Activation of periodate by ABTS as an electron shuttle for degradation of aqueous organic pollutants and enhancement effect of phosphate.

Periodate (PI) based advanced oxidation processes (AOPs) have recently attracted much attention due to their high application potential in water purification through production of reactive species. In the study, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) was used as a representative electron shuttle, and its reaction with PI was investigated in detail. It was found that PI can be activated by ABTS via one-electron transfer to produce ABTS•+ and IO3•, cooperatively promoting oxidation of organic contaminants such as bisphenol A (BPA). Their contribution in BPA oxidation at pH 7 was estimated as 81.9% and 18.1%, respectively. With phosphate, BPA oxidation rate in the PI/ABTS process increased linearly with raised phosphate concentrations from 0 to 10 mM. The enhancement effect of phosphate is attributed to formation of PI-phosphate complexes, which facilitate PI activation by ABTS, and production of more ABTS•+ and IO3•, and additional phosphate radicals. Accordingly, the contribution of IO3• and phosphate radicals in BPA oxidation raised to 57.7% in the process with 4 mM phosphate, while that of ABTS•+ decreased to 42.3%. The reaction stoichiometry ratio of ABTS to PI was measured as 1.1 at pH 7, suggesting the little involvement of IO3• and phosphate radicals in production of ABTS•+ due to their high self-quenching. The PI/ABTS process exhibited excellent anti-interference capacity towards water matrix components (e.g. Cl-, HCO3- and natural organic matters). Moreover, an immobilized ABTS (ABTS/ZnAl-LDH) was successfully developed as a heterogeneous electron shuttle for PI oxidation, which resultantly exhibited the good catalytic activity and stability in degradation of BPA, further improving feasibility of the process in treatment of actual water. This work advances understanding on reaction of PI with ABTS from stoichiometric and kinetic aspects, and provides a high performance AOP for selective oxidation of trace organic contaminants.

A Retrospective Statistical Validation Approach for Panel of Normal-Based Single-Nucleotide Variant Detection in Tumor Sequencing.

An important step of somatic variant calling algorithms for deep sequencing data is quantifying the errors. For targeted sequencing in which hotspot mutations are of interest, site-specific error estimation allows more accurate calling. The site-specific error rates are often estimated from a panel of normal samples, which has limited size and is subject to sampling bias and variance. We propose a novel statistical validation method for single-nucleotide variation (SNV) calling based on historical data. The validation method extracts the high-quality reads from the Binary Alignment/Map (BAM) files, finds the negative samples in the data, and builds a statistical model to call individual samples. It is particularly useful in detecting low-frequency variants that may be missed by traditional panel of normal-based SNV methods. The proposed method makes it possible to launch a simple and parallel validation pipeline for SNV calling and improve the detection limit.