Bioinspired Smart Nanogels for Rapid Blue Laser‐Activated Hemostasis in Gastrointestinal Bleeding
Why this work is in the frame
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Bibliographic record
Abstract
Gastrointestinal bleeding (GIB) is a critical condition that requires rapid and effective intervention. Although thrombin is a widely used hemostatic agent, its efficacy is limited in the harsh environment of the digestive tract, especially in patients with chronic liver disease or coagulation disorders. Current treatment techniques often fall short, particularly when faced with severe blood loss and coagulation challenges. Here, a novel solution: waxberry-inspired smart nanogels that offer a cost-effective, highly efficient, and mechanically stable approach for local hemostasis is presented. Drawing inspiration from the microfibrous structures of waxberry, a waxberry-like nano-silica with a radially fibrous structure is synthesized for effective thrombin loading and release upon emergency. This nano-silica, coated with GelMA, forms a stable nanogel network activated by blue laser during endoscopy. Within just 5 s, the nanogel effectively triggers coagulation, even in patients with coagulation disorders. The formed blood clots are stable enough to withstand the challenging conditions of the digestive tract, preventing secondary bleeding. Upon injection, thrombin rapidly converts fibrinogen to fibrin, creating a secondary network that reinforces clot stability. This dual-network system demonstrates strong adhesive properties and effective hemostasis in the blood of cirrhotic patients, as well as in gastrointestinal bleeding scenarios involving the esophagus, stomach, and duodenum of mini-pigs.
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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 | 0.001 | 0.001 |
| 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 it