Fatigue in inflammatory rheumatic disorders: pathophysiological mechanisms
Bibliographic record
Abstract
Today, inflammatory rheumatic disorders are effectively treated, but many patients still suffer from residual fatigue. This work presents pathophysiological mechanisms of fatigue. First, cytokines can interfere with neurotransmitter release at the preterminal ending. Second, a long-term increase in serum concentrations of proinflammatory cytokines increase the uptake and breakdown of monoamines (serotonin, noradrenaline and dopamine). Third, chronic inflammation can also decrease monoaminergic neurotransmission via oxidative stress (oxidation of tetrahydrobiopterin [BH4]). Fourth, proinflammatory cytokines increase the level of enzyme indoleamine-2, 3-dioxygenase activity and shunt tryptophan away from the serotonin pathway. Fifth, oxidative stress stimulates astrocytes to inhibit excitatory amino acid transporters. Sixth, astrocytes produce kynurenic acid that acts as an antagonist on the α7-nicotinic acetylcholine receptor to inhibit dopamine release. Jointly, these actions result in increased glutamatergic and decreased monoaminergic neurotransmission. The above-described pathophysiological mechanisms negatively affect brain functioning in areas that are involved in fatigue.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".