Neuro-immune crosstalk in depressive symptoms of multiple sclerosis
Bibliographic record
Abstract
Depressive disorders can occur in up to 50% of people with multiple sclerosis in their lifetime. If left untreated, comorbid major depressive disorders may not spontaneously remit and is associated with an increased morbidity and mortality. Conversely, epidemiological evidence supports increased psychiatric visit as a significant prodromal event prior to diagnosis of MS. Are there common molecular pathways that contribute to the co-development of MS and psychiatric illnesses? We discuss immune cells that are dysregulated in MS and how such dysregulation can induce or protect against depressive symptoms. This is not meant to be a comprehensive review of all molecular pathways but rather a framework to guide future investigations of immune responses in depressed versus euthymic people with MS. Currently, there is weak evidence supporting the use of antidepressant medication in comorbid MS patients. It is our hope that by better understanding the neuroimmune crosstalk in the context of depression in MS, we can enhance the potential for future therapeutic options.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
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".