Gene Expression of Inflammation and Bone Healing in Peri‐Implant Crevicular Fluid after Placement and Loading of Dental Implants. A Kinetic Clinical Pilot Study Using Quantitative Real‐Time PCR
Bibliographic record
Abstract
PURPOSE: Early detection of healing complications after placement of dental implants is a pressing but elusive goal. This paper proposes a non-invasive diagnostic tool for monitoring healing- and peri-implant disease specific genes, complementary to clinical evaluations. MATERIAL AND METHODS: Eighteen partially edentulous patients were recruited to this pilot study. Three Brånemark TiUnite® implants/patient (Nobel Biocare) were placed in a one-stage procedure. Abutments with smooth or rough (TiUnite®) surface were placed. The test group (n = 9) received fixed bridges (immediate loading), whereas the control group (n = 9) implants were loaded 3 months after surgery. In addition to clinical measurements, crevicular fluid was collected using paper strips at the implant abutments 2, 14, 28, and 90 days postoperative. mRNA was extracted, purified, and converted to cDNA. Quantitative PCR assays for IL-1β, TNF-α, Osteocalcin (OC), Alkaline Phosphatase (ALP), Cathepsin K, Tartrate Resistant Acid Phosphatase, and 18S ribosomal RNA were designed and validated. Relative gene expression levels were calculated. RESULTS: One implant was lost in the control group and three in the test group. In one test patient, one implant showed lowered stability after 2 to 4 weeks and was unloaded. Later implant stability improved which allowed for loading after 3 to 4 months. TNF-α and ALP most commonly showed correlation with clinical parameters followed by IL-1β and OC. The strongest correlation was found for TNF-α with clinical complications at 2 and 14 days (p = .01/r = -048, and p = .0004/r = -0.56, respectively; test and control groups together). In some cases, gene expression predicted clinical complications (TNF-α, ALP, CK). CONCLUSION: This study is based on samples from few individuals; still, some genes showed correlation with clinical findings. Further studies are needed to refine and optimize the sampling process, to find the appropriate panel, and to validate gene expression for monitoring implant 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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".