A cross-linked hyaluronan gel accelerates healing of corneal epithelial abrasion and alkali burn injuries in rabbits
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy of a chemically modified and cross-linked derivative of hyaluronan (CMHA-SX) for treatment of corneal epithelial abrasion and standardized alkali burn injuries. ANIMALS: Twelve female New Zealand white rabbits in two groups were used. PROCEDURES: Bilateral 6-mm diameter corneal epithelial abrasions were made in each of six rabbits in one group and 6-mm standardized alkali burn injuries were made in the second group. A 1% CMHA-SX formulation was applied topically four times per day in right eye of each rabbit for 1 week, and phosphate buffered saline (PBS) was placed in left (control) eye of each rabbit. The wound size was determined by staining with 1% fluorescein and photographed at the slit lamp with a digital camera at 0, 1, 2, 3 days postoperatively in the first group and 0, 1, 2, 3, 7, 12 days in the second group. Rabbit corneas were collected for histological examination on day 7 in the first group and day 12 in the second group. RESULTS: Closure of corneal wound in the abrasion model was complete in the CMHA-SX treated eye by 48 h. The wound closure rate and thickness of the central corneal epithelium in the CMHA-SX treated group was greater than in control eyes for both the abrasion and alkali burn injuries. Moreover, the CMHA-SX treated cornea exhibited better epithelial and stromal organization than the untreated control cornea. CONCLUSIONS: Chemically modified and cross-linked derivative of hyaluronan improved corneal wound healing and could be useful for treating noninfectious corneal injuries.
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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) | 0.001 | 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) | 0.001 | 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".