Modulating the sEH/EETs Axis Restrains Specialized Proresolving Mediator Impairment and Regulates T Cell Imbalance in Experimental Periodontitis
Bibliographic record
Abstract
Epoxyeicosatrienoic acids (EETs) and other epoxy fatty acids are short-acting lipids involved in resolution of inflammation. Their short half-life, due to its metabolism by soluble epoxide hydrolase (sEH), limits their effects. Specialized proresolving mediators (SPMs) are endogenous regulatory lipids insufficiently synthesized in uncontrolled and chronic inflammation. Using an experimental periodontitis model, we pharmacologically inhibited sEH, examining its impact on T cell activation and systemic SPM production. In humans, we analyzed sEH in the gingival tissue of periodontitis patients. Mice were treated with sEH inhibitor (sEHi) and/or EETs before ligature placement and treated for 14 d. Bone parameters were assessed by microcomputed tomography and methylene blue staining. Blood plasma metabololipidomics were carried out to quantify SPM levels. We also determined T cell activation by reverse transcription-quantitative PCR and flow cytometry in cervical lymph nodes. Human gingival samples were collected to analyze sEH using ELISA and electrophoresis. Data reveal that pharmacological sEHi abrogated bone resorption and preserved bone architecture. Metabololipidomics revealed that sEHi enhances lipoxin A4, lipoxin B4, resolvin E2, and resolvin D6. An increased percentage of regulatory T cells over Th17 was noted in sEHi-treated mice. Lastly, inflamed human gingival tissues presented higher levels and expression of sEH than did healthy gingivae, being positively correlated with periodontitis severity. Our findings indicate that sEHi preserves bone architecture and stimulates SPM production, associated with regulatory actions on T cells favoring resolution of inflammation. Because sEH is enhanced in human gingivae from patients with periodontitis and connected with disease severity, inhibition may prove to be an attractive target for managing osteolytic inflammatory diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".