Delayed Onset of Changes in Soma Action Potential Genesis in Nociceptive A-Beta DRG Neurons in Vivo in a Rat Model of Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Clinical data on osteoarthritis (OA) suggest widespread changes in sensory function that vary during the progression of OA. In previous studies on a surgically-induced animal model of OA we have observed that changes in structure and gene expression follow a variable trajectory over the initial days and weeks. To investigate mechanisms underlying changes in sensory function in this model, the present electrophysiological study compared properties of primary sensory nociceptive neurons at one and two months after model induction with properties in naïve control animals. Pilot data indicated no difference in C- or Adelta-fiber associated neurons and therefore the focus is on Abeta-fiber nociceptive neurons. RESULTS: At one month after unilateral derangement of the knee by cutting the anterior cruciate ligament and removing the medial meniscus, the only changes observed in Abeta-fiber dorsal root ganglion (DRG) neurons were in nociceptor-like unresponsive neurons bearing a hump on the repolarization phase; these changes consisted of longer half width, reflecting slowed dynamics of AP genesis, a depolarized Vm and an increased AP amplitude. At two months, changes observed were in Abeta-fiber high threshold mechanoreceptors, which exhibited shorter AP duration at base and half width, shorter rise time and fall time, and faster maximum rising rate/maximum falling rate, reflecting accelerated dynamics of AP genesis. CONCLUSION: These data indicate that Abeta nociceptive neurons undergo significant changes that vary in time and occur later than changes in structure and in nociceptive scores in this surgically induced OA model. Thus, if changes in Abeta-fiber nociceptive neurons in this model reflect a role in OA pain, they may relate to mechanisms underlying pain associated with advanced OA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".