Effects of amniotic membrane extract on primary human corneal epithelial and limbal cells
Bibliographic record
Abstract
BACKGROUND: To assess the effects of amniotic membrane extract (AMX) on cellular activity of primary human corneal epithelial (HCE) cells under mechanical and oxidative stress, and on human limbal cells under oxidative stress. METHODS: Corneal mechanical stress was simulated with a linear scratch in confluent HCE cell plates, then incubated with 0.1% AMX for 48 and 72 h. Subjecting HCE cultures to 0.5 mmol/L tertiary-butylhydroperoxide for 1 h simulated an oxidative stress. 0.1% AMX-treated cultures were compared with controls at 24 and 48 h using cellular viability assay, along with 12-h AMX pretreatment and human limbal cell comparisons. RESULTS: Mechanical stress on HCE cultures revealed a statistically significant distance ratio at 48 and 72 h in favour of 0.1% AMX-treated cultures (P = 0.021 and 0.035, respectively). Oxidative stress did not reveal any significant difference in cellular viability of AMX-treated versus control cultures. Twelve hour AMX pre-treatment prior to oxidative stress revealed a significant difference after 24 h from oxidative injury (73.3% AMX vs. 66.0% control, P = 0.035), but not after 48 h. Human limbal cells demonstrated significantly improved oxidative viability compared with HCE cells, with (91.0% vs. 82.0% control, P = 0.017) and without 0.1% AMX pre-treatment (91.2% vs. 83.7% control, P = 0.019). CONCLUSIONS: HCE cells treated with AMX healed faster after mechanical insult, suggesting a potential benefit in acute corneal injuries. Under oxidative stress, human limbal cells, a more proliferative cell type, showed superior viability compared with HCE cells.
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 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) | 0.000 | 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) | 0.002 | 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".