Activated protein C (APC) inactivates membrane-bound factor Va following cleavages of the heavy chain at Arg, Arg, and Arg. The objective of this study is to examine which cleavage is most important for inactivation. The recombinant factor V molecules were constructed as follows: factor V (mutations R→Q), factor V (mutations R→Q), and factor V (mutations R→Q and R→Q). The recombinant molecules were expressed in mammalian cells, purified, and assayed prior and after incubation with APC and lipids for 30 min (factor Vai) in clotting assays and in an assay using purified reagents and saturating concentrations of factor Va. Clotting assays demonstrated that wild-type factor Vai (Vai), factor Vai, and factor Vai were devoid of activity, whereas factor Vai maintained approximately 70% activity following a 30 min incubation with APC. Prothrombinase assembled with all mutant cofactor molecules before and after treatment with APC had kinetic constant (Km) values similar to values found with prothrombinase assembled with factor Va. Prothrombinase assembled with factor Vai demonstrated a 20-fold reduction in kcat, whereas prothrombinase assembled with factor Vai had a two-fold reduction in kcat as compared with prothrombinase assembled with factor Va. In contrast, factor Vai and factor Vai did not show any loss in kcat under similar experimental conditions. In conclusion, our data demonstrate that the activity of an APC-treated factor Va molecule bearing a single mutation at Arg or Arg depends on the assay used; and regardless of the assay employed, in the absence of the APC-cleavage sites at Arg and Arg, the active cofactor is unable to be significantly inactivated by APC in the presence of a membrane surface.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3089681 | PMC |
http://dx.doi.org/10.1097/MBC.0b013e3283456c4e | DOI Listing |
Hormones (Athens)
January 2025
Endocrinology and Metabolism Research Center, Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences, Kerman, Iran.
Purpose: Metabolic syndrome (MetS) is a condition of high prevalence worldwide associated with increased risk of cardiovascular disease. The predictive value of novel indices of combined anthropometric and serum lipid parameters as predictors of MetS is, to our knowledge, unexplored. We aimed to assess the 10-year predictive value of three indices of triglyceride-glucose index (TyG), visceral adiposity index (VAI), and lipid accumulation product (LAP) for incidence of MetS in Southeastern Iran.
View Article and Find Full Text PDFBMC Nephrol
January 2025
Nutrition Research Center, Department of Clinical Nutrition, School of Nutrition and Food Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
Background: The prevalence of chronic kidney disease (CKD) is estimated to be about 13.4% worldwide. Studies have shown that CKD accounts for up to 2% of the health cost burden.
View Article and Find Full Text PDFSci Rep
January 2025
The Department of Orthopaedic Surgery, Southeast Hospital of Chongqing, Chongqing, 401336, China.
This study aimed to explore the synergistic effect of lipid accumulation product (LAP) and visceral adiposity index (VAI) on diabetes risk, and to evaluate the potential associations of these novel metabolic markers with diabetes. The current cross-sectional survey utilised data from the 2015-2018 National Health and Nutrition Examination Survey (NHANES). The relationship between LAP and VAI levels and diabetes was examined using multiple logistic regression analysis.
View Article and Find Full Text PDFHum Brain Mapp
December 2024
Department of Neurosciences and Mental Health, Fondazione IRCS Cà Granda Ospedale Policlinico, Milano, Italy.
Data aggregation across multiple research centers is gaining importance in the context of MRI research, driving diverse high-dimensional datasets to form large-scale heterogeneous sample, increasing statistical power and relevance of machine learning and deep learning algorithm. Site-related effects have been demonstrated to introduce bias in MRI features and confound subsequent analyses. Although Combating Batch (ComBat) technique has been recently reported to successfully harmonize multi-scale neuroimaging features, its performance assessments are still limited and largely based on qualitative visualizations and statistical analyses.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!