Convergent depression of activity-dependent bulk endocytosis in rodent models of autism spectrum disorder
Bibliographic record
Abstract
BACKGROUND: The key pathological mechanisms underlying autism spectrum disorder (ASD) remain relatively undetermined, potentially due to the heterogenous nature of the condition. Targeted studies of a series of monogenic ASDs have revealed postsynaptic dysfunction as a central conserved mechanism. Presynaptic dysfunction is emerging as an additional disease locus in neurodevelopmental disorders; however, it is unclear whether this dysfunction drives ASD or is an adaptation to the altered brain microenvironment. METHODS: ) were specifically selected to have perturbations in a diverse palette of genes that were expressed either at the pre- or post-synapse. Synaptic vesicle exocytosis and cargo trafficking were triggered via two discrete trains of activity and monitored using the genetically-encoded reporter synaptophysin-pHluorin. Activity-dependent bulk endocytosis was assessed during intense neuronal activity using the fluid phase marker tetramethylrhodamine-dextran. RESULTS: Both synaptic vesicle fusion events and cargo trafficking were unaffected in all models investigated under all stimulation protocols. However, a key convergent phenotype across neurons derived from all five models was revealed, a depression in activity-dependent bulk endocytosis. LIMITATIONS: The study is exclusively conducted in primary cultures of hippocampal neurons; therefore, the impact on neurons from other brain regions or altered brain microcircuitry was not assessed. No molecular mechanism has been identified for this depression. CONCLUSION: This suggests that depression of activity-dependent bulk endocytosis is a presynaptic homeostatic mechanism to correct for intrinsic dysfunction in ASD neurons.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".