The high cost of the platinum-based cathode catalysts for the oxygen reduction reaction (ORR) has impeded the widespread application of polymer electrolyte fuel cells. We report on a new family of non-precious metal catalysts based on ordered mesoporous porphyrinic carbons (M-OMPC; M = Fe, Co, or FeCo) with high surface areas and tunable pore structures, which were prepared by nanocasting mesoporous silica templates with metalloporphyrin precursors. The FeCo-OMPC catalyst exhibited an excellent ORR activity in an acidic medium, higher than other non-precious metal catalysts. It showed higher kinetic current at 0.9 V than Pt/C catalysts, as well as superior long-term durability and MeOH-tolerance. Density functional theory calculations in combination with extended X-ray absorption fine structure analysis revealed a weakening of the interaction between oxygen atom and FeCo-OMPC compared to Pt/C. This effect and high surface area of FeCo-OMPC appear responsible for its significantly high ORR activity.

Considering the anti‐photoaging effect of antioxidant compounds, we investigated the protective capacity of grape peel extract (GPE) and resveratrol on ultraviolet (UV)‐induced skin wrinkle formation. Total phenolic, total anthocyanin, and total flavonoid content in GPE prepared from peel of Campbell Early variety were 23.96 ± 0.09, 3.27 ± 0.40, and 1.24 ± 0.09 mg/g dry weight, respectively. Additionally, trans‐resveratrol and piceid content of the resulting GPE were 117.14 ± 19.97 and 85.23 ± 8.89 µg/g dry weight, respectively. Oral administration of either 2 g GPE or 2 mg resveratrol per kg body weight in mice attenuated UVB‐induced epidermal thickening (the thickness was reduced by about 63% and 55% with GPE and resveratrol consumption prior to exposure to UVB, respectively, compared to only UVB‐treated condition) and had marginally protective effect on wrinkle formation of skin exposed to UVB. As introduction of either GPE or resveratrol induced Nrf2‐dependent antioxidant enzymes including heme oxygenase‐1 (HO‐1) in liver and skin as well as inhibited metalloproteinases, it is highly probable that the extract or resveratrol mitigated UVB‐induced photoaging through activation of Nrf2/HO‐1 signaling pathway. Practical Application This study proved that resveratrol and the extract of grape peel, a common by‐product of grape juice processing, provide effective protection from UV‐induced skin wrinkle formation. Therefore, grape peel extract, which contains an appreciable amount of bioactive compound resveratrol, can be utilized as functional food ingredient for the manufacture of inner beauty products.

Background Integrating the rich information from multi-omics data has been a popular approach to survival prediction and bio-marker identification for several cancer studies. To facilitate the integrative analysis of multiple genomic profiles, several studies have suggested utilizing pathway information rather than using individual genomic profiles. Methods We have recently proposed an integrative directed random walk-based method utilizing pathway information (iDRW) for more robust and effective genomic feature extraction. In this study, we applied iDRW to multiple genomic profiles for two different cancers, and designed a directed gene-gene graph which reflects the interaction between gene expression and copy number data. In the experiments, the performances of the iDRW method and four state-of-the-art pathway-based methods were compared using a survival prediction model which classifies samples into two survival groups. Results The results show that the integrative analysis guided by pathway information not only improves prediction performance, but also provides better biological insights into the top pathways and genes prioritized by the model in both the neuroblastoma and the breast cancer datasets. The pathways and genes selected by the iDRW method were shown to be related to the corresponding cancers. Conclusions In this study, we demonstrated the effectiveness of a directed random walk-based multi-omics data integration method applied to gene expression and copy number data for both breast cancer and neuroblastoma datasets. We revamped a directed gene-gene graph considering the impact of copy number variation on gene expression and redefined the weight initialization and gene-scoring method. The benchmark result for iDRW with four pathway-based methods demonstrated that the iDRW method improved survival prediction performance and jointly identified cancer-related pathways and genes for two different cancer datasets. Reviewers This article was reviewed by Helena Molina-Abril and Marta Hidalgo.

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This paper proposes an online fault diagnosis system for induction motors through the combination of discrete wavelet transform (DWT), feature extraction, genetic algorithm (GA), and neural network (ANN) techniques. The wavelet transform improves the signal-to-noise ratio during a preprocessing. Features are extracted from motor stator current, while reducing data transfers and making online application available. GA is used to select the most significant features from the whole feature database and optimize the ANN structure parameter. Optimized ANN is trained and tested by the selected features of the measurement data of stator current. The combination of advanced techniques reduces the learning time and increases the diagnosis accuracy. The efficiency of the proposed system is demonstrated through motor faults of electrical and mechanical origins on the induction motors. The results of the test indicate that the proposed system is promising for the real-time application.