Modulating the Effects of Diabetes on Osseointegration With Aminoguanidine and Doxycycline
Bibliographic record
Abstract
BACKGROUND: The current knowledge of wound healing around implant surfaces is quite limited, particularly as it relates to the effects of systemic diseases such as diabetes. The purpose of our research is to histologically evaluate the effects of aminoguanidine and doxycycline in the modification of peri-implant wound healing around endosseous implants in diabetic rats. METHODS: Thirty-two Sprague-Dawley rats were randomly assigned to four different treatment groups. One group served as the non-diabetic control, while diabetes was induced in other groups. Titanium plasma-sprayed (TPS) implants were placed in the femora of each animal 2 weeks following diabetic induction. One group of diabetic rats was given aminoguanidine via intraperitoneal injection, and another given doxycycline via oral gavage for 28 days beginning on the day of implantation. The third group of diabetic rats received no medication (controls). All animals were sacrificed following 28 days of healing. RESULTS: The results were measured by marrow bone-to implant contact (MBIC) between the groups. Values for MBIC were greater for the non-diabetic control group than the diabetic control group (P < 0.001). Aminoguanidine-treated diabetic animals had a significantly greater MBIC than the diabetic control group (P < 0.01). Diabetic animals receiving doxycycline did not differ significantly from the diabetic control group (P > 0.05). CONCLUSIONS: The results of this study using a rat model con- firm previous reports that diabetes inhibits osseointegration, as defined by MBIC. In addition, this study demonstrates that the detrimental effects of diabetes on osseointegration can be modified using aminoguanidine systemically. However, systemic administration of doxycycline only slightly enhances osseointegration.
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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) | 0.000 | 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) | 0.000 | 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".