Ampakines Increase Spinal Respiratory Motor Output after Cervical Spinal Cord Injury in Rats
Bibliographic record
Abstract
Glutamatergic synaptic transmission is a fundamental component of the neural drive to breathe, and α‐Amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptor (AMPAR) mediated synaptic currents contribute to respiratory rhythmogenesis and respiratory motoneuron depolarization during inspiration. Ampakines are a class of synthetic compounds initially designed to enhance AMPAR‐mediated glutamatergic neurotransmission related to cognition, learning and memory. Ampakines are also a potent respiratory stimulant, particularly during conditions of suppressed respiratory motor output. While ampakines have been safely used in clinical studies, to our knowledge they have never been evaluated with respect to neurological disorders that compromise breathing, such as cervical spinal cord injury (SCI). Therefore, we aimed to test the hypothesis that ampakines increase respiratory motor output following cervical spinal cord injury. To test this hypothesis, we gave ampakine CX717 to urethane anesthetized rats (15–30 mg/kg, i.v.) with chronic (2–8 wks) cervical (C2) hemi‐section injury (C2Hx) or mid‐cervical (C3/C4) lateral contusion injury. In preliminary experiments, ampakines caused a rapid and robust increase in phrenic motor output ipsilateral to the injury and also increased contralateral phrenic motor output to a lesser extent. Responses were similar across time points post‐injury. In addition, we observed that i.v. ampakine caused a rapid change in the discharge of spinal interneurons below the spinal injury in the vicinity of the phrenic motor pool (C4). These initial results indicate that ampakine CX717 can stimulate respiratory motor output following cervical spinal cord injury, and also alters the activity of the mid‐cervical propriospinal network. Support or Funding Information Funding: 1R01NS080180‐01A1 (DF) and 1F32NS095620‐01 (KS)
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".