Flow cytometry to identify leukocyte sub-populations in blood and induced sputum in asthmatic and healthy volunteers exposed to diesel exhaust
Bibliographic record
Abstract
To identify five leukocyte types (in blood and induced sputum) and bronchial epithelial cells (in sputum only) using multi-colour flow cytometry in healthy and mildly asthmatic volunteers exposed to diesel exhaust. Mild asthmatics and normal controls were recruited as study subjects. This crossover study was double-blinded, randomized and counter-balanced to the order of three conditions: diesel exhaust with anti-oxidant, diesel exhaust with placebo, or filtered air with placebo. The subjects were exposed to either filtered air or diesel exhaust (300 ug PM 2.5 /m ) in a state-of-the-art diesel exhaust exposure facility. An anti-oxidant, N-acetylcysteine (600 mg), or a placebo was taken orally for five days preceding, and on the day of the exposure. Each subject was exposed to each of the three conditions. Peripheral blood samples were taken pre-exposure, and also at 2, 6, and 30 hours after the beginning of exposure. Sputum induction was performed by inhalation of hypertonic saline according to ATS guidelines pre-exposure, and also at 6, and 30 hours after the beginning of exposure. FACSCanto II (BD Biosciences) was used for flow cytometry. A 5-colour, 12-marker (CD3/CD9/CD14/CD16/CD19/CD20/CD45/CD56/CD83/CD206/CD326/HLA-DR) combination was used to identify dendritic cells, macrophages, monocytes, neutrophils, eosinophils, and bronchial epithelial cells. Direct immunolabelling was performed on whole peripheral blood. After incubation, red blood cells were lysed. Remaining cells were washed and resuspended in PBS with 0.5% paraformaldehyde. Sputum plugs were homogenized with 0.1% DTT, filtered, and then centrifuged to remove supernatant. Sputum cells were resuspended in PBS at 1 million per mL. Direct immunolabelling was performed. After incubation, cells were washed and resuspended in PBS with 0.5% paraformaldehyde. Spectral compensation for flow cytometry was performed using an automatic calibration technique (BD CompBeads). Cellular debris was eliminated on the SSC/FSC scattergram. A gating strategy was designed to identify the leukocyte sub-populations and bronchial epithelial cells. Surface markers were chosen based on differential cell-specific expression according to existing literature.
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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 | 0.000 |
| 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 | 0.001 |
| 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".