Notice bibliographique
Résumé
With the ongoing development of nanotechnology comes the recognition that there are significant challenges regarding the definition, characterization, and safety testing of engineered nanomaterials. This holds true for nanotechnology-derived materials and products containing such materials that are destined for use in many industries, including those related to base chemicals, pesticides, drugs, medical devices, and, of course, foods and beverages. It is evident from the published literature that applications of nanotechnology and nanotechnology-derived products in food science are rapidly increasing. Indeed, a search of the PubMed database (http://www.ncbi.nlm.nih.gov/sites/entrez) conducted on August 26, 2009 that used the search terms [(nanoscale OR nanoparticle OR nanomaterial* OR nanotoxic* OR nanoscience OR nanotechnolog*) AND (oral* OR food* OR feed* OR diet OR dietary OR drink* OR beverage)] identified 57 unique articles that were published in 2003; the same search revealed that 410 unique articles were published in 2008, representing an increase of over 600% in just 5 years. The continued development and application of nanotechnology in food science give reason to pause and take stock of the current status of nanomaterial definition, characterization, and safety testing in this area. The definition of a nanomaterial is generally accepted to be one for which at least 1 dimension is 100 nm or less (Stern and McNeil 2008; EFSA 2009), although it is recognized that in some circumstances this definition may be too restrictive. Strategies for assessing the safety of nanomaterials has been the topic of a number of recent review articles, with the general consensus being that tiered approaches (that is, in vitro and in vivo screening studies followed by pivotal in vivo studies and supportive mechanistic studies) are best suited for this purpose (Oberdörster and others 2005; Warheit and others 2007). This approach is not unlike the general safety testing strategy that is employed in the development of food additive and pharmaceutical drug candidates. As highlighted by Ostrowski and others (2008), however, most of the research on the safety of nanomaterials that has been conducted to date has tended to emphasize acute toxicity and mortality rather than chronic exposure and morbidity; in other words, the pivotal studies are lacking. While it is important to characterize acute effects, it is chronic exposure to nanomaterials that is arguably more relevant to food science applications. We are not aware of the publication to date of any such long-term studies and we look forward to the reporting of such studies conducted with nanomaterials with potential food science applications. Prolonged exposure studies will be required to determine the safety of nanomaterials that humans may be exposed to via foods and beverages, and physicochemical characterization of the nanomaterials that are used in such toxicology studies will be of utmost importance. Lack of adequate nanomaterial characterization limits the value and significance of a given study and renders it impossible to compare studies and recognize parameters that might influence biological activity (that is, desirable effects) or toxicity (that is, undesirable effects) (Stern and McNeil 2008; Warheit and others 2008). There are numerous nanomaterial characteristics that can be measured and described, but attempting to satisfy a “laundry list” of parameters often is not practical or necessary. Thus, we propose that a set of minimum parameters be determined and reported for nanomaterials that are used in experiments assessing various biological activities, including toxicity, regardless of the route of exposure that is being examined. This set includes the following 9 parameters: agglomeration and/or aggregation chemical composition crystal structure/crystallinity particle size/size distribution purity shape surface area surface charge surface chemistry (including composition and reactivity) This list of parameters was compiled following a review of those that have been suggested by a number of authors and scientific organizations (NCI/NCL 2009; Oberdörster and others 2005; Powers and others 2006; Gonzalez and others 2008; Warheit 2008; Characterization Matters 2008). A parameter was selected for inclusion in our set if it was listed as a suggested characterization parameter in at least 3 of the 6 sources that we reviewed. In addition to these 9 parameters, we, like others in the field, feel it is imperative to document these parameters in the experimental exposure media (cell culture media, oral dosing solution, and so on) to the greatest extent possible. This is due to the fact that some physicochemical parameters are likely to differ depending on whether they are determined in the experimental media or in the bulk (that is, “as received”) state. While the Journal of Food Science does not appear to have published dedicated in vitro or in vivo nanomaterial toxicology studies as of yet, it is anticipated that it may do so in the near future. In this regard, we propose that authors of studies of nanomaterial biological activity and toxicity, and reviewers and editors of journals that evaluate such studies for publication, consider using our set of minimum physicochemical parameters as a checklist to determine the adequacy of nanomaterial characterization in a given study. It is recognized that for some nanomaterials there are some parameters that may be difficult or even impossible to describe or measure with accuracy. An example of this is purity. As highlighted recently by Walker and Bucher (2009), an engineered nanomaterial may be composed of multiple entities, have a distribution profile for its primary particle size, may aggregate, and may also have a surface coating. In such a case, it would be difficult to determine how purity (and deviation from the stated purity) would best be described. Nonetheless, we are of the opinion that opening a dialogue on these types of issues through the (attempted) reporting of a set of minimum physicochemical parameters for nanomaterials in studies of their biological activity and toxicity is a step in the right direction and will assist in bringing the benefits of nanotechnology to food science in a safe and transparent manner. We acknowledge the financial support from IFT, the GMA Science and Education Foundation, and ILSI North America for the development of these recommendations as part of an ongoing project to assess the safety of oral exposure to nanoscale materials.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».