Functional Changes in Muscle Afferent Neurones in an Osteoarthritis Model: Implications for Impaired Proprioceptive Performance
Bibliographic record
Abstract
BACKGROUND: Impaired proprioceptive performance is a significant clinical issue for many who suffer osteoarthritis (OA) and is a risk factor for falls and other liabilities. This study was designed to evaluate weight-bearing distribution in a rat model of OA and to determine whether changes also occur in muscle afferent neurones. METHODOLOGY/PRINCIPAL FINDINGS: Intracellular recordings were made in functionally identified dorsal root ganglion neurones in acute electrophysiological experiments on the anaesthetized animal following measurements of hind limb weight bearing in the incapacitance test. OA rats but not naïve control rats stood with less weight on the ipsilateral hind leg (P = 0.02). In the acute electrophysiological experiments that followed weight bearing measurements, action potentials (AP) elicited by electrical stimulation of the dorsal roots differed in OA rats, including longer AP duration (P = 0.006), slower rise time (P = 0.001) and slower maximum rising rate (P = 0.03). Depolarizing intracellular current injection elicited more APs in models than in naïve muscle afferent neurones (P = 0.01) indicating greater excitability. Axonal conduction velocity in model animals was slower (P = 0.04). CONCLUSIONS/SIGNIFICANCE: The present study demonstrates changes in hind limb stance accompanied by changes in the functional properties of muscle afferent neurones in this derangement model of OA. This may provide a possible avenue to explore mechanisms underlying the impaired proprioceptive performance and perhaps other sensory disorders in people with OA.
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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) | 0.002 | 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".