Shear-Thinning Nanocomposite Hydrogels for the Treatment of Hemorrhage
Bibliographic record
Abstract
Internal hemorrhaging is a leading cause of death after traumatic injury on the battlefield. Although several surgical approaches such as the use of fibrin glue and tissue adhesive have been commercialized to achieve hemostasis, these approaches are difficult to employ on the battlefield and cannot be used for incompressible wounds. Here, we present shear-thinning nanocomposite hydrogels composed of synthetic silicate nanoplatelets and gelatin as injectable hemostatic agents. These materials are demonstrated to decrease in vitro blood clotting times by 77%, and to form stable clot-gel systems. In vivo tests indicated that the nanocomposites are biocompatible and capable of promoting hemostasis in an otherwise lethal liver laceration. The combination of injectability, rapid mechanical recovery, physiological stability, and the ability to promote coagulation result in a hemostat for treating incompressible wounds in out-of-hospital, emergency conditions.
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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".