Transport or Store? Synthesizing Flow-based Microfluidic Biochips using Distributed Channel Storage

Flow-based microfluidic biochips have attracted much atten- tion in the EDA community due to their miniaturized size and execution efficiency. Previous research, however, still follows the traditional computing model with a dedicated storage unit, which actually becomes a bottleneck of the performance of bio- chips. In this paper, we propose the first architectural synthe- sis framework considering distributed storage constructed tem- porarily from transportation channels to cache fluid samples. Since distributed storage can be accessed more efficiently than a dedicated storage unit and channels can switch between the roles of transportation and storage easily, biochips with this dis- tributed computing architecture can achieve a higher execution efficiency even with fewer resources. Experimental results con- firm that the execution efficiency of a bioassay can be improved by up to 28% while the number of valves in the biochip can be reduced effectively.Comment: ACM/IEEE Design Automation Conference (DAC), June 201

Heteroaromatic organic compound with conjugated multi-carbonyl as cathode material for rechargeable lithium batteries

The heteroaromatic organic compound, N,N\u27-diphenyl-1,4,5,8-naphthalenetetra-carboxylic diimide (DP-NTCDI-250) as the cathode material of lithium batteries is prepared through a simple one-pot N-acylation reaction of 1,4,5,8-naphthalenetetra-carboxylic dianhydride (NTCDA) with phenylamine (PA) in DMF solution followed by heat treatment in 250 °C. The as prepared sample is characterized by the combination of elemental analysis, NMR, FT-IR, TGA, XRD, SEM and TEM. The electrochemical measurements show that DP-NTCDI-250 can deliver an initial discharge capacity of 170 mAh g-1 at the current density of 25 mA g-1. The capacity of 119 mAh g-1 can be retained after 100 cycles. Even at the high current density of 500 mA g-1, its capacity still reaches 105 mAh g-1, indicating its high rate capability. Therefore, the as-prepared DP-NTCDI-250 could be a promising candidate as low cost cathode materials for lithium batteries

Celecoxib ameliorates diabetic sarcopenia by inhibiting inflammation, stress response, mitochondrial dysfunction, and subsequent activation of the protein degradation systems

Aim: Diabetic sarcopenia leads to disability and seriously affects the quality of life. Currently, there are no effective therapeutic strategies for diabetic sarcopenia. Our previous studies have shown that inflammation plays a critical role in skeletal muscle atrophy. Interestingly, the connection between chronic inflammation and diabetic complications has been revealed. However, the effects of non-steroidal anti-inflammatory drug celecoxib on diabetic sarcopenia remains unclear.Materials and Methods: The streptozotocin (streptozotocin)-induced diabetic sarcopenia model was established. Rotarod test and grip strength test were used to assess skeletal muscle function. Hematoxylin and eosin and immunofluorescence staining were performed to evaluate inflammatory infiltration and the morphology of motor endplates in skeletal muscles. Succinate dehydrogenase (SDH) staining was used to determine the number of succinate dehydrogenase-positive muscle fibers. Dihydroethidium staining was performed to assess the levels of reactive oxygen species (ROS). Western blot was used to measure the levels of proteins involved in inflammation, oxidative stress, endoplasmic reticulum stress, ubiquitination, and autophagic-lysosomal pathway. Transmission electron microscopy was used to evaluate mitophagy.Results: Celecoxib significantly ameliorated skeletal muscle atrophy, improving skeletal muscle function and preserving motor endplates in diabetic mice. Celecoxib also decreased infiltration of inflammatory cell, reduced the levels of IL-6 and TNF-α, and suppressed the activation of NF-κB, Stat3, and NLRP3 inflammasome pathways in diabetic skeletal muscles. Celecoxib decreased reactive oxygen species levels, downregulated the levels of Nox2 and Nox4, upregulated the levels of GPX1 and Nrf2, and further suppressed endoplasmic reticulum stress by inhibiting the activation of the Perk-EIF-2α-ATF4-Chop in diabetic skeletal muscles. Celecoxib also inhibited the levels of Foxo3a, Fbx32 and MuRF1 in the ubiquitin-proteasome system, as well as the levels of BNIP3, Beclin1, ATG7, and LC3Ⅱ in the autophagic-lysosomal system, and celecoxib protected mitochondria and promoted mitochondrial biogenesis by elevating the levels of SIRT1 and PGC1-α, increased the number of SDH-positive fibers in diabetic skeletal muscles.Conclusion: Celecoxib improved diabetic sarcopenia by inhibiting inflammation, oxidative stress, endoplasmic reticulum stress, and protecting mitochondria, and subsequently suppressing proteolytic systems. Our study provides evidences for the molecular mechanism and treatment of diabetic sarcopenia, and broaden the way for the new use of celecoxib in diabetic sarcopenia

Development of a chimeric Zika vaccine using a licensed live-attenuated flavivirus vaccine as backbone

Given the recent Zika virus (ZIKV) epidemic, development of an effective vaccine is of high importance. Here, the authors use a licensed live-attenuated flavivirus vaccine backbone to develop a ZIKV vaccine and determine immunogenicity, safety and protection profiles in different animal models

Multivariate intrinsic random functions for cokriging

In multivariate geostatistics, suppose that we relax the usual second-orderstationarity assumptions and assume that the component processes are intrinsic random functions of general orders. In this article, we introduce a generalized crosscovariance function to describe the spatial cross-dependencies in multivariate intrinsic random functions. A nonparametric method is then proposed for its estimation. Based on this class of generalized cross-covariance functions, we give cokriging equations for multivariate intrinsic random functions in the presence of measurement error. A simulation is presented that demonstrates the accuracy of the proposed nonparametric estimation method. Finally, an application is given to a dataset of plutonium and americium concentrations collected from a region of the Nevada Test Site used for atomic-bomb testing. International Association for Mathematical Geosciences 2009

Evaluation and Parameter Optimization of Monthly Net Long-Wave Radiation Climatology Methods in China

Based on surface radiation balance data and meteorological observations at 19 radiation stations in China from 1993 to 2012, we assessed the applicability of seven empirical formulas for the estimation of monthly surface net long-wave radiation (Rnl). We then established a revised method applicable to China by re-fitting the formula using new observational data. The iterative solution method and the multivariate regression analysis method with the minimum root mean square error (RMSE) were used as the objective functions in the revised method. Meanwhile, the accuracy of the CERES (Clouds and the Earth’s Radiant Energy System) estimated Rnl was also evaluated. Results show that monthly Rnl over China was underestimated by the seven formulas and the CERES data. The Tong Hongliang formula with lowest errors was the best among the seven formulas for estimating Rnl over China as a whole, followed by the Penman and the Deng Genyun formulas. The estimated Rnl based on the CERES data also showed relatively higher precision in accordance with the three formulas mentioned above. The FAO56-PM formula (Penman–Monteith formula recommended in the No. 56 report of the Food and Agriculture Organization) without calibration was not applicable to China due to its low accuracy. For individual stations, the Deng Genyun formula was the most accurate in the eastern plain area, while the Tong Hongliang formula was suitable for the plateau. Regional formulas were established based on the geographical distribution of water vapor pressure and elevation over China. The revised national and regional formulas were more accurate than the seven original formulas and the CERES data. Furthermore, the regional formulas produced smaller errors than the national formula at most of the stations. The regional formulas were clearly more accurate than the Deng Genyun formula at stations in Northwestern China and on the Tibetan Plateau. They were also more accurate than the Tong Hongliang formula at the stations located in the eastern area. Therefore, the regional formulas developed in this study are recommended as the standard climatology formulas to calculate monthly Rnl over China