Substance P Modulation of Hypoglossal Motoneuron Excitability During Development: Changing Balance Between Conductances
Bibliographic record
Abstract
Although Substance P (SP) acts primarily through neurokinin 1 (NK1) receptors to increase the excitability of virtually all motoneurons (MNs) tested, the ontogeny of this transmitter system is not known for any MN pool. Hypoglossal (XII) MNs innervate tongue protruder muscles and participate in several behaviors that must be functional from birth including swallowing, suckling and breathing. We used immunohistochemistry, Western immunoblotting, and whole cell recording of XII MNs in brain stem slices from rats ranging in age from postnatal day zero (P0) to P23 to explore developmental changes in: NK1 receptor expression; currents evoked by SP(NK1) (an NK1-selective SP receptor agonist) and; the efficacy of transduction pathways transforming ligand binding into channel modulation. Despite developmental reductions in XII MN NK1 receptor expression, SP(NK1) current density remained constant at 6.1 +/- 1.0 (SE) pA/pF. SP(NK1) activated at least two conductances. Activation of a pH-insensitive Na(+) conductance dominated in neonates (P0-P5), but its contribution fell from approximately 80 to approximately 55% in juveniles (P14-P23). SP(NK1) also inhibited a pH-sensitive, two-pore domain K(+) (TASK)-like K(+) current. Its contribution increased developmentally. First, the density of this pH-sensitive K(+) current doubled between P0 and P23. Second, SP(NK1) did not affect this current in neonates, but reduced it by 20% at P7-P10 and 80% in juveniles. In addition, potentiation of repetitive firing was greatest in juveniles. These data establish that despite apparent reductions in NK1 receptor density, SP remains an important modulator of XII MN excitability throughout postnatal development due, in part, to increased expression of a pH-sensitive, TASK-like conductance.
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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 | 0.001 |
| 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".