Evidence map›Paper›PMID 35518970›Full record

ArticleRSC advances2019

Bacteria-supported iron scraps for the removal of nitrate from low carbon-to-nitrogen ratio wastewater.

Xiawei Liu, Jian Xu, Jiaolong Huang, Manqi Huang, Tao Wang, Shaopan Bao, Wei Tang, Tao Fang

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 32 citations in OpenAlex.

  1. 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 at 1 institution in 2 countries.

Xiawei LiuInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Jian XuInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Jiaolong HuangInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Manqi HuangInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Tao WangInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Shaopan BaoInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Wei TangInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.
Tao FangInstitute of Hydrobiology, Chinese Academy of Sciences 7 Donghu South Road, Wuchang District Wuhan 430072 China fangt@ihb.ac.cn.ORCID https://orcid.org/0000-0002-0995-691X
Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel bacteria-supported iron scraps (BSIS) system was developed for nitrate removal from low carbon-to-nitrogen ratio (C/N) wastewater. The system consisted of low-cost iron scraps and the accumulated denitrifying-related bacteria enriched from an Fe-wastewater environment when the system was operating. After operating for 39 d, the nitrate removal rate of the system increased to 73.55% within 24 h. The extraction of bacteria from the system revealed that iron scraps and bacteria had a synergistic effect on nitrate removal and bacteria only took effect when cooperating with iron. Microbial analysis using high-throughput sequencing showed that

Identifiers

PMID35518970
PMCPMC9059957
OpenAlexW2913515010

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.