Evidence map›Paper›PMID 39316167›Full record

ArticleBioprocess and biosystems engineering2025

Evaluating the efficacy of microalgal-bacterial granular sludge system in lake water remediation.

Siqi Du, Shaodong Guo, Jieru Yang, Anjie Li, Wenxuan Xiong, Chi Zhang, Shenghui Xu, Yuting Shi, Bin Ji

Abstract read
PubMed Publisher
In one paragraph

Article in Bioprocess and biosystems engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Siqi DuDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Shaodong GuoDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Jieru YangDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Anjie LiKey Laboratory of Water and Sediment Sciences of Ministry of Education, State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China.
Wenxuan XiongDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Chi ZhangDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Shenghui XuDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Yuting ShiDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China.
Bin JiDepartment of Water and Wastewater Engineering, School of Urban Construction, Wuhan University of Science and Technology, Wuhan, 430065, China. binji@wust.edu.cn.

Funding

Hubei Province University Student Innovation and Entrepreneurship Training Program, China S202310488075National Natural Science Foundation of China 51808416National Natural Science Foundation of China 52261135627
6 · The paper itself

Abstract

The microalgal-bacterial granular sludge (MBGS) process is attracting attention as a green wastewater treatment technology. However, research on the application of MBGS in lake water remediation is limited. Thus, this experiment investigated the feasibility and the efficacy of the MBGS process for the treatment of natural lake water in a continuous-flow tubular reactor. The average removal efficiencies of COD, NH

Indexed as

BacteriaBioreactorsLakesMicroalgaeSewageWater PurificationSewageBacteriaContinuous-flowLake water treatmentMicroalgaeMicrobial community

Identifiers

PMID39316167

What OpenQuestion holds

Textmetadata
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.