Taking the Initiative? TLRP and Educational Research

Evaluating the effects of known subject traits on pediatric GI community structure and function. PCoA of the GI microbial communities of healthy children as a function of Bray-Curtis dissimilarities and 16S-based OTUs (A–D), WGS-based species (E–H), KO groups (I–L), and KEGG pathway profiles (M–P). Variation among profiles was evaluated with respect to known traits, and the percent variation captured by each axis is indicated in parenthesis. Adonis analysis results describe the significance of each trait to overall community variation. (TIF 1.58 kb

It’s not which school but which set you’re in that matters: the influence of ability-grouping practices on student progress in mathematics

The mathematics achievement of a cohort of 955 students in 42 classes in six schools in London was followed over a four-year period, until they took their GCSEs in the summer of 2000. All six schools were regarded by Ofsted as providing a good standard of education, and all were involved in teacher-training partnerships with universities. Matched data on key stage 3 test scores and GCSE grades were available for 709 students, and these data were analysed in terms of the progress from key stage 3 test scores to GCSE grades. Although there were wide differences between schools in terms of overall GCSE grades, the average progress made by students was similar in all six schools. However, within each school, the progress made during key stage 4 varied greatly from set to set. Comparing students with the same key stage 3 scores, students placed in top sets averaged nearly half a GCSE grade higher than those in the other upper sets, who in turn averaged a third of a grade higher than those in lower sets, who in turn averaged around a third of a grade higher than those students placed in bottom sets. In the four schools that used formal whole-class teaching, the difference in GCSE grades between top and bottom sets, taking key stage 3 scores into account, ranged from just over 1 grade at GCSE to nearly 3 grades. At the schools using small-group and individualised teaching, the differences in value-added between sets were not significant. In two of the schools, a significant proportion of working class students were placed into lower sets than would be indicated by their key stage 3 test scores

Global phylogenetic trees after AbundantOTU and QIIME denoising.

<p>Global phylogenetic trees show the distribution of taxonomy among all the pregnant and non-pregnant subject samples. The internal cluster dendrograms are colored by taxa Family level projections (annotated in figure legend), while the mid-circle is colored by the majority origins of OTUs from pregnant or non-pregnant subject samples (pregnant-magenta; non-pregnant-brown). Outermost circle using text to indicates OTU projection to Order level (Bacteroidales-red, Actinomycetales-yellow, Lactobacillales-green, Clostridiales-blue). OTU tables and representative sequences generated from AbundantOTU (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036466#pone-0036466-g004" target="_blank"><b>Figure 4A</b></a>) and QIIME denoised (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0036466#pone-0036466-g004" target="_blank"><b>Figure 4B</b></a>) datasets were employed in generating these global phylogenetic trees.</p

Additional file 9: Table S7. of Structure and function of the healthy pre-adolescent pediatric gut microbiome

Genera differing in the 16S profiles of healthy child and adult GI communities. Between-group differences were evaluated with two-tailed White’s non-parametric t-tests with Storey’s FDR corrections. (XLSX 14.6 kb

Beta diversity metrics of bacterial 16S rRNA genes reveal distinctly clustered vaginal microbiome communities structured by pregnancy.

<p>Datasets were minimally filtered for removal of singletons (left panels) or filtered for chimeras (right panels; QIIME ChimeraSlayer). Beta diversity microbiome community clustering is observed for non-phylogenetic methods ((A) normalized Canberra), binary non-phylogenetic methods ((B) binary Chord, (C) binary Ochiai), and phylogenetic beta diversity metrics ((D) unweighted UniFrac). In each panel, each point corresponds to a vaginal sample from either a pregnant (green) or non-pregnant (blue) subject. The percentage of variation explained by the plotted principal coordinates is indicated on the axes.</p

Measures of within community diversity (alpha diversity) at two levels of data filtering.

<p>Black lines indicate pregnant cohort, with red lines indicating non-pregnant cohort. Data sets were subjected AbundantOTU (left panels), or denoising and chimera slaying with removal of singletons and chimeras (right panels). (A) Rarefaction alpha diversity metrics note significantly lower richness in the pregnant data set, while (B) Renyi alpha diversity metrics indicates significantly less diversity among pregnant vaginal communities following denoising. Significance is denoted by the absence of curves crossing over at any point following denoising and chimera slaying (right panels).</p

Subclassification of microbial community structure by vaginal subsite and week of gestation.

<p>(A) Pregnancy clusters vaginal microbial communities, while site of vaginal sampling minimally contributes to within cluster formation. Canberra beta diversity metric with PCoA plot clustering. Each dots represents one sample from the distinct vaginal subsites (mid vagina, posterior fornix, and vaginal introitus) of individual subjects from pregnant (green shades) and non-pregnant (blue and purple shades). (B) Among gravid subjects, microbial community richness and diversity (Shannon indices) vary by week of gestation and proximity to the uterus. Community richness and Shannon diversity indices by gestational age and vaginal sampling site against normalized abundance values from both OTU and phylogeny based analysis charted by vaginal site (posterior fornix, mid vagina, introitus) and gestational age. Richness - Black; Diversity – Dark Red; Left panel designates OTU based; Right panel designates Phylogeny based. Gestational age interval shown in weeks, or designated as non-pregnant (NP). Error bars denote variance (standard error of the mean, s.e.m.). In each of the gestational age intervals, an equivalent number of gravidae were sampled and compared (n = 6 per strata).</p

V5V3 Sequence Metrics.

<p>Sequence metrics for the pregnant (gravidae), non-pregnant, and combined cohorts. Pregnant subject’s samples were of comparable average sequence length, but retained a higher average number of sequence reads per sample.</p

Additional file 7: Figure S2. of Structure and function of the healthy pre-adolescent pediatric gut microbiome

Evaluating the effects of known traits on community structure and function in children and adults. PCoA of the GI microbial communities of healthy children and adults as a function of Bray-Curtis dissimilarities and 16S-based OTUs (A–D), WGS-based species (E–H), KO groups (I–L), and KEGG pathway profiles (M–P). Profiles were evaluated with respect to known traits, and the percent variation explained by each axis is indicated in parenthesis. Adonis analysis results describe the significance of each trait to overall community variation. (TIF 752 kb

Subject Characteristics and Pregnancy Outcomes.

<p>Characteristics of both pregnant (gravidae) and non-pregnant subject cohorts, alongside pregnancy outcomes of the gravid cohort. GDMA1, gestational diabetes mellitus White classification A1 (diet controlled). There were no significant differences with respect to Race/Ethnicity among gravidae and non-pregnant subjects (p>0.05 by independent samples t-test and ANOVA).</p