Published: Jan. 1, 2024
Language: Английский
BMC Cardiovascular Disorders, Journal Year: 2024, Volume and Issue: 24(1)
Published: July 18, 2024
Abstract Background Expanding the number of biomarkers is imperative for studying etiology and improving venous thromboembolism prediction. In this study, we aimed to identify promising or targeted therapies improve detection accuracy early-stage deep vein thrombosis (DVT) reduce complications. Methods Quantibody Human Cytokine Antibody Array 440 (QAH-CAA-440) was used screen novel serum-based DVT/non-lower extremity DVT (NDVT). Differentially expressed proteins in were analyzed using bioinformatics methods validated a customized array. Diagnostic calculated receiver operating characteristics, machine learning applied establish biomarker model evaluating identified targets. Twelve targets selected validation. Results profiling conducted QAH-CAA-440 (RayBiotech, USA) quantimeter Cross-tabulation analysis with Venn diagrams common differential factors, leading selection 12 cytokines validation based on their clinical significance. These consistent results previous array analysis: FGF-6 (AUC = 0.956), Galectin-3 0.942), EDA-A2 0.933), CHI3L1 0.911), IL-1 F9 0.898), Dkk-4 0.88), IG-H3 0.876), IGFBP 0.858), Gas-1 Layilin 0.849), ULBP-2 0.813)and FGF-9 0.773). are expected serve as biomarkers, targets, therapeutic differentiate from NDVT. Conclusions EDA-A2, FGF-6, Dkk-4, F9, Galentin-3, Layilin, Big-h3, CHI3L1, ULBP-2, Gas-1, IGFBP-5, diagnosis treatment.
Language: Английский
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Medicina Clínica, Journal Year: 2024, Volume and Issue: 163(10), P. 517 - 521
Published: July 30, 2024
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Medicina Clínica (English Edition), Journal Year: 2024, Volume and Issue: 163(10), P. 517 - 521
Published: Nov. 1, 2024
Language: Английский
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International Immunopharmacology, Journal Year: 2024, Volume and Issue: 144, P. 113503 - 113503
Published: Nov. 25, 2024
Language: Английский
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Published: Jan. 1, 2024
Language: Английский
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