Medullary tachykinin precursor 1 neurons promote rhythmic breathing
Bibliographic record
Abstract
Rhythmic breathing is generated by neural circuits located in the brainstem. At its core is the preBötzinger Complex (preBötC), a region of the medulla, necessary for the generation of rhythmic breathing in mammals. The preBötC is comprised of various neuronal populations expressing neurokinin-1 receptors, the cognate G-protein-coupled receptor of the neuropeptide substance P (encoded by the tachykinin precursor 1 or Tac1 ). Neurokinin-1 receptors are highly expressed in the preBötC and destruction or deletion of neurokinin-1 receptor-expressing preBötC neurons severely impair rhythmic breathing. Although, the application of substance P to the preBötC stimulates breathing in rodents, substance P is also involved in nociception and locomotion in various brain regions, suggesting that Tac1 neurons found in the preBötC may have diverse functional roles. Here, we characterized the role of Tac1 -expressing preBötC neurons in the generation of rhythmic breathing in vivo, as well as motor behaviors. Using a cre-lox recombination approach, we injected adeno-associated virus containing the excitatory channelrhodopsin-2 ChETA in the preBötC region of Tac1 -cre mice. Employing a combination of histological, optogenetics, respiratory, and behavioral assays, we showed that stimulation of glutamatergic or Tac1 preBötC neurons promoted rhythmic breathing in both anesthetized and freely moving animals, but also triggered locomotion and overcame respiratory depression by opioid drugs. Overall, our study identified a population of excitatory preBötC with major roles in rhythmic breathing and behaviors.
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 | 0.001 |
| 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".