Notice bibliographique
Résumé
We thank Dietrich and Geier for their comments and the opportunity for a deeper discussion of our work. We presented clear evidence that: (1) in human liver microsomes N-OH-PhIP is metabolized into glucuronides predominantly by UGT1A1, and (2) polymorphisms in this gene influence the carcinogen metabolism.1 We agree that no conclusions can be extrapolated regarding the general detoxification of carcinogens, and additional studies evidently are needed to extend our data to the in vivo situation regarding PhIP. Yet, we believe our study presented relevant information for genetic epidemiological studies aimed at identifying genes affecting an individual's susceptibility though dietary exposure, which was the primary aim of our study. We agree that changes in protein expression and activity at different levels of any of the components involved in the biotransformation and transport of PhIP are likely to influence exposure to N-OH-PhIP. In Fig. 1 of their letter, Dietrich and Geier draw our attention to the fact that an altered UGT1A-dependent conjugation of N-OH-PhIP would largely be compensated by other enzymes, such as UGT2 or sulfotransferases. However, this is supported by data obtained in rodents. Indeed, as elegantly demonstrated by our colleagues and others, sulfation is the major N-OH-PhIP–conjugating reaction occurring in rats,2, 3 instead of glucuronidation in humans.4-6 Consequently, alterations of UGT1A in rodents would only affect a small fraction of N-OH-PhIP metabolism, and this loss will be easily compensated by SULT enzymes.3 In addition, whereas UGT2 may play a significant role in N-OH-PhIP glucuronidation in rats,3 we and others1, 7 demonstrated that human UGT2 is not reactive with this substrate, and therefore cannot compensate for a loss of UGT1A. Thus, we emphasize the fact that mechanisms illustrated in Fig. 1 in the letter by Dietrich and Geier are valid for rodents only. After the publication of our work1 Malfatti et al. reported2 that an impaired UGT1A pathway leads to lower DNA adduct formation in the colon of rats. Lower formation of N-OH-PhIP glucuronides in the liver has the potential to decrease the exposure of the colon to N-OH-PhIP-N3-G. In fact, N-OH-PhIP-N3-G can be hydrolysed to N-OH-PhIP by bacterial β-glucuronidases and converted locally to reactive metabolites.2 As a result and consistent with our hypothesis, detoxification by UGT1A in the liver, a predominant site for PhIP metabolism via N3 glucuronidation in addition to N2G formation in humans,4 would be likely to influence the exposure to carcinogens in the intestine and the colon. Finally, we did not intend to confirm the work by Peters et al.8 but rather to concede our hypothesis. We agree that it is complex to compare the level of glucuronidation determined with human liver microsomes to the concentration of glucuronides found in human urine. However, despite the limited statistical power of Peters et al.'s study, it cannot be ignored that UGT1A1 polymorphisms were found to alter the mutagenicity of urinary dietary carcinogens in healthy volunteers. This observation strongly supports the hypothesis that in humans UGT genetic alteration influences the carcinogenic potential of PhIP exposure. Chantal Guillemette*, Hugo Girard*, * Canada Research Chair in Pharmacogenomics, Laval University – Pharmacy, Quebec, Canada.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,004 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,013 | 0,022 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,060 | 0,042 |
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 ».