Expression of ICAM‐1 and E‐selectin in gingival tissues of smokers and non‐smokers with periodontitis
Bibliographic record
Abstract
BACKGROUND: Tobacco smoking affects systemic concentrations of soluble intercellular adhesion molecule (ICAM)-1, but its effect on local expression of adhesion molecules in gingival tissue has not been studied previously. METHODS: E-selectin and ICAM-1 expression on small blood vessel endothelia in gingival biopsies obtained from smokers (n=17) and non-smokers (n=17) with periodontitis was examined with immunohistochemistry. Blood vessels were identified with monoclonal antibody for von Willebrand's factor. RESULTS: A significantly larger number of vessels were observed in inflamed tissues of non-smokers than smokers (P<0.05). The number and proportion of vessels expressing both ICAM-1 and E-selectin was greater in sites with inflammation compared to non-inflamed sites in both smokers and non-smokers (P<0.05). The proportion of the total number of vessels expressing ICAM-1 in non-inflamed sites was greater in non-smokers compared with smokers (P<0.05). CONCLUSIONS: These results suggest that the inflammatory response in smokers with periodontitis may not be accompanied by an equivalent increase in vascularity. Reduced ICAM-1 expression in non-inflamed areas of smokers could reflect a systemic effect of tobacco smoking on ICAM-1 independent of inflammation.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".