Involvement of ERK Phosphorylation of Trigeminal Spinal Subnucleus Caudalis Neurons in Thermal Hypersensitivity in Rats with Infraorbital Nerve Injury
Bibliographic record
Abstract
To evaluate the involvement of the mitogen-activated protein kinase (MAPK) cascade in orofacial neuropathic pain mechanisms, this study assessed nocifensive behavior evoked by mechanical or thermal stimulation of the whisker pad skin, phosphorylation of extracellular signal-regulated kinase (ERK) in trigeminal spinal subnucleus caudalis (Vc) neurons, and Vc neuronal responses to mechanical or thermal stimulation of the whisker pad skin in rats with the chronic constriction nerve injury of the infraorbital nerve (ION-CCI). The mechanical and thermal nocifensive behavior was significantly enhanced on the side ipsilateral to the ION-CCI compared to the contralateral whisker pad or sham rats. ION-CCI rats had an increased number of phosphorylated ERK immunoreactive (pERK-IR) cells which also manifested NeuN-IR but not GFAP-IR and Iba1-IR, and were significantly more in ION-CCI rats compared with sham rats following noxious but not non-noxious mechanical stimulation. After intrathecal administration of the MEK1 inhibitor PD98059 in ION-CCI rats, the number of pERK-IR cells after noxious stimulation and the enhanced thermal nocifensive behavior but not the mechanical nocifensive behavior were significantly reduced in ION-CCI rats. The enhanced background activities, afterdischarges and responses of wide dynamic range neurons to noxious mechanical and thermal stimulation in ION-CCI rats were significantly depressed following i.t. administration of PD98059, whereas responses to non-noxious mechanical and thermal stimulation were not altered. The present findings suggest that pERK-IR neurons in the Vc play a pivotal role in the development of thermal hypersensitivity in the face following trigeminal nerve injury.
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 | 0.000 | 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".