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Showing papers by "McGill University published in 2017"


Journal ArticleDOI
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.

10,401 citations


Journal ArticleDOI
TL;DR: Antiinflammatory therapy targeting the interleukin‐1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid‐level lowering.
Abstract: BackgroundExperimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. MethodsWe conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. ResultsAt 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in t...

5,660 citations


Journal ArticleDOI
TL;DR: This book is dedicated to the memory of those who have served in the armed forces and their families during the conflicts of the twentieth century.

2,628 citations


Journal ArticleDOI
TL;DR: TAVR was a noninferior alternative to surgery in patients with severe aortic stenosis at intermediate surgical risk, with a different pattern of adverse events associated with each procedure.
Abstract: BackgroundAlthough transcatheter aortic-valve replacement (TAVR) is an accepted alternative to surgery in patients with severe aortic stenosis who are at high surgical risk, less is known about comparative outcomes among patients with aortic stenosis who are at intermediate surgical risk. MethodsWe evaluated the clinical outcomes in intermediate-risk patients with severe, symptomatic aortic stenosis in a randomized trial comparing TAVR (performed with the use of a self-expanding prosthesis) with surgical aortic-valve replacement. The primary end point was a composite of death from any cause or disabling stroke at 24 months in patients undergoing attempted aortic-valve replacement. We used Bayesian analytical methods (with a margin of 0.07) to evaluate the noninferiority of TAVR as compared with surgical valve replacement. ResultsA total of 1746 patients underwent randomization at 87 centers. Of these patients, 1660 underwent an attempted TAVR or surgical procedure. The mean (±SD) age of the patients was 7...

2,095 citations


Journal ArticleDOI
TL;DR: This 2017 Consensus Statement is to provide a state-of-the-art review of the field of catheter and surgical ablation of AF and to report the findings of a writing group, convened by these five international societies.

1,626 citations


Journal ArticleDOI
Andrew I R Maas1, David K. Menon2, P. David Adelson3, Nada Andelic4  +339 moreInstitutions (110)
TL;DR: The InTBIR Participants and Investigators have provided informed consent for the study to take place in Poland.
Abstract: Additional co-authors: Endre Czeiter, Marek Czosnyka, Ramon Diaz-Arrastia, Jens P Dreier, Ann-Christine Duhaime, Ari Ercole, Thomas A van Essen, Valery L Feigin, Guoyi Gao, Joseph Giacino, Laura E Gonzalez-Lara, Russell L Gruen, Deepak Gupta, Jed A Hartings, Sean Hill, Ji-yao Jiang, Naomi Ketharanathan, Erwin J O Kompanje, Linda Lanyon, Steven Laureys, Fiona Lecky, Harvey Levin, Hester F Lingsma, Marc Maegele, Marek Majdan, Geoffrey Manley, Jill Marsteller, Luciana Mascia, Charles McFadyen, Stefania Mondello, Virginia Newcombe, Aarno Palotie, Paul M Parizel, Wilco Peul, James Piercy, Suzanne Polinder, Louis Puybasset, Todd E Rasmussen, Rolf Rossaint, Peter Smielewski, Jeannette Soderberg, Simon J Stanworth, Murray B Stein, Nicole von Steinbuchel, William Stewart, Ewout W Steyerberg, Nino Stocchetti, Anneliese Synnot, Braden Te Ao, Olli Tenovuo, Alice Theadom, Dick Tibboel, Walter Videtta, Kevin K W Wang, W Huw Williams, Kristine Yaffe for the InTBIR Participants and Investigators

1,354 citations


Proceedings Article
07 Jun 2017
TL;DR: In this article, an actor-critic method was used to learn multi-agent coordination policies in cooperative and competitive multi-player RL games, where agent populations are able to discover various physical and informational coordination strategies.
Abstract: We explore deep reinforcement learning methods for multi-agent domains. We begin by analyzing the difficulty of traditional algorithms in the multi-agent case: Q-learning is challenged by an inherent non-stationarity of the environment, while policy gradient suffers from a variance that increases as the number of agents grows. We then present an adaptation of actor-critic methods that considers action policies of other agents and is able to successfully learn policies that require complex multi-agent coordination. Additionally, we introduce a training regimen utilizing an ensemble of policies for each agent that leads to more robust multi-agent policies. We show the strength of our approach compared to existing methods in cooperative as well as competitive scenarios, where agent populations are able to discover various physical and informational coordination strategies.

1,273 citations


Journal ArticleDOI
TL;DR: Among patients with primary progressive multiple sclerosis, ocrelizumab was associated with lower rates of clinical and MRI progression than placebo; there was no clinically significant difference between groups in the rates of serious adverse events and serious infections.
Abstract: BackgroundAn evolving understanding of the immunopathogenesis of multiple sclerosis suggests that depleting B cells could be useful for treatment. We studied ocrelizumab, a humanized monoclonal antibody that selectively depletes CD20-expressing B cells, in the primary progressive form of the disease. MethodsIn this phase 3 trial, we randomly assigned 732 patients with primary progressive multiple sclerosis in a 2:1 ratio to receive intravenous ocrelizumab (600 mg) or placebo every 24 weeks for at least 120 weeks and until a prespecified number of confirmed disability progression events had occurred. The primary end point was the percentage of patients with disability progression confirmed at 12 weeks in a time-to-event analysis. ResultsThe percentage of patients with 12-week confirmed disability progression was 32.9% with ocrelizumab versus 39.3% with placebo (hazard ratio, 0.76; 95% confidence interval [CI], 0.59 to 0.98; P=0.03). The percentage of patients with 24-week confirmed disability progression w...

1,220 citations


Journal ArticleDOI
TL;DR: Among patients with relapsing multiple sclerosis, ocrelizumab was associated with lower rates of disease activity and progression than interferon beta‐1a over a period of 96 weeks.
Abstract: BackgroundB cells influence the pathogenesis of multiple sclerosis. Ocrelizumab is a humanized monoclonal antibody that selectively depletes CD20+ B cells. MethodsIn two identical phase 3 trials, we randomly assigned 821 and 835 patients with relapsing multiple sclerosis to receive intravenous ocrelizumab at a dose of 600 mg every 24 weeks or subcutaneous interferon beta-1a at a dose of 44 μg three times weekly for 96 weeks. The primary end point was the annualized relapse rate. ResultsThe annualized relapse rate was lower with ocrelizumab than with interferon beta-1a in trial 1 (0.16 vs. 0.29; 46% lower rate with ocrelizumab; P<0.001) and in trial 2 (0.16 vs. 0.29; 47% lower rate; P<0.001). In prespecified pooled analyses, the percentage of patients with disability progression confirmed at 12 weeks was significantly lower with ocrelizumab than with interferon beta-1a (9.1% vs. 13.6%; hazard ratio, 0.60; 95% confidence interval [CI], 0.45 to 0.81; P<0.001), as was the percentage of patients with disabilit...

1,198 citations


Proceedings ArticleDOI
27 Nov 2017
TL;DR: This paper develops an active learning framework for high dimensional data, a task which has been extremely challenging so far, with very sparse existing literature, and demonstrates its active learning techniques with image data, obtaining a significant improvement on existing active learning approaches.
Abstract: Even though active learning forms an important pillar of machine learning, deep learning tools are not prevalent within it. Deep learning poses several difficulties when used in an active learning setting. First, active learning (AL) methods generally rely on being able to learn and update models from small amounts of data. Recent advances in deep learning, on the other hand, are notorious for their dependence on large amounts of data. Second, many AL acquisition functions rely on model uncertainty, yet deep learning methods rarely represent such model uncertainty. In this paper we combine recent advances in Bayesian deep learning into the active learning framework in a practical way. We develop an active learning framework for high dimensional data, a task which has been extremely challenging so far, with very sparse existing literature. Taking advantage of specialised models such as Bayesian convolutional neural networks, we demonstrate our active learning techniques with image data, obtaining a significant improvement on existing active learning approaches. We demonstrate this on both the MNIST dataset, as well as for skin cancer diagnosis from lesion images (ISIC2016 task).

1,139 citations


Proceedings Article
06 Aug 2017
TL;DR: The analysis suggests that the notions of effective capacity which are dataset independent are unlikely to explain the generalization performance of deep networks when trained with gradient based methods because training data itself plays an important role in determining the degree of memorization.
Abstract: We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noise data, our results suggest that they tend to prioritize learning simple patterns first. In our experiments, we expose qualitative differences in gradient-based optimization of deep neural networks (DNNs) on noise vs. real data. We also demonstrate that for appropriately tuned explicit regularization (e.g., dropout) we can degrade DNN training performance on noise datasets without compromising generalization on real data. Our analysis suggests that the notions of effective capacity which are dataset independent are unlikely to explain the generalization performance of deep networks when trained with gradient based methods because training data itself plays an important role in determining the degree of memorization.

Journal ArticleDOI
TL;DR: It is demonstrated that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable.
Abstract: The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Journal ArticleDOI
TL;DR: This work introduces MicrobiomeAnalyst, a user-friendly tool that integrates recent progress in statistics and visualization techniques, coupled with novel knowledge bases, to enable comprehensive analysis of common data outputs produced from microbiome studies.
Abstract: The widespread application of next-generation sequencing technologies has revolutionized microbiome research by enabling high-throughput profiling of the genetic contents of microbial communities. How to analyze the resulting large complex datasets remains a key challenge in current microbiome studies. Over the past decade, powerful computational pipelines and robust protocols have been established to enable efficient raw data processing and annotation. The focus has shifted toward downstream statistical analysis and functional interpretation. Here, we introduce MicrobiomeAnalyst, a user-friendly tool that integrates recent progress in statistics and visualization techniques, coupled with novel knowledge bases, to enable comprehensive analysis of common data outputs produced from microbiome studies. MicrobiomeAnalyst contains four modules - the Marker Data Profiling module offers various options for community profiling, comparative analysis and functional prediction based on 16S rRNA marker gene data; the Shotgun Data Profiling module supports exploratory data analysis, functional profiling and metabolic network visualization of shotgun metagenomics or metatranscriptomics data; the Taxon Set Enrichment Analysis module helps interpret taxonomic signatures via enrichment analysis against >300 taxon sets manually curated from literature and public databases; finally, the Projection with Public Data module allows users to visually explore their data with a public reference data for pattern discovery and biological insights. MicrobiomeAnalyst is freely available at http://www.microbiomeanalyst.ca.

Journal ArticleDOI
02 Nov 2017-Nature
TL;DR: A genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry finds that heritability of Breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome- wide average.
Abstract: Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Journal ArticleDOI
TL;DR: A number of distinct features of the brain tumor microenvironment are discussed, including brain-resident cell types, the blood-brain barrier, and various aspects of the immune-suppressive environment.

Journal ArticleDOI
TL;DR: An international multidisciplinary team of 29 members with expertise in guideline development, evidence analysis, and family-centered care is assembled to revise the 2007 Clinical Practice Guidelines for support of the family in the patient-centered ICU.
Abstract: Objective:To provide clinicians with evidence-based strategies to optimize the support of the family of critically ill patients in the ICU.Methods:We used the Council of Medical Specialty Societies principles for the development of clinical guidelines as the framework for guideline development. We a

Journal ArticleDOI
28 Jul 2017-Science
TL;DR: A bioinspired design for adhesives consisting of an adhesive surface with a flexible matrix to develop an adhesive that has the right level of stick but moves with the surrounding tissues, which is effective in the presence of blood and thus might work during wound repair.
Abstract: Adhesion to wet and dynamic surfaces, including biological tissues, is important in many fields but has proven to be extremely challenging. Existing adhesives are cytotoxic, adhere weakly to tissues, or cannot be used in wet environments. We report a bioinspired design for adhesives consisting of two layers: an adhesive surface and a dissipative matrix. The former adheres to the substrate by electrostatic interactions, covalent bonds, and physical interpenetration. The latter amplifies energy dissipation through hysteresis. The two layers synergistically lead to higher adhesion energies on wet surfaces as compared with those of existing adhesives. Adhesion occurs within minutes, independent of blood exposure and compatible with in vivo dynamic movements. This family of adhesives may be useful in many areas of application, including tissue adhesives, wound dressings, and tissue repair.

Journal ArticleDOI
TL;DR: In postmenopausal women with osteoporosis who were at high risk for fracture, romosozumab treatment for 12 months followed by alendronsate resulted in a significantly lower risk of fracture than alendronate alone.
Abstract: BackgroundRomosozumab is a monoclonal antibody that binds to and inhibits sclerostin, increases bone formation, and decreases bone resorption. MethodsWe enrolled 4093 postmenopausal women with osteoporosis and a fragility fracture and randomly assigned them in a 1:1 ratio to receive monthly subcutaneous romosozumab (210 mg) or weekly oral alendronate (70 mg) in a blinded fashion for 12 months, followed by open-label alendronate in both groups. The primary end points were the cumulative incidence of new vertebral fracture at 24 months and the cumulative incidence of clinical fracture (nonvertebral and symptomatic vertebral fracture) at the time of the primary analysis (after clinical fractures had been confirmed in ≥330 patients). Secondary end points included the incidences of nonvertebral and hip fracture at the time of the primary analysis. Serious cardiovascular adverse events, osteonecrosis of the jaw, and atypical femoral fractures were adjudicated. ResultsOver a period of 24 months, a 48% lower risk...

Proceedings Article
19 Sep 2017
TL;DR: Challenges posed by reproducibility, proper experimental techniques, and reporting procedures are investigated and guidelines to make future results in deep RL more reproducible are suggested.
Abstract: In recent years, significant progress has been made in solving challenging problems across various domains using deep reinforcement learning (RL). Reproducing existing work and accurately judging the improvements offered by novel methods is vital to sustaining this progress. Unfortunately, reproducing results for state-of-the-art deep RL methods is seldom straightforward. In particular, non-determinism in standard benchmark environments, combined with variance intrinsic to the methods, can make reported results tough to interpret. Without significance metrics and tighter standardization of experimental reporting, it is difficult to determine whether improvements over the prior state-of-the-art are meaningful. In this paper, we investigate challenges posed by reproducibility, proper experimental techniques, and reporting procedures. We illustrate the variability in reported metrics and results when comparing against common baselines and suggest guidelines to make future results in deep RL more reproducible. We aim to spur discussion about how to ensure continued progress in the field by minimizing wasted effort stemming from results that are non-reproducible and easily misinterpreted.

Journal ArticleDOI
05 Jan 2017-Nature
TL;DR: The authors' observations are inconsistent with the fast radio burst having a Galactic origin or its source being located within a prominent star-forming galaxy, and the source appears to be co-located with a low-luminosity active galactic nucleus or a previously unknown type of extragalactic source.
Abstract: Subarcsecond localization of the repeating fast radio burst FRB 121102 shows that its source is co-located with a faint galaxy with a low-luminosity active galactic nucleus, or a previously unknown type of extragalactic source. Shami Chatterjee et al. report the subarcsecond localization of the Arecibo-discovered fast radio burst FRB 121102, the only known repeating burst source, using high-time-resolution radio interferometric observations that directly image the bursts. FRBs are radio flashes of unknown physical nature with durations of milliseconds. Previous observations have lacked the resolution to uniquely identify a host or multi-wavelength counterpart. The localization of FRB 121102 reveals a persistent radio and optical source that is coincident with the bursts to within 100 milliarcseconds. The enigmatic persistent source could be a neutron star within its nebula in a distant host galaxy, a low-luminosity active galactic nucleus, or a previously unknown type of extragalactic source. Fast radio bursts1,2 are astronomical radio flashes of unknown physical nature with durations of milliseconds. Their dispersive arrival times suggest an extragalactic origin and imply radio luminosities that are orders of magnitude larger than those of all known short-duration radio transients3. So far all fast radio bursts have been detected with large single-dish telescopes with arcminute localizations, and attempts to identify their counterparts (source or host galaxy) have relied on the contemporaneous variability of field sources4 or the presence of peculiar field stars5 or galaxies4. These attempts have not resulted in an unambiguous association6,7 with a host or multi-wavelength counterpart. Here we report the subarcsecond localization of the fast radio burst FRB 121102, the only known repeating burst source8,9,10,11, using high-time-resolution radio interferometric observations that directly image the bursts. Our precise localization reveals that FRB 121102 originates within 100 milliarcseconds of a faint 180-microJansky persistent radio source with a continuum spectrum that is consistent with non-thermal emission, and a faint (twenty-fifth magnitude) optical counterpart. The flux density of the persistent radio source varies by around ten per cent on day timescales, and very long baseline radio interferometry yields an angular size of less than 1.7 milliarcseconds. Our observations are inconsistent with the fast radio burst having a Galactic origin or its source being located within a prominent star-forming galaxy. Instead, the source appears to be co-located with a low-luminosity active galactic nucleus or a previously unknown type of extragalactic source. Localization and identification of a host or counterpart has been essential to understanding the origins and physics of other kinds of transient events, including gamma-ray bursts12,13 and tidal disruption events14. However, if other fast radio bursts have similarly faint radio and optical counterparts, our findings imply that direct subarcsecond localizations may be the only way to provide reliable associations.

Journal ArticleDOI
Florence M.G. Cavalli1, Marc Remke1, Marc Remke2, Marc Remke3, Ladislav Rampášek1, John Peacock1, David Shih1, Betty Luu1, Livia Garzia1, Jonathon Torchia1, Carolina Nor1, A. Sorana Morrissy1, Sameer Agnihotri4, Yuan Yao Thompson1, Claudia M. Kuzan-Fischer1, Hamza Farooq1, Keren Isaev1, Keren Isaev5, Craig Daniels1, Byung Kyu Cho6, Seung-Ki Kim6, Kyu-Chang Wang6, Ji Yeoun Lee6, Wiesława Grajkowska7, Marta Perek-Polnik7, Alexandre Vasiljevic, Cécile Faure-Conter, Anne Jouvet8, Caterina Giannini9, Amulya A. Nageswara Rao9, Kay Ka Wai Li10, Ho Keung Ng10, Charles G. Eberhart11, Ian F. Pollack4, Ronald L. Hamilton4, G. Yancey Gillespie12, James M. Olson13, James M. Olson14, Sarah Leary13, William A. Weiss15, Boleslaw Lach16, Boleslaw Lach17, Lola B. Chambless18, Reid C. Thompson18, Michael K. Cooper18, Rajeev Vibhakar19, Peter Hauser20, Marie Lise C. van Veelen21, Johan M. Kros21, Pim J. French21, Young Shin Ra22, Toshihiro Kumabe23, Enrique López-Aguilar24, Karel Zitterbart25, Jaroslav Sterba25, Gaetano Finocchiaro, Maura Massimino, Erwin G. Van Meir26, Satoru Osuka26, Tomoko Shofuda, Almos Klekner27, Massimo Zollo28, Jeffrey R. Leonard29, Joshua B. Rubin29, Nada Jabado30, Steffen Albrecht31, Steffen Albrecht30, Jaume Mora, Timothy E. Van Meter32, Shin Jung33, Andrew S. Moore34, Andrew R. Hallahan34, Jennifer A. Chan35, Daniela Pretti da Cunha Tirapelli36, Carlos Gilberto Carlotti36, Maryam Fouladi37, José Pimentel, Claudia C. Faria, Ali G. Saad38, Luca Massimi39, Linda M. Liau40, Helen Wheeler41, Hideo Nakamura42, Samer K. Elbabaa43, Mario Perezpeña-Diazconti, Fernando Chico Ponce de León, Shenandoah Robinson44, Michal Zapotocky1, Alvaro Lassaletta1, Annie Huang1, Cynthia Hawkins1, Uri Tabori1, Eric Bouffet1, Ute Bartels1, Peter B. Dirks1, James T. Rutka1, Gary D. Bader1, Jüri Reimand5, Jüri Reimand1, Anna Goldenberg1, Vijay Ramaswamy1, Michael D. Taylor1 
TL;DR: Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes.

Journal ArticleDOI
15 Feb 2017-Nature
TL;DR: It is shown that hyperexpansion of the cortical surface area between 6 and 12 months of age precedes brain volume overgrowth observed between 12 and 24 months in 15 high-risk infants who were diagnosed with autism at 24 months.
Abstract: Autism spectrum disorder (ASD) is associated with brain overgrowth, but it has been unclear how this relates to behavioural symptoms. In a longitudinal neuroimaging study of young children at high familial risk of autism, Heather Hazlett and colleagues now show that high-risk children who receive a diagnosis of ASD at 24 months of age had an increased cortical growth rate at 612 months. Early overgrowth in high-risk children is associated with social impairments at 24 months, and imaging data obtained at 6 and 12 months can predict an ASD diagnosis at 24 months in high-risk children. These findings indicate that differences in the developmental trajectory towards ASD emerge as early as the first year of life.

Proceedings ArticleDOI
20 Aug 2017
TL;DR: The Montreal Forced Aligner (MFA) is an update to the Prosodylab-Aligner, and maintains its key functionality of trainability on new data, as well as incorporating improved architecture (triphone acoustic models and speaker adaptation), and other features.
Abstract: We present the Montreal Forced Aligner (MFA), a new opensource system for speech-text alignment. MFA is an update to the Prosodylab-Aligner, and maintains its key functionality of trainability on new data, as well as incorporating improved architecture (triphone acoustic models and speaker adaptation), and other features. MFA uses Kaldi instead of HTK, allowing MFA to be distributed as a stand-alone package, and to exploit parallel processing for computationally-intensive training and scaling to larger datasets. We evaluate MFA’s performance on aligning word and phone boundaries in English conversational and laboratory speech, relative to human-annotated boundaries, focusing on the effects of aligner architecture and training on the data to be aligned. MFA performs well relative to two existing open-source aligners with simpler architecture (Prosodylab-Aligner and FAVE), and both its improved architecture and training on data to be aligned generally result in more accurate boundaries.

Journal ArticleDOI
TL;DR: A brief overview of the recent achievements and opportunities created by mechanochemistry, including access to materials, molecular targets, and synthetic strategies that are hard or even impossible to access by conventional means are provided.
Abstract: The past decade has seen a reawakening of solid-state approaches to chemical synthesis, driven by the search for new, cleaner synthetic methodologies. Mechanochemistry, i.e., chemical transformations initiated or sustained by mechanical force, has been advancing particularly rapidly, from a laboratory curiosity to a widely applicable technique that not only enables a cleaner route to chemical transformations but offers completely new opportunities in making and screening for molecules and materials. This Outlook provides a brief overview of the recent achievements and opportunities created by mechanochemistry, including access to materials, molecular targets, and synthetic strategies that are hard or even impossible to access by conventional means.

Journal ArticleDOI
Paul A. Northcott1, Paul A. Northcott2, Ivo Buchhalter3, Ivo Buchhalter2, A. Sorana Morrissy, Volker Hovestadt2, Joachim Weischenfeldt4, Tobias Ehrenberger5, Susanne Gröbner2, Maia Segura-Wang6, Thomas Zichner6, Vasilisa A. Rudneva, Hans-Jörg Warnatz7, Nikos Sidiropoulos4, Aaron H. Phillips1, Steven E. Schumacher8, Kortine Kleinheinz2, Sebastian M. Waszak6, Serap Erkek2, Serap Erkek6, David T.W. Jones2, Barbara C. Worst2, Marcel Kool2, Marc Zapatka2, Natalie Jäger2, Lukas Chavez2, Barbara Hutter2, Matthias Bieg2, Nagarajan Paramasivam2, Nagarajan Paramasivam3, Michael Heinold3, Michael Heinold2, Zuguang Gu2, Naveed Ishaque2, Christina Jäger-Schmidt2, Charles D. Imbusch2, Alke Jugold2, Daniel Hübschmann9, Daniel Hübschmann3, Daniel Hübschmann2, Thomas Risch7, Vyacheslav Amstislavskiy7, Francisco German Rodriguez Gonzalez4, Ursula D. Weber2, Stephan Wolf2, Giles W. Robinson1, Xin Zhou1, Gang Wu1, David Finkelstein1, Yanling Liu1, Florence M.G. Cavalli, Betty Luu, Vijay Ramaswamy, Xiaochong Wu, Jan Koster, Marina Ryzhova, Yoon Jae Cho10, Scott L. Pomeroy11, Christel Herold-Mende3, Martin U. Schuhmann12, Martin Ebinger, Linda M. Liau13, Jaume Mora14, Roger E. McLendon15, Nada Jabado16, Toshihiro Kumabe17, Eric Chuah18, Yussanne Ma18, Richard A. Moore18, Andrew J. Mungall18, Karen Mungall18, Nina Thiessen18, Kane Tse18, Tina Wong18, Steven J.M. Jones18, Olaf Witt9, Till Milde9, Andreas von Deimling9, David Capper9, Andrey Korshunov9, Marie-Laure Yaspo7, Richard W. Kriwacki1, Amar Gajjar1, Jinghui Zhang1, Rameen Beroukhim8, Ernest Fraenkel5, Jan O. Korbel6, Benedikt Brors2, Matthias Schlesner2, Roland Eils2, Roland Eils3, Marco A. Marra18, Stefan M. Pfister2, Stefan M. Pfister9, Michael D. Taylor19, Peter Lichter2 
19 Jul 2017-Nature
TL;DR: The application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.
Abstract: Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

Journal ArticleDOI
TL;DR: Genomic aberrations increase with age, highlighting the infant population as biologically and clinically distinct, and co-segregating mutations in histone-mutant subgroups including loss of FBXW7 in H 3.3G34R/V, TOP3A rearrangements in H3.3K27M, and BCOR mutations in H2.1K 27M are identified.

Journal ArticleDOI
Ryan K. C. Yuen1, Daniele Merico1, Matt Bookman2, Jennifer L. Howe1, Bhooma Thiruvahindrapuram1, Rohan V. Patel1, Joe Whitney1, Nicole A. Deflaux2, Jonathan Bingham2, Zhuozhi Wang1, Giovanna Pellecchia1, Janet A. Buchanan1, Susan Walker1, Christian R. Marshall1, Mohammed Uddin1, Mehdi Zarrei1, Eric Deneault1, Lia D’Abate1, Lia D’Abate3, Ada J.S. Chan1, Ada J.S. Chan3, Stephanie Koyanagi1, Tara Paton1, Sergio L. Pereira1, Ny Hoang1, Worrawat Engchuan1, Edward J Higginbotham1, Karen Ho1, Sylvia Lamoureux1, Weili Li1, Jeffrey R. MacDonald1, Thomas Nalpathamkalam1, Wilson W L Sung1, Fiona Tsoi1, John Wei1, Lizhen Xu1, Anne Marie Tassé4, Emily Kirby4, William Van Etten, Simon N. Twigger, Wendy Roberts, Irene Drmic1, Sanne Jilderda1, Bonnie Mackinnon Modi1, Barbara Kellam1, Michael J. Szego3, Michael J. Szego1, Cheryl Cytrynbaum, Rosanna Weksberg3, Lonnie Zwaigenbaum5, Marc Woodbury-Smith6, Marc Woodbury-Smith1, Jessica Brian3, Lili Senman3, Alana Iaboni3, Krissy A.R. Doyle-Thomas3, Ann Thompson6, Christina Chrysler6, Jonathan Leef3, Tal Savion-Lemieux4, Isabel M. Smith7, Xudong Liu8, Rob Nicolson9, Vicki Seifer10, Angie Fedele10, Edwin H. Cook11, Stephen R. Dager12, Annette Estes12, Louise Gallagher13, Beth A. Malow14, Jeremy R. Parr15, Sarah J. Spence16, Jacob A. S. Vorstman17, Brendan J. Frey3, James T. Robinson18, Lisa J. Strug1, Lisa J. Strug3, Bridget A. Fernandez19, Mayada Elsabbagh4, Melissa T. Carter20, Joachim Hallmayer21, Bartha Maria Knoppers4, Evdokia Anagnostou3, Peter Szatmari3, Peter Szatmari22, Robert H. Ring23, David Glazer2, Mathew T. Pletcher10, Stephen W. Scherer3, Stephen W. Scherer1 
TL;DR: Se sequencing of 5,205 samples from families with ASD, accompanied by clinical information, creating a database accessible on a cloud platform and through a controlled-access internet portal that identified 18 new candidate ASD-risk genes and found that participants bearing mutations in susceptibility genes had significantly lower adaptive ability.
Abstract: We are performing whole-genome sequencing of families with autism spectrum disorder (ASD) to build a resource (MSSNG) for subcategorizing the phenotypes and underlying genetic factors involved. Here we report sequencing of 5,205 samples from families with ASD, accompanied by clinical information, creating a database accessible on a cloud platform and through a controlled-access internet portal. We found an average of 73.8 de novo single nucleotide variants and 12.6 de novo insertions and deletions or copy number variations per ASD subject. We identified 18 new candidate ASD-risk genes and found that participants bearing mutations in susceptibility genes had significantly lower adaptive ability (P = 6 × 10-4). In 294 of 2,620 (11.2%) of ASD cases, a molecular basis could be determined and 7.2% of these carried copy number variations and/or chromosomal abnormalities, emphasizing the importance of detecting all forms of genetic variation as diagnostic and therapeutic targets in ASD.

Journal ArticleDOI
TL;DR: Twenty-three evidence-based recommendations about diagnostic testing for latent tuberculosis infection, pulmonary tuberculosis, and extrapulmonary tuberculosis are provided and six of the recommendations are strong, whereas the remaining 17 are conditional.
Abstract: Background Individuals infected with Mycobacterium tuberculosis (Mtb) may develop symptoms and signs of disease (tuberculosis disease) or may have no clinical evidence of disease (latent tuberculosis infection [LTBI]). Tuberculosis disease is a leading cause of infectious disease morbidity and mortality worldwide, yet many questions related to its diagnosis remain. Methods A task force supported by the American Thoracic Society, Centers for Disease Control and Prevention, and Infectious Diseases Society of America searched, selected, and synthesized relevant evidence. The evidence was then used as the basis for recommendations about the diagnosis of tuberculosis disease and LTBI in adults and children. The recommendations were formulated, written, and graded using the Grading, Recommendations, Assessment, Development and Evaluation (GRADE) approach. Results Twenty-three evidence-based recommendations about diagnostic testing for latent tuberculosis infection, pulmonary tuberculosis, and extrapulmonary tuberculosis are provided. Six of the recommendations are strong, whereas the remaining 17 are conditional. Conclusions These guidelines are not intended to impose a standard of care. They provide the basis for rational decisions in the diagnosis of tuberculosis in the context of the existing evidence. No guidelines can take into account all of the often compelling unique individual clinical circumstances.

Posted Content
TL;DR: In this article, the authors investigate the challenges posed by reproducibility, proper experimental techniques, and reporting procedures for state-of-the-art deep RL methods and suggest guidelines to make future results in deep RL more reproducible.
Abstract: In recent years, significant progress has been made in solving challenging problems across various domains using deep reinforcement learning (RL). Reproducing existing work and accurately judging the improvements offered by novel methods is vital to sustaining this progress. Unfortunately, reproducing results for state-of-the-art deep RL methods is seldom straightforward. In particular, non-determinism in standard benchmark environments, combined with variance intrinsic to the methods, can make reported results tough to interpret. Without significance metrics and tighter standardization of experimental reporting, it is difficult to determine whether improvements over the prior state-of-the-art are meaningful. In this paper, we investigate challenges posed by reproducibility, proper experimental techniques, and reporting procedures. We illustrate the variability in reported metrics and results when comparing against common baselines and suggest guidelines to make future results in deep RL more reproducible. We aim to spur discussion about how to ensure continued progress in the field by minimizing wasted effort stemming from results that are non-reproducible and easily misinterpreted.

Journal ArticleDOI
TL;DR: A review of the recent molecular advances that have been uncovered in normal and diseased mammalian cells linking protein arginine methyltransferases to diseases such as cancer and metabolic, neurodegenerative, and muscular disorders is described.