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Institution

McGill University

EducationMontreal, Quebec, Canada
About: McGill University is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 72688 authors who have published 162565 publications receiving 6966523 citations. The organization is also known as: Royal institution of advanced learning & University of McGill College.


Papers
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Journal ArticleDOI
TL;DR: These indices and related worksheet provide an accurate and facile diagnosis-specific tool to estimate survival, potentially select appropriate treatment, and stratify clinical trials for patients with brain metastases.
Abstract: Purpose Our group has previously published the Graded Prognostic Assessment (GPA), a prognostic index for patients with brain metastases. Updates have been published with refinements to create diagnosis-specific Graded Prognostic Assessment indices. The purpose of this report is to present the updated diagnosis-specific GPA indices in a single, unified, user-friendly report to allow ease of access and use by treating physicians. Methods A multi-institutional retrospective (1985 to 2007) database of 3,940 patients with newly diagnosed brain metastases underwent univariate and multivariate analyses of prognostic factors associated with outcomes by primary site and treatment. Significant prognostic factors were used to define the diagnosis-specific GPA prognostic indices. A GPA of 4.0 correlates with the best prognosis, whereas a GPA of 0.0 corresponds with the worst prognosis. Results Significant prognostic factors varied by diagnosis. For lung cancer, prognostic factors were Karnofsky performance score, ag...

1,170 citations

Journal ArticleDOI
TL;DR: This chapter focuses on the metabolic pathways that are associated with the biosynthesis and degradation of the acyl lipids that represent their major form of carbon and energy storage in Arabidopsis.
Abstract: Acyl lipids in Arabidopsis and all other plants have a myriad of diverse functions. These include providing the core diffusion barrier of the membranes that separates cells and subcellular organelles. This function alone involves more than 10 membrane lipid classes, including the phospholipids, galactolipids, and sphingolipids, and within each class the variations in acyl chain composition expand the number of structures to several hundred possible molecular species. Acyl lipids in the form of triacylglycerol account for 35% of the weight of Arabidopsis seeds and represent their major form of carbon and energy storage. A layer of cutin and cuticular waxes that restricts the loss of water and provides protection from invasions by pathogens and other stresses covers the entire aerial surface of Arabidopsis. Similar functions are provided by suberin and its associated waxes that are localized in roots, seed coats, and abscission zones and are produced in response to wounding. This chapter focuses on the metabolic pathways that are associated with the biosynthesis and degradation of the acyl lipids mentioned above. These pathways, enzymes, and genes are also presented in detail in an associated website (ARALIP: http://aralip.plantbiology.msu.edu/). Protocols and methods used for analysis of Arabidopsis lipids are provided. Finally, a detailed summary of the composition of Arabidopsis lipids is provided in three figures and 15 tables.

1,169 citations

Journal ArticleDOI
TL;DR: In vertebrates, the Rpd3/Hda1 family contains 11 members, traditionally referred to as histone deacetylases (HDAC) 1–11, which are further grouped into classes I, II and IV.
Abstract: The Rpd3/Hda1 family of protein lysine deacetylases has numerous substrates and diverse functions. Whereas class I enzymes are multiprotein histone deacetylase complexes that are crucial for chromatin modification and transcriptional regulation, some class II enzymes function as signal transducers that are regulated by nucleocytoplasmic translocation. Protein lysine deacetylases have a pivotal role in numerous biological processes and can be divided into the Rpd3/Hda1 and sirtuin families, each having members in diverse organisms including prokaryotes. In vertebrates, the Rpd3/Hda1 family contains 11 members, traditionally referred to as histone deacetylases (HDAC) 1–11, which are further grouped into classes I, II and IV. Whereas most class I HDACs are subunits of multiprotein nuclear complexes that are crucial for transcriptional repression and epigenetic landscaping, class II members regulate cytoplasmic processes or function as signal transducers that shuttle between the cytoplasm and the nucleus. Little is known about class IV HDAC11, although its evolutionary conservation implies a fundamental role in various organisms.

1,168 citations

Journal ArticleDOI
TL;DR: In this paper, the insoluble block (PS) contents in the copolymers ranged from 80 to 98 wt % and the micelle cores, formed by aggregation of the PS blocks, were generally monodisperse.
Abstract: Crew-cut micelle-like aggregates of various morphologies prepared from polystyrene-b-poly(acrylic acid), PS-b-PAA, diblock copolymers under near-equilibrium conditions, were studied by transmission electron microscopy (TEM). The insoluble block (PS) contents in the copolymers ranged from 80 to 98 wt %. In spherical micelles, the micelle cores, formed by aggregation of the PS blocks, were generally monodisperse. A comparison between star and crew-cut micelles showed that the latter are distinguished by a low density of corona chains on the core surface and a low degree of stretching of the PS blocks in the cores. As the PAA content in block copolymer decreased, the morphology of the aggregates changed progressively from spheres to cylinders, to bilayers (both vesicles and lamellae), and eventually to compound micelles consisting of an assembly of inverted micelles surrounded by a hydrophilic surface. The compound micelles are believed to be a new morphology for block copolymers. The addition of homopolysty...

1,167 citations

Posted ContentDOI
Spyridon Bakas1, Mauricio Reyes, Andras Jakab2, Stefan Bauer3  +435 moreInstitutions (111)
TL;DR: This study assesses the state-of-the-art machine learning methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018, and investigates the challenge of identifying the best ML algorithms for each of these tasks.
Abstract: Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.

1,165 citations


Authors

Showing all 73373 results

NameH-indexPapersCitations
Karl J. Friston2171267217169
Yi Chen2174342293080
Yoshua Bengio2021033420313
Irving L. Weissman2011141172504
Mark I. McCarthy2001028187898
Lewis C. Cantley196748169037
Martin White1962038232387
Michael Marmot1931147170338
Michael A. Strauss1851688208506
Alan C. Evans183866134642
Douglas R. Green182661145944
David A. Weitz1781038114182
David L. Kaplan1771944146082
Hyun-Chul Kim1764076183227
Feng Zhang1721278181865
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023342
2022998
20219,055
20208,668
20197,828
20187,237