Loss of Synapse Repressor MDGA1 Enhances Perisomatic Inhibition, Confers Resistance to Network Excitation, and Impairs Cognitive Function
Bibliographic record
Abstract
Synaptopathies contributing to neurodevelopmental disorders are linked to mutations in synaptic organizing molecules, including postsynaptic neuroligins, presynaptic neurexins, and MDGAs, which regulate their interaction. The role of MDGA1 in suppressing inhibitory versus excitatory synapses is controversial based on in vitro studies. We show that genetic deletion of MDGA1 in vivo elevates hippocampal CA1 inhibitory, but not excitatory, synapse density and transmission. Furthermore, MDGA1 is selectively expressed by pyramidal neurons and regulates perisomatic, but not distal dendritic, inhibitory synapses. Mdga1 −/− hippocampal networks demonstrate muted responses to neural excitation, and Mdga1 −/− mice are resistant to induced seizures. Mdga1 −/− mice further demonstrate compromised hippocampal long-term potentiation, consistent with observed deficits in spatial and context-dependent learning and memory. These results suggest that mutations in MDGA1 may contribute to cognitive deficits through altered synaptic transmission and plasticity by loss of suppression of inhibitory synapse development in a subcellular domain- and cell-type-selective manner.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".