Evidence map›Paper›PMID 28246922›Full record

ArticleMicrobial ecology2017

Investigating the Microbial Degradation Potential in Oil Sands Fluid Fine Tailings Using Gamma Irradiation: A Metagenomic Perspective.

Danielle VanMensel, Subba Rao Chaganti, Ryan Boudens, Thomas Reid, Jan Ciborowski, Christopher Weisener

Abstract read
PubMed Publisher
In one paragraph

Article in Microbial ecology, 2017. 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
–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

1 citing paper in PubMed.

  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

6 authors.

Danielle VanMenselGreat Lakes Institute of Environmental Science, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada. vanmensd@uwindsor.ca.
Subba Rao ChagantiGreat Lakes Institute of Environmental Science, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada.
Ryan BoudensGreat Lakes Institute of Environmental Science, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada.
Thomas ReidGreat Lakes Institute of Environmental Science, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada.
Jan CiborowskiDepartment of Biology, University of Windsor, Windsor, Ontario, Canada.
Christopher WeisenerGreat Lakes Institute of Environmental Science, University of Windsor, 401 Sunset Avenue, Windsor, Ontario, N9B 3P4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Open-pit mining of the Athabasca oil sands has generated large volumes of waste termed fluid fine tailings (FFT), stored in tailings ponds. Accumulation of toxic organic substances in the tailings ponds is one of the biggest concerns. Gamma irradiation (GI) treatment could accelerate the biodegradation of toxic organic substances. Hence, this research investigates the response of the microbial consortia in GI-treated FFT materials with an emphasis on changes in diversity and organism-related stimuli. FFT materials from aged and fresh ponds were used in the study under aerobic and anaerobic conditions. Variations in the microbial diversity in GI-treated FFT materials were monitored for 52 weeks and significant stimuli (p < 0.05) were observed. Chemoorganotrophic organisms dominated in fresh and aged ponds and showed increased relative abundance resulting from GI treatment. GI-treated anaerobic FFT

Indexed as

Gamma RaysMetagenomeMicrobial ConsortiaBiodegradation, EnvironmentalMiningOil and Gas FieldsPondsBiodegradationBioremediationFluid fine tailingsGamma irradiationMicrobial communityOil sands

Identifiers

PMID28246922

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.