Lateral specialization in unilateral spatial neglect : a cognitive robotics model

In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans

Mixing of rhyolite, trachyte and basalt magma erupted from a vertically and laterally zoned reservoir, composite flow P1, Gran Canaria

The 14.1 Ma composite welded ignimbrite P1 (45 km3 DRE) on Gran Canaria is compositionally zoned from a felsic lower part to a basaltic top. It is composed of four component magmas mixed in vertically varying proportions: (1) Na-rhyolite (10 km3) zoned from crystal-poor to highly phyric; (2) a continuously zoned, evolved trachyte to sodic trachyandesite magma group (6 km3); (3) a minor fraction of Na-poor trachyandesite (<1 km3); and (4) nearly aphyric basalt (26 km3) zoned from 4.3 to 5.2 wt% MgO. We distinguish three sites and phases of mixing: (a) Mutual mineral inclusions show that mixing between trachytic and rhyolitic magmas occurred during early stages of their intratelluric crystallization, providing evidence for long-term residence in a common reservoir prior to eruption. This first phase of mixing was retarded by increasing viscosity of the rhyolite magma upon massive anorthoclase precipitation and accumulation. (b) All component magmas probably erupted through a ring-fissure from a common upper-crustal reservoir into which the basalt intruded during eruption. The second phase of mixing occurred during simultaneous withdrawal of magmas from the chamber and ascent through the conduit. The overall withdrawal and mixing pattern evolved in response to pre-eruptive chamber zonation and density and viscosity relationships among the magmas. Minor sectorial variations around the caldera reflect both varying configurations at the conduit entrance and unsteady discharge. (c) During each eruptive pulse, fragmentation and particulate transport in the vent and as pyroclastic flows caused additional mixing by reducing the length scale of heterogeneities. Based on considerations of magma density changes during crystallization, magma temperature constraints, and the pattern of withdrawal during eruption, we propose that eruption tapped the P1 magma chamber during a transient state of concentric zonation, which had resulted from destruction of a formerly layered zonation in order to maintain gravitational equilibrium. Our model of magma chamber zonation at the time of eruption envisages a basal high-density Na-poor trachyandesite layer that was overlain by a central mass of highly phyric rhyolite magma mantled by a sheath of vertically zoned trachyte-trachyandesite magma along the chamber walls. A conventional model of vertically stacked horizontal layers cannot account for the deduced density relationships nor for the withdrawal pattern

Development and content validity of a patient reported outcomes measure to assess symptoms of major depressive disorder

<p>Abstract</p> <p>Background</p> <p>Although many symptoms of Major Depressive Disorder (MDD) are assessed through patient-report, there are currently no patient-reported outcome (PRO) instruments that incorporate documented evidence of patient input in PRO instrument development. A review of existing PROs used in MDD suggested the need to conduct qualitative research with patients with MDD to better understand their experience of MDD and develop an evaluative instrument with content validity. The aim of this study was to develop a disease-specific questionnaire to assess symptoms important and relevant to adult MDD patients.</p> <p>Methods</p> <p>The questionnaire development involved qualitative interviews for concept elicitation, instrument development, and cognitive interviews to support content validity. For concept elicitation, ten MDD severity-specific focus group interviews with thirty-eight patients having clinician-confirmed diagnoses of MDD were conducted in January 2009. A semi-structured discussion guide was used to elicit patients' spontaneous descriptions of MDD symptoms. Verbatim transcripts of focus groups were coded and analyzed to develop a conceptual framework to describe MDD. A PRO instrument was developed by operationalizing concepts elicited in the conceptual framework. Cognitive interviews were carried out in patients (n = 20) to refine and test the content validity of the instrument in terms of item relevance and comprehension, instructions, recall period, and response categories.</p> <p>Results</p> <p>Concept elicitation focus groups identified thirty-five unique concepts falling into several domains: i) emotional, ii) cognitive, iii) motivation, iv) work, v) sleep, vi) appetite, vii) social, viii) activities of daily living, ix) tired/fatigue, x) body pain, and xi) suicidality. Concept saturation, the point at which no new relevant information emerges in later interviews, was achieved for each of the concepts. Based on the qualitative findings, the PRO instrument developed had 15 daily and 20 weekly items. The cognitive interviews confirmed that the instructions, item content, and response scales were understood by the patients.</p> <p>Conclusions</p> <p>Rigorous qualitative research resulted in the development of a PRO measure for MDD with supported content validity. The MDD PRO can assist in understanding and assessing MDD symptoms from patients' perspectives as well as evaluating treatment benefit of new targeted therapies.</p

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies.ope

Racism as a determinant of health: a systematic review and meta-analysis

Despite a growing body of epidemiological evidence in recent years documenting the health impacts of racism, the cumulative evidence base has yet to be synthesized in a comprehensive meta-analysis focused specifically on racism as a determinant of health. This meta-analysis reviewed the literature focusing on the relationship between reported racism and mental and physical health outcomes. Data from 293 studies reported in 333 articles published between 1983 and 2013, and conducted predominately in the U.S., were analysed using random effects models and mean weighted effect sizes. Racism was associated with poorer mental health (negative mental health: r = -.23, 95% CI [-.24,-.21], k = 227; positive mental health: r = -.13, 95% CI [-.16,-.10], k = 113), including depression, anxiety, psychological stress and various other outcomes. Racism was also associated with poorer general health (r = -.13 (95% CI [-.18,-.09], k = 30), and poorer physical health (r = -.09, 95% CI [-.12,-.06], k = 50). Moderation effects were found for some outcomes with regard to study and exposure characteristics. Effect sizes of racism on mental health were stronger in cross-sectional compared with longitudinal data and in non-representative samples compared with representative samples. Age, sex, birthplace and education level did not moderate the effects of racism on health. Ethnicity significantly moderated the effect of racism on negative mental health and physical health: the association between racism and negative mental health was significantly stronger for Asian American and Latino(a) American participants compared with African American participants, and the association between racism and physical health was significantly stronger for Latino(a) American participants compared with African American participants.<br /

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯