Sex differences in central nervous system plasticity and pain in experimental autoimmune encephalomyelitis
Bibliographic record
Abstract
Multiple sclerosis (MS) is a neurodegenerative autoimmune disease with many known structural and functional changes in the central nervous system. A well-recognized, but poorly understood, complication of MS is chronic pain. Little is known regarding the influence of sex on the development and maintenance of MS-related pain. This is important to consider, as MS is a predominantly female disease. Using the experimental autoimmune encephalomyelitis (EAE) mouse model of MS, we demonstrate sex differences in measures of spinal cord inflammation and plasticity that accompany tactile hypersensitivity. Although we observed substantial inflammatory activity in both sexes, only male EAE mice exhibit robust staining of axonal injury markers and increased dendritic arborisation in morphology of deep dorsal horn neurons. We propose that tactile hypersensitivity in female EAE mice may be more immune-driven, whereas pain in male mice with EAE may rely more heavily on neurodegenerative and plasticity-related mechanisms. Morphological and inflammatory differences in the spinal cord associated with pain early in EAE progression supports the idea of differentially regulated pain pathways between the sexes. Results from this study may indicate future sex-specific targets that are worth investigating for their functional role in pain circuitry.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".