Alien Registration- Lapointe, Charles J. (Jackman, Somerset County)

https://digitalmaine.com/alien_docs/7039/thumbnail.jp

An algorithm for classifying tumors based on genomic aberrations and selecting representative tumor models

<p>Abstract</p> <p>Background</p> <p>Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose.</p> <p>Method</p> <p>To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.</p> <p>Result</p> <p>We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC), colorectal cancer (CRC), and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes.</p> <p>Conclusions</p> <p>We developed an algorithm for cancer classification based on genome-wide patterns of copy number aberrations and demonstrated its superiority to existing clustering methods. The algorithm was applied to define genomic subgroups of three cancer types and identify cell lines representative of these subgroups. Our data enabled the assembly of representative cell line panels for testing drug candidates.</p

Alien Registration- Lapointe, Charles J. (Jackman, Somerset County)

https://digitalmaine.com/alien_docs/7039/thumbnail.jp

Habitat du faucon pèlerin dans le sud du Québec durant la période de reproduction : conséquences pour l’implantation de parcs éoliens

Le Québec offre un potentiel considérable pour le développement de l’industrie éolienne. Cette industrie peut être à l’origine de mortalités chez les rapaces et pourrait affecter certaines espèces vulnérables comme le faucon pèlerin. De 2008 à 2010, nous avons comparé l’utilisation de 5 types de milieux par 10 femelles nicheuses de faucon pèlerin dans le Québec méridional, afin de déterminer ceux à favoriser pour l’implantation de parcs éoliens. Les milieux les moins utilisés par les femelles étaient ceux considérés comme diminuant les risques de collision avec les éoliennes. Après l’envol des fauconneaux, les femelles parcouraient de plus grandes distances que lorsque les fauconneaux étaient confinés au nid. À cette période, 90 % des localisations télémétriques dans les cultures de maïs et de soya ont été enregistrées à l’intérieur d’un rayon de 8,3 km d’un nid, comparativement à un rayon de 15,9 km dans les autres cultures. Aussi, les femelles avaient moins de chances d’utiliser les cultures de maïs et de soya que les autres cultures et les milieux non propices pour la chasse. Nos résultats permettent de faire des recommandations quant à la localisation de projets éoliens, en termes de milieux à favoriser et de distances à respecter, afin de minimiser les risques de collision du faucon pèlerin.The province of Québec has considerable potential for the continued expansion of its wind power industry. Wind farms may be a cause of mortality for birds of prey and could have a particularly negative affect on certain vulnerable species, such as the peregrine falcon. To help determine the types of sites to favour for the establishment of new wind farms, we compared the use of 5 environments by 10 female peregrine falcons nesting in southern Québec during the period from 2008 to 2010. To minimize potential collision risks with wind turbines, the environments least used by females peregrine falcons should be preferentially chosen for locating wind farms. Once the young had fledged, females traveled farther afield than when the chicks were flightless. During this period, 90 % of the telemetry locations in corn and soybean fields were recorded within an 8.3-km radius of the nest, compared to a 15.9-km radius for other crops. Also, females were less likely to use corn and soybean fields, than other crops and environments that were not suitable for hunting. Our results lead to recommendations regarding the environments to favour for the location of future wind farms, and the minimal distances that should be respected between wind farms and peregrine falcon nests sites to minimize collision risks