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Ruth Lehmann elected as director of Whitehead Institute Study finds hub linking movement and motivation in the brain. A new lens into the past. Startup uses virtual reality to help seniors re-engage with the world Demo Day celebrates student entrepreneurship MIT named No. A new lens into the past New approach suggests path to emissions-free cement How to make a book last for millennia A comprehensive catalogue of human digestive tract bacteria. Using data science to improve public policy Helping Mexico design an effective climate policy. Image: Nicolas Bertrand.
Nanomaterial-Biofilm Interactions | Frontiers Research Topic
Fact Sheet. Result in Brief. Objective "Nanotechnology is rapidly expanding. However, some types of engineered nanoparticles can be toxic for living organisms and exhibit negative impact on the environment. Thus, the design of new nanomaterials must be supported by a rigorous risk analysis. Following the recommendations by the EU REACH system and regarding ethical aspects, the risk assessment procedures should be performed with possible reduction of living animal use.
The main objective of the NanoPuzzles project is to create new computational methods for comprehensive modelling the relationships between the structure, properties, molecular interactions and toxicity of engineered nanoparticles. The methods will be based on the Quantitative Structure - Activity Relationship approach, chemical category formation and read-across techniques.
Those methods have been widely used in risk assessment of other groups of priority chemicals. But, because of some specific reasons, they can not be applied directly to nanoparticles. We will be developing novel methods within four complimentary areas ""puzzles"" , namely: i evaluation of physico-chemical and toxicological data available for nanoparticles NanoDATA , ii developing novel descriptors of nanoparticles' structure NanoDESC , iii investigating interactions of nanoparticles with biological systems NanoINTER , and iv quantitative structure - activity relationships modelling NanoQSAR.
Developed methods will be tested and verified for their technical viability by the collaborating industry representative. By implementing the NanoPuzzles methods, extensive animal testing would be significantly reduced. Moreover, the project will deliver the basis for categorising nanoparticles based on potential exposure, phys-chem, structural and toxicological properties. Topic s NMP. Bazynskiego 8 Gdansk Poland. Activity type Higher or Secondary Education Establishments.
Website Contact the organisation. Administrative Contact Tomasz Puzyn Dr. Project website. Status Closed project. Start date 1 January End date 31 December Model for nanoparticle behaviour and properties Metal oxide nanoparticles NPs and carbon-based NPs have helped to improve products and services in numerous fields due to their widespread application and commercial availability.
Discover other articles in the same domain of application. The main objective of the NanoPUZZLES project is to create new computational methods for comprehensive modelling of the relationships between the structure, properties, molecular interactions and toxicity of engineered nanoparticles. In addition we have introduced three novel kinds of descriptors not previously anticipated in the DoW i.
Specific rules workflows have been proposed for the computation of the interaction properties of small, medium and large size systems. In addition conceptual framework for further grouping of NPs was established. We have presented that the causal structures can efficiently be used in Nano-SAR modelling as additional criteria for quality evaluation. Project Context and Objectives: Nanotechnology is a rapidly expanding area of research with huge potential in many sectors. Different types of nanoparticles NPs find a vast range of medicinal applications.
Thus, the design of new nanoparticles must be accompanied by a rigorous risk analysis. Following the European recommendations and bearing the ethical aspects of such research in mind, the risk assessment procedures should be performed with possible reduction of animal testing. One of the most promising alternatives is the application of computational techniques, which not only allows curtailing animal use, but also enables a significant reduction of in cost of the required risk assessment. The package i will serve as a proof-of-concept that the risk related to NPs can be comprehensively assessed with use of computational techniques and ii will define a basis for development of further modelling techniques for a large variety of nanoparticles.
WP2: NanoDESC The main objective of the second thematic area is to develop a framework to optimally characterise the structure of engineered NP using appropriate descriptors and categorising them according to structural similarities. WP3: NanoINTER The objective of the third thematic area is to develop a computational protocol to satisfactorily predict and explain interactions between engineered NPs and biological systems as well as small molecules. There are several important factors related with the NP.
Among those we note: i the chemical composition of the NP e. NPs e. CNTs may involve one or more toxic metals e. Fe, Co, Ni which may be considered as contaminants; vi functionalization. It is understood that functionalization may affect the toxicity of the NP as well as its solubility. We shall look for functional groups, which seriously reduce the genotoxicity and increase the solubility of the considered NPs.
Moreover, engineered nanoparticles exposed to environment participate in reactions of other environmental pollutants oxidation reactions etc. WP4: NanoQSAR The objective of this thematic area is to develop scientifically justified and technically viable methods to quantitatively model the relationships between chemical structure and toxicological targets as well as to extend the understanding of toxicity and behaviour of emerging nanoparticles by establishing relations between experimental based on available, validated data and computational properties.
The information about the character of interaction mechanisms will be important for an appropriate selection of nanodescriptors representing structural features of the studied nanoparticles. Moreover, it will result in a framework being established to categorise nanoparticles according to the potential for exposure, as well as physicochemical, structural and toxicological properties based on available empirical data and computationally predicted results.
This, in the longer perspective, should lead to designing and engineering nanomaterials that are of low risk for human and the environment. WP6: Management The objective is to ensure successful implementation of the project plan on time and at cost. Project Results: The main objective of the NanoPUZZLES project was to create new computational methods for comprehensive modelling of the relationships between the structure, properties, molecular interactions and toxicity of engineered nanoparticles.
These initial datasets were organised within non-standardised Excel workbooks and few experimental details were extracted. Following discussions with other NanoSafety Modelling Cluster projects i. These case studies entailed thorough collection of data, including details regarding experimental conditions and techniques, from primary literature articles.
It was determined that various challenges were associated with the use of the evaluated version of ISA-TAB-Nano, including ambiguity perceived in the existing documentation and difficulties associated with creating appropriately named columns: creating column names using standardised terms from ontologies at the point of data collection was deemed inefficient and the potential need for new ontology terms to be defined was identified. Proposals were developed for resolving these challenges, such as the creation of specific templates based upon the ISA-TAB-Nano specification with pre-defined columns to be used in ongoing data collection efforts.
Additional challenges facing ongoing data collection efforts included the need to define appropriate minimum information standards, as well as potential copyright restrictions, which could affect, for example, the inclusion of transmission electron microscopy TEM images in the publicly released data collection. A detailed description of the initial data collection activities referred to above was presented in deliverable D1.
Subsequent data collection activities, within the first reporting period, are summarised below. In total, primary references were identified with relevant data for one or more nanomaterials. The summaries of the data contained within all these articles serve as a basis for prioritising articles from which data are being extracted into ISA-TAB-Nano files.
These templates were developed by extending the generic templates available from the US Nanotechnology Working Group. These data collection templates have been used to record data extracted from prioritised journal articles and scientific reports identified via the literature analysis described above.
Extraction of data from additional prioritised articles will continue in the next reporting period.
Additional data were extracted from the literature as part of the Harmonisation of Modelling Projects initiative and a session was arranged to provide feedback to the developers of the PreNanoTox database into which data were entered as part of this initiative. Recent discussions within NanoPUZZLES led to aquatic toxicity, an important ecotoxicological endpoint, being added to the set of prioritised endpoints and fullerene genotoxicity data was required by WP3.
Hence, new literature searches identified additional articles with fullerene genotoxicity data or Daphnia aquatic toxicity data for nanomaterials. Additional genotoxicity data were also separately identified during the preparation of a review of the genotoxicity of metal oxides. Provisional datasets summarising the data within these additional articles have been prepared.
The most appropriate means of integrating all of these additional data into the final NanoPUZZLES datasets were discussed during the first reporting period and a solution will be developed in the next reporting period. Task 1. The proposed criteria to be applied consider this information to be of higher quality if it is more complete, has been recorded using a standardised terminology, is defined using sufficiently precise terms and has undergone quality assurance.
Based upon these criteria, a proposal for assigning quality scores for this information was developed. The selection of the structural information to be recorded and the means of assigning a quality score to this information were based upon a careful review of the literature. This proposal was described in detail in deliverable D1. This created a starting point for further discussion and harmonisation of the criteria with other projects.
The assignment procedure was designed to be as transparent and as objective as possible. The conclusion drawn from this body of literature was that expert-based approaches to grouping of nanomaterials were challenging due to a lack of complete understanding of the features responsible for the dominant nanomaterial toxicity mechanisms e. Hence, an additional literature review was carried out to identify suitable pattern recognition approaches to be investigated for category formation. A detailed description of this work was presented in deliverable D1.
It was resolved to investigate these issues via arranging discussions with the MODERN project team see the description of work carried out towards Task 1. Two datasets were identified as potentially useful for Task 1. Dataset b was of interest due to the experimental assignment, by the authors of the original study, of different mechanisms for cytotoxicity to different nanomaterials in the dataset.
These dataset characteristics were all relevant for the assignment of different types of nanomaterials to groups associated with a common mechanism for a given endpoint i. However, the categories obtained via these pattern recognition techniques i.
Hence, the scientific validity of the categories obtained was uncertain. This emphasised the importance of continued investigation of grouping approaches in WP4. The publicly released data resources are as follows: a set of ISA-TAB-Nano datasets, containing meta data extracted from prioritised nanotoxicology literature references, as well as a list of evaluated references used to identify sources of data to be used within the project. A detailed description of most of this work was presented in deliverable report D1.
Hence, a brief summary of the work reported in that deliverable report and carried out during the second reporting period is provided here. The initial ISA-TAB-Nano data collection created within the first reporting period was significantly expanded to include data for an additional nominal nanomaterials, extracted from six additional references.
This entailed additional searches for references providing data relevant to the NanoPUZZLES prioritised endpoints cytoxicity, genotoxicity and zebrafish toxicity , including incorporation of work carried out in the second reporting period towards Golbamaki et al. The provisional scoring schemes developed in the first reporting period and reported in deliverables D1. Nanotechnology Working Group within the context of developing an article, for which work was led by NanoPUZZLES, addressing the challenges associated with evaluating the quality and completeness of curated nanomaterial data.
In addition to simply expanding the ISA-TAB-Nano datasets developed within the first reporting period, the tools developed to support the creation of these datasets needed to be updated for two reasons: 1 to enable compatibility with the nanoDMS database developed within the MODERN project;5 2 to support the integration of additional kinds of meta data, such as in vivo cytotoxicity and zebrafish mortality data, identified as being important but which were not captured by earlier iterations of the NanoPUZZLES ISA-TAB-Nano templates. Hence, the Excel templates6 and Python program7 for generating tab-delimited text versions of the datasets which could be integrated within nanoinformatics resources such as the MODERN nanoDMS database were updated and have also been publicly released.
In order to address issue 1 , errors in all ISA-TAB-Nano datasets — including those developed within the first reporting period — needed to be manually fixed. Nanotechnology Working Group, which helped to improve the article and make it a valuable reference for nanosafety researchers aiming to make use of ISA-TAB-Nano in the future. It should be noted that this article refers to a snapshot of these resources, which have subsequently been extended and the extended versions publicly released. An overview of all ISA-TAB-Nano datasets planned for public released, along with the spreadsheet of evaluated references, was provided in deliverable report D1.
Subsequent to submitting deliverable report D1. However, in some cases, the Material files correspond to nominal nanomaterials, with the curated size measurements outside the 1 — nm range, and data were not available for all endpoints for all materials. Toxicity data collected were primarily for different kinds of cytotoxicity assays, with some embryonic zebrafish mortality and genotoxicity data also collected.
chapter and author info
In addition, corresponding physicochemical data were collected for a range of endpoints, such as size, zeta potential and dissolution. These metadata include the number of nanomaterials studied or, in some cases where data were not available for all nanomaterials, the number of nanomaterials for which at least some data were available and the availability of different kinds of data for various nanosafety related endpoints.
In order to identify possible means for making all publicly released datasets available via a searchable database and to ensure that they would be available for future nanosafety researchers, a review of various options was considered. First, we evaluated the classical descriptors, used for classical QSAR and then we discussed the appropriate descriptors used for nanoparticles.
However, there are specific parameters which go beyond the traditional approach es for QSAR and may be profitably used as descriptors for nanoparticles. The emphasis of Task 2. We compared the descriptors for nanoparticles with those used for bulk materials. Furthermore, we identified the use of traditional and new descriptors, as applied within a series of examples. The use of these descriptors has been discussed in detail, defining the domain and limitations of their application.
An appropriate review of the descriptors was presented in deliverable D2. Task 2. The modeller may combine descriptors and formats from different backgrounds where the information is not redundant. A possible way to organise a model for endpoints related to nanomaterials, at the present time, is to assume that the measured endpoint is a mathematical function of all available eclectic information.
This list can be easily extended e. These additional descriptors have to be obtained from experimental measurements, associated to the specific nanomaterial, and cannot be calculated. Many other factors able to influence the numerical values of the measured endpoint, and thus the model can be detailed according to new available information irradiation, dark, temperature, etc.
The statistical and operative schemes of the QSAR models should be adopted as usual, including a broader definition of descriptors in their applicability domain. This means that if we extend the definition of the descriptors to other non-classical features, these have also to be used for the characterisation of the applicability domain of the model. Two papers have been published see below in which we used the proposed format for modelling nanomaterials. NHRF investigated various descriptors in order to be used as a basis to build up predictive models for a nanomaterials endpoint.
The work of A. Avramopoulos and G. Leonis has been continued and extended in their contribution to WP4. Toropova A. Toropov A. Puzyn T. Journal of Mathematical Chemistry 51, Chemosphere 92, They can also be based on physicochemical parameters. As an application and demonstration of the utility of this kind of descriptors, we studied: 1 cytotoxicity of metal oxide nanoparticles, 2 mutagenicity of fullerenes and multi-walled carbon-nanotubes, 3 membrane damage by TiO2 and ZnO nanoparticles, as well as 4 cell viability of human embryonic kidney cells exposed to SiO2 nanoparticles.
Rallo R. Benfenati E. Manganelli S. Nano-descriptors derived from quantum-mechanical calculations Based on simply computable, interpretable and reproducible molecular descriptors calculated with Gaussian09, MOPAC and Dragon software we have demonstrated the utility of the quantum-mechanical descriptors in developing new predictive Nano-QSAR models. Golbamaki N. Gromelski M. Manuscript is being prepared. With NanoImpact, we aim to publish the most high quality, novel and rigorous science and technology in the field to support its continued growth.
Nanomaterials are tiny particles on the nano scale — one-billionth of a meter — that can be engineered to have applications in a variety of settings.
They are already used in medicine, electronics, cosmetics and bioremediation, and many other areas. Because of their rapid and broad uptake, nanomaterials are already found in the environment and our bodies. Take silver nanomaterials. Many antibacterial products contain silver nanomaterials that kill the bacteria, preventing, for example, hospital acquired infections; even retail clothing stores are starting to stock antibacterial pajamas for people to wear after an operation.
Silver nanoparticles are known to be toxic to some organisms, and because they are so widely used and dispersed they pose a substantial — but as yet undefined — risk to people and the environment. As nanomaterials continue to develop into new generation materials such as nanohybrids, which combine nano and other materials, they will become even smaller, multi-functional and more dispersible. NanoImpact co-Editor-in-Chief Dr.
All these properties provide greater potential for benefit, but also greater potential to harm human and environmental health. The risk posed by nanomaterials is poorly understood because of a lack of detailed data, the novelty of the area and the potential novel behaviors of nanomaterials. But they are important emerging contaminants, so to protect health and ensure the long-term sustainability of the technology, these risks need to be understood, quantified and reduced.
NanoImpact aims to play an important role in disseminating knowledge about nanomaterials in human and environmental systems. It focuses on four main areas:.backtoddtempnoti.tk
Nano Contaminants: How Nanoparticles Get Into the Environment
By focusing on research in these areas, we hope to provide a central point of reference and contact for scientists working in this area from different angles. By pulling together all the research on nanosafety, we hope to connect researchers and support the multidisciplinary research that is so vital in this area.
Only by working in an interdisciplinary manner across the exposure-disease continuum can we understand potential nano-specific risks and pave the way for a more sustainable nanotechnology industry. NanoImpact will stimulate such interdisciplinary research and safer-by-design approaches and bring together the application and implication communities and other stakeholders.
NanoImpact is a multidisciplinary journal that focuses on nanosafety research and areas related to the impacts of manufactured nanomaterials on human and environmental systems and the behavior of nanomaterials in these systems. This journal is published by Elsevier. His research interests are primarily in the areas of aerosol science and technology with emphasis on the elucidation of particulate matter PM health effects and environmental health and safety implications of engineered nanomatrerials ENMs. His current research focuses on nanosafety and nano-bio interactions and the role of ENM structure on bioactivity.
He is a co-author of two books, numerous book chapters and hundreds of articles in leading journals and conference proceedings in the particle health effect and nanoscience fields. He is an Associate Professor at Harvard T. His research aims at understanding nanoscale phenomena in the environment and he is interested in investigating natural nanomaterials, manufactured nanomaterials and their interactions, behaviors and risks.
He has published widely in the field, with more than publications, and he has edited five books on natural and manufactured nanomaterials. Lead is a founding and current member of the organizing committee of the International Conference series on the Environmental Effects of Nanoparticles and Nanomaterials.