https://www.selleckchem.com/products/FK-506-(Tacrolimus).html Quantitative serological assays detecting response to SARS-CoV-2 are needed to quantify immunity. This study analyzed the performance and correlation of two quantitative anti-S1 assays in oligo-/asymptomatic individuals from a population-based cohort. In total, 362 plasma samples (108 with reverse transcription-polymerase chain reaction [RT-PCR]-positive pharyngeal swabs, 111 negative controls, and 143 with positive serology without confirmation by RT-PCR) were tested with quantitative assays (Euroimmun Anti-SARS-CoV-2 QuantiVac enzyme-linked immunosorbent assay [EI-S1-IgG-quant]) and Roche Elecsys Anti-SARS-CoV-2 S [Ro-RBD-Ig-quant]), which were compared with each other and confirmatory tests, including wild-type virus micro-neutralization (NT) and GenScript cPass™. Square roots of coefficients of determination were calculated for continuous variables and non-parametric tests were used for paired comparisons. Quantitative anti-S1 serology correlated well with each other (true positives, 96%; true00475-x. The online version contains supplementary material available at 10.1007/s40121-021-00475-x.Enormous amounts of unstructured data such as images, videos, emails, sensors' data and documents of multiple types are being generated daily by varied applications. Apart from the challenges related to collection or processing of this data, its efficient storage is also a significant challenge since this data do not conform to any predefined storage model. Therefore, any enterprise dealing with huge unstructured data requires a scalable storage system that can provide data durability and availability at a low cost. The paper proposes a tenant-centric approach to develop an object-based software defined storage system for SaaS multi-tenant applications. We present TOSDS (Tenant-centric Object-based Software Defined Storage), a system that can efficiently meet the storage requirements of users or tenants with divers