1
|
Afantitis A. Computational and structural biotechnology meets nanoscience and advanced materials. Comput Struct Biotechnol J 2024; 25:1-2. [PMID: 38230388 PMCID: PMC10788362 DOI: 10.1016/j.csbj.2023.12.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024] Open
Affiliation(s)
- Antreas Afantitis
- Corresponding author at: Nanoinformatics Department, NovaMechanics Ltd, Nicosia, Cyprus.
| |
Collapse
|
2
|
Huang ETC, Yang JS, Liao KYK, Tseng WCW, Lee CK, Gill M, Compas C, See S, Tsai FJ. Predicting blood-brain barrier permeability of molecules with a large language model and machine learning. Sci Rep 2024; 14:15844. [PMID: 38982309 PMCID: PMC11233737 DOI: 10.1038/s41598-024-66897-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 07/05/2024] [Indexed: 07/11/2024] Open
Abstract
Predicting the blood-brain barrier (BBB) permeability of small-molecule compounds using a novel artificial intelligence platform is necessary for drug discovery. Machine learning and a large language model on artificial intelligence (AI) tools improve the accuracy and shorten the time for new drug development. The primary goal of this research is to develop artificial intelligence (AI) computing models and novel deep learning architectures capable of predicting whether molecules can permeate the human blood-brain barrier (BBB). The in silico (computational) and in vitro (experimental) results were validated by the Natural Products Research Laboratories (NPRL) at China Medical University Hospital (CMUH). The transformer-based MegaMolBART was used as the simplified molecular input line entry system (SMILES) encoder with an XGBoost classifier as an in silico method to check if a molecule could cross through the BBB. We used Morgan or Circular fingerprints to apply the Morgan algorithm to a set of atomic invariants as a baseline encoder also with an XGBoost classifier to compare the results. BBB permeability was assessed in vitro using three-dimensional (3D) human BBB spheroids (human brain microvascular endothelial cells, brain vascular pericytes, and astrocytes). Using multiple BBB databases, the results of the final in silico transformer and XGBoost model achieved an area under the receiver operating characteristic curve of 0.88 on the held-out test dataset. Temozolomide (TMZ) and 21 randomly selected BBB permeable compounds (Pred scores = 1, indicating BBB-permeable) from the NPRL penetrated human BBB spheroid cells. No evidence suggests that ferulic acid or five BBB-impermeable compounds (Pred scores < 1.29423E-05, which designate compounds that pass through the human BBB) can pass through the spheroid cells of the BBB. Our validation of in vitro experiments indicated that the in silico prediction of small-molecule permeation in the BBB model is accurate. Transformer-based models like MegaMolBART, leveraging the SMILES representations of molecules, show great promise for applications in new drug discovery. These models have the potential to accelerate the development of novel targeted treatments for disorders of the central nervous system.
Collapse
Affiliation(s)
- Eddie T C Huang
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - Jai-Sing Yang
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Ken Y K Liao
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - Warren C W Tseng
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - C K Lee
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - Michelle Gill
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - Colin Compas
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - Simon See
- NVIDIA AI Technology Center, NVIDIA Corporation, Santa Clara, USA
| | - Fuu-Jen Tsai
- School of Chinese Medicine, College of Chinese Medicine, China Medical University, China Medical University Children's Hospital, No. 2, Yude Road, Taichung, 404332, Taiwan.
- China Medical University Children's Hospital, Taichung, Taiwan.
| |
Collapse
|
3
|
Groenewold M, Bleeker EAJ, Noorlander CW, Sips AJAM, van der Zee M, Aitken RJ, Baker JH, Bakker MI, Bouman EA, Doak SH, Drobne D, Dumit VI, Florin MV, Fransman W, Gonzalez MM, Heunisch E, Isigonis P, Jeliazkova N, Jensen KA, Kuhlbusch T, Lynch I, Morrison M, Porcari A, Rodríguez-Llopis I, Pozuelo BM, Resch S, Säämänen AJ, Serchi T, Soeteman-Hernandez LG, Willighagen E, Dusinska M, Scott-Fordsmand JJ. Governance of advanced materials: Shaping a safe and sustainable future. NANOIMPACT 2024; 35:100513. [PMID: 38821170 DOI: 10.1016/j.impact.2024.100513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 04/30/2024] [Accepted: 05/27/2024] [Indexed: 06/02/2024]
Abstract
The past few decades of managing the uncertain risks associated with nanomaterials have provided valuable insights (knowledge gaps, tools, methods, etc.) that are equally important to promote safe and sustainable development and use of advanced materials. Based on these insights, the current paper proposes several actions to optimize the risk and sustainability governance of advanced materials. We emphasise the importance of establishing a European approach for risk and sustainability governance of advanced materials as soon as possible to keep up with the pace of innovation and to manage uncertainty among regulators, industry, SMEs and the public, regarding potential risks and impacts of advanced materials. Coordination of safe and sustainable advanced material research efforts, and data management according to the Findable, Accessible, Interoperable and Reusable (FAIR) principles will enhance the generation of regulatory-relevant knowledge. This knowledge is crucial to identify whether current regulatory standardised and harmonised test methods are adequate to assess advanced materials. At the same time, there is urgent need for responsible innovation beyond regulatory compliance which can be promoted through the Safe and Sustainable Innovation Approach. that combines the Safe and Sustainable by Design concept with Regulatory Preparedness, supported by a trusted environment. We further recommend consolidating all efforts and networks related to the risk and sustainability governance of advanced materials in a single, easy-to-use digital portal. Given the anticipated complexity and tremendous efforts required, we identified the need of establishing an organisational structure dedicated to aligning the fast technological developments in advanced materials with proper risk and sustainability governance. Involvement of multiple stakeholders in a trusted environment ensures a coordinated effort towards the safe and sustainable development, production, and use of advanced materials. The existing infrastructures and network of experts involved in the governance of nanomaterials would form a solid foundation for such an organisational structure.
Collapse
Affiliation(s)
- Monique Groenewold
- National Institute for Public Health and the Environment (RIVM), Centre for Safety of Substances and Products, Bilthoven, the Netherlands.
| | - Eric A J Bleeker
- National Institute for Public Health and the Environment (RIVM), Centre for Safety of Substances and Products, Bilthoven, the Netherlands
| | - Cornelle W Noorlander
- National Institute for Public Health and the Environment (RIVM), Centre for Safety of Substances and Products, Bilthoven, the Netherlands
| | - Adriënne J A M Sips
- National Institute for Public Health and the Environment (RIVM), Centre for Safety of Substances and Products, Bilthoven, the Netherlands
| | | | - Robert J Aitken
- Institute of Occupational Medicine (IOM), Edinburgh, United Kingdom
| | - James H Baker
- Nanotechnology Industries Association (NIA), Brussels, Belgium
| | - Martine I Bakker
- National Institute for Public Health and the Environment (RIVM), Centre for Safety of Substances and Products, Bilthoven, the Netherlands
| | - Evert A Bouman
- The Climate and Environmental Research Institute (NILU), Department of Environmental Chemistry and Health, Kjeller, Norway
| | - Shareen H Doak
- Swansea University, Medical School, Faculty of Medicine, Health & Life Sciences, SA2 8PP, Wales, United Kingdom
| | - Damjana Drobne
- University of Ljubljana, Department of Biology, Biotechnical Faculty, Ljubljana, Slovenia
| | - Verónica I Dumit
- German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin, Germany
| | | | | | - Mar M Gonzalez
- Organisation for Economic Co-operation and Development (OECD), Paris, France
| | - Elisabeth Heunisch
- Federal Institute for Occupational Safety and Health (BAUA), Dortmund/ Berlin, Germany
| | | | | | - Keld Alstrup Jensen
- National Research Centre for the Working Environment (NFA), Copenhagen, Denmark
| | - Thomas Kuhlbusch
- Federal Institute for Occupational Safety and Health (BAUA), Dortmund/ Berlin, Germany
| | - Iseult Lynch
- University of Birmingham, School of Geography, Earth and Environmental Sciences, Edgbaston, Birmingham, United Kingdom
| | | | - Andrea Porcari
- Italian Association for Industrial Research (AIRI), Roma, Italy
| | | | | | - Susanne Resch
- BioNanoNet Forschungsgesellschaft mbH, Graz, Austria
| | | | - Tommaso Serchi
- Luxembourg Institute of Science and Technology (LIST), Belvaux, Luxembourg
| | - Lya G Soeteman-Hernandez
- National Institute for Public Health and the Environment (RIVM), Centre for Safety of Substances and Products, Bilthoven, the Netherlands
| | - Egon Willighagen
- Maastricht University, Dept of Bioinformatics - BiGCaT, NUTRIM, Maastricht, the Netherlands
| | - Maria Dusinska
- The Climate and Environmental Research Institute (NILU), Department of Environmental Chemistry and Health, Kjeller, Norway
| | | |
Collapse
|
4
|
Balraadjsing S, J G M Peijnenburg W, Vijver MG. Building species trait-specific nano-QSARs: Model stacking, navigating model uncertainties and limitations, and the effect of dataset size. ENVIRONMENT INTERNATIONAL 2024; 188:108764. [PMID: 38788418 DOI: 10.1016/j.envint.2024.108764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/17/2024] [Accepted: 05/19/2024] [Indexed: 05/26/2024]
Abstract
A strong need exists for broadly applicable nano-QSARs, capable of predicting toxicological outcomes towards untested species and nanomaterials, under different environmental conditions. Existing nano-QSARs are generally limited to only a few species but the inclusion of species characteristics into models can aid in making them applicable to multiple species, even when toxicity data is not available for biological species. Species traits were used to create classification- and regression machine learning models to predict acute toxicity towards aquatic species for metallic nanomaterials. Afterwards, the individual classification- and regression models were stacked into a meta-model to improve performance. Additionally, the uncertainty and limitations of the models were assessed in detail (beyond the OECD principles) and it was investigated whether models would benefit from the addition of more data. Results showed a significant improvement in model performance following model stacking. Investigation of model uncertainties and limitations highlighted the discrepancy between the applicability domain and accuracy of predictions. Data points outside of the assessed chemical space did not have higher likelihoods of generating inadequate predictions or vice versa. It is therefore concluded that the applicability domain does not give complete insight into the uncertainty of predictions and instead the generation of prediction intervals can help in this regard. Furthermore, results indicated that an increase of the dataset size did not improve model performance. This implies that larger dataset sizes may not necessarily improve model performance while in turn also meaning that large datasets are not necessarily required for prediction of acute toxicity with nano-QSARs.
Collapse
Affiliation(s)
- Surendra Balraadjsing
- Institute of Environmental Sciences (CML), Leiden University, PO Box 9518, 2300 RA Leiden, the Netherlands.
| | - Willie J G M Peijnenburg
- Institute of Environmental Sciences (CML), Leiden University, PO Box 9518, 2300 RA Leiden, the Netherlands; Centre for Safety of Substances and Products, National Institute of Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, the Netherlands
| | - Martina G Vijver
- Institute of Environmental Sciences (CML), Leiden University, PO Box 9518, 2300 RA Leiden, the Netherlands
| |
Collapse
|
5
|
Saeedimasine M, Rahmani R, Lyubartsev AP. Biomolecular Adsorption on Nanomaterials: Combining Molecular Simulations with Machine Learning. J Chem Inf Model 2024; 64:3799-3811. [PMID: 38623916 PMCID: PMC11094735 DOI: 10.1021/acs.jcim.3c01606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 04/03/2024] [Accepted: 04/03/2024] [Indexed: 04/17/2024]
Abstract
Adsorption free energies of 32 small biomolecules (amino acids side chains, fragments of lipids, and sugar molecules) on 33 different nanomaterials, computed by the molecular dynamics - metadynamics methodology, have been analyzed using statistical machine learning approaches. Multiple unsupervised learning algorithms (principal component analysis, agglomerative clustering, and K-means) as well as supervised linear and nonlinear regression algorithms (linear regression, AdaBoost ensemble learning, artificial neural network) have been applied. As a result, a small set of biomolecules has been identified, knowledge of adsorption free energies of which to a specific nanomaterial can be used to predict, within the developed machine learning model, adsorption free energies of other biomolecules. Furthermore, the methodology of grouping of nanomaterials according to their interactions with biomolecules has been presented.
Collapse
Affiliation(s)
- Marzieh Saeedimasine
- Department of Materials and Environmental
Chemistry, Stockholm University, Stockholm SE-106 91, Sweden
| | - Roja Rahmani
- Department of Materials and Environmental
Chemistry, Stockholm University, Stockholm SE-106 91, Sweden
| | - Alexander P. Lyubartsev
- Department of Materials and Environmental
Chemistry, Stockholm University, Stockholm SE-106 91, Sweden
| |
Collapse
|
6
|
Ficiarà E, Stura I, Vernone A, Silvagno F, Cavalli R, Guiot C. Iron Overload in Brain: Transport Mismatches, Microbleeding Events, and How Nanochelating Therapies May Counteract Their Effects. Int J Mol Sci 2024; 25:2337. [PMID: 38397013 PMCID: PMC10889007 DOI: 10.3390/ijms25042337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
Iron overload in many brain regions is a common feature of aging and most neurodegenerative diseases. In this review, the causes, mechanisms, mathematical models, and possible therapies are summarized. Indeed, physiological and pathological conditions can be investigated using compartmental models mimicking iron trafficking across the blood-brain barrier and the Cerebrospinal Fluid-Brain exchange membranes located in the choroid plexus. In silico models can investigate the alteration of iron homeostasis and simulate iron concentration in the brain environment, as well as the effects of intracerebral iron chelation, determining potential doses and timing to recover the physiological state. Novel formulations of non-toxic nanovectors with chelating capacity are already tested in organotypic brain models and could be available to move from in silico to in vivo experiments.
Collapse
Affiliation(s)
- Eleonora Ficiarà
- School of Pharmacy, University of Camerino, 62032 Camerino, MC, Italy;
| | - Ilaria Stura
- Department of Neurosciences, Università degli Studi di Torino, 10125 Torino, TO, Italy; (A.V.); (C.G.)
| | - Annamaria Vernone
- Department of Neurosciences, Università degli Studi di Torino, 10125 Torino, TO, Italy; (A.V.); (C.G.)
| | - Francesca Silvagno
- Department of Oncology, Università degli Studi di Torino, 10126 Torino, TO, Italy;
| | - Roberta Cavalli
- Department of Drug Science and Technology, Università degli Studi di Torino, 10125 Torino, TO, Italy;
| | - Caterina Guiot
- Department of Neurosciences, Università degli Studi di Torino, 10125 Torino, TO, Italy; (A.V.); (C.G.)
| |
Collapse
|
7
|
Singh AV, Shelar A, Rai M, Laux P, Thakur M, Dosnkyi I, Santomauro G, Singh AK, Luch A, Patil R, Bill J. Harmonization Risks and Rewards: Nano-QSAR for Agricultural Nanomaterials. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:2835-2852. [PMID: 38315814 DOI: 10.1021/acs.jafc.3c06466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
This comprehensive review explores the emerging landscape of Nano-QSAR (quantitative structure-activity relationship) for assessing the risk and potency of nanomaterials in agricultural settings. The paper begins with an introduction to Nano-QSAR, providing background and rationale, and explicitly states the hypotheses guiding the review. The study navigates through various dimensions of nanomaterial applications in agriculture, encompassing their diverse properties, types, and associated challenges. Delving into the principles of QSAR in nanotoxicology, this article elucidates its application in evaluating the safety of nanomaterials, while addressing the unique limitations posed by these materials. The narrative then transitions to the progression of Nano-QSAR in the context of agricultural nanomaterials, exemplified by insightful case studies that highlight both the strengths and the limitations inherent in this methodology. Emerging prospects and hurdles tied to Nano-QSAR in agriculture are rigorously examined, casting light on important pathways forward, existing constraints, and avenues for research enhancement. Culminating in a synthesis of key insights, the review underscores the significance of Nano-QSAR in shaping the future of nanoenabled agriculture. It provides strategic guidance to steer forthcoming research endeavors in this dynamic field.
Collapse
Affiliation(s)
- Ajay Vikram Singh
- Department of Chemical and Product Safety, German Federal Institute of Risk Assessment (BfR), Maxdohrnstrasse 8-10, 10589 Berlin, Germany
| | - Amruta Shelar
- Department of Technology, Savitribai Phule Pune University, Pune 411007, India
| | - Mansi Rai
- Department of Microbiology, Central University of Rajasthan NH-8, Bandar Sindri, Dist-Ajmer-305817, Rajasthan, India
| | - Peter Laux
- Department of Chemical and Product Safety, German Federal Institute of Risk Assessment (BfR), Maxdohrnstrasse 8-10, 10589 Berlin, Germany
| | - Manali Thakur
- Uniklinik Köln, Kerpener Strasse 62, 50937 Köln Germany
| | - Ievgen Dosnkyi
- Institute of Chemistry and Biochemistry Department of Organic ChemistryFreie Universität Berlin Takustr. 3 14195 Berlin, Germany
| | - Giulia Santomauro
- Institute for Materials Science, Department of Bioinspired Materials, University of Stuttgart, 70569, Stuttgart, Germany
| | - Alok Kumar Singh
- Department of Plant Molecular Biology & Genetic Engineering, ANDUA&T, Ayodhya 224229, Uttar Pradesh, India
| | - Andreas Luch
- Department of Chemical and Product Safety, German Federal Institute of Risk Assessment (BfR), Maxdohrnstrasse 8-10, 10589 Berlin, Germany
| | - Rajendra Patil
- Department of Technology, Savitribai Phule Pune University, Pune 411007, India
| | - Joachim Bill
- Institute for Materials Science, Department of Bioinspired Materials, University of Stuttgart, 70569, Stuttgart, Germany
| |
Collapse
|
8
|
Maia MT, Delite FS, da Silva GH, Ellis LJA, Papadiamantis AG, Paula AJ, Lynch I, Martinez DST. Combined toxicity of fluorescent silica nanoparticles with cadmium in Ceriodaphnia dubia: Interactive effects of natural organic matter and green algae feeding. JOURNAL OF HAZARDOUS MATERIALS 2024; 461:132623. [PMID: 37776779 DOI: 10.1016/j.jhazmat.2023.132623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 07/31/2023] [Accepted: 09/23/2023] [Indexed: 10/02/2023]
Abstract
The environmental risks of silica nanoparticles (SiNP) reported in the literature are contradictory and bring into question its safety for use in consumer applications. Organisms are never exposed to NPs alone in the real environment, while studies of the combined toxicity of SiNP are limited. To address this, we compared the acute toxicity of fluorescent core-shell SiNPs alone and in mixtures with Cd2+ to Ceriodaphnia dubia in the absence and presence of NOM. We identified biodistribution and feeding behaviour in addition to the traditional endpoints. NOM increased the colloidal stability of SiNPs in reconstituted water. In immobility tests, no significant effects were observed from Cd2+ exposure with NOM and varying concentrations of SiNPs. A similar pattern of curve dose-response was observed for varying concentrations of SiNPs and increasing Cd2+ concentration and constant NOM. Fluorescence microscopy verified a dose-dependent bioaccumulation of SiNPs in C. dubia. Co-exposure to 10 mg L-1 SiNP with NOM and Cd2+ resulted in a stimulated stress feeding response at the lower Cd2+ concentrations which declined at the higher dose due to a functional impairment of the digestive tract. Alterations in feeding behaviour and the increasing bioaccumulation of SiNP indicate a potential ecological risk for Ceriodaphnia dubia from the mixture exposure.
Collapse
Affiliation(s)
- Marcella T Maia
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Sao Paulo, Brazil.
| | - Fabrício S Delite
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Sao Paulo, Brazil
| | - Gabriela Helena da Silva
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Sao Paulo, Brazil
| | - Laura-Jayne A Ellis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
| | - Anastasios G Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK; NovaMechanics Ltd, Nicosia, Cyprus
| | - Amauri J Paula
- Solid-Biological Interface group (SolBIN), Federal University of Ceará (UFC), Fortaleza, Ceará, Brazil; Ilum School of Science, Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Sao Paulo, Brazil
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK.
| | - Diego Stéfani T Martinez
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Sao Paulo, Brazil.
| |
Collapse
|
9
|
Rahmani R, Lyubartsev AP. Biomolecular Adsorprion at ZnS Nanomaterials: A Molecular Dynamics Simulation Study of the Adsorption Preferences, Effects of the Surface Curvature and Coating. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:2239. [PMID: 37570556 PMCID: PMC10421200 DOI: 10.3390/nano13152239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 07/25/2023] [Accepted: 07/30/2023] [Indexed: 08/13/2023]
Abstract
The understanding of interactions between nanomaterials and biological molecules is of primary importance for biomedical applications of nanomaterials, as well as for the evaluation of their possible toxic effects. Here, we carried out extensive molecular dynamics simulations of the adsorption properties of about 30 small molecules representing biomolecular fragments at ZnS surfaces in aqueous media. We computed adsorption free energies and potentials of mean force of amino acid side chain analogs, lipids, and sugar fragments to ZnS (110) crystal surface and to a spherical ZnS nanoparticle. Furthermore, we investigated the effect of poly-methylmethacrylate (PMMA) coating on the adsorption preferences of biomolecules to ZnS. We found that only a few anionic molecules: aspartic and glutamic acids side chains, as well as the anionic form of cysteine show significant binding to pristine ZnS surface, while other molecules show weak or no binding. Spherical ZnS nanoparticles show stronger binding of these molecules due to binding at the edges between different surface facets. Coating of ZnS by PMMA changes binding preferences drastically: the molecules that adsorb to a pristine ZnS surface do not adsorb on PMMA-coated surfaces, while some others, particularly hydrophobic or aromatic amino-acids, show high binding affinity due to binding to the coating. We investigate further the hydration properties of the ZnS surface and relate them to the binding preferences of biomolecules.
Collapse
Affiliation(s)
| | - Alexander P. Lyubartsev
- Department of Materials and Environmental Chemistry, Stockholm University, S-10691 Stockholm, Sweden
| |
Collapse
|
10
|
Mazuryk J, Klepacka K, Kutner W, Sharma PS. Glyphosate Separating and Sensing for Precision Agriculture and Environmental Protection in the Era of Smart Materials. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023. [PMID: 37384557 DOI: 10.1021/acs.est.3c01269] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
The present article critically and comprehensively reviews the most recent reports on smart sensors for determining glyphosate (GLP), an active agent of GLP-based herbicides (GBHs) traditionally used in agriculture over the past decades. Commercialized in 1974, GBHs have now reached 350 million hectares of crops in over 140 countries with an annual turnover of 11 billion USD worldwide. However, rolling exploitation of GLP and GBHs in the last decades has led to environmental pollution, animal intoxication, bacterial resistance, and sustained occupational exposure of the herbicide of farm and companies' workers. Intoxication with these herbicides dysregulates the microbiome-gut-brain axis, cholinergic neurotransmission, and endocrine system, causing paralytic ileus, hyperkalemia, oliguria, pulmonary edema, and cardiogenic shock. Precision agriculture, i.e., an (information technology)-enhanced approach to crop management, including a site-specific determination of agrochemicals, derives from the benefits of smart materials (SMs), data science, and nanosensors. Those typically feature fluorescent molecularly imprinted polymers or immunochemical aptamer artificial receptors integrated with electrochemical transducers. Fabricated as portable or wearable lab-on-chips, smartphones, and soft robotics and connected with SM-based devices that provide machine learning algorithms and online databases, they integrate, process, analyze, and interpret massive amounts of spatiotemporal data in a user-friendly and decision-making manner. Exploited for the ultrasensitive determination of toxins, including GLP, they will become practical tools in farmlands and point-of-care testing. Expectedly, smart sensors can be used for personalized diagnostics, real-time water, food, soil, and air quality monitoring, site-specific herbicide management, and crop control.
Collapse
Affiliation(s)
- Jarosław Mazuryk
- Department of Electrode Processes, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
- Bio & Soft Matter, Institute of Condensed Matter and Nanosciences, Université catholique de Louvain, 1 Place Louis Pasteur, 1348 Louvain-la-Neuve, Belgium
| | - Katarzyna Klepacka
- Functional Polymers Research Team, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
- ENSEMBLE3 sp. z o. o., 01-919 Warsaw, Poland
- Faculty of Mathematics and Natural Sciences. School of Sciences, Cardinal Stefan Wyszynski University in Warsaw, 01-938 Warsaw, Poland
| | - Włodzimierz Kutner
- Faculty of Mathematics and Natural Sciences. School of Sciences, Cardinal Stefan Wyszynski University in Warsaw, 01-938 Warsaw, Poland
- Modified Electrodes for Potential Application in Sensors and Cells Research Team, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
| | - Piyush Sindhu Sharma
- Functional Polymers Research Team, Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
| |
Collapse
|
11
|
Saarimäki LA, Fratello M, Pavel A, Korpilähde S, Leppänen J, Serra A, Greco D. A curated gene and biological system annotation of adverse outcome pathways related to human health. Sci Data 2023; 10:409. [PMID: 37355733 PMCID: PMC10290716 DOI: 10.1038/s41597-023-02321-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 06/20/2023] [Indexed: 06/26/2023] Open
Abstract
Adverse outcome pathways (AOPs) are emerging as a central framework in modern toxicology and other fields in biomedicine. They serve as an extension of pathway-based concepts by depicting biological mechanisms as causally linked sequences of key events (KEs) from a molecular initiating event (MIE) to an adverse outcome. AOPs guide the use and development of new approach methodologies (NAMs) aimed at reducing animal experimentation. While AOPs model the systemic mechanisms at various levels of biological organisation, toxicogenomics provides the means to study the molecular mechanisms of chemical exposures. Systematic integration of these two concepts would improve the application of AOP-based knowledge while also supporting the interpretation of complex omics data. Hence, we established this link through rigorous curation of molecular annotations for the KEs of human relevant AOPs. We further expanded and consolidated the annotations of the biological context of KEs. These curated annotations pave the way to embed AOPs in molecular data interpretation, facilitating the emergence of new knowledge in biomedicine.
Collapse
Affiliation(s)
- Laura Aliisa Saarimäki
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Michele Fratello
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Alisa Pavel
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Seela Korpilähde
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jenni Leppänen
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Angela Serra
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
- Institute for Advanced Study, Tampere University, Tampere, Finland
| | - Dario Greco
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland.
| |
Collapse
|
12
|
Blekos K, Chairetakis K, Lynch I, Marcoulaki E. Principles and requirements for nanomaterial representations to facilitate machine processing and cooperation with nanoinformatics tools. J Cheminform 2023; 15:44. [PMID: 37046286 PMCID: PMC10099932 DOI: 10.1186/s13321-022-00669-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 12/10/2022] [Indexed: 04/14/2023] Open
Abstract
Efficient and machine-readable representations are needed to accurately identify, validate and communicate information of chemical structures. Many such representations have been developed (as, for example, the Simplified Molecular-Input Line-Entry System and the IUPAC International Chemical Identifier), each offering advantages specific to various use-cases. Representation of the multi-component structures of nanomaterials (NMs), though, remains out of scope for all the currently available standards, as the nature of NMs sets new challenges on formalizing the encoding of their structure, interactions and environmental parameters. In this work we identify a set of principles that a NM representation should adhere to in order to provide "machine-friendly" encodings of NMs, i.e. encodings that facilitate machine processing and cooperation with nanoinformatics tools. We illustrate our principles by showing how the recently introduced InChI-based NM representation, might be augmented, in principle, to also encode morphology and mixture properties, distributions of properties, and also to capture auxiliary information and allow data reuse.
Collapse
Affiliation(s)
- Kostas Blekos
- Institute of Nuclear and Radiological Sciences and Technology, Energy and Safety, National Centre for Scientific Research "Demokritos", 15341, Agia Paraskevi, Greece
| | - Kostas Chairetakis
- Institute of Nuclear and Radiological Sciences and Technology, Energy and Safety, National Centre for Scientific Research "Demokritos", 15341, Agia Paraskevi, Greece
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Effie Marcoulaki
- Institute of Nuclear and Radiological Sciences and Technology, Energy and Safety, National Centre for Scientific Research "Demokritos", 15341, Agia Paraskevi, Greece.
| |
Collapse
|
13
|
Grote F, Lyubartsev AP. Water structure, dynamics and reactivity on a TiO 2-nanoparticle surface: new insights from ab initio molecular dynamics. NANOSCALE 2022; 14:16536-16547. [PMID: 36314644 DOI: 10.1039/d2nr02354g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Water structure, dynamics and reactivity at the surface of a small TiO2-nanoparticle fully immersed in water was investigated by an ab initio molecular dynamics simulation. Several modes of water binding were identified by assigning each atom to an atom type, representing a distinct chemical environment in the ab initio ensemble, and then computing radial distribution functions between the atom types. Surface reactivity was investigated by monitoring how populations of atom types change during the simulation. In order to acquire further insight, electron densities for a set of representative system snapshots were analyzed using an atoms-in-molecules approach. Our results reveal that water dissociation, where a water molecule splits at a bridging oxygen site to form a hydroxyl group and a protonated oxygen bridge, can occur by a mechanism involving transfer of a proton over several water molecules. The hydroxyl group and protonated oxygen bridge formed in the process persist (on a 10 ps time scale) and the hydroxyl group undergoes exchange using a mechanism similar to the one responsible for water dissociation. Rotational and translational dynamics of water molecules around the nanoparticle were analyzed in terms of reorientational time correlation functions and mean square displacement. While reorientation of water O-H vectors decreases quickly in the proximity of the nanoparticle surface, translational diffusion slows down more gradually. Our results give new insight into water structure, dynamics and reactivity on TiO2-nanoparticle surfaces and suggest that water dissociation on curved TiO2-nanoparticle surfaces can occur via more complex mechanisms than those previously identified for flat defect-free surfaces.
Collapse
Affiliation(s)
- Fredrik Grote
- Department of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius väg 16 C, 106 91 Stockholm, Sweden.
| | - Alexander P Lyubartsev
- Department of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius väg 16 C, 106 91 Stockholm, Sweden.
| |
Collapse
|
14
|
Kutumova EO, Akberdin IR, Kiselev IN, Sharipov RN, Egorova VS, Syrocheva AO, Parodi A, Zamyatnin AA, Kolpakov FA. Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools. Int J Mol Sci 2022; 23:12560. [PMID: 36293410 PMCID: PMC9604366 DOI: 10.3390/ijms232012560] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 10/07/2022] [Accepted: 10/14/2022] [Indexed: 11/30/2022] Open
Abstract
Cancer treatment and pharmaceutical development require targeted treatment and less toxic therapeutic intervention to achieve real progress against this disease. In this scenario, nanomedicine emerged as a reliable tool to improve drug pharmacokinetics and to translate to the clinical biologics based on large molecules. However, the ability of our body to recognize foreign objects together with carrier transport heterogeneity derived from the combination of particle physical and chemical properties, payload and surface modification, make the designing of effective carriers very difficult. In this scenario, physiologically based pharmacokinetic modeling can help to design the particles and eventually predict their ability to reach the target and treat the tumor. This effort is performed by scientists with specific expertise and skills and familiarity with artificial intelligence tools such as advanced software that are not usually in the "cords" of traditional medical or material researchers. The goal of this review was to highlight the advantages that computational modeling could provide to nanomedicine and bring together scientists with different background by portraying in the most simple way the work of computational developers through the description of the tools that they use to predict nanoparticle transport and tumor targeting in our body.
Collapse
Affiliation(s)
- Elena O. Kutumova
- Scientific Center for Information Technologies and Artificial Intelligence, Sirius University of Science and Technology, 354340 Sochi, Russia
- Federal Research Center for Information and Computational Technologies, 630090 Novosibirsk, Russia
- BIOSOFT.RU, Ltd., 630058 Novosibirsk, Russia
| | - Ilya R. Akberdin
- Scientific Center for Information Technologies and Artificial Intelligence, Sirius University of Science and Technology, 354340 Sochi, Russia
- BIOSOFT.RU, Ltd., 630058 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Ilya N. Kiselev
- Scientific Center for Information Technologies and Artificial Intelligence, Sirius University of Science and Technology, 354340 Sochi, Russia
- Federal Research Center for Information and Computational Technologies, 630090 Novosibirsk, Russia
- BIOSOFT.RU, Ltd., 630058 Novosibirsk, Russia
| | - Ruslan N. Sharipov
- Scientific Center for Information Technologies and Artificial Intelligence, Sirius University of Science and Technology, 354340 Sochi, Russia
- Federal Research Center for Information and Computational Technologies, 630090 Novosibirsk, Russia
- BIOSOFT.RU, Ltd., 630058 Novosibirsk, Russia
- Specialized Educational Scientific Center, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Vera S. Egorova
- Scientific Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - Anastasiia O. Syrocheva
- Scientific Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - Alessandro Parodi
- Scientific Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Andrey A. Zamyatnin
- Scientific Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia
- Institute of Molecular Medicine, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119992 Moscow, Russia
| | - Fedor A. Kolpakov
- Scientific Center for Information Technologies and Artificial Intelligence, Sirius University of Science and Technology, 354340 Sochi, Russia
- Federal Research Center for Information and Computational Technologies, 630090 Novosibirsk, Russia
- BIOSOFT.RU, Ltd., 630058 Novosibirsk, Russia
| |
Collapse
|
15
|
Li J, Wang C, Yue L, Chen F, Cao X, Wang Z. Nano-QSAR modeling for predicting the cytotoxicity of metallic and metal oxide nanoparticles: A review. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 243:113955. [PMID: 35961199 DOI: 10.1016/j.ecoenv.2022.113955] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/11/2022] [Accepted: 08/03/2022] [Indexed: 06/15/2023]
Abstract
Given the rapid development of nanotechnology, it is crucial to understand the effects of nanoparticles on living organisms. However, it is laborious to perform toxicological tests on a case-by-case basis. Quantitative structure-activity relationship (QSAR) is an effective computational technique because it saves time, costs, and animal sacrifice. Therefore, this review presents general procedures for the construction and application of nano-QSAR models of metal-based and metal-oxide nanoparticles (MBNPs and MONPs). We also provide an overview of available databases and common algorithms. The molecular descriptors and their roles in the toxicological interpretation of MBNPs and MONPs are systematically reviewed and the future of nano-QSAR is discussed. Finally, we address the growing demand for novel nano-specific descriptors, new computational strategies to address the data shortage, in situ data for regulatory concerns, a better understanding of the physicochemical properties of NPs with bioactivity, and, most importantly, the design of nano-QSAR for real-life environmental predictions rather than laboratory simulations.
Collapse
Affiliation(s)
- Jing Li
- Institute of Environmental Processes and Pollution Control, and School of Environment and Civil Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Engineering Laboratory for Biomass Energy and Carbon Reduction Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Chuanxi Wang
- Institute of Environmental Processes and Pollution Control, and School of Environment and Civil Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Engineering Laboratory for Biomass Energy and Carbon Reduction Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Le Yue
- Institute of Environmental Processes and Pollution Control, and School of Environment and Civil Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Engineering Laboratory for Biomass Energy and Carbon Reduction Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Feiran Chen
- Institute of Environmental Processes and Pollution Control, and School of Environment and Civil Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Engineering Laboratory for Biomass Energy and Carbon Reduction Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Xuesong Cao
- Institute of Environmental Processes and Pollution Control, and School of Environment and Civil Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Engineering Laboratory for Biomass Energy and Carbon Reduction Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China
| | - Zhenyu Wang
- Institute of Environmental Processes and Pollution Control, and School of Environment and Civil Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Engineering Laboratory for Biomass Energy and Carbon Reduction Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi, Jiangsu 214122, China.
| |
Collapse
|
16
|
van Rijn J, Afantitis A, Culha M, Dusinska M, Exner TE, Jeliazkova N, Longhin EM, Lynch I, Melagraki G, Nymark P, Papadiamantis AG, Winkler DA, Yilmaz H, Willighagen E. European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials. J Cheminform 2022; 14:57. [PMID: 36002868 PMCID: PMC9400299 DOI: 10.1186/s13321-022-00614-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 05/21/2022] [Indexed: 11/25/2022] Open
Abstract
Management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier for each nanomaterial. Existing identifiers may not always be applicable or sufficient to definitively identify the specific nanomaterial used in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier. We here describe the background to this new identifier, including FAIR interoperability as defined by FAIRSharing, identifiers.org, Bioregistry, and the CHEMINF ontology, and show how it complements other identifiers such as CAS numbers and the ongoing efforts to extend the InChI identifier to cover nanomaterials. We provide examples of its use in various H2020-funded nanosafety projects.
Collapse
Affiliation(s)
- Jeaphianne van Rijn
- Department of Bioinformatics-BiGCaT, NUTRIM, FHML, Maastricht University, Maastricht, The Netherlands.
| | | | - Mustafa Culha
- Sabanci University Nanotechnology Research and Application Center (SUNUM), Tuzla, 34956, Istanbul, Turkey
| | - Maria Dusinska
- Health Effects Laboratory, Department of Environmental Chemistry, Norwegian Institute for Air Research, 2007, Kjeller, Norway
| | | | | | - Eleonora Marta Longhin
- Health Effects Laboratory, Department of Environmental Chemistry, Norwegian Institute for Air Research, 2007, Kjeller, Norway
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, UK
| | | | - Penny Nymark
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Anastasios G Papadiamantis
- NovaMechanics Ltd., 1070, Nicosia, Cyprus.,School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, UK
| | - David A Winkler
- School of Biochemistry and Chemistry, La Trobe Institute for Molecular Science, La Trobe University, Bundoora, Australia.,Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Australia.,School of Pharmacy, University of Nottingham, Nottingham, UK
| | - Hulya Yilmaz
- Sabanci University Nanotechnology Research and Application Center (SUNUM), Tuzla, 34956, Istanbul, Turkey
| | - Egon Willighagen
- Department of Bioinformatics-BiGCaT, NUTRIM, FHML, Maastricht University, Maastricht, The Netherlands
| |
Collapse
|
17
|
Domingues C, Santos A, Alvarez-Lorenzo C, Concheiro A, Jarak I, Veiga F, Barbosa I, Dourado M, Figueiras A. Where Is Nano Today and Where Is It Headed? A Review of Nanomedicine and the Dilemma of Nanotoxicology. ACS NANO 2022; 16:9994-10041. [PMID: 35729778 DOI: 10.1021/acsnano.2c00128] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Worldwide nanotechnology development and application have fueled many scientific advances, but technophilic expectations and technophobic demands must be counterbalanced in parallel. Some of the burning issues today are the following: (1) Where is nano today? (2) How good are the communication and investment networks between academia/research and governments? (3) Is there any spotlight application for nanotechnology? Nanomedicine is a particular arm of nanotechnology within the healthcare landscape, focused on diagnosis, treatment, and monitoring of emerging (such as coronavirus disease 2019, COVID-19) and contemporary (including diabetes, cardiovascular diseases, neurodegenerative disorders, and cancer) diseases. However, it may only represent the bright side of the coin. In fact, in the recent past, the concept of nanotoxicology has emerged to address the dark shadows of nanomedicine. The nanomedicine field requires more nanotoxicological studies to identify undesirable effects and guarantee safety. Here, we provide an overall perspective on nanomedicine and nanotoxicology as central pieces of the giant puzzle of nanotechnology. First, the impact of nanotechnology on education and research is highlighted, followed by market trends and scientific output tendencies. In the next section, the nanomedicine and nanotoxicology dilemma is addressed through the interplay of in silico, in vitro, and in vivo models with the support of omics and microfluidic approaches. Lastly, a reflection on the regulatory issues and clinical trials is provided. Finally, some conclusions and future perspectives are proposed for a clearer and safer translation of nanomedicines from the bench to the bedside.
Collapse
Affiliation(s)
- Cátia Domingues
- Univ. Coimbra, Faculty of Pharmacy, Galenic and Pharmaceutical Technology Laboratory, 3000-548 Coimbra, Portugal
- LAQV-REQUIMTE, Galenic and Pharmaceutical Technology Laboratory, Faculty of Pharmacy, Univ. Coimbra, 3000-548 Coimbra, Portugal
- Univ. Coimbra, Institute for Clinical and Biomedical Research (iCBR) Area of Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, 3000-548 Coimbra, Portugal
| | - Ana Santos
- Univ. Coimbra, Faculty of Pharmacy, Galenic and Pharmaceutical Technology Laboratory, 3000-548 Coimbra, Portugal
| | - Carmen Alvarez-Lorenzo
- Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, iMATUS, and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Angel Concheiro
- Departamento de Farmacología, Farmacia y Tecnología Farmacéutica, I+D Farma (GI-1645), Facultad de Farmacia, iMATUS, and Health Research Institute of Santiago de Compostela (IDIS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
| | - Ivana Jarak
- Univ. Coimbra, Faculty of Pharmacy, Galenic and Pharmaceutical Technology Laboratory, 3000-548 Coimbra, Portugal
| | - Francisco Veiga
- Univ. Coimbra, Faculty of Pharmacy, Galenic and Pharmaceutical Technology Laboratory, 3000-548 Coimbra, Portugal
- LAQV-REQUIMTE, Galenic and Pharmaceutical Technology Laboratory, Faculty of Pharmacy, Univ. Coimbra, 3000-548 Coimbra, Portugal
| | - Isabel Barbosa
- Univ. Coimbra, Faculty of Pharmacy, Phamaceutical Chemistry Laboratory, 3000-548 Coimbra, Portugal
| | - Marília Dourado
- Univ. Coimbra, Institute for Clinical and Biomedical Research (iCBR) Area of Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine, 3000-548 Coimbra, Portugal
- Univ. Coimbra, Center for Health Studies and Research of the University of Coimbra (CEISUC), Faculty of Medicine, 3000-548 Coimbra, Portugal
- Univ. Coimbra, Center for Studies and Development of Continuous and Palliative Care (CEDCCP), Faculty of Medicine, 3000-548 Coimbra, Portugal
| | - Ana Figueiras
- Univ. Coimbra, Faculty of Pharmacy, Galenic and Pharmaceutical Technology Laboratory, 3000-548 Coimbra, Portugal
- LAQV-REQUIMTE, Galenic and Pharmaceutical Technology Laboratory, Faculty of Pharmacy, Univ. Coimbra, 3000-548 Coimbra, Portugal
| |
Collapse
|
18
|
Mullins M, Himly M, Llopis IR, Furxhi I, Hofer S, Hofstätter N, Wick P, Romeo D, Küehnel D, Siivola K, Catalán J, Hund-Rinke K, Xiarchos I, Linehan S, Schuurbiers D, Bilbao AG, Barruetabeña L, Drobne D. (Re)Conceptualizing decision-making tools in a risk governance framework for emerging technologies-the case of nanomaterials. ENVIRONMENT SYSTEMS & DECISIONS 2022; 43:3-15. [PMID: 35912374 PMCID: PMC9309004 DOI: 10.1007/s10669-022-09870-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/06/2022] [Indexed: 12/03/2022]
Abstract
The utility of decision-making tools for the risk governance of nanotechnology is at the core of this paper. Those working in nanotechnology risk management have been prolific in creating such tools, many derived from European FP7 and H2020-funded projects. What is less clear is how such tools might assist the overarching ambition of creating a fair system of risk governance. In this paper, we reflect upon the role that tools might and should play in any system of risk governance. With many tools designed for the risk governance of this emerging technology falling into disuse, this paper provides an overview of extant tools and addresses their potential shortcomings. We also posit the need for a data readiness tool. With the EUs NMP13 family of research consortia about to report to the Commission on ways forward in terms of risk governance of this domain, this is a timely intervention on an important element of any risk governance system.
Collapse
Affiliation(s)
- Martin Mullins
- Transgero Limited, Cullinagh, Newcastle West, Co., Limerick, Ireland
- Department of Accounting and Finance, Kemmy Business School, University of Limerick, Limerick, Ireland
| | - Martin Himly
- Department of Biosciences, Paris Lodron University of Salzburg (PLUS), 5020 Salzburg, Austria
| | - Isabel Rodríguez Llopis
- GAIKER Technology Centre, Basque Research and Technology Alliance, (BRTA) ES, Gipuzkoa, Spain
| | - Irini Furxhi
- Transgero Limited, Cullinagh, Newcastle West, Co., Limerick, Ireland
- Department of Accounting and Finance, Kemmy Business School, University of Limerick, Limerick, Ireland
| | - Sabine Hofer
- Department of Biosciences, Paris Lodron University of Salzburg (PLUS), 5020 Salzburg, Austria
| | - Norbert Hofstätter
- Department of Biosciences, Paris Lodron University of Salzburg (PLUS), 5020 Salzburg, Austria
| | - Peter Wick
- Particles-Biology Interactions Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology, Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland
| | - Daina Romeo
- Particles-Biology Interactions Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology, Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland
| | - Dana Küehnel
- Department Bioanalytical Ecotoxicology (BIOTOX), Helmholtz Centre for Environmental Research - UFZ, Permoserstraße 15, 04318 Leipzig, Germany
| | - Kirsi Siivola
- Finnish Institute of Occupational Health, Työterveyslaitos, Box 40, 00032 Helsinki, Finland
| | - Julia Catalán
- Finnish Institute of Occupational Health, Työterveyslaitos, Box 40, 00032 Helsinki, Finland
- Department of Anatomy, Embryology and Genetics, University of Zaragoza, Saragossa, Spain
| | - Kerstin Hund-Rinke
- Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Auf dem Aberg 1, 57392 Schmallenberg, Germany
| | - Ioannis Xiarchos
- Research Lab of Advanced Composite, Nanomaterials, and Nanotechnology (R-NanoLab), School of Chemical Engineering, National Technical University of Athens, 9 Heroon Polytechniou str, 15780 Zographos, Athens Greece
| | - Shona Linehan
- Management, Cairnes School of Business and Economics, National University of Ireland Galway, Galway, Ireland
| | - Daan Schuurbiers
- De Proeffabriek Josef Israelslaan 63, NL-6813 JB Arnhem, The Netherlands
| | - Amaia García Bilbao
- GAIKER Technology Centre, Basque Research and Technology Alliance, (BRTA) ES, Gipuzkoa, Spain
| | - Leire Barruetabeña
- GAIKER Technology Centre, Basque Research and Technology Alliance, (BRTA) ES, Gipuzkoa, Spain
| | - Damjana Drobne
- Department Biology, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| |
Collapse
|
19
|
Kad A, Pundir A, Arya SK, Puri S, Khatri M. Meta-analysis of in-vitro cytotoxicity evaluation studies of zinc oxide nanoparticles: Paving way for safer innovations. Toxicol In Vitro 2022; 83:105418. [PMID: 35724836 DOI: 10.1016/j.tiv.2022.105418] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/03/2022] [Accepted: 06/14/2022] [Indexed: 02/02/2023]
Abstract
Nano-based products have shown their daunting presence in several sectors. Among them, Zinc Oxide (ZnO) nanoparticles wangled the reputation of providing "next-generation solutions" and are being utilized in plethora of products. Their widespread application has led to increased exposure of these particles, raising concerns regarding toxicological repercussions to the human health and environment. The diversity, complexity, and heterogeneity in the available literature, along with correlation of befitting attributes, makes it challenging to develop one systematic framework to predict this toxicity. The present study aims at developing predictive modelling framework to tap the prospective features responsible for causing cytotoxicity in-vitro on exposure to ZnO nanoparticles. Rigorous approach was used to mine the information from complete body of evidence published to date. The attributes, features and experimental conditions were systematically extracted to unmask the effect of varied features. 1240 data points from 76 publications were obtained, containing 14 qualitative and quantitative attributes, including physiochemical properties of nanoparticles, cell culture and experimental parameters to perform meta-analysis. For the first time, the efforts were made to investigate the degree of significance of attributes accountable for causing cytotoxicity on exposure to ZnO nanoparticles. We show that in-vitro cytotoxicity is closely related with dose concentration of nanoparticles, followed by exposure time, disease state of the cell line and size of these nanoparticles among other attributes.
Collapse
Affiliation(s)
- Anaida Kad
- Department of Biotechnology, University Institute of Engineering and Technology, Panjab University, Sector-25, Chandigarh 160014, India
| | - Archit Pundir
- Department of Biotechnology, University Institute of Engineering and Technology, Panjab University, Sector-25, Chandigarh 160014, India
| | - Shailendra Kumar Arya
- Department of Biotechnology, University Institute of Engineering and Technology, Panjab University, Sector-25, Chandigarh 160014, India
| | - Sanjeev Puri
- Department of Biotechnology, University Institute of Engineering and Technology, Panjab University, Sector-25, Chandigarh 160014, India
| | - Madhu Khatri
- Department of Biotechnology, University Institute of Engineering and Technology, Panjab University, Sector-25, Chandigarh 160014, India; Wellcome trustTrust/DBT IA Early Career Fellow Panjab University, Chandigarh 160014, India.
| |
Collapse
|
20
|
Stoliński F, Rybińska-Fryca A, Gromelski M, Mikolajczyk A, Puzyn T. NanoMixHamster: a web-based tool for predicting cytotoxicity of TiO 2-based multicomponent nanomaterials toward Chinese hamster ovary (CHO-K1) cells. Nanotoxicology 2022; 16:276-289. [PMID: 35713578 DOI: 10.1080/17435390.2022.2080609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Nano-QSAR models can be effectively used for prediction of the biological activity of nanomaterials that have not been experimentally tested before. However, their use is associated with the need to have appropriate knowledge and skills in chemoinformatics. Thus, they are mainly aimed at specialists in the field. This significantly limits the potential group of recipients of the developed solutions. In this perspective, the purpose of the presented research was to develop an easily accessible and user-friendly web-based application that could enable the prediction of TiO2-based multicomponent nanomaterials cytotoxicity toward Chinese Hamster Ovary (CHO-K1) cells. The graphical user interface is clear and intuitive and the only information required from the user is the type and concentration of the metals which will be modifying TiO2-based nanomaterial. Thanks to this, the application will be easy to use not only by cheminformatics but also by specialists in the field of nanotechnology or toxicology, who will be able to quickly predict cytotoxicity of desired nanoclusters. We have performed case studies to demonstrate the features and utilities of developed application. The NanoMixHamster application is freely available at https://nanomixhamster.cloud.nanosolveit.eu/.
Collapse
Affiliation(s)
- Filip Stoliński
- QSAR Lab Ltd, Gdansk, Poland.,Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | | | | | - Alicja Mikolajczyk
- QSAR Lab Ltd, Gdansk, Poland.,Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Tomasz Puzyn
- QSAR Lab Ltd, Gdansk, Poland.,Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| |
Collapse
|
21
|
Toropova AP, Toropov AA. Nanomaterials: Quasi-SMILES as a flexible basis for regulation and environmental risk assessment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 823:153747. [PMID: 35149067 DOI: 10.1016/j.scitotenv.2022.153747] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 06/14/2023]
Abstract
Basic principles and problems of the systematization of data on nanomaterials are discussed. The eclectic character of nanomaterials is defined as the key difference between nanomaterials and traditional substances. The quasi-SMILES technique is described and discussed. The possible role of the approach is bridging between experimentalists and developers of models for endpoints related to nanomaterials. The use of models on the possible impact of nanomaterials on the environment and human health has been collected and compared. The new criteria of the predictive potential for the above models are discussed. The advantage of the statistical criteria sensitive simultaneously to both the correlation coefficient and the root mean square error noted. The rejection of the border between the effect of the biochemical reality of substances at a molecular level and the effect of experiment conditions at the macro level gives the possibility to develop models that are epistemologically more reliable in the comparison with traditional models based exclusively on the molecular structure-biological activity interdependence (without taking into account experimental conditions). Models of the physicochemical and biochemical behaviour of nanomaterials are necessary in order to develop and apply new industrial achievements, everyday comfort species, medicine, cosmetics, and foods without negative effects on ecology and human health. The CORAL (abbreviation CORrelation And Logic) software provides the user with the possibility to build up nano-QSAR models as a mathematical function of so-called correlation weights of fragments of quasi-SMILES. These models are built up via the Monte Carlo method. Apparently, the quasi-SMILES is a universal representation of nano-reality since there is no limitation to choose the list of eclectic data able to have an impact on nano-phenomena. This paradigm is a convenient language to the conversation of experimentalists and developers of models for nano-phenomena.
Collapse
Affiliation(s)
- Alla P Toropova
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy.
| | - Andrey A Toropov
- Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Via Mario Negri 2, 20156 Milano, Italy
| |
Collapse
|
22
|
Wang W, Ouyang D. Opportunities and challenges of physiologically based pharmacokinetic modeling in drug delivery. Drug Discov Today 2022; 27:2100-2120. [PMID: 35452792 DOI: 10.1016/j.drudis.2022.04.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/03/2022] [Accepted: 04/13/2022] [Indexed: 12/15/2022]
Abstract
Physiologically based pharmacokinetic (PBPK) modeling is an important in silico tool to bridge drug properties and in vivo PK behaviors during drug development. Over the recent decade, the PBPK method has been largely applied to drug delivery systems (DDS), including oral, inhaled, transdermal, ophthalmic, and complex injectable products. The related therapeutic agents have included small-molecule drugs, therapeutic proteins, nucleic acids, and even cells. Simulation results have provided important insights into PK behaviors of new dosage forms, which strongly support drug regulation. In this review, we comprehensively summarize recent progress in PBPK applications in drug delivery, which shows large opportunities for facilitating drug development. In addition, we discuss the challenges of applying this methodology from a practical viewpoint.
Collapse
Affiliation(s)
- Wei Wang
- Institute of Chinese Medical Sciences (ICMS), State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau, China; Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Macau, China
| | - Defang Ouyang
- Institute of Chinese Medical Sciences (ICMS), State Key Laboratory of Quality Research in Chinese Medicine, University of Macau, Macau, China; Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Macau, China.
| |
Collapse
|
23
|
Forest V. Experimental and Computational Nanotoxicology-Complementary Approaches for Nanomaterial Hazard Assessment. NANOMATERIALS 2022; 12:nano12081346. [PMID: 35458054 PMCID: PMC9031966 DOI: 10.3390/nano12081346] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/07/2022] [Accepted: 04/12/2022] [Indexed: 12/25/2022]
Abstract
The growing development and applications of nanomaterials lead to an increasing release of these materials in the environment. The adverse effects they may elicit on ecosystems or human health are not always fully characterized. Such potential toxicity must be carefully assessed with the underlying mechanisms elucidated. To that purpose, different approaches can be used. First, experimental toxicology consisting of conducting in vitro or in vivo experiments (including clinical studies) can be used to evaluate the nanomaterial hazard. It can rely on variable models (more or less complex), allowing the investigation of different biological endpoints. The respective advantages and limitations of in vitro and in vivo models are discussed as well as some issues associated with experimental nanotoxicology. Perspectives of future developments in the field are also proposed. Second, computational nanotoxicology, i.e., in silico approaches, can be used to predict nanomaterial toxicity. In this context, we describe the general principles, advantages, and limitations especially of quantitative structure–activity relationship (QSAR) models and grouping/read-across approaches. The aim of this review is to provide an overview of these different approaches based on examples and highlight their complementarity.
Collapse
Affiliation(s)
- Valérie Forest
- Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, Etablissement Français du Sang, INSERM, U1059 Sainbiose, Centre CIS, F-42023 Saint-Etienne, France
| |
Collapse
|
24
|
Serra A, Saarimäki LA, Pavel A, del Giudice G, Fratello M, Cattelani L, Federico A, Laurino O, Marwah VS, Fortino V, Scala G, Sofia Kinaret PA, Greco D. Nextcast: A software suite to analyse and model toxicogenomics data. Comput Struct Biotechnol J 2022; 20:1413-1426. [PMID: 35386103 PMCID: PMC8956870 DOI: 10.1016/j.csbj.2022.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 03/16/2022] [Accepted: 03/16/2022] [Indexed: 11/28/2022] Open
Abstract
The recent advancements in toxicogenomics have led to the availability of large omics data sets, representing the starting point for studying the exposure mechanism of action and identifying candidate biomarkers for toxicity prediction. The current lack of standard methods in data generation and analysis hampers the full exploitation of toxicogenomics-based evidence in regulatory risk assessment. Moreover, the pipelines for the preprocessing and downstream analyses of toxicogenomic data sets can be quite challenging to implement. During the years, we have developed a number of software packages to address specific questions related to multiple steps of toxicogenomics data analysis and modelling. In this review we present the Nextcast software collection and discuss how its individual tools can be combined into efficient pipelines to answer specific biological questions. Nextcast components are of great support to the scientific community for analysing and interpreting large data sets for the toxicity evaluation of compounds in an unbiased, straightforward, and reliable manner. The Nextcast software suite is available at: ( https://github.com/fhaive/nextcast).
Collapse
Affiliation(s)
- Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Alisa Pavel
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Giusy del Giudice
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Michele Fratello
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Luca Cattelani
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
| | | | - Veer Singh Marwah
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
| | - Vittorio Fortino
- Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Giovanni Scala
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Department of Biology, University of Naples Federico II, Naples, Italy
| | - Pia Anneli Sofia Kinaret
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere University, Tampere, Finland
- Finnish Hub for Development and Validation of Integrated Approaches (FHAIVE), Tampere, Finland
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| |
Collapse
|
25
|
Hofer S, Hofstätter N, Punz B, Hasenkopf I, Johnson L, Himly M. Immunotoxicity of nanomaterials in health and disease: Current challenges and emerging approaches for identifying immune modifiers in susceptible populations. WILEY INTERDISCIPLINARY REVIEWS. NANOMEDICINE AND NANOBIOTECHNOLOGY 2022; 14:e1804. [PMID: 36416020 PMCID: PMC9787548 DOI: 10.1002/wnan.1804] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/24/2022] [Accepted: 03/30/2022] [Indexed: 11/24/2022]
Abstract
Nanosafety assessment has experienced an intense era of research during the past decades driven by a vivid interest of regulators, industry, and society. Toxicological assays based on in vitro cellular models have undergone an evolution from experimentation using nanoparticulate systems on singular epithelial cell models to employing advanced complex models more realistically mimicking the respective body barriers for analyzing their capacity to alter the immune state of exposed individuals. During this phase, a number of lessons were learned. We have thus arrived at a state where the next chapters have to be opened, pursuing the following objectives: (1) to elucidate underlying mechanisms, (2) to address effects on vulnerable groups, (3) to test material mixtures, and (4) to use realistic doses on (5) sophisticated models. Moreover, data reproducibility has become a significant demand. In this context, we studied the emerging concept of adverse outcome pathways (AOPs) from the perspective of immune activation and modulation resulting in pro-inflammatory versus tolerogenic responses. When considering the interaction of nanomaterials with biological systems, protein corona formation represents the relevant molecular initiating event (e.g., by potential alterations of nanomaterial-adsorbed proteins). Using this as an example, we illustrate how integrated experimental-computational workflows combining in vitro assays with in silico models aid in data enrichment and upon comprehensive ontology-annotated (meta)data upload to online repositories assure FAIRness (Findability, Accessibility, Interoperability, Reusability). Such digital twinning may, in future, assist in early-stage decision-making during therapeutic development, and hence, promote safe-by-design innovation in nanomedicine. Moreover, it may, in combination with in silico-based exposure-relevant dose-finding, serve for risk monitoring in particularly loaded areas, for example, workplaces, taking into account pre-existing health conditions. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials.
Collapse
Affiliation(s)
- Sabine Hofer
- Division of Allergy & Immunology, Department of Biosciences & Medical BiologyParis Lodron University of SalzburgSalzburgAustria
| | - Norbert Hofstätter
- Division of Allergy & Immunology, Department of Biosciences & Medical BiologyParis Lodron University of SalzburgSalzburgAustria
| | - Benjamin Punz
- Division of Allergy & Immunology, Department of Biosciences & Medical BiologyParis Lodron University of SalzburgSalzburgAustria
| | - Ingrid Hasenkopf
- Division of Allergy & Immunology, Department of Biosciences & Medical BiologyParis Lodron University of SalzburgSalzburgAustria
| | - Litty Johnson
- Division of Allergy & Immunology, Department of Biosciences & Medical BiologyParis Lodron University of SalzburgSalzburgAustria
| | - Martin Himly
- Division of Allergy & Immunology, Department of Biosciences & Medical BiologyParis Lodron University of SalzburgSalzburgAustria
| |
Collapse
|
26
|
Furxhi I. Health and environmental safety of nanomaterials: O Data, Where Art Thou? NANOIMPACT 2022; 25:100378. [PMID: 35559884 DOI: 10.1016/j.impact.2021.100378] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/15/2021] [Accepted: 12/17/2021] [Indexed: 06/15/2023]
Abstract
Nanotechnology keeps drawing attention due to the great tunable properties of nanomaterials in comparison to their bulk conventional materials. The growth of nanotechnology in combination with the digitization era has led to an increased need of safety related data. In addition to safety, new data-driven paradigms on safe and sustainable by design materials are stressing the necessity of data even more. Data is a fundamental asset to the scientific community in studying and analysing the entire life-cycle of nanomaterials. Unfortunately, data exist in a scattered fashion, in different sources and formats. To our knowledge, there is no study focusing on aspects of actual data-structure knowledge that exists in literature and databases. The purpose of this review research is to transparently and comprehensively, display to the nanoscience community the datasets readily available for machine learning purposes making it convenient and more efficient for the next users such as modellers or data curators to retrieve information. We systematically recorded the features and descriptors available in the datasets and provide synopsised information on their ranges, forms and metrics in the supplementary material.
Collapse
Affiliation(s)
- Irini Furxhi
- Transgero Limited, Cullinagh, Newcastle West, Co. Limerick, Ireland; Dept. of Accounting and Finance, Kemmy Business School, University of Limerick, V94PH93, Ireland.
| |
Collapse
|
27
|
Sánchez Jiménez A, Puelles R, Perez-Fernandez M, Barruetabeña L, Jacobsen NR, Suarez-Merino B, Micheletti C, Manier N, Salieri B, Hischier R, Tsekovska R, Handzhiyski Y, Bouillard J, Oudart Y, Galea KS, Kelly S, Shandilya N, Goede H, Gomez-Cordon J, Jensen KA, van Tongeren M, Apostolova MD, Llopis IR. Safe(r) by design guidelines for the nanotechnology industry. NANOIMPACT 2022; 25:100385. [PMID: 35559891 DOI: 10.1016/j.impact.2022.100385] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/24/2022] [Accepted: 01/24/2022] [Indexed: 06/15/2023]
Abstract
Expectations for safer and sustainable chemicals and products are growing to comply with the United Nations and European strategies for sustainability. The application of Safe(r) by Design (SbD) in nanotechnology implies an iterative process where functionality, human health and safety, environmental and economic impact and cost are assessed and balanced as early as possible in the innovation process and updated at each step. The EU H2020 NanoReg2 project was the first European project to implement SbD in six companies handling and/or manufacturing nanomaterials (NMs) and nano-enabled products (NEP). The results from this experience have been used to develop these guidelines on the practical application of SbD. The SbD approach foresees the identification, estimation, and reduction of human and environmental risks as early as possible in the development of a NM or NEP, and it is based on three pillars: (i) safer NMs and NEP; (ii) safer use and end of life and (iii) safer industrial production. The presented guidelines include a set of information and tools that will help deciding at each step of the innovation process whether to continue, apply SbD measures or carry out further tests to reduce uncertainty. It does not intend to be a prescriptive protocol where all suggested steps have to be followed to achieve a SbD NM/NEP or process. Rather, the guidelines are designed to identify risks at an early state and information to be considered to identify those risks. Each company adapts the approach to its specific needs and circumstances as company decisions influence the way forward.
Collapse
Affiliation(s)
| | - Raquel Puelles
- Avanzare Innovación Tecnológica S.L., Av. Lentiscares, 4-6, 26370 Navarrete, La Rioja, Spain
| | - Marta Perez-Fernandez
- Avanzare Innovación Tecnológica S.L., Av. Lentiscares, 4-6, 26370 Navarrete, La Rioja, Spain
| | - Leire Barruetabeña
- GAIKER Technology Centre, Basque Research and Technology Alliance (BRTA), Parque Tecnológico de Bizkaia, E-48170 Zamudio, Spain
| | - Nicklas Raun Jacobsen
- National Research Centre for the Working Environment (NRCWE), Lersoe Park Alle 105, 2100 Copenhagen, Denmark
| | | | | | - Nicolas Manier
- Institut national de l'environnement industriel et des risques (INERIS), Verneuil-en-Halatte 60550, France
| | - Beatrice Salieri
- TEMAS AG, 8048 Zurich, Switzerland; Swiss Federal Laboratories for Materials Science and Technology (Empa), Technology and Society Lab (TSL), Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland
| | - Roland Hischier
- Swiss Federal Laboratories for Materials Science and Technology (Empa), Technology and Society Lab (TSL), Lerchenfeldstrasse 5, 9014 St. Gallen, Switzerland
| | - Rositsa Tsekovska
- Roumen Tsanev Institute of Molecular Biology, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 21, 1113 Sofia, Bulgaria
| | - Yordan Handzhiyski
- Roumen Tsanev Institute of Molecular Biology, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 21, 1113 Sofia, Bulgaria
| | - Jacques Bouillard
- Institut national de l'environnement industriel et des risques (INERIS), Verneuil-en-Halatte 60550, France
| | - Yohan Oudart
- Nanomakers, 1 Rue de Clairefontaine, 78 120 Rambouillet, France
| | - Karen S Galea
- Institute of Occupational Medicine (IOM), Research Avenue North, Edinburgh, UK
| | - Sean Kelly
- Nanotechnology Industries Association (NIA), Avenue Tervueren 143, 1150 Brussels, Belgium
| | | | - Henk Goede
- TNO, Princetonlaan 6, 3584 CB Utrecht, Netherlands
| | - Julio Gomez-Cordon
- Avanzare Innovación Tecnológica S.L., Av. Lentiscares, 4-6, 26370 Navarrete, La Rioja, Spain
| | - Keld Alstrup Jensen
- National Research Centre for the Working Environment (NRCWE), Lersoe Park Alle 105, 2100 Copenhagen, Denmark
| | - Martie van Tongeren
- School of Health Sciences, The University of Manchester, Oxford Rd., Manchester M13 9PL,UK
| | - Margarita D Apostolova
- Roumen Tsanev Institute of Molecular Biology, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., bl. 21, 1113 Sofia, Bulgaria
| | - Isabel Rodríguez Llopis
- GAIKER Technology Centre, Basque Research and Technology Alliance (BRTA), Parque Tecnológico de Bizkaia, E-48170 Zamudio, Spain
| |
Collapse
|
28
|
Lynch I, Nymark P, Doganis P, Gulumian M, Yoon TH, Martinez DST, Afantitis A. Methods, models, mechanisms and metadata: Introducing the Nanotoxicology collection at F1000Research. F1000Res 2021; 10:1196. [PMID: 34853679 PMCID: PMC8613506 DOI: 10.12688/f1000research.75113.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/03/2021] [Indexed: 11/28/2022] Open
Abstract
Nanotoxicology is a relatively new field of research concerning the study and application of nanomaterials to evaluate the potential for harmful effects in parallel with the development of applications. Nanotoxicology as a field spans materials synthesis and characterisation, assessment of fate and behaviour, exposure science, toxicology / ecotoxicology, molecular biology and toxicogenomics, epidemiology, safe and sustainable by design approaches, and chemoinformatics and nanoinformatics, thus requiring scientists to work collaboratively, often outside their core expertise area. This interdisciplinarity can lead to challenges in terms of interpretation and reporting, and calls for a platform for sharing of best-practice in nanotoxicology research. The F1000Research Nanotoxicology collection, introduced via this editorial, will provide a place to share accumulated best practice, via original research reports including no-effects studies, protocols and methods papers, software reports and living systematic reviews, which can be updated as new knowledge emerges or as the domain of applicability of the method, model or software is expanded. This editorial introduces the Nanotoxicology Collection in
F1000Research. The aim of the collection is to provide an open access platform for nanotoxicology researchers, to support an improved culture of
data sharing and documentation of evolving protocols, biological and computational models, software tools and datasets, that can be applied and built upon to develop predictive models and move towards
in silico nanotoxicology and nanoinformatics. Submissions will be assessed for fit to the collection and subjected to the F1000Research open peer review process.
Collapse
Affiliation(s)
- Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Penny Nymark
- Institute of Environmental Medicine, Karolinska Institutet, Nobels väg 13, Stockholm, 17 177, Sweden
| | - Philip Doganis
- School of Chemical Engineering, National Technical University of Athens, Athens, 10682, Greece
| | - Mary Gulumian
- National Health Laboratory Services, 1 Modderfontein Rd, Sandringham, Johannesburg, 2192, South Africa.,Haematology and Molecular Medicine, University of the Witwatersrand, 1 Jan Smuts Ave, Johannesburg, 2000, South Africa.,Water Research Group, Unit for Environmental Sciences and Management Potchefstroom, North West University, Potchefstroom, South Africa
| | - Tae-Hyun Yoon
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul, 04763, South Korea.,Institute of Next Generation Material Design, Hanyang University, Seoul, 04763, South Korea
| | - Diego S T Martinez
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas,, Sao Paulo, CEP 13083-970, Brazil
| | | |
Collapse
|
29
|
Varsou DD, Ellis LJA, Afantitis A, Melagraki G, Lynch I. Ecotoxicological read-across models for predicting acute toxicity of freshly dispersed versus medium-aged NMs to Daphnia magna. CHEMOSPHERE 2021; 285:131452. [PMID: 34265725 DOI: 10.1016/j.chemosphere.2021.131452] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 06/29/2021] [Accepted: 07/04/2021] [Indexed: 06/13/2023]
Abstract
Nanoinformatics models to predict the toxicity/ecotoxicity of nanomaterials (NMs) are urgently needed to support commercialization of nanotechnologies and allow grouping of NMs based on their physico-chemical and/or (eco)toxicological properties, to facilitate read-across of knowledge from data-rich NMs to data-poor ones. Here we present the first ecotoxicological read-across models for predicting NMs ecotoxicity, which were developed in accordance with ECHA's recommended strategy for grouping of NMs as a means to explore in silico the effects of a panel of freshly dispersed versus environmentally aged (in various media) Ag and TiO2 NMs on the freshwater zooplankton Daphnia magna, a keystone species used in regulatory testing. The dataset used to develop the models consisted of dose-response data from 11 NMs (5 TiO2 NMs of identical cores with different coatings, and 6 Ag NMs with different capping agents/coatings) each dispersed in three different media (a high hardness medium (HH Combo) and two representative river waters containing different amounts of natural organic matter (NOM) and having different ionic strengths), generated in accordance with the OECD 202 immobilization test. The experimental hypotheses being tested were (1) that the presence of NOM in the medium would reduce the toxicity of the NMs by forming an ecological corona, and (2) that environmental ageing of NMs reduces their toxicity compared to the freshly dispersed NMs irrespective of the medium composition (salt only or NOM-containing). As per the ECHA guidance, the NMs were grouped into two categories - freshly dispersed and 2-year-aged and explored in silico to identify the most important features driving the toxicity in each group. The final predictive models have been validated according to the OECD criteria and a QSAR model report form (QMRF) report included in the supplementary information to support adoption of the models for regulatory purposes.
Collapse
Affiliation(s)
| | - Laura-Jayne A Ellis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT, Birmingham, UK
| | | | - Georgia Melagraki
- Division of Physical Sciences and Applications, Hellenic Military Academy, Vari, Greece.
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT, Birmingham, UK.
| |
Collapse
|
30
|
Wang W, Ye Z, Gao H, Ouyang D. Computational pharmaceutics - A new paradigm of drug delivery. J Control Release 2021; 338:119-136. [PMID: 34418520 DOI: 10.1016/j.jconrel.2021.08.030] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 08/17/2021] [Accepted: 08/17/2021] [Indexed: 01/18/2023]
Abstract
In recent decades pharmaceutics and drug delivery have become increasingly critical in the pharmaceutical industry due to longer time, higher cost, and less productivity of new molecular entities (NMEs). However, current formulation development still relies on traditional trial-and-error experiments, which are time-consuming, costly, and unpredictable. With the exponential growth of computing capability and algorithms, in recent ten years, a new discipline named "computational pharmaceutics" integrates with big data, artificial intelligence, and multi-scale modeling techniques into pharmaceutics, which offered great potential to shift the paradigm of drug delivery. Computational pharmaceutics can provide multi-scale lenses to pharmaceutical scientists, revealing physical, chemical, mathematical, and data-driven details ranging across pre-formulation studies, formulation screening, in vivo prediction in the human body, and precision medicine in the clinic. The present paper provides a comprehensive and detailed review in all areas of computational pharmaceutics and "Pharma 4.0", including artificial intelligence and machine learning algorithms, molecular modeling, mathematical modeling, process simulation, and physiologically based pharmacokinetic (PBPK) modeling. We not only summarized the theories and progress of these technologies but also discussed the regulatory requirements, current challenges, and future perspectives in the area, such as talent training and a culture change in the future pharmaceutical industry.
Collapse
Affiliation(s)
- Wei Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China
| | - Zhuyifan Ye
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China
| | - Hanlu Gao
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China
| | - Defang Ouyang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences (ICMS), University of Macau, Macau, China.
| |
Collapse
|
31
|
Guo Z, Chakraborty S, Monikh FA, Varsou DD, Chetwynd AJ, Afantitis A, Lynch I, Zhang P. Surface Functionalization of Graphene-Based Materials: Biological Behavior, Toxicology, and Safe-By-Design Aspects. Adv Biol (Weinh) 2021; 5:e2100637. [PMID: 34288601 DOI: 10.1002/adbi.202100637] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 06/11/2021] [Indexed: 01/08/2023]
Abstract
The increasing exploitation of graphene-based materials (GBMs) is driven by their unique properties and structures, which ignite the imagination of scientists and engineers. At the same time, the very properties that make them so useful for applications lead to growing concerns regarding their potential impacts on human health and the environment. Since GBMs are inert to reaction, various attempts of surface functionalization are made to make them reactive. Herein, surface functionalization of GBMs, including those intentionally designed for specific applications, as well as those unintentionally acquired (e.g., protein corona formation) from the environment and biota, are reviewed through the lenses of nanotoxicity and design of safe materials (safe-by-design). Uptake and toxicity of functionalized GBMs and the underlying mechanisms are discussed and linked with the surface functionalization. Computational tools that can predict the interaction of GBMs behavior with their toxicity are discussed. A concise framing of current knowledge and key features of GBMs to be controlled for safe and sustainable applications are provided for the community.
Collapse
Affiliation(s)
- Zhiling Guo
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Swaroop Chakraborty
- Department of Biological Engineering, Indian Institute of Technology, Gandhinagar, Gujarat, 382355, India
| | - Fazel Abdolahpur Monikh
- Department of Environmental & Biological Sciences, University of Eastern Finland, P.O. Box 111, Joensuu, FI-80101, Finland
| | - Dimitra-Danai Varsou
- School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece
| | - Andrew J Chetwynd
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Antreas Afantitis
- Department of ChemoInformatics, NovaMechanics Ltd., Nicosia, 1046, Cyprus
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Peng Zhang
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| |
Collapse
|
32
|
Zhang P, Guo Z, Ullah S, Melagraki G, Afantitis A, Lynch I. Nanotechnology and artificial intelligence to enable sustainable and precision agriculture. NATURE PLANTS 2021; 7:864-876. [PMID: 34168318 DOI: 10.1038/s41477-021-00946-6] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 05/17/2021] [Indexed: 06/13/2023]
Abstract
Climate change, increasing populations, competing demands on land for production of biofuels and declining soil quality are challenging global food security. Finding sustainable solutions requires bold new approaches and integration of knowledge from diverse fields, such as materials science and informatics. The convergence of precision agriculture, in which farmers respond in real time to changes in crop growth with nanotechnology and artificial intelligence, offers exciting opportunities for sustainable food production. Coupling existing models for nutrient cycling and crop productivity with nanoinformatics approaches to optimize targeting, uptake, delivery, nutrient capture and long-term impacts on soil microbial communities will enable design of nanoscale agrochemicals that combine optimal safety and functionality profiles.
Collapse
Affiliation(s)
- Peng Zhang
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK.
| | - Zhiling Guo
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
| | - Sami Ullah
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
| | - Georgia Melagraki
- Division of Physical Sciences and Applications, Hellenic Military Academy, Vari, Greece
| | | | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
| |
Collapse
|
33
|
Amos JD, Tian Y, Zhang Z, Lowry GV, Wiesner MR, Hendren CO. The NanoInformatics Knowledge Commons: Capturing spatial and temporal nanomaterial transformations in diverse systems. NANOIMPACT 2021; 23:100331. [PMID: 35559832 DOI: 10.1016/j.impact.2021.100331] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 05/25/2021] [Accepted: 06/04/2021] [Indexed: 06/15/2023]
Abstract
The empirical necessity for integrating informatics throughout the experimental process has become a focal point of the nano-community as we work in parallel to converge efforts for making nano-data reproducible and accessible. The NanoInformatics Knowledge Commons (NIKC) Database was designed to capture the complex relationship between nanomaterials and their environments over time in the concept of an 'Instance'. Our Instance Organizational Structure (IOS) was built to record metadata on nanomaterial transformations in an organizational structure permitting readily accessible data for broader scientific inquiry. By transforming published and on-going data into the IOS we are able to tell the full transformational journey of a nanomaterial within its experimental life cycle. The IOS structure has prepared curated data to be fully analyzed to uncover relationships between observable phenomenon and medium or nanomaterial characteristics. Essential to building the NIKC database and associated applications was incorporating the researcher's needs into every level of development. We started by centering the research question, the query, and the necessary data needed to support the question and query. The process used to create nanoinformatic tools informs usability and analytical capability. In this paper we present the NIKC database, our developmental process, and its curated contents. We also present the Collaboration Tool which was built to foster building new collaboration teams. Through these efforts we aim to: 1) elucidate the general principles that determine nanomaterial behavior in the environment; 2) identify metadata necessary to predict exposure potential and bio-uptake; and 3) identify key characterization assays that predict outcomes of interest.
Collapse
Affiliation(s)
- Jaleesia D Amos
- Center for the Environmental Implications of Nano Technology (CEINT), United States; Civil & Environmental Engineering, Duke University, Durham, North Carolina 27708, United States
| | - Yuan Tian
- Center for the Environmental Implications of Nano Technology (CEINT), United States; Civil & Environmental Engineering, Duke University, Durham, North Carolina 27708, United States
| | - Zhao Zhang
- Center for the Environmental Implications of Nano Technology (CEINT), United States; Civil & Environmental Engineering, Duke University, Durham, North Carolina 27708, United States
| | - Greg V Lowry
- Center for the Environmental Implications of Nano Technology (CEINT), United States; Civil & Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States
| | - Mark R Wiesner
- Center for the Environmental Implications of Nano Technology (CEINT), United States; Civil & Environmental Engineering, Duke University, Durham, North Carolina 27708, United States.
| | - Christine Ogilvie Hendren
- Center for the Environmental Implications of Nano Technology (CEINT), United States; Civil & Environmental Engineering, Duke University, Durham, North Carolina 27708, United States
| |
Collapse
|
34
|
Da Silva GH, Franqui LS, Petry R, Maia MT, Fonseca LC, Fazzio A, Alves OL, Martinez DST. Recent Advances in Immunosafety and Nanoinformatics of Two-Dimensional Materials Applied to Nano-imaging. Front Immunol 2021; 12:689519. [PMID: 34149731 PMCID: PMC8210669 DOI: 10.3389/fimmu.2021.689519] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/10/2021] [Indexed: 01/10/2023] Open
Abstract
Two-dimensional (2D) materials have emerged as an important class of nanomaterials for technological innovation due to their remarkable physicochemical properties, including sheet-like morphology and minimal thickness, high surface area, tuneable chemical composition, and surface functionalization. These materials are being proposed for new applications in energy, health, and the environment; these are all strategic society sectors toward sustainable development. Specifically, 2D materials for nano-imaging have shown exciting opportunities in in vitro and in vivo models, providing novel molecular imaging techniques such as computed tomography, magnetic resonance imaging, fluorescence and luminescence optical imaging and others. Therefore, given the growing interest in 2D materials, it is mandatory to evaluate their impact on the immune system in a broader sense, because it is responsible for detecting and eliminating foreign agents in living organisms. This mini-review presents an overview on the frontier of research involving 2D materials applications, nano-imaging and their immunosafety aspects. Finally, we highlight the importance of nanoinformatics approaches and computational modeling for a deeper understanding of the links between nanomaterial physicochemical properties and biological responses (immunotoxicity/biocompatibility) towards enabling immunosafety-by-design 2D materials.
Collapse
Affiliation(s)
- Gabriela H. Da Silva
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
| | - Lidiane S. Franqui
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
- School of Technology, University of Campinas (Unicamp), Limeira, Brazil
| | - Romana Petry
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
- Center of Natural and Human Sciences, Federal University of ABC (UFABC), Santo Andre, Brazil
| | - Marcella T. Maia
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
| | - Leandro C. Fonseca
- NanoBioss Laboratory and Solid State Chemistry Laboratory (LQES), Institute of Chemistry, University of Campinas (Unicamp), Campinas, Brazil
| | - Adalberto Fazzio
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
- Center of Natural and Human Sciences, Federal University of ABC (UFABC), Santo Andre, Brazil
| | - Oswaldo L. Alves
- NanoBioss Laboratory and Solid State Chemistry Laboratory (LQES), Institute of Chemistry, University of Campinas (Unicamp), Campinas, Brazil
| | - Diego Stéfani T. Martinez
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, Brazil
- School of Technology, University of Campinas (Unicamp), Limeira, Brazil
| |
Collapse
|
35
|
Ahmad F, Mahmood A, Muhmood T. Machine learning-integrated omics for the risk and safety assessment of nanomaterials. Biomater Sci 2021; 9:1598-1608. [PMID: 33443512 DOI: 10.1039/d0bm01672a] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessities to advanced electronics, health care products and medicines. Therefore, nanoproducts, however, can have negative side effects and must be strictly monitored to avoid negative outcomes. Future toxicity and safety challenges regarding nanomaterial incorporation into consumer products, including rapid addition of nanomaterials with diverse functionalities and attributes, highlight the limitations of traditional safety evaluation tools. Currently, artificial intelligence and machine learning algorithms are envisioned for enhancing and improving the nano-bio-interaction simulation and modeling, and they extend to the post-marketing surveillance of nanomaterials in the real world. Thus, hyphenation of machine learning with biology and nanomaterials could provide exclusive insights into the perturbations of delicate biological functions after integration with nanomaterials. In this review, we discuss the potential of combining integrative omics with machine learning in profiling nanomaterial safety and risk assessment and provide guidance for regulatory authorities as well.
Collapse
Affiliation(s)
- Farooq Ahmad
- College of Engineering and Applied Sciences, Nanjing National Laboratory of Microstructures, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, Jiangsu 210093, China.
| | - Asif Mahmood
- Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing, 100081, China
| | - Tahir Muhmood
- State Key Lab of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| |
Collapse
|
36
|
Papadiamantis AG, Afantitis A, Tsoumanis A, Valsami-Jones E, Lynch I, Melagraki G. Computational enrichment of physicochemical data for the development of a ζ-potential read-across predictive model with Isalos Analytics Platform. NANOIMPACT 2021; 22:100308. [PMID: 35559965 DOI: 10.1016/j.impact.2021.100308] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/01/2021] [Accepted: 03/01/2021] [Indexed: 06/15/2023]
Abstract
The physicochemical characterisation data from a library of 69 engineered nanomaterials (ENMs) has been exploited in silico following enrichment with a set of molecular descriptors that can be easily acquired or calculated using atomic periodicity and other fundamental atomic parameters. Based on the extended set of twenty descriptors, a robust and validated nanoinformatics model has been proposed to predict the ENM ζ-potential. The five critical parameters selected as the most significant for the model development included the ENM size and coating as well as three molecular descriptors, metal ionic radius (rion), the sum of metal electronegativity divided by the number of oxygen atoms present in a particular metal oxide (Σχ/nO) and the absolute electronegativity (χabs), each of which is thoroughly discussed to interpret their influence on ζ-potential values. The model was developed using the Isalos Analytics Platform and is available to the community as a web service through the Horizon 2020 (H2020) NanoCommons Transnational Access services and the H2020 NanoSoveIT Integrated Approach to Testing and Assessment (IATA).
Collapse
Affiliation(s)
- Anastasios G Papadiamantis
- NovaMechanics Ltd, 1065 Nicosia, Cyprus; School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, United Kingdom
| | | | | | - Eugenia Valsami-Jones
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, United Kingdom
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, B15 2TT Birmingham, United Kingdom.
| | | |
Collapse
|
37
|
Saarimäki LA, Federico A, Lynch I, Papadiamantis AG, Tsoumanis A, Melagraki G, Afantitis A, Serra A, Greco D. Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials. Sci Data 2021; 8:49. [PMID: 33558569 PMCID: PMC7870661 DOI: 10.1038/s41597-021-00808-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 12/16/2020] [Indexed: 02/07/2023] Open
Abstract
Toxicogenomics (TGx) approaches are increasingly applied to gain insight into the possible toxicity mechanisms of engineered nanomaterials (ENMs). Omics data can be valuable to elucidate the mechanism of action of chemicals and to develop predictive models in toxicology. While vast amounts of transcriptomics data from ENM exposures have already been accumulated, a unified, easily accessible and reusable collection of transcriptomics data for ENMs is currently lacking. In an attempt to improve the FAIRness of already existing transcriptomics data for ENMs, we curated a collection of homogenized transcriptomics data from human, mouse and rat ENM exposures in vitro and in vivo including the physicochemical characteristics of the ENMs used in each study.
Collapse
Affiliation(s)
- Laura Aliisa Saarimäki
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
| | - Antonio Federico
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, Birmingham, United Kingdom
| | - Anastasios G Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, Birmingham, United Kingdom
- NovaMechanics Ltd, P.O Box 26014 1666, Nicosia, Cyprus
| | | | | | | | - Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- BioMediTech Institute, Tampere University, Tampere, Finland
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
- BioMediTech Institute, Tampere University, Tampere, Finland.
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland.
- Finnish Centre for Alternative Methods (FICAM), Faculty of Medicine and Heath Technology, Tampere University, Tampere, Finland.
| |
Collapse
|
38
|
Halappanavar S, Ede JD, Mahapatra I, Krug HF, Kuempel ED, Lynch I, Vandebriel RJ, Shatkin JA. A methodology for developing key events to advance nanomaterial-relevant adverse outcome pathways to inform risk assessment. Nanotoxicology 2020; 15:289-310. [PMID: 33317378 DOI: 10.1080/17435390.2020.1851419] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Significant advances have been made in the development of Adverse Outcome Pathways (AOPs) over the last decade, mainly focused on the toxicity mechanisms of chemicals. These AOPs, although relevant to manufactured nanomaterials (MNs), do not currently capture the reported roles of size-associated properties of MNs on toxicity. Moreover, some AOs of relevance to airborne exposures to MNs such as lung inflammation and fibrosis shown in animal studies may not be targeted in routine regulatory decision making. The primary objective of the present study was to establish an approach to advance the development of AOPs of relevance to MNs using existing, publicly available, nanotoxicology literature. A systematic methodology was created for curating, organizing and applying the available literature for identifying key events (KEs). Using a case study approach, the study applied the available literature to build the biological plausibility for 'tissue injury', a KE of regulatory relevance to MNs. The results of the analysis reveal the various endpoints, assays and specific biological markers used for assessing and reporting tissue injury. The study elaborates on the limitations and opportunities of the current nanotoxicology literature and provides recommendations for the future reporting of nanotoxicology results that will expedite not only the development of AOPs for MNs but also aid in application of existing data for decision making.
Collapse
Affiliation(s)
- Sabina Halappanavar
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Canada
| | | | - Indrani Mahapatra
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
| | - Harald F Krug
- Retired International Research Cooperation Manager, Empa - Swiss Federal Laboratories for Science and Materials Technology, St. Gallen, Switzerland.,NanoCASE GmbH, Engelburg, Switzerland
| | - Eileen D Kuempel
- National Institute for Occupational Safety and Health, Nanotechnology Research Center, Cincinnati, OH, USA
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK
| | - Rob J Vandebriel
- National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands
| | | |
Collapse
|
39
|
Lynch I, Afantitis A, Exner T, Himly M, Lobaskin V, Doganis P, Maier D, Sanabria N, Papadiamantis AG, Rybinska-Fryca A, Gromelski M, Puzyn T, Willighagen E, Johnston BD, Gulumian M, Matzke M, Green Etxabe A, Bossa N, Serra A, Liampa I, Harper S, Tämm K, Jensen ACØ, Kohonen P, Slater L, Tsoumanis A, Greco D, Winkler DA, Sarimveis H, Melagraki G. Can an InChI for Nano Address the Need for a Simplified Representation of Complex Nanomaterials across Experimental and Nanoinformatics Studies? NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E2493. [PMID: 33322568 PMCID: PMC7764592 DOI: 10.3390/nano10122493] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 12/05/2020] [Accepted: 12/08/2020] [Indexed: 12/16/2022]
Abstract
Chemoinformatics has developed efficient ways of representing chemical structures for small molecules as simple text strings, simplified molecular-input line-entry system (SMILES) and the IUPAC International Chemical Identifier (InChI), which are machine-readable. In particular, InChIs have been extended to encode formalized representations of mixtures and reactions, and work is ongoing to represent polymers and other macromolecules in this way. The next frontier is encoding the multi-component structures of nanomaterials (NMs) in a machine-readable format to enable linking of datasets for nanoinformatics and regulatory applications. A workshop organized by the H2020 research infrastructure NanoCommons and the nanoinformatics project NanoSolveIT analyzed issues involved in developing an InChI for NMs (NInChI). The layers needed to capture NM structures include but are not limited to: core composition (possibly multi-layered); surface topography; surface coatings or functionalization; doping with other chemicals; and representation of impurities. NM distributions (size, shape, composition, surface properties, etc.), types of chemical linkages connecting surface functionalization and coating molecules to the core, and various crystallographic forms exhibited by NMs also need to be considered. Six case studies were conducted to elucidate requirements for unambiguous description of NMs. The suggested NInChI layers are intended to stimulate further analysis that will lead to the first version of a "nano" extension to the InChI standard.
Collapse
Affiliation(s)
- Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
| | - Antreas Afantitis
- Nanoinformatics Department, NovaMechanics Ltd., 1666 Nicosia, Cyprus; (A.A.); (A.T.)
| | - Thomas Exner
- Edelweiss Connect GmbH, Hochbergerstrasse 60C, 4057 Basel, Switzerland;
| | - Martin Himly
- Department Biosciences, Paris Lodron University of Salzburg, Hellbrunnerstrasse 34, 5020 Salzburg, Austria;
| | - Vladimir Lobaskin
- School of Physics, University College Dublin, Belfield, Dublin 4, Ireland;
| | - Philip Doganis
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (P.D.); (I.L.); (H.S.)
| | - Dieter Maier
- Biomax Informatics AG, Robert-Koch-Str. 2, 82152 Planegg, Germany;
| | - Natasha Sanabria
- National Health Laboratory Services, 1 Modderfontein Rd, Sandringham, Johannesburg 2192, South Africa; (N.S.); (M.G.)
| | - Anastasios G. Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
- Nanoinformatics Department, NovaMechanics Ltd., 1666 Nicosia, Cyprus; (A.A.); (A.T.)
| | - Anna Rybinska-Fryca
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (A.R.-F.); (M.G.); (T.P.)
| | - Maciej Gromelski
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (A.R.-F.); (M.G.); (T.P.)
| | - Tomasz Puzyn
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland; (A.R.-F.); (M.G.); (T.P.)
| | - Egon Willighagen
- Department of Bioinformatics—BiGCaT, School of Nutrition and Translational Research in Metabolism, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands;
| | - Blair D. Johnston
- Department Chemicals and Product Safety, Federal Institute for Risk Assessment, Max-Dohrn-Str. 8-10, 10589 Berlin, Germany;
| | - Mary Gulumian
- National Health Laboratory Services, 1 Modderfontein Rd, Sandringham, Johannesburg 2192, South Africa; (N.S.); (M.G.)
- Haematology and Molecular Medicine, University of the Witwatersrand, 1 Jan Smuts Ave, Johannesburg 2000, South Africa
| | - Marianne Matzke
- UK Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford OX10 8BB, UK; (M.M.); (A.G.E.)
| | - Amaia Green Etxabe
- UK Centre for Ecology and Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford OX10 8BB, UK; (M.M.); (A.G.E.)
| | - Nathan Bossa
- LEITAT Technological Center, Circular Economy Business Unit, C/de La Innovació 2, 08225 Terrassa, Barcelona, Spain;
| | - Angela Serra
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (D.G.)
| | - Irene Liampa
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (P.D.); (I.L.); (H.S.)
| | - Stacey Harper
- School of Chemical, Biological, and Environmental Engineering, Oregon State University, 116 Johnson Hall 105 SW 26th St., Corvallis, OR 97331, USA;
| | - Kaido Tämm
- Institute of Chemistry, University of Tartu, Ülikooli 18, 50090 Tartu, Estonia;
| | - Alexander CØ Jensen
- The National Research Center for the Work Environment, Lersø Parkallé 105, 2100 Copenhagen, Denmark;
| | - Pekka Kohonen
- Misvik Biology OY, Karjakatu 35 B, 20520 Turku, Finland;
| | - Luke Slater
- Institute of Cancer and Genomics, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
| | - Andreas Tsoumanis
- Nanoinformatics Department, NovaMechanics Ltd., 1666 Nicosia, Cyprus; (A.A.); (A.T.)
| | - Dario Greco
- Faculty of Medicine and Health Technology, Tampere University, FI-33014 Tampere, Finland; (A.S.); (D.G.)
| | - David A. Winkler
- Institute of Molecular Sciences, La Trobe University, Kingsbury Drive, Bundoora 3086, Australia;
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville 3052, Australia
- School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK
- CSIRO Data61, Pullenvale 4069, Australia
| | - Haralambos Sarimveis
- School of Chemical Engineering, National Technical University of Athens, 157 80 Athens, Greece; (P.D.); (I.L.); (H.S.)
| | - Georgia Melagraki
- Nanoinformatics Department, NovaMechanics Ltd., 1666 Nicosia, Cyprus; (A.A.); (A.T.)
| |
Collapse
|
40
|
Buocikova V, Rios-Mondragon I, Pilalis E, Chatziioannou A, Miklikova S, Mego M, Pajuste K, Rucins M, Yamani NE, Longhin EM, Sobolev A, Freixanet M, Puntes V, Plotniece A, Dusinska M, Cimpan MR, Gabelova A, Smolkova B. Epigenetics in Breast Cancer Therapy-New Strategies and Future Nanomedicine Perspectives. Cancers (Basel) 2020; 12:E3622. [PMID: 33287297 PMCID: PMC7761669 DOI: 10.3390/cancers12123622] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 11/30/2020] [Accepted: 11/30/2020] [Indexed: 12/12/2022] Open
Abstract
Epigenetic dysregulation has been recognized as a critical factor contributing to the development of resistance against standard chemotherapy and to breast cancer progression via epithelial-to-mesenchymal transition. Although the efficacy of the first-generation epigenetic drugs (epi-drugs) in solid tumor management has been disappointing, there is an increasing body of evidence showing that epigenome modulation, in synergy with other therapeutic approaches, could play an important role in cancer treatment, reversing acquired therapy resistance. However, the epigenetic therapy of solid malignancies is not straightforward. The emergence of nanotechnologies applied to medicine has brought new opportunities to advance the targeted delivery of epi-drugs while improving their stability and solubility, and minimizing off-target effects. Furthermore, the omics technologies, as powerful molecular epidemiology screening tools, enable new diagnostic and prognostic epigenetic biomarker identification, allowing for patient stratification and tailored management. In combination with new-generation epi-drugs, nanomedicine can help to overcome low therapeutic efficacy in treatment-resistant tumors. This review provides an overview of ongoing clinical trials focusing on combination therapies employing epi-drugs for breast cancer treatment and summarizes the latest nano-based targeted delivery approaches for epi-drugs. Moreover, it highlights the current limitations and obstacles associated with applying these experimental strategies in the clinics.
Collapse
Affiliation(s)
- Verona Buocikova
- Cancer Research Institute, Biomedical Research Center of the Slovak Academy of Sciences, Dubravska Cesta 9, 845 05 Bratislava, Slovakia; (V.B.); (S.M.); (A.G.)
| | - Ivan Rios-Mondragon
- Department of Clinical Dentistry, University of Bergen, Aarstadveien 19, 5009 Bergen, Norway; (I.R.-M.); (M.R.C.)
| | - Eleftherios Pilalis
- e-NIOS Applications Private Company, Alexandrou Pantou 25, 17671 Kallithea, Greece; (E.P.); (A.C.)
- Center of Systems Biology, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece
| | - Aristotelis Chatziioannou
- e-NIOS Applications Private Company, Alexandrou Pantou 25, 17671 Kallithea, Greece; (E.P.); (A.C.)
- Center of Systems Biology, Biomedical Research Foundation of the Academy of Athens, 11527 Athens, Greece
| | - Svetlana Miklikova
- Cancer Research Institute, Biomedical Research Center of the Slovak Academy of Sciences, Dubravska Cesta 9, 845 05 Bratislava, Slovakia; (V.B.); (S.M.); (A.G.)
| | - Michal Mego
- 2nd Department of Oncology, Faculty of Medicine, Comenius University and National Cancer Institute, Klenova 1, 833 10 Bratislava, Slovakia;
| | - Karlis Pajuste
- Latvian Institute of Organic Synthesis, Aizkraukles str. 21, LV-1006 Riga, Latvia; (K.P.); (M.R.); (A.S.); (A.P.)
| | - Martins Rucins
- Latvian Institute of Organic Synthesis, Aizkraukles str. 21, LV-1006 Riga, Latvia; (K.P.); (M.R.); (A.S.); (A.P.)
| | - Naouale El Yamani
- Health Effects Laboratory, NILU-Norwegian Institute for Air Research, 2007 Kjeller, Norway; (N.E.Y.); (E.M.L.); (M.D.)
| | - Eleonora Marta Longhin
- Health Effects Laboratory, NILU-Norwegian Institute for Air Research, 2007 Kjeller, Norway; (N.E.Y.); (E.M.L.); (M.D.)
| | - Arkadij Sobolev
- Latvian Institute of Organic Synthesis, Aizkraukles str. 21, LV-1006 Riga, Latvia; (K.P.); (M.R.); (A.S.); (A.P.)
| | - Muriel Freixanet
- Vall d Hebron, Institut de Recerca (VHIR), 08035 Barcelona, Spain; (M.F.); (V.P.)
| | - Victor Puntes
- Vall d Hebron, Institut de Recerca (VHIR), 08035 Barcelona, Spain; (M.F.); (V.P.)
- Institut Català de Nanosciència i Nanotecnologia (ICN2), Bellaterra, 08193 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
| | - Aiva Plotniece
- Latvian Institute of Organic Synthesis, Aizkraukles str. 21, LV-1006 Riga, Latvia; (K.P.); (M.R.); (A.S.); (A.P.)
| | - Maria Dusinska
- Health Effects Laboratory, NILU-Norwegian Institute for Air Research, 2007 Kjeller, Norway; (N.E.Y.); (E.M.L.); (M.D.)
| | - Mihaela Roxana Cimpan
- Department of Clinical Dentistry, University of Bergen, Aarstadveien 19, 5009 Bergen, Norway; (I.R.-M.); (M.R.C.)
| | - Alena Gabelova
- Cancer Research Institute, Biomedical Research Center of the Slovak Academy of Sciences, Dubravska Cesta 9, 845 05 Bratislava, Slovakia; (V.B.); (S.M.); (A.G.)
| | - Bozena Smolkova
- Cancer Research Institute, Biomedical Research Center of the Slovak Academy of Sciences, Dubravska Cesta 9, 845 05 Bratislava, Slovakia; (V.B.); (S.M.); (A.G.)
| |
Collapse
|
41
|
Surmounting the endothelial barrier for delivery of drugs and imaging tracers. Atherosclerosis 2020; 315:93-101. [DOI: 10.1016/j.atherosclerosis.2020.04.025] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 04/14/2020] [Accepted: 04/29/2020] [Indexed: 12/18/2022]
|
42
|
Peng T, Wei C, Yu F, Xu J, Zhou Q, Shi T, Hu X. Predicting nanotoxicity by an integrated machine learning and metabolomics approach. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 267:115434. [PMID: 32841907 DOI: 10.1016/j.envpol.2020.115434] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Revised: 08/11/2020] [Accepted: 08/12/2020] [Indexed: 06/11/2023]
Abstract
Predicting the biological responses to engineered nanoparticles (ENPs) is critical to their environmental health assessment. The disturbances of metabolic pathways reflect the global profile of biological responses to ENPs but are difficult to predict due to the highly heterogeneous data from complicated biological systems and various ENP properties. Herein, integrating multiple machine learning models and metabolomics enabled accurate prediction of the disturbance of metabolic pathways induced by 33 ENPs. Screening nine typical properties of ENPs identified type and size as the top features determining the effects on metabolic pathways. Similarity network analysis and decision tree models overcame the highly heterogeneous data sources to visualize and judge the occurrence of metabolic pathways depending on the sorting priority features. The model accuracy was verified by animal experiments and reached 75%-100%, even for the prediction of ENPs outside of databases. The models also predicted metabolic pathway-related histopathology. This work provides an approach for the quick assessment of environmental health risks induced by known and unknown ENPs.
Collapse
Affiliation(s)
- Ting Peng
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Changhong Wei
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Fubo Yu
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Jing Xu
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Qixing Zhou
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Tonglei Shi
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Xiangang Hu
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| |
Collapse
|
43
|
Rybińska-Fryca A, Mikolajczyk A, Puzyn T. Structure-activity prediction networks (SAPNets): a step beyond Nano-QSAR for effective implementation of the safe-by-design concept. NANOSCALE 2020; 12:20669-20676. [PMID: 33048104 DOI: 10.1039/d0nr05220e] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
A significant number of experimental studies are supported by computational methods such as quantitative structure-activity relationship modeling of nanoparticles (Nano-QSAR). This is especially so in research focused on design and synthesis of new, safer nanomaterials using safe-by-design concepts. However, Nano-QSAR has a number of important limitations. For example, it is not clear which descriptors that describe the nanoparticle physicochemical and structural properties are essential and can be adjusted to alter the target properties. This limitation can be overcome with the use of the Structure-Activity Prediction Network (SAPNet) presented in this paper. There are three main phases of building the SAPNet. First, information about the structural characterization of a nanomaterial, its physical and chemical properties and toxicity is compiled. Then, the most relevant properties (intrinsic/extrinsic) likely to influence the ENM toxicity are identified by developing "meta-models". Finally, these "meta-models" describing the dependencies between the most relevant properties of the ENMs and their adverse biological properties are developed. In this way, the network is built layer by layer from the endpoint (e.g. toxicity or other properties of interest) to descriptors that describe the particle structure. Therefore, SAPNets go beyond the current standards and provide sufficient information on what structural features should be altered to obtain a material with desired properties.
Collapse
Affiliation(s)
| | - Alicja Mikolajczyk
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland. and University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Tomasz Puzyn
- QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland. and University of Gdansk, Faculty of Chemistry, Wita Stwosza 63, 80-308 Gdansk, Poland
| |
Collapse
|
44
|
Papadiamantis AG, Jänes J, Voyiatzis E, Sikk L, Burk J, Burk P, Tsoumanis A, Ha MK, Yoon TH, Valsami-Jones E, Lynch I, Melagraki G, Tämm K, Afantitis A. Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E2017. [PMID: 33066094 PMCID: PMC7601995 DOI: 10.3390/nano10102017] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 10/03/2020] [Accepted: 10/07/2020] [Indexed: 02/07/2023]
Abstract
A literature curated dataset containing 24 distinct metal oxide (MexOy) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MexOy NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MexOy NPs. These were NP core size, hydrodynamic size, assay type, exposure dose, the energy of the MexOy conduction band (EC), the coordination number of the metal atoms on the NP surface (Avg. C.N. Me atoms surface) and the average force vector surface normal component of all metal atoms (v⟂ Me atoms surface). The significance and effect of these descriptors is discussed to demonstrate their direct correlation with cytotoxicity. The produced model has been made publicly available by the Horizon 2020 (H2020) NanoSolveIT project and will be added to the project's Integrated Approach to Testing and Assessment (IATA).
Collapse
Affiliation(s)
- Anastasios G. Papadiamantis
- NovaMechanics Ltd., Nicosia 1065, Cyprus; (A.G.P.); (E.V.); (A.T.)
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK; (E.V.-J.); (I.L.)
| | - Jaak Jänes
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | | | - Lauri Sikk
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | - Jaanus Burk
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | - Peeter Burk
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | | | - My Kieu Ha
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea; (M.K.H.); (T.H.Y.)
| | - Tae Hyun Yoon
- Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea; (M.K.H.); (T.H.Y.)
- Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
| | - Eugenia Valsami-Jones
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK; (E.V.-J.); (I.L.)
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK; (E.V.-J.); (I.L.)
| | - Georgia Melagraki
- Division of Physical Sciences and Applications, Hellenic Military Academy, 16672 Vari, Greece;
| | - Kaido Tämm
- Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia; (J.J.); (L.S.); (J.B.); (P.B.)
| | | |
Collapse
|
45
|
Martinez DST, Da Silva GH, de Medeiros AMZ, Khan LU, Papadiamantis AG, Lynch I. Effect of the Albumin Corona on the Toxicity of Combined Graphene Oxide and Cadmium to Daphnia magna and Integration of the Datasets into the NanoCommons Knowledge Base. NANOMATERIALS (BASEL, SWITZERLAND) 2020; 10:E1936. [PMID: 33003330 PMCID: PMC7599915 DOI: 10.3390/nano10101936] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 12/12/2022]
Abstract
In this work, we evaluated the effect of protein corona formation on graphene oxide (GO) mixture toxicity testing (i.e., co-exposure) using the Daphnia magna model and assessing acute toxicity determined as immobilisation. Cadmium (Cd2+) and bovine serum albumin (BSA) were selected as co-pollutant and protein model system, respectively. Albumin corona formation on GO dramatically increased its colloidal stability (ca. 60%) and Cd2+ adsorption capacity (ca. 4.5 times) in reconstituted water (Daphnia medium). The acute toxicity values (48 h-EC50) observed were 0.18 mg L-1 for Cd2+-only and 0.29 and 0.61 mg L-1 following co-exposure of Cd2+ with GO and BSA@GO materials, respectively, at a fixed non-toxic concentration of 1.0 mg L-1. After coronation of GO with BSA, a reduction in cadmium toxicity of 110 % and 238% was achieved when compared to bare GO and Cd2+-only, respectively. Integration of datasets associated with graphene-based materials, heavy metals and mixture toxicity is essential to enable re-use of the data and facilitate nanoinformatics approaches for design of safer nanomaterials for water quality monitoring and remediation technologies. Hence, all data from this work were annotated and integrated into the NanoCommons Knowledge Base, connecting the experimental data to nanoinformatics platforms under the FAIR data principles and making them interoperable with similar datasets.
Collapse
Affiliation(s)
- Diego Stéfani T. Martinez
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, Sao Paulo, Brazil; (G.H.D.S.); (A.M.Z.d.M.); (L.U.K.)
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
- Center of Nuclear Energy in Agriculture (CENA), University of Sao Paulo (USP), Piracicaba 13416-000, Sao Paulo, Brazil
| | - Gabriela H. Da Silva
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, Sao Paulo, Brazil; (G.H.D.S.); (A.M.Z.d.M.); (L.U.K.)
| | - Aline Maria Z. de Medeiros
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, Sao Paulo, Brazil; (G.H.D.S.); (A.M.Z.d.M.); (L.U.K.)
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
- Center of Nuclear Energy in Agriculture (CENA), University of Sao Paulo (USP), Piracicaba 13416-000, Sao Paulo, Brazil
| | - Latif U. Khan
- Brazilian Nanotechnology National Laboratory (LNNano), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, Sao Paulo, Brazil; (G.H.D.S.); (A.M.Z.d.M.); (L.U.K.)
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
- Synchrotron-Light for Experimental Science and Applications in the Middle East (SESAME), Allan 19252, Jordan
| | - Anastasios G. Papadiamantis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
- NovaMechanics Ltd., Nicosia 1065, Cyprus
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK;
| |
Collapse
|
46
|
Isigonis P, Afantitis A, Antunes D, Bartonova A, Beitollahi A, Bohmer N, Bouman E, Chaudhry Q, Cimpan MR, Cimpan E, Doak S, Dupin D, Fedrigo D, Fessard V, Gromelski M, Gutleb AC, Halappanavar S, Hoet P, Jeliazkova N, Jomini S, Lindner S, Linkov I, Longhin EM, Lynch I, Malsch I, Marcomini A, Mariussen E, de la Fuente JM, Melagraki G, Murphy F, Neaves M, Packroff R, Pfuhler S, Puzyn T, Rahman Q, Pran ER, Semenzin E, Serchi T, Steinbach C, Trump B, Vrček IV, Warheit D, Wiesner MR, Willighagen E, Dusinska M. Risk Governance of Emerging Technologies Demonstrated in Terms of its Applicability to Nanomaterials. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2003303. [PMID: 32700469 DOI: 10.1002/smll.202003303] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Indexed: 06/11/2023]
Abstract
Nanotechnologies have reached maturity and market penetration that require nano-specific changes in legislation and harmonization among legislation domains, such as the amendments to REACH for nanomaterials (NMs) which came into force in 2020. Thus, an assessment of the components and regulatory boundaries of NMs risk governance is timely, alongside related methods and tools, as part of the global efforts to optimise nanosafety and integrate it into product design processes, via Safe(r)-by-Design (SbD) concepts. This paper provides an overview of the state-of-the-art regarding risk governance of NMs and lays out the theoretical basis for the development and implementation of an effective, trustworthy and transparent risk governance framework for NMs. The proposed framework enables continuous integration of the evolving state of the science, leverages best practice from contiguous disciplines and facilitates responsive re-thinking of nanosafety governance to meet future needs. To achieve and operationalise such framework, a science-based Risk Governance Council (RGC) for NMs is being developed. The framework will provide a toolkit for independent NMs' risk governance and integrates needs and views of stakeholders. An extension of this framework to relevant advanced materials and emerging technologies is also envisaged, in view of future foundations of risk research in Europe and globally.
Collapse
Affiliation(s)
- Panagiotis Isigonis
- Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari of Venice, Via Torino 155, Mestre, Venice, 30172, Italy
| | | | | | - Alena Bartonova
- NILU, Norwegian Institute for Air Research, Kjeller, 2007, Norway
| | - Ali Beitollahi
- INIC, Iran Nanotechnology Initiate Council, Tehran, Iran
| | - Nils Bohmer
- Society for Chemical Engineering and Biotechnology (DECHEMA), Theodor-Heuss-Allee 25, Frankfurt am Main, 60486, Germany
| | - Evert Bouman
- NILU, Norwegian Institute for Air Research, Kjeller, 2007, Norway
| | - Qasim Chaudhry
- University of Chester, Parkgate Road, Chester, CH1 4BJ, UK
| | - Mihaela Roxana Cimpan
- Department of Clinical Dentistry, Biomaterials, Faculty of Medicine, University of Bergen, Aarstadveien 19, Bergen, 5009, Norway
| | - Emil Cimpan
- Western Norway University of Applied Sciences, Inndalsveien 28, Bergen, 5063, Norway
| | - Shareen Doak
- Swansea University Medical School, Singleton Park, Swansea, Wales, SA2 8PP, UK
| | - Damien Dupin
- CIDETEC, Paseo Miramón 196, Donostia-San Sebastián, 20014, Spain
| | - Doreen Fedrigo
- ECOS - European Environmental Citizens Organization for Standardization, Rue d'Edimbourg, 26, Brussels, 1050, Belgium
| | - Valérie Fessard
- ANSES Fougères Laboratory, Contaminant Toxicology Unit and Risk Management Support, Unit of Chemicals Assessment, Risk Assessment Department, 14 rue Pierre et Marie Curie, Maisons-Alfort, Cedex 94701, France
| | - Maciej Gromelski
- QSAR Lab Sp. z o.o., al. Grunwaldzka 190/102, Gdańsk, 80-266, Poland
| | - Arno C Gutleb
- LIST, Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
| | - Sabina Halappanavar
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Peter Hoet
- KU Leuven, Department of Public Health and Primary Care, Unit of Environment and Health, Leuven, 3000, Belgium
| | - Nina Jeliazkova
- IDEA Ideaconsult Limited Liability Company, Angel Kanchev 4, Sofia, 1000, Bulgaria
| | - Stéphane Jomini
- ANSES Fougères Laboratory, Contaminant Toxicology Unit and Risk Management Support, Unit of Chemicals Assessment, Risk Assessment Department, 14 rue Pierre et Marie Curie, Maisons-Alfort, Cedex 94701, France
| | - Sabine Lindner
- Plastics Europe Deutschland e. V., Mainzer Landstrasse 55, Frankfurt am Main, 60329, Germany
| | - Igor Linkov
- Factor Social Lda., Lisbon, Portugal
- US Army Engineer Research and Development Center and Carnegie Mellon University, Lisbon, Portugal
| | | | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ineke Malsch
- Malsch TechnoValuation, PO Box 455, Utrecht, AL, 3500, The Netherlands
| | - Antonio Marcomini
- Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari of Venice, Via Torino 155, Mestre, Venice, 30172, Italy
| | - Espen Mariussen
- NILU, Norwegian Institute for Air Research, Kjeller, 2007, Norway
| | - Jesus M de la Fuente
- Instituto de Ciencia de Materiales de Aragón (ICMA), Consejo Superior de Investigaciones Científicas (CSIC)-Universidad de Zaragoza, C/Pedro Cerbuna 12, Zaragoza, 50009, Spain
| | | | | | - Michael Neaves
- ECOS - European Environmental Citizens Organization for Standardization, Rue d'Edimbourg, 26, Brussels, 1050, Belgium
| | - Rolf Packroff
- Division of 'Hazardous chemicals and biological agents', BAuA - Federal Institute for Occupational Safety and Health, Dortmund, Germany
| | - Stefan Pfuhler
- Procter & Gamble Co., Miami Valley Innovation Center, 11810 East Miami River Road, Cincinnati, OH, 45239 8707, USA
| | - Tomasz Puzyn
- QSAR Lab Sp. z o.o., al. Grunwaldzka 190/102, Gdańsk, 80-266, Poland
- University of Gdansk, Faculty of Chemistry, Group of Environmental Chemometrics, Wita Stwosza 63, Gdańsk, 80-308, Poland
| | | | | | - Elena Semenzin
- Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari of Venice, Via Torino 155, Mestre, Venice, 30172, Italy
| | - Tommaso Serchi
- LIST, Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
| | - Christoph Steinbach
- Society for Chemical Engineering and Biotechnology (DECHEMA), Theodor-Heuss-Allee 25, Frankfurt am Main, 60486, Germany
| | - Benjamin Trump
- Factor Social Lda., Lisbon, Portugal
- US Army Engineer Research and Development Center and University of Michigan, Lisbon, Portugal
| | - Ivana Vinković Vrček
- Institute for Medical Research and Occupational Health, Analytical Toxicology and Mineral Metabolism Unit, Ksaverska cesta 2, Zagreb, 10 000, Croatia
| | | | - Mark R Wiesner
- Department of Civil and Environmental Engineering, Center for the Environmental Implications of NanoTechnology (CEINT) Duke University, 121 Hudson Hall, Durham, NC, 27708-0287, USA
| | - Egon Willighagen
- Department of Bioinformatics, BiGCaT, NUTRIM, Maastricht University, Maastricht, ER 6229, The Netherlands
| | - Maria Dusinska
- NILU, Norwegian Institute for Air Research, Kjeller, 2007, Norway
| |
Collapse
|
47
|
Setyawati MI, Zhao Z, Ng KW. Transformation of Nanomaterials and Its Implications in Gut Nanotoxicology. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2001246. [PMID: 32495486 DOI: 10.1002/smll.202001246] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 04/24/2020] [Indexed: 06/11/2023]
Abstract
Ingestion of engineered nanomaterials (ENMs) is inevitable due to their widespread utilization in the agrifood industry. Safety evaluation has become pivotal to identify the consequences on human health of exposure to these ingested ENMs. Much of the current understanding of nanotoxicology in the gastrointestinal tract (GIT) is derived from studies utilizing pristine ENMs. In reality, agrifood ENMs interact with their microenvironment, and undergo multiple physicochemical transformations, such as aggregation/agglomeration, dissolution, speciation change, and surface characteristics alteration, across their life cycle from synthesis to consumption. This work sieves out the implications of ENM transformations on their behavior, stability, and reactivity in food and product matrices and through the GIT, in relation to measured toxicological profiles. In particular, a strong emphasis is given to understand the mechanisms through which these transformations can affect ENM induced gut nanotoxicity.
Collapse
Affiliation(s)
- Magdiel Inggrid Setyawati
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Zhitong Zhao
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Kee Woei Ng
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA, 02115, USA
- Environmental Chemistry and Materials Centre, Nanyang Environment and Water Research Institute (NEWRI), Nanyang Technological University, 1 Cleantech Loop, CleanTech One, Singapore, 637141, Singapore
- Skin Research Institute of Singapore, Biomedical Science Institutes, Immunos, 8A Biomedical Grove, Singapore, 138648, Singapore
| |
Collapse
|
48
|
Winkler DA. Role of Artificial Intelligence and Machine Learning in Nanosafety. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2001883. [PMID: 32537842 DOI: 10.1002/smll.202001883] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Revised: 05/07/2020] [Indexed: 06/11/2023]
Abstract
Robotics and automation provide potentially paradigm shifting improvements in the way materials are synthesized and characterized, generating large, complex data sets that are ideal for modeling and analysis by modern machine learning (ML) methods. Nanomaterials have not yet fully captured the benefits of automation, so lag behind in the application of ML methods of data analysis. Here, some key developments in, and roadblocks to the application of ML methods are reviewed to model and predict potentially adverse biological and environmental effects of nanomaterials. This work focuses on the diverse ways a range of ML algorithms are applied to understand and predict nanomaterials properties, provides examples of the application of traditional ML and deep learning methods to nanosafety, and provides context and future perspectives on developments that are likely to occur, or need to occur in the near future that allow artificial intelligence to make a deeper contribution to nanosafety.
Collapse
Affiliation(s)
- David A Winkler
- La Trobe Institute for Molecular Science, La Trobe University, Kingsbury Drive, Bundoora, 3042, Australia
- CSIRO Data61, 1 Technology Court, Pullenvale, 4069, Australia
- School of Pharmacy, University of Nottingham, Nottingham, NG7 2QL, UK
- Monash Institute of Pharmaceutical Sciences, Monash University, 392 Royal Parade, Parkville, 3052, Australia
| |
Collapse
|
49
|
Karatzas P, Melagraki G, Ellis LJA, Lynch I, Varsou DD, Afantitis A, Tsoumanis A, Doganis P, Sarimveis H. Development of Deep Learning Models for Predicting the Effects of Exposure to Engineered Nanomaterials on Daphnia magna. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2020; 16:e2001080. [PMID: 32548897 DOI: 10.1002/smll.202001080] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 04/27/2020] [Accepted: 04/28/2020] [Indexed: 06/11/2023]
Abstract
This study presents the results of applying deep learning methodologies within the ecotoxicology field, with the objective of training predictive models that can support hazard assessment and eventually the design of safer engineered nanomaterials (ENMs). A workflow applying two different deep learning architectures on microscopic images of Daphnia magna is proposed that can automatically detect possible malformations, such as effects on the length of the tail, and the overall size, and uncommon lipid concentrations and lipid deposit shapes, which are due to direct or parental exposure to ENMs. Next, classification models assign specific objects (heart, abdomen/claw) to classes that depend on lipid densities and compare the results with controls. The models are statistically validated in terms of their prediction accuracy on external D. magna images and illustrate that deep learning technologies can be useful in the nanoinformatics field, because they can automate time-consuming manual procedures, accelerate the investigation of adverse effects of ENMs, and facilitate the process of designing safer nanostructures. It may even be possible in the future to predict impacts on subsequent generations from images of parental exposure, reducing the time and cost involved in long-term reproductive toxicity assays over multiple generations.
Collapse
Affiliation(s)
- Pantelis Karatzas
- School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece
| | - Georgia Melagraki
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
| | - Laura-Jayne A Ellis
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Iseult Lynch
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Dimitra-Danai Varsou
- School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
| | - Antreas Afantitis
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
| | - Andreas Tsoumanis
- Nanoinformatics Department, NovaMechanics Ltd., Nicosia, 1065, Cyprus
| | - Philip Doganis
- School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece
| | - Haralambos Sarimveis
- School of Chemical Engineering, National Technical University of Athens, Athens, 15780, Greece
| |
Collapse
|
50
|
Abstract
Nanoparticles from natural and anthropogenic sources are abundant in the environment, thus human exposure to nanoparticles is inevitable. Due to this constant exposure, it is critically important to understand the potential acute and chronic adverse effects that nanoparticles may cause to humans. In this review, we explore and highlight the current state of nanotoxicology research with a focus on mechanistic understanding of nanoparticle toxicity at organ, tissue, cell, and biomolecular levels. We discuss nanotoxicity mechanisms, including generation of reactive oxygen species, nanoparticle disintegration, modulation of cell signaling pathways, protein corona formation, and poly(ethylene glycol)-mediated immunogenicity. We conclude with a perspective on potential approaches to advance current understanding of nanoparticle toxicity. Such improved understanding may lead to mitigation strategies that could enable safe application of nanoparticles in humans. Advances in nanotoxicity research will ultimately inform efforts to establish standardized regulatory frameworks with the goal of fully exploiting the potential of nanotechnology while minimizing harm to humans.
Collapse
Affiliation(s)
- Wen Yang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma 73019, USA;
| | - Lin Wang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma 73019, USA;
| | - Evan M Mettenbrink
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma 73019, USA;
| | - Paul L DeAngelis
- Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma 73104, USA
| | - Stefan Wilhelm
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, Oklahoma 73019, USA; .,Institute for Biomedical Engineering, Science, and Technology (IBEST), Norman, Oklahoma 73019, USA.,Stephenson Cancer Center, Oklahoma City, Oklahoma 73104, USA
| |
Collapse
|