Synthesis, characterisation and performance of calcium phosphate bone graft substitutes
Bibliographic record
Abstract
Synthetic bone graft substitutes are frequently used to fill defects with significant bone loss to prevent fibrous tissue ingrowth and loss of function. Bone grafts are often used to augment deficient alveolar ridges allowing placement of dental implants subsequent to prior bone loss. Although autografts, allografts and xenografts have been used and researched extensively, they have inherent limitations. To overcome these, synthetic alternatives, such as calcium phosphate cement-based biomaterials are being developed. Brushite and monetite are acidic calcium phosphates having similar chemical composition. However, their in vivo behavior differs in terms of resorption and bone response. Although brushite and monetite have been shown to resorb faster in vivo than hydroxyapatite (HA), a significant reduction in the rate of resorption occurs following phase conversion of brushite to insoluble HA. As such differences between bone grafts are attributed to material composition even though physical properties such as surface area and porosity invariably differ. This thesis focuses on determining the factors and mechanisms that makes these chemically similar materials behave differently in vivo. We produced brushite cement grafts and converted them to two types of monetite by using wet (autoclaving) and dry heat (under vacuum) dehydration which resulted in materials with differing physicochemical properties. These grafts were then aged in vitro using bovine serum and phosphate buffered saline (PBS) solutions, implanted subcutaneously, in femoral condyles and onlay grafted on calvaria. The dissolution, resorption and bone formation potential of these dicalcium phosphate cement grafts was assessed and compared. Also, we developed a new alkali ion (sodium and potassium) substituted calcium phosphate cement, reinforced with silica and set using phytic acid. The set cement blocks were aged in PBS solutions and their in vitro dissolution and degradation along with other physico-chemical properties was assessed.Results presented in this Ph.D thesis discuss and shed light on the fundamental yet not understood questions regarding the relative contributions from chemico- vs physico-biomaterial properties in graft resorption and bone regeneration. This will allow in future the preparation of improved calcium phosphate-based bone substitute grafts with potential to achieve higher clinical efficiency.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".