Characterization of presynaptic septin complexes in mammalian hippocampal neurons
Bibliographic record
Abstract
Septins are GTPases that form heteromeric complexes and are linked to neurological disorders. Although several septin subcomplexes have been reported in various mammalian tissues, the cellular and subcellular distribution of these complexes is largely unexplored. Using antibodies against ten mammalian septins, we show that septins diverge with respect to their tissue distribution implying that septin complexes in various tissues have unique composition. Although all ten septins examined were expressed in brain tissue, we describe septin complex(es) including SEPT3, SEPT5, SEPT6, SEPT7 and SEPT11 that could be functional within the presynapse because, unlike other septins they: (1) showed an increase in expression from embryonic day 15 to post-natal day 70, (2) were abundantly expressed in axons and growth cones of developing hippocampal neurons, (3) were found in presynaptic terminals of mature synapses, (4) were enriched in a preparation of synaptic vesicles and (5) immunoprecipitated together from brain tissue and cultured nerve cells. Knockdown of SEPT5 or SEPT7 in developing hippocampal neurons impaired axon growth. Because septins are functionally linked to the cytoskeleton and vesicle traffic, presynaptic neuronal septin complexes could be important for ensuring proper axon development and neurotransmitter release.
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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 | 0.001 | 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".