Search alternatives:
significant deviation » significant variation (Expand Search), significant elevation (Expand Search), significant variations (Expand Search)
force decrease » forces increased (Expand Search)
deviation test » mediation test (Expand Search), devaluation test (Expand Search), deviation costs (Expand Search)
fold decrease » fold increase (Expand Search), fold increased (Expand Search)
significant deviation » significant variation (Expand Search), significant elevation (Expand Search), significant variations (Expand Search)
force decrease » forces increased (Expand Search)
deviation test » mediation test (Expand Search), devaluation test (Expand Search), deviation costs (Expand Search)
fold decrease » fold increase (Expand Search), fold increased (Expand Search)
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Number of significantly significant (P < 0.05) differentially abundant (SSDA) proteins showing increased or decreased activity (fold change +/- 1.5-fold) relative to time 0 following storage at 9°C or 20°C of infective juveniles of <i>S</i>....
Published 2022“…<p>Number of significantly significant (P < 0.05) differentially abundant (SSDA) proteins showing increased or decreased activity (fold change +/- 1.5-fold) relative to time 0 following storage at 9°C or 20°C of infective juveniles of <i>S</i>. …”
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Log fold change (FC), mean and standard deviation (SD) of each lipid specie from the morbid obese (MO) and the normal-weight (NW) groups, and p-values.
Published 2024“…One-way ANOVA test was used to identify significant differences (adjusted p-value <0.05 was considered significant).…”
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Means (and standard deviations) of the difference scores between the ratings for the present minus the ratings for the past/future for five personality dimensions, with the significance test of the difference from 0 (one-sample t-test).
Published 2022“…<p>Means (and standard deviations) of the difference scores between the ratings for the present minus the ratings for the past/future for five personality dimensions, with the significance test of the difference from 0 (one-sample t-test).…”
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