Ephrin B/EphB in neuropathic pain: Role and molecular mechanisms
Bibliographic record
Abstract
Ephrins are protein ligands that act through the tyrosine kinase receptor family, Eph receptors. The role of ephrin/Eph in the critical processes involved in the development of the nervous system, including axon guidance and cell migration, has been well documented. Moreover, studies have shown an upregulation of ephrin B1/EphB1 and ephrin B2/EphB2 in neuropathic pain of different etiology. The activation of the ephrin B/EphB system in the dorsal root ganglion and dorsal horn of the spinal cord may be essential in initiating and maintaining neuropathic pain. Accordingly, it can be proposed that the pharmacological inhibitors of EphB receptors may be potentially employed to manage the manifestations of pain. One of the primary mechanisms involved in ephrin B/EphB-mediated synaptic plasticity includes phosphorylation and activation of NMDA receptors, which may be secondary to activation of different kinases, including MAP kinases (MAPK), protein kinase C (PKC), and Src family kinases (SFK). The other molecular mechanisms may include activation of inflammatory cytokines in the spinal cord, caspase-3, calpain-1, phosphoinositide 3-kinase (PI3K), protein kinase A (PKA), and cAMP Response Element-Binding Protein (CREB). The present review discusses the role and molecular mechanisms involved in ephrin B/EphB-mediated neuropathic pain of different etiology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".