Amination of cotton fiber using polyethyleneimine and its application as an adsorbent to directly remove a harmful cyanobacterial species, Microcystis aeruginosa, from an aqueous medium.

In the present study, we applied an adsorption-based strategy for the removal of a harmful cyanobacterial species, Microcystis aeruginosa, using cotton fiber. Considering the negatively charged surface properties of M. aeruginosa cells in aqueous phases, aminated cotton fibers were prepared through polyethyleneimine (PEI) modification on the pristine cotton fibers.

Phosphorus adsorption behavior of industrial waste biomass-based adsorbent, esterified polyethylenimine-coated polysulfone-Escherichia coli biomass composite fibers in aqueous solution.

This study sought to develop a highly efficient adsorbent material for phosphorus (P) removal via valorization of industrial Escherichia coli biomass waste. To ensure an easy and fast recovery after the sorption process, the E. coli biomass waste was immobilized into polysulfone matrix.

Application of a polyethylenimine-modified polyacrylonitrile-biomass waste composite fiber sorbent for the removal of a harmful cyanobacterial species from an aqueous solution.

Cyanobacterial harmful algal blooms (Cyano-HABs) in water resources involving algal species such as Microcystis aeruginosa have become a serious environmental issue due to their severely negative effects. In the present study, an adsorption-based strategy was employed to control M. aeruginosa, with industrial waste-derived Escherichia coli biomass valorized to produce polyethylenimine-modified polyacrylonitrile-E.

[Factors Affecting the Self-Management of Adolescents with Type 1 Diabetes Mellitus based on the Information-Motivation-Behavioral Skills Model].

Purpose: The purpose of this study was to investigate associations between self-management and diabetes knowledge, diabetesrelated attitudes, family support, and self-efficacy in adolescents with type 1 diabetes mellitus based on the information-motivation- behavior skills model.

Methods: Data collection was conducted between March 18 and September 30, 2018. Patients (=87) aged 12 to 19 years were recruited from the outpatient clinic of S children's hospital and an online community for patient with type 1 diabetes mellitus.