CA2 Spine Density in an In-Vivo Model of Autism Spectrum Disorder
Bibliographic record
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder, characterized by a wide range of social and behavioral symptoms. Pathophysiology of ASD in humans is highly variable, however, there are differences seen in spine morphology and density, specifically in the hippocampus, which is involved in social memory. Treatment of ASD is limited, targeting only certain symptoms, through both pharmacological and non-pharmacological methods. Prenatal exposure to valproic acid (VPA) can create an animal model of ASD that shows similarities to the pathophysiology of ASD in humans. Animal models of ASD can provide the framework for developing treatments targeted towards the underlying neurobiology of ASD and a wider range of symptoms. This study used a VPA-induced mouse model of ASD to examine dendritic spine density and morphology within the CA2 region of the hippocampus, a region implicated in social memory. Neuron reconstruction was performed using Neurolucida (MicroBrightField, Williston, VT, USA) at a magnification of 100x. Neurons within the CA2 of the hippocampus were traced, and spines were quantified as thin, mushroom, or stubby. Reconstruction was done with set criteria to ensure consistency across brain slices. There were no significant changes observed in thin and total spine density between treatments, but a significant decrease in thin spine density in females was observed. A significant increase in stubby spine density and decreased mushroom spine density were observed in the VPA treatment groups. Future studies may investigate additional brain regions and spine density after VPA exposure to further the development of viable treatment options.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".