Phytonutrient diet supplementation promotes beneficial Clostridia species and intestinal mucus secretion resulting in protection against enteric infection
Bibliographic record
Abstract
Plant extracts, or phytonutrients, are used in traditional medicine practices as supplements to enhance the immune system and gain resistance to various infectious diseases and are used in animal production as health promoting feed additives. To date, there are no studies that have assessed their mechanism of action and ability to alter mucosal immune responses in the intestine. We characterized the immunomodulatory function of six phytonutrients: anethol, carvacrol, cinnamaldehyde, eugenol, capsicum oleoresin and garlic extract. Mice were treated with each phytonutrient to assess changes to colonic gene expression and mucus production. All six phytonutrients showed variable changes in expression of innate immune genes in the colon. However only eugenol stimulated production of the inner mucus layer, a key mucosal barrier to microbes. The mechanism by which eugenol causes mucus layer thickening likely involves microbial stimulation as analysis of the intestinal microbiota composition showed eugenol treatment led to an increase in abundance of specific families within the Clostridiales order. Further, eugenol treatment confers colonization resistance to the enteric pathogen Citrobacter rodentium. These results suggest that eugenol acts to strengthen the mucosal barrier by increasing the thickness of the inner mucus layer, which protects against invading pathogens and disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".