Artificial sweetener consumption differentially affects the gut microbiota‐host metabolic interactions
Bibliographic record
Abstract
While there is general agreement on the safety and potential uses of artificial sweeteners, the literature is still lacking a consensus on their long‐term effects on gut microbiota and host‐microbe interactions. To this end, we examined the impact of chronic sweetener consumption on the gut microbiome in lean and diet‐induced obese rats. Male Sprague‐Dawley rats (n=40) were randomized into two dietary groups; chow (CH, 12% kcal fat) and high fat (HF, 60% kcal fat). Each dietary group was further divided into groups consuming water or artificially sweetened water (0.4g/100mL EQUAL®, aspartame) for 8wk (n=10/treatment). Animals consumed food and fluids ad libitum. CH and HF animals showed a difference in weight gain and body fat, with the HF rats becoming obese and glucose intolerant (OGTT). Analysis of insulin tolerance (ITT) demonstrated sweetener consumption to reduce insulin sensitivity in both CH and HF. Analysis of the gut microbiome showed marked differences between both diet and fluid treatment. Total Eubacteria was reduced by HF, but maintained with sweetener consumption. Reductions in Lactobacillus were observed in CH sweetener and both HF groups. Bacteroides was reduced in both HF groups but not CH sweetener compared to water controls. In conclusion, results show sweetener to alter host‐microbe interactions in both chow and diet‐induced obese animals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".