Biparametric multicommutated flow analysis system for determination of human serum phosphoesterase activity

A multicommutated flow analysis (MCFA) system constructed of microsolenoid valves and pumps offering simultaneous determination of activity of acid phosphatase (ACP) and alkaline phosphatase (ALP) in human serum samples has been developed. The MCFA system is based on optoelectronic flow-through detector made of two light emitting diodes and operating according to paired emitter detector diode (PEDD) principle. This photometric PEDD device has been dedicated for detection of p-nitrophenol (NP) generated in the course of enzymatic hydrolysis of p-nitrophenyl phosphate and optimized for the determination of NP in human serum samples. The developed PEDD-based MCFA system allows independent optimization of conditions for reaction and detection steps of photometric ACP and ALP bioassays. Moreover, it allows elimination of photometric interferences from serum matrix components according to two-points kinetic mode of measurement. The single measurement cycle takes 12 min, consists of four measurements (two for each phosphoesterase) and enables determination of serum ACP and ALP activities at physiological and pathological levels. The real analytical utility of the developed MCFA system has been confirmed by analysis of control sera as well as real human serum samples from healthy persons and oncological patients.     

高容量超级电容器电极材料的设计与制备

超级电容器寿命长,安全性高,并可以实现快速充放电,是化学电源研究的热点之一。然而,超级电容器的能量密度较低限制了其更多的应用。因此,超级电容器领域的研究关注点在如何提高超级电容器的能量密度。其中,提高比容量是提高能量密度的一种有效途径。本文通过对电极材料和电解液的优化来研究制备得到高容量超级电容器的方法。电极材料的比表面积、孔道结构和导电性对其电化学性能有着直接的影响。一方面,通过优化电极材料的孔道结构和比表面积可以增加活性位点并提高电解液离子传导率,从而得到高比电容。另一方面,电极材料导电性的提高有利于提升其电子传导率从而得到较高的比容量。本文分别对碳材料和金属氧化物/氢氧化物的优化达到了增加双电层电容和赝电容的目的。不仅如此,还可以通过在电解液中增加氧化还原电对从而得到高比电容。这一方法为高容量超级电容器的制备提供了新的思路。     

Surface modification by graphene oxide:An efficient strategy to improve the performance of activated carbon based supercapacitors

An efficient and cost-effective strategy to modificate the surface of active carbon (AC), form a 3D-conductive network, and therefore improve the electrochemical performance of AC based supercapacitor was developed.     

Asymmetric synthesis of 1,3-oxathiolan-5-one derivatives through dynamic covalent kinetic resolution

The asymmetric synthesis of 1,3-oxathiolan-5-one derivatives through an enzyme-catalyzed, dynamic covalent kinetic resolution strategy is presented. Dynamic hemithioacetal formation combined with intramolecular, lipase-catalyzed lactonization resulted in good conversions with moderate to good enantiomeric excess (ee) for the final products. The process was evaluated for different lipase preparations, solvents, bases, and reaction temperatures, where lipase B from Candida antarctica (CAL-B) proved most efficient. The substrate scope was furthermore explored for a range of aldehyde structures, together with the potential access to nucleoside analog inhibitor core structures.     

ABLE: Attention based learning for enzyme classification

Classifying proteins into their respective enzyme class is an interesting question for researchers for a variety of reasons. The open source Protein Data Bank (PDB) contains more than 1,60,000 structures, with more being added everyday. This paper proposes an attention-based bidirectional-LSTM model (ABLE) trained on over sampled data generated by SMOTE to analyse and classify a protein into one of the six enzyme classes or a negative class using only the primary structure of the protein described as a string by the FASTA sequence as an input. We achieve the highest F1-score of 0.834 using our proposed model on a dataset of proteins from the PDB. We baseline our model against eighteen other machine learning and deep learning networks, including CNN, LSTM, Bi-LSTM, GRU, and the state-of-the-art DeepEC model. We conduct experiments with two different oversampling techniques, SMOTE and ADASYN. To corroborate the obtained results, we perform extensive experimentation and statistical testing.