What’s So Special About Patent Law?

The widespread belief that patent law is special has shaped the development of patent law into one of the most specialized areas of the law today. The belief in patent law’s exceptionalism manifests itself as two related presumptions with respect to the judiciary: first, that generalist judges who do not have patent law expertise cannot effectively decide patent cases, and second, that judges can develop necessary expertise through repeated experience with patent cases. Congress showed that it acquiesced to both views when it created the Federal Circuit and the Patent Pilot Program. In recent years, however, the Supreme Court has reminded us that the judiciary’s difficulty with patent cases is not the law, but is instead that patent cases often involve difficult subject matter, which sometimes requires technical or scientific expertise. While Congress’s early attempts to deal with these difficulties focused on courts with legal―rather than technical―expertise, the Supreme Court’s recent pronouncements suggest that they should have been doing the reverse. Moreover, to the extent that it is the underlying technology that makes patent cases difficult, that commends the use of an administrative, rather than a judicial, solution. One potentially viable answer to the judiciary’s problem with patent law has already been partly implemented in the form of the recently created Patent Trial and Appeal Board. This Article proposes expansion of that solution by making that new entity the exclusive forum for deciding issues of patent validity

Dissecting clinical outcome of porcine circovirus type 2 with in vivo derived transcriptomic signatures of host tissue responses

Background: Porcine Circovirus Type 2 (PCV2) is a pathogen that has the ability to cause often devastating disease manifestations in pig populations with major economic implications. How PCV2 establishes subclinical persistence and why certain individuals progress to lethal lymphoid depletion remain to be elucidated. Results: Here we present PorSignDB, a gene signature database describing in vivo porcine tissue physiology that we generated from a large compendium of in vivo transcriptional profiles and that we subsequently leveraged for deciphering the distinct physiological states underlying PCV2-affected lymph nodes. This systems genomics approach indicated that subclinical PCV2 infections suppress a myeloid leukocyte mediated immune response. However, in contrast an inflammatory myeloid cell activation is promoted in PCV2 patients with clinical manifestations. Functional genomics further uncovered STAT3 as a druggable PCV2 host factor candidate. Moreover, IL-2 supplementation of primary lymphocytes enabled ex vivo study of PCV2 replication in its target cell, the lymphoblast. Conclusion: Our systematic dissection of the mechanistic basis of PCV2 reveals that subclinical and clinical PCV2 display two diametrically opposed immunotranscriptomic recalibrations that represent distinct physiological states in vivo, which suggests a paradigm shift in this field. Finally, our PorSignDB signature database is publicly available as a community resource (http://www.vetvirology.ugent.be/PorSignDB/, included in Gene Sets from Community Contributors http://software.broadinstitute.org/gsea/msigdb/contributed_genesets.jsp) and provides systems biologists with a valuable tool for catalyzing studies of human and veterinary disease. Finally, a primary porcine lymphoblast cell culture system paves the way for unraveling the impact of host genetics on PCV2 replication

Mobilités, différenciations et inégalités : des questions actuelles

Voir l'article : http://www.espacestemps.net/articles/mobilites-differenciations-et-inegalites-des-questions-actuelles/Cet article est une introduction au dossier thématique « Mobilités, différenciations et inégalités » de la traverse « Mobilités »

FLO1 is a variable green beard gene that drives biofilm-like cooperation in budding yeast

The budding yeast, Saccharomyces cerevisiae, has emerged as an archetype of eukaryotic cell biology. Here we show that S. cerevisiae is also a model for the evolution of cooperative behavior by revisiting flocculation, a self-adherence phenotype lacking in most laboratory strains. Expression of the gene FLO1 in the laboratory strain S288C restores flocculation, an altered physiological state, reminiscent of bacterial biofilms. Flocculation protects the FLO1 expressing cells from multiple stresses, including antimicrobials and ethanol. Furthermore, FLO1(+) cells avoid exploitation by nonexpressing flo1 cells by self/non-self recognition: FLO1(+) cells preferentially stick to one another, regardless of genetic relatedness across the rest of the genome. Flocculation, therefore, is driven by one of a few known "green beard genes,'' which direct cooperation toward other carriers of the same gene. Moreover, FLO1 is highly variable among strains both in expression and in sequence, suggesting that flocculation in S. cerevisiae is a dynamic, rapidly evolving social trait

Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples

RNA-Seq is an effective method to study the transcriptome, but can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations, or cadavers. Recent studies have proposed several methods for RNA-Seq of low quality and/or low quantity samples, but their relative merits have not been systematically analyzed. Here, we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery, and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and two control libraries. We find that the RNase H method performed best for low quality RNA, and confirmed this with actual degraded samples. RNase H can even effectively replace oligo (dT) based methods for standard RNA-Seq. SMART and NuGEN had distinct strengths for low quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development

Les transports urbains non motorisés en Afrique sub-saharienne : le cas du Mali

L'objectif de ce travail est l'identification des obstacles à l'usage de la bicyclette, ainsi que l'appréciation des possibilités de développement de l'usage de ce mode par des mesures pour éliminer ces obstacles. Le postulat de cette démarche est que la bicyclette est potentiellement un mode favorisant la mobilité dans un contexte économique difficile où l'ensemble des besoins de déplacements ne peuvent être assurés par les transports collectifs ou encore par des moyens individuels motorisés, en raison des coûts économiques de ces modes.Ceci a conduit les auteurs à appréhender l'ensemble de la mobilité pour analyser quelles pratiques de déplacements et d'usage des modes se sont développées et quelle peut être l'évolution de ces pratiques.Bicyclette ; modes de transports ; politique des transports ; étude des déplacements ; mobilité quotidienne ; Bamako ; Mali

STAR-Fusion: Fast and Accurate Fusion Transcript Detection from RNA-Seq

Motivation Fusion genes created by genomic rearrangements can be potent drivers of tumorigenesis. However, accurate identification of functionally fusion genes from genomic sequencing requires whole genome sequencing, since exonic sequencing alone is often insufficient. Transcriptome sequencing provides a direct, highly effective alternative for capturing molecular evidence of expressed fusions in the precision medicine pipeline, but current methods tend to be inefficient or insufficiently accurate, lacking in sensitivity or predicting large numbers of false positives. Here, we describe STAR-Fusion, a method that is both fast and accurate in identifying fusion transcripts from RNA-Seq data. Results We benchmarked STAR-Fusion’s fusion detection accuracy using both simulated and genuine Illumina paired-end RNA-Seq data, and show that it has superior performance compared to popular alternative fusion detection methods. Availability and implementation STAR-Fusion is implemented in Perl, freely available as open source software at http://star-fusion.github.io, and supported on Linux

Comparative analysis of RNA sequencing methods for degraded or low-input samples

available in PMC 2014 January 01RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.National Institutes of Health (U.S.) (Pioneer Award DP1-OD003958-01)National Human Genome Research Institute (U.S.) (NHGRI) 1P01HG005062-01)National Human Genome Research Institute (U.S.) (NHGRI Center of Excellence in Genome Science Award 1P50HG006193-01)Howard Hughes Medical Institute (Investigator)Merkin Family Foundation for Stem Cell ResearchBroad Institute of MIT and Harvard (Klarman Cell Observatory)National Human Genome Research Institute (U.S.) (NHGRI grant HG03067)Fonds voor Wetenschappelijk Onderzoek--Vlaandere

Mutations causing medullary cystic kidney disease type 1 (MCKD1) lie in a large VNTR in MUC1 missed by massively parallel sequencing

While genetic lesions responsible for some Mendelian disorders can be rapidly discovered through massively parallel sequencing (MPS) of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple Mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing, and de novo assembly, we found that each of six MCKD1 families harbors an equivalent, but apparently independently arising, mutation in sequence dramatically underrepresented in MPS data: the insertion of a single C in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (~1.5-5 kb), GC-rich (>80%), coding VNTR in the mucin 1 gene. The results provide a cautionary tale about the challenges in identifying genes responsible for Mendelian, let alone more complex, disorders through MPS