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10.52586/4934 http://scihub22266oqcxt.onion/10.52586/4934 34340267!ä!34340267 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Biosci+(Landmark+Ed) 2021 ; 26 (7): 198-206 Nephropedia Template TP {{tp|p=34340267|t=2021. Can commercial automated immunoassays be utilized to predict neutralizing antibodies after SARS-CoV-2 infection? A comparative study between three different assays |pdf=|usr=}}{{34340267}} gab.com Text Can commercial automated immunoassays be utilized to predict neutralizing antibodies after SARS-CoV-2 infection A comparative study between three different assays JO: Front Biosci (Landmark Ed) http://www.kidney.de/pget.php?&tw=1&pmid=34340267 #FOAvip Background: High-throughput assays that can infer neutralizing activity against SARS-CoV-2 are of great importance for assessing the immunity induced by natural infection and COVID-19 vaccines. We aimed to evaluate the performance and degree of correlation of three fully automated anti-SARS-CoV-2 immunoassays with neutralization activity using a surrogate virus-neutralizing test (sVNT) from GenScript, targeting the receptor-binding domain. Methods: 110 sera collected from PCR-confirmed asymptomatic COVID-19 individuals were tested for neutralizing antibodies (nAbs) using the sVNT. Positive samples were tested on three automated immunoassays targeting different viral antigens: Mindray CL-900i(R), Abbott Architect, and Ortho VITROS(R). The diagnostic sensitivity, specificity, agreement, and correlation with the sVNT were assessed. Receiver operating characteristic (ROC) curve analysis was performed to determine optimal thresholds for predicting the presence of neutralizing activity by each assay. Results: All three assays showed 100% specificities. The highest sensitivity was 99.0%, demonstrated by VITROS(R), followed by 94.3%, for CL-900i(R), and 81.0%, for Architect. Both VITROS(R) and CL-900i(R) had the strongest correlation with the sVNT (rho = 0.718 and rho = 0.712, respectively), while Architect showed a moderate correlation (rho = 0.618). ROC curve analysis indicated that the manufacturer's recommended cutoff values are adequate for predicting the presence of nAbs and providing a strong correlation with the sVNT. Conclusion: VITROS(R) and CL-900i(R) serological assays, which detect antibodies against SARS-CoV-2 spike protein, could serve as reliable assays to predict neutralization activity after infection or vaccination. Twit Text FOAVip Can commercial automated immunoassays be utilized to predict neutralizing antibodies after SARS-CoV-2 infection A comparative study between three different assays ????Front Biosci (Landmark Ed) http://www.kidney.de/pget.php?&tw=1&pmid=34340267 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34340267 #FOAvip English Wikipedia <ref>{{Cite pmid|34340267}}</ref> Can commercial automated immunoassays be utilized to predict neutralizing antibodies after SARS-CoV-2 infection? A comparative study between three different assays #MMPMID34340267 Ismail A; Shurrab FM; Al-Jighefee HT; Al-Sadeq DW; Qotba H; Al-Shaar IA; Yassine HM; Abu-Raddad LJ; Nasrallah GK Front Biosci (Landmark Ed) 2021[Jul]; 26 (7): 198-206 PMID34340267show ga Background: High-throughput assays that can infer neutralizing activity against SARS-CoV-2 are of great importance for assessing the immunity induced by natural infection and COVID-19 vaccines. We aimed to evaluate the performance and degree of correlation of three fully automated anti-SARS-CoV-2 immunoassays with neutralization activity using a surrogate virus-neutralizing test (sVNT) from GenScript, targeting the receptor-binding domain. Methods: 110 sera collected from PCR-confirmed asymptomatic COVID-19 individuals were tested for neutralizing antibodies (nAbs) using the sVNT. Positive samples were tested on three automated immunoassays targeting different viral antigens: Mindray CL-900i(R), Abbott Architect, and Ortho VITROS(R). The diagnostic sensitivity, specificity, agreement, and correlation with the sVNT were assessed. Receiver operating characteristic (ROC) curve analysis was performed to determine optimal thresholds for predicting the presence of neutralizing activity by each assay. Results: All three assays showed 100% specificities. The highest sensitivity was 99.0%, demonstrated by VITROS(R), followed by 94.3%, for CL-900i(R), and 81.0%, for Architect. Both VITROS(R) and CL-900i(R) had the strongest correlation with the sVNT (rho = 0.718 and rho = 0.712, respectively), while Architect showed a moderate correlation (rho = 0.618). ROC curve analysis indicated that the manufacturer's recommended cutoff values are adequate for predicting the presence of nAbs and providing a strong correlation with the sVNT. Conclusion: VITROS(R) and CL-900i(R) serological assays, which detect antibodies against SARS-CoV-2 spike protein, could serve as reliable assays to predict neutralization activity after infection or vaccination. |Antibodies, Neutralizing/*blood[MESH] |Automation[MESH] |COVID-19/*immunology/virology[MESH] |Humans[MESH] |Immunoassay/*methods[MESH] |Limit of Detection[MESH]Can commercial automated immunoassays be utilized to predict neutraliz(epmc).pdf DeepDyve Pubget Overpricing