Disaggregating non-volatile memory for throughput-oriented genomics workloads

Massive exploitation of next-generation sequencing technologies requires dealing with both: huge amounts of data and complex bioinformatics pipelines. Computing architectures have evolved to deal with these problems, enabling approaches that were unfeasible years ago: accelerators and Non-Volatile Memories (NVM) are becoming widely used to enhance the most demanding workloads. However, bioinformatics workloads are usually part of bigger pipelines with different and dynamic needs in terms of resources. The introduction of Software Defined Infrastructures (SDI) for data centers provides roots to dramatically increase the efficiency in the management of infrastructures. SDI enables new ways to structure hardware resources through disaggregation, and provides new hardware composability and sharing mechanisms to deploy workloads in more flexible ways. In this paper we study a state-of-the-art genomics application, SMUFIN, aiming to address the challenges of future HPC facilities.This work is partially supported by the European Research Council (ERC) under the EU Horizon 2020 programme (GA 639595), the Spanish Ministry of Economy, Industry and Competitivity (TIN2015-65316-P) and the Generalitat de Catalunya (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

Evaluating the role of intestinal transporters in fruit juice-drug interactions

Fruit juice-drug interactions (FJDIs) involving non-metabolized oral medications result in decreased drug exposure that may lead to reduced therapeutic efficacy. The effect is thought to be mediated by inhibition of the intestinal drug transporters organic anion transporting polypeptide 1A2 and 2B1 (OATP1A2 and OATP2B1) by fruit juice constituents, however the exact mechanisms remain controversial. We tested the hypothesis that fruit juices limit the absorption of fexofenadine through interactions with specific intestinal transporters. In vitro transport and fruit juice inhibition studies using fexofenadine, a medication involved in FJDIs, revealed that in addition to previously implicated transporters, organic cation transporter 1 (OCT1) and organic solute transporter alpha/beta (OSTα/β) are potential novel targets of fruit juice components. Pharmacokinetic interaction studies in wild-type and mOatp2b1 knockout mice demonstrated that mOatp2b1 is not involved in fexofenadine absorption or FJDIs in vivo. These findings provide new insights into the mechanism of FJDIs

Contribution of an alveolar cell of origin to the high-grade malignant phenotype of pregnancy-associated breast cancer.

Pregnancy-associated breast cancers (PABCs) are tumors diagnosed during pregnancy or up to 5 years following parturition, and are usually high-grade, connective tissue-rich, and estrogen receptor (ER)/progesterone receptor-negative. Little is known about the cellular origin of PABCs or the mechanisms by which PABCs are initiated. Using the RCAS retrovirus to deliver the ErbB2 oncogene into the mammary epithelium of our previously reported MMTV-tva transgenic mice, we detected high-grade, poorly differentiated, stroma-rich and ER-negative tumors during pregnancy and lactation. These high-grade and stroma-rich tumors were less frequent in involuted mice or in age-matched nulliparous mice. More importantly, by generating a WAP-tva transgenic line for expression of ErbB2 selectively in WAP(+) mammary alveolar cells, we found that tumors had similar morphological phenotypes (high grade, poorly differentiated, stroma-rich and ER-negative), irrespective of the time since pregnancy and even in the absence of pregnancy. These data suggest that PABCs arise preferentially from an alveolar cell population that expands during pregnancy and lactation. This somatic mouse model may also be useful for preclinical testing of new prophylactic and therapeutic strategies against PABC

Nanostructured thermoelectric generator for energy harvesting

This paper presents the development processes towards a new generation of nanostructured thermoelectric generators for power harvesting from small temperature gradients by using a combination of traditional silicon microfabrication techniques, electroplating and submicron ion-track nanolithography. Polyimide nanotemplates with pore diameters ranging from 30nm to 120 nm were fabricated. Preliminary results for Bi2Te3 nanowires (50 and 120 nm diameter) electroplated into polycarbonate ion-track commercial membranes are presented. Bi2Te3 nanowires of R ̄ 3m structure, with preferential orientation in the (015) and (110) crystallographic plans with nearly stoichiometric composition were electroplated. The fine-grained observed microstructure (6-10 nm) and (110) crystalline orientation appear extremely promising for improving thermoelectric material properties

Rectification of electronic heat current by a hybrid thermal diode

We report the realization of an ultra-efficient low-temperature hybrid heat current rectifier, thermal counterpart of the well-known electric diode. Our design is based on a tunnel junction between two different elements: a normal metal and a superconducting island. Electronic heat current asymmetry in the structure arises from large mismatch between the thermal properties of these two. We demonstrate experimentally temperature differences exceeding $60$ mK between the forward and reverse thermal bias configurations. Our device offers a remarkably large heat rectification ratio up to $\sim 140$ and allows its prompt implementation in true solid-state thermal nanocircuits and general-purpose electronic applications requiring energy harvesting or thermal management and isolation at the nanoscale.Comment: 8 pages, 6 color figure

FastPval: A fast and memory efficient program to calculate very low P-values from empirical distribution

Motivation: Resampling methods, such as permutation and bootstrap, have been widely used to generate an empirical distribution for assessing the statistical significance of a measurement. However, to obtain a very low P-value, a large size of resampling is required, where computing speed, memory and storage consumption become bottlenecks, and sometimes become impossible, even on a computer cluster. Results: We have developed a multiple stage P-value calculating program called FastPval that can efficiently calculate very low (up to 10-9) P-values from a large number of resampled measurements. With only two input files and a few parameter settings from the users, the program can compute P-values from empirical distribution very efficiently, even on a personal computer. When tested on the order of 109 resampled data, our method only uses 52.94% the time used by the conventional method, implemented by standard quicksort and binary search algorithms, and consumes only 0.11% of the memory and storage. Furthermore, our method can be applied to extra large datasets that the conventional method fails to calculate. The accuracy of the method was tested on data generated from Normal, Poison and Gumbel distributions and was found to be no different from the exact ranking approach. © The Author(s) 2010. Published by Oxford University Press.published_or_final_versio

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models

Alkylated-C-60 based soft materials: regulation of self-assembly and optoelectronic properties by chain branching

Derivatization of fullerene (C60) with branched aliphatic chains softens C60-based materials and enables the formation of thermotropic liquid crystals and room temperature nonvolatile liquids. This work demonstrates that by carefully tuning parameters such as type, number and substituent position of the branched chains, liquid crystalline C60 materials with mesophase temperatures suited for photovoltaic cell fabrication and room temperature nonvolatile liquid fullerenes with tunable viscosity can be obtained. In particular, compound 1, with branched chains, exhibits a smectic liquid crystalline phase extending from 84 °C to room temperature. Analysis of bulk heterojunction (BHJ) organic solar cells with a ca. 100 nm active layer of compound 1 and poly(3-hexylthiophene) (P3HT) as an electron acceptor and an electron donor, respectively, reveals an improved performance (power conversion efficiency, PCE: 1.6 ± 0.1%) in comparison with another compound, 10 (PCE: 0.5 ± 0.1%). The latter, in contrast to 1, carries linear aliphatic chains and thus forms a highly ordered solid lamellar phase at room temperature. The solar cell performance of 1 blended with P3HT approaches that of PCBM/P3HT for the same active layer thickness. This indicates that C60 derivatives bearing branched tails are a promising class of electron acceptors in soft (flexible) photovoltaic devices

Software that goes with the flow in systems biology

A recent article in BMC Bioinformatics describes new advances in workflow systems for computational modeling in systems biology. Such systems can accelerate, and improve the consistency of, modeling through automation not only at the simulation and results-production stages, but also at the model-generation stage. Their work is a harbinger of the next generation of more powerful software for systems biologists