Evidence map›Paper›PMID 37129646›Full record

ArticleWorld journal of microbiology & biotechnology2023

Production, characterization, and kinetic modeling of biosurfactant synthesis by Pseudomonas aeruginosa gi |KP 163922|: a mechanism perspective.

Shailee Gaur, Suresh Gupta, Amit Jain

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Article in World journal of microbiology & biotechnology, 2023. 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
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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

3 authors.

Shailee GaurDepartment of Chemical Engineering, Birla Institute of Technology and Science, Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India.ORCID http://orcid.org/0000-0003-2278-4128
Suresh GuptaDepartment of Chemical Engineering, Birla Institute of Technology and Science, Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India.ORCID http://orcid.org/0000-0003-0701-9049
Amit JainDepartment of Chemical Engineering, Birla Institute of Technology and Science, Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India. amitjain@pilani.bits-pilani.ac.in.ORCID http://orcid.org/0000-0002-7184-9322

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kinetic studies and modeling of production parameters are essential for developing economical biosurfactant production processes. This study will provide a perspective on mechanistic reaction pathways to metabolize Waste Engine Oil (WEO). The results will provide relevant information on (i) WEO concentration above which growth inhibition occurs, (ii) chemical changes in WEO during biodegradation, and (iii) understanding of growth kinetics for the strain utilizing complex substrates. Laboratory scale experiments were conducted to study the kinetics and biodegradation potential of the strain Pseudomonas aeruginosa gi |KP 163922| over a range (0.5-8% (v/v)) of initial WEO concentration for 168 h. The kinetic models, such as Monod, Powell, Edward, Luong, and Haldane, were evaluated by fitting the experimental results in respective model equations. An unprecedented characterization of the substrate before and after degradation is presented, along with biosurfactant characterization. The secretion of biosurfactant during the growth, validated by surface tension reduction (72.07 ± 1.14 to 29.32 ± 1.08 mN/m), facilitated the biodegradation of WEO to less harmful components. The strain showed an increase in maximum specific growth rate (µ

Indexed as

Pseudomonas aeruginosaSurface-Active AgentsBiodegradation, EnvironmentalGlycolipidsKineticsGlycolipidsSurface-Active AgentsLuong modelNon-linear regressionRhamnolipidSpecific growth rateSubstrate inhibitionWaste engine oilβ-oxidation

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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.