Genetic Deletion of Rheb1 in the Brain Reduces Food Intake and Causes Hypoglycemia with Altered Peripheral Metabolism

Excessive food/energy intake is linked to obesity and metabolic disorders, such as diabetes. The hypothalamus in the brain plays a critical role in the control of food intake and peripheral metabolism. The signaling pathways in hypothalamic neurons that regulate food intake and peripheral metabolism need to be better understood for developing pharmacological interventions to manage eating behavior and obesity. Mammalian target of rapamycin (mTOR), a serine/threonine kinase, is a master regulator of cellular metabolism in different cell types. Pharmacological manipulations of mTOR complex 1 (mTORC1) activity in hypothalamic neurons alter food intake and body weight. Our previous study identified Rheb1 (Ras homolog enriched in brain 1) as an essential activator of mTORC1 activity in the brain. Here we examine whether central Rheb1 regulates food intake and peripheral metabolism through mTORC1 signaling. We find that genetic deletion of Rheb1 in the brain causes a reduction in mTORC1 activity and impairs normal food intake. As a result, Rheb1 knockout mice exhibit hypoglycemia and increased lipid mobilization in adipose tissue and ketogenesis in the liver. Our work highlights the importance of central Rheb1 signaling in euglycemia and energy homeostasis in animals.     

Analysis of polychlorinated biphenyls (PCBs), heavy metals and omega‐3 fatty acids in commercially available Korean functional fish oil supplements

In this study, the levels of polychlorinated biphenyls (PCBs), heavy metals and omega‐3 polyunsaturated fatty acids (docosahexaenoic acid; DHA and eicosapentaenoic acid; EPA), as well as chemical indices including acid and peroxide values were determined among twenty‐four commercially available functional fish oil supplements. The sum of indicator PCB congeners (congeners 28, 52, 101, 118, 138, 153 and 180) was below the limit of quantification of 0.043 mg kg^?1. Metallic compounds (Cd, Pb, Hg and As) were not detected in all fish oil supplement samples. The relative percentages of EPA and DHA in fish oil supplements ranged from 25% to 80%. The acid values ranged from 0.1 to 1.4 mg KOH per g oil, and peroxide values ranged from 2.7 to 28.8 meq per kg oil. All fish oil supplement samples tested in current study met the safety standard for fish oil supplements set by Korean government as well as International standard.     

Conjugated polymers with regularly spaced m‐phenylene units and post‐polymerization modification to yield stimuli‐responsive materials

Two π‐conjugated polymers featuring main‐chain m‐phenylene linkers as well as iodo substituents were initially prepared. The presence of the iodo functionality allowed for the preparation of six additional polymers from the initial two iodo‐substituted polymers via facile post‐polymerization modification using Sonogashira‐type coupling chemistry. The post‐polymerization modification led to crosslinking, to the incorporation of a pyridyl‐bearing functionality for potential use as a ligand for transition metals or to the introduction of a ferrocenyl substituent as a possible redox‐active unit. The m‐phenylene units were incorporated into the polymer main‐chain structure in order to periodically disrupt conjugation, thereby allowing for more uniformity in the effective conjugation length and thus in absorption and emission profiles. The thermal stability and photophysical properties of all eight polymers, as well as the stimuli‐responsiveness of relevant materials to nitroaromatics and metal ions, are reported. © 2015 Society of Chemical Industry     

Remote-sensing image fusion based on curvelets and ICA

Improving the quality of pan-sharpened multispectral (MS) bands is the main aim of the recent research on pan-sharpening. In this article, we present a novel image fusion method based on combining the curvelet transform and independent component analysis (ICA). The idea is to map the MS bands onto a statistically independent domain to determine the intensity component, which contains the common information of the MS bands, and then to pan-sharpen it using curvelets and a modified adaptive fusion rule. The proposed method is evaluated by visual and statistical analyses and compared with the curvelet (CVT)-based method using a context-based decision model, the CVT-based method using the Dempster–Shafer evidence theory, the improved ICA method, and the combined adaptive principle component analysis (PCA)–Contourlet method. The experimental results using QuickBird and WorldView-2 data show that the proposed method effectively reduces the spectral distortion while injecting spatial details into the fused bands as much as possible.     

A liquid-state high sensitive accelerometer based on a micro-scale liquid marble

Microsystem Technologies - In this paper, the dynamic behavior of a high sensitive liquid marble based accelerometer in the presence of the external acceleration field is investigated. The...     

An Efficient Programming Skeleton for Clusters of Multi-Core Processors

This paper proposes a divide and conquer skeleton which aids parallel system programmers by (1) reducing programming complexity, (2) shortening programming time, and (3) enhancing code efficiency. To do this, the proposed skeleton exploits three mechanisms of (1) work-stealing, and (2) communication/computation overlapping, and (3) architectural awareness in the proposed divide and conquer skeleton. Using the work-stealing mechanism, when a processing element reaches a low-load condition, the processing core fetches a new job from the waiting queue of other cores. The second mechanism uses special threads to enable the proposed skeleton to overlapping computations with communications. The third mechanism considers the architectural parameters of the host system e.g., size of L1 cache, network bandwidth, network latency to maximally match a divide and conquer problem with the proposed skeleton. To evaluate the proposed skeleton, three benchmarks of merge sort, fast Fourier transform, and standard matrix multiplication are developed by the proposed skeleton as well as customized programming. Experiments are done in both simulation and real implementation environments. The set of six codes are simulated using COTSon simulator and also implemented on 28 dual-core real system. Obtained results from simulations showed an average of 12.6% speed-up of the proposed skeleton as compared to the customized programming; obtained speed-up in real environment is 9.6%. Furthermore, programming aided by the proposed skeleton, is at least 70% faster than custom programming while this difference increases as the program volume increases.     

Photochemically Activated Notch Signaling Hydrogel Preferentially Differentiates Human Derived Hepatoblasts to Cholangiocytes

Cholangiocytes form an intricate network of bile ducts to enable proper liver function; yet, recapitulating human stem cell differentiation to cholangiocytes in vitro requires Notch signaling and soluble ligands do not activate the Notch pathway. To overcome these limitations, jagged1 is immobilized on a chemically defined hyaluronan to specifically differentiate human embryonic stem cell-derived hepatoblasts to cholangiocytes. Hepatoblasts cultured on the jagged1-hydrogels upregulate Notch target genes and express key cholangiocyte markers including cystic fibrosis transmembrane conductance regulator. Moreover, cholangiocytes adopt morphological changes that resemble liver biliary structures. To emulate natural biliary system development, a new strategy is developed to achieve spatiotemporal control over the Jagged1–Notch2 interaction: jagged1 is first caged with a photocleavable streptavidin and then it is uncaged photochemically to restore the biological function of Jagged1, which is confirmed with Notch2 activation in a fluorescent reporter cell line. Moreover, the differentiation of human embryonic stem cell-derived hepatoblasts to cholangiocytes is temporally controlled with photochemical uncaging of this streptavidin-Jagged1-immobilized hyaluronan hydrogel. This strategy defines a framework to control protein signaling in time and space and specifically for Notch signaling for ultimate use in regenerative medicine strategies of the liver.     

Copolymer-Templated Nickel Oxide for High-Efficiency Mesoscopic Perovskite Solar Cells in Inverted Architecture

Despite the outstanding role of mesoscopic structures on the efficiency and stability of perovskite solar cells (PSCs) in the regular (n–i–p) architecture, mesoscopic PSCs in inverted (p–i–n) architecture have rarely been reported. Herein, an efficient and stable mesoscopic NiO_x (mp-NiO_x) scaffold formed via a simple and low-cost triblock copolymer template-assisted strategy is employed, and this mp-NiO_x film is utilized as a hole transport layer (HTL) in PSCs, for the first time. Promisingly, this approach allows the fabrication of homogenous, crack-free, and robust 150 nm thick mp-NiO_x HTLs through a facile chemical approach. Such a high-quality templated mp-NiO_x structure promotes the growth of the perovskite film yielding better surface coverage and enlarged grains. These desired structural and morphological features effectively translate into improved charge extraction, accelerated charge transportation, and suppressed trap-assisted recombination. Ultimately, a considerable efficiency of 20.2% is achieved with negligible hysteresis which is among the highest efficiencies for mp-NiO_x based inverted PSCs so far. Moreover, mesoscopic devices indicate higher long-term stability under ambient conditions compared to planar devices. Overall, these results may set new benchmarks in terms of performance for mesoscopic inverted PSCs employing templated mp-NiO_x films as highly efficient, stable, and easy fabricated HTLs.     

Sign prediction in sparse social networks using clustering and collaborative filtering

Today, social networks have created a wide variety of relationships between users. Friendships on Facebook and trust in the Epinions network are examples of these relationships. Most social media research has often focused on positive interpersonal relationships, such as friendships. However, in many real-world applications, there are also networks of negative relationships whose communication between users is either distrustful or hostile in nature. Such networks are called signed networks. In this work, sign prediction is made based on existing links between nodes. However, in real signed networks, links between nodes are usually sparse and sometimes absent. Therefore, existing methods are not appropriate to address the challenges of accurate sign prediction. To address the sparsity problem, this work aims to propose a method to predict the sign of positive and negative links based on clustering and collaborative filtering methods. Network clustering is done in such a way that the number of negative links between the clusters and the number of positive links within the clusters are as large as possible. As a result, the clusters are as close as possible to social balance. The main contribution of this work is using clustering and collaborative filtering methods, as well as proposing a new similarity criterion, to overcome the data sparseness problem and predict the unknown sign of links. Evaluations on the Epinions network have shown that the prediction accuracy of the proposed method has improved by 8% compared to previous studies.