Preventing Corneal Calcification Associated With Xylazine for Longitudinal Optical Coherence Tomography in Young Rodents.
Bibliographic record
Abstract
Purpose: Spectral-domain optical coherence tomography (SD-OCT) is widely used in clinical ophthalmology and recently gained popularity in laboratory research involving small rodents. Its noninvasive nature allows repeated measurements, thereby decreasing the number of animals required. However, when used at a conventional dosage, xylazine (an α2-adrenoceptor) can cause irreversible corneal calcification, especially among young rodents. In the present study, we test whether corneal calcification associated with xylazine is mediated by the α2-adrenoceptor. Methods: Our study tested Sprague-Dawley rats, Long-Evans rats, and CD-1 mice (postnatal day [P]14). Retinal images were captured by SD-OCT. Quantitative PCR (qPCR) was used to study gene expression, whereas receptor localization was examined by immunofluorescent staining followed by confocal microscopy. Calcium deposits were detected via von Kossa staining. Results: When used at dosages appropriate for adult animals, ketamine-xylazine anesthetics led to a high rate of respiratory failure, increased apoptotic activity in the corneal epithelium, and irreversible corneal calcification in P14 rat pups. Meanwhile, OCT image quality decreased drastically as a result of corneal calcification among animals recovering from anesthesia. α2-Adrenoceptor subtypes were highly expressed on P14, in line with rodents' age-specific sensitivity to xylazine. Clonidine, a potent α2-adrenoceptor agonist, dose-dependently induced corneal calcification, which could be prevented by an α2-adrenoceptor antagonist. Conclusions: These data suggest that α2-adrenoceptors contribute to corneal calcification in young rodents. Therefore, we developed a suitable OCT imaging protocol for this cohort, including a carefully tailored ketamine-xylazine dosage (60 mg/kg and 2.5 kg/mg, respectively).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".