Profile of circulating microRNAs in myalgic encephalomyelitis and their relation to symptom severity, and disease pathophysiology
Bibliographic record
Abstract
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex chronic disease, rooted in multi-system dysfunctions characterized by unexplained debilitating fatigue. Post-exertional malaise (PEM), defined as the exacerbation of the patient's symptoms following minimal physical or mental stress, is a hallmark of ME/CFS. While multiple case definitions exist, there is currently no well-established biomarkers or laboratory tests to diagnose ME/CFS. Our study aimed to investigate circulating microRNA expression in severely ill ME/CFS patients before and after an innovative stress challenge that stimulates PEM. Our findings highlight the differential expression of eleven microRNAs associated with a physiological response to PEM. The present study uncovers specific microRNA expression signatures associated with ME/CFS in response to PEM induction and reports microRNA expression patterns associated to specific symptom severities. The identification of distinctive microRNA expression signatures for ME/CFS through a provocation challenge is essential for the elucidation of the ME/CFS pathophysiology, and lead to accurate diagnoses, prevention measures, and effective treatment 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 | 0.001 |
| 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 | 0.000 |
| 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".