Oral challenge with increasing doses of LPS modulated the patterns of plasma metabolites and minerals in periparturient dairy cows
Bibliographic record
Abstract
We showed recently that repeated oral exposure to LPS stimulated humoral immune responses in periparturient dairy cows. Here, metabolic and mineral responses to repeated oral administration of LPS were investigated. Sixteen clinically healthy, pregnant Holstein cows were orally administered 3 ml of saline solution (control) or 3 ml of saline solution containing 3 increasing doses of LPS, at 07:00 h, as follows: (i) 0.01 µg/kg body mass (BM) on d -14 and -10, (ii) 0.05 µg/kg BM on d -7 and -3, and (iii) 0.1 µg/kg BM on d 3 and 7 relative to parturition. Blood samples were measured shortly before, and at 8 different time-points after (up to 6 h), the first challenge of each LPS dosage to evaluate the post-challenge plasma profile, as well as weekly up to 4 wk postpartum. Results showed that oral administration of LPS lowered concentrations of non-esterified fatty acids (P < 0.01) and β-hydroxy-butyrate (P < 0.01) in the plasma, particularly after the third LPS challenge. Also, after the third oral LPS challenge, treatment tended to increase plasma glucose. Plasma calcium did not change, but concentrations of insulin (P < 0.01) and zinc (P < 0.01) were greater, while that of copper was lower (P < 0.01) in the plasma of treated cows. This is the first report to indicate a potential role for repeated oral administration of LPS around parturition to modulate the profile of plasma metabolites and minerals postpartum.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".