Immunological challenges associated with artificial skin grafts: available solutions and stem cells in future design of synthetic skin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The repair or replacement of damaged skins is still an important, challenging public health problem. Immune acceptance and long-term survival of skin grafts represent the major problem to overcome in grafting given that in most situations autografts cannot be used. The emergence of artificial skin substitutes provides alternative treatment with the capacity to reduce the dependency on the increasing demand of cadaver skin grafts. Over the years, considerable research efforts have focused on strategies for skin repair or permanent skin graft transplantations. Available skin substitutes include pre- or post-transplantation treatments of donor cells, stem cell-based therapies, and skin equivalents composed of bio-engineered acellular or cellular skin substitutes. However, skin substitutes are still prone to immunological rejection, and as such, there is currently no skin substitute available to overcome this phenomenon. This review focuses on the mechanisms of skin rejection and tolerance induction and outlines in detail current available strategies and alternatives that may allow achieving full-thickness skin replacement and repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| 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