Evidence map›Paper›PMID 30841572›Full record

ArticleInternational journal of environmental research and public health2019

Impacting Microbial Communities and Absorbing Pollutants by

Yinghai Wu, Tao He, Chen Chen, Xiaohang Fang, Dongyang Wei, Jing Yang, Renduo Zhang, Rui Han

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Ceramsite Facilitated Microbial Degradation of Pollutants in Domestic Wastewater.International journal of environmental research and public health · 2020
    Article
  5. 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

8 authors.

Yinghai WuCollege of Marine and Civil Engineering, Dalian Ocean University, Dalian 116023, China. wuyinghai@dlou.edu.cn.
Tao HeSouth China Institute of Environmental Science, Ministry of Environment Protection, Guangzhou 510655, China. hetao@scies.org.
Chen ChenSouth China Institute of Environmental Science, Ministry of Environment Protection, Guangzhou 510655, China. chenchen7@scies.org.
Xiaohang FangSouth China Institute of Environmental Science, Ministry of Environment Protection, Guangzhou 510655, China. fangxiaohang@scies.org.
Dongyang WeiSouth China Institute of Environmental Science, Ministry of Environment Protection, Guangzhou 510655, China. weidongyang@scies.org.
Jing YangSouth China Institute of Environmental Science, Ministry of Environment Protection, Guangzhou 510655, China. yangjing@scies.org.
Renduo ZhangGuangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, Sun Yat-sen University, Guangzhou 510275, China. Zhangrd@mail.sysu.edu.cn.
Rui HanCollege of Marine Technology and Environment, Dalian Ocean University, Dalian 116023, China. hanrui@dlou.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wetland plants that cover the wetlands play an important role in reducing pollutants. The aim of this study was to investigate the effect of two plant species on microbial communities and nitrogen-removal genes and to evaluate the contributions of absorbing pollutants by

Indexed as

MicrobiotaWetlandsAmmoniaBacteriaCyperusNitrogenRhizosphereRNA, Ribosomal, 16SWaste Disposal, FluidWater PollutantsZingiberalesAmmoniaNitrogenRNA, Ribosomal, 16SWater Pollutantsbiological inhibitionfunctional genehigh-throughputmicrobial distributionphytoremediationwetland plant

Identifiers

PMID30841572
PMCPMC6427132

What OpenQuestion holds

Textmetadata
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.