Enzymatic processing of protein-based fibers

Wool and silk are major protein fiber materials used by the textile industry. Fiber protein structure-function relationships are briefly described here, and the major enzymatic processing routes for textiles and other novel applications are deeply reviewed. Fiber biomodification is described here with various classes of enzymes such as protease, transglutaminase, tyrosinase, and laccase. It is expected that the reader will get a perspective on the research done as a basis for new applications in other areas such as cosmetics and pharma.This work was financially supported by the National Natural Science Foundation of China (21274055,51373071, 31201134 and 31470509), the Program for New Century Excellent Talents in University (NCET-12-0883), the Program for Changjiang Scholars and Innovative Research Team in University (IRT1135), the Jiangsu Provincial Natural Science Foundation of China (BK2012112), and the Fundamental Research Funds for the Central Universities (JUSRP51312B)

A novel technique for detoxification of phenol from wastewater: Nanoparticle Assisted Nano Filtration (NANF)

© 2016 Naidu et al. Background: Phenol is one of the most versatile and important organic compound. It is also a growing concern as water pollutants due to its high persistence and toxicity. Removal of Phenol from wastewaters was investigated using a novel nanoparticle adsorption and nanofiltration technique named as Nanoparticle Assisted Nano Filtration (NANF). Methods: The nanoparticle used for NANF study were silver nanoparticles and synthesized to three distinct average particle sizes of 10 nm, 40 nm and 70 nm. The effect of nanoparticle size, their concentrations and their tri and diparticle combinations upon phenol removal were studied. Results: Total surface areas (TSA) for various particle size and concentrations have been calculated and the highest was 4710 × 1012 nm2 for 10 nm particles and 180 ppm concentration while the lowest was for 2461 × 1011 for 70 nm and 60 ppm concentrations. Tri and diparticle studies showed more phenol removal % than that of their individual particles, particularly for using small particles on large membrane pore size and large particles at low concentrations. These results have also been confirmed with COD and toxicity removal studies. Conclusions: The combination of nanoparticles adsorption and nanofiltration results in high phenol removal and mineralization, leading to the conclusion that NANF has very high potential for treating toxic chemical wastewaters

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

BACKGROUND: Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. METHODS: We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. RESULTS: We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. CONCLUSIONS: Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described