Maintenance of Osseointegration Utilizing Insulin Therapy in a Diabetic Rat Model
Bibliographic record
Abstract
BACKGROUND: Normal wound healing processes have been shown to be altered in diabetes, and the effect of the diabetes on bone-to-implant contact (BIC) once osseointegration has been established is still unknown. The purpose of this study was to histologically evaluate the bone-to-implant contact in uncontrolled and insulin-controlled rats in which diabetes was induced following the establishment of osseointegration. METHODS: Thirty-two rats were assigned to eight different treatment groups of four each. Titanium plasma-sprayed (TPS) implants were placed in the femora of each animal, and allowed to osseointegrate for 28 days before diabetic induction. Daily insulin injections were given to four groups of rats and the other four groups received no insulin (uncontrolled). The rats were sacrificed at 1, 2, 3, and 4 months following diabetic induction. RESULTS: The results indicated that at 1, 2, 3, and 4 months, there was more BIC in the insulin-controlled groups compared to the uncontrolled groups. The differences were significantly greater at 2, 3, and 4 months (P < or =0.001). CONCLUSIONS: This study demonstrated that osseointegrated dental implants in insulin-controlled diabetic rats maintained bone-to-implant contacts over a 4-month period. However, boneto- implant contact appears to decrease with time in uncontrolled diabetic rats.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".