Neuronal SNAP-23 scales hippocampal synaptic plasticity and memory
Bibliographic record
Abstract
Summary Soluble NSF Attachment protein REceptor (SNARE)-mediated membrane fusion plays a crucial role not only in presynaptic vesicle exocytosis but also in postsynaptic receptor delivery. The latter is considered particularly important for long-term synaptic plasticity and learning and memory, yet underlying mechanisms including the identity of the key SNARE proteins remain elusive. Here, we investigate the role of neuronal Synaptosomal-Associated Protein-23 (SNAP-23) by analyzing pyramidal-neuron specific SNAP-23 conditional knockout (cKO) mice. SNAP-23 immunostaining in postsynaptic spines was effectively decreased in the SNAP-23 cKO hippocampus. Electrophysiological analysis of SNAP-23 deficient neurons using acute hippocampal slices showed normal basal neurotransmission in CA3-CA1 synapses with unchanged AMPA and NMDA currents. Nevertheless, we found theta-burst stimulation induced long-term potentiation (LTP) was vastly diminished in SNAP-23 cKO. Moreover, unlike syntaxin-4 cKO mice in which both basal neurotransmission and LTP decrease manifested changes in a broad set of behavioral tasks, deficits of SNAP-23 cKO is more limited to spatial memory. Our data reveal that neuronal SNAP-23 is selectively crucial for synaptic plasticity and spatial memory without affecting basal glutamate receptor function.
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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) | 0.002 | 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".