Evidence map›Paper›PMID 21323332›Full record

ArticleACS nano2011

Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials.

Saji George, Tian Xia, Robert Rallo, Yan Zhao, Zhaoxia Ji, Sijie Lin, Xiang Wang, Haiyuan Zhang, Bryan France, David Schoenfeld and 6 more

Abstract read
In one paragraph

Article in ACS nano, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed
18.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

81 citing papers in PubMed, 319 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Safety Considerations of Cancer Nanomedicine-A Key Step toward Translation.Small (Weinheim an der Bergstrasse, Germany) · 2020
    Review
  14. Review
  15. Review
  16. Review
  17. Article
  18. Article
  19. Teratological and Behavioral Screening of the National Toxicology Program 91-Compound Library in Zebrafish (Danio rerio).Toxicological sciences : an official journal of the Society of Toxicology · 2019
    Article
  20. Review

21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 2 countries.

Saji GeorgeDepartment of Medicine, Division of NanoMedicine, Center for Environmental Implications of Nanotechnology, California NanoSystems Institute, Los Angeles, CA 90095, USA.
Tian Xia
Robert Rallo
Yan Zhao
Zhaoxia Ji
Sijie Lin
Xiang Wang
Haiyuan Zhang
Bryan France
David Schoenfeld
Robert Damoiseaux
Rong Liu
Shuo Lin
Kenneth A Bradley
Yoram Cohen
André E Nel
California NanoSystems Institute · USScreen · US

Funding

Scientific Core: Acquisition, Synthesis, and Characterization of NanomaterialsU19ES019528 · NIEHS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NEL, ANDRE ELIAS · 2010 to 2014
$5.5M
Predictive Toxicological Paradigm for Chronic Nanoparticle Injury in the LungR01ES016746 · NIEHS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NEL, ANDRE ELIAS · 2008 to 2017
$3.4M
Predictive Toxicological Paradigms to Establish Inhalation Toxicology ModelsRC2ES018766 · NIEHS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI NEL, ANDRE ELIAS · 2009 to 2010
$1.1M
NIEHS NIH HHS R01 ES016746NIEHS NIH HHS RC2 ES018766NIEHS NIH HHS U19 ES019528
6 · The paper itself

Abstract

Because of concerns about the safety of a growing number of engineered nanomaterials (ENM), it is necessary to develop high-throughput screening and in silico data transformation tools that can speed up in vitro hazard ranking. Here, we report the use of a multiparametric, automated screening assay that incorporates sublethal and lethal cellular injury responses to perform high-throughput analysis of a batch of commercial metal/metal oxide nanoparticles (NP) with the inclusion of a quantum dot (QD1). The responses chosen for tracking cellular injury through automated epifluorescence microscopy included ROS production, intracellular calcium flux, mitochondrial depolarization, and plasma membrane permeability. The z-score transformed high volume data set was used to construct heat maps for in vitro hazard ranking as well as showing the similarity patterns of NPs and response parameters through the use of self-organizing maps (SOM). Among the materials analyzed, QD1 and nano-ZnO showed the most prominent lethality, while Pt, Ag, SiO2, Al2O3, and Au triggered sublethal effects but without cytotoxicity. In order to compare the in vitro with the in vivo response outcomes in zebrafish embryos, NPs were used to assess their impact on mortality rate, hatching rate, cardiac rate, and morphological defects. While QDs, ZnO, and Ag induced morphological abnormalities or interfered in embryo hatching, Pt and Ag exerted inhibitory effects on cardiac rate. Ag toxicity in zebrafish differed from the in vitro results, which is congruent with this material's designation as extremely dangerous in the environment. Interestingly, while toxicity in the initially selected QD formulation was due to a solvent (toluene), supplementary testing of additional QDs selections yielded in vitro hazard profiling that reflect the release of chalcogenides. In conclusion, the use of a high-throughput screening, in silico data handling and zebrafish testing may constitute a paradigm for rapid and integrated ENM toxicological screening.

Indexed as

Quantum DotsAnimalsBiological AssayDrug Evaluation, PreclinicalEmbryo, NonmammalianMicroscopy, FluorescenceNanostructuresToxicity TestsZebrafish

Identifiers

PMID21323332
PMCPMC3896549
OpenAlexW2036661308

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.