Graded hypoxia acts through a network of distributed peripheral oxygen chemoreceptors to produce changes in respiratory behaviour and plasticity
Bibliographic record
Abstract
Respiratory behaviour relies critically upon sensory feedback from peripheral oxygen chemoreceptors. During environmental or systemic hypoxia, chemoreceptor input modulates respiratory central pattern generator activity to produce reflex-based increases in respiration and also shapes respiratory plasticity over longer timescales. The best-studied oxygen chemoreceptors are undoubtedly the mammalian carotid bodies; however, questions remain regarding this complex organ's role in shaping respiration in response to varying oxygen levels. Furthermore, many taxa possess distinct oxygen chemoreceptors located within the lungs, airways and cardiovasculature, but the functional advantage of multiple chemoreceptor sites is unclear. In this study, it is demonstrated that a distributed network of peripheral oxygen chemoreceptors exists in Lymnaea stagnalis and significantly modulates aerial respiration. Specifically, Lymnaea breath frequency and duration represent parameters that are shaped by interactions between hypoxic severity and its time-course. Using a combination of behaviour and electrophysiology approaches, the chemosensory pathways underlying hypoxia-induced changes in breath frequency/duration were explored. The current findings demonstrate that breath frequency is uniquely modulated by the known osphradial ganglion oxygen chemoreceptors during moderate hypoxia, while a newly discovered area of pneumostome oxygen chemoreception serves a similar function specifically during more severe hypoxia. Together, these findings suggest that multiple oxygen chemosensory sites, each with their own sensory and modulatory properties, act synergistically to form a functionally distributed network that dynamically shapes respiration in response to changing systemic or environmental oxygen levels. These distributed networks may represent an evolutionarily conserved strategy vis-à-vis respiratory adaptability and have significant implications for the understanding of fundamental respiratory control systems.
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 | 0.000 |
| 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".