Plasma fibrinogen participates in several physiological and pathological events thus becoming a useful studying material in biomedical research. Here we report a new convenient method for fibrinogen purification based on the affinity of Staphylococcus aureus clumping factor A to fibrinogen. Clumping factor A (ClfA) is a cell wall-anchored surface protein of S. aureus bacteria that binds with a high affinity to the fibrinogen gamma chain C-terminus via a segment encompassing the residues 221-550. This activity of ClfA (ClfA(221-550)) was produced in fusion to the C-terminus of glutathione-S-transferase (GST) with recombinant technology and used as an affinity ligand to capture plasma fibrinogen. GST-ClfA(221-550) fusion protein was immobilized onto the glutathione-conjugated beads packed in a plastic column by its GST part. Then, this affinity column was loaded with citrated and heparinized human plasma. After washing out unbound proteins, column-captured fibrinogen was specifically eluted down with a citrate buffer solution (50mM, pH 5.6). Purified human fibrinogen exhibited the ability to support platelet adhesion and aggregation and formed fibrin clot by thrombin, indicating that ClfA(221-550)-purified human fibrinogen is a functionally active product. We also found that both the rat and mouse fibrinogens could be purified as well as human fibrinogen with this method. By virtue of its simplicity and feasibility, ClfA(221-550)-based method would be very useful to the investigators who need fibrinogen to perform their studies.
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http://dx.doi.org/10.1016/j.pep.2008.05.007 | DOI Listing |
J Inflamm Res
January 2025
Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Purpose: The albumin to fibrinogen ratio (AFR), a biomarker associated with inflammatory, nutritional, and coagulation status, and the CALLY index, a biomarker combining C-reactive protein, albumin, and lymphocyte count, have been suggested to correlate with prognosis in a variety of diseases in previous studies; however, studies of these two markers in ulcerative colitis (UC) are lacking. The aim of this study was to evaluate the clinical significance of AFR and CALLY index in UC.
Methods: The study included 109 UC patients and 126 healthy controls.
Transl Lung Cancer Res
December 2024
Department of Respiratory Medicine, Qingdao Municipal Hospital, Qingdao, China.
Background: Patients diagnosed with non-small cell lung cancer (NSCLC) usually have a poor prognosis, so it is critical to identify effective biomarkers for prognosis prediction. The aim of this study is to establish a nomogram to evaluate the prognostic significance of blood markers in patients with NSCLC and provide reference for clinical work.
Methods: A total of 486 patients with NSCLC who were admitted to hospital from January 2009 to December 2019 were retrospectively analyzed.
Front Pharmacol
January 2025
Institute of Medicinal Plant Development, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
Background: Diabetic nephropathy (DN) is a prevalent global renal illness and one of the main causes of end-stage renal disease (ESRD). FGF21 has been shown to ameliorate diabetic nephropathy, and in addition FGF-21-treated mice impeded mitogenicity, whereas it is unclear whether FGF21 can influence DN progression by regulating the cell cycle in diabetic nephropathy.
Methods: In order to create a diabetic model, STZ injections were given to C57BL/6J mice for this investigation.
Front Pharmacol
January 2025
TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Background: Diabetic kidney disease (DKD) has become the leading cause of end-stage renal disease in the world. However, the current conventional approaches have not yet achieved satisfactory efficacy. As one of the most influential products in botanical medicine, L.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Neurosurgery, Tokyo Medical and Dental University, Bunkyo-ku, Japan.
Objective: Neurological deterioration after mild traumatic brain injury (TBI) has been recognized as a poor prognostic factor. Early detection of neurological deterioration would allow appropriate monitoring and timely therapeutic interventions to improve patient outcomes. In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.
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