Netrin-1 Promotes Excitatory Synaptogenesis between Cortical Neurons by Initiating Synapse Assembly
Bibliographic record
Abstract
Netrin-1 is a secreted protein that directs long-range axon guidance during early stages of neural circuit formation and continues to be expressed in the mammalian forebrain during the postnatal period of peak synapse formation. Here we demonstrate a synaptogenic function of netrin-1 in rat and mouse cortical neurons and investigate the underlying mechanism. We report that netrin-1 and its receptor DCC are widely expressed by neurons in the developing mammalian cortex during synapse formation and are enriched at synapses in vivo. We detect DCC protein distributed along the axons and dendrites of cultured cortical neurons and provide evidence that newly translated netrin-1 is selectively transported to dendrites. Using gain and loss of function manipulations, we demonstrate that netrin-1 increases the number and strength of excitatory synapses made between developing cortical neurons. We show that netrin-1 increases the complexity of axon and dendrite arbors, thereby increasing the probability of contact. At sites of contact, netrin-1 promotes adhesion, while locally enriching and reorganizing the underlying actin cytoskeleton through Src family kinase signaling and m-Tor-dependent protein translation to locally cluster presynaptic and postsynaptic proteins. Finally, we demonstrate using whole-cell patch-clamp electrophysiology that netrin-1 increases the frequency and amplitude of mEPSCs recorded from cortical pyramidal neurons. These findings identify netrin-1 as a synapse-enriched protein that promotes synaptogenesis between mammalian 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 | 0.001 |
| 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".