Evidence map›Paper›PMID 28508333›Full record

ArticleEnvironmental science and pollution research international2017

Levels and risk assessment of metals in sediment and fish from Chaohu Lake, Anhui Province, China.

Ting Fang, Wenxuan Lu, Jing Li, Xiuxia Zhao, Kun Yang

Abstract read
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Article in Environmental science and pollution research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Metal concentrations in fish from nine lakes of Anhui Province and the health risk assessment.Environmental science and pollution research international · 2020
    Article
  7. Article
  8. 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

5 authors.

Ting FangFisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China.
Wenxuan LuFisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China. ahfishery@163.com.
Jing LiFisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China.
Xiuxia ZhaoFisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China.
Kun YangFisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chaohu Lake is the fifth largest freshwater lake in China, which tolerates substantial amount of anthropogenic discharge from surrounding cities that resulting in the degradation of water and damage of aquatic ecosystem. Metal analysis of sediment and aquatic organisms can provide important information on the environmental contamination and potential impact of aquatic food consumption. Thus, the concentrations of Cu, Pb, Zn, Cr, Cd, As, and Hg in sediment and fish from Chaohu Lake were analyzed with inductively coupled plasma mass spectrometry and atomic fluorescence spectrometry. The mean content of Cu, Pb, Zn, Cr, Cd, As, and Hg in the sediment samples were 27.4 ± 6.3, 40.5 ± 12.3, 136.8 ± 65.5, 68.5 ± 9.1, 0.357 ± 0.141, 10.8 ± 1.7, and 0.117 ± 0.049 mg/kg, respectively. The results were compared with background values and evaluation methods, to characterize the potential ecological risk. The concentrations of Cu, Pb, Zn, Cr, Cd, As, and Hg in the fish muscle samples were 1.68-5.31, 0.078-0.31, 15.55-372.98, 0.31-0.93, 0.001-0.033, 0.29-1.03, and 0.04-0.197 mg kg

Indexed as

FishesAnimalsChinaEnvironmental MonitoringFood ContaminationGeologic SedimentsHumansLakesMetals, HeavyRisk AssessmentWater Pollutants, ChemicalMetals, HeavyWater Pollutants, ChemicalChaohu LakeFishMetalRisk assessmentSediment

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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.