Evidence map›Paper›PMID 29234833›Full record

ArticleArchives of toxicology2018

Towards a generic physiologically based kinetic model to predict in vivo uterotrophic responses in rats by reverse dosimetry of in vitro estrogenicity data.

Mengying Zhang, Bennard van Ravenzwaay, Eric Fabian, Ivonne M C M Rietjens, Jochem Louisse

Abstract read
In one paragraph

Article in Archives of toxicology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Toward Realistic DosimetryChemical research in toxicology · 2022
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  6. Review
  7. Article
  8. Article
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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

5 authors.

Mengying ZhangDivision of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands. mengying.zhang@wur.nl.ORCID http://orcid.org/0000-0003-2106-5842
Bennard van RavenzwaayDivision of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.
Eric FabianExperimental Toxicology and Ecology, BASF SE, Z 470, 67056, Ludwigshafen, Germany.
Ivonne M C M RietjensDivision of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.
Jochem LouisseDivision of Toxicology, Wageningen University, Stippeneng 4, 6708 WE, Wageningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physiologically based kinetic (PBK) modelling-based reverse dosimetry is a promising tool for the prediction of in vivo developmental toxicity using in vitro concentration-response data. In the present study, the potential of this approach to predict the dose-dependent increase of uterus weight in rats upon exposure to estrogenic chemicals was assessed. In vitro concentration-response data of 17β-estradiol (E2) and bisphenol A (BPA) obtained in the MCF-7/BOS proliferation assay, the U2OS ER-CALUX assay and the yeast estrogen screen (YES) assay, were translated into in vivo dose-response data in rat, using a PBK model with a minimum number of in vitro and in silico determined parameter values. To evaluate the predictions made, benchmark dose (BMD) analysis was performed on the predicted dose-response data and the obtained BMDL

Indexed as

Dose-Response Relationship, DrugModels, BiologicalAnimalsBenzhydryl CompoundsBisphenol A CompoundsChromatography, High Pressure LiquidEstradiolEstrogens, Non-SteroidalFemaleHumansInactivation, MetabolicKineticsMaleMCF-7 CellsPhenolsRats, Sprague-DawleyBenzhydryl Compoundsbisphenol ABisphenol A CompoundsEstradiolEstrogens, Non-SteroidalPhenolstebuconazoleTriazoles17β-estradiolBisphenol AIn vitro–in vivo extrapolationPhysiologically based kinetic modellingReverse dosimetryUterotrophic assay

Identifiers

PMID29234833
PMCPMC5866837

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Registered trials

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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.