Interactions of corneal cells with transforming growth factor β2‐modified poly dimethyl siloxane surfaces
Bibliographic record
Abstract
The downgrowth of corneal epithelial cells at the interface of an artificial cornea and the host eye tissue poses a significant problem to be overcome in developing a successful implant. As a means of inhibiting the proliferation of corneal epithelial cells on the stromal surface of the implant, we examined the immobilization of transforming growth factor beta-2 (TGF-beta2) via a bifunctional poly ethylene glycol (PEG) spacer to poly dimethyl siloxane (PDMS) surfaces. Growth factor immobilization was confirmed by modification with (125)I-labeled TGF-beta 2. The modified surfaces were also characterized by advancing water contact angles, X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM). Although the amount of growth factor covalently bound to the surface was difficult to quantify apparently due to strong interactions between the growth factor and the PEG layer and high levels of adsorption, differences in the modified surfaces, suggestive of the presence of a significant amount of TGF-beta 2, were found. In vitro interactions of the modified surfaces with human corneal epithelial and stromal cells were examined. Growth factor surface concentrations as well as culture in the absence and presence of serum and other adhesive proteins were examined. Corneal stromal and epithelial cells cultured on the TGF-beta 2-modified surfaces consistently gave results opposite to those expected. Likely, the most notable and surprising result was the almost complete lack of adhesion of the stromal cells, with coverage averaging between 3 and 5%. In comparison, corneal epithelial cell growth appeared to be promoted by the presence of the immobilized growth factor, with cell coverage averaging 50-60% at 7 days of culture. A TGF-beta 2 concentration effect was noted with both cell types in the absence of serum, with increases in the coverage at higher TGF-beta 2 concentrations. The observed cell growth appeared to be the result of interactions between the cells and active growth factor, because the addition of anti-TGF-beta 2 to the culture medium reduced cell coverage to levels similar to those noted on control surfaces. Therefore, although TGF-beta 2-modified surfaces may not be suitable as corneal epithelial cell inhibiting surfaces, interactions of surface immobilized growth factor and corneal cells are complex and should be further examined.
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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) | 0.000 | 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) | 0.001 | 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".