首页|Federal State Budgetary Educational Institution of Higher Education Reports Find ings in COVID-19 (Evaluation of serum and urine biomarkers for severe COVID-19)
Federal State Budgetary Educational Institution of Higher Education Reports Find ings in COVID-19 (Evaluation of serum and urine biomarkers for severe COVID-19)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Coronavirus-COVID-19 is the subject of a report. According to news reporting originating in Moscow, Russia, by NewsRx journalists, research stated, "The new coronavirus disease, CO VID-19, poses complex challenges exacerbated by several factors, with respirator y tissue lesions being notably significant among them. Consequently, there is a pressing need to identify informative biological markers that can indicate the s everity of the disease." The news reporters obtained a quote from the research from the Federal State Bud getary Educational Institution of Higher Education, "Several studies have highli ghted the involvement of proteins such as APOA1, XPNPEP2, ORP150, CUBN, HCII, an d CREB3L3 in these respiratory tissue lesions. However, there is a lack of infor mation regarding antibodies to these proteins in the human body, which could pot entially serve as valuable diagnostic markers for COVID-19. Simultaneously, it i s relevant to select biological fluids that can be obtained without invasive pro cedures. Urine is one such fluid, but its effect on clinical laboratory analysis is not yet fully understood due to lack of study on its composition. Methods us ed in this study are as follows: total serum protein analysis; ELISA on moderate and severe COVID-19 patients' serum and urine; bioinformatic methods: ROC analy sis, PCA, SVM. The levels of antiAPOA1, antiXPNPEP2, antiORP150, antiCUBN, antiH CII, and antiCREB3L3 exhibit gradual fluctuations ranging from moderate to sever e in both the serum and urine of COVID-19 patients. However, the diagnostic valu e of individual anti-protein antibodies is low, in both blood serum and urine. O n the contrary, joint detection of these antibodies in patients' serum significa ntly increases the diagnostic value as demonstrated by the results of principal component analysis (PCA) and support vector machine (SVM). The non-linear regres sion model achieved an accuracy of 0.833. Furthermore, PCA aided in identifying serum protein markers that have the greatest impact on patient group discriminat ion."
MoscowRussiaEurasiaAntibodiesBio markersBlood ProteinsCOVID-19CoronavirusDiagnostics and ScreeningHealt h and MedicineImmunoglobulinsImmunologyProteinsRNA VirusesRisk and Pre ventionSARS-CoV-2Severe Acute Respiratory Syndrome Coronavirus 2TestingV iralVirology
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