Neurotrophic factors and target-specific retrograde signaling interactions define the specificity of classical and neuropeptide cotransmitter release at identified Lymnaea synapses
Bibliographic record
Abstract
Many neurons concurrently and/or differentially release multiple neurotransmitter substances to selectively modulate the activity of distinct postsynaptic targets within a network. However, the molecular mechanisms that produce synaptic heterogeneity by regulating the cotransmitter release characteristics of individual presynaptic terminals remain poorly defined. In particular, we know little about the regulation of neuropeptide corelease, despite the fact that they mediate synaptic transmission, plasticity and neuromodulation. Here, we report that an identified Lymnaea neuron selectively releases its classical small molecule and peptide neurotransmitters, acetylcholine and FMRFamide-derived neuropeptides, to differentially influence the activity of distinct postsynaptic targets that coordinate cardiorespiratory behaviour. Using a combination of electrophysiological, molecular, and pharmacological approaches, we found that neuropeptide cotransmitter release was regulated by cross-talk between extrinsic neurotrophic factor signaling and target-specific retrograde arachidonic acid signaling, which converged on modulation of glycogen synthase kinase 3. In this context, we identified a novel role for the Lymnaea synaptophysin homologue as a specific and synapse-delimited inhibitory regulator of peptide neurotransmitter release. This study is among the first to define the cellular and molecular mechanisms underlying the differential release of cotransmitter substances from individual presynaptic terminals, which allow for context-dependent tuning and plasticity of the synaptic networks underlying patterned motor behaviour.
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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) | 0.000 | 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".