Dendritic spines on GABAergic neurons respond to cholinergic signaling in the <i>Caenorhabditis elegans</i> motor circuit
Bibliographic record
Abstract
SUMMARY Dendritic spines are specialized postsynaptic structures that detect and integrate presynaptic signals. The shape and number of dendritic spines are regulated by neural activity and correlated with learning and memory. Most studies of spine function have focused on the mammalian nervous system. However, spine-like protrusions have been previously reported in invertebrates, suggesting that the experimental advantages of smaller model organisms could be exploited to study the biology of dendritic spines. Here, we document the presence of dendritic spines in Caenorhabditis elegans motor neurons. We used super-resolution microscopy, electron microscopy, live-cell imaging and genetic manipulation to show that GABAergic motor neurons display functional dendritic spines. Our analysis revealed salient features of dendritic spines: (1) A key role for the actin cytoskeleton in spine morphogenesis; (2) Postsynaptic receptor complexes at the tips of spines in close proximity to presynaptic active zones; (3) Localized postsynaptic calcium transients evoked by presynaptic activity; (4) The presence of endoplasmic reticulum and ribosomes; (5) The regulation of spine density by presynaptic activity. These studies provide a solid foundation for a new experimental paradigm that exploits the power of C. elegans genetics and live-cell imaging for fundamental studies of dendritic spine morphogenesis and function. HIGHLIGHTS - Spines in C. elegans GABAergic motor neurons are enriched in actin cytoskeleton. - Spines are dynamic structures. - Spines display Ca ++ transients coupled with presynaptic activation. - Spine density is regulated during development and is modulated by actin dynamics and cholinergic signaling.
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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) | 0.001 | 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".