Analyzing Mushroom Structural Patterns of a Highly Compressible and Expandable Hemostatic Foam for Gastric Perforation Repair
Bibliographic record
Abstract
Nature presents the most beautiful patterns through evolving. Here, a layered porous pattern in golden ratio (0.618) is reported from a type of mushroom -Dictyophora Rubrovalvata stipe (DRS). The hierarchical structure shows a mathematical correlation with the golden ratio. This unique structure leads to superior mechanical properties. The gradient porous structure from outside to innermost endows it with asymmetrical hydrophilicity. A mathematical model is then developed to predict and apply to 3D printed structures. The mushroom is then explored to repair gastric perforation because the stomach is a continuous peristaltic organ, and the perforated site is subject to repeated mechanical movements and pressure changes. At present, endoscopic clipping is ineffective in treating ulcerative perforation with fragile surrounding tissues. Although endoscopic implant occlusion provides a new direction for the treatment of gastric ulcers, but the metal or plastic occluder needs to be removed, requiring a second intervention. Decellularized DRS (DDRS) is found with asymmetric water absorption rate, super-compressive elasticity, shape memory, and biocompatibility, making it a suitable occluder for the gastric perforation. The efficacy in blocking gastric perforation and promoting healing is confirmed by endoscopic observation and tissue analysis during a 2-month study.
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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".