A preliminary investigation of exhaled breath from patients with celiac disease using selected ion flow tube mass spectrometry.
Bibliographic record
Abstract
BACKGROUND AND AIMS: Breath diagnostics, the measurement of volatile chemicals in human breath, is currently receiving attention as a technique for the detection of disease which, being non-invasive in nature, is particularly suited to screening for pre-symptomatic disease in healthy populations. A disorder in which more effective screening would be beneficial is celiac disease (CD), an under-diagnosed autoimmune disease of the small intestine characterized by nutritional malabsorption, which presents with diverse, and sometimes serious, symptoms. We aimed to determine whether breath analyses could be used to screen for the presence of CD. METHODS: Based on our hypotheses that malabsorption of dietary carbohydrates would lead to over production of alcohol fermentation products in the large intestine, we investigated levels of alcohols in the breath of 10 patients with CD compared to that in 10 healthy controls using selected ion flow tube mass spectrometry (SIFT-MS). RESULTS: No differences were found in the breath levels of methanol, propanol, butanol, heptanol or hexanol investigated using chemical ionization of breath air with H3O+ and/or NO+ precursor ions. In one patient, diagnosed within days of our study and not currently in receipt of any therapeutic intervention, a relatively high production of three product ions was detected compared to all other study patients. CONCLUSION: Our data suggest that breath alcohol levels are unlikely to be of diagnostic use in CD, although further investigation of those recently diagnosed with the disorder may be warranted.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".