Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75247/1/j.1461-0248.2007.01094.x.pd

Variant-Specific Viral Kinetics in Acute COVID-19

Understanding variant-specific differences in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral kinetics may explain differences in transmission efficiency and provide insights on pathogenesis and prevention. We evaluated SARS-CoV-2 kinetics from nasal swabs across multiple variants (Alpha, Delta, Epsilon, Gamma) in placebo recipients of the ACTIV-2/A5401 trial. Delta variant infection led to the highest maximum viral load and shortest time from symptom onset to viral load peak. There were no significant differences in time to viral clearance across the variants. Viral decline was biphasic with first- and second-phase decays having half-lives of 11 hours and 2.5 days, respectively, with differences among variants, especially in the second phase. These results suggest that while variant-specific differences in viral kinetics exist, post-peak viral load all variants appeared to be efficiently cleared by the host. Clinical Trials Registration. NCT04518410

Statistical Challenges When Analyzing SARS-CoV-2 RNA Measurements Below the Assay Limit of Quantification in COVID-19 Clinical Trials

Most clinical trials evaluating coronavirus disease 2019 (COVID-19) therapeutics include assessments of antiviral activity. In recently completed outpatient trials, changes in nasal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA levels from baseline were commonly assessed using analysis of covariance (ANCOVA) or mixed models for repeated measures (MMRM) with single imputation for results below assay lower limits of quantification (LLoQ). Analyzing changes in viral RNA levels with singly imputed values can lead to biased estimates of treatment effects. In this article, using an illustrative example from the ACTIV-2 trial, we highlight potential pitfalls of imputation when using ANCOVA or MMRM methods, and illustrate how these methods can be used when considering value

Association Between Anterior Nasal and Plasma SARS-CoV-2 RNA Levels and Hospitalization or Death in Nonhospitalized Adults With Mild-to-Moderate COVID-19

BackgroundThere is little information regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA as a predictor for clinical outcomes in outpatients with mild-to-moderate coronavirus disease 2019 (COVID-19).MethodsAnterior nasal (AN) and plasma SARS-CoV-2 RNA data from 2115 nonhospitalized adults who received monoclonal antibodies (mAbs) or placebo in the ACTIV-2/A5401 trial were analyzed for associations with hospitalization or death.ResultsOne hundred two participants were hospitalized or died through 28 days of follow-up. Higher day 0 (pretreatment) AN RNA was associated with increasing risk of hospitalization/death (risk ratio [RR], 1.24 per log10 copies/mL [95% confidence interval {CI}, 1.04-1.49]) among placebo recipients, ranging from 3% to 16% for <2 to ≥6 log10 copies/mL. Although only 1% had quantifiable levels, there was a similar trend across day 0 plasma RNA categories. Higher day 3 AN RNA was associated with subsequent hospitalization/death among placebo recipients (RR, 1.42 per log10 copies/mL [95% CI, 1.00-2.03]), but not mAb recipients (RR, 1.02 per log10 copies/mL [95% CI, 0.68-1.56]). The proportion of treatment effect (reduction in hospitalizations/deaths after day 3 for mAb vs placebo) explained by day 3 AN RNA was 8%.ConclusionsSARS-CoV-2 RNA levels are predictive of hospitalization/death in the natural history setting, but AN RNA levels may not be a reliable surrogate marker of mAb treatment effect in COVID-19 trials. Clinical Trials Registration. NCT04518410

Assessing the Influence of Different ROI Selection Strategies on Functional Connectivity Analyses of fMRI Data Acquired During Steady-State Conditions

In blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI), assessing functional connectivity between and within brain networks from datasets acquired during steady-state conditions has become increasingly common. However, in contrast to connectivity analyses based on task-evoked signal changes, selecting the optimal spatial location of the regions of interest (ROIs) whose timecourses will be extracted and used in subsequent analyses is not straightforward. Moreover, it is also unknown how different choices of the precise anatomical locations within given brain regions influence the estimates of functional connectivity under steady-state conditions. The objective of the present study was to assess the variability in estimates of functional connectivity induced by different anatomical choices of ROI locations for a given brain network. We here targeted the default mode network (DMN) sampled during both resting-state and a continuous verbal 2-back working memory task to compare four different methods to extract ROIs in terms of ROI features (spatial overlap, spatial functional heterogeneity), signal features (signal distribution, mean, variance, correlation) as well as strength of functional connectivity as a function of condition. We show that, while different ROI selection methods produced quantitatively different results, all tested ROI selection methods agreed on the final conclusion that functional connectivity within the DMN decreased during the continuous working memory task compared to rest