IgSF21 promotes differentiation of inhibitory synapses via binding to neurexin2α
Bibliographic record
Abstract
Coordinated development of excitatory and inhibitory synapses is essential for higher brain function, and impairment in this development is associated with neuropsychiatric disorders. In contrast to the large body of accumulated evidence regarding excitatory synapse development, little is known about synaptic adhesion and organization mechanisms underlying inhibitory synapse development. Through unbiased expression screens and proteomics, we identified immunoglobulin superfamily member 21 (IgSF21) as a neurexin2α-interacting membrane protein that selectively induces inhibitory presynaptic differentiation. IgSF21 localizes postsynaptically and recruits axonal neurexin2α in a trans-interaction manner. Deleting IgSF21 in mice impairs inhibitory presynaptic organization, especially in the hippocampal CA1 stratum radiatum, and also diminishes GABA-mediated synaptic transmission in hippocampal CA1 neurons without affecting their excitatory synapses. Finally, mice lacking IgSF21 show a sensorimotor gating deficit. These findings suggest that IgSF21 selectively regulates inhibitory presynaptic differentiation through interacting with presynaptic neurexin2α and plays a crucial role in synaptic inhibition in the brain.Molecular mechanisms regulating the development of inhibitory synapses are poorly understood. Here the authors show that IgSF21 interacts with neurexin2α to induce presynaptic differentiation of inhibitory synapses, and that mice lacking IgSF21 exhibit deficits in inhibitory synaptic transmission.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".