The Effect of honey consumption on the gut microbiome of Hadza hunter-gatherers in Tanzania
Bibliographic record
Abstract
The Hadza are a hunter-gatherer society who live in northern Tanzania and serve as an excellent model to study the dynamics of the human gut microbiome in a nonindustrial, nonurban setting. Females and males, in the Hadza society, gather different food to provide for their camp. During the wet season, their main food source is honey which is principally foraged by Hadza adult males and is therefore consumed in a higher proportion by men than by women and children. The Hadza microbiome is well studied, but little is known about how honey-associated microbial communities affect the Hadza gut microbiome. Our study investigated if there are differences between the microbial composition of honey in the local Tanzania area and Hadza fecal samples, and how they vary between sexes and life stages. Diversity and differential abundance analysis showed that humans have higher microbial diversity compared to honey samples, and that some components of honey microbial communities are more similar to adult samples than children or infant samples. Additionally, we found that adult males and females have similar gut microbiota, suggesting no honey consumption driven microbiota differences between sexes. We postulate that honey may have a greater effect on Hadza adult microbiomes compared to children and infants, however our results are inconclusive. Our research provides valuable insight into the dynamics of the Hadza gut microbiome with increasing age, as well as the effect of diet on the microbiome.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".