Re-evaluation of antimalarials in treating rheumatic diseases: re-appreciation and insights into new mechanisms of action
Bibliographic record
Abstract
PURPOSE OF REVIEW: Whereas antimalarials have been in use to treat rheumatic disease for over 50 years, their exact mechanism of action remains unclear. Over the past decade, new theories have been proposed in this regard both for rheumatic disease, as well as related conditions. RECENT FINDINGS: Whereas the classical explanation was an impairment of phago/lysosomal function, antimalarials also appear to have an impact through inhibition of intracellular toll-like receptors (TLRs), particularly TLR9. This may mediate its effect on lupus, rheumatoid arthritis, as well as ancillary conditions including diabetes and hyperlipidemia. The potential role for antimalarials in antiphospholipid syndrome also appears clearer, with an effect proposed through Annexin5 binding. SUMMARY: Despite their established clinical utility, the mode of action for antimalarials remains uncertain despite recent advances and still requires further investigation. By better understanding how antimalarials function, their optimal use in the clinical setting can be ensured.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".