Tantalum-doped Mesoporous Bioactive Glass Fibers and Powders for Hemostatic Applications
Bibliographic record
Abstract
<p>Hemorrhage is the leading cause of battlefield deaths and second most common cause for civilian mortality worldwide, and mesoporous BGs (MBGs), are candidates for hemostasis. </p> <p>Novel tantalum-containing MBG (Ta-MBG) powders: (80-<em>x</em>)SiO<sub>2</sub>-15CaO-5P<sub>2</sub>O<sub>5</sub>-<em>x</em>Ta<sub>2</sub>O<sub>5</sub> with <em>x</em>=0 (0Ta), 0.5 (0.5Ta), 1 (1Ta), 5 (5Ta), and 10 (10Ta), were developed using a sol-gel process. The powders were non-cytotoxic to bovine fibroblasts (MTT assay) and had a negative surface charge (-20.4 to -24.8 mV measured using zeta potential, ZP) which enhanced the intrinsic coagulation pathway (assessed using activated partial thromboplastin time, APTT). The powders (except 10Ta) showed lower hemolysis and APTT than ‘no treatment’ (physiological clotting). Among Ta-MBGs, 5Ta (11.6±5.8 sec) reduced APTT significantly compared to 1Ta (31.5±5.8 sec) and 10Ta (28±5.9 sec). Furthermore, lethal-liver-injury porcine trials of two best powders (5Ta and 1Ta) confirmed 5Ta as the most suitable composition for hemostasis. </p> <p>Powder hemostats pose handling and functional challenges in the wet surgical field; to address these challenges, the hemostatic compositions (0Ta, 0.5Ta, 1Ta, and 5Ta) were fabricated as fibrous mats using a combination of sol-gel route and electrospinning technique. </p> <p>The state-of-the-art analytical techniques showed fibers encompassing a hierarchical micro (0.5-2 µm) and nano (1-8 nm) porosity while the powders displaying unimodal mesopores (4 nm) leading to higher (298-374 m<sup>2</sup>g<sup>-1</sup>) surface areas than equivalent fibers (5-61 m<sup>2</sup>g<sup>-1</sup>). The ZP of the fibers (-26.2 to -48.7 mV) was better for hemostasis and stability in the wet environment than powders (-20.4 to -24.8 mV). The fibers were also non-cytotoxic to primary rat fibroblasts. The powders showed higher non-bridging oxygen-silicon (Si-NBO) bonds leading to higher ionic release than the fibers. Lower Si-NBO, lesser ionic release and more negative ZP provide advantageous stability to the fibers in wet environments. No significant differences between the bleeding times of powders and fibres was found using murine tail-bleed models. APTT suggested 1Ta composition to be most suitable among fibers to enhance hemostasis.</p> <p>It is concluded that 5Ta and 1Ta provide the best compositions to enhance hemostasis among powders and fibers, respectively. The structural and functional differences/similarities of two forms were not reflected in their hemostatic capabilities. Finally, the fibers provide a stable matrix for clot formation that can compress the bleeding site.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".