Widespread use of serological tests for tuberculosis: data from 22 high-burden countries: Table 1–
Bibliographic record
Abstract
In summary, we show for the first time that the absence of a trident peak at 7 ppm in NMR spectra of EBC, related to ammonium, is associated with asthma.The loss of ammonium reflects reduced ammonia synthesis due to downregulation of glutaminase, leading to impaired acid neutralisation.Surprisingly, despite a very strong association in our study, this signature was not noted in the seminal study by CARRARO et al.[2], who first described the use of NMR spectroscopy of EBC in asthma.Only spectra between 1 and 4 ppm were shown in their study.One possibility for the observed differences is that CARRARO et al.[2] used a reusable collection system.It is possible, as suggested by IZQUIERDO-GARCı ´A et al. [4], that the use of disinfectants in reusable collection systems may create artefacts, cleaning of which may in turn obscure some parts of the spectra.As we use a completely disposable tube for EBC collection, with only a chilled external metal sleeve being reused, there is no possibility of such contamination in our data.It was additionally confirmed that EBC spectra including the 7 ppm peaks were distinct from deuterated water condensate collected from identical tubes.Furthermore, independent previous reports of ammonia and ammonium being reduced in asthma corroborate our findings [5, 9].The small number of controls in our study, particularly of children, limits our study and further studies are needed to establish the usefulness of our finding.Also, it appears likely that the ammonium signature is enhanced by acidic load on the airway, which may vary across geographical regions.This study was conducted in Delhi, India, where ambient air contains high sulphuric and nitric oxides.Applicability of our finding to less polluted regions needs to be tested.However, despite this, our data hopefully removes the need for any further debate regarding whether valid and useful NMR spectra can be obtained for EBC [4].This nascent field holds much potential for translation, and concerted efforts of many investigators are needed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".