Evaluation of plant‐derived biomaterials for the development of tissue‐engineered corneal substitutes
Bibliographic record
Abstract
Abstract Corneal blindness affects over 10 million patients worldwide. Due to the limited supply of donor corneas and frequent graft failure, bioengineered alternatives are crucial. To overcome drawbacks associated with corneal substitutes from synthetic biomaterials, fabrication from plant‐derived biomaterials is a potential alternative. Herein, soy protein and glutenin in combination with different crosslinkers were evaluated for fabrication of corneal substitutes. Optical, mechanical, and biochemical properties of fabricated constructs and control rabbit corneas were evaluated in vitro. Soy protein crosslinked with peroxidase/H202 possessed transparency and mechanical properties comparable to controls, although their water content and biocompatibility were inferior. In contrast, soy protein crosslinked with tannic acid showed similar water content, tensile strength, and biocompatibility as rabbit corneas; however, these constructs displayed significantly lower transparency and higher strain to failure. Finally, glutenin cross‐linked using formaldehyde showed excellent transparency, strain to failure, and biocompatibility, however; they exhibited significantly lower water content and tensile strength than controls. This study is the first to establish CIELAB color values for the rabbit cornea, allowing quantitative optical evaluation of tissue‐engineered substitutes. Thus, a crosslinking strategy utilizing plant‐derived proteins for fabrication of constructs with properties comparable to rabbit corneas is a promising direction for development of tissue‐engineered corneal substitutes.
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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) | 0.000 | 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 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".