Author: Bingyi Yang; Justin Lessler; Huachen Zhu; Chaoqiang Jiang; Jonathan M. Read; James A Hay; Kin On Kwok; Ruiyin Shen; Yi Guan; Steven Riley; Derek A.T. Cummings
Title: Life course exposures continually shape antibody profile and risk of seroconversion to influenza Document date: 2020_1_16
ID: cyxn7dpw_94
Snippet: We characterized the strain distribution among for subgroups of titers, i.e. decrease, no change, two-fold increase and seroconversion and compared these distributions with the underlying strain distribution (fig. S15 ). The underlying strain distribution was calculated by dividing the number of available titers for the strain by the total number of available titers for all strains in the examined dataset. In order to assess the ceiling effects, .....
Document: We characterized the strain distribution among for subgroups of titers, i.e. decrease, no change, two-fold increase and seroconversion and compared these distributions with the underlying strain distribution (fig. S15 ). The underlying strain distribution was calculated by dividing the number of available titers for the strain by the total number of available titers for all strains in the examined dataset. In order to assess the ceiling effects, we performed this analysis to two separate subsets of titers that only include pre-existing titers 1 : 8 0 and 1 : 8 0 (fig. S15 B and C), respectively. Results suggested that the strain distribution by changes in titers seemed not to be affected by the ceiling effects, with the most dynamic changes observed for recent strains.
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