The Role of Complement in Autoimmune Disease-Associated Thrombotic Microangiopathy and the Potential for Therapeutics
Bibliographic record
Abstract
The complement system is a tightly regulated, cascading protein network representing a key component linking the innate and humoral immune systems. However, if misdirected or dysregulated, it can be similarly damaging to host-tissue. The role of complement dysregulation on vascular endothelial cells has been well established in atypical hemolytic uremic syndrome (aHUS), a thrombotic microangiopathy (TMA) characterized by microangiopathic hemolytic anemia, thrombocytopenia, and target organ injury. Yet, a great deal of complexity exists around the role of complement in TMA associated with other diseases. A further complicating factor is the cross-talk between complement, neutrophils, and coagulation pathways in the pathophysiology of TMA. Advancements in the understanding of the etiopathogenesis of aHUS paved the way for the successful development of anticomplement therapies (complement C5 inhibitors), which have revolutionized the treatment of aHUS. Therefore, a clearer understanding of the role of the complement system in TMA associated with other conditions will help to identify patients who would benefit from these therapies. This review aims to provide an assessment of the nature and extent of complement involvement in TMA associated with autoimmune diseases such as systemic lupus erythematosus, antiphospholipid syndrome, and scleroderma renal crisis. Defining the role of complement in TMA in these conditions will help to guide timely diagnosis and management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".