Methotrexate-loaded glass ionomer cements for drug release in the skeleton: An examination of composition–property relationships
Bibliographic record
Abstract
Chemotherapeutic-loaded bone cement may be an effective method of drug delivery for the management of cancer-related vertebral fractures that require cement injection for pain relief. Recent advancements in the development of aluminum-free glass ionomer cements (GICs) have rendered this class of biomaterials clinically viable for such applications. To expand the therapeutic benefits of these materials, this study examined, for the first time, their drug delivery potential. Through incrementally loading the GIC with methotrexate (MTX) by up to 10-wt%, composition-property relationships were established, correlating MTX loading with working time and setting time, as well as compressive strength, drug release, and cytotoxic effect over 31 days. The most significant finding of this study was that MTX was readily released from the GIC, while maintaining cytotoxic activity. Release correlated linearly with initial loading and appeared to be diffusion mediated, delivering a total of 1-2% of the incorporated drug. MTX loading in this range exerted minimal effects to handling and strength, indicating the clinical utility of the material was not compromised by MTX loading. The MTX-GIC systems examined herein are promising materials for combined structural delivery applications.
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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 | 0.001 |
| 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) | 0.001 | 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".