Nrf2 and NF-κB/NLRP3 inflammasome pathways are involved in Prototheca bovis infections of mouse mammary gland tissue and mammary epithelial cells
Bibliographic record
Abstract
Prototheca bovis is a serious pathogen for animals, but pathogenesis of P. bovis mastitis is unclear. The objective was to characterize how P. bovis induces inflammatory responses in mouse mammary gland tissue and mammary epithelial cells (mMECs). Prototheca bovis damaged mammary gland tissue and mitochondrial structure, and induced oxidative stress, as evident by significant increases in mtROS and MDA concentrations and significant decreases in T-SOD activity in both mammary gland tissue and mMECs. Expression of Nrf2, HO-1 and Keap1 proteins was significantly changed in mammary gland tissue and mMECs after P. bovis infection. Additionally, cytokines (IL-1β, IL-6 and IL-18) and protein expressions in NF-κB and in the NLRP3 inflammasome pathway were significantly increased in mammary gland tissue and mMECs. In the P. bovis group, treatment with N-acetyl-l-cysteine (NAC) significantly decreased protein expression in NF-κB and the NLRP3 inflammasome pathway, as well as IL-1β, IL-6 and IL-18, whereas protein expression in the Nrf2 pathway was significantly changed. Inhibition of NF-κB or NLRP3 significantly decreased expression of IL-1β and IL-18 proteins in mMECs infected with P. bovis. Additionally, activating Nrf2 inhibited expression of NLRP3 and IL-1β. In conclusion, P. bovis induced an inflammatory response via the NF-κB/NLRP3 inflammasome pathway; however, scavenging ROS or activating Nrf2 mitigated the inflammatory response in infected mMECs.
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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 | 0.001 |
| 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 | 0.001 | 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".