Implications of maternal nutrient restriction in transgenerational programming of hypertension and endothelial dysfunction across F1-F3 offspring

Aims: An extensive variety of prenatal insults are associated with an increased incidence of metabolic and cardiovascular disorders in adult life. We previously demonstrated that maternal global nutrient restriction during pregnancy leads to increased blood pressure and endothelial dysfunction in the adult offspring. This study aimed to assess whether prenatal exposure to nutritional insult has transgenerational effects in F-2 and F-3 offspring. Main methods: For this, female Wistar rats were randomly divided into two groups on day 1 of pregnancy: a control group fed standard chow ad libitum and a restricted group fed 50% of the ad libitum intake throughout gestation. At delivery, all animals were fed a standard laboratory chow diet. At 11 weeks of age, one female and one male from each restricted litter were randomly selected and mated with rats from another restricted litters in order to generate the F-2 offspring. The same procedure produced F-3 generation. Similarly, the rats in the control group were bred for each generation. Key Findings: Our findings show that the deleterious effects of maternal nutrient restriction to which the F-0 mothers were exposed may not be limited to the male first generation. In fact, we found that elevated blood pressure, an impaired vasodilatory response to acetylcholine and alterations in NO production were all transferred to the subsequent males from F-2 and F-3 generations. Significance: Our data show that global nutrient restriction during pregnancy results in a specific phenotype that can be passed transgenerationally to a second and third generation. (c) 2012 Elsevier Inc. All rights reserved.

An integer linear programming approach for bilinear integer programming

We introduce a new Integer Linear Programming (ILP) approach for solving Integer Programming (IP) problems with bilinear objectives and linear constraints. The approach relies on a series of ILP approximations of the bilinear P. We compare this approach with standard linearization techniques on random instances and a set of real-world product bundling problems. (C) 2011 Elsevier B.V. All rights reserved.

LALP: a language to program custom FPGA-based acceleration engines

Field-Programmable Gate Arrays (FPGAs) are becoming increasingly important in embedded and high-performance computing systems. They allow performance levels close to the ones obtained with Application-Specific Integrated Circuits, while still keeping design and implementation flexibility. However, to efficiently program FPGAs, one needs the expertise of hardware developers in order to master hardware description languages (HDLs) such as VHDL or Verilog. Attempts to furnish a high-level compilation flow (e.g., from C programs) still have to address open issues before broader efficient results can be obtained. Bearing in mind an FPGA available resources, it has been developed LALP (Language for Aggressive Loop Pipelining), a novel language to program FPGA-based accelerators, and its compilation framework, including mapping capabilities. The main ideas behind LALP are to provide a higher abstraction level than HDLs, to exploit the intrinsic parallelism of hardware resources, and to allow the programmer to control execution stages whenever the compiler techniques are unable to generate efficient implementations. Those features are particularly useful to implement loop pipelining, a well regarded technique used to accelerate computations in several application domains. This paper describes LALP, and shows how it can be used to achieve high-performance computing solutions.