Bibliographic record
Abstract
PURPOSE OF REVIEW: Warm autoimmune hemolytic anemia (wAIHA) is the most common of the immune hemolytic anemias. Although there are numerous case reports and reviews regarding this condition, some of the unusual and more recent findings have not been fully defined and may be contentious. This review will provide insight into the common specificity of the warm autoantibodies and hypothesize a novel mechanism of wAIHA, that is proposed to be linked to the controversial subject of red blood cell senescence. RECENT FINDINGS AND HYPOTHESES: It is now well established that band 3 on the red blood cell is the main target of autoantibodies in wAIHA. wAIHA targets the older red blood cells (RBCs) in about 80% of cases and, recently, it has been shown that the RBCs in these patients are aging faster than normal. It has been proposed that in these 80% of patients, that the autoantibody recognizes the senescent red blood cell antigen on band 3. It is further hypothesized that this autoantibody's production and potency has been exacerbated by hypersensitization to the RBC senescent antigen, which is processed through the adaptive immune system to create the pathogenic autoantibody. Recent publications have supported previous data that the senescent RBC antigen is exposed via a dynamic process, wherein oscillation of a band 3 internal loop flipping to the cell surface, creates a conformational neoantigen that is the RBC senescent antigen. It has also recently been shown that the cytokine profile in patients with wAIHA favors production of inflammatory cytokines/chemokines that includes interleukin-8 which can activate neutrophils to increase the oxidative stress on circulating RBCs to induce novel antigens, as has been postulated to favour exposure of the senescent RBC antigen. SUMMARY: This manuscript reviews new findings and hypotheses regarding wAIHA and proposes a novel mechanism active in most wAIHA patients that is due to an exacerbation of normal RBC senescence.
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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 | 0.002 |
| 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".