QS8: The Roles of the TrkA and p75NTR NGF Receptors in Corneal Wound Healing
Bibliographic record
Abstract
Purpose: The cornea is the window through which we see the world and is one of the most densely innervated structures in the body. Besides providing protective sensory input, corneal nerves have been postulated to stimulate limbal stem cells (LSCs), hence governing corneal epithelial maintenance and recovery. Loss of corneal innervation, through injury, diabetes, tumors, infections, and even improper contact lens use, leads to neurotrophic keratopathy (NK), a degenerative corneal disease that is characterized by corneal epithelial breakdown, scarring, and permanent vision loss1. The only non-invasive treatment option for NK is the human recombinant nerve growth factor (rhNGF), but the short half-life of exogenous neurotrophins-based therapies make this therapeutic approach less effective2. Development of the small molecule ligands for neurotrophins receptors that have better pharmacokinetics and plasma stability showed promising results in the treatment of several neurodegenerative conditions in the recent years3. In this study, we were prompted to investigate the molecular mechanism of NK and the role of NGF receptors, TrkA and p75NTR, in corneal healing. We hypothesized that TrkA inhibition would delay corneal wound healing and p75NTR inhibition accelerates corneal healing. This knowledge will lay the basis for a new non-invasive approach for NK. Methods: For this experiment, we took advantage of commercially available Ntrk1 mutant mice, which allow for pharmacological inhibition of TrkA receptor with an inhibitor known as not mammalian kinase inhibitor (1-NM-PP1)4. Ntrk1 mice (n=20) were divided into three groups, which received saline injection as a control. In one experimental group animals were received TrkA inhibitor and the other group received both TrkA and p75 inhibitor for 5 days. On day six we removed the corneal epithelium with a 0.5 mm rotating brush. To measure epithelial healing, we performed digital imaging of fluorescein staining daily for four days after injury. We then harvested the corneas for immunofluorescent and biochemical analyses. Results: Our results show a significant delay in corneal epithelial healing following TrkA inhibition and acceleration in corneal healing after p75NTR inhibition. Conclusion: A selective TrkA agonist or p75NTR inhibitors could be a new therapeutic approach for NK.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".