Role of plasma composition on bone healing and implant osseointegration
Bibliographic record
Abstract
Blood plasma plays a key role in bone regeneration, and plasma-derived products such as platelet concentrates (PCs) have been used to enhance bone healing in oral and orthopedic surgeries. In this thesis, we hypothesized that changes in plasma composition affect its ability to regenerate bone. Accordingly, the goal of this thesis was to study how changes in plasma composition affect bone regeneration and implant osseointegration. This manuscript-based dissertation includes four interconnected manuscripts. In the first study (review study), we summarized the clinical research on the effect of PCs on oral and craniofacial regeneration. We concluded that PCs could enhance soft tissue and bone healing, although, these beneficial outcomes are clinically inconsistent. Also, there is a lack of standardized clinical and experimental studies assessing how changes in PC composition affect bone regeneration. In the second study, we assessed how changes in PC composition affect bone healing. We compared PCs with different concentrations of platelets and metabolites in a bone defect rat model. We showed that differences in the composition of PCs, especially the concentration of platelets, affect their ability to regenerate bone. In the third study, we assessed how changes in plasma composition due to aging affect bone regeneration by applying plasma derived from young or old rats in a bone defect model. We showed that plasma composition changes with age and this seems to affect its ability to regenerate bone. Also, we have discovered that plasma aging modifies the proteomes of bone defects. Young plasma upregulated pathways essential for bone healing while old plasma upregulated pathways involved in disease and inflammation. In the fourth study, we assessed how changes in plasma composition due to the short-term administration of donepezil, anti-Alzihmer’s drug known to reduce the plasma concentrations of adrenaline and nor-adrenaline, affect bone healing and implant osseointegration. We have shown that short-term administration of donepezil hindered bone healing and implant osseointegration. In conclusion, this thesis presents fundamental knowledge regarding the effect of changes in plasma composition on bone healing and implant osseointegration. These results could help develop a new biological material with better regenerative potential
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".