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

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 IC 50 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 IC 50 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. Toxicity Models www.advancedsciencenews.com

Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data

“…Several studies [ 116 , 124 , 125 , 126 , 127 , 128 , 129 , 130 ] have demonstrated the benefits of meta-analysis through data combination and reusability for assessing NM toxicity. A characteristic example is that of Labouta et al (2019), in which the meta-analysis of 93 peer-reviewed papers, corresponding to over 3000 data points on the cytotoxicity of organic and inorganic NMs, established decision trees combined with feature selection methods to reveal hidden relationships [ 130 ].…”

Predicting Cytotoxicity of Metal Oxide Nanoparticles Using Isalos Analytics Platform

“…The final dataset included a total of 77 descriptors (independent variables), which were studied in terms of their correlation to % cell viability (dependent variable) of BEAS-2B and RAW 264.7 cell lines exposed to the NPs for 24 h. One of the descriptors used during model development was the assay type (ATP or LDH) used to measure cell viability. The reason for including the assay type was its statistical significance on the produced results, as demonstrated in previous meta-analysis studies [ 60 , 63 , 64 , 65 ]. As a result, extra care needs to be taken when dataset combination takes place regarding their interoperability to flag sources of potential variability.…”

“…In the current study, we used a subset of the data for modelling from the aforementioned single-parameter ATP and LDH assays carried out in BEAS-2B and RAW 264.7 cell lines. The type of assay (ATP or LDH) was included as an extra parameter, since significant correlation was identified in various instances [ 60 , 63 , 64 , 65 ] between the type of assay and cytotoxicity results. In total, 15 descriptors (independent variables) originating from Zhang et al (2012) were included in the analysis: 6 physicochemical (chemical formula, core size, specific surface area, total surface area, hydrodynamic size and ζ-potential), 6 molecular ( E V , E C , E g , χ cation , χ oxide and E ΔH ) and 3 assay-related (assay type, cell species and NP exposure dose) descriptors.…”

Molecular Mechanisms, Characterization Methods, and Utilities of Nanoparticle Biotransformation in Nanosafety Assessments

“…To explore the key attributes relating to the cytotoxicity of Cd-containing quantum dots (QDs), Bilal et al developed Bayesian network (BN) model based on a dataset compiled from 517 publications comprising 3028 cell viability data and 837 IC50 values of QDs. [204] Both continuous and categorical attributes are involved in BN QD toxicity models. They successfully identified three physicochemical properties correlating IC50, including diameter, surface ligand, and surface charge.…”