processing on Allergenicity.
Curr Allergy Asthma Rep
January 2025
Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Purpose Of Review: There is an increasing awareness among clinicians that industrial and household food processing methods can increase or decrease the allergenicity of foods. Modification to allergen properties through processing can enable dietary liberations. Reduced allergenicity may also allow for lower risk immunotherapy approaches.
View Article and Find Full Text PDFExploring the potential of compound-protein complex structure-free models in virtual screening using BlendNet.
Brief Bioinform
November 2024
Department of Computer Science, Yonsei University, Yonsei-ro 50, Seodaemun-gu, 03722, Seoul, Republic of Korea.
Identifying new compounds that interact with a target is a crucial time-limiting step in the initial phases of drug discovery. Compound-protein complex structure-based affinity prediction models can expedite this process; however, their dependence on high-quality three-dimensional (3D) complex structures limits their practical application. Prediction models that do not require 3D complex structures for binding-affinity estimation offer a theoretically attractive alternative; however, accurately predicting affinity without interaction information presents significant challenges.
View Article and Find Full Text PDFIdentification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms.
Ann Med
December 2025
Institute of Clinical Virology, Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Objective: We aimed at identifying acute phase biomarkers in Severe Fever with Thrombocytopenia Syndrome (SFTS), and to establish a model to predict mortality outcomes.
Methods: A retrospective analysis was conducted on multicenter clinical data. Group-based trajectory modeling (GBTM) was utilized to demonstrate the overall trend of laboratory indicators and their correlation with mortality.
Probing Biomolecular Interactions with Paramagnetic Nuclear Magnetic Resonance Spectroscopy.
Chembiochem
January 2025
Institute for Drug Discovery, University of Leipzig, Brüderstr. 34, 04103, Leipzig, Germany.
Recent advances in computational methods like AlphaFold have transformed structural biology, enabling accurate modeling of protein complexes and driving applications in drug discovery and protein engineering. However, predicting the structure of systems involving weak, transient, or dynamic interactions, or of complexes with disordered regions, remains challenging. Nuclear Magnetic Resonance (NMR) spectroscopy offers atomic-level insights into biomolecular complexes, even in weakly interacting and dynamic systems.
View Article and Find Full Text PDFIdentification of pyrimidine metabolism-based molecular subtypes and prognostic signature to predict immune landscape and guide clinical treatment in prostate cancer.
Ann Med
December 2025
Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Background: We previously described the enrichment of plasma exosome metabolites in CRPC, PCa, and TFC cohorts, and found significant differences in pyrimidine metabolites. The PMGs is associated with the clinical prognosis of several cancers, but its biological role in PCa is still unclear.
Methods: This study extracted 98 reliable PMGs, and analyzed their somatic mutations, expression levels, and prognostic significance.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!