Upregulation of p75NTR by Histone Deacetylase Inhibitors Sensitizes Human Neuroblastoma Cells to Targeted Immunotoxin-Induced Apoptosis

Histone deacetylase (HDAC) inhibitors are novel chemotherapy agents with potential utility in the treatment of neuroblastoma, the most frequent solid tumor of childhood. Previous studies have shown that the exposure of human neuroblastoma cells to some HDAC inhibitors enhanced the expression of the common neurotrophin receptor p75NTR. In the present study we investigated whether the upregulation of p75NTR could be exploited to render neuroblastoma cells susceptible to the cytotoxic action of an anti-p75NTR antibody conjugated to the toxin saporin-S6 (p75IgG-Sap). We found that two well-characterized HDAC inhibitors, valproic acid (VPA) and entinostat, were able to induce a strong expression of p75NTR in different human neuroblastoma cell lines but not in other cells, with entinostat, displaying a greater efficacy than VPA. Cell pretreatment with entinostat enhanced p75NTR internalization and intracellular saporin-S6 delivery following p75IgG-Sap exposure. The addition of p75IgG-Sap had no effect on vehicle-pretreated cells but potentiated the apoptotic cell death that was induced by entinostat. In three-dimensional neuroblastoma cell cultures, the subsequent treatment with p75IgG-Sap enhanced the inhibition of spheroid growth and the impairment of cell viability that was produced by entinostat. In athymic mice bearing neuroblastoma xenografts, chronic treatment with entinostat increased the expression of p75NTR in tumors but not in liver, kidney, heart, and cerebellum. The administration of p75IgG-Sap induced apoptosis only in tumors of mice that were pretreated with entinostat. These findings define a novel experimental strategy to selectively eliminate neuroblastoma cells based on the sequential treatment with entinostat and a toxin-conjugated anti-p75NTR antibody.     

Coupling and thermal integration of a solid oxide fuel cell with a magnesium hydride tank

A solid oxide fuel cell (SOFC) based combined heat and power (CHP) system in the power range of 1 kWe fed by pure hydrogen stored in a MgH₂ tank thermally integrated with the SOFC is presented. Different system configurations were first simulated to compare the system performances in each case. An experimental setup specially designed to test the thermal integration of a magnesium hydride tank with a 1 kWe SOFC stack is fully described. The difficulties encountered during the coupling tests are useful to understand how to solve these technical issues.     

Phenolic Metabolites in Leaves of the Invasive Shrub, Lonicera maackii, and Their Potential Phytotoxic and Anti-Herbivore Effects

Lonicera maackii is an invasive shrub in North America for which allelopathic effects toward other plants or herbivores have been suspected. We characterized the major phenolic metabolites present in methanol extracts of L. maackii leaves. In addition, we examined the effects of methanol–water extracts of L. maackii leaves on seed germination of a target plant species and on feeding preference and growth rate of a generalist insect herbivore. A total of 13 individual major and minor compounds were detected in crude leaf extracts by high-performance liquid chromatography coupled to electronspray ionization-tandem mass spectrometry (ESI-MS/MS). Extracts were dominated by two major flavones, apigenin and luteolin, and their glucoside derivatives, apigenin-7-glucoside and luteolin-7-glucoside. Quantities of these compounds, along with chlorogenic acid, varied between two sampling points. Leaf extracts that contained these compounds were inhibitory to seed germination of Arabidopsis thaliana. In addition, treatment of artificial diet with leaf extracts deterred feeding of the generalist herbivore, Spodoptera exigua, in choice experiments but had no effect on growth rate in short-term no-choice bioassays. Purified apigenin tended to deter feeding by S. exigua and inhibited seed germination of A. thaliana. We conclude that leaves of L. maackii contain phenolic compounds, including apigenin and chlorogenic acid, capable of having biological effects on other plants and insects.     

Rosiglitazone,a PPAR-γ Agonist,Fails to Attenuate CLA-Induced Milk Fat Depression and Hepatic Lipid Accumulation in Lactating Mice

Our objective was to investigate the combination of rosiglitazone (ROSI) and conjugated linoleic acid (CLA) on mammary and hepatic lipogenesis in lactating C57Bl/6 J mice. Twenty-four lactating mice were randomly assigned to one of four treatments applied from postpartum day 6 to day 10. Treatments included: (1) control diet, (2) control plus 1.5 % dietary CLA (CLA) substituted for soybean oil, (3) control plus daily intra-peritoneal (IP) rosiglitazone injections (10 mg/kg body weight) (ROSI), and (4) CLA plus ROSI (CLA-ROSI). Dam food intake and milk fat concentration were depressed with CLA. However, no effects were observed with ROSI. The CLA-induced milk fat depression was due to reduced expression for mammary lipogenic genes involved in de-novo fatty acid (FA) synthesis, FA uptake and desaturation, and triacyglycerol synthesis. Liver weight (g/100 g body weight) was increased by CLA due to an increase in lipid accumulation triggering a compensatory reduction in mRNA abundance of hepatic lipogenic enzymes, including acetyl-CoA carboxylase I and stearoyl-CoA desaturase I. On the contrary, no effects were observed with ROSI on hepatic and mammary lipogenic gene and enzyme expression. Overall, feeding CLA to lactating mice induced milk fat depression and increased hepatic lipid accumulation, probably due to the presence of trans-10, cis-12 CLA isomer, while ROSI failed to significantly attenuate both hepatic steatosis and reduction in milk fat content.     

Rapid FT-NIR Analysis of Edible Oils for Total SFA, MUFA, PUFA, and Trans FA with Comparison to GC

Declarations of the total content of trans fatty acids (FA) and saturated FA (SFA) are mandatory on food labels in the US and Canada. Gas chromatography (GC) has been the method of choice for the determination of FA composition. However, GC is time consuming and requires conversion of fats and oils to their FA methyl esters. In the present study, a recently published Fourier transform near-infrared (FT-NIR) spectroscopic procedure was applied to the rapid (<5 min) determination of total SFA, monounsaturated FA (MUFA), polyunsaturated FA (PUFA), and trans FA contents of 30 commercially available edible fats and oils. Good agreement was obtained between the GC and FT-NIR methods for the determination of total SFA, MUFA, and PUFA contents. Differences between the two methods were apparent for the determination of trans fat at trans fat levels <2 % of total fat. The analytical determinations of total SFA, MUFA, and PUFA contents for many of the oils examined differed from the respective values declared on the product labels. Our findings demonstrate that the FT-NIR procedure serves as a suitable alternative method for the rapid determination of total SFA, MUFA, PUFA and trans FA contents of neat vegetable oils.     

Parsimonious flooding in dynamic graphs

An edge-Markovian process with birth-rate p and death-rate q generates infinite sequences of graphs (G ₀, G ₁, G ₂,…) with the same node set [n] such that G _t is obtained from G _t-1 as follows: if e ? E(G_t-1){e\notin E(G_{t-1})} then e ? E(G_t){e\in E(G_{t})} with probability p, and if e ? E(G_t-1){e\in E(G_{t-1})} then e ? E(G_t){e\notin E(G_{t})} with probability q. In this paper, we establish tight bounds on the complexity of flooding in edge-Markovian graphs, where flooding is the basic mechanism in which every node becoming aware of an information at step t forwards this information to all its neighbors at all forthcoming steps t′ > t. These bounds complete previous results obtained by Clementi et al. Moreover, we also show that flooding in dynamic graphs can be implemented in a parsimonious manner, so that to save bandwidth, yet preserving efficiency in term of simplicity and completion time. For a positive integer k, we say that the flooding protocol is k-active if each node forwards an information only during the k time steps immediately following the step at which the node receives that information for the first time. We define the reachability threshold for the flooding protocol as the smallest integer k such that, for any source s ? [n]{s\in [n]} , the k-active flooding protocol from s completes (i.e., reaches all nodes), and we establish tight bounds for this parameter. We show that, for a large spectrum of parameters p and q, the reachability threshold is by several orders of magnitude smaller than the flooding time. In particular, we show that it is even constant whenever the ratio p/(p + q) exceeds log n/n. Moreover, we also show that being active for a number of steps equal to the reachability threshold (up to a multiplicative constant) allows the flooding protocol to complete in optimal time, i.e., in asymptotically the same number of steps as when being perpetually active. These results demonstrate that flooding can be implemented in a practical and efficient manner in dynamic graphs. The main ingredient in the proofs of our results is a reduction lemma enabling to overcome the time dependencies in edge-Markovian dynamic graphs.     

Flooding in dynamic graphs with arbitrary degree sequence

This paper addresses the flooding problem in dynamic graphs, where flooding is the basic mechanism in which every node becoming aware of a piece of information at step t$t$ forwards this information to all its neighbors at all forthcoming steps t^′>t$t^{\prime }>t$. We show that a technique developed in a previous paper, for analyzing flooding in a Markovian sequence of Erdös–Rényi graphs, is robust enough to be used also in different contexts. We establish this fact by analyzing flooding in a sequence of graphs drawn independently at random according to a model of random graphs with given expected degree sequence. In the prominent case of power-law degree distributions, we prove that flooding takes almost surely O(logn)$O(logn)$ steps even if, almost surely, none of the graphs in the sequence is connected. In the general case of graphs with an arbitrary degree sequence, we prove several upper bounds on the flooding time, which depend on specific properties of the degree sequence.     

Platform-based mixed signal design: Optimizing a high-performance pipelined ADC

We apply Platform-Based Design (PBD) to the power optimization of a 14 bit, 80 MS/s pipelined Analog-to-Digital Converter (ADC) in a mixed signal formulation. A platform is a library of components and interconnects, each characterized with a set of behavioral, performance and composition models, that is used to raise the level of abstraction to enable system-level design. PBD is a meet-in-the-middle methodology that consists of two phases. The bottom-up phase generates a set of platform libraries that are exploited in the system hierarchy. The top-down phase allows exploring feasible solutions within the platform libraries and selecting the optimum implementation. To evaluate the cost of each implementation, the behavioral models available through platform abstraction are used both for digital and analog components. We provide an example of the use of the methodology and its features for analog circuits by modeling two amplifiers with different topologies as analog components, showing details of the analog characterization process. Then, we create a mixed signal platform library as a combination of an analog and a digital platform (bottom-up phase). The top-down phase performs optimization across the analog/digital boundary to minimize power consumption constrained to given noise and linearity requirements. Simulation results show that interesting power saving can be achieved, as much as 64% compared with an original hand-optimized ADC. Pierluigi Nuzzo received the Laurea degree in electrical engineering from the University of Pisa, Italy, in 2003, and the Diploma from the Scuola Superiore Sant’Anna, Pisa, in 2004, both with honors. Since 2004, he has been with the Department of Information Engineering, University of Pisa, where he is currently working toward the Ph.D. degree in electrical engineering and computer science. During summer 2002 he was with the Fermi National Accelerator Laboratory, Batavia, IL as a student intern working on ASIC testing. From August 2004 to February 2005 he was with IMEC, Leuven, Belgium, as a visiting scholar, working on low power A/D converter design for ultra-wide band applications. His research interests include high speed, low power analog and mixed-signal circuits in CMOS technology, digital calibration of ADCs, system level mixed-signal design and design methodologies. Mr. Nuzzo received first place in the operational category and best overall submission in the 2006 DAC/ISSCC student design competition. Fernando De Bernardinis received the Laurea degree in Electrical Engineering from the University of Pisa, Italy, in 1996 and the M.S. degree and Ph.D. degree from the University of California at Berkeley in 2001 and 2005, respectively. Between 1992 and 1996 he was at the Scuola Superiore S. Anna in Pisa. From 1997 to 1998 he collaborated with the PARADES research center in Rome. During the summers 1999 and 2000 he was at the ST Berkeley labs, working on wireless embedded system design. From 2000 to 2006 he was assistant professor at the Department of Information Engineering at the University of Pisa, Italy. His research interests include mixed-signal design, analog CAD, system level analog design and design methodologies. In 2006 he has joined Marvell Semiconductors, Pavia, Italy, where he works on mixed-signal and RF system design. Alberto Sangiovanni Vincentelli holds the Edgar L. and Harold H. Buttner Chair of Electrical Engineering and Computer Sciences at the University of California at Berkeley. He has been on the Faculty since 1976. He obtained an electrical engineering and computer science degree (“Dottore in Ingegneria”) summa cum laude from the Politecnico di Milano, Milano, Italy in 1971. In 1980–1981, he spent a year as a Visiting Scientist at the Mathematical Sciences Department of the IBM T.J. Watson Research Center. In 1987, he was Visiting Professor at MIT. He has held a number of visiting professor positions at Italian Universities, including Politecnico di Torino, Universita’ di Roma La Sapienza, Universita’ di Roma Tor Vergata, Universita’ di Pavia, Universita’ di Pisa, Scuola Sant’Anna. He was a co-founder of Cadence and Synopsys, the two leading companies in the area of Electronic Design Automation. He is the Chief Technology Adviser of Cadence. He is a member of the Board of Directors of Cadence and the Chair of the Technology Committee, UPEK, a company he helped spinning off from ST Microelectronics, where he is the Chair of its Nominating and Governance Committee and a member of the Audit Committee, Sonics, where he serves as the Chair of the Nominating and Governance Committee, Gradient, where he is a member of the Compensation committee, Accent, an ST Microelectronics-Cadence joint venture he helped founding, and Value Partners. He is the Technology Advisor to the President of the Abruzzo Region. He is a member of the HP Strategic Technology Advisory Board, of the Science and Technology Advisory Board of General Motors and of the Scientific Council of the Tronchetti Provera foundation. He consulted for many companies including Bell Labs, IBM, Intel, United Technology, COMAU, Magneti Marelli, Pirelli, BMW, Daimler-Chrysler, Fujitsu, Kawasaki Steel, Sony, ST and Hitachi. He was an advisor to the Singapore Government for microelectronics and new ventures. He has consulted as Technology Partner for Greylock Ventures and for Vertex Investment. He served as witness in US Congressional investigations on competitiveness of the US economy. He is the founder and Scientific Director of the Project on Advanced Research on Architectures and Design of Electronic Systems (PARADES), a European Group of Economic Interest supported by Cadence, Magneti-Marelli and ST Microelectronics. He is a member of the Advisory Board of the Lester Center for Innovation of the Haas School of Business and of the Center for Western European Studies and a member of the Berkeley Roundtable of the International Economy (BRIE). He is a member of the High-Level Group and of the Steering Committee of the EU Artemis Technology Platform. In 1981, he received the Distinguished Teaching Award of the University of California. He received the worldwide 1995 Graduate Teaching Award of the IEEE (a Technical Field award for “inspirational teaching of graduate students”). In 2002, he was the recipient of the Aristotle Award of the Semiconductor Research Corporation. He has received numerous research awards including the Guillemin-Cauer Award (1982–1983), the Darlington Award (1987–1988) of the IEEE for the best paper bridging theory and applications, and two awards for the best paper published in the Transactions on CAS and CAD, three best paper awards and one best presentation awards at the Design Automation Conference. In 2001, he was given the prestigious Kaufman Award of the Electronic Design Automation Council for pioneering contributions to EDA. He is an author of over 700 papers and 15 books in the area of design tools and methodologies, large-scale systems, embedded controllers, hybrid systems and innovation. Dr. Sangiovanni-Vincentelli has been a Fellow of the IEEE since 1982 and a Member of the National Academy of Engineering, the highest honor bestowed upon a US engineer, since 1998.