Background: Exposure of cryptic, functional sites on fibrinogen upon its adsorption to hydrophobic surfaces of biomaterials has been linked to an inflammatory response and fibrosis. Such adsorption also induces ordered fibrinogen aggregation which is poorly understood.
Objective: To investigate hydrophobic surface-induced fibrinogen aggregation.
Methods: Contact and lateral force scanning probe microscopy, yielding topography, image dimensions and fiber elastic modulus measurements were used along with transmission and scanning electron microscopy. Fibrinogen aggregation was induced under non-enzymatic conditions by adsorption on a trioctyl-surface monolayer (trioctylmethylamine) grafted onto silica clay plates.
Results: A more than one molecule thick coating was generated by adsorption on the plate from 100 to 200 μg mL⁻¹ fibrinogen solutions, and three-dimensional networks formed from 4 mg mL⁻¹ fibrinogen incubated with uncoated or fibrinogen-coated plates. Fibrils appeared laterally assembled into branching and overlapping fibers whose heights from the surface ranged from approximately 3 to 740 nm. The elastic modulus of fibrinogen fibers was 1.55 MPa. No fibrils formed when fibrinogen lacking αC-domains was used as a coating or was incubated with intact fibrinogen-coated plates, or when the latter plates were sequentially incubated with anti-Aα529-539 mAb and intact fibrinogen. When an anti-Aα241-476 mAb was used instead, fine, long fibers formed. Similarly, sequential incubations of fibrinogen-coated plates with recombinant αC-domain (Aα392-610 fragment) or αC-connector (Aα221-372 fragment) and fibrinogen resulted in distinctly fine fiber networks.
Conclusions: Adsorption-induced fibrinogen self-assembly is initiated by a more than one molecule-thick surface layer and eventuates in three-dimensional networks whose formation requires fibrinogen with intact αC-domains.
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http://dx.doi.org/10.1111/j.1538-7836.2010.04072.x | DOI Listing |
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1st Respiratory Medicine Department, "Sotiria" Chest Hospital, National and Kapodistrian University of Athens Medical School, 11527 Athens, Greece.
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Federal State Budgetary Scientific Institution, Research Institute for Complex Issues of Cardiovascular Diseases, Academician LS Barbarash Boulevard, 6, Kemerovo 650002, Russia.
We aim to evaluate the dynamics of glycemic status and markers of carbohydrate metabolism 12 months after coronary artery bypass grafting (CABG) and their relationship with the one-year prognosis. The analysis of outcomes of 653 patients during 1 year after coronary artery bypass grafting is presented. In those patients who visited the study center after 1 year, markers of carbohydrate metabolism (glucose, glycated hemoglobin, fructosamine, 1.
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Department of Tissue Engineering and Regenerative Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur 56000, Malaysia.
Fetal bovine serum (FBS) has long been the standard supplement in cell culture media, providing essential growth factors and proteins that support cell growth and differentiation. However, ethical concerns and rising costs associated with FBS have driven researchers to explore alternatives, particularly human platelet lysate (HPL). Among these alternatives, fibrinogen-depleted HPL (FD-HPL) has gained attention due to its reduced thrombogenicity, which minimizes the risk of clot formation in cell cultures and enhances the safety of therapeutic applications.
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Platelet-Rich Plasma (PRP) is a biological treatment widely used in regenerative medicine for its restorative capacity. Although PRP is typically applied at the time of obtention, long-term storage and preservation could enhance its versatility and clinical applications. The objective of this study was to evaluate the effect of long-term freezing on PRP.
View Article and Find Full Text PDFInt J Mol Sci
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Expert Medical Analysis Group, Institute of Technology, University of Castilla-La Mancha, 16071 Cuenca, Spain.
The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate between severe and mild cases. Furthermore, the use of artificial intelligence (AI) and machine learning (ML) to analyze large datasets has been crucial for rapidly identifying relevant biomarkers for disease prognosis, including COVID-19. This approach enhances diagnostics in emergency settings, allowing for more accurate and efficient patient management.
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