Low-Dose Stevia (Rebaudioside A) Consumption Perturbs Gut Microbiota and the Mesolimbic Dopamine Reward System
Bibliographic record
Abstract
Stevia is a natural low-calorie sweetener that is growing in popularity in food and beverage products. Despite its widespread use, little is understood of its impact on the gut microbiota, an important environmental factor that can mediate metabolism and subsequent obesity and disease risk. Furthermore, given previous reports of dysbiosis with some artificial low-calorie sweeteners, we wanted to understand whether prebiotic consumption could rescue potential stevia-mediated changes in gut microbiota. Three-week old male Sprague–Dawley rats were randomized to consume: (1) Water (CTR); (2) Rebaudioside A (STV); (3) prebiotic (PRE); (4) Rebaudioside A + prebiotic (SP) (n = 8/group) for 9 weeks. Rebaudioside was added to drinking water and prebiotic oligofructose-enriched inulin added to control diet (10%). Body weight and feces were collected weekly and food and fluid intake biweekly. Oral glucose and insulin tolerance tests, gut permeability tests, dual X-ray absorptiometry, and tissue harvest were performed at age 12 weeks. Rebaudioside A consumption alone did not alter weight gain or glucose tolerance compared to CTR. Rebaudioside A did, however, alter gut microbiota composition and reduce nucleus accumbens tyrosine hydroxylase and dopamine transporter mRNA levels compared to CTR. Prebiotic animals, alone or with Rebaudioside A, had reduced fat mass, food intake, and gut permeability and cecal SCFA concentration. Adding Rebaudioside A did not interfere with the benefits of the prebiotic except for a significant reduction in cecal weight. Long-term low-dose Rebaudioside A consumption had little effect on glucose metabolism and weight gain; however, its impact on gut microbial taxa should be further examined in populations exhibiting dysbiosis such as obesity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".