Evidence map›Paper›PMID 26920535›Full record

ArticleEnvironmental science and pollution research international2016

Use of RSM modeling for optimizing decolorization of simulated textile wastewater by Pseudomonas aeruginosa strain ZM130 capable of simultaneous removal of reactive dyes and hexavalent chromium.

Zahid Maqbool, Sabir Hussain, Tanvir Ahmad, Habibullah Nadeem, Muhammad Imran, Azeem Khalid, Muhammad Abid, Fabrice Martin-Laurent

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Article in Environmental science and pollution research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
19.9field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 76 citations in OpenAlex.

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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 6 institutions in 3 countries.

Zahid MaqboolDepartment of Environmental Sciences and Engineering, Government College University, Allama Iqbal Road, 38000, Faisalabad, Pakistan.
Sabir HussainDepartment of Environmental Sciences and Engineering, Government College University, Allama Iqbal Road, 38000, Faisalabad, Pakistan. sabirghani@gmail.com.
Tanvir AhmadDepartment of Statistics, Government College University, Faisalabad, Pakistan.
Habibullah NadeemDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.
Muhammad ImranDepartment of Soil Science, Muhammad Nawaz Shareef University of Agriculture, Multan, Pakistan.
Azeem KhalidDepartment of Environmental Sciences, PMAS Arid Agriculture University, Rawalpindi, Pakistan.
Muhammad AbidDepartment of Plant Pathology, Faculty of Agricultural Sciences and Technology, Bahauddin Zakaria University, Multan, Pakistan.
Fabrice Martin-LaurentINRA, UMR 1347 Agroécologie, 17 Rue Sully, BP 86 510, 21065, Dijon, Cedex, France.
Government College University, Faisalabad · PKAgroécologie · FRBahauddin Zakariya University · PKMuhammad Nawaz Shareef University of Agriculture · PKPir Mehr Ali Shah Arid Agriculture University · PKUniversity College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remediation of colored wastewater loaded with dyes and metal ions is a matter of interest nowadays. In this study, 220 bacteria isolated from textile wastewater were tested for their potential to decolorize each of the four reactive dyes (reactive red-120, reactive black-5, reactive yellow-2, and reactive orange-16) in the presence of a mixture of four different heavy metals (Cr, Zn, Pb, Cd) commonly found in textile effluents. Among the tested bacteria, the isolate ZM130 was found to be the most efficient in decolorizing reactive dyes in the presence of the mixture of heavy metals and was identified as Pseudomonas aeruginosa strain ZM130 by 16S rRNA gene analysis. The strain ZM130 was highly effective in simultaneously removing hexavalent chromium (25 mg L(-1)) and the azo dyes (100 mg L(-1)) from the simulated wastewater even in the presence of other three heavy metals (Zn, Pb, Cd). Simultaneous removal of chromium and azo dyes ranged as 76.6-98.7 % and 51.9-91.1 %, respectively, after 180 h incubation. On the basis of quadratic polynomial equation and response surfaces given by the response surface methodology (RSM), optimal salt content, pH, carbon co-substrate content, and level of multi-metal mixtures for decolorization of reactive red-120 in a simulated textile wastewater by the strain ZM130 were predicted to be 19.8, 7.8, and 6.33 g L(-1) and a multi-metal mixture (Cr 13.10 mg L(-1), Pb 26.21 mg L(-1), Cd 13.10 mg L(-1), Zn 26.21 mg L(-1)), respectively. Moreover, the strain ZM130 also exhibited laccase and nicotinamide adenine dinucleotide (reduced)-dichlorophenolindophenol reductase (NADH-DCIP reductase) activity during the decolorization of reactive red-120. However, the laccase activity was found to be maximum in the presence of 300 mg L(-1) of the dye as compared to other concentrations. Hence, the isolation of this strain might serve as a potential bio-resource required for developing the strategies aiming at bioremediation of the wastewater contaminated with dyes and heavy metals.

Indexed as

Models, TheoreticalTextile IndustryAzo CompoundsBiodegradation, EnvironmentalChromiumColoring AgentsLaccaseMetals, HeavyPseudomonas aeruginosaQuinone ReductasesRNA, Ribosomal, 16SWastewaterWater Pollutants, ChemicalWater PurificationAzo CompoundsChromiumchromium hexavalent ionColoring Agentsdichlorophenolindophenol reductaseLaccaseMetals, HeavyQuinone ReductasesRNA, Ribosomal, 16SWastewaterWater Pollutants, ChemicalBiodecolorizationCr(VI) reductionLaccase and NADH-DCIP reductaseMulti-metal mixture stressPseudomonasResponse surface methodology (RSM)

Identifiers

PMID26920535
OpenAlexW2290778903

What OpenQuestion holds

Textmetadata
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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.