Prevention of the neutrophil-induced mammary epithelial damage during bovine mastitis
Bibliographic record
Abstract
Reduction of milk production following acute bovine mastitis causes important economic losses. In this study, two experiments were conducted to asses the ability of different antioxidants to prevent neutrophil (PMN)-induced mammary damage in acute bovine mastitis. First, a co-culture model composed of bovine mammary epithelial cell line (MAC-T cells) and bovine PMN activated by phorbol myristate acetate was used. Activated PMN release reactive oxygen species that are cytotoxic for bovine epithelial cells. Addition of dimethylthiourea or bathocuproinic acid did not induce any protective effect. On the other hand, addition of catechin, deferoxamine or glutathione ethyl ester (GEE) significantly reduced PMN-induced cytotoxicity in a dose-dependent manner as demonstrated by lower levels of released lactate dehydrogenase (LDH). The second experiment was undertaken with the last three antioxidants to evaluate their protective effects in vivo. A model of LPS-induced mastitis on dairy cows was used. The extent of cell damages was evaluated by measuring quarter milk levels of LDH and 4-methylumbelliferyl N-acetyl beta-D-glucosaminidase ( NAGase) at varying intervals before and after intramammary infusions of LPS, with or without antioxidants. Milk levels of haptoglobin and bovine serum albumin were also analysed. Catechin and GEE did not induce any protective effect whereas infusions of deferoxamine, a chelator of iron, decreased milk levels of LDH, NAGase and haptoglobin hence suggesting a protective effect against PMN-induced damage. Deferoxamine did not interfere with PMN migration into the mammary gland. Additionally, deferoxamine inhibited bacterial growth in vitro but did not affect PMN's ability to phagocytize live Escherichia coli. Overall, our results suggest that local infusion of deferoxamine may be an effective tool to protect mammary tissue against PMN-induced oxidative stress during bovine mastitis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".