757 Associations between gut, mammary and vaginal microbiomes in dairy cows: Role in health and disease
Bibliographic record
Abstract
The crucial role of rumen and hindgut microbiomes in intestinal and extra-intestinal diseases is emerging. Both rumen and hindgut microbiomes have been shown to impact host physiology, metabolism, and immune function and to confer direct and indirect (immune-mediated) resistance against enteric pathogens. Disruption of rumen and hindgut microbiomes or dysbiosis – which is referred to as an abnormal balance of beneficial and protective versus opportunistic members of microbiota – have been linked to a number of metabolic disorders that occur around early to mid-lactation periods, such as acute and subacute ruminal acidosis, milk fat depression, and bloat. Dysbiosis of the gut microbiome impacts the profile of microbially-driven metabolites and compounds produced by the microbiota. These molecules influence the metabolic and immunological capacities of the host both within and outside of the gut, e.g. through the enterohepatic pathway or the gut-brain axis, which retroactively impacts the diversity and behaviour of the microbiome in the digestive tract, and also potentially influences the microbiomes of other body sites, such as vaginal tract or mammary gland resulting in initiation or progression of infectious or inflammatory diseases in those systems, e.g. mastitis. The research by our group and others shows that interactions among commensal members inhabiting different ecological niches of the udder (i.e. teat apex, teat canal, and milk) are crucial for shaping the composition and functional properties of the mammary gland microbiome, and potentially govern the susceptibility of dairy cows to infectious mastitis. Similarly, a healthy vaginal microbiome has a key role in improving ruminants' reproductive performance and preventing infectious diseases. It is thus speculated that nutritional and physiological stressors at early lactation, which are one of the significant underpinnings of the microbiome-gut-brain axis, not only impact the diversity and behavior of the gastrointestinal tract microbiome but also the vaginal and mammary gland microbiomes and thus susceptibility to infectious diseases. In this presentation, I will review the role of rumen and hindgut microbiomes in the context of their association with vaginal tract and mammary microbiomes in dairy cows subjected to subacute ruminal acidosis during early lactation. I will also highlight the pressing need for development of synthetic microbial communities to improve gut, mammary and vaginal health and production efficiency of ruminant animals.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".