Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module

Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.

Initial results from sequencing studies suggest that there are relatively few low-frequency (<5%) variants associated with large effects on common phenotypes. We performed low-pass whole-genome sequencing in 680 individuals from the InCHIANTI study to test two primary hypotheses: (i) that sequencing would detect single low-frequency-large effect variants that explained similar amounts of phenotypic variance as single common variants, and (ii) that some common variant associations could be explained by low-frequency variants. We tested two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common variant-common phenotype associations-11 132 cis-gene expression traits in 450 individuals and 93 circulating biomarkers in all 680 individuals. From a total of 11 657 229 high-quality variants of which 6 129 221 and 5 528 008 were common and low frequency (<5%), respectively, low frequency-large effect associations comprised 7% of detectable cis-gene expression traits [89 of 1314 cis-eQTLs at P < 1 × 10(-06) (false discovery rate ∼5%)] and one of eight biomarker associations at P < 8 × 10(-10). Very few (30 of 1232; 2%) common variant associations were fully explained by low-frequency variants. Our data show that whole-genome sequencing can identify low-frequency variants undetected by genotyping based approaches when sample sizes are sufficiently large to detect substantial numbers of common variant associations, and that common variant associations are rarely explained by single low-frequency variants of large effect

Plasmodium falciparum heterochromatin protein 1 binds to tri-methylated histone 3 lysine 9 and is linked to mutually exclusive expression of var genes

Increasing experimental evidence shows a prominent role of histone modifications in the coordinated control of gene expression in the human malaria parasite Plasmodium falciparum. The search for the histone-mark-reading machinery that translates histone modifications into biological processes, such as formation of heterochromatin and antigenic variation is of foremost importance. In this work, we identified the first member of a histone modification specific recognition protein, an orthologue of heterochromatin protein 1 (PfHP1). Analysis of the PfHP1 amino-acid sequence revealed the presence of the two characteristic HP1 domains: a chromodomain (CD) and a chromo shadow domain (CSD). Recombinant CD binds to di- and tri-methylated lysine 9 from histone H3, but not to unmodified or methylated histone H3 in lysine 4. PfHP1 is able to interact with itself to form dimers, underlying its potential role in aggregating nucleosomes to form heterochromatin. Antibodies raised against PfHP1 detect this molecule in foci at the perinuclear region. ChIP analysis using anti-PfHP1 shows that this protein is linked to heterochromatin of subtelomeric non-coding repeat regions and monoallelic expression of the major virulence var gene family. This is the first report implicating an HP1 protein in the control of antigenic variation of a protozoan parasite

Spanish guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia

The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large-scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies

Analisis de las respuestas moleculares profundas alcanzadas por las multiples secuencias de tratamientos con ITKS en LMC. Estudio de largo seguimiento del registro español de LMC

Poster [PC-231] Introducción: Cinco inhibidores de tirosina cinasa (ITKs) están disponibles para el tratamiento de pacientes con leucemia mieloide crónica en fase crónica (LMC-FC). Analizamos las diferentes secuencias de ITKs utilizadas como terapia para la LMC-FC en un análisis a largo plazo en vida real. Métodos: En un análisis retrospectivo de cohortes, se incluyeron pacientes con LMC-FC tratados en la práctica clínica con diferentes ITKs en el Registro Español de LMC (RELMC) (17 hospitales de todo el país) entre 2000 y 2014. El objetivo principal del estudio fue describir la secuencia del tratamiento con ITKs en la práctica de la vida real y la última respuesta molecular profunda (DMR) (MR4, MR4.5 o transcrito indetectable) para cada esquema. Resultados: Nuestro análisis incluyó 862 pacientes con LMC en 1º FC tratados con ITKs en 1ª línea o después de interferón alfa. Datos demográficos demográficos: 517 H, 345 M, mediana de edad: 52 años (14-94a). Distribución del Índice Sokal (bajo 49% Inter 38% Alto 13%), Índice EURO (bajo 50% Inter 45% Alto 5%), Índice EUTOS (bajo 93% Alto 7%), Índice LT-EUTOS (bajo 68 % Inter 25% Alto 7%). Esquemas de tratamiento: la Tabla 1 resume todos los esquemas utilizados y la última respuesta molecular. Los pacientes se dividieron en 4 grupos según el tratamiento con ITKs. Grupo 1: solo tratados con Imatinib 394 p (45, 7%) Grupo 2: Imatinib y luego 2ºGITKs debido a intolerancia o fallo 170 p (19, 7%) (12 esquemas de tratamiento secuenciales diferentes con ITKs) Grupo 3: 2ºGITKs en 1ª línea 91 p (13 esquemas secuenciales) (10, 5%) Grupo 4: Interferón alfa y luego ITKs 207 p (24%) (9 esquemas secuenciales). La Figura 1 resume la evolución de diferentes tratamientos alrededor de los 14 años. Última respuesta molecular profunda: con una mediana de seguimiento de 82 meses (1-351 m) desde el diagnóstico, 77 m (1-311 m) desde el primer tratamiento y 70 m (1-191 m) desde el primer tratamiento con ITK. Las tasas de respuesta molecular profunda para cada grupo fueron (G1: DMR 65% MMR 13% No MMR 15%, G2: DMR 46% MMR 24% No MMR 17%, G3: DMR 62% MMR 13% No MMR 12%, G4: DMR 53% MMR 17% No MMR 18%). Supervivencia a largo plazo (SLP o SG): no se encontraron diferencias estadísticas entre los grupos de tratamiento, ya sea desde el diagnóstico, el primer tratamiento o el primer ITK. Alcanzar una respuesta profunda garantiza mejores resultados. Variables predictivas de respuesta: los índices SOKAL, EUTOS, EURO y LT-EUTOS continúan siendo útiles para predecir el resultado a largo plazo. Conclusiones: En el contexto de un registro multicéntrico basado en hospitales, el tratamiento con ITKs es muy variable, con un gran número de secuencias diferentes de ITKs. Con una mediana de seguimiento de 7 años la tasa de respuesta molecular profunda es aproximadamente del 60% en pacientes tratados con imatinib y que no necesitan cambio de ITKs, y en aquellos tratados en 1º línea con 2ºGITKs(a pesar de su corto seguimiento), pero parece menor en pacientes tratados con imatinib que necesitan cambiar a 2ºGITKs. Los resultados de supervivencia fueron similares para todos los grupos

Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks

8 páginas, 3 figuras, 1 tabla.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License.This work has been supported by funds provided by the Local Government Junta de Castilla y León (JCyL, ref. project: CSI07A09), by the Spanish Ministry of Science and Innovation (MICINN - ISCiii, ref. projects: PI061153 and PS09/00843) and by the European Commission Research Grant PSIMEx (ref. FP7-HEALTH-2007-223411).Peer Reviewe

Latin America: the next region for haematopoietic transplant progress

Haematopoietic cell transplant activity in the 28 countries comprising Latin America is poorly defined. We conducted a voluntary survey of members of the Latin American Bone Marrow Transplantation Group regarding transplant activity 2009–2012. Collated responses were compared with data of transplant rates from the Worldwide Network for Blood and Marrow Transplantation for other geographic regions. Several socio-economic variables were analysed to determine correlations with transplant rates. In total, 94 teams from 12 countries reported 11519 transplants including 7033 autotransplants and 4486 allotransplants. Annual activity increased from 2517 transplants in 2009 to 3263 in 2012, a 30% increase. Median transplants rate (transplant per million inhabitants) in 2012 was 64 (autotransplants, median 40; allotransplants, median 24). This rate is substantially lower than that in North America and European regions (482 and 378) but higher than that in the Eastern Mediterranean and Asia Pacific regions (30 and 45). However, the Latin America transplant rate is 5–8-fold lower than that in America and Europe, suggesting a need to increase transplant availability. Transplant team density in Latin America (teams per million population; 1.8) is 3–4-fold lower than that in North America (6.2) or Europe (7.6). Within Latin America, there is substantial diversity in transplant rates by country partially explained by diverse socio-economic variables including per capita gross national income, health expenditure and physician density. These data should help inform future health-care policy in Latin America

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

SummaryBackground 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. Funding Bill & Melinda Gates Foundation