Cancer pain and neuropathic pain are associated with A <b> <i>β</i> </b> sensory neuronal plasticity in dorsal root ganglia and abnormal sprouting in lumbar spinal cord
Bibliographic record
Abstract
Evidence suggests that there are both nociceptive and neuropathic components of cancer-induced pain. We have observed that changes in intrinsic membrane properties and excitability of normally non-nociceptive Aβ sensory neurons are consistent in rat models of peripheral neuropathic pain and cancer-induced pain. This has prompted a comparative investigation of the intracellular electrophysiological characteristics of sensory neurons and of the ultrastructural morphology of the dorsal horn in rat models of neuropathic pain and cancer-induced pain. Neuropathic pain model rats were induced with a polyethylene cuff implanted around a sciatic nerve. Cancer-induced pain model rats were induced with mammary rat metastasis tumour-1 rat breast cancer or MATLyLu rat prostate cancer cells implanted into the distal epiphysis of a femur. Behavioural evidence of nociception was detected using von Frey tactile assessment. Aβ-fibre low threshold mechanoreceptor neurons in both cancer-induced pain and neuropathic pain models exhibited slower dynamics of action potential genesis, including a wider action potential duration and lower action potential amplitude compared to those in control animals. Enhanced excitability of Aβ-fibre low threshold mechanoreceptor neurons was also observed in cancer-induced pain and neuropathic pain models. Furthermore, both cancer-induced pain and neuropathic pain models showed abundant abnormal axonal sprouting in bundles of myelinated axons in the ipsilateral spinal laminae IV and V. The patterns of changes show consistency between rat models of cancer-induced pain and neuropathic pain. These findings add to the body of evidence that animal models of cancer-induced pain and neuropathic pain share features that may contribute to the peripheral and central sensitization and tactile hypersensitivity in both pain states.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".