Effect of Nicotine on Fibroblast β<sub>1</sub> Integrin Expression and Distribution In Vitro
Bibliographic record
Abstract
BACKGROUND: Integrins are a family of transmembrane cell surface glycoproteins, and those with the beta 1-subunit function in both cell-to-cell and cell-to-substrate adhesion. The purpose of this study was to determine nicotine's effect on the expression and distribution of the beta 1 integrin subunit on the human gingival fibroblast cell surface. METHODS: Pure nicotine was diluted in medium to the following concentrations: 0 (control), 0.025, 0.05, 0.1, 0.2, and 0.4 microM. Human gingival fibroblasts (HFG) were grown for 24 hours in each concentration and fluorescein-labeled with a mouse monoclonal anti-human beta 1 antibody and secondarily incubated with a urease-labeled anti-mouse IgG antibody. After a final wash, the cells were incubated with urea/bromcresol blue substrate for 15 minutes at 37 degrees C and measured in a microplate reader at 570 nm. RESULTS: The integrin beta 1-subunit was detected on the HGF surface membrane by fluorescence labeling, and cell-enzyme-linked immunosorbent assay testing demonstrated its decreased expression with increasing nicotine concentrations that were statistically different at the concentrations of 0.2 and 0.4 microM versus controls (P < 0.05). CONCLUSIONS: Nicotine concentrations of 0.2 and 0.4 microM significantly decrease beta 1 integrin expression in human gingival fibroblasts that may affect cell-cell and cell-substratum adhesion during wound healing.
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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 | 0.000 |
| 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".