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

Additional file 6: Table S4A. of Characterization of Lactobacillus salivarius strains B37 and B60 capable of inhibiting IL-8 production in Helicobacter pylori-stimulated gastric epithelial cells

Raw data used to generate Fig. 5 showing the effect of enzyme treatment on LCM of LS-B37; Table S4B Raw data used to generate Fig. 5 showing the effect of enzyme treatment on LCM of LS-B60. (DOCX 21 kb

Additional file 5: Table S3A. of Characterization of Lactobacillus salivarius strains B37 and B60 capable of inhibiting IL-8 production in Helicobacter pylori-stimulated gastric epithelial cells

Raw data used to generate Fig. 4b showing the effect of size fractionation on LCM of LS-B37; Table S3B Raw data used to generate Fig. 4b showing the effect of size fractionation on LCM of LS-B60. (DOCX 21 kb

Longitudinal and site-specific development of the cutaneous microbiome in preterm and term infants.

<p>Observed Operational Taxonomic Units (OTUs) (mean ± SEM) and Shannon diversity index (mean ± SEM) for preterm (Fig 1A and 1B) and term infants (Fig 1C and 1D) are plotted by sampling week and skin site. Term infants were sampled at 2 time points (birth and between 2–3 weeks of age) and preterm infants every week from birth for 5 time-points. For each skin site, the number of OTUs and Shannon diversity index in preterm infants decreased between week 1 and week 2, and then increased over time until week 5. The trend for diversity over time was not significantly different between the three sites in our linear mixed effects model for observed OTUs and Shannon diversity index in preterm infants. Overall, bacterial diversity tended to be higher for term infants compared to preterm infants (p = 0.04 for main effect of term vs. preterm status for Shannon diversity index; p = 0.05 for observed number of OTUs).</p

Gestational age is associated with the skin microbiome (at baseline) in preterm infants.

<p><b>3A. Average Observed OTU:</b> Each dot represents the average number of Operational Taxonomic Units (OTUs) for the subject, across the sites. The average OTU is linearly regressed against gestational age at baseline samples and shaded areas are the 95% confidence intervals for the regression line. Gestational age is significantly associated with average number of OTUs, when both preterm and term infants are considered together (R = 0.39, p = 0.04). <b>3B. Average Shannon diversity index</b>: Each dot represents the average Shannon diversity index for the subject, across the sites. The average Shannon diversity index is linearly regressed against gestational age at baseline samples and shaded areas are the 95% confidence intervals for the regression line. Gestational age is significantly associated with average Shannon diversity index, when both preterm and term infants are considered together (R = 0.49, p < 0.009).</p

Hierarchical clustering for preterm and term infants, based on relative abundance at the genus level.

<p>Each column represents a sample, with darker red indicating higher relative abundance. The top 10 most abundant genera are shown for preterm (2A) and term (2B) infants, separately. The top four rows show metadata for each sample namely use of significant antibiotics, mode of delivery, week of sample collection and sampling site.</p

Characteristics of enrolled patients.

<p>Characteristics of enrolled patients.</p

Postnatal colonization with human "infant-type" <i>Bifidobacterium</i> species alters behavior of adult gnotobiotic mice

<div><p>Accumulating studies have defined a role for the intestinal microbiota in modulation of host behavior. Research using gnotobiotic mice emphasizes that early microbial colonization with a complex microbiota (conventionalization) can rescue some of the behavioral abnormalities observed in mice that grow to adulthood completely devoid of bacteria (germ-free mice). However, the human infant and adult microbiomes vary greatly, and effects of the neonatal microbiome on neurodevelopment are currently not well understood. Microbe-mediated modulation of neural circuit patterning in the brain during neurodevelopment may have significant long-term implications that we are only beginning to appreciate. Modulation of the host central nervous system by the early-life microbiota is predicted to have pervasive and lasting effects on brain function and behavior. We sought to replicate this early microbe-host interaction by colonizing gnotobiotic mice at the neonatal stage with a simplified model of the human infant gut microbiota. This model consortium consisted of four “infant-type” <i>Bifidobacterium</i> species known to be commensal members of the human infant microbiota present in high abundance during postnatal development. Germ-free mice and mice neonatally-colonized with a complex, conventional murine microbiota were used for comparison. Motor and non-motor behaviors of the mice were tested at 6–7 weeks of age, and colonization patterns were characterized by 16S ribosomal RNA gene sequencing. Adult germ-free mice were observed to have abnormal memory, sociability, anxiety-like behaviors, and motor performance. Conventionalization at the neonatal stage rescued these behavioral abnormalities, and mice colonized with <i>Bifidobacterium</i> spp. also exhibited important behavioral differences relative to the germ-free controls. The ability of <i>Bifidobacterium</i> spp. to improve the recognition memory of both male and female germ-free mice was a prominent finding. Together, these data demonstrate that the early-life gut microbiome, and human “infant-type” <i>Bifidobacterium</i> species, affect adult behavior in a strongly sex-dependent manner, and can selectively recapitulate the results observed when mice are colonized with a complex microbiota.</p></div

<i>Bifidobacterium</i> colonization improves motor performance defect of germ-free mice.

<p><b>(A)</b> Plots show the mean latency (±SEM) to fall from the rotating rod over the course of 8 trials (4 trials on day 1, and 4 trials and day 2). Males and females are plotted separately <b>(B)</b> Average latency to fall from the rod (±SEM) averaged over all 8 trials for each group of mice. <b>(C)</b> Plots represent the relative maximum performance of males and females in each treatment group (percentage of mice that were capable of reaching maximum speeds (40 RPM ± 2) on the Rotarod apparatus during each trial). <b>(D)</b> Plot represents the average percentage of mice in each group that reached peak performance over all 8 trials. <b>(E)</b> Weight of male and female mice in each treatment group at time of testing. All data (A-E) are presented as means ± SEM. Significant treatment effects (T), sex effects (S), and interaction between treatment and sex (TxS) as determined by 2-way ANOVA are indicated under the title of each graph. Data are shown as sexes combined and sexes separated in the same graph for visualization purposes. Tests used to determine statistical significance notated in graphs are summarized in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196510#pone.0196510.s001" target="_blank">S1 Table</a>. *<i>p</i> < 0.05 (GF (G) = germ-free, ■ (n = 9m/13f); CONV (C) = conventionalized, ▲ (n = 11m/8f); BIF (B) = <i>Bifidobacterium</i>-colonized, ● (n = 8m/9f)).</p