Nerve growth factor induces P2X<sub>3</sub> expression in sensory neurons
Bibliographic record
Abstract
Glial cell line-derived neurotrophic factor (GDNF) and nerve growth factor (NGF) are neuroprotective for subpopulations of sensory neurons and thus are candidates for pain treatment. However, delivering these factors to damaged neurons will invariably result in undamaged systems also being treated, with possible consequences for sensory processing. In sensory neurons the purinergic receptor P2X(3) is found predominantly in GDNF-sensitive nociceptors. ATP signalling via the P2X(3) receptor may contribute to pathological pain, suggesting an important role for this receptor in regulating nociceptive function. We therefore investigated the effects of intrathecal GDNF or NGF on P2X(3) expression in adult rat spinal cord and dorsal root ganglia (DRG). In control spinal cords, P2X(3) expression was restricted to a narrow band of primary afferent terminals within inner lamina II (II(i)). Glial cell line-derived neurotrophic factor treatment increased P2X(3) immunoreactivity within lamina II(i) but not elsewhere in the cord. Nerve growth factor treatment, however, induced novel P2X(3) expression, with intense immunoreactivity in axons projecting to lamina I and outer lamina II and to the ventro-medial afferent bundle beneath the central canal. In the normal DRG, we found a greater proportion of P2X(3)-positive neurons at cervical levels, many of which were large-diameter and calcitonin gene-related peptide-positive. In both cervical and lumbar DRG, the number of P2X(3)-positive cells increased following GDNF or NGF treatment. De novo expression of P2X(3) in NGF-sensitive nociceptors may contribute to chronic inflammatory pain.
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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".