In vitro osteogenic performance of two novel strontium and zinc‐containing glass polyalkenoate cements
Bibliographic record
Abstract
Abstract Glass polyalkenoate cements (GPCs) are under investigation as potential bone adhesives, as they may provide an alternative to polymethylmethacrylate‐based cements. GPCs containing strontium (Sr) and zinc (Zn) in place of aluminium (Al) are of particular interest because these ions are known stimulators of osteoprogenitor differentiation. GPCs have been manufactured from a novel bioactive glass (SiO2:0.48, ZnO:0.36, CaO:0.12, SrO:0.04) in the past, but, while such materials have been assessed for their influence on viability, their influence on osteogenic function has not been investigated until now. For this study, two GPCs were formulated from the same glass precursor evaluated in previous studies. These GPCs were named GPC A and GPC B, and they differed in glass particle size, polyacrylic acid molecular weight, and their powder: liquid ratios. The effect of these two GPCs on osteogenic differentiation of primary rat osteoblasts were evaluated using three culture systems: culture with dissolution extracts, indirect contact with transwell‐inserts and direct contact. Additionally, the degradation characteristics of GPCs were assessed, including their interfacial pH and surrounding pH. The experimental outcomes revealed that collagen deposition, alkaline phosphatase expression, and mineralization were largely dependent on GPC composition as well as the mode of interaction with cells. These markers were found to be significantly elevated in response to GPC A's dissolution products. However, osteogenic differentiation was inhibited when osteoblasts were cultured indirectly and directly with GPCs, with, overall, GPC B significantly outperforming GPC A. These results suggest that GPC degradation products effect osteogenic differentiation in a dose‐dependent manner.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".