Randomized Open-Label Pilot Study of the Influence of Probiotics and the Gut Microbiome on Toxic Metal Levels in Tanzanian Pregnant Women and School Children
Bibliographic record
Abstract
Exposure to environmental toxins is a 21st century global health problem that is often the result of dietary intake. Although efforts are made to reduce dietary toxin levels, they are often unsuccessful, warranting research into novel methods to reduce host exposure. Food-grade microbes that can be delivered to the gastrointestinal tract and that are capable of sequestering toxins present a safe and cost-effective intervention. We sought to investigate the potential for probiotic-supplemented yogurt to lower heavy metal levels in at-risk populations of pregnant women and in children in Mwanza, Tanzania, and to examine the microbiome in relation to toxin levels. Two populations suspected to have high toxic metal exposures were studied. A group of 44 school-aged children was followed over 25 days, and 60 pregnant women were followed over their last two trimesters until birth. A yogurt containing 10(10) CFU Lactobacillus rhamnosus GR-1 per 250 g was administered, while control groups received either whole milk or no intervention. Changes in blood metal levels were assessed, and the gut microbiomes of the children were profiled by analyzing 16S rRNA sequencing via the Ion Torrent platform. The children and pregnant women in the study were found to have elevated blood levels of lead and mercury compared to age- and sex-matched Canadians. Consumption of probiotic yogurt had a protective effect against further increases in mercury (3.2 nmol/liter; P = 0.035) and arsenic (2.3 nmol/liter; P = 0.011) blood levels in the pregnant women, but this trend was not statistically significant in the children. Elevated blood lead was associated with increases in Succinivibrionaceae and Gammaproteobacteria relative abundance levels in stool. Importance: Probiotic food produced locally represents a nutritious and affordable means for people in some developing countries to counter exposures to toxic metals. Further research and field trials are warranted to explore this approach in countries where communities are located near mining sites and agricultural areas, two types of areas where toxins are likely to be elevated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".