We investigated a sequential photocatalysis-dark reaction, wherein organic pollutants were degraded on Ag/TiO under UV irradiation and the dark reduction of hexavalent chromium (Cr(VI)) was subsequently followed. The photocatalytic oxidation of 4-chlorophenol (4-CP), a test organic substrate, induced the generation of degradation intermediates and the storage of electrons in Ag/TiO which were then utilized for reducing Cr(VI) in the postirradiation period. The dark reduction efficiency of Cr(VI) was much higher with Ag/TiO (87%), compared with bare TiO (27%) and Pt/TiO (22%). The Cr(VI) removal by Ag/TiO (87%) was contributed by adsorption (31%), chemical reduction by intermediates of 4-CP degradation (26%), and reduction by electrons stored in Ag (30%). When formic acid, humic acid or ethanol was used as an alternative organic substrate, the electron storage effect was also observed. The postirradiation removal of Cr(VI) on Ag/TiO continued for hours, which is consistent with the observation that a residual potential persisted on the Ag/TiO electrode in the dark whereas little residual potential was observed on bare TiO and Pt/TiO electrodes. The stored electrons in Ag/TiO and their transfer to Cr(VI) were also indicated by the UV-visible absorption spectral change. Moreover, the electrons stored in the preirradiated Ag/TiO reacted with O with showing a sign of low-level OH radical generation in the dark period.
Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational biomarkers from preclinical models. Here, we present a machine-learning framework to identify robust drug biomarkers by taking advantage of network-based analyses using pharmacogenomic data derived from three-dimensional organoid culture models. The biomarkers identified by our approach accurately predict the drug responses of 114 colorectal cancer patients treated with 5-fluorouracil and 77 bladder cancer patients treated with cisplatin. We further confirm our biomarkers using external transcriptomic datasets of drug-sensitive and -resistant isogenic cancer cell lines. Finally, concordance analysis between the transcriptomic biomarkers and independent somatic mutation-based biomarkers further validate our method. This work presents a method to predict cancer patient drug responses using pharmacogenomic data derived from organoid models by combining the application of gene modules and network-based approaches.
The oxidation of As(III) (arsenite) to As(V) (arsenate), a critical pretreatment process for total arsenic removal, is easily achieved using chemical oxidation methods. Hydrogen peroxide (H2O2) is widely used as an environmentally benign oxidant but its practical use for the arsenite oxidation is limited by the strong pH dependence and slow oxidation kinetics. This study demonstrated that H2O2-induced oxidation of As(III) can be markedly enhanced in the presence of nonferrous metal oxides (e.g., WO3, TiO2, ZrO2) as a heterogeneous catalyst working over a wide pH range in ambient reaction conditions. In particular, TiO2 is an ideal catalyst because it is not only active and stable but also easily available and inexpensive. Although the photocatalytic oxidation of As(III) on TiO2 was intensively studied, the thermal catalytic activities of TiO2 and other nonferrous metal oxides for the arsenic oxidation have been little investigated. The heterogeneous oxidation rate increased with increasing the TiO2 surface area and [H2O2] and weakly depended on pH whereas the homogeneous oxidation by H2O2 alone was favored only at alkaline condition. The oxidation rate in the TiO2/H2O2 system was not reduced at all in the absence of dioxygen. It was not retarded at all by OH radical scavengers but markedly inhibited by hydroperoxyl radical scavengers. It is proposed that the surface complexation of H2O2 on TiO2 induces the generation of the surface hydroperoxyl radical through an inner-sphere electron transfer, which subsequently reacts with As(III). The catalytic activity of TiO2 was maintained without showing any sign of deactivation. The heterogeneous catalytic oxidation is proposed as a viable method for the preoxidation treatment of As(III)-contaminated water under ambient conditions.
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