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1,5-Pentanediol (1,5-PeD) is an important raw material for the preparation of degradable polyesters, polyurethanes and pharmaceutical intermediates. Efficient synthesis of 1,5-PeD from biomass-derived furfuryl alcohol (FFA) by hydrogenation is a green synthetic route instead of using fossil raw material production. Nevertheless, it suffers from great challenges as the various adsorption configurations of FFA on the catalyst surface induce diverse product distributions and low selectivity for 1,5-PeD. Herein, a CuCoAl hydrotalcite catalyst modified by La was fabricated and applied in the hydrogenation of FFA to 1,5-PeD. The results demonstrated that in the catalyst doped with La via deposition–precipitation methods (La/CuCoAl-DP) there appeared a strong Cu–La interaction, and it exhibited superior activity compared with other catalysts. A near 60% yield of 1,5-PeD was achieved under 160 °C, 4 MPa H2 within 2 h. Extensive characterizations including XRD, HRTEM, N2O-TPD and CO2-TPD demonstrated that the doping of La improved markedly the dispersion of Cu and the concentration of strong basic sites. Furthermore, HRTEM and the in situ XPS characterization verified that the addition of La species promoted the formation of a Cu–La interface with a stable Cun+–O–La(OH)3 structure on the catalyst surface. Such Cun+–O–La(OH)3 sites can simultaneously activate the furan ring and the –OH group in FFA with an intermediate six-membered ring transition state, leading to high selective cleavage of the C2–O1 bond in the furan ring to 1,5-PeD. Meanwhile, the DFT calculation results corroborated that the modifying by La species remarkably promoted the C2-end tilted adsorption of FFA on the catalyst surface and enhanced the ability of the catalyst to activate hydrogen. This study provided a new strategy for the high-value utilization of biomass resources and the development of multi-center catalysts. [ABSTRACT FROM AUTHOR]

In this study, the neuroprotective potential of arbutin (100 µmol L−1) pre-treatment and post-treatment against oxygen/ glucose deprivation (OGD) and reoxygenation (R) induced ischemic injury in cultured rat cortical neurons was explored. The OGD (60 min) and reoxygenation (24 h) treatment significantly (p < 0.001) compromised the antioxidant defence in cultured neurons. Subsequently, an increase (p < 0.001) in lipid peroxidation and inflammatory cytokines (tumour necrosis factor-α and nuclear factor kappa-B) declined neuron survival. In pre- and post-condition experiments, treatment with arbutin enhanced both survival (p < 0.01) and integrity (p < 0.05) of cultured neurons. Results showed that arbutin protects (p < 0.05) against peroxidative changes, inflammation, and enhanced the antioxidant activity (e.g., glutathione, superoxide dismutase and catalase) in cultured neurons subjected to OGD/R. It can be inferred that arbutin could protect against ischemic injuries and stroke. The anti-ischemic activity of arbutin can arrest post-stroke damage to the brain.

Correlation clustering problem (CorCP) is a classical clustering problem, which clusters data based on the similarity of data set, and has many applications in interaction networks, cross-lingual link detection, and communication networks, etc. In this paper, we study a practical generalization of the CorCP, called the capacitated correlation clustering problem (the capacitated CorCP), by constructing a labeled complete graph. On this labeled complete graph, each vertex represents a piece of data. If two pieces of data are similar, then the edge between the corresponding vertices is marked by a positive label +. Otherwise, this edge is marked by a negative label -. The objective of the capacitated CorCP is to group some similar data sets into one cluster as far as possible, while satisfying the cluster capacity constraint. To achieve this objective, we shall partition the vertex set of the labeled complete graph into several clusters, each cluster's size subjecting to an upper bound, so as to minimize the number of disagreements. Here the number of disagreements is defined as the total number of the edges with positive labels between clusters and the edges with negative labels within clusters. Different with the previous algorithm in [18], which subjects to the constraint on the cluster size by a penalty measure, we design an algorithm for the capacitated CorCP to directly output a feasible solution by iteratively constructing clusters based on a preset threshold. Through carefully setting the threshold and sophisticatedly analyzing, our algorithm is proved to have an improved approximation ratio of 5.37. In addition, we also conduct a series of numerical experiments to demonstrate the effectiveness of our algorithm. [ABSTRACT FROM AUTHOR]