Fine-grained parallel RNAalifold algorithm for RNA secondary structure prediction on FPGA

<p>Abstract</p> <p>Background</p> <p>In the field of RNA secondary structure prediction, the RNAalifold algorithm is one of the most popular methods using free energy minimization. However, general-purpose computers including parallel computers or multi-core computers exhibit parallel efficiency of no more than 50%. Field Programmable Gate-Array (FPGA) chips provide a new approach to accelerate RNAalifold by exploiting fine-grained custom design.</p> <p>Results</p> <p>RNAalifold shows complicated data dependences, in which the dependence distance is variable, and the dependence direction is also across two dimensions. We propose a systolic array structure including one master Processing Element (PE) and multiple slave PEs for fine grain hardware implementation on FPGA. We exploit data reuse schemes to reduce the need to load energy matrices from external memory. We also propose several methods to reduce energy table parameter size by 80%.</p> <p>Conclusion</p> <p>To our knowledge, our implementation with 16 PEs is the only FPGA accelerator implementing the complete RNAalifold algorithm. The experimental results show a factor of 12.2 speedup over the RNAalifold (<it>ViennaPackage </it>– 1.6.5) software for a group of aligned RNA sequences with 2981-residue running on a Personal Computer (PC) platform with Pentium 4 2.6 GHz CPU.</p

Anti-inflammatory effect of rosiglitazone is not reflected in expression of NFκB-related genes in peripheral blood mononuclear cells of patients with type 2 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Rosiglitazone not only improves insulin-sensitivity, but also exerts anti-inflammatory effects. We have now examined in type 2 diabetic patients if these effects are reflected by changes in mRNA expression in peripheral blood mononuclear cells (PBMCs) to see if these cells can be used to study these anti-inflammatory effects at the molecular level <it>in vivo</it>.</p> <p>Method</p> <p>Eleven obese type 2 diabetic patients received rosiglitazone (2 × 4 mg/d) for 8 weeks. Fasting blood samples were obtained before and after treatment. Ten obese control subjects served as reference group. The expression of NFκB-related genes and PPARγ target genes in PBMCs, plasma TNFα, IL6, MCP1 and hsCRP concentrations were measured. In addition, blood samples were obtained after a hyperinsulinemic-euglycemic clamp.</p> <p>Results</p> <p>Rosiglitazone reduced plasma MCP1 and hsCRP concentrations in diabetic patients (-9.5 ± 5.3 pg/mL, <it>p </it> = 0.043 and -1.1 ± 0.3 mg/L <it>p </it> = 0.003), respectively). For hsCRP, the concentration became comparable with the non-diabetic reference group. However, of the 84 NFκB-related genes that were measured in PBMCs from type 2 diabetic subjects, only RELA, SLC20A1, INFγ and IL1R1 changed significantly (<it>p </it> < 0.05). In addition, PPARγ and its target genes (CD36 and LPL) did not change. During the clamp, insulin reduced plasma MCP1 concentration in the diabetic and reference groups (-9.1 ± 1.8%, <it>p </it> = 0.001 and -11.1 ± 4.1%, <it>p </it> = 0.023, respectively) and increased IL6 concentration in the reference group only (23.5 ± 9.0%, <it>p </it> = 0.028).</p> <p>Conclusion</p> <p>In type 2 diabetic patients, the anti-inflammatory effect of rosiglitazone is not reflected by changes in NFκB and PPARγ target genes in PBMCs <it>in vivo</it>. Furthermore, our results do not support that high insulin concentrations contribute to the pro-inflammatory profile in type 2 diabetic patients.</p

Speciation in the Deep Sea: Multi-Locus Analysis of Divergence and Gene Flow between Two Hybridizing Species of Hydrothermal Vent Mussels

International audienceBackground: Reconstructing the history of divergence and gene flow between closely-related organisms has long been a difficult task of evolutionary genetics. Recently, new approaches based on the coalescence theory have been developed to test the existence of gene flow during the process of divergence. The deep sea is a motivating place to apply these new approaches. Differentiation by adaptation can be driven by the heterogeneity of the hydrothermal environment while populations should not have been strongly perturbed by climatic oscillations, the main cause of geographic isolation at the surface. Methodology/Principal Finding: Samples of DNA sequences were obtained for seven nuclear loci and a mitochondrial locus in order to conduct a multi-locus analysis of divergence and gene flow between two closely related and hybridizing species of hydrothermal vent mussels, Bathymodiolus azoricus and B. puteoserpentis. The analysis revealed that (i) the two species have started to diverge approximately 0.760 million years ago, (ii) the B. azoricus population size was 2 to 5 time greater than the B. puteoserpentis and the ancestral population and (iii) gene flow between the two species occurred over the complete species range and was mainly asymmetric, at least for the chromosomal regions studied. Conclusions/Significance: A long history of gene flow has been detected between the two Bathymodiolus species. However, it proved very difficult to conclusively distinguish secondary introgression from ongoing parapatric differentiation. As powerful as coalescence approaches could be, we are left by the fact that natural populations often deviates from standard assumptions of the underlying model. A more direct observation of the history of recombination at one of the seven loci studied suggests an initial period of allopatric differentiation during which recombination was blocked between lineages. Even in the deep sea, geographic isolation may well be a crucial promoter of speciation

Central Exercise Action Increases the AMPK and mTOR Response to Leptin

AMP-activated protein kinase (AMPK) and mammalian Target of Rapamycin (mTOR) are key regulators of cellular energy balance and of the effects of leptin on food intake. Acute exercise is associated with increased sensitivity to the effects of leptin on food intake in an IL-6-dependent manner. To determine whether exercise ameliorates the AMPK and mTOR response to leptin in the hypothalamus in an IL-6-dependent manner, rats performed two 3-h exercise bouts, separated by one 45-min rest period. Intracerebroventricular IL-6 infusion reduced food intake and pretreatment with AMPK activators and mTOR inhibitor prevented IL-6-induced anorexia. Activators of AMPK and fasting increased food intake in control rats to a greater extent than that observed in exercised ones, whereas inhibitor of AMPK had the opposite effect. Furthermore, the reduction of AMPK and ACC phosphorylation and increase in phosphorylation of proteins involved in mTOR signal transduction, observed in the hypothalamus after leptin infusion, were more pronounced in both lean and diet-induced obesity rats after acute exercise. Treatment with leptin reduced food intake in exercised rats that were pretreated with vehicle, although no increase in responsiveness to leptin-induced anorexia after pretreatment with anti-IL6 antibody, AICAR or Rapamycin was detected. Thus, the effects of leptin on the AMPK/mTOR pathway, potentiated by acute exercise, may contribute to appetite suppressive actions in the hypothalamus

Evolving stochastic context--free grammars for RNA secondary structure prediction.

BACKGROUND: Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s. The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few intuitively designed grammars have remained dominant. In this paper we investigate two automatic search techniques for effective grammars - exhaustive search for very compact grammars and an evolutionary algorithm to find larger grammars. We also examine whether grammar ambiguity is as problematic to structure prediction as has been previously suggested. RESULTS: These search techniques were applied to predict RNA secondary structure on a maximal data set and revealed new and interesting grammars, though none are dramatically better than classic grammars. In general, results showed that many grammars with quite different structure could have very similar predictive ability. Many ambiguous grammars were found which were at least as effective as the best current unambiguous grammars. CONCLUSIONS: Overall the method of evolving SCFGs for RNA secondary structure prediction proved effective in finding many grammars that had strong predictive accuracy, as good or slightly better than those designed manually. Furthermore, several of the best grammars found were ambiguous, demonstrating that such grammars should not be disregarded