Biomaterial‐Induction of a Transplantable Angiosome
Bibliographic record
Abstract
Abstract Creating transplantable vascular networks (angiosomes) that are fed and drained by vessels large enough to be surgically reconnected is key to harnessing the potential of regenerative medicine and advancing reconstructive surgical techniques. Currently, the only way to create a new angiosome is nontrivial and involves pressurizing a vein graft by its surgical attachment to an artery forming an arteriovenous loop (AVL). Material induction of a venous angiosome is reported, by placement of a 3D printed microporous monetite scaffold around a vein and its transplantability is further demonstrated. When the transplanted venosome is cut, it bleeds, illustrating potential reconstructive functionality. The volume of blood vessels generated by biomaterial‐induction is as great as by AVL. Direct contact of the material with the vein does not appear to be critical to luminal sprouting, and wrapping the implant in a silicone membrane significantly reduces sprouting. Pilot studies with microporous polymeric scaffolds induce far less vascular invasion. After 4 weeks, monetite scaffolds are extensively vascularized and can be transplanted to an arterial vessel. This report is significant since a lack of tools to control vascular generation is an impediment to the treatment of several conditions that give rise to tissue ischemia and tissue reconstruction.
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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) | 0.000 | 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) | 0.009 | 0.001 |
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; both teacher heads agree on what is shown here.
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".