Ampakines induce a persistent increase in phrenic motor output in rats with cervical spinal cord injury
Bibliographic record
Abstract
Cervical spinal cord injury (SCI) typically interrupts descending synaptic inputs to phrenic motoneurons resulting in diaphragm paralysis and respiratory impairment. The primary bulbospinal excitatory inputs to phrenic motoneurons are glutamatergic with AMPA receptors playing a prominent role. Ampakines are a group of compounds that can enhance the function of AMPA receptors, and prior work demonstrates that these compounds can increase respiratory output during conditions associated with blunted respiratory drive. Accordingly, in ongoing studies we are testing the hypothesis that intravenous delivery of an ampakine, CX717, will trigger increases in inspiratory phrenic motor output in rats with chronic cervical contusive SCI. Bilateral phrenic nerve activity was recorded in rats that received cervical (C3) hemicontusion of the spinal cord 8 wks prior. A single dose of CX717 (30mg/kg) triggered a modest increase in phrenic inspiratory burst amplitude ipsilateral but not contralateral to the contusion injury. However, repeated doses (3 × 10mg/kg at 5min intervals) triggered a substantial and persistent increase (lasting at least 60mins) in the inspiratory burst amplitude recorded in both phrenic nerves. These results demonstrate ampakines can increase phrenic motor output after cervical SCI and may provide a new means of enhancing respiratory function after SCI. Support: Craig H. Neilsen Foundation #220521 (MSS), Parker B. Francis Fellowship (MKE), 1R01NS080180–01A1 (DDF), NIH1R21HL104294–01 (DDF)
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".