Sex differences in neuro(auto)immunity and chronic sciatic nerve pain
Bibliographic record
Abstract
Chronic pain occurs with greater frequency in women, with a parallel sexually dimorphic trend reported in sufferers of many autoimmune diseases. There is a need to continue examining neuro-immune-endocrine crosstalk in the context of sexual dimorphisms in chronic pain. Several phenomena in particular need to be further explored. In patients, autoantibodies to neural antigens have been associated with sensory pathway hyper-excitability, and the role of self-antigens released by damaged nerves remains to be defined. In addition, specific immune cells release pro-nociceptive cytokines that directly influence neural firing, while T lymphocytes activated by specific antigens secrete factors that either support nerve repair or exacerbate the damage. Modulating specific immune cell populations could therefore be a means to promote nerve recovery, with sex-specific outcomes. Understanding biological sex differences that maintain, or fail to maintain, neuroimmune homeostasis may inform the selection of sex-specific treatment regimens, improving chronic pain management by rebalancing neuroimmune feedback. Given the significance of interactions between nerves and immune cells in the generation and maintenance of neuropathic pain, this review focuses on sex differences and possible links with persistent autoimmune activity using sciatica as an example.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".