Diisocyanate Antigen-stimulated Monocyte Chemoattractant Protein-1 Synthesis Has Greater Test Efficiency than Specific Antibodies for Identification of Diisocyanate Asthma
Bibliographic record
Abstract
We previously reported that diisocyanate-human serum albumin (DIISO-HSA) stimulated production of monocyte chemoattractant protein-1 (MCP-1) by peripheral blood mononuclear cells is significantly associated with a clinical diagnosis of diisocyanate asthma (DA). Others have reported that antibodies for DIISO-HSA are specific but insensitive markers of DA. This study was performed to evaluate test characteristics of the in vitro MCP-1 assay compared with DIISO-HSA-specific immunoglobulin (Ig) G and IgE in identifying workers with DA. MCP-1 was quantitated in peripheral blood mononuclear cell supernatants 48 hours after incubation with DIISO-HSA antigens. Assay results were compared with outcomes of specific inhalation challenge (SIC) testing. Nineteen of 54 (35%) workers assayed for antibodies and MCP-1 stimulation had SIC-confirmed DA. Mean MCP-1 produced by SIC-positive workers was greater than SIC-negative workers (p < or = 0.001). Diagnostic sensitivity, specificity, and test efficiency for specific IgG were 47%, 74%, and 65%, respectively, and for specific IgE were 21%, 89%, and 65%, respectively. Sensitivity, specificity, and test efficiency of the MCP-1 test were 79%, 91%, and 87%, respectively. This study indicates that the MCP-1 stimulation assay has greater sensitivity and specificity than the specific antibody assays in correctly identifying DA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".