The Nogo Receptor Ligand LGI1 Regulates Synapse Number and Synaptic Activity in Hippocampal and Cortical Neurons
Bibliographic record
Abstract
Leucine-rich glioma-inactivated protein 1 (LGI1) is a secreted neuronal protein and a Nogo receptor 1 (NgR1) ligand. Mutations in LGI1 in humans causes autosomal dominant lateral temporal lobe epilepsy and homozygous deletion of LGI1 in mice results in severe epileptic seizures that cause early postnatal death. NgR1 plays an important role in the development of CNS synapses and circuitry by limiting plasticity in the adult cortex via the activation of RhoA. These relationships and functions prompted us to examine the effect of LGI1 on synapse formationin vitroandin vivo. We report that application of LGI1 increases synaptic density in neuronal culture and that LGI1 null hippocampus has fewer dendritic mushroom spines than in wild-type (WT) littermates. Further, our electrophysiological investigations demonstrate that LGI1 null hippocampal neurons possess fewer and weaker synapses. RhoA activity is significantly increased in cortical cultures derived from LGI1 null mice and using a reconstituted system; we show directly that LGI1 antagonizes NgR1-tumor necrosis factor receptor orphan Y (TROY) signaling. Our data suggests that LGI1 enhances synapse formation in cortical and hippocampal neurons by reducing NgR1 signaling.
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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 | 0.000 |
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".