Plasma surface modification and characterization of collagen‐based artificial cornea for enhanced epithelialization
Bibliographic record
Abstract
Abstract Argon plasma treatment enhanced the attachment of epithelial cells to a collagen‐based artificial cornea crosslinked using glutaraldehyde (GA) and glutaraldehyde‐polyethylene oxide dialdehyde (GA‐PEODA) systems. The epithelialization of untreated and treated surfaces was evaluated by the seeding and growth of human corneal epithelial cells. Characterization of polymer surface properties such as surface hydrophilicity and roughness was also made by contact angle measurement and atomic force microscopy, respectively. Contact angle analysis revealed that the surface hydrophilicity significantly increased after the treatment. In addition, AFM characterization showed an increase in surface roughness through argon plasma treatment. Based on the biological and surface analysis, argon plasma treatment displays promising potential for biocompatibility enhancement of collagen‐based artificial corneas. It was also found that the cell attachment to artificial cornea surfaces was influenced by the combined effects of surface chemistry (i.e., surface energy), polymer surface morphology (i.e., surface roughness), and polar interactions between functional groups at the polymer surface and cell membrane proteins. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007
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 | 0.001 | 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".