Functional neuroimaging of the interaction between social and executive neural circuitry in individuals with high-functioning autism

Autism has been associated with deficits in both social cognition and aspects of executive processing. While previous studies have elegantly demonstrated deificts in each of these processes in isolation, little is known about the interaction between these cognitive domains. The goal of this research was twofold: aim one was to utilize functional magnetic resonance imaging (fMRI) technology to probe how the neurotypical brain resolves competition between task-irrelevant social-cues and goal-directed information during an executive task in which the social context is irrelevant to the executive component. Aim two was to utilize the same fMRI task to probe the interaction between the social-cue and executive networks in a group of individuals with high-functioning autism. Elucidating the neural underpinnings of how individuals with autism differentially resolve competition between social-cues and executive attention may provide insight into the neural circuitry underlying the increased difficulty that individuals with autism often exhibit when performing executive tasks administered in a social context and more broadly expands our understanding of the social cognitive deficits in autism. Results from this work suggest that the presence of task-irrelevant social cues, namely pictures of eyes, increased attention to the target stimulus in both neurotypical controls and individuals with autism. Specifically, behavioral results suggest that in neurotypical participants the social cue facilitated target detection and promoted discrimination between target and non-target events. In contrast, while social cues behaviorally facilitated target detection in individuals with autism, the social information simultaneously impaired their ability to discriminate between target and non-target events. The enhanced discrimination of target and non-target events in neurotypical controls is likely due to the engagement of frontal cognitive control and selective attention circuitry, which modulates attention to and enhances processing of task-relevant information while filtering distracting irrelevant sensory input. Conversely, dysregulation of fronto-limbic circuits in individuals with autism was associated with an inability to filter interference by the task-irrelevant social stimuli, thus resulting in reduced executive control processes and decreased ability to discriminate between stimuli paired with task-irrelevant eyes

Transplantation Outcomes for Children with Hypodiploid Acute Lymphoblastic Leukemia

Children with hypodiploid acute lymphoblastic leukemia (ALL) have inferior outcomes despite intensive risk adapted chemotherapy regimens. We describe 78 children with hypodiploid ALL who underwent hematopoietic stem cell transplant (HSCT) between 1990 and 2010. Thirty nine (50%) patients had ≤ 43 chromosomes, 12 (15%) had 44 chromosomes and 27 (35%) had 45 chromosomes. Forty three (55%) patients were transplanted in first remission (CR1) while 35 (45%) were transplanted in ≥CR2. Twenty nine patients (37%) received a graft from a related donor and 49 (63%) from an unrelated donor. All patients received a myeloablative conditioning regimen. The 5-year probabilities of leukemia-free survival (LFS), overall survival (OS), relapse, and treatment related mortality (TRM) for the entire cohort were 51%, 56%, 27% and 22% respectively. Multivariate analysis confirmed that mortality risks were higher for patients transplanted in CR2 (HR 2.16, p=0.05), with chromosome number ≤43 (HR 2.15, p=0.05) and for those transplanted in the first decade of the study period (HR 2.60, p=0.01). Similarly, treatment failure risks were higher with chromosome number ≤43 (HR 2.28, p=0.04) and the earlier transplant period (HR 2.51, p=0.01). Although survival is better with advances in donor selection and supportive care, disease-related risk factors significantly influence transplantation outcomes

The benefit of directly comparing autism and schizophrenia for revealing mechanisms of social cognitive impairment

Autism and schizophrenia share a history of diagnostic conflation that was not definitively resolved until the publication of the DSM-III in 1980. Though now recognized as heterogeneous disorders with distinct developmental trajectories and dissociative features, much of the early nosological confusion stemmed from apparent overlap in certain areas of social dysfunction. In more recent years, separate but substantial literatures have accumulated for autism and schizophrenia demonstrating that abnormalities in social cognition directly contribute to the characteristic social deficits of both disorders. The current paper argues that direct comparison of social cognitive impairment can highlight shared and divergent mechanisms underlying pathways to social dysfunction, a process that can provide significant clinical benefit by informing the development of tailored treatment efforts. Thus, while the history of diagnostic conflation between autism and schizophrenia may have originated in similarities in social dysfunction, the goal of direct comparisons is not to conflate them once again but rather to reveal distinctions that illuminate disorder-specific mechanisms and pathways that contribute to social cognitive impairment

A Multicenter Pilot Evaluation of the National Institutes of Health Chronic Graft-versus-Host Disease (cGVHD) Therapeutic Response Measures: Feasibility, Interrater Reliability, and Minimum Detectable Change

The lack of standardized criteria for measuring therapeutic response is a major obstacle to the development of new therapeutic agents for chronic graft-versus-host disease (cGVHD). National Institutes of Health (NIH) consensus criteria for evaluating therapeutic response were published in 2006. We report the results of four consecutive pilot trials evaluating the feasibility and estimating the inter-rater reliability and minimum detectable change of these response criteria

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Forouzanfar MH, Afshin A, Alexander LT, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. LANCET. 2016;388(10053):1659-1724.Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57.8% (95% CI 56.6-58.8) of global deaths and 41.2% (39.8-42.8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211.8 million [192.7 million to 231.1 million] global DALYs), smoking (148.6 million [134.2 million to 163.1 million]), high fasting plasma glucose (143.1 million [125.1 million to 163.5 million]), high BMI (120.1 million [83.8 million to 158.4 million]), childhood undernutrition (113.3 million [103.9 million to 123.4 million]), ambient particulate matter (103.1 million [90.8 million to 115.1 million]), high total cholesterol (88.7 million [74.6 million to 105.7 million]), household air pollution (85.6 million [66.7 million to 106.1 million]), alcohol use (85.0 million [77.2 million to 93.0 million]), and diets high in sodium (83.0 million [49.3 million to 127.5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Copyright (C) The Author(s). Published by Elsevier Ltd

Example Clinical Screening Form.

<p>Example of an auto-scoring form populated with questions and AD-Scores from the GAD ADTree depicted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0165524#pone.0165524.g003" target="_blank">Fig 3</a>. As the examiner answers the questions (denoted as an “X” next to the associated answer in the “Response” column), the score sheet automatically assigns the associated AD-Score and calculates a cumulative risk score using the equation: <i>Risk Score</i> = 1 − (1/(<i>exp</i>(<i>AD</i> − <i>Score</i>) + 1)) <i>with each additional question</i>.</p