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Terbogrel, (E)-6-[4-(3-tert-butyl-2-cyanoguanidino)phenyl]-6-(3-pyridyl)hex-5-enoic acid, C23H27N5O2, a mixed thromboxane A2 receptor antagonist and thromboxane A2 synthase inhibitor, shows a hairpin-like conformation stabilized by an intramolecular hydrogen bond. A structural feature characteristic of the thromboxane A2 synthase inhibitor mode is observed: a distance of 8.4257 (19) Å between the pyridine N atom and the carboxyl group.
Some studies suggest that the monovalent mRNA-1273 vaccine is more effective than BNT162b2 in producing higher levels of antibodies. However, limited data are available, and the methods used are not directly comparable.
Accumulating evidence in the literature exemplifies the failings of real-time polymerase chain reaction (RT-PCR) as a sole diagnostic method in COVID-19 surveillance, because of its inability to detect past infection.1Winter A.K. Hegde S.T. The important role of serology for COVID-19 control.Lancet Infect Dis. 2020 Apr 21; (PubMed PMID:32330441Pubmed Central PMCID: PMC7173803. Epub 2020/04/25)Abstract Full Text Full Text PDF PubMed Scopus (175) Google Scholar, 2Yong S.E.F. Anderson D.E. Wei W.E. Pang J. Chia W.N. Tan C.W. et al.Connecting clusters of COVID-19: an epidemiological and serological investigation.Lancet Infect Dis. 2020 Apr 21; (PubMed PMID:32330439Pubmed Central PMCID: PMC7173813. Epub 2020/04/25)Abstract Full Text Full Text PDF PubMed Scopus (177) Google Scholar, 3Xu Y. Xiao M. Liu X. Xu S. Du T. Xu J. et al.Significance of serology testing to assist timely diagnosis of SARS-CoV-2 infections: implication from a family cluster.Emerg Microbes Infect. 2020 Apr 14; (PubMed PMID:32286155Epub 2020/04/15): 1-12PubMed Google Scholar, 4Stowell S. Guarner J. Role of serology in the COVID-19 pandemic.Clin Infect Dis. 2020 May 1; (PubMed PMID:32357206Pubmed Central PMCID: PMC7197618. Epub 2020/05/02)Crossref PubMed Scopus (25) Google Scholar The authors of these reports or correspondence highlighted the added value of serological testing, which, if captured within the correct timeframe after disease onset, can detect both active and past infections.1Winter A.K. Hegde S.T. The important role of serology for COVID-19 control.Lancet Infect Dis. 2020 Apr 21; (PubMed PMID:32330441Pubmed Central PMCID: PMC7173803. Epub 2020/04/25)Abstract Full Text Full Text PDF PubMed Scopus (175) Google Scholar By providing estimates of who is and is not immune to SARS-CoV-2, serological data can be used to estimate epidemiological variables, such as the attack rate or case-fatality rate, which are necessary to assess how much community transmission has occurred and its burden.5Jiang Y. Niu W. Wang Q. Zhao H. Meng L. Zhang C. Characteristics of a family cluster of Severe Acute Respiratory Syndrome Coronavirus 2 in Henan, China.J Infect. 2020 Apr 23; (PubMed PMID:32335170Pubmed Central PMCID: PMC7179487. Epub 2020/04/27)Abstract Full Text Full Text PDF Scopus (11) Google Scholar They can also be used to strategically deploy immune health-care workers to reduce exposure of the virus to susceptible individuals or to assess the effect of non-pharmaceutical interventions at the population level and inform policy changes to release such measures.6Dimeglio C. Loubes J.M. Deporte B. Dubois M. Latour J. Mansuy J.M. et al.The SARS-CoV-2 seroprevalence is the key factor for deconfinement in France.J Infect. 2020 Apr 28; (PubMed PMID:32360497Pubmed Central PMCID: PMC7189187. Epub 2020/05/04)Abstract Full Text Full Text PDF PubMed Scopus (17) Google Scholar In the near future, serological testing will be required to assess the effectiveness of vaccine candidates and finally, they are also useful to identify individuals who developed a strong immunological response to the virus and whose antibody isolates can be used to treat patients via plasma therapy.7Chen L. Xiong J. Bao L. Shi Y. Convalescent plasma as a potential therapy for COVID-19.Lancet Infect Dis. 2020; 20: 398-400Abstract Full Text Full Text PDF PubMed Scopus (772) Google Scholar However, several challenges still remain to correctly address the appropriate implementation, validation and interpretation of serological testing. Among them, understanding the kinetics of the antibodies matters as divergent opinion are reported in the literature.8Padoan A. Cosma C. Sciacovelli L. Faggian D. Plebani M. Analytical performances of a chemiluminescence immunoassay for SARS-CoV-2 IgM/IgG and antibody kinetics.Clin. Chem Lab Med CCLM / FESCC. 2020 Apr 16; (PubMed PMID:32301749Epub 2020/04/18)Crossref Scopus (227) Google Scholar,9Spicuzza L. Montineri A. Manuele R. Crimi C. Pistorio M.P. Campisi R. et al.Reliability and usefulness of a rapid IgM-IgG antibody test for the diagnosis of SARS-CoV-2 infection: a preliminary report.J Infect. 2020 Apr 23; (PubMed PMID:32335175Pubmed Central PMCID: PMC7177053. Epub 2020/04/27)Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar Our group recently reported the validation of a chemiluminescence immunoassay (CLIA) for IgG determination (LIAISONⓇSARS-CoV-2, DiaSorinⓇ, Saluggia, Italy) and reported the excellent analytical and clinical performance of the assay. However, data on antibody kinetics and assessment of IgA were not conveyed yet on this cohort. The sera from 182 symptomatic patients, positive for RT-PCR at admission, were included and assessed at different time points for dosing IgA (ELISA method, Euroimmun Medizinische LabordiagnostikaⓇ, Lübeck, Germany) and IgG (ELISA method, Euroimmun Medizinische LabordiagnostikaⓇ and CLIA LIAISONⓇSARS-CoV-2, DiaSorinⓇ). The complete follow-up at the 4 different time points was obtained for 15 of them. Statistical analyses show they are representative of the full cohort. Fig. 1 reports the change from the baseline and sensitivity at weeks 0, 1, 2 and 3 for IgA and IgG determinations. Both immunoglobulin levels increase over time and tend to stabilize after two weeks. Using our adapted cut-off, IgA determination shows a sensitivity of 100% after one week while it reaches 87% for IgG testing. The cut-off provided by the manufacturer still shows a sensitivity of 100% for IgA but it diminishes to 80% and 67% for IgG ELISA and IgG CLIA, respectively. After two weeks, all tests demonstrate a sensitivity of 100%, as reported by other groups,8Padoan A. Cosma C. Sciacovelli L. Faggian D. Plebani M. Analytical performances of a chemiluminescence immunoassay for SARS-CoV-2 IgM/IgG and antibody kinetics.Clin. Chem Lab Med CCLM / FESCC. 2020 Apr 16; (PubMed PMID:32301749Epub 2020/04/18)Crossref Scopus (227) Google Scholar,10Jin Y. Wang M. Zuo Z. Fan C. Ye F. Cai Z. et al.Diagnostic value and dynamic variance of serum antibody in coronavirus disease 2019.Int J Infect Dis. 2020 Apr 3; 94 (PubMed PMID:32251798Epub 2020/04/07): 49-52Abstract Full Text Full Text PDF PubMed Scopus (221) Google Scholar except when the cut-off provided by the manufacturer were used for IgG detection (i.e. one of our 15 patients was never considered as positive). These observations are of upmost importance for at least two analytical and clinical matters: first, the selection of the appropriate timeframe is essential for the detection of immunity. Namely, these results show that IgA immunity can be accurately detected one week after the RT-PCR positivity while IgG immunity has to be assessed after two weeks to avoid false negative results. Secondly, adapted cut-offs have to be established by each laboratory in order to improve the sensitivity of the commercial assays. However, this implies that the sera selected to define the adapted cut-off is crucial. In our case, the cut-off was determined on samples from symptomatic patients collected 14 days after the positive RT-PCR. Of note, there is to date no consensus on how to define the disease onset, i.e. date of first COVID-19 symptoms or date of RT-PCR. Despite being both validated and approved by competent authorities, these results show that the two IgG assays are not similar for determining positivity if measurement is performed at the time of RT-PCR determination (i.e. sensitivity of 7 and 20% for the CLIA and the ELISA method, respectively using the manufacturer cut-off). This further complexifies the interpretation of the results and highlights the need for competent national authorities and learned societies to establish guidance and procedures for serological testing to avoid misinterpretation of too early determination, leading to a high rate of false negative results. This study was not funded by governmental or industrial grant.
Background: Standardization, machine learning techniques and comparison to normality are concepts that are changing the landscape of multiparameter flow cytometry data analysis in clinical hematology. We applied these concepts to the follow‐up of acute myeloid leukemia (AML), which remains challenging due to the heterogeneity of the disease. Aims: To evaluate a new flow cytometry data analysis approach for the follow‐up of measurable residual disease in AML. Methods: Based on retrospective flow cytometry data, we developed a strategy for personalized monitoring of AML. This strategy is an evolution of the “leukemia associated immunophenotype” or “LAIP”‐approach that has been used the last decades in specialized flow cytometry laboratories. It relies on new concepts, comparing simultaneously the patient's follow‐up and diagnosis results to control group samples. We named these concepts the “leukemic cloud” and the “abnormality ratio”. To evaluate this approach, flow cytometry data of 6 AML patients and 20 control patients was used. All samples were analyzed with the same 10‐parameter (FSC‐A, SSC‐A, CD45, CD34, CD117, CD13, CD33, CD19, CD3, HLA‐DR) FACS Canto II flow cytometry assay. The “abnormality ratio” results over time were compared with morphology and molecular biology results. Results: The “Abnormality Ratio” results over time were in line with the clinical evolution of the patients (see example on image below) and were overall more sensitive for detecting residual disease than morphology and molecular biology, excepted for NPM1‐mutated AML. The “Abnormality Ratio” did not consider phenotypic switches of the malignant cell population identified at diagnosis. However, the discrepancy between the “abnormality ratio” results and morphology or molecular biology results could be used to objectify these phenotypic switches. Summary/Conclusion: We developed a quasi‐fully automatable flow cytometry data analysis algorithm. It could be used as a basis for the development of “next generation” flow cytometry assays for monitoring of hematological malignancies such as AML. Prospective studies are needed to confirm the applicability and limitations of our concepts. image
