Evidence map›Paper›PMID 36399308›Full record

ArticleApplied biochemistry and biotechnology2024

Microbial Remediation of Crude Oil in Saline Conditions by Oil-Degrading Bacterium Priestia megaterium FDU301.

Xiaoyan Liu, Jinghao Ji, Xinying Zhang, Zongze Chen, Lihong He, Chuanhua Wang

Abstract read
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In one paragraph

Article in Applied biochemistry and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Xiaoyan LiuLaboratory of Environmental Remediation, College of Environmental and Chemical Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, China.
Jinghao JiLaboratory of Environmental Remediation, College of Environmental and Chemical Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, China.
Xinying ZhangLaboratory of Environmental Remediation, College of Environmental and Chemical Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, China. zxyshu@shu.edu.cn.
Zongze ChenLaboratory of Environmental Remediation, College of Environmental and Chemical Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, China.
Lihong HeLaboratory of Environmental Remediation, College of Environmental and Chemical Engineering, Shanghai University, 99 Shangda Road, Shanghai, 200444, China.
Chuanhua WangCollege of Life and Environmental Science, Wenzhou University, Wenzhou, 325035, Zhejiang, China.

Funding

National Natural Science Foundation of China 21677093National Natural Science Foundation of China 21806100Natural Science Foundation of Shanghai 18ZR1414100Natural Science Foundation of Zhejiang LY20D030002
6 · The paper itself

Abstract

Salinity greatly affects the microbial degradation process of crude oil; thus, the isolation and identification of halotolerant microbes is essential. Limited studies explored how microbes respond to increased salinity. In this study, an oil-degrading bacterium Priestia megaterium FDU301 was isolated from the Dagang oil field, which can tolerate a salinity of 6%. Compared to the non-saline condition, oil degradation ratios by P. megaterium FDU301 increased by 15.27% and 11.26% in 0.5% and 3.5% salinity media, respectively. Meanwhile, bacteria degraded various components of crude oil more thoroughly in saline environments, especially mid-chain hydrocarbons (C

Indexed as

Biodegradation, EnvironmentalPetroleumSalinityBiofilmsSaccharomycetalesSurface-Active AgentsPetroleumSurface-Active AgentsBioremediationDegradation mechanismHalotolerant strainOil contaminationSalinity

Identifiers

PMID36399308

What OpenQuestion holds

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Registered trials

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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.