Cigarette Smoke and E-Cigarette Vapor Dysregulate Osteoblast Interaction With Titanium Dental Implant Surface
Bibliographic record
Abstract
The purpose of this study was to determine the possible deleterious effects of e-cigarette vapor on osteoblast interaction with dental implant material. Osteoblasts were cultured onto Ti6Al4V titanium implant disks and were then exposed or not to whole cigarette smoke (CS), as well as to nicotine-rich (NR) or nicotine-free (NF) e-vapor for 15 or 30 minutes once a day for 1, 2, or 3 days, after which time various analyses were performed. Osteoblast growth on the titanium implant disks was found to be significantly ( P < .001) reduced following exposure to CS and to the NR and NF e-vapors. Osteoblast attachment to the dental implant material was also dysregulated by CS and the NR and NF e-vapors through a decreased production of adhesion proteins such as F-actin. The effects of CS and e-cigarette vapor on osteoblast growth and attachment were confirmed by reduced alkaline phosphatase (ALP) activity and tissue mineralization. The adverse effects of CS and the NR and NF e-vapors on osteoblast interaction with dental implant material also involved the caspase-3 pathway, as the caspase-3 protein level increased following exposure of the osteoblasts to CS or e-vapor. It should be noted that the adverse effects of CS on osteoblast growth, attachment, ALP, and mineralized degradation were greater than those of the NR and NF e-vapors, although the latter did downregulate osteoblast interaction with the dental implant material. Overall results suggest the need to consider e-cigarettes as a possible contributor to dental implant failure and/or complications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".