Evidence map›Paper›PMID 19507023›Full record

ArticleEcotoxicology (London, England)2009

Endocrine-disrupting equivalents in industrial effluents discharged into Yangtze River.

Wei Shi, Xiaoyi Wang, Wei Hu, Hong Sun, Ouxi Shen, Hongling Liu, Xinru Wang, John P Giesy, Shupei Cheng, Hongxia Yu

Abstract read
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In one paragraph

Article in Ecotoxicology (London, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

2 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 3 institutions in 2 countries.

Wei ShiState Key Laboratory of Pollution Control and Resource Reuse & School of the Environment, Nanjing University, 210093 Nanjing, People's Republic of China.
Xiaoyi Wang
Wei Hu
Hong Sun
Ouxi Shen
Hongling Liu
Xinru Wang
John P Giesy
Shupei Cheng
Hongxia Yu
Nanjing University · CNNanjing Medical University · CNState Key Laboratory of Pollution Control and Resource Reuse · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The endocrine-disrupting equivalents in effluents from three chemical industry wastewater treatment systems in the vicinity of Yangtze River were determined by several transactivation reporter gene assays. Transient transfections of African green monkey kidney cell line (CV-1) were used to determine the estrogenic, anti-androgenic and anti-thyroid equivalents in the effluents. Organic extracts of the effluents contained compounds that were potent anti-androgens and the activities measured as an equivalent concentration of flutamide were 45.53, 34.65 and 91.61 nM, respectively. The extracts also contained detectable concentrations of thyroid antagonists. Estrogenic activities, measured with the reporter gene assay, were near or below the method detection limit (0.58 pM as E2). Concentrations of some of the major constituents such as di(2-ethylhexyl)phthalate, dibutyl phthalate, 2,6-dinitrotoluene and nitrobenzene were quantified. The data suggest that the reporter gene assay is useful to predication of endocrine disrupting effects in polluted aquatic body.

Indexed as

AnimalsCell LineChinaChlorocebus aethiopsEndocrine DisruptorsEnvironmental MonitoringGenes, ReporterIndustrial WasteLuciferasesReceptors, AndrogenReceptors, EstrogenReceptors, Thyroid HormoneRiversTranscriptional ActivationTransfectionWater Pollutants, ChemicalEndocrine DisruptorsIndustrial WasteLuciferasesReceptors, AndrogenReceptors, EstrogenReceptors, Thyroid HormoneWater Pollutants, Chemical

Identifiers

PMID19507023
OpenAlexW2147469314

What OpenQuestion holds

Textmetadata
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.