Quantification of S100A12 (EN‐RAGE) in Blood Varies with Sampling Method, Calcium and Heparin
Bibliographic record
Abstract
S100A12 is a calcium-binding protein predominantly found in neutrophil granulocytes and monocytes. Its usefulness in monitoring inflammatory disease states depends on documentation that assay results are reliable. This study aimed at defining guidelines for blood sampling, selection of optimal material handling and reference intervals in healthy controls while taking into account the basic features of S100A12. An enzyme linked immunosorbent assay was developed based upon antibodies induced in rabbits by injection of recombinant S100A12. Our studies confirm that oligomers of S100A12 are generated in the presence of calcium. Structural changes in S100A12 mediated by calcium influence the interaction with antibody. This is proposed as the background for our very low readings of S100A12 in Ethylene Diamine Tetraacetic Acid (EDTA) plasma. Individual S100A12 levels did not change substantially over a 5-week sampling period. Based upon testing of 150 blood donors we suggest reference intervals of S100A12 in serum to be 49-1340 microg/l for women and 27-1750 microg/l for men. The estimated mean concentrations were 234 microg/l in serum samples (range 12-15791), 114 microg/l (range 3-17282) in re-calcified EDTA plasma and 48 microg/l (range 2-14843) in heparin plasma. Without adding calcium to EDTA plasma before running the assay, concentrations were around 2 microg/l (16 persons). S100A12 quantification is assumed to become relevant for diagnostic use in many disease states. The importance of the handling and analysing conditions for a reliable result was examined. We recommend serum collected in gel-containing tubes as the preferred sample material and have suggested reference intervals for healthy individuals.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".