Mixture designs to assess composition–structure–property relationships in SiO <sub>2</sub> –CaO–ZnO–La <sub>2</sub> O <sub>3</sub> –TiO <sub>2</sub> –MgO–SrO–Na <sub>2</sub> O glasses: Potential materials for embolization
Bibliographic record
Abstract
Embolization with micron-sized particulates is widely applied to treat uterine fibroids. The objective of this work was to develop mixture designs to predict materials composition-structure-property relationships for the SiO₂-CaO-ZnO-La₂O₃-TiO₂-MgO-SrO-Na₂O glass system and compare its fundamental materials properties (density and cytocompatibility), against a state-of-the-art embolic agent (contour polyvinyl alcohol) to assess the potential of these materials for embolization therapies. The glass structures were evaluated using ²⁹Si MAS NMR to identify chemical shift and line width; the particulate densities were determined using helium pycnometry and the cell viabilities were assessed via MTT assay. ²⁹Si MAS NMR results indicated peak maxima for each glass in the range of -82.3 ppm to -89.9 ppm; associated with Q² to Q³ units in silicate glasses. All experimental embolic compositions showed enhanced in vitro compatibility in comparison to Contour PVA with the exceptions of ORP9 and ORP11 (containing no TiO₂). In this study, optimal compositions for cell viability were obtained for the following compositional ranges: 0.095-0.188 mole fraction ZnO; 0.068-0.159 mole fraction La₂O₃; 0.545-0.562 mole fraction SiO₂ and 0.042-0.050 mole fraction TiO₂. To ensure ease of producibility in obtaining good melts, a maximum loading of 0.068 mole fraction La₂O₃ is required. This is confirmed by the desirability approach, for which the only experimental composition (ORP5) of the materials evaluated was presented as an optimum composition; combining high cell viability with ease of production (0.188 mole fraction ZnO; 0.068 mole fraction La₂O₃; 0.562 mole fraction SiO₂ and 0.042 mole fraction TiO₂).
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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 | 0.001 |
| 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".