Concurrent engineering and design for manufacture in the medical device industry

Concurrent Engineering (CE) is an approach to product development in which engineers work on design and manufacturability at the same time. The ultimate goal of concurrent engineering is to reduce the time-to-market while improving quality. This thesis goes into details about the tools necessary to achieve successful product development in the Medical Device Industry. The novelty of this thesis is not in the tools themselves but rather in the way that they are applied to the medical device industry. The need for the CE approach is of utmost importance because of the vast competition in the medical device industry. The times now require changes. These changes are depicted in detail early in this thesis. This latter suggests that manufacturing is to be perceived like another science. The axiomatic approach to manufacturing answers these needs. A new way of designing a product and collecting data is relevant. It is known as the technique of Quality function Deployment (QFD). Finally, all these tools are managed with the phase approach to management. I sincerely think that this thesis will constitute an invaluable tool for managers and engineers in the medical industry

Économies haïtienne et dominicaine : dépendance et/ou interdépendance?

Notre propos dans cet article est surtout de soulever la question de linterdépendance des économies haïtienne et dominicaine afin de signaler des pistes pour une recherche entre elles dune synergie pouvant avoir des répercussions positives qui amélioreraient les conditions de vie de la population de lîle. En dautres termes, la dépendance de léconomie haïtienne une fois constatée, notre objectif serait essentiellement didentifier les facteurs, les ressources ou les faits qui démontreraient une corrélation entre ces deux économies

Predicted human structural clusters of miRNAs target cancer genes

Deregulation of gene expression is one of the main characteristics of cancer cells. The implication of microRNAs (miRNAs), a class of small non-coding RNAs implicated in post-transcriptional regulation of gene expression, in this process have rapidly become evident. As protein-coding genes, miRNAs can act as tumor suppressors or oncogenes (we speak about oncomirs). Recent studies have highlighted the paralogous clusters of miRNAs mir-17-92 and mir-106a-363 to be involved in carcinogenesis. It features the importance of a local and structural organization of miRNAs with potential impact on cancers. We performed computational predictions of structural clusters of miRNAs sharing the same characteristics as the two previously described clusters at the human genome scale. We show a functional organization of miRNAs in structural clusters where the predicted miRNA targets are enriched for cancer associated genes. On the other hand, we also show co-localization of structural clusters of miRNAs with genes involved in signaling pathways known to be disrupted in cancer. Taken together, the results provide new insights into the organization of miRNAs in the human genome along with their potential impact on carcinogenesis

JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles.

JASPAR (http://jaspar.genereg.net) is an open-access database storing curated, non-redundant transcription factor (TF) binding profiles representing transcription factor binding preferences as position frequency matrices for multiple species in six taxonomic groups. For this 2016 release, we expanded the JASPAR CORE collection with 494 new TF binding profiles (315 in vertebrates, 11 in nematodes, 3 in insects, 1 in fungi and 164 in plants) and updated 59 profiles (58 in vertebrates and 1 in fungi). The introduced profiles represent an 83% expansion and 10% update when compared to the previous release. We updated the structural annotation of the TF DNA binding domains (DBDs) following a published hierarchical structural classification. In addition, we introduced 130 transcription factor flexible models trained on ChIP-seq data for vertebrates, which capture dinucleotide dependencies within TF binding sites. This new JASPAR release is accompanied by a new web tool to infer JASPAR TF binding profiles recognized by a given TF protein sequence. Moreover, we provide the users with a Ruby module complementing the JASPAR API to ease programmatic access and use of the JASPAR collection of profiles. Finally, we provide the JASPAR2016 R/Bioconductor data package with the data of this release

New miniPromoter Ple345 (NEFL) drives strong and specific expression in retinal ganglion cells of mouse and primate retina.

Retinal gene therapy is leading the neurological gene therapy field, with 32 ongoing clinical trials of recombinant adeno-associated virus (rAAV)-based therapies. Importantly, over 50% of those trials are using restricted promoters from human genes. Promoters that restrict expression have demonstrated increased efficacy and can limit the therapeutic to the target cells thereby reducing unwanted off-target effects. Retinal ganglion cells are a critical target in ocular gene therapy; they are involved in common diseases such as glaucoma, rare diseases such as Leber's hereditary optic neuropathy, and in revolutionary optogenetic treatments. Here, we used computational biology and mined the human genome for the best genes from which to develop a novel minimal promoter element(s) designed for expression in restricted cell types (MiniPromoter) to improve the safety and efficacy of retinal ganglion cell gene therapy. Gene selection included the use of the first available droplet-based single-cell RNA sequencing (Drop-seq) dataset, and promoter design was bioinformatically driven and informed by a wide range of genomics datasets. We tested seven promoter designs from four genes in rAAV for specificity and quantified expression strength in retinal ganglion cells in mouse, and then the single best in nonhuman primate retina. Thus, we developed a new human-DNA MiniPromoter, Ple345 (NEFL), which in combination with intravitreal delivery in rAAV9 showed specific and robust expression in the retinal ganglion cells of the nonhuman-primate rhesus macaque retina. In mouse, we also developed MiniPromoters expressing in retinal ganglion cells, the hippocampus of the brain, a pan neuronal pattern in the brain, and peripheral nerves. As single-cell transcriptomics such as Drop-seq become available for other cell types, many new opportunities for additional novel restricted MiniPromoters will present

PAX6 MiniPromoters drive restricted expression from rAAV in the adult mouse retina.

Current gene therapies predominantly use small, strong, and readily available ubiquitous promoters. However, as the field matures, the availability of small, cell-specific promoters would be greatly beneficial. Here we design seven small promoters from the human paired box 6 (PAX6) gene and test them in the adult mouse retina using recombinant adeno-associated virus. We chose the retina due to previous successes in gene therapy for blindness, and the PAX6 gene since it is: well studied; known to be driven by discrete regulatory regions; expressed in therapeutically interesting retinal cell types; and mutated in the vision-loss disorder aniridia, which is in need of improved therapy. At the PAX6 locus, 31 regulatory regions were bioinformatically predicted, and nine regulatory regions were constructed into seven MiniPromoters. Driving Emerald GFP, these MiniPromoters were packaged into recombinant adeno-associated virus, and injected intravitreally into postnatal day 14 mice. Four MiniPromoters drove consistent retinal expression in the adult mouse, driving expression in combinations of cell-types that endogenously express Pax6: ganglion, amacrine, horizontal, and Müller glia. Two PAX6-MiniPromoters drive expression in three of the four cell types that express PAX6 in the adult mouse retina. Combined, they capture all four cell types, making them potential tools for research, and PAX6-gene therapy for aniridia

The genetic basis of a social polymorphism in halictid bees

The emergence of eusociality represents a major evolutionary transition from solitary to group reproduction. The most commonly studied eusocial species, honey bees and ants, represent the behavioral extremes of social evolution but lack close relatives that are non-social. Unlike these species, the halictid bee Lasioglossum albipes produces both solitary and eusocial nests and this intraspecific variation has a genetic basis. Here, we identify genetic variants associated with this polymorphism, including one located in the intron of syntaxin 1a (syx1a), a gene that mediates synaptic vesicle release. We show that this variant can alter gene expression in a pattern consistent with differences between social and solitary bees. Surprisingly, syx1a and several other genes associated with sociality in L. albipes have also been implicated in autism spectrum disorder in humans. Thus, genes underlying behavioral variation in L. albipes may also shape social behaviors across a wide range of taxa, including humans

Erratum: JASPAR 2018: update of the open-access database of transcription factor binding profiles and its web framework

JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) and TF flexible models (TFFMs) for TFs across multiple species in six taxonomic groups. In the 2018 release of JASPAR, the CORE collection has been expanded with 322 new PFMs (60 for vertebrates and 262 for plants) and 33 PFMs were updated (24 for vertebrates, 8 for plants and 1 for insects). These new profiles represent a 30% expansion compared to the 2016 release. In addition, we have introduced 316 TFFMs (95 for vertebrates, 218 for plants and 3 for insects). This release incorporates clusters of similar PFMs in each taxon and each TF class per taxon. The JASPAR 2018 CORE vertebrate collection of PFMs was used to predict TF-binding sites in the human genome. The predictions are made available to the scientific community through a UCSC Genome Browser track data hub. Finally, this update comes with a new web framework with an interactive and responsive user-interface, along with new features. All the underlying data can be retrieved programmatically using a RESTful API and through the JASPAR 2018 R/Bioconductor package

A systematic, large-scale comparison of transcription factor binding site models

Background The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified “real” in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. Results While the area- under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. Conclusions Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM (http:/mutationtaster.charite.de/ePOSSUM/) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites