Peripheral oxygen‐sensing cells directly modulate the output of an identified respiratory central pattern generating neuron
Bibliographic record
Abstract
Breathing is an essential homeostatic behavior regulated by central neuronal networks, often called central pattern generators (CPGs). Despite ongoing advances in our understanding of the neural control of breathing, the basic mechanisms by which peripheral input modulates the activities of the central respiratory CPG remain elusive. This lack of fundamental knowledge vis-à-vis the role of peripheral influences in the control of the respiratory CPG is due in large part to the complexity of mammalian respiratory control centres. We have therefore developed a simpler invertebrate model to study the basic cellular and synaptic mechanisms by which a peripheral chemosensory input affects the central respiratory CPG. Here we report on the identification and characterization of peripheral chemoreceptor cells (PCRCs) that relay hypoxia-sensitive chemosensory information to the known respiratory CPG neuron right pedal dorsal 1 in the mollusk Lymnaea stagnalis. Selective perfusion of these PCRCs with hypoxic saline triggered bursting activity in these neurons and when isolated in cell culture these cells also demonstrated hypoxic sensitivity that resulted in membrane depolarization and spiking activity. When cocultured with right pedal dorsal 1, the PCRCs developed synapses that exhibited a form of short-term synaptic plasticity in response to hypoxia. Finally, osphradial denervation in intact animals significantly perturbed respiratory activity compared with their sham counterparts. This study provides evidence for direct synaptic connectivity between a peripheral regulatory element and a central respiratory CPG neuron, revealing a potential locus for hypoxia-induced synaptic plasticity underlying breathing behavior.
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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".