Pro-Resolving Effects of Resolvin D2 in LTD4 and TNF-α Pre-Treated Human Bronchi
Bibliographic record
Abstract
Inflammation is a major burden in respiratory diseases, resulting in airway hyperresponsiveness. Our hypothesis is that resolution of inflammation may represent a long-term solution in preventing human bronchial dysfunctions. The aim of the present study was to assess the anti-inflammatory effects of RvD2, a member of the D-series resolving family, with concomitant effects on ASM mechanical reactivity. The role and mode of action of RvD2 were assessed in an in vitro model of human bronchi under pro-inflammatory conditions, induced either by 1 μM LTD4 or 10 ng/ml TNF-α pre-treatment for 48h. TNF-α and LTD4 both induced hyperreactivity in response to pharmacological stimuli. Enhanced 5-Lipoxygenase (5-LOX) and cysteinyl leukotriene receptor 1 (CysLTR1) detection was documented in LTD4 or TNF-α pre-treated human bronchi when compared to control (untreated) human bronchi. In contrast, RvD2 treatments reversed 5-LOX/β-actin and CysLTR1/β-actin ratios and decreased the phosphorylation levels of AP-1 subunits (c-Fos, c-Jun) and p38-MAP kinase, while increasing the detection of the ALX/FPR2 receptor. Moreover, various pharmacological agents revealed the blunting effects of RvD2 on LTD4 or TNF-α induced hyper-responsiveness. Combined treatment with 300 nM RvD2 and 1 μM WRW4 (an ALX/FPR2 receptor inhibitor) blunted the pro-resolving and broncho-modulatory effects of RvD2. The present data provide new evidence regarding the role of RvD2 in a human model of airway inflammation and hyperrresponsiveness.
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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 | 0.000 |
| 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".