Application of acellular dermal xenografts in full-thickness skin burns
Bibliographic record
Abstract
The aim of this study was to explore the clinical value of the porcine acellular dermal xenograft (ADX) in combination with autologous split-thickness skin and pure autologous split-thickness skin grafting applied in deep full-thickness burns and scar wounds. A total of 30 patients with deep burns were randomly divided into experimental and control groups following escharectomy. The patients were separately treated with porcine acellular dermal xenograft (ADX) in combination with autologous split-thickness skin and pure autologous split-thickness skin graft. The wound healing was observed routinely and the scores were evaluated using Vancouver scar scale at different times following transplant surgery. The samples of cograft regions and the control group (pure transplant split-thickness skin autograft) were observed using light microscopy and electron microscopy, and the follow-up results were recorded. No conspicuous rejections on the cograft wound surface were observed. Compared with the control group, the cograft wounds were smooth, presented no scar contracture and exhibited good skin elasticity and recovery of the joint function. The cografted skin combined well and displayed a clear and continuous basal membrane, as well as gradually combined skin structure, a mature stratum corneum, downward extended rete pegs, a mainly uniform dermal collagen fiber structure, regular alignment, and fewer blood capillaries. Clear desmosome cograft regions were identified among heckle cells, as well as a clear and continuous basal membrane. The cografted skin of the combined split-thickness autograft and the acellular heterologous (porcine) dermal matrix showed an improved shape and functional recovery compared with the pure split-thickness skin autograft. The combination of the meshed ADX and the split-thickness skin autograft applied in deep full-thickness burns and scar wounds may induce tissue regeneration via dermis aiming. This method also has superior shape and functional recovery, and has an extensive clinical application value.
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.
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) | 0.000 | 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 teacher head, 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".