Oral‐Facial Tissue Reconstruction in the Regenerative Axolotl
Bibliographic record
Abstract
Absence of large amounts of orofacial tissues caused by cancerous resections, congenital defects, or trauma results in sequelae such as dysphagia and noticeable scars. Oral-neck tissue regeneration was studied in the axolotl (regenerative amphibian) following a 2.5-mm punch biopsy that simultaneously removed skin, connective tissue, muscle, and cartilage in the tongue and intermandibular region. The untreated wound was studied macroscopically and histologically at 17 different time points ranging from 0 to180 days (N = 120 axolotls). At 12 hr, the wound's surface was smoothened and within 1mm, internal lingual muscular modifications occurred; at the same distance, between days 4-7 lingual muscle degradation was complete. Immunofluorescence indicates complete keratinocytes migration by 48 hr. These cells with epidermal Leydig cells, appearing yellow, lead the chin's deep tissue outgrowth until its closure on the 14th day. Regeneration speeds varied and peaked in time for each tissue, (1) deep chin 84.3 μm/hr from 24 to 96 hr, (2) superficial chin 71.1 μm/hr from 7-14 days, and (3) tongue 86.0 μm/hr between 48 hr and 7 days. Immunofluorescence to Col IV showed basement membrane reconnected between days 30-45 coinciding with the chin's dermal tissue's surface area recovery. New muscle appeared at 21 days and was always preceded by the formation of a collagen bed. Both chin tissues regain all surface area and practically all components while the lingual structure lacks some content but is generally similar to the original. The methodology and high-resolution observations described here are the first of its kind for this animal model and could serve as a basis for future studies in oral and facial regenerative research.
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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) | 0.000 | 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".