A Gallium-doped cement for the treatment of bone cancers. The effect of ZnO ↔ Ga<sub>2</sub>O<sub>3</sub> substitution of an ionomeric glass series on the rheological, mechanical, pH and ion-eluting properties of their corresponding glass polyalkenoate cements
Bibliographic record
Abstract
Abstract The primary treatment for patients suffering from bone cancers is resection of the tumour followed by reconstruction of the damaged bone. Despite the administration of post-operative chemotherapy, tumour recurrence continues to present itself as a severe complication leading to re-operation. Attempts to incorporate chemotherapeutic drugs into bone cements elicits local toxic effects on healthy bone, which could compromise implant fixation. Alternatively, the local administration of gallium (Ga) may prove to be more effective. This report considers the development of a Ga ionomeric glass series (0.48SiO2-0.355ZnO-0.06CaO-0.08SrO-0.02P2O5-0.005Ta2O5, with 0.01–0.05 mol% substitution for ZnO). X-ray Diffraction (XRD) confirmed the amorphous glass structure and Energy Dispersive x-ray Fluorescence (EDXRF) verified the successful addition of Ga into the glass series at the expense of Zinc (Zn). A Ga-GPC series was then formulated by mixing the glass particles with aqueous poly(acrylic) acid (PAA) and trisodium citrate (TSC). Fourier transform infrared (FTIR) spectroscopy demonstrated no structural changes to the GPC matrix with the incorporation of Ga. Measurements of the rheological properties demonstrated an exponential increase in setting time with increasing Ga content. Furthermore, the addition of ≥ 3 mol% Ga demonstrated deleterious effects on the GPC’s mechanical properties and an analysis of pH confirmed that it decreased with increasing Ga content, suggesting a reduction in glass reactivity and PAA cross-linking. Finally, inductively coupled plasma—optical emission spectrometry (ICP-OES) demonstrated the controlled release of Ga across the GPC series, which will prove beneficial to future in vitro studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".