Tantalum-containing mesoporous bioactive glass powder for hemostasis
Bibliographic record
Abstract
This study evaluates the hemostatic properties of tantalum-containing mesoporous bioactive glasses (Ta-MBGs) through a suite of in-vitro methods: hemolysis percentage, zeta potential, blood coagulation assays (Activated Partial Thromboplastin Time – APTT and Prothrombin Time - PT) and cytotoxicity tests. Five compositions of Ta-MBG, with x mol% Ta 2 O 5 added to the glass series (80- x)SiO 2 -15CaO-5P 2 O 5 - xTa 2 O 5 where x=0 (0Ta), x=0.5 (0.5Ta), x=1 (1Ta), x=5 (5Ta), and x=10 (10Ta) mol%, were synthesised. The hemostatic potential of all the Ta-MBGs was confirmed by their negative zeta potential (–23 to –31 mV), which enhances the intrinsic pathway of blood coagulation. The hemolysis percentages of all Ta-MBGs except 10Ta showed statistically significant reductions compared to the same experiments carried out both in the absence of a sample (‘no treatment’ group) and in the presence of 10Ta. These observations validate the consideration of Ta-MBGs as hemostatic agents as they do not cause significant lysis of red blood cells. Cytotoxicity analysis revealed that Ta-MBGs had no effect on bovine fibroblast viability. Furthermore, a reduction in both APTT (a test to evaluate the intrinsic pathway of coagulation) and PT (a test to evaluate the extrinsic pathway) signified enhancement of hemostasis: 5Ta caused a significant reduction in APTT compared to ‘no treatment’, 1Ta and 10Ta and a significant reduction in PT compared to 0Ta. Therefore, we conclude that 5mol% of Ta optimised the hemostatic properties of these mesoporous bioactive glasses.
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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) | 0.000 | 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".