MicroRNA miR-223 modulates NLRP3 and Keap1, mitigating lipopolysaccharide-induced inflammation and oxidative stress in bovine mammary epithelial cells and murine mammary glands
Why this work is in the frame
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Bibliographic record
Abstract
Bovine mastitis, the most prevalent and costly disease in dairy cows worldwide, decreases milk quality and quantity, and increases cow culling. However, involvement of microRNAs (miRNAs) in mastitis is not well characterized. The objective was to determine the role of microRNA-223 (miR-223) in regulation of the nucleotide-binding oligomerization domain-like receptor containing pyrin domain 3 (NLRP3) inflammasome and kelch like ECH-associated protein 1 (Keap1)/nuclear factor erythroid 2-related factor 2 (Nrf2) oxidative stress pathway in mastitis models induced by lipopolysaccharide (LPS) treatment of immortalized bovine mammary epithelial cells (bMECs) and murine mammary glands. In bMECs cultured in vitro, LPS-induced inflammation downregulated bta-miR-223; the latter interacted directly with the 3' untranslated region (3' UTR) of NLRP3 and Keap1. Overexpression of bta-miR-223 in bMECs decreased LPS and Adenosine 5'-triphosphate (ATP)-induced NLRP3 and its mediation of caspase 1 and IL-1β, and inhibited LPS-induced Keap1 and Nrf2 mediated oxidative stress, whereas inhibition of bta-miR-223 had opposite effects. In an in vivo murine model of LPS-induced mastitis, increased miR-223 mitigated pathology in the murine mammary gland, whereas decreased miR-223 increased inflammatory changes and oxidative stress. In conclusion, bta-miR-223 mitigated inflammation and oxidative injury by downregulating the NLRP3 inflammasome and Keap1/Nrf2 signaling pathway. This study implicated bta-miR-223 in regulation of inflammatory responses, with potential as a novel target for treating bovine mastitis and other diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 it