Evidence map›Paper›PMID 40356659›Full record

ArticleFrontiers in microbiology2025

Microalgae-bacteria symbiosis enhanced nitrogen removal from wastewater in an inversed fluidized bed bioreactor: performance and microflora.

Xin Zheng, Ruoting Liu, Kai Li, Junhao Sun, Kanming Wang, Yuanyuan Shao, Zhongce Hu, Jesse Zhu, Zhiyan Pan, George Nakhla

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Xin ZhengCollege of Environment, Zhejiang University of Technology, Hangzhou, China.
Ruoting LiuDepartment of Chemical and Biochemical Engineering, The University of Western Ontario, London, ON, Canada.
Kai LiWenzhou Ecological and Environmental Monitoring Center of Zhejiang Province, Wenzhou, China.
Junhao SunDepartment of Chemical and Biochemical Engineering, The University of Western Ontario, London, ON, Canada.
Kanming WangCollege of Environment, Zhejiang University of Technology, Hangzhou, China.
Yuanyuan ShaoNottingham Ningbo China Beacons of Excellence Research and Innovation Institute, The University of Nottingham Ningbo China, Ningbo, China.
Zhongce HuCollege of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, China.
Jesse ZhuDepartment of Chemical and Biochemical Engineering, The University of Western Ontario, London, ON, Canada.
Zhiyan PanCollege of Environment, Zhejiang University of Technology, Hangzhou, China.
George NakhlaDepartment of Chemical and Biochemical Engineering, The University of Western Ontario, London, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional wastewater biological nitrogen removal (BNR) processes require a large amount of air and external organic carbon, causing a significant increase in operating costs and potential secondary pollution. Herein, this study investigated the nitrogen removal performance and the underlying mechanisms of a novel simultaneous nitrification and denitrification (SND) coupled with photoautotrophic assimilation system in an inversed fluidized bed bioreactor (IFBBR). Nitrogen removal was achieved through the synergistic interaction of microalgae and bacteria, with microalgae providing O

Indexed as

biological nitrogen removalmass balancemicroalgal-bacterial symbiosis systemsimultaneous nitrification and denitrificationsyntrophic microbial communities

Identifiers

PMID40356659
PMCPMC12066685

What OpenQuestion holds

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LicenceCC BY
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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.