Multiple Sclerosis and the Endogenous Opioid System
Bibliographic record
Abstract
Multiple sclerosis (MS) is an autoimmune disease characterized by chronic inflammation, neuronal degeneration and demyelinating lesions within the central nervous system. The mechanisms that underlie the pathogenesis and progression of MS are not fully known and current therapies have limited efficacy. Preclinical investigations using the murine experimental autoimmune encephalomyelitis (EAE) model of MS, as well as clinical observations in patients with MS, provide converging lines of evidence implicating the endogenous opioid system in the pathogenesis of this disease. In recent years, it has become increasingly clear that endogenous opioid peptides, binding μ- (MOR), κ- (KOR) and δ-opioid receptors (DOR), function as immunomodulatory molecules within both the immune and nervous systems. The endogenous opioid system is also well known to play a role in the development of chronic pain and negative affect, both of which are common comorbidities in MS. As such, dysregulation of the opioid system may be a mechanism that contributes to the pathogenesis of MS and associated symptoms. Here, we review the evidence for a connection between the endogenous opioid system and MS. We further explore the mechanisms by which opioidergic signaling might contribute to the pathophysiology and symptomatology of MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".