The Effects of Exenatide Microsphere on Serum <scp>BGP</scp> and <scp>ALP</scp> Levels in <scp>ZDF</scp> Rats after Implantation
Bibliographic record
Abstract
PURPOSE: The aim of this project is to investigate the impact of diabetes mellitus and different glycemic control times on early osseointegration of dental implants by expression and significance of serum bone Gla protein (BGP) and alkaline phosphatase (ALP) levels in Zucker diabetic fatty (ZDF) rats after implantation. MATERIALS AND METHODS: The animals were divided into three groups, each group with 11 rats and each rat with two dental implants (33 rats and 66 implants in total): group A, diabetic rats with dental implants (controls); group B, diabetic rats treated with insulin and implants placed simultaneously; and group C, diabetic rats treated with insulin until serum glucose at a constant level and then implants be placed. Levels of BGP and ALP in the serum were measured by enzyme-linked immunosorbent assay in each group. The software program SPSS (version 17.0 for Windows) was used to analyze all data; p < .05 was set as the level of statistical significance. RESULTS: At the 7th day, serum levels of BGP in group B and C were lower than that in group A (p > 0.05). At the 14th day, serum levels of BGP in group C were significantly higher (p < 0.05). After 30 days, compared with group A, the serum levels of BGP in group B and C seems to be lower. Compared with group A, the serum levels of ALP in group B and C were significantly higher, whereas the serum levels of ALP in group C seems to be higher than B (p < 0.05). CONCLUSIONS: The present results suggest that injection of delayed release microsphere of exenatide on ZDF rats can release exenatide at a steady rate and the blood glucose can be controlled at a constant level. Implant survival rates could be enhanced in DM subjects when blood plasma glucose level is under control; the serum levels of BGP in this study seems to have no relationship with local osseointegration, whereas the serum levels of ALP might offer insights into the activity of osseointegration around the implant surface.
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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 | 0.000 | 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 | 0.001 |
| 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".