Characterizing maternal isolation‐induced ultrasonic vocalizations in a gene–environment interaction rat model for autism
Bibliographic record
Abstract
Deficits in social communication and language development belong to the earliest diagnostic criteria of autism spectrum disorders. Of the many risk factors for autism spectrum disorder, the contactin-associated protein-like 2 gene, CNTNAP2, is thought to be important for language development. The present study used a rat model to investigate the potential compounding effects of autism spectrum disorder risk gene mutation and environmental challenges, including breeding conditions or maternal immune activation during pregnancy, on early vocal communication in the offspring. Maternal isolation-induced ultrasonic vocalizations from Cntnap2 wildtype and knockout rats at selected postnatal days were analyzed for their acoustic, temporal and syntax characteristics. Cntnap2 knockout pups from heterozygous breeding showed normal numbers and largely similar temporal structures of ultrasonic vocalizations to wildtype controls, whereas both parameters were affected in homozygously bred knockouts. Homozygous breeding further exacerbated altered pitch and transitioning between call types found in Cntnap2 knockout pups from heterozygous breeding. In contrast, the effect of maternal immune activation on the offspring's vocal communication was confined to call type syntax, but left ultrasonic vocalization acoustic and temporal organization intact. Our results support the "double-hit hypothesis" of autism spectrum disorder risk gene-environment interactions and emphasize that complex features of vocal communication are a useful tool for identifying early autistic-like features in rodent models.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".