Prevotella in Pigs: The Positive and Negative Associations with Production and Health
Bibliographic record
Abstract
A diverse and dynamic microbial community (known as microbiota) resides within the pig gastrointestinal tract (GIT). The microbiota contributes to host health and performance by mediating nutrient metabolism, stimulating the immune system, and providing colonization resistance against pathogens. Manipulation of gut microbiota to enhance growth performance and disease resilience in pigs has recently become an active area of research in an era defined by increasing scrutiny of antimicrobial use in swine production. In order to develop microbiota-targeted strategies, or to identify potential next-generation probiotic strains originating from the endogenous members of GIT microbiota in pigs, it is necessary to understand the role of key commensal members in host health. Many, though not all, correlative studies have associated members of the genus Prevotella with positive outcomes in pig production, including growth performance and immune response; therefore, a comprehensive review of the genus in the context of pig production is needed. In the present review, we summarize the current state of knowledge about the genus Prevotella in the intestinal microbial community of pigs, including relevant information from other animal species that provide mechanistic insights, and identify gaps in knowledge that must be addressed before development of Prevotella species as next-generation probiotics can be supported.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".