Temporal and spatial patterns of Kv1.1 and Kv1.2 protein and gene expression in spinal cord white matter after acute and chronic spinal cord injury in rats: implications for axonal pathophysiology after neurotrauma
Bibliographic record
Abstract
After spinal cord injury (SCI), surviving white matter axons display axonal dysfunction associated with demyelination and altered K+ channel activity. To clarify the molecular basis of posttraumatic axonal pathophysiology after SCI, we investigated the changes in expression and distribution of the axonal K+ channel subunits Kv1.1 and Kv1.2 in spinal cord white matter after in vivo SCI in the rat. Using Western blot analysis, we found an increased expression of Kv1.1 and Kv1.2 at 2 and 6 weeks after SCI. By real-time PCR we observed an increase in Kv1.1 and Kv1.2 mRNA levels 1 day after SCI, which persisted until 6 weeks. Confocal immunohistochemistry showed a markedly dispersed labelling of Kv1.1 and Kv1.2 along the injured axons, in contrast to the tight localization of these channels to the juxtaparanodes of noninjured axons. This redistribution of Kv1.1 and Kv1.2 occurred as early as 1 h postinjury along some injured axons, and persisted at 6 weeks postinjury. In parallel with the redistribution of Kv1.1 and 1.2, contactin-associated protein (Caspr), which is normally confined to a paranodal location, also displayed a more diffuse distribution along the injured spinal cord axons. Our results suggest that the increased expression of Kv1.1 and Kv1.2 proteins is transcriptionally regulated. In contrast, the redistribution of the axonal K+ channel subunits occurs very early postinjury and probably reflects a disruption of the juxtaparanodal axonal region due to physical trauma, as shown by altered localization of Caspr.
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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 | 0.001 | 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) | 0.001 | 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".