Collagen analogs with phosphorylcholine are inflammation-suppressing scaffolds for corneal regeneration from alkali burns in mini-pigs
Bibliographic record
Abstract
The long-term survival of biomaterial implants is often hampered by surgery-induced inflammation that can lead to graft failure. Considering that most corneas receiving grafts are either pathological or inflamed before implantation, the risk of rejection is heightened. Here, we show that bioengineered, fully synthetic, and robust corneal implants can be manufactured from a collagen analog (collagen-like peptide-polyethylene glycol hybrid, CLP-PEG) and inflammation-suppressing polymeric 2-methacryloyloxyethyl phosphorylcholine (MPC) when stabilized with the triazine-based crosslinker 4-(4,6-Dimethoxy-1,3,5-triazin-2-yl)-4-methylmorpholinium chloride. The resulting CLP-PEG-MPC implants led to reduced corneal swelling, haze, and neovascularization in comparison to CLP-PEG only implants when grafted into a mini-pig cornea alkali burn model of inflammation over 12 months. Implants incorporating MPC allowed for faster nerve regeneration and recovery of corneal sensation. CLP-PEG-MPC implants appear to be at a more advanced stage of regeneration than the CLP-PEG only implants, as evidenced by the presence of higher amounts of cornea-specific type V collagen, and a corresponding decrease in the presence of extracellular vesicles and exosomes in the corneal stroma, in keeping with the amounts present in healthy, unoperated corneas.
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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 | 0.000 | 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 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".