Insights in the Development and Uses of Alternatives to Antibiotic Growth Promoters in Poultry and Swine Production
Bibliographic record
Abstract
The overuse and misuse of antibiotics has contributed to the rise and spread of multidrug-resistant bacteria. To address this global public health threat, many countries have restricted the use of antibiotics as growth promoters and promoted the development of alternatives to antibiotics in human and veterinary medicine and animal farming. In food-animal production, acidifiers, bacteriophages, enzymes, phytochemicals, probiotics, prebiotics, and antimicrobial peptides have shown hallmarks as alternatives to antibiotics. This review reports the current state of these alternatives as growth-promoting factors for poultry and swine production and describes their mode of action. Recent findings on their usefulness and the factors that presently hinder their broader use in animal food production are identified by SWOT (strength, weakness, opportunity, and threat) analysis. The potential for resistance development as well as co- and cross-resistance with currently used antibiotics is also discussed. Using predetermined keywords, we searched specialized databases including Scopus, Web of Science, and Google Scholar. Antibiotic resistance cannot be stopped, but its spreading can certainly be hindered or delayed with the development of more alternatives with innovative modes of action and a wise and careful use of antimicrobials in a One Health approach.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".