Second Harmonic Generation Signals in Rabbit Sclera As a Tool for Evaluation of Therapeutic Tissue Cross-linking (TXL) for Myopia
Bibliographic record
Abstract
Methods to strengthen tissue by introducing chemical bonds (non-enzymatic cross-linking) into structural proteins (fibrillar collagens) for therapy include photochemical cross-linking and tissue cross-linking (TXL) methods. Such methods for inducing mechanical tissue property changes are being employed to the cornea in corneal thinning (mechanically weakened) disorders such as keratoconus as well as the sclera in progressive myopia, where thinning and weakening of the posterior sclera occurs and likely contributes to axial elongation. The primary target proteins for such tissue strengthening are fibrillar collagens which constitute the great majority of dry weight proteins in the cornea and sclera. Fortuitously, fibrillar collagens are the main source of second harmonic generation signals in the tissue extracellular space. Therefore, modifications of the collagen proteins, such as those induced through cross-linking therapies, could potentially be detected and quantitated through the use of second harmonic generation microscopy (SHGM). Monitoring SHGM signals through the use of a laser scanning microscopy system coupled with an infrared excitation light source is an exciting modern imaging method that is enjoying widespread usage in the biomedical sciences. Thus, the present study was undertaken in order to evaluate the use of SHGM microscopy as a means to measure induced cross-linking effects in ex vivo rabbit sclera, following an injection of a chemical cross-linking agent into the sub-Tenon's space (sT), an injection approach that is standard practice for causing ocular anesthesia during ophthalmologic clinical procedures. The chemical cross-linking agent, sodium hydroxymethylglycinate (SMG), is from a class of cosmetic preservatives known as formaldehyde releasing agents (FARs). Scleral changes following reaction with SMG resulted in increases in SHG signals and correlated with shifts in thermal denaturation temperature, a standard method for evaluating induced tissue cross-linking effects.
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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 | 0.000 | 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".