Syntaxin-3 is dispensable for basal neurotransmission and synaptic plasticity in postsynaptic hippocampal CA1 neurons
Bibliographic record
Abstract
Recent evidence suggests that SNARE fusion machinery play critical roles in postsynaptic neurotransmitter receptor trafficking, which is essential for synaptic plasticity. However, the key SNAREs involved remain highly controversial; syntaxin-3 and syntaxin-4 are leading candidates for the syntaxin isoform underlying postsynaptic plasticity. In a previous study, we showed that pyramidal-neuron specific conditional knockout (cKO) of syntaxin-4 significantly reduces basal transmission, synaptic plasticity and impairs postsynaptic receptor trafficking. However, this does not exclude a role for syntaxin-3 in such processes. Here, we generated and analyzed syntaxin-3 cKO mice. Extracellular field recordings in hippocampal slices showed that syntaxin-3 cKO did not exhibit significant changes in CA1 basal neurotransmission or in paired-pulse ratios. Importantly, there were no observed differences during LTP in comparison to control mice. Syntaxin-3 cKO mice performed similarly as the controls in spatial and contextual learning tasks. Consistent with the minimal effects of syntaxin-3 cKO, syntaxin-3 mRNA level was very low in hippocampal and cortex pyramidal neurons, but strongly expressed in the corpus callosum and caudate axon fibers. Together, our data suggest that syntaxin-3 is dispensable for hippocampal basal neurotransmission and synaptic plasticity, and further supports the notion that syntaxin-4 is the major isoform mediating these processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".