Vocal communication in asocial BTBR mice is more malleable by a ketogenic diet in juveniles than adults
Bibliographic record
Abstract
Deficits in social communication and language development are a hallmark of autism spectrum disorder currently with no effective approaches to reduce the negative impact. Interventional studies using animal models have been very limited in demonstrating improved vocal communication. Autism has been proposed to involve metabolic dysregulation. Ketogenic diet (KD) is a metabolism-based therapy for medically intractable epilepsy, and its applications in other neurological conditions have been increasingly tested. However, how KD would affect vocal communication has not been explored. The BTBR mouse strain is widely used to model asocial phenotypes. They display robust and pronounced deficits in vocalization during social interaction, and have metabolic changes implicated in autism. We investigated the effects of KD on ultrasonic vocalizations (USVs) in juvenile and adult BTBR mice during male-female social encounters. After a brief treatment with KD, the number, spectral bandwidth, and much of the temporal structure of USVs were robustly closer to control levels in both juvenile and adult BTBR mice. Composition of call categories and transitioning between individual call subtypes were more effectively altered to more closely align with the control group in juvenile BTBR mice. Together, our data provide further support to the hypothesis that metabolism-based dietary intervention could modify disease expression, including core symptoms, in autism. Future studies should tease apart the molecular mechanisms of KD's effects on vocalization.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".