Innervated human corneal equivalents as in vitro models for nerve‐target cell interactions
Bibliographic record
Abstract
A sensory nerve supply is crucial for optimal tissue function. However, the mechanisms for successful innervation and the signaling pathways between nerves and their target tissue are not fully understood. Engineered tissue substitutes can provide controllable environments in which to study tissue innervation. We have therefore engineered human corneal substitutes that promote nerve in-growth in a pattern similar to in vivo re-innervation. We demonstrate that these nerves (a) are morphologically equivalent to natural corneal nerves; (b) make appropriate contact with target cells; (c) can generate action potentials; (d) respond to chemical and physical stimuli; and (e) play an important role in the overall functioning of the bioengineered tissue. This model can be used for studying the more general topics of nerve ingrowth or regeneration and the interaction between nerves and their target cells and, more specifically, the role of nerves in corneal function. This model could also be used as an in vitro alternative to animals for safety and efficacy testing of chemicals and drugs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".