Chemogenetic stimulation of grafted neurons and changes in spinal afferent input in paraplegic rats
Bibliographic record
Abstract
Over 2,000 yearly new cases of spinal cord injury (SCI) in Canada leave many people with reduced motor function that leads to secondary health complications. Increasing one’s ability to walk can significantly curtail these complications but there is currently no treatment for recovering locomotor function after SCI in humans. Preclinical research with rodent models was used for my studies described in this dissertation to seek a better understanding of mechanisms underlying the recovery of walking. The purpose of the first study was to examine changes in networks transmitting sensory input to motoneurons between the first and the fifth week after a complete SCI. The hypothesis that afferent input from the tibial nerve (TIB) in the lumbar segments is distributed differently after SCI was examined. A complete spinal transection injury in rats and in vivo electrophysiological measurements of evoked potentials following TIB stimulation were used. TIB afferents evoked intraspinal field potentials in the dorsal horn that showed a significant reduction in amplitude at one-week post-SCI. By five weeks post-SCI, however, TIB afferent transmission efficacy in these pathways was similar in rats without SCI. These findings suggest that TIB afferent input combined with dorsal horn neural excitability of spinal interneurons drives the reorganization needed for recovery of some walking capacity. My second study utilized a genetically modified rat model in which neurons producing serotonin (5-HT) could be activated to escalate locomotor recovery. By using grafting of embryonic 5-HT neurons below the level of SCI, we tested the hypothesis that activation of grafted 5-HT neurons by chemogenetic means in paraplegic rats improves locomotor activity (compared to rats in which only grafting was done). Behavioral analysis by kinematic and hindlimb EMG assessments during treadmill walking were performed before and after chemogenetic stimulation of grafted 5-HT cells and immunohistochemistry on spinal tissue was used to verify the targets of this stimulation. We found that locomotor cycle regularity and left-right coordination were altered. The findings suggest that selective targeting of neural subpopulations may be a better strategy for improving recovery of walking after complete SCI.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".