Evidence map›Paper›PMID 24205252›Full record

ArticlePloS one2013

Correlation models between environmental factors and bacterial resistance to antimony and copper.

Zunji Shi, Zhan Cao, Dong Qin, Wentao Zhu, Qian Wang, Mingshun Li, Gejiao Wang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
4.0field-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

19 citing papers in PubMed, 80 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. A halophilicFrontiers in microbiology · 2023
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Bacterial community profile of contaminated soils in a typical antimony mining site.Environmental science and pollution research international · 2018
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Arsenite oxidase also functions as an antimonite oxidase.Applied and environmental microbiology · 2015
    Article
  17. Article
  18. Article
  19. 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 at 1 institution in 1 country.

Zunji ShiState Key Laboratory of Agricultural Microbiology, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, P.R. China.
Zhan Cao
Dong Qin
Wentao Zhu
Qian Wang
Mingshun Li
Gejiao Wang
Huazhong Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimony (Sb) and copper (Cu) are toxic heavy metals that are associated with a wide variety of minerals. Sb(III)-oxidizing bacteria that convert the toxic Sb(III) to the less toxic Sb(V) are potentially useful for environmental Sb bioremediation. A total of 125 culturable Sb(III)/Cu(II)-resistant bacteria from 11 different types of mining soils were isolated. Four strains identified as Arthrobacter, Acinetobacter and Janibacter exhibited notably high minimum inhibitory concentrations (MICs) for Sb(III) (>10 mM),making them the most highly Sb(III)-resistant bacteria to date. Thirty-six strains were able to oxidize Sb(III), including Pseudomonas-, Comamonas-, Acinetobacter-, Sphingopyxis-, Paracoccus- Aminobacter-, Arthrobacter-, Bacillus-, Janibacter- and Variovorax-like isolates. Canonical correspondence analysis (CCA) revealed that the soil concentrations of Sb and Cu were the most obvious environmental factors affecting the culturable bacterial population structures. Stepwise linear regression was used to create two predictive models for the correlation between soil characteristics and the bacterial Sb(III) or Cu(II) resistance. The concentrations of Sb and Cu in the soil was the significant factors affecting the bacterial Sb(III) resistance, whereas the concentrations of S and P in the soil greatly affected the bacterial Cu(II) resistance. The two stepwise linear regression models that we derived are as follows: MIC(Sb(III))=606.605+0.14533 x C(Sb)+0.4128 x C(Cu) and MIC((Cu)(II))=58.3844+0.02119 x C(S)+0.00199 x CP [where the MIC(Sb(III)) and MIC(Cu(II)) represent the average bacterial MIC for the metal of each soil (μM), and the C(Sb), C(Cu), C(S) and C(P) represent concentrations for Sb, Cu, S and P (mg/kg) in soil, respectively, p<0.01]. The stepwise linear regression models we developed suggest that metals as well as other soil physicochemical parameters can contribute to bacterial resistance to metals.

Indexed as

EnvironmentModels, TheoreticalAntimonyBacteriaBiodegradation, EnvironmentalBiodiversityCopperEnvironmental PollutantsMiningOxidation-ReductionSoil MicrobiologyAntimonyCopperEnvironmental Pollutants

Identifiers

PMID24205252
PMCPMC3812145
OpenAlexW1988644222

What OpenQuestion holds

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LicenceCC BY
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.