ABSTRACTS FROM THE INTERNATIONAL UNDERGRADUATE MEDICAL RESEARCH CONFERENCE 2022 (PPS-PPE)
Bibliographic record
Abstract
Activation of sensory afferents in one leg has been known to elicit motor responses on the opposite side of the body.This is a type of reflex movement defined as crossed reflex, and it has been examined extensively using cat and human models.Interneurons known as commissural interneurons, whose axons cross the midline of the spinal cord to the contralateral side, also have been described using cat models.However, the role of these commissural pathways and the type of sensory signals they transmit during the crossed reflex remain obscure in mice.This research aimed to present a detailed analysis of the mechanisms underlying sensory signal transmission to the contralateral limb in mice using electrophysiological approach.This was done by using in vivo stimulations of the left peroneal nerve combined with simultaneous electromyogram recordings from multiple muscles of the right leg.We show that left peroneal nerve stimulation evoked motor responses in all recorded muscles of the right leg.These responses are mediated by a combination of proprioceptive and cutaneous sensory afferents.Furthermore, we also conducted bilateral stimulations of the left peroneal and right sural nerves to look for inhibitory crossed pathway, which was found previously using different nerves (Laflamme and Akay, 2018).We provide evidence for an inhibitory pathway in the crossed reflex controlling the activity of some, but not all recorded muscles.The cutaneous sensory afferents possibly mediate these inhibitory pathways.Overall, this research project provides a detailed analysis for excitatory, as well as inhibitory crossed reflex pathways transduced by sensory signals from peroneal nerve stimulations.The data presented contribute to the understanding of crossed reflexes in wild-type mice, and will pave the way for future studies to use transgenic mice in an effort to map out the spinal circuitries involved in such processes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.581 | 0.431 |
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".