Non-therapeutic administration of a model antimicrobial growth promoter modulates intestinal immune responses
Bibliographic record
Abstract
BACKGROUND: The development of efficacious alternatives to antimicrobial growth promoters (AGP) in livestock production is an urgent issue, but is hampered by a lack of knowledge regarding the mode of action of AGP. The belief that AGP modulate the intestinal microbiota has become prominent in the literature; however, there is a lack of experimental evidence to support this hypothesis. Using a chlortetracycline-murine-Citrobacter rodentium model, the ability of AGP to modulate the intestinal immune system in mammals was investigated. RESULTS: C. rodentium was transformed with the tetracycline resistance gene, tetO, and continuous oral administration of a non-therapeutic dose of chlortetracycline to mice did not affect densities of C. rodentium CFU in feces throughout the experiment or associated with mucosal surfaces in the colon (i.e. at peak and late infection). However, chlortetracycline regulated transcription levels of Th1 and Th17 inflammatory cytokines in a temporal manner in C. rodentium-inoculated mice, and ameliorated weight loss associated with infection. In mice inoculated with C. rodentium, those that received chlortetracycline had less pathologic changes in the distal colon than mice not administered CTC (i.e. relative to untreated mice). Furthermore, chlortetracycline administration at a non-therapeutic dose did not impart either prominent or consistent effects on the colonic microbiota. CONCLUSION: Data support the hypothesis that AGP function by modulating the intestinal immune system in mammals. This finding may facilitate the development of biorationale-based and efficacious alternatives to AGP.
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 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) | 0.000 | 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 | 0.001 |
| 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 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".