Evidence map›Paper›PMID 27143523›Full record

ArticleJournal of applied toxicology : JAT2017

Characterization of three human cell line models for high-throughput neuronal cytotoxicity screening.

Zhi-Bin Tong, Helena Hogberg, David Kuo, Srilatha Sakamuru, Menghang Xia, Lena Smirnova, Thomas Hartung, David Gerhold

Abstract read
In one paragraph

Article in Journal of applied toxicology : JAT, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
3.4field-weighted citation impact, top 8% 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

38 citing papers in PubMed, 73 citations in OpenAlex.

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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

8 authors at 4 institutions in 2 countries.

Zhi-Bin TongNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Rockville, MD, USA.
Helena HogbergCenters for Alternatives to Animal Testing (CAAT) at Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, USA.
David KuoNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Rockville, MD, USA.
Srilatha SakamuruNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Rockville, MD, USA.
Menghang XiaNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Rockville, MD, USA.
Lena SmirnovaCenters for Alternatives to Animal Testing (CAAT) at Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, USA.
Thomas HartungCenters for Alternatives to Animal Testing (CAAT) at Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD, USA.
David GerholdNational Center for Advancing Translational Sciences (NCATS), National Institutes of Health, Rockville, MD, USA.
National Institutes of Health · USJohns Hopkins University · USNational Center for Advancing Translational Sciences · USUniversity of Konstanz · DE

Funding

Toxicology in the 21st Century Program (Tox21) - Genomic ToxicologyZIATR000039 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI GERHOLD, DAVID · 2016 to 2025
$5.1M
Toxicology in the 21st Century Program (Tox21) Genomic ToxicologyZICTR000039 · NCATS · NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES · PI GERHOLD, DAVID · 2015 to 2015
$100k
Intramural NIH HHS Z99 TR999999Intramural NIH HHS ZIC TR000039
6 · The paper itself

Abstract

More than 75 000 man-made chemicals contaminate the environment; many of these have not been tested for toxicities. These chemicals demand quantitative high-throughput screening assays to assess them for causative roles in neurotoxicities, including Parkinson's disease and other neurodegenerative disorders. To facilitate high throughput screening for cytotoxicity to neurons, three human neuronal cellular models were compared: SH-SY5Y neuroblastoma cells, LUHMES conditionally-immortalized dopaminergic neurons, and Neural Stem Cells (NSC) derived from human fetal brain. These three cell lines were evaluated for rapidity and degree of differentiation, and sensitivity to 32 known or candidate neurotoxicants. First, expression of neural differentiation genes was assayed during a 7-day differentiation period. Of the three cell lines, LUHMES showed the highest gene expression of neuronal markers after differentiation. Both in the undifferentiated state and after 7 days of neuronal differentiation, LUHMES cells exhibited greater cytotoxic sensitivity to most of 32 suspected or known neurotoxicants than SH-SY5Y or NSCs. LUHMES cells were also unique in being more susceptible to several compounds in the differentiating state than in the undifferentiated state; including known neurotoxicants colchicine, methyl-mercury (II), and vincristine. Gene expression results suggest that differentiating LUHMES cells may be susceptible to apoptosis because they express low levels of anti-apoptotic genes BCL2 and BIRC5/survivin, whereas SH-SY5Y cells may be resistant to apoptosis because they express high levels of BCL2, BIRC5/survivin, and BIRC3 genes. Thus, LUHMES cells exhibited favorable characteristics for neuro-cytotoxicity screening: rapid differentiation into neurons that exhibit high level expression neuronal marker genes, and marked sensitivity of LUHMES cells to known neurotoxicants. Copyright © 2016 John Wiley & Sons, Ltd.

Indexed as

ApoptosisCell DifferentiationCell LineCell SurvivalDopaminergic NeuronsEnvironmental PollutantsGene ExpressionHigh-Throughput Screening AssaysHumansNeural Stem CellsEnvironmental PollutantsapoptosisdifferentiationLUHMESneural stem cellsneurotoxicantneurotoxicitySH-SY5Y

Identifiers

PMID27143523
PMCPMC5094908
OpenAlexW2346555472

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.