Neuropilin 1 Directly Interacts with Fer Kinase to Mediate Semaphorin 3A-induced Death of Cortical Neurons
Bibliographic record
Abstract
Neuropilins (NRPs) are receptors for the major chemorepulsive axonal guidance cue semaphorins (Sema). The interaction of Sema3A/NRP1 during development leads to the collapse of growth cones. Here we show that Sema3A also induces death of cultured cortical neurons through NRP1. A specific NRP1 inhibitory peptide ameliorated Sema3A-evoked cortical axonal retraction and neuronal death. Moreover, Sema3A was also involved in cerebral ischemia-induced neuronal death. Expression levels of Sema3A and NRP1, but not NRP2, were significantly increased early during brain reperfusion following transient focal cerebral ischemia. NRP1 inhibitory peptide delivered to the ischemic brain was potently neuroprotective and prevented the loss of motor functions in mice. The integrity of the injected NRP1 inhibitory peptide into the brain remained unchanged, and the intact peptide permeated the ischemic hemisphere of the brain as determined using MALDI-MS-based imaging. Mechanistically, NRP1-mediated axonal collapse and neuronal death is through direct and selective interaction with the cytoplasmic tyrosine kinase Fer. Fer RNA interference effectively attenuated Sema3A-induced neurite retraction and neuronal death in cortical neurons. More importantly, down-regulation of Fer expression using Fer-specific RNA interference attenuated cerebral ischemia-induced brain damage. Together, these studies revealed a previously unknown function of NRP1 in signaling Sema3A-evoked neuronal death through Fer in cortical 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) | 0.000 | 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 | 0.001 |
| 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".