Nonwoven Hemostatic Dressings Formed by Contact Drawing of Interposed Polyethylene Oxide (PEO)‐Fibrinogen and PEO‐Thrombin Microfibers
Bibliographic record
Abstract
Abstract Textiles containing interposed layers of polyethylene oxide (PEO)‐fibrinogen and PEO‐thrombin fibers are explored as biomaterials for hemostasis. The PEO‐fibrinogen and PEO‐thrombin fibers are formed by contact drawing, an approach that uses an entangled polymer solution and a pin array to form fibers by extension of liquid bridges. The interposition of the PEO‐fibrinogen and PEO‐thrombin fibers results in polymerization of a fibrin hydrogel mesh once the textile is hydrated. This fibrin hydrogel mesh displays the expected bands and diffraction peaks by Fourier‐transform infrared spectromicroscopy and X‐ray diffraction, respectively. The functionality of the hemostatic textiles formed from the interposed PEO‐fibrinogen and PEO‐thrombin fibers is demonstrated by analyzing human blood hemolysis, complement activation, protein adsorption, and platelet and leukocyte adhesion, indicating compatibility with human blood (hemolysis ratio <5%), with minimal inflammatory response (levels of terminal complement complex equivalent to plasma). The cytocompatibility and potential for cell remodeling of the fibrin hydrogel mesh formed by this process is evaluated with human dermal fibroblasts and human keratinocytes and it is found that both cell types attach and grow on the fibrin mesh. Finally, a whole blood clotting time of less than 30 s suggests a potential use of this material in hemorrhage control.
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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".