Whole Cigarette Smoke Increased the Expression of TLRs, HBDs, and Proinflammory Cytokines by Human Gingival Epithelial Cells through Different Signaling Pathways
Bibliographic record
Abstract
The gingival epithelium is becoming known as a regulator of the oral innate immune responses to a variety of insults such as bacteria and chemicals, including those chemicals found in cigarette smoke. We investigated the effects of whole cigarette smoke on cell-surface-expressed Toll-like receptors (TLR)-2, -4 and -6, human β-defensin (HBD) and proinflammatory cytokine expression and production in primary human gingival epithelial cells. Whole cigarette smoke was shown to increase TLR2, TLR4 and TLR6 expression. Cigarette smoke led to ERK1/2, p38 and JNK phosphorylation in conjunction with nuclear factor-κB (NFκB) translocation into the nucleus. TLR expression following cigarette smoke exposure was down regulated by the use of ERK1/2, p38, JNK MAP kinases, and NFκB inhibitors, suggesting the involvement of these signaling pathways in the cellular response against cigarette smoke. Cigarette smoke also promoted HBD2, HBD3, IL-1β, and IL-6 expression through the ERK1/2 and NFκB pathways. Interestingly, the modulation of TLR, HBD, and cytokine expression was maintained long after the gingival epithelial cells were exposed to smoke. By promoting TLR, HBDs, and proinflammatory cytokine expression and production, cigarette smoke may contribute to innate immunity dysregulation, which may have a negative effect on human health.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".