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Maurice Ekpenyong

Researcher at University of Calabar

Publications -  32
Citations -  225

Maurice Ekpenyong is an academic researcher from University of Calabar. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 6, co-authored 20 publications receiving 119 citations.

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Plackett-Burman Design and Response Surface Optimization of Medium Trace Nutrients for Glycolipopeptide Biosurfactant Production

TL;DR: The glycolipopeptide biosurfactant produced by Pseudomonas aeruginosa strain IKW1 reduced the surface tension of fermentation broth from 71.31 to 24.62 dynes/cm at a critical micelle concentration of 20.80 mg/L and is recommended for the formulation of inexpensive pharmaceutical products that require surface-active compounds.
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Response surface modeling and optimization of major medium variables for glycolipopeptide production

TL;DR: In this article, an unusual strain of Pseudomonas aeruginosa readily produced a glycolipopeptide compound which reduced surface tension of fermentation broth from 71.31dnes/cm to 24.62dynes/cm at a critical micelle concentration of 20.80mg/L.
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Statistical and Artificial Neural Network Approaches to Modeling and Optimization of Fermentation Conditions for Production of a Surface/Bioactive Glyco-lipo-peptide

TL;DR: Bioprocess conditions namely temperature, pH, agitation and duration were comparatively modeled using statistical and artificial neural network methods to predict and optimize product yield using the matrix of a central composite rotatable design (CCRD).
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A Pseudomonas aeruginosa Strain Ikw1 Produces an Unusual Polymeric Surface-Active Compound in Waste Frying Oil-Minimal Medium

TL;DR: Oil displacement, emulsifying and antimicrobial activities of the compound were relatively stable at relevant temperatures, pH and NaCl levels suggesting suitability for applications in hydrophobic compound remediation, emulsion stabilization and preservation of formulations.
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Bioprocess Optimization of Nutritional Parameters for Enhanced Anti-leukemic L-Asparaginase Production by Aspergillus candidus UCCM 00117: A Sequential Statistical Approach

TL;DR: In this paper, a multi-objective approach using desirability function generated through predictor importance and weighted coefficient methodology was adopted for optimization of Bioprocess nutritional conditions for production of glutaminase-near free L-asparaginase by Aspergillus candidus UCCM 00117 was conducted under shake flask laboratory conditions.