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The CRISPR-Cas9 system provides the ability to edit, repress, activate, or mark any gene (or DNA element) by pairing of a programmable single guide RNA (sgRNA) with a complementary sequence on the DNA target. Here we present a new method for small-molecule control of CRISPR-Cas9 function through insertion of RNA aptamers into the sgRNA. We show that CRISPR-Cas9-based gene repression (CRISPRi) can be either activated or deactivated in a dose-dependent fashion over a >10-fold dynamic range in response to two different small-molecule ligands. Since our system acts directly on each target-specific sgRNA, it enables new applications that require differential and opposing temporal control of multiple genes.

Abstract Managing invasive species with prevention and early‐detection strategies can avert severe ecological and economic impacts. Horizon scanning, an evidence‐based process combining risk screening and consensus building to identify threats, has become a valuable tool for prioritizing invasive species management and prevention. We assembled a working group of experts from academic, government, and nonprofit agencies and organizations, and conducted a multi‐taxa horizon scan for Florida, USA, the first of its kind in North America. Our primary objectives were to identify high‐risk species and their introduction pathways, to detail the magnitude and mechanism of potential impacts, and, more broadly, to demonstrate the utility of horizon scanning. As a means to facilitate future horizon scans, we document the process used to generate the list of taxa for screening. We evaluated 460 taxa for their potential to arrive, establish, and cause negative ecological and socioeconomic impacts, and identified 40 potential invaders, including alewife, zebra mussel, crab‐eating macaque, and red swamp crayfish. Vertebrates and aquatic invertebrates posed the greatest invasion threat, over half of the high‐risk taxa were omnivores, and there was high confidence in the scoring of high‐risk taxa. Common arrival pathways were ballast water, biofouling of vessels, and escape from the pet/aquarium/horticulture trade. Competition, predation, and damage to agriculture/forestry/aquaculture were common impact mechanisms. We recommend full risk analysis for the high‐risk taxa; increased surveillance at Florida's ports, state borders, and high‐risk pathways; and periodic review and revision of the list. Few horizon scans detail the comprehensive methodology (including list‐building), certainty estimates for all scoring categories and the final score, detailed pathways, and the magnitude and mechanism of impact. Providing this information can further inform prevention efforts and can be efficiently replicated in other regions. Moreover, harmonizing methodology can facilitate data sharing and enhance interpretation of results for stakeholders and the general public.

ABSTRACT Purpose: to investigate, examine and synthesize evidence from studies on permanent education for health professionals aimed at the covid-19 pandemic. Methods: six national and international indexed sources will be searched. The review will include studies with any methodological approach, addressing permanent education for health professionals during the covid-19 pandemic. The context of health services in any scenario will be considered - national or international primary, specialized, or hospital healthcare. Final Considerations: research results are expected to reveal the topics approached in permanent health education in various national and international contexts. The review will also list the gains and problems found in various places while applying permanent education as a strategy to fight the covid-19 pandemic.

Abstract Reserve mobilisation and metabolite utilisation were characterised during seed germination and seedling establishment in Pityrocarpa moniliformis, an endospermic legume from Caatinga. Seeds were germinated under controlled conditions for four days and seedlings were transferred to hydroponics and maintained at a greenhouse during four days. Samples were collected at distinct physiological stages and reserves, metabolites, and enzymatic activities were determined in different seedling parts. Galactomannans stored in the endosperm and non-reducing sugars accumulated in the cotyledons were mobilised from seed germination to hypocotyl emergence. During these processes, the accumulation of reducing sugars in the endosperm coincided with an increase in the starch content in the cotyledons and seedling axis, indicating that sugars released from galactomannans may have been utilised in starch biosynthesis. Starch and storage protein mobilisation in the cotyledons occurred later, from hypocotyl elongation to cotyledon expansion. Starch degradation possibly supported the accumulation of starch and soluble sugars in the root, while storage protein hydrolysis was associated with cotyledon greening and first leaf emergence. Accordingly, reserve mobilisation exhibits a biphasic pattern, enabling fast seedling establishment as a physiological strategy to ensure environmental colonisation.

Abstract The Theraphosidae family includes the largest number of species of the Mygalomorphae infraorder, with hundreds of species currently catalogued. However, there is a huge lack on physiologic and even ecologic information available, especially in Brazil, which is the most biodiverse country in the world. Over the years, spiders have been presented as a source of multiple biologically active compounds with basic roles, such as primary defense against pathogenic microorganisms or modulation of metabolic pathways and as specialized hunters. Spider venoms also evolved in order to enable the capture of prey by interaction with a diversity of molecular targets of interest, raising their pharmaceutical potential for the development of new drugs. Among the activities found in compounds isolated from venoms and hemocytes of Brazilian Theraphosidae there are antimicrobial, antifungal, antiparasitic and antitumoral, as well as properties related to proteinase action and neuromuscular blockage modulated by ionic voltage-gated channel interaction. These characteristics are present in different species from multiple genera, which is strong evidence of the important role in spider survival. The present review aims to compile the main results of studies from the last decades on Brazilian Theraphosidae with special focus on results obtained with the crude venom or compounds isolated from both venom and hemocytes, and their physiological and chemical characterization.

ABSTRACT The objective of this study was to monitor and compare runoff at 2.5 and 3.5 years of rehabilitation of a mined bauxite area with clonal planting of Eucalyptus. Seven plots were allocated for collecting runoff and precipitation was recorded with a pluviograph. The physical and environmental factors which interfere with runoff were characterized in both periods and subjected to principal component analysis (PCA) to show the most explanatory factors. The average monthly runoff percentage at 2.5 years was 0.25% (± 0.26%) of precipitation and equal (p-value

We extended the research on autonomy-supportive teaching to universities and examined the relationships between autonomous motivation to teach and autonomy-supportive teaching. Autonomously motivated university instructors were more autonomy-supportive instructors. The freedom to make pedagogical decisions was negatively correlated with external motivation towards teaching. Participants indicated that large class sizes, high teaching loads, publication pressures, and a culture that undervalues effective undergraduate teaching undermined both student learning and their feelings of autonomy. Together these results presents a picture of a subset of university instructors who remained autonomously motivated to teach, irrespective of barriers they experienced from university administrators or policies.

Alzheimer's disease is considered a disconnection syndrome, motivating the use of brain network measures to detect changes in whole-brain resting state functional connectivity (FC). We investigated changes in FC within and among resting state networks (RSN) across four different stages in the Alzheimer's disease continuum. FC changes were examined in two independent cohorts of individuals (84 and 58 individuals, respectively) each comprising control, subjective cognitive decline, mild cognitive impairment and Alzheimer's dementia groups. For each participant, FC was computed as a matrix of Pearson correlations between pairs of time series from 278 gray matter brain regions. We determined significant differences in FC modular organization with two distinct approaches, network contingency analysis and multiresolution consensus clustering. Network contingency analysis identified RSN sub-blocks that differed significantly across clinical groups. Multiresolution consensus clustering identified differences in the stability of modules across multiple spatial scales. Significant modules were further tested for statistical association with memory and executive function cognitive domain scores. Across both analytic approaches and in both participant cohorts, the findings converged on a pattern of FC that varied systematically with diagnosis within the frontoparietal network (FP) and between the FP network and default mode network (DMN). Disturbances of modular organization were manifest as greater internal coherence of the FP network and stronger coupling between FP and DMN, resulting in less segregation of these two networks. Our findings suggest that the pattern of interactions within and between specific RSNs offers new insight into the functional disruption that occurs across the Alzheimer's disease spectrum. Keywords: Alzheimer's disease, Resting state, Brain networks, Functional connectivity, Connectomics

ABSTRACT Several studies have been conducted aiming to explore the commercial potential of the macaúba palm. However, research on the hydrological processes of this crop are scarce. Thus, we aimed to quantify the surface runoff in a macaúba plantation subjected to different crop management techniques, from September 2012 toAugust 2013. We established 10 plots for surface runoff quantification; each plot had a 63-m² area, was delimited by metallic foils and had a gallon to collect runoff water at its outlet. Plots consisted of three treatments and three repetitions, plus one control plot, each having four macaúba plants. Treatments were as follows: treatment one (T1) - with no soil conservation technique being implemented; treatment two (T2) - with a narrow-base terrace 40 cm wide and 30 cm deep; treatment three (T3) - with bean being planted during the rainy months, forming vegetation strips; and control treatment (T0) - with no macaúba plants, with spontaneous vegetation growing throughout the entire plot and with no soil conservation technique being implemented. Surface runoff differed among treatments. T2 was the treatment with lowest runoff and also the one that demanded the highest precipitation volume for surface runoff to occur. Our results indicate that both the cover and the use of soil conservation techniques are closely related to surface runoff, which in turn affects the occurrence of erosion and infiltration.

O conhecimento da diversidade biológica da araneofauna da região amazônica é ainda incipiente, sendo necessário ampliar as pesquisas com esses animais. As aranhas são excelentes objetos de estudo para a avaliação da organização das comunidades animais e da influência do hábitat sobre estas comunidades. O objetivo do presente estudo foi inventariar a comunidade de aranhas em uma pastagem de criação bovina no município de Uruará, Pará. A pesquisa foi desenvolvida no mês de junho de 2014 através de armadilhas pitfall e coletas manuais. Como resultado, foram coletados 99 espécimes distribuídas em seis famílias e 19 morfoespécies. A família com maior abundância foi Araneidae com 63 espécimes, seguida por Anapidae e Anyphaenidae com dez espécimes cada. Através do teste do Qui-quadrado não verificamos diferença significativa entre as metodologias de coletas (p > 0,05), entretanto, as metodologias se complementaram, sendo que os espécimes Araneidae sp7, Theridiidae sp1 e Theridiidae sp3 foram coletados através das armadilhas pitfall, enquanto Araneidae sp5 e Ctenidae sp2 foram amostradas apenas em coletas manuais. O índice de diversidade Shannon mostrou que mesmo o ambiente bastante antroponizado, apresenta uma diversidade relativamente alta quando comparado com outras regiões mais preservadas, entretanto, a curva de rarefação de espécies não se estabilizou, mostrando que deverá ser aplicado um maior esforço amostral em coletas futuras. Palavras-chave: Amazônia, biodiversidade, aranhas. DOI: http://dx.doi.org/10.18561/2179-5746/biotaamazonia.v4n4p98-101

O Programa RECAJ UFMG, originado em 2007, consiste em grupo de estudos, pesquisa e extensão acerca das formas de resolução de conflitos e do acesso à justiça. Orientado pela Professora Adjunta da Faculdade de Direito da Universidade Federal de Minas Gerais, Dra. Adriana Goulart de Sena Orsini, o RECAJ UFMG, composto por alunos e ex?alunos de graduação e pós? graduação, dedica suas atividades ao estudo e à difusão social dos diferentes métodos de solução de controvérsias, com destaque para as formas alternativas e pacíficas de resolução de conflitos. Ao longo de sua existência, o Programa já promoveu, dentre outros, seminários, pesquisas e uma cartilha didática em parceria com o Ministério da Educação intitulada “Formas de resolução de conflitos e acesso à justiça”.Boaventura de Souza Santos (2004) considera ser inerente à universidade pública a função de estabelecer uma relação dialógica e mutuamente benéfica entre o meio acadêmico e comunidade em geral . Por meio da extensão universitária, o Programa RECAJ criou em 2011 o Projeto “RECAJ nas Escolas”, compreendendo ser possível e necessária a realização de parcerias autênticas entre as diferentes instituições de ensino ? públicas e privadas – nas quais se enseje relações dialógicas entre o ensino fundamental, médio e superior. O enfoque pluralista, interdisciplinar e construtivista do referido projeto, encontrou, nas obras pedagógico?educacionais de Paulo Freire, um importante norte teórico para o desenvolvimento dos trabalhos junto às crianças e aos adolescentes.

HIV infection, through the actions of viral accessory protein Nef, impairs activity of cholesterol transporter ABCA1, inhibiting cholesterol efflux from macrophages and elevating the risk of atherosclerosis. Nef also induces lipid raft formation. In this study, we demonstrate that these activities are tightly linked and affect macrophage function and HIV replication. Nef stimulated lipid raft formation in macrophage cell line RAW 264.7, and lipid rafts were also mobilized in HIV-1-infected human monocyte-derived macrophages. Nef-mediated transfer of cholesterol to lipid rafts competed with the ABCA1-dependent pathway of cholesterol efflux, and pharmacological inhibition of ABCA1 functionality or suppression of ABCA1 expression by RNAi increased Nef-dependent delivery of cholesterol to lipid rafts. Nef reduced cell-surface accessibility of ABCA1 and induced ABCA1 catabolism via the lysosomal pathway. Despite increasing the abundance of lipid rafts, expression of Nef impaired phagocytic functions of macrophages. The infectivity of the virus produced in natural target cells of HIV-1 negatively correlated with the level of ABCA1. These findings demonstrate that Nef-dependent inhibition of ABCA1 is an essential component of the viral replication strategy and underscore the role of ABCA1 as an innate anti-HIV factor.

Multilayer capsules templated on decomposable vaterite CaCO3 crystals are widely used as vehicles for drug delivery. The capsule represents typically not a hollow but matrix-like structure due to polymer diffusion into the porous crystals during multilayer deposition. The capsule formation mechanism is not well-studied but its understanding is crucial to tune capsule structure for a proper drug release performance. This study proposes new approach to noninvasively probe and adjust internal capsule structure. Polymer capsules made of poly(styrene-sulfonate) (PSS) and poly(diallyldimethylammonium chloride) (PDAD) have been stained with fluorescence dye rhodamine 6G. Physical-chemical aspects of intermolecular interactions required to validate the approach and adjust capsule structure are addressed. The capsules consist of a defined shell (typically 0.5⁻2 µm) and an internal matrix of PSS-PDAD complex (typically 10⁻40% of a total capsule volume). An increase of ionic strength and polymer deposition time leads to the thickening of the capsule shell and formation of a denser internal matrix, respectively. This is explained by effects of a polymer conformation and limitations in polymer diffusion through the crystal pores. We believe that the design of the capsules with desired internal structure will allow achieving effective encapsulation and controlled/programmed release of bioactives for advanced drug delivery applications.

The integrated approach of weed management refers to a combination of direct and indirect methods in order to limit chemical applications. In oilseed rape, sunflower and soybean, mechanical weed control can be an alternative or a complement to herbicides and should take progressively a larger place in the direct weed control options, taking into account of the policy of restriction of chemical use. CETIOM launched a research program to assess, in different backgrounds, the selectivity and the efficacy of three tools, used either alone or combined with herbicides: the rotary hoe, the finger weeder and the in-row hoe. As an alternative or a complement to herbicides, mechanical weed control strategies were selective enough for oil crops if they were used in appropriate conditions (crop stage, soil surface moisture, adjustments of the tools). Linked with long term preventive measures to maintain weed population at a low level, they could be as efficient as herbicides but with an irregularity and strongly dependent on weed development stage. These techniques could be economically competitive but require often more working time. Mechanical management can thus be an answer to some of the new requirements of the agricultural context but operator skill, experience and knowledge are critical to success. Introducing these weed control methods in a farm requires a deep change of state of mind which appears today as a major restraint for the farmers.

INRA has initiated a comprehensive approach to food loss and waste for all the plant and animal sectors, from field to distribution. In this study, all comestibles that leave the human food chain and are not recycled into animal feed are considered as losses and waste. The main French oilseed sectors are studied (rapeseed, sunflower and soya, as well as tofu). In order to identify the key sources of loss, all of the various steps in the process of the oleaginous production chain are described, from harvesting through to distribution, including storage, transport, crushing, refining and packaging. For tofu, the study also examines the chain from harvest through to distribution, including as soy milk and tofu paste. Published data are lacking; they were therefore primarily collected directly from professionals in the sectors concerned. Although oilseeds and vegetable oils are apt to have a relatively long shelf-life compared to other products, losses of vegetable oil from field to distribution are substantial (approximately 71.4 kT, equivalent to 10% of the amount consumed in France). We establish that the principal steps giving rise to losses are harvesting and refining. Total losses in French rapeseed oil, sunflower and soybean were estimated at 9.8%, 7.0% and 6.0% of their respective total potential production, worth approximately 50.6, 14.3 and 6.5 € million and equivalent to the annual consumption of approximately 3 030 000, 855 000 and 390 000 people. In the case of tofu, harvest is the most important area of loss. Total losses of tofu are equivalent to 8.2% of potential production. We discuss potential measures to improve the efficiency of the individual steps of French oilseed production.

Oilseed rape seed loss during harvest can cause subsequent unwanted gene flow and thus give raise to management difficulties in order to keep segmented different productions. Furthermore, seed loss reduces benefits of producers. This loss was evaluated in different conditions and trials carried out in three French regions from 2002 to 2004. Seed loss was divided into three categories : before harvest, under the cutter bar and behind the combine harvester. Total loss represented on average 8,2 % of the harvest for grain water content under 12 %. But this figure does not take an important variability into account. Indeed, an advanced cutter bar could reduce loss by 80 % and grain humidity at harvest plays an important part in the total loss level and its distribution. Before harvest low grain water content could make seed loss more sensitive to climatic events. Under the cutter bar, seed loss is inversely proportional to grain water content. On the contrary, it increases with grain water content behind the combine, due to loss in green siliquae. These studies can help improving advice to producers and contribute to improve gene flow models.

The default network is a system of brain areas that are engaged when the mind is not involved in goal-directed activity. Most previous studies of age-related changes in default mode processing have used verbal tasks. We studied non-verbal spatial tasks that vary in difficulty. We presented old and young participants with two spatial judgment tasks: an easy categorical judgment and a more demanding coordinate judgment. We report that (a) Older adults show markedly less default network modulation than young on the demanding spatial task, but there is age equivalence on the easy task; (b) This Age x Task interaction is restricted to the default network: Brain areas that are deactivated by the tasks, but that are outside the default network, show no interaction; (c) Young adults exhibit significantly stronger functional connectivity among posterior regions of the default network compared with older adults, whereas older adults exhibit stronger connectivity between medial prefrontal cortex and other sites; and (d) The relationship of default activity to reaction time performance on the spatial tasks is mediated by age: in old adults, those who deactivate the default network most also perform best, whereas the opposite is true in younger adults. These results extend the findings of age-related changes in default mode processing and connectivity to visuo-spatial tasks and demonstrate that the results are specific to the default network.

Abstract Background The amount of lead in the environment has decreased significantly in recent years, and so did exposure. However, there is no known safe exposure level and, therefore, the exposure of children to lead, although low, remains a major public health issue. With the lower levels of exposure, it is becoming more difficult to identify lead sources and new approaches may be required for preventive action. This study assessed the usefulness of lead isotope ratios for identifying sources of lead using data from a nationwide sample of French children aged from six months to six years with blood lead levels ≥25 μg/L. Methods Blood samples were taken from 125 children, representing about 600,000 French children; environmental samples were taken from their homes and personal information was collected. Lead isotope ratios were determined using quadrupole ICP-MS (inductively coupled plasma - mass spectrometry) and the isotopic signatures of potential sources of exposure were matched with those of blood in order to identify the most likely sources. Results In addition to the interpretation of lead concentrations, lead isotope ratios were potentially of use for 57% of children aged from six months to six years with blood lead level ≥ 25 μg/L (7% of overall children in France, about 332,000 children), with at least one potential source of lead and sufficiently well discriminated lead isotope ratios. Lead isotope ratios revealed a single suspected source of exposure for 32% of the subjects and were able to eliminate at least one unlikely source of exposure for 30% of the children. Conclusions In France, lead isotope ratios could provide valuable additional information in about a third of routine environmental investigations.

Background: Advanced liver disease due to hepatitis C virus (HCV) is a leading cause of human immunodeficiency virus (HIV)-related morbidity and mortality. There remains a need to develop noninvasive predictors of clinical outcomes in persons with HIV/HCV coinfection., Methods: We conducted a nested case-control study in 126 patients with HIV/HCV and utilized multiple quantitative metabolomic assays to identify a prognostic profile that predicts end-stage liver disease (ESLD) events including ascites, hepatic encephalopathy, hepatocellular carcinoma, esophageal variceal bleed, and spontaneous bacterial peritonitis. Each analyte class was included in predictive modeling, and area under the receiver operator characteristic curves (AUC) and accuracy were determined., Results: The baseline model including demographic and clinical data had an AUC of 0.79. Three models (baseline plus amino acids, lipid metabolites, or all combined metabolites) had very good accuracy (AUC, 0.84-0.89) in differentiating patients at risk of developing an ESLD complication up to 2 years in advance. The all combined metabolites model had sensitivity 0.70, specificity 0.85, positive likelihood ratio 4.78, and negative likelihood ratio 0.35., Conclusions: We report that quantification of a novel set of metabolites may allow earlier identification of patients with HIV/HCV who have the greatest risk of developing ESLD clinical events., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Protein binding to small molecules is fundamental to many biological processes, yet it remains challenging to predictively design this functionality de novo. Current state-of-the-art computational design methods typically rely on existing small molecule binding sites or protein scaffolds with existing shape complementarity for a target ligand. Here we introduce new methods that utilize pools of discrete contacts between protein side chains and defined small molecule ligand substructures (ligand fragments) observed in the Protein Data Bank. We use the Rosetta Molecular Modeling Suite to recombine protein side chains in these contact pools to generate hundreds of thousands of energetically favorable binding sites for a target ligand. These composite binding sites are built into existing scaffold proteins matching the intended binding site geometry with high accuracy. In addition, we apply pools of side chain rotamers interacting with the target ligand to augment Rosetta's conventional design machinery and improve key metrics known to be predictive of design success. We demonstrate that our method reliably builds diverse binding sites into different scaffold proteins for a variety of target molecules. Our generalizable de novo ligand binding site design method provides a foundation for versatile design of protein to interface previously unattainable molecules for applications in medical diagnostics and synthetic biology., Competing Interests: The authors have declared that no competing interests exist.

Objectives: To assess the association of a clinical decision support (CDS) algorithm for hospital discharge disposition with spending, readmissions, and postdischarge emergency department (ED) use., Study Design: A retrospective study in a cohort of fee-for-service Medicare patients 65 years or older linked to a database of patients receiving CDS., Methods: We evaluated (1) patients whose discharge disposition was concordant with the CDS recommendation versus those whose disposition was not and (2) patients receiving CDS for discharge disposition versus those not receiving CDS, regardless of concordance. Outcomes were spending over a 90-day episode, 90-day readmissions, and postdischarge ED utilization not associated with a readmission., Results: Analysis of concordant versus discordant cases showed decreased spending for concordant cases ($860 savings; 95% CI, $162-$1558; P = .016), a decrease in readmissions (adjusted odds ratio [OR], 0.920; 95% CI, 0.850-0.995; P = .038), and no change in rate of postdischarge ED use (adjusted OR, 0.990; 95% CI, 0.882-1.110; P = .858). Analysis of patients receiving CDS versus not receiving CDS showed no significant difference in spending ($221 savings; 95% CI, -$115 to $557; P = .198), ED use (adjusted OR, 0.959; 95% CI, 0.908-1.012; P = .128), or readmission rate (adjusted OR, 1.004; 95% CI, 0.966-1.043; P = .840)., Conclusions: Following the recommendation of a CDS algorithm for hospital discharge disposition was associated with lower spending, fewer readmissions, and no change in ED use over a 90-day episode of care.

Purpose: In the interferon era of hepatitis C virus (HCV) therapies, genotype/subtype, cirrhosis, prior treatment failure, sex, and race predicted relapse. Our objective is to validate a targeted proteomics platform of 17 peptides to predict sustained virologic response (SVR)., Experimental Design: Stored plasma from three, open-label, trials of HIV/HCV-coinfected subjects receiving interferon-containing regimens is identified. LC-MS/MS is used to quantitate the peptides directly from plasma, and IL28B genotyping is completed using stored peripheral blood mononuclear cells (PBMC). A logistic regression model is built to analyze the probability of SVR using responders and nonresponders to interferon-based regimens., Results: The cohort (N = 35) is predominantly black (51.4%), male (86%), and with median age 48 years. Most patients achieve SVR (54%). Using multivariable models, it is verified that three human corticosteroid binding globulin (CBG) peptides are predictive of SVR in patients with the unfavorable IL28B genotypes (CT/TT). The model performs better than IL28B alone, with an area under the curve of 0.870., Conclusions and Clinical Relevance: In HIV/HCV-coinfected patients, three human CBG peptides that accurately predict treatment response with interferon-based therapy are identified. This study suggests that a stepwise approach combining a genetic predictor followed by targeted proteomics can improve the accuracy of clinical decision-making., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Computationally modeling changes in binding free energies upon mutation (interface ΔΔ G) allows large-scale prediction and perturbation of protein-protein interactions. Additionally, methods that consider and sample relevant conformational plasticity should be able to achieve higher prediction accuracy over methods that do not. To test this hypothesis, we developed a method within the Rosetta macromolecular modeling suite (flex ddG) that samples conformational diversity using "backrub" to generate an ensemble of models and then applies torsion minimization, side chain repacking, and averaging across this ensemble to estimate interface ΔΔ G values. We tested our method on a curated benchmark set of 1240 mutants, and found the method outperformed existing methods that sampled conformational space to a lesser degree. We observed considerable improvements with flex ddG over existing methods on the subset of small side chain to large side chain mutations, as well as for multiple simultaneous non-alanine mutations, stabilizing mutations, and mutations in antibody-antigen interfaces. Finally, we applied a generalized additive model (GAM) approach to the Rosetta energy function; the resulting nonlinear reweighting model improved the agreement with experimentally determined interface ΔΔ G values but also highlighted the necessity of future energy function improvements.

Sex differences in Alzheimer's disease (AD) biology and progression are not yet fully characterized. The goal of this study is to examine the effect of sex on cognitive progression in subjects with high likelihood of mild cognitive impairment (MCI) due to Alzheimer's and followed up to 10 years in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cerebrospinal fluid total-tau and amyloid-beta (Aβ42) ratio values were used to sub-classify 559 MCI subjects (216 females, 343 males) as having "high" or "low" likelihood for MCI due to Alzheimer's. Data were analyzed using mixed-effects models incorporating all follow-ups. The worsening from baseline in Alzheimer's Disease Assessment Scale-Cognitive score (mean, SD) (9 ± 12) in subjects with high likelihood of MCI due to Alzheimer's was markedly greater than that in subjects with low likelihood (1 ± 6, p < 0.0001). Among MCI due to AD subjects, the mean worsening in cognitive score was significantly greater in females (11.58 ± 14) than in males (6.87 ± 11, p = 0.006). Our findings highlight the need to further investigate these findings in other populations and develop sex specific timelines for Alzheimer's disease progression.

Little is known about the reproductive effects of paternal cannabis exposure. We evaluated associations between cannabis or tetrahydrocannabinol (THC) exposure and altered DNA methylation in sperm from humans and rats, respectively. DNA methylation, measured by reduced representation bisulfite sequencing, differed in the sperm of human users from non-users by at least 10% at 3,979 CpG sites. Pathway analyses indicated Hippo Signaling and Pathways in Cancer as enriched with altered genes (Bonferroni p < 0.02). These same two pathways were also enriched with genes having altered methylation in sperm from THC-exposed versus vehicle-exposed rats (p < 0.01). Data validity is supported by significant correlations between THC exposure levels in humans and methylation for 177 genes, and substantial overlap in THC target genes in rat sperm (this study) and genes previously reported as having altered methylation in the brain of rat offspring born to parents both exposed to THC during adolescence. In humans, cannabis use was also associated with significantly lower sperm concentration. Findings point to possible pre-conception paternal reproductive risks associated with cannabis use.

Background: An estimated 43% of children younger than 5 years of age are at elevated risk of failing to achieve their human potential. In response, the World Health Organization and UNICEF developed Care for Child Development (CCD), based on the science of child development, to improve sensitive and responsive caregiving and promote the psychosocial development of young children., Methods: In 2015, the World Health Organization and UNICEF identified sites where CCD has been implemented and sustained. The sites were surveyed, and responses were followed up by phone interviews. Project reports provided information on additional sites, and a review of published studies was undertaken to document the effectiveness of CCD for improving child and family outcomes, as well as its feasibility for implementation in resource-constrained communities., Results: The inventory found that CCD had been integrated into existing services in diverse sectors in 19 countries and 23 sites, including child survival, health, nutrition, infant day care, early education, family and child protection and services for children with disabilities. Published and unpublished evaluations have found that CCD interventions can improve child development, growth and health, as well as responsive caregiving. It has also been reported to reduce maternal depression, a known risk factor for poor pregnancy outcomes and poor child health, growth and development. Although CCD has expanded beyond initial implementation sites, only three countries reported having national policy support for integrating CCD into health or other services., Conclusions: Strong interest exists in many countries to move beyond child survival to protect and support optimal child development. The United Nations Sustainable Development Goals depend on children realizing their potential to build healthy and emotionally, cognitively and socially competent future generations. More studies are needed to guide the integration of the CCD approach under different conditions. Nevertheless, the time is right to provide for the scale-up of CCD as part of services for families and children., (© 2017 The Authors. Child: Care, Health and Development Published by John Wiley & Sons Ltd.)

Objectives: To provide an accurate, web-based tool for stratifying patients with atrial fibrillation to facilitate decisions on the potential benefits/risks of anticoagulation, based on mortality, stroke and bleeding risks., Design: The new tool was developed, using stepwise regression, for all and then applied to lower risk patients. C-statistics were compared with CHA 2 DS 2 -VASc using 30-fold cross-validation to control for overfitting. External validation was undertaken in an independent dataset, Outcome Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF)., Participants: Data from 39 898 patients enrolled in the prospective GARFIELD-AF registry provided the basis for deriving and validating an integrated risk tool to predict stroke risk, mortality and bleeding risk., Results: The discriminatory value of the GARFIELD-AF risk model was superior to CHA 2 DS 2 -VASc for patients with or without anticoagulation. C-statistics (95% CI) for all-cause mortality, ischaemic stroke/systemic embolism and haemorrhagic stroke/major bleeding (treated patients) were: 0.77 (0.76 to 0.78), 0.69 (0.67 to 0.71) and 0.66 (0.62 to 0.69), respectively, for the GARFIELD-AF risk models, and 0.66 (0.64-0.67), 0.64 (0.61-0.66) and 0.64 (0.61-0.68), respectively, for CHA 2 DS 2 -VASc (or HAS-BLED for bleeding). In very low to low risk patients (CHA 2 DS 2 -VASc 0 or 1 (men) and 1 or 2 (women)), the CHA 2 DS 2 -VASc and HAS-BLED (for bleeding) scores offered weak discriminatory value for mortality, stroke/systemic embolism and major bleeding. C-statistics for the GARFIELD-AF risk tool were 0.69 (0.64 to 0.75), 0.65 (0.56 to 0.73) and 0.60 (0.47 to 0.73) for each end point, respectively, versus 0.50 (0.45 to 0.55), 0.59 (0.50 to 0.67) and 0.55 (0.53 to 0.56) for CHA 2 DS 2 -VASc (or HAS-BLED for bleeding). Upon validation in the ORBIT-AF population, C-statistics showed that the GARFIELD-AF risk tool was effective for predicting 1-year all-cause mortality using the full and simplified model for all-cause mortality: C-statistics 0.75 (0.73 to 0.77) and 0.75 (0.73 to 0.77), respectively, and for predicting for any stroke or systemic embolism over 1 year, C-statistics 0.68 (0.62 to 0.74)., Conclusions: Performance of the GARFIELD-AF risk tool was superior to CHA 2 DS 2 -VASc in predicting stroke and mortality and superior to HAS-BLED for bleeding, overall and in lower risk patients. The GARFIELD-AF tool has the potential for incorporation in routine electronic systems, and for the first time, permits simultaneous evaluation of ischaemic stroke, mortality and bleeding risks., Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF (NCT01090362) and for ORBIT-AF (NCT01165710)., Competing Interests: Competing interests: KAAF reports grants and personal fees from Bayer, and Johnson and Johnson, personal fees from Lilly, grants and personal fees from AstraZeneca and personal fees from Sanofi/Regeneron outside the submitted work. JEL and KSP have provided statistical support and thought leadership for the Thrombosis Research Institute, during the conduct of the study, and KSP has received personal fees from Bayer outside the submitted work. J-PB reports personal fees from Aspen outside the submitted work. AJC is an advisor to Bayer, Boehringer Ingelheim, Pfizer/BMS and Daiichi Sankyo. DAF reports personal fees from Bayer outside the submitted work. SZG reports grants from BiO2 Medical, Boehringer-Ingelheim, Bristol Meyers Squibb, BTG EKOS, Daiichi Sankyo, National Heart Lung and Blood Institute of the National Institutes of Health, Janssen and Thrombosis Research Group and personal fees from Bayer, Boehringer-Ingelheim, Bristol Meyers Squibb, Daiichi Sankyo, Janssen and Portola outside the submitted work. SG reports personal fees from Bayer, grants from Sanofi, grants from Pfizer, personal fees from Daiichi-Sankyo, personal fees from AstraZeneca during the conduct of the study and grants from Bayer outside the submitted work. SH reports personal fees from Aspen, Bayer AG, BMS, Daiichi-Sankyo, Pfizer and Sanofi outside the submitted work. WH reports personal fees from Bayer during the conduct of the study. GK reports grants from Bayer during the conduct of the study. LGM reports grants and personal fees from Bayer AG during the conduct of the study, and grants from Boehringer Ingelheim, grants and personal fees from Pfizer and personal fees from Daiichi Sankyo outside the submitted work. FM reports grants and other from Bayer AG during the conduct of the study, and other from Bayer AG outside the submitted work. FM is an employee of Bayer AG. JP has nothing to disclose. AGGT reports consultant fees from Bayer AG during the conduct of the study. FWAV reports personal fees from Boehringer-Ingelheim, Bayer AG, BMS/Pfizer and Daiichi-Sankyo during the conduct of the study and personal fees from AstraZeneca outside the submitted work. AKK reports grants and personal fees from Bayer AG, Boehringer-Ingelheim Pharma, Daiichi Sankyo Europe, Sanofi SA and Janssen Pharma outside the submitted work., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

HMG-CoA reductase inhibitors (or "statins") are important and commonly used medications to lower cholesterol and prevent cardiovascular disease. Nearly half of patients stop taking statin medications one year after they are prescribed leading to higher cholesterol, increased cardiovascular risk, and costs due to excess hospitalizations. Identifying which patients are at highest risk for not adhering to long-term statin therapy is an important step towards individualizing interventions to improve adherence. Electronic health records (EHR) are an increasingly common source of data that are challenging to analyze but have potential for generating more accurate predictions of disease risk. The aim of this study was to build an EHR based model for statin adherence and link this model to biologic and clinical outcomes in patients receiving statin therapy. We gathered EHR data from the Military Health System which maintains administrative data for active duty, retirees, and dependents of the United States armed forces military that receive health care benefits. Data were gathered from patients prescribed their first statin prescription in 2005 and 2006. Baseline billing, laboratory, and pharmacy claims data were collected from the two years leading up to the first statin prescription and summarized using non-negative matrix factorization. Follow up statin prescription refill data was used to define the adherence outcome (> 80 percent days covered). The subsequent factors to emerge from this model were then used to build cross-validated, predictive models of 1) overall disease risk using coalescent regression and 2) statin adherence (using random forest regression). The predicted statin adherence for each patient was subsequently used to correlate with cholesterol lowering and hospitalizations for cardiovascular disease during the 5 year follow up period using Cox regression. The analytical dataset included 138 731 individuals and 1840 potential baseline predictors that were reduced to 30 independent EHR "factors". A random forest predictive model taking patient, statin prescription, predicted disease risk, and the EHR factors as potential inputs produced a cross-validated c-statistic of 0.736 for classifying statin non-adherence. The addition of the first refill to the model increased the c-statistic to 0.81. The predicted statin adherence was independently associated with greater cholesterol lowering (correlation = 0.14, p < 1e-20) and lower hospitalization for myocardial infarction, coronary artery disease, and stroke (hazard ratio = 0.84, p = 1.87E-06). Electronic health records data can be used to build a predictive model of statin adherence that also correlates with statins' cardiovascular benefits.

Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.

Introduction: The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance., Methods: Fasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted., Results: Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and α-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for Aβ 1-42 , tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease., Discussion: Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery., (Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Objective: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts., Materials and Methods: We identified EHR-based diabetes phenotype definitions that were developed for various purposes by a variety of users, including academic medical centers, Medicare, the New York City Health Department, and pharmacy benefit managers. We applied these definitions to a sample of 173 503 patients with records in the Duke Health System Enterprise Data Warehouse and at least 1 visit over a 5-year period (2007-2011). Of these patients, 22 679 (13%) met the criteria of 1 or more of the selected diabetes phenotype definitions. A statistically balanced sample of these patients was selected for chart review by clinical experts to determine the presence or absence of type 2 diabetes in the sample., Results: The sensitivity (62-94%) and specificity (95-99%) of EHR-based type 2 diabetes phenotypes (compared with the gold standard ADA criteria via chart review) varied depending on the component criteria and timing of observations and measurements., Discussion and Conclusions: Researchers using EHR-based phenotype definitions should clearly specify the characteristics that comprise the definition, variations of ADA criteria, and how different phenotype definitions and components impact the patient populations retrieved and the intended application. Careful attention to phenotype definitions is critical if the promise of leveraging EHR data to improve individual and population health is to be fulfilled., (© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Scope: Nutrigenomics is a rapidly expanding field that elucidates the link between diet-genome interactions. Recent evidence demonstrates that regulation of the epigenome, and in particular inhibition of histone deacetylases (HDACs), impact pathogenetic mechanisms involved in chronic disease. Few studies, to date, have screened libraries of bioactive compounds that act as epigenetic modifiers. This study screened a library of 131 natural compounds to determine bioactive compounds that inhibit Zn-dependent HDAC activity., Methods and Results: Using class-specific HDAC substrates, we screened 131 natural compounds for HDAC activity in bovine cardiac tissue. From this screen, we identified 18 bioactive compound HDAC inhibitors. Using our class-specific HDAC substrates, we next screened these 18 bioactive compounds against recombinant HDAC proteins. Consistent with inhibition of HDAC activity, these compounds were capable of inhibiting activity of individual HDAC isoforms. Lastly, we report that treatment of H9c2 cardiac myoblasts with bioactive HDAC inhibitors was sufficient to increase lysine acetylation as assessed via immunoblot., Conclusion: This study provided the first step in identifying multiple bioactive compound HDAC inhibitors. Taken together, this report sets the stage for future exploration of these bioactive compounds as epigenetic regulators to potentially ameliorate chronic disease., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Infection of respiratory mucosa with viral pathogens triggers complex immunologic events in the affected host. We sought to characterize this response through proteomic analysis of nasopharyngeal lavage in human subjects experimentally challenged with influenza A/H3N2 or human rhinovirus, and to develop targeted assays measuring peptides involved in this host response allowing classification of acute respiratory virus infection. Unbiased proteomic discovery analysis identified 3285 peptides corresponding to 438 unique proteins, and revealed that infection with H3N2 induces significant alterations in protein expression. These include proteins involved in acute inflammatory response, innate immune response, and the complement cascade. These data provide insights into the nature of the biological response to viral infection of the upper respiratory tract, and the proteins that are dysregulated by viral infection form the basis of signature that accurately classifies the infected state. Verification of this signature using targeted mass spectrometry in independent cohorts of subjects challenged with influenza or rhinovirus demonstrates that it performs with high accuracy (0.8623 AUROC, 75% TPR, 97.46% TNR). With further development as a clinical diagnostic, this signature may have utility in rapid screening for emerging infections, avoidance of inappropriate antibacterial therapy, and more rapid implementation of appropriate therapeutic and public health strategies., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Building on long-term benefits of early intervention (Paper 2 of this Series) and increasing commitment to early childhood development (Paper 1 of this Series), scaled up support for the youngest children is essential to improving health, human capital, and wellbeing across the life course. In this third paper, new analyses show that the burden of poor development is higher than estimated, taking into account additional risk factors. National programmes are needed. Greater political prioritisation is core to scale-up, as are policies that afford families time and financial resources to provide nurturing care for young children. Effective and feasible programmes to support early child development are now available. All sectors, particularly education, and social and child protection, must play a role to meet the holistic needs of young children. However, health provides a critical starting point for scaling up, given its reach to pregnant women, families, and young children. Starting at conception, interventions to promote nurturing care can feasibly build on existing health and nutrition services at limited additional cost. Failure to scale up has severe personal and social consequences. Children at elevated risk for compromised development due to stunting and poverty are likely to forgo about a quarter of average adult income per year, and the cost of inaction to gross domestic product can be double what some countries currently spend on health. Services and interventions to support early childhood development are essential to realising the vision of the Sustainable Development Goals., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Influenza infection is associated with myocardial infarction (MI), suggesting that respiratory viral infection may induce biologic pathways that contribute to MI. We tested the hypotheses that 1) a validated blood gene expression signature of respiratory viral infection (viral GES) was associated with MI and 2) respiratory viral exposure changes levels of a validated platelet gene expression signature (platelet GES) of platelet function in response to aspirin that is associated with MI., Methods: A previously defined viral GES was projected into blood RNA data from 594 patients undergoing elective cardiac catheterization and used to classify patients as having evidence of viral infection or not and tested for association with acute MI using logistic regression. A previously defined platelet GES was projected into blood RNA data from 81 healthy subjects before and after exposure to four respiratory viruses: Respiratory Syncytial Virus (RSV) (n=20), Human Rhinovirus (HRV) (n=20), Influenza A virus subtype H1N1 (H1N1) (n=24), Influenza A Virus subtype H3N2 (H3N2) (n=17). We tested for the change in platelet GES with viral exposure using linear mixed-effects regression and by symptom status., Results: In the catheterization cohort, 32 patients had evidence of viral infection based upon the viral GES, of which 25% (8/32) had MI versus 12.2% (69/567) among those without evidence of viral infection (OR 2.3; CI [1.03-5.5], p=0.04). In the infection cohorts, only H1N1 exposure increased platelet GES over time (time course p-value = 1e-04)., Conclusions: A viral GES of non-specific, respiratory viral infection was associated with acute MI; 18% of the top 49 genes in the viral GES are involved with hemostasis and/or platelet aggregation. Separately, H1N1 exposure, but not exposure to other respiratory viruses, increased a platelet GES previously shown to be associated with MI. Together, these results highlight specific genes and pathways that link viral infection, platelet activation, and MI especially in the case of H1N1 influenza infection.

Enzyme active site residues are often highly conserved, indicating a significant role in function. In this study we quantitate the functional contribution for all conserved molecular interactions occurring within a Michaelis complex for mannitol 2-dehydrogenase derived from Pseudomonas fluorescens (pfMDH). Through systematic mutagenesis of active site residues, we reveal that the molecular interactions in pfMDH mediated by highly conserved residues not directly involved in reaction chemistry can be as important to catalysis as those directly involved in the reaction chemistry. This quantitative analysis of the molecular interactions within the pfMDH active site provides direct insight into the functional role of each molecular interaction, several of which were unexpected based on canonical sequence conservation and structural analyses., (© 2015 The Protein Society.)

Background & Aims: Noninvasive tests cannot differentiate between adjacent stages of fibrosis, which limits assessment of disease progression and regression during therapy. We investigated whether levels of cytokines and extracellular matrix proteins in serum and biopsy samples can be used to determine actual stage of liver fibrosis in patients with chronic hepatitis C (CHC) and in prognosis., Methods: We collected data from 383 treatment-naive patients with CHC from the Duke Hepatology Clinical Research Database and Biorepository, from 2006 through 2009, for use in the training set. Serum samples were obtained from 100 individuals without CHC (controls). We selected 37 serum biomarkers for customized array analysis by using the SearchLight multiplex sandwich enzyme-linked immunosorbent assay. Data from 434 treatment-naive patients with CHC, which were obtained from the Trent HCV cohort, were used in the validation analysis. Multivariable modeling, marker selection, and validation included randomForest and Obuchowski measures, with independent comparison with FibroSURE., Results: Four serum markers (levels of hyaluronic acid, vascular cell adhesion molecule 1, alpha-2 macroglobulin, and retinol-binding protein 4) and age associated with fibrosis stage (F0-1, F2-3, or F4); these had Obuchowski measures of 0.85-0.89, with misclassification rates of 38% and 29% in training and validation sets, compared with 50% for the FibroSURE test. In the training set, area under the curve values for the multiplex markers were similar to those from the FibroSURE test: stages F0 vs F1 (0.51 vs 0.53), F1 vs F2 (0.60 vs 0.59), F2 vs F3 (0.69 vs 0.72), and F3 vs F4 (0.51 vs 0.52). Area under the curve values were similar in the validation cohort. In longitudinal analyses of 133 paired biopsies, 9 markers (level of alanine aminotransferase, γ-glutamyltransferase, hyaluronic acid, intracellular adhesion molecule 1, interleukin 4, CXCL10, CXCL9, and vascular cell adhesion molecule 1) were associated with change in the histologic activity index (P values ranging from .000 to .049), and 4 (granulocyte-macrophage colony-stimulating factor, interleukin 12, interleukin 2, and matrix metalloproteinase 13) were associated with a change in fibrosis stage (P values ranging from .001 to .042)., Conclusions: We identified serum biomarkers that can be measured by multiplex enzyme-linked immunosorbent assay to determine levels of fibrosis in patients with CHC, although misclassification is frequent and results are comparable with those from the FibroSURE test. Changes in protein levels in biopsy samples were associated with progression of fibrosis in patients., (Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Background: The application of next-generation sequencing technology to gene expression quantification analysis, namely, RNA-Sequencing, has transformed the way in which gene expression studies are conducted and analyzed. These advances are of particular interest to researchers studying organisms with missing or incomplete genomes, as the need for knowledge of sequence information is overcome. De novo assembly methods have gained widespread acceptance in the RNA-Seq community for organisms with no true reference genome or transcriptome. While such methods have tremendous utility, computational cost is still a significant challenge for organisms with large and complex genomes., Results: In this manuscript, we present a comparison of four reference-based mapping methods for non-human primate data. We utilize TopHat2 and GSNAP for mapping to the human genome, and Bowtie2 and Stampy for mapping to the human genome and transcriptome for a total of six mapping approaches. For each of these methods, we explore mapping rates and locations, number of detected genes, correlations between computed expression values, and the utility of the resulting data for differential expression analysis., Conclusions: We show that reference-based mapping methods indeed have utility in RNA-Seq analysis of mammalian data with no true reference, and the details of mapping methods should be carefully considered when doing so. Critical algorithm features include short seed sequences, the allowance of mismatches, and the allowance of gapped alignments in addition to splice junction gaps. Such features facilitate sensitive alignment of non-human primate RNA-Seq data to a human reference.

Pneumococcal pneumonia is a leading cause of bacterial infection and death worldwide. Current diagnostic tests for detecting Streptococcus pneumoniae can be unreliable and can mislead clinical decision-making and treatment. To address this concern, we developed a preclinical model of pneumococcal pneumonia in nonhuman primates useful for identifying novel biomarkers, diagnostic tests, and therapies for human S. pneumoniae infection. Adult colony-bred baboons (n = 15) were infected with escalating doses of S. pneumoniae (Serotype 19A-7). We characterized the pathophysiological and serological profiles of healthy and infected animals over 7 days. Pneumonia was prospectively defined by the presence of three criteria: (1) change in white blood cell count, (2) isolation of S. pneumoniae from bronchoalveolar lavage fluid (BALF) or blood, and (3) concurrent signs/symptoms of infection. Animals given 10(9) CFU consistently met our definition and developed a phenotype of tachypnea, tachycardia, fever, hypoxemia, and radiographic lobar infiltrates at 48 hours. BALF and plasma cytokines, including granulocyte colony-stimulating factor, IL-6, IL-10, and IL-1ra, peaked at 24 to 48 hours. At necropsy, there was lobar consolidation with frequent pleural involvement. Lung histopathology showed alveolar edema and macrophage influx in areas of organizing pneumonia. Hierarchical clustering of peripheral blood RNA data at 48 hours correctly identified animals with and without pneumonia. Dose-dependent inoculation of baboons with S. pneumoniae produces a host response ranging from spontaneous clearance (10(6) CFU) to severe pneumonia (10(9) CFU). Selected BALF and plasma cytokine levels and RNA profiles were associated with severe pneumonia and may provide clinically useful parameters after validation.

Technological advances have allowed the generation of high-throughput imaging of tissue sections. However, the analysis of these samples is typically still performed manually by one or multiple pathologists. We present a novel statistical model for the automated, quantitative analysis of these images. Our approach requires minimal tuning and allows recapitulation of estimates of staining strength in the nuclei of tumor cells as estimated by the gold standard. Besides, it compares favorably to other quantitative approaches available in the public domain.

The effectiveness of interventions promoting healthy child growth and development depends upon the capacity of the health system to deliver a high-quality intervention. However, few health workers are trained in providing integrated early child-development services. Building capacity entails not only training the frontline worker, but also mobilizing knowledge and support to promote early child development across the health system. In this paper, we present the paradigm shift required to build effective partnerships between health workers and families in order to support children's health, growth, and development, the practical skills frontline health workers require to promote optimal caregiving, and the need for knowledge mobilization across multiple institutional levels to support frontline health workers. We present case studies illustrating challenges and success stories around capacity development. There is a need to galvanize increased commitment and resources to building capacity in health systems to deliver early child-development services., (© 2014 New York Academy of Sciences.)

Background: The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, specifically label-free LC-MS/MS, allows rapid measurement of thousands of proteins, enabling large-scale studies of various biological systems. Prior to analyzing these information-rich datasets, raw data must undergo several computational processing steps. We present a method to address one of the essential steps in proteomics data processing--the matching of peptide measurements across samples., Results: We describe a novel method for label-free proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion information. We compare the results of our alignment method to PEPPeR and OpenMS, and compare alignment accuracy achieved by different versions of our method utilizing various data characteristics. Our method results in increased match recall rates and similar or improved mismatch rates compared to PEPPeR and OpenMS feature-based alignment. We also show that the inclusion of drift time and product ion information results in higher recall rates and more confident matches, without increases in error rates., Conclusions: Based on the results presented here, we argue that the incorporation of ion mobility drift time and product ion information are worthy pursuits. Alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods.

We propose a mixture model for text data designed to capture underlying structure in the history of present illness section of electronic medical records data. Additionally, we propose a method to induce bias that leads to more homogeneous sets of diagnoses for patients in each cluster. We apply our model to a collection of electronic records from an emergency department and compare our results to three other relevant models in order to assess performance. Results using standard metrics demonstrate that patient clusters from our model are more homogeneous when compared to others, and qualitative analyses suggest that our approach leads to interpretable patient sub-populations when applied to real data. Finally, we demonstrate an example of our patient clustering model to identify adverse drug events.

Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa.

In the intrinsic pathway of apoptosis, cell-damaging signals promote the release of cytochrome c from mitochondria, triggering activation of the Apaf-1 and caspase-9 apoptosome. The ubiquitin E3 ligase MDM2 decreases the stability of the proapoptotic factor p53. We show that it also coordinated apoptotic events in a p53-independent manner by ubiquitylating the apoptosome activator CAS and the ubiquitin E3 ligase HUWE1. HUWE1 ubiquitylates the antiapoptotic factor Mcl-1, and we found that HUWE1 also ubiquitylated PP5 (protein phosphatase 5), which indirectly inhibited apoptosome activation. Breast cancers that are positive for the tyrosine receptor kinase HER2 (human epidermal growth factor receptor 2) tend to be highly aggressive. In HER2-positive breast cancer cells treated with the HER2 tyrosine kinase inhibitor lapatinib, MDM2 was degraded and HUWE1 was stabilized. In contrast, in breast cancer cells that acquired resistance to lapatinib, the abundance of MDM2 was not decreased and HUWE1 was degraded, which inhibited apoptosis, regardless of p53 status. MDM2 inhibition overcame lapatinib resistance in cells with either wild-type or mutant p53 and in xenograft models. These findings demonstrate broader, p53-independent roles for MDM2 and HUWE1 in apoptosis and specifically suggest the potential for therapy directed against MDM2 to overcome lapatinib resistance.

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent.