TNF-α mediated upregulation of NaV1.7 currents in rat dorsal root ganglion neurons is independent of CRMP2 SUMOylation
Bibliographic record
Abstract
Abstract Clinical and preclinical studies have shown that patients with Diabetic Neuropathy Pain (DNP) present with increased tumor necrosis factor alpha (TNF-α) serum concentration, whereas studies with diabetic animals have shown that TNF-α induces an increase in NaV1.7 sodium channel expression. This is expected to result in sensitization of nociceptor neuron terminals, and therefore the development of DNP. For further study of this mechanism, dissociated dorsal root ganglion (DRG) neurons were exposed to TNF-α for 6 h, at a concentration equivalent to that measured in STZ-induced diabetic rats that developed hyperalgesia. Tetrodotoxin sensitive (TTXs), resistant (TTXr) and total sodium current was studied in these DRG neurons. Total sodium current was also studied in DRG neurons expressing the collapsin response mediator protein 2 (CRMP2) SUMO-incompetent mutant protein (CRMP2-K374A), which causes a significant reduction in NaV1.7 membrane cell expression levels. Our results show that TNF-α exposure increased the density of the total, TTXs and TTXr sodium current in DRG neurons. Furthermore, TNF-α shifted the steady state activation and inactivation curves of the total and TTXs sodium current. DRG neurons expressing the CRMP2-K374A mutant also exhibited total sodium current increases after exposure to TNF-α, indicating that these effects were independent of SUMOylation of CRMP2. In conclusion, TNF-α sensitizes DRG neurons via augmentation of whole cell sodium current. This may underlie the pronociceptive effects of TNF-α and suggests a molecular mechanism responsible for pain hypersensitivity in diabetic neuropathy patients.
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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".