Evidence map›Paper›PMID 29761935›Full record

ArticleEnvironmental and molecular mutagenesis2018

The application of transcriptional benchmark dose modeling for deriving thresholds of effects associated with solar-simulated ultraviolet radiation exposure.

Sami S Qutob, Vinita Chauhan, Byron Kuo, Andrew Williams, Carole L Yauk, James P McNamee, B Gollapudi

Abstract read
In one paragraph

Article in Environmental and molecular mutagenesis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping.Toxicological sciences : an official journal of the Society of Toxicology · 2024
    Article
  2. Article
  3. From vision toward best practices: EvaluatingFrontiers in toxicology · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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

7 authors.

Sami S QutobConsumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Ontario, K1A 1C1, Canada.
Vinita ChauhanConsumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Ontario, K1A 1C1, Canada.
Byron KuoEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada.
Andrew WilliamsEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada.
Carole L YaukEnvironmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada.
James P McNameeConsumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Ontario, K1A 1C1, Canada.
B Gollapudi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Considerable data has been generated to elucidate the transcriptional response of cells to ultraviolet radiation (UVR) exposure providing a mechanistic understanding of UVR-induced cellular responses. However, using these data to support standards development has been challenging. In this study, we apply benchmark dose (BMD) modeling of transcriptional data to derive thresholds of gene responsiveness following exposure to solar-simulated UVR. Human epidermal keratinocytes were exposed to three doses (10, 20, 150 kJ/m

Indexed as

Cell LineDNA DamageDose-Response Relationship, RadiationGene Expression RegulationHumansKeratinocytesModels, GeneticNeoplasmsSignal TransductionTranscriptional ActivationUltraviolet Raysbenchmark dosegenomicskeratinocytessolar simulatedultraviolet radiation

Identifiers

PMID29761935
PMCPMC6099464

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.