Immunohistochemical Study of Vestibular Gingival Blood Vessel Density and Internal Circumference in Smokers and Non‐Smokers
Bibliographic record
Abstract
BACKGROUND: This study was undertaken to determine: 1) if sections stained with monoclonal antibody to CD34 can be used for measurement of gingival blood vessel density and circumference and 2) if long-term smoking affects either of these 2 parameters. METHODS: Vestibular gingival biopsy samples were obtained from 17 adults (5 smokers and 12 non-smokers) who were undergoing routine periodontal surgery independently of this study. Hematoxylin and eosin staining was used for histological assessment of inflammation, while immunohistochemical staining with CD34 mouse monoclonal antibody was used to mark the endothelial cells of the blood vessels within each sample. Stringent selection criteria were applied to the 17 biopsy samples, and 7 (from 3 smokers and 4 non-smokers) were chosen to have their vascular density (number of vessels/unit area) and internal vessel circumference (IC) measured under a blinded protocol. RESULTS: Repeated measurements of vascular density and internal circumference showed small standard deviations, indicating the high reproducibility of the measurement technique. The smoker group showed a higher proportion of small (IC < 50 microns) and a lower proportion of large blood vessels (IC > 100 microns), which was statistically significant (P = 0.0403 and P < 0.001, respectively). The difference between the vascular density of smokers and non-smokers was not significant (P = 0.092). CONCLUSIONS: The present study indicates that the CD34 immunohistochemical staining technique is a simple and reproducible method for the measurement of density and internal circumference of gingival blood vessels. Based on this technique, cigarette smokers show a higher percentage of smaller blood vessels and a lower percentage of larger vessels, but similar vascular density, to non-smokers.
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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 | 0.001 | 0.000 |
| 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) | 0.001 | 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".