A novel approach to diagnostic biomarker definition and analysis

We have developed a method for the definition and the analysis of gene expression signatures for diagnostic purposes. Our approach relies on construction of a reference map of transcriptional signatures, from both healthy controls and affected patients, using the respective mRNA or miRNA profiles. Subsequently, disease diagnosis can be performed by determining the relative map position of an individual's transcriptional signature. Our approach addresses simultaneously the scarce repeatability issue and the high sensitivity of expression profiling methods to protocol variations, thereby providing a novel approach to RNA signature definition and analysis. Specifically, our method requires only that the relative position of RNA species be accurate in a ranking by value, not their absolute values. Furthermore, our method makes no assumptions on which RNA species must be included in the signature and, by considering a large subset (or even the whole set) of known RNAs, our approach can tolerate a moderate numb..

Efficient layering for high speed communication: the MPI over Fast Messages (FM) experience

We describe our experience of designing, implementing, and evaluating two generations of high performance communication libraries, Fast Messages (FM) for Myrinet. In FM 1, we designed a simple interface and provided guarantees of reliable and in-order delivery, and flow control. While this was a significant improvement over previous systems, it was not enough. Layering MPI atop FM 1 showed that only about 35 % of the FM 1 bandwidth could be delivered to higher level communication APIs. Our second generation communication layer, FM 2, addresses the identified problems, providing gather-scatter, interlayer scheduling, receiver flow control, as well as some convenient API features which simplify programming. FM 2 can deliver 55–95 % to higher level APIs such as MPI. This is especially impressive as the absolute bandwidths delivered have increased over fourfold to 90 MB/s. We describe general issues encountered in matching two communication layers, and our solutions as embodied in FM 2

Genetic Strategies to Enhance Plant Biomass Yield and Quality- Related Traits for Bio-Renewable Fuel and Chemical Productions

Owing to the increasing concerns on the environment, climate change, and limited natural resources, there are currently considerable efforts applied to produce chemicals and materials from renewable biomass. While initial emphasis has been placed on biofuel production from food plant sugars, the competition between crop usage for food and non-food applications has promoted research efforts to genetically improve yield and quality-related traits for biorefining applications. This chapter summarizes the potential of genetic and biotechnological strategies for improving plant biomass yields and quality-related traits and for breeding varieties more suitable to meet biorefining applications. Attempts were also made to provide a description on the genetic and molecular mechanisms affecting starch, cell wall composition and architecture, and oils synthesis and deposition, including genetic strategies to modify these traits. Similarly, the chapter covers the genetic strategies to improve yields by emphasizing the efforts done to identifying genetic variation and gene(s) governing critical morphological, structural, and physiological traits that in turn influence biomass yields. Finally, in the chapter it is suggested that knowledge of plant biosynthetic pathways will eventually provide valuable opportunities for metabolic engineering, as well as access to chemical transformations unique to plants for breeding varieties with built-in new traits

SCUDO: a tool for signature-based clustering of expression profiles

SCUDO (Signature-based ClUstering for DiagnOstic purposes) is an online tool for the analysis of gene expression profiles for diagnostic and classification purposes. The tool is based on a new method for the clustering of profiles based on a subject-specific, as opposed to disease-specific, signature. Our approach relies on construction of a reference map of transcriptional signatures, from both healthy and affected subjects, derived from their respective mRNA or miRNA profiles. A diagnosis for a new individual can then be performed by determining the position of the individual's transcriptional signature on the map. The diagnostic power of our method has been convincingly demonstrated in an open scientific competition (SBV Improver Diagnostic Signature Challenge), scoring second place overall and first place in one of the sub-challenges

Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness

Systems biology has been recently applied to vaccinology to better understand immunological responses to the influenza vaccine. Particular attention has been paid to the identification of early signatures capable of predicting vaccine immunogenicity. Building fromprevious studies, we employed a recently established algorithm for signature-based clustering of expression profiles, SCUDO, to provide new insights into why blood-derived transcriptome biomarkers often fail to predict the seroresponse to the influenza virus vaccination. Specifically, preexisting immunity against one or more vaccine antigens, which was found to negatively affect the seroresponse, was identified as a confounding factor able to decouple early transcriptome fromlater antibody responses, resulting in the degradation of a biomarker predictive power. Finally, the broadly accepted definition of seroresponse to influenza virus vaccine, represented by the maximum response across the vaccine-targeted strains, was compared to a composite measure integrating the responses against all strains. This analysis revealed that compositemeasures provide amore accurate assessment of the seroresponse to multicomponent influenza vaccines

New clinical insight in amyotrophic lateral sclerosis and innovative clinical development from the non-profit repurposing trial of the old drug guanabenz

Drug repurposing is considered a valid approach to accelerate therapeutic solutions for rare diseases. However, it is not as widely applied as it could be, due to several barriers that discourage both industry and academic institutions from pursuing this path. Herein we present the case of an academic multicentre study that considered the repurposing of the old drug guanabenz as a therapeutic strategy in amyotrophic lateral sclerosis. The difficulties encountered are discussed as an example of the barriers that academics involved in this type of study may face. Although further development of the drug for this target population was hampered for several reasons, the study was successful in many ways. Firstly, because the hypothesis tested was confirmed in a sub-population, leading to alternative innovative solutions that are now under clinical investigation. In addition, the study was informative and provided new insights into the disease, which are now giving new impetus to laboratory research. The message from this example is that even a repurposing study with an old product has the potential to generate innovation and interest from industry partners, provided it is based on a sound rationale, the study design is adequate to ensure meaningful results, and the investigators keep the full clinical development picture in mind