Invited review: Mastitis Escherichia coli strains—Mastitis-associated or mammo-pathogenic?
Bibliographic record
Abstract
Bovine mastitis remains a major concern for dairy farmers, mainly because of its effect on the economy of their activity and on animal welfare. Because Escherichia coli is considered a major mastitis pathogen, the diversity of E. coli strains isolated from mastitis cases has been studied for decades, with the aim to discover new ways to fight this infection. With the recent advances in whole-genome sequencing, a detailed view of the peculiarities of mastitis E. coli strains has emerged. This review aims to bring together the knowledge garnered over the years with the more recent results of whole-genome analyses. Whereas the concept of a mammary pathogenic E. coli has been proposed, because a common set of virulence genes cannot be identified among mastitis E. coli strains, we prefer the use of mastitis-associated E. coli (MAEC), with MAEC being more an "ecotype" rather than a "pathotype." Indeed, data available so far suggest that a common feature of MAEC would rather be an enrichment in fitness capabilities that makes them well-suited for survival and rapid adaptation to changing biotopes in the mammary gland, which we qualify as intramammary ecotopes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".