Effects of Prenatal Alcohol Exposure on the Visual System of Monkeys Measured at Different Stages of Development
Bibliographic record
Abstract
Purpose: Fetal alcohol spectrum disorder (FASD) is a developmental disease characterized by behavioral problems and physical defects including malformations of the eye and associated optical defects. How these malformations affect retinal functioning is not well known, although animal models have suggested that scotopic vision is particularly deficient. Age is also known to affect scotopic vision. Here, we determined the combined effects of age and fetal alcohol exposure (FAE) on retinal function using full-field electroretinograms (ERGs) in monkeys (Chlorocebus sabaeus). Methods: ERGs were recorded in monkeys aged 3- to 12-years old, at multiple flash intensities under scotopic and photopic conditions, and functions were fit to the amplitudes of the a- and b-waves. Results: We found that both age and alcohol exposure affected ERGs. In photopic ERGs, amplitudes increased with age, and were higher in FAEs than controls, for data related to the OFF- and ON-pathways. In scotopic ERGs, amplitudes were decreased in young FAE compared with age-matched controls but only for the rod-dominated responses, while at brighter flashes, alcohol exposure led to an increase in the amplitude of the a- and b-waves. Conclusions: The ERGs from the FAE animals closely resembled the data from the older sucrose-control monkeys. This suggests that the FAE monkey retina ages more quickly than the control monkeys. This large sample of nonhuman primates, with carefully monitored ethanol exposure, demonstrates the critical interplay between age and alcohol when assessing the integrity of the retina. We suggest that ERGs might be an important adjunct to diagnosing human FASD.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".