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Haishan Qi

Researcher at Tianjin University

Publications -  42
Citations -  573

Haishan Qi is an academic researcher from Tianjin University. The author has contributed to research in topics: Chemistry & Streptomyces hygroscopicus. The author has an hindex of 13, co-authored 30 publications receiving 373 citations. Previous affiliations of Haishan Qi include Chinese Ministry of Education.

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Bioinspired Multifunctional Protein Coating for Antifogging, Self-Cleaning, and Antimicrobial Properties.

TL;DR: A multifunctional coating with antifogging, self-cleaning, and antimicrobial properties has been prepared based on a mussel-inspired chimeric protein MP-KE, which is the first example that these proteins were successfully applied to fabricate antifogged surfaces.
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Poly(carboxybetaine methacrylate)-functionalized magnetic composite particles: A biofriendly support for lipase immobilization.

TL;DR: Results showed that pCB-Fe3O4 composite particles had higher efficiency and improved stability for lipase immobilization, which are more promising for industrial scale up of biocatalytic systems with excellent biocompatibility.
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A mussel-inspired chimeric protein as a novel facile antifouling coating.

TL;DR: 3,4-Dihydroxyphenyl-alanine and zwitterionic peptides inspired from molecular chaperones were incorporated into the designed protein and exhibits superior antifouling properties.
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Engineering Scheffersomyces stipitis for fumaric acid production from xylose.

TL;DR: In this work, Scheffersomyces stipitis, the yeast with excellent xylose-utilizing ability, was firstly engineered for fumaric acid production fromxylose with the heterologous reductive pathway from Rhizopus oryzae FM19, and it was indicated that the S. stipitis was a promising platform.
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Rational medium optimization based on comparative metabolic profiling analysis to improve fumaric acid production

TL;DR: Exogenous addition strategies were developed, which resulted in 14% increase of fumaric acid and less by-products and demonstrated that metabolic profiling analysis could be successfully applied to the rational guidance of medium optimization and the productivity improvement of value-added compounds.