Data-driven sentence simplification: Survey and benchmark

Sentence Simplification (SS) aims to modify a sentence in order to make it easier to read and understand. In order to do so, several rewriting transformations can be performed such as replacement, reordering, and splitting. Executing these transformations while keeping sentences grammatical, preserving their main idea, and generating simpler output, is a challenging and still far from solved problem. In this article, we survey research on SS, focusing on approaches that attempt to learn how to simplify using corpora of aligned original-simplified sentence pairs in English, which is the dominant paradigm nowadays. We also include a benchmark of different approaches on common datasets so as to compare them and highlight their strengths and limitations. We expect that this survey will serve as a starting point for researchers interested in the task and help spark new ideas for future developments

Global Variation of Nutritional Status in Children Undergoing Chronic Peritoneal Dialysis : A Longitudinal Study of the International Pediatric Peritoneal Dialysis Network

While children approaching end-stage kidney disease (ESKD) are considered at risk of uremic anorexia and underweight they are also exposed to the global obesity epidemic. We sought to investigate the variation of nutritional status in children undergoing chronic peritoneal dialysis (CPD) around the globe. The distribution and course of body mass index (BMI) standard deviation score over time was examined prospectively in 1001 children and adolescents from 35 countries starting CPD who were followed in the International Pediatric PD Network (IPPN) Registry. The overall prevalence of underweight, and overweight/obesity at start of CPD was 8.9% and 19.7%, respectively. Underweight was most prevalent in South and Southeast Asia (20%), Central Europe (16.7%) and Turkey (15.2%), whereas overweight and obesity were most common in the Middle East (40%) and the US (33%). BMI SDS at PD initiation was associated positively with current eGFR and gastrostomy feeding prior to PD start. Over the course of PD BMI SDS tended to increase on CPD in underweight and normal weight children, whereas it decreased in initially overweight patients. In infancy, mortality risk was amplified by obesity, whereas in older children mortality was markedly increased in association with underweight. Both underweight and overweight are prevalent in pediatric ESKD, with the prevalence varying across the globe. Late dialysis start is associated with underweight, while enteral feeding can lead to obesity. Nutritional abnormalities tend to attenuate with time on dialysis. Mortality risk appears increased with obesity in infants and with underweight in older children.Peer reviewe

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer

Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3 and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized Luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Sub- and non-state climate action: a framework to assess progress, implementation and impact

The rising importance of cities, states and regions, firms, investors, and other subnational and non-state actors in global and national responses to climate change raises a critical question: to what extent does this climate action deliver results? This article introduces a conceptual framework that researchers and practitioners can use as a template to assess the progress, implementation, and impact of climate action by sub- and non-state actors. This framework is used to review existing studies that track progress, implementation, and achievement of such climate action between 2014 and mid-2019. While researchers have made important advances in assessing the scope and future potential of sub- and non-state climate action, we find knowledge gaps around ex-post achievement of results, indirect impacts, and climate action beyond the realm of greenhouse gas reductions. Key policy insights While we increasingly understand the scale, scope, and potential of climate action by sub- and non-state actors, we lack rigorous evidence regarding the results achieved and their broader impacts. More information on progress and impact is essential for the credibility of sub- and non-state climate action. Policymakers need to understand which approaches are working and which are not, promoting the diffusion of best practice and creating conditions for stronger action in the future. The proposed conceptual framework can be tailored and applied to a wide range of initiatives that target mitigation, adaptation, and other spheres of climate action. By providing a template to identify key elements of progress tracking and evaluation, the framework can help align both research and practitioner communities around the data and metrics required to understand the overall impact of climate action

Sub- and non-state climate action: a framework to assess progress, implementation and impact

The rising importance of cities, states and regions, firms, investors, and other subnational and non-state actors in global and national responses to climate change raises a critical question: to what extent does this climate action deliver results? This article introduces a conceptual framework that researchers and practitioners can use as a template to assess the progress, implementation, and impact of climate action by sub- and non-state actors. This framework is used to review existing studies that track progress, implementation, and achievement of such climate action between 2014 and mid-2019. While researchers have made important advances in assessing the scope and future potential of sub- and non-state climate action, we find knowledge gaps around ex-post achievement of results, indirect impacts, and climate action beyond the realm of greenhouse gas reductions. Key policy insights While we increasingly understand the scale, scope, and potential of climate action by sub- and non-state actors, we lack rigorous evidence regarding the results achieved and their broader impacts. More information on progress and impact is essential for the credibility of sub- and non-state climate action. Policymakers need to understand which approaches are working and which are not, promoting the diffusion of best practice and creating conditions for stronger action in the future. The proposed conceptual framework can be tailored and applied to a wide range of initiatives that target mitigation, adaptation, and other spheres of climate action. By providing a template to identify key elements of progress tracking and evaluation, the framework can help align both research and practitioner communities around the data and metrics required to understand the overall impact of climate action