Automatic Postural Responses Are Delayed by Pyridoxine-Induced Somatosensory Loss
Bibliographic record
Abstract
Pyridoxine given in large doses is thought to destroy selectively the large-diameter peripheral sensory nerve fibers, leaving motor fibers intact. This study examined the effects of pyridoxine-induced somatosensory loss on automatic postural responses to sudden displacements of the support surface in the standing cat. Two cats were trained to stand on four force plates mounted on a movable platform. They were given pyridoxine (350 mg/kg, i.p.) on 2 successive days (0 and 1). Electromyographic (EMG) activity was recorded from selected hindlimb muscles during linear ramp-and-hold platform displacements in each of 12 directions at 15 cm/sec. In control trials onset latencies of evoked activity in hindlimb flexor and extensor muscles ranged from 40 to 65 msec after the onset of platform acceleration. After injection the EMG latencies increased over days, becoming two to three times longer than controls by day 7. Excursions of the body center of mass (CoM) in the direction opposite to that of platform translation were significantly greater at day 7 compared with controls, and the time at which the CoM subsequently reversed direction was delayed. Both animals were ataxic from day 2 onward. Histological analysis of cutaneous and muscle nerves in the hindlimb revealed a significant loss of fibers in the group I range. Our results suggest that large afferent fibers are critical for the timing of automatic postural responses to ensure coordinated control of the body CoM and balance after unexpected disturbances of the support surface.
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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 | 0.001 |
| 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".