Identification of the pre-Bötzinger complex inspiratory center in calibrated “sandwich” slices from newborn mice with fluorescent Dbx1 interneurons
Bibliographic record
Abstract
Inspiratory active pre-Bötzinger complex (preBötC) networks produce the neural rhythm that initiates and controls breathing movements. We previously identified the preBötC in the newborn rat brainstem and established anatomically defined transverse slices in which the preBötC remains active when exposed at one surface. This follow-up study uses a neonatal mouse model in which the preBötC as well as a genetically defined class of respiratory interneurons can be identified and selectively targeted for physiological recordings. The population of glutamatergic interneurons whose precursors express the transcription factor Dbx1 putatively comprises the core respiratory rhythmogenic circuit. Here, we used intersectional mouse genetics to identify the brainstem distribution of Dbx1-derived neurons in the context of observable respiratory marker structures. This reference brainstem atlas enabled online histology for generating calibrated sandwich slices to identify the preBötC location, which was heretofore unspecified for perinatal mice. Sensitivity to opioids ensured that slice rhythms originated from preBötC neurons and not parafacial respiratory group/retrotrapezoid nucleus (pFRG/RTN) cells because opioids depress preBötC, but not pFRG/RTN rhythms. We found that the preBötC is centered ~0.4 mm caudal to the facial motor nucleus in this Cre/lox reporter mouse during postnatal days 0-4. Our findings provide the essential basis for future optically guided electrophysiological and fluorescence imaging-based studies, as well as the application of other Cre-dependent tools to record or manipulate respiratory rhythmogenic neurons. These resources will ultimately help elucidate the mechanisms that promote respiratory-related oscillations of preBötC Dbx1-derived neurons and thus breathing.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".