Analysis of Reference Cigarette Smoke Yield Data From 21 Laboratories for 28 Selected Analytes as a Guide to Selection of New Coresta Recommended Methods
Notice bibliographique
Résumé
Abstract Since 1999, the CORESTA Special Analytes Sub Group (SPA SG) has been working on the development of CORESTA Recommended Methods (CRMs) for the analysis of cigarette smoke components. All CRMs have been posted on the CORESTA website and several associated papers published. In this study, 21 laboratories shared data and in-house methodologies for 28 additional smoke components of regulatory interest to prioritise the development of further CRMs. Laboratories provided data, where available, from CORESTA monitor test pieces (CM6 and CM7) and Kentucky Reference Cigarettes (1R5F / 3R4F) covering the period 2010-2012 obtained under both the ISO 3308 and Health Canada Intense regimes. Scant data were available on the CORESTA monitor test pieces and the Kentucky 1R5F reference. The greatest amount of data was obtained on the Kentucky 3R4F and this was used in the analyses described in this paper. SPA SG discussions provided invaluable insight into identifying causes and ways of reducing inter-laboratory variability which will be investigated in joint experiments before embarking on final collaborative studies using draft CRMs to obtain mean yields, repeatability and reproducibility values. Phenolic compounds (phenol, 3 cresol isomers, hydroquinone, catechol and resorcinol) gave consistent results by liquid chromatography (LC) separation and fluorescence detection after extracting collected “tar” on a Cambridge filter pad (CFP). Yields were similar to those obtained by a derivatisation method followed by gas chromatography - mass spectrometry (GC-MS) analysis. Similar ratios of phenols were also obtained from each method. Of the 28 studied analytes, the between-laboratory variability was lowest for the phenols. Hydrogen cyanide was derivatised using various reagents and the colour development measured after continuous flow analysis (CFA) by ultra-violet absorbance. Although, methodologies gave reasonably consistent results, investigations on the trapping system and on differences in the application of the various colour complexes used for quantification with UV absorbance is required. Ammonia analysis was carried out by ion chromatography (IC) followed by conductivity measurement and gave very similar results between laboratories. Yields were similar to those obtained by a derivatisation method followed by LC/MS-MS methodology. Optimal conditions for the separation of ammonium from interfering ions and minimizing artefactual ammonia formation from other smoke components need to be addressed during standardisation. Aromatic amine methods involved either LC/MS-MS separation and detection or derivatisation by one of two main reagents followed by GC-MS analysis. Yields were at similar but variable levels using these different techniques. It is currently unclear which method will be taken to a CRM. In general, four compounds were measured (1-amino naphthalene; 2-amino naphthalene; 3-amino biphenyl and 4-amino biphenyl) although two others were incorporated in methodologies used by 3 laboratories (o-anisidine and o-toluidine). Semi-volatiles (pyridine, quinoline and styrene) were often integrated with the selected volatiles method by measurement of the combination of CFP extracts and the contents of the impinger trapping system. Less data, obtained mainly by inductively-coupled plasma - mass spectrometry (ICP-MS), were available on metals (cadmium, lead, arsenic, beryllium, cobalt, chromium, nickel, selenium and mercury) in smoke. Trace metals were the most variable of the studied smoke analytes. Optimisation of the digestion step to remove the organic matrix needs to be addressed. As a consequence of this study and subsequent discussions within the Sub Group, it was decided to prioritise the development of CRMs for selected phenols followed by hydrogen cyanide and ammonia.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,053 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,010 | 0,005 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».