Lasting changes induced by mild alcohol exposure during embryonic development in <scp>BDNF</scp>,<scp> NCAM</scp> and synaptophysin‐positive neurons quantified in adult zebrafish
Bibliographic record
Abstract
Fetal alcohol spectrum disorder is one of the leading causes of mental health issues worldwide. Analysis of zebrafish exposed to alcohol during embryonic development confirmed that even low concentrations of alcohol for a short period of time may have lasting behavioral consequences at the adult or old age. The mechanism of this alteration has not been studied. Here, we immersed zebrafish embryos into 1% alcohol solution (vol/vol%) at 24 hr post-fertilization (hpf) for 2 hr and analyzed potential changes using immunohistochemistry. We measured the number of BDNF (brain-derived neurotrophic factor) and NCAM (neuronal cell adhesion molecule)-positive neurons and the intensity of synaptophysin staining in eight brain regions: lateral zone of the dorsal telencephalic area, medial zone of the dorsal telencephalic area, dorsal nucleus of the ventral telencephalic area, ventral nucleus of the ventral telencephalic area, parvocellular preoptic nucleus, ventral habenular nucleus, corpus cerebella and inferior reticular formation. We found embryonic alcohol exposure to significantly reduce the number of BDNF- and NCAM-positive cells in all brain areas studied as compared to control. We also found alcohol to significantly reduce the intensity of synaptophysin staining in all brain areas except the cerebellum and preoptic area. These neuroanatomical changes correlated with previously demonstrated reduction of social behavior in embryonic alcohol-exposed zebrafish, raising the possibility of a causal link. Given the evolutionary conservation across fish and mammals, we emphasize the implication of our current study for human health: even small amount of alcohol consumption may be unsafe during pregnancy.
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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 | 0.001 |
| 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".