Serum soluble Siglec-8 in hypereosinophilic syndromes
Bibliographic record
Abstract
Abstract Siglec-8, selectively expressed on eosinophils, basophils and mast cells, is the target of novel biologics in clinical development for eosinophil and mast cell-associated disorders. Since soluble Siglec-8 (sSiglec-8) can be detected in serum and could interfere with the efficacy of biologics targeting Siglec-8, the aim of the present study is to assess sSiglec-8 levels in a large cohort of subjects with hypereosinophilic syndrome (HES). sSiglec-8 levels were quantified in serum from normal (n=9) and eosinophilic (n=123) subjects using an in-house sandwich ELISA (limit of detection: 0.5 ng/mL) and correlated with Siglec-8 expression on the surface of eosinophils (measured by flow cytometry on whole blood eosinophils gated as granulocytes CD45+CD16neg) and absolute eosinophil count (AEC). The effects of treatment were also examined. Serum levels of sSiglec-8 were undetectable in 28 subjects, did not differ between untreated HES subjects and normal donors (GM 1.23 and 1.53 ng/mL), and did not correlate either with AEC (n=123) or with Siglec-8 surface expression on blood eosinophils (n= 35). There was also no clear relationship between the clinical subtype of HES and levels of sSiglec-8. Levels measured before and after varied HES treatments in 7 subjects showed a significant decrease from 1.82 to 0.50 ng/mL (P<0.05). In contrast, serum from 8 HES patients at two different time points on no treatment showed no significant change (GM 2.35 and 2.10 ng/mL respectively). These data suggest that, despite the lack of correlation with AEC, eosinophils are a significant source of sSiglec-8 in serum. Whether serum sSiglec-8 is predominantly from tissue eosinophils or mast cells, or requires eosinophil activation, is currently under investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".