Serotonin receptor and KCC2 gene expression in lumbar flexor and extensor motoneurons posttransection with and without passive cycling
Bibliographic record
Abstract
Sacrocaudal motoneuron gene expression is altered following a spinal transection. Of interest here is the regulation of serotonin (5-HT) receptors (R), glutamate receptor, metabotropic 1 (mGluR1), and potassium-chloride cotransporter (KCC2), which mediate motoneuron excitability, locomotor recovery, and spasticity posttransection. The examination of these genes in lumbar motoneurons posttransection has not been studied, which is necessary for developing potential pharmacological interventions aimed at restoring locomotion and/or reducing spasticity. Also, if activity is to be used to promote recovery or reduce spasticity postinjury, a further examination of neuromuscular activity on gene expression posttransection is warranted. The purpose of this study was to examine motoneuronal gene expression of 5-HT receptors, KCC2, and mGluR1 at 3 mo following a complete thoracic spinal cord transection, with and without the inclusion of daily passive cycling. Physiological hindlimb extensor and flexor motoneurons were differentially identified with two retrograde fluorescent tracers, allowing for the identification and separate harvesting of extensor and flexor motoneurons with laser capture microdissection and the subsequent examination of mRNA content using quantitative RT-PCR analysis. We demonstrate that posttransection 5-HT1AR, 5-HT2CR, and mGluR1 expression was downregulated, whereas the 5-HT2AR was upregulated. These alterations in gene expression were observed in both flexor and extensor motoneurons, whereas passive cycling influenced gene expression in extensor but not flexor motoneurons. Passive cycling in extensor motoneurons further enhanced 5-HT2AR expression and increased 5-HT7R and KCC2 expression. Our results demonstrate that passive cycling influences serotonin receptor and KCC2 gene expression and that extensor motoneurons compared with flexor motoneurons may be more plastic to activity-based interventions posttransection.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".