The Nasopharyngeal, Ruminal, and Vaginal Microbiota and the Core Taxa Shared across These Microbiomes in Virgin Yearling Heifers Exposed to Divergent In Utero Nutrition during Their First Trimester of Gestation and in Pregnant Beef Heifers in Response to Mineral Supplementation
Bibliographic record
Abstract
In the present study, we evaluated whether the nasopharyngeal, ruminal, and vaginal microbiota would diverge (1) in virgin yearling beef heifers (9 months old) due to the maternal restricted gain during the first trimester of gestation; and (2) in pregnant beef heifers in response to the vitamin and mineral (VTM) supplementation during the first 6 months of pregnancy. As a secondary objective, using the microbiota data obtained from these two cohorts of beef heifers managed at the same location and sampled at the same time, we performed a holistic assessment of the microbial ecology residing within the respiratory, gastrointestinal, and reproductive tract of cattle. Our 16S rRNA gene sequencing results revealed that both α and β-diversity of the nasopharyngeal, ruminal and vaginal microbiota did not differ between virgin heifers raised from dams exposed to either a low gain (targeted average daily gain of 0.28 kg/d, n = 22) or a moderate gain treatment (0.79 kg/d, n = 23) during the first 84 days of gestation. Only in the vaginal microbiota were there relatively abundant genera that were affected by maternal rate of gain during early gestation. Whilst there was no significant difference in community structure and diversity in any of the three microbiota between pregnant heifers received no VTM (n = 15) and VTM supplemented (n = 17) diets, the VTM supplementation resulted in subtle compositional alterations in the nasopharyngeal and ruminal microbiota. Although the nasopharyngeal, ruminal, and vaginal microbiota were clearly distinct, a total of 41 OTUs, including methanogenic archaea, were identified as core taxa shared across the respiratory, gastrointestinal, and reproductive tracts of both virgin and pregnant heifers.
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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 | 0.000 | 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 | 0.000 |
| 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".