The effect of tantalum incorporation on the physical and chemical properties of ternary silicon–calcium–phosphorous mesoporous bioactive glasses
Bibliographic record
Abstract
Synthesis and characterization of the first mesoporous bioactive glasses (MBGs) containing tantalum are reported here, along with their potential application as hemostats. Silica MBGs were synthesized using with the molar composition of (80-x)% Si, 15% Ca, 5% P, and x% Ta. It was found that incorporation of >1 mol % Ta into the MBGs changes their physical and chemical properties. Increasing Ta content from 0 to 10 mol % causes a decrease in the surface area and pore volume of ~20 and ~35%, respectively. This is due to the increase in nonbridging oxygens and mismatch of thermal expansion coefficient which created discontinuities in the ordered channel structure. However, the effect is not significant on the amount of ions (Si, Ca, P, and Ta) released, from the sample into deionized water, for short durations (<60 min). In a mouse tail-cut model, a significant decrease in bleeding time (≥50% of average bleeding time) was found for Ta-MBGs compared to having no treatment, Arista, and MBG without Ta. Further studies are proposed to determine the mechanism of Ta involvement with the hemostatic process. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 2229-2237, 2019.
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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) | 0.000 | 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".