Molecules in living organisms are in a constant state of turnover at varying rates, i.e., synthesis, breakdown, oxidation, and/or conversion to different compounds. Despite the dynamic nature of biomolecules, metabolic research has focused heavily on static, snapshot information such as the abundances of mRNA, protein, and metabolites and/or (in)activation of molecular signaling, often leading to erroneous conclusions regarding metabolic status. Over the past century, stable, non-radioactive isotope tracers have been widely used to provide critical information on the dynamics of specific biomolecules (metabolites and polymers including lipids, proteins, and DNA), in studies in vitro in cells as well as in vivo in both animals and humans. In this review, we discuss (1) the historical background of the use of stable isotope tracer methodology in metabolic research; (2) the importance of obtaining kinetic information for a better understanding of metabolism; and (3) the basic principles and model structures of stable isotope tracer methodology using C-, N-, or H-labeled tracers.
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http://dx.doi.org/10.1038/s12276-022-00814-z | DOI Listing |
Methods Cell Biol
January 2025
Translational Radiomics, Luxembourg Institute of Health, Luxembourg City, Luxembourg; In-Vivo Imaging Platform, Luxembourg Institute of Health, Luxembourg City, Luxembourg.
During hypoxia, tissues are subjected to an inadequate oxygen supply, disrupting the balance needed to maintain normal function. This deficiency can occur due to reduced oxygen delivery caused by impaired blood flow or a decline in the blood's ability to carry oxygen. In tumors, hypoxia and vascularization play crucial roles, shaping their microenvironments and influencing cancer progression, response to treatment and metastatic potential.
View Article and Find Full Text PDFAlzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
View Article and Find Full Text PDFActa Physiol (Oxf)
February 2025
Clinical Physiology/Nutritional Medicine, Medical Department, Division of Gastroenterology, Infectiology, Rheumatology, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Aim: Members of the claudin protein family are the major constituents of tight junction strands and determine the permeability properties of the paracellular pathway. In the kidney, each nephron segment expresses a distinct subset of claudins that form either barriers against paracellular solute transport or charge- and size-selective paracellular channels. It was the aim of the present study to determine and compare the permeation properties of these renal paracellular ion channel-forming claudins.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Radiation Oncology, University Medical Centre Freiburg, Robert-Koch Straße 3, 79106, Freiburg, Germany.
Purpose: Prostate-specific membrane-antigen positron emission tomography (PSMA PET) is a promising candidate for non-invasive characterization of prostate cancer (PCa). This study evaluated whether PET with tracers [Ga]Ga-PSMA-11 or [F]PSMA-1007 is capable to depict intratumour heterogeneity of histological PSMA expression.
Methods: Thirty-five patients with biopsy-proven primary PCa without evidence of metastatic disease nor prior interventions were prospectively enrolled.
Sports Med
January 2025
Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
Background: Identification of genetic alleles associated with both Alzheimer's disease (AD) and concussion severity/recovery could help explain the association between concussion and elevated dementia risk. However, there has been little investigation into whether AD risk genes associate with concussion severity/recovery, and the limited findings are mixed.
Objective: We used AD polygenic risk scores (PRS) and APOE genotypes to investigate any such associations in the NCAA-DoD Grand Alliance CARE Consortium (CARE) dataset.
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