Literature DB >> 31207082

Bayesian Network Resource for Meta-Analysis: Cellular Toxicity of Quantum Dots.

Muhammad Bilal1,2, Eunkeu Oh3,4, Rong Liu2, Joyce C Breger5, Igor L Medintz5, Yoram Cohen1,2,6.   

Abstract

A web-based resource for meta-analysis of nanomaterials toxicity is developed whereby the utility of Bayesian networks (BNs) is illustrated for exploring the cellular toxicity of Cd-containing quantum dots (QDs). BN models are developed based on a dataset compiled from 517 publications comprising 3028 cell viability data samples and 837 IC50 values. BN QD toxicity (BN-QDTox) models are developed using both continuous (i.e., numerical) and categorical attributes. Using these models, the most relevant attributes identified for correlating IC50 are: QD diameter, exposure time, surface ligand, shell, assay type, surface modification, and surface charge, with the addition of QD concentration for the cell viability analysis. Data exploration via BN models further enables identification of possible association rules for QDs cellular toxicity. The BN models as web-based applications can be used for rapid intelligent query of the available body of evidence for a given nanomaterial and can be readily updated as the body of knowledge expands.
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Bayesian networks; attribute significance; conditional dependence; quantum dots; sensitivity analysis

Year:  2019        PMID: 31207082     DOI: 10.1002/smll.201900510

Source DB:  PubMed          Journal:  Small        ISSN: 1613-6810            Impact factor:   13.281


  6 in total

1.  Shell-Free Copper Indium Sulfide Quantum Dots Induce Toxicity in Vitro and in Vivo.

Authors:  Joshua C Kays; Alexander M Saeboe; Reyhaneh Toufanian; Danielle E Kurant; Allison M Dennis
Journal:  Nano Lett       Date:  2020-02-05       Impact factor: 11.189

2.  Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning.

Authors:  Irini Furxhi; Finbarr Murphy
Journal:  Int J Mol Sci       Date:  2020-07-25       Impact factor: 5.923

Review 3.  Practices and Trends of Machine Learning Application in Nanotoxicology.

Authors:  Irini Furxhi; Finbarr Murphy; Martin Mullins; Athanasios Arvanitis; Craig A Poland
Journal:  Nanomaterials (Basel)       Date:  2020-01-08       Impact factor: 5.076

Review 4.  Bioluminescence-Based Energy Transfer Using Semiconductor Quantum Dots as Acceptors.

Authors:  Anirban Samanta; Igor L Medintz
Journal:  Sensors (Basel)       Date:  2020-05-21       Impact factor: 3.576

5.  NanoTox: Development of a Parsimonious In Silico Model for Toxicity Assessment of Metal-Oxide Nanoparticles Using Physicochemical Features.

Authors:  Nilesh Anantha Subramanian; Ashok Palaniappan
Journal:  ACS Omega       Date:  2021-04-23

Review 6.  Potential Development of N-Doped Carbon Dots and Metal-Oxide Carbon Dot Composites for Chemical and Biosensing.

Authors:  Yogita Sahu; Ayesha Hashmi; Rajmani Patel; Ajaya K Singh; Md Abu Bin Hasan Susan; Sónia A C Carabineiro
Journal:  Nanomaterials (Basel)       Date:  2022-09-30       Impact factor: 5.719

  6 in total

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