Genetic Basis of Atherosclerosis: Insights from Mice and Humans

PubMed Central

Stylianou, Ioannis M.; Bauer, Robert C.; Reilly, Muredach P.; Rader, Daniel J.

2012-01-01

Atherosclerosis is a complex and heritable disease involving multiple cell types and the interactions of many different molecular pathways. The genetic and molecular mechanisms of atherosclerosis have in part been elucidated by mouse models; at least 100 different genes have been shown to influence atherosclerosis in mice. Importantly, unbiased genome-wide association studies have recently identified a number of novel loci robustly associated with atherosclerotic coronary artery disease (CAD). Here we review the genetic data elucidated from mouse models of atherosclerosis, as well as significant associations for human CAD. Furthermore, we discuss in greater detail some of these novel human CAD loci. The combination of mouse and human genetics has the potential to identify and validate novel genes that influence atherosclerosis, some of which may be candidates for new therapeutic approaches. PMID:22267839

Folding of polyglutamine chains

NASA Astrophysics Data System (ADS)

Chopra, Manan; Reddy, Allam S.; Abbott, N. L.; de Pablo, J. J.

2008-10-01

Long polyglutamine chains have been associated with a number of neurodegenerative diseases. These include Huntington's disease, where expanded polyglutamine (PolyQ) sequences longer than 36 residues are correlated with the onset of symptoms. In this paper we study the folding pathway of a 54-residue PolyQ chain into a β-helical structure. Transition path sampling Monte Carlo simulations are used to generate unbiased reactive pathways between unfolded configurations and the folded β-helical structure of the polyglutamine chain. The folding process is examined in both explicit water and an implicit solvent. Both models reveal that the formation of a few critical contacts is necessary and sufficient for the molecule to fold. Once the primary contacts are formed, the fate of the protein is sealed and it is largely committed to fold. We find that, consistent with emerging hypotheses about PolyQ aggregation, a stable β-helical structure could serve as the nucleus for subsequent polymerization of amyloid fibrils. Our results indicate that PolyQ sequences shorter than 36 residues cannot form that nucleus, and it is also shown that specific mutations inferred from an analysis of the simulated folding pathway exacerbate its stability.

Novel and ultra-rare damaging variants in neuropeptide signaling are associated with disordered eating behaviors

PubMed Central

Bahl, Ethan; Hannah, Claire; Hofammann, Dabney; Acevedo, Summer; Cui, Huxing; McAdams, Carrie J.

2017-01-01

Objective Eating disorders develop through a combination of genetic vulnerability and environmental stress, however the genetic basis of this risk is unknown. Methods To understand the genetic basis of this risk, we performed whole exome sequencing on 93 unrelated individuals with eating disorders (38 restricted-eating and 55 binge-eating) to identify novel damaging variants. Candidate genes with an excessive burden of predicted damaging variants were then prioritized based upon an unbiased, data-driven bioinformatic analysis. One top candidate pathway was empirically tested for therapeutic potential in a mouse model of binge-like eating. Results An excessive burden of novel damaging variants was identified in 186 genes in the restricted-eating group and 245 genes in the binge-eating group. This list is significantly enriched (OR = 4.6, p<0.0001) for genes involved in neuropeptide/neurotrophic pathways implicated in appetite regulation, including neurotensin-, glucagon-like peptide 1- and BDNF-signaling. Administration of the glucagon-like peptide 1 receptor agonist exendin-4 significantly reduced food intake in a mouse model of ‘binge-like’ eating. Conclusions These findings implicate ultra-rare and novel damaging variants in neuropeptide/neurotropic factor signaling pathways in the development of eating disorder behaviors and identify glucagon-like peptide 1-receptor agonists as a potential treatment for binge eating. PMID:28846695

Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology.

PubMed

Pei, Fen; Li, Hongchun; Henderson, Mark J; Titus, Steven A; Jadhav, Ajit; Simeonov, Anton; Cobanoglu, Murat Can; Mousavi, Seyed H; Shun, Tongying; McDermott, Lee; Iyer, Prema; Fioravanti, Michael; Carlisle, Diane; Friedlander, Robert M; Bahar, Ivet; Taylor, D Lansing; Lezon, Timothy R; Stern, Andrew M; Schurdak, Mark E

2017-12-19

Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain a comprehensive, unbiased understanding of disease processes to inform effective therapeutic strategies. We report the implementation of QSP to Huntington's Disease, with the application of a chemogenomics platform to identify strategies to protect neuronal cells from mutant huntingtin induced death. Using the STHdh Q111 cell model, we investigated the protective effects of small molecule probes having diverse canonical modes-of-action to infer pathways of neuronal cell protection connected to drug mechanism. Several mechanistically diverse protective probes were identified, most of which showed less than 50% efficacy. Specific combinations of these probes were synergistic in enhancing efficacy. Computational analysis of these probes revealed a convergence of pathways indicating activation of PKA. Analysis of phospho-PKA levels showed lower cytoplasmic levels in STHdh Q111 cells compared to wild type STHdh Q7 cells, and these levels were increased by several of the protective compounds. Pharmacological inhibition of PKA activity reduced protection supporting the hypothesis that protection may be working, in part, through activation of the PKA network. The systems-level studies described here can be broadly applied to any discovery strategy involving small molecule modulation of disease phenotype.

Variation in isotopologues of atmospheric nitric acid in passively collected samples along an air pollution gradient in southern California

Treesearch

Michael D. Bell; James O. Sickman; Andrzej Bytnerowicz; Pamela E. Padgett; Edith B. Allen

2014-01-01

The sources and oxidation pathways of atmospheric nitric acid (HNO3) can be evaluated using the isotopic signatures of oxygen (O) and nitrogen (N). This study evaluated the ability of Nylasorb nylon filters to passively collect unbiased isotopologues of atmospheric HNO3 under controlled and field conditions. Filters...

A statistical test of unbiased evolution of body size in birds.

PubMed

Bokma, Folmer

2002-12-01

Of the approximately 9500 bird species, the vast majority is small-bodied. That is a general feature of evolutionary lineages, also observed for instance in mammals and plants. The avian interspecific body size distribution is right-skewed even on a logarithmic scale. That has previously been interpreted as evidence that body size evolution has been biased. However, a procedure to test for unbiased evolution from the shape of body size distributions was lacking. In the present paper unbiased body size evolution is defined precisely, and a statistical test is developed based on Monte Carlo simulation of unbiased evolution. Application of the test to birds suggests that it is highly unlikely that avian body size evolution has been unbiased as defined. Several possible explanations for this result are discussed. A plausible explanation is that the general model of unbiased evolution assumes that population size and generation time do not affect the evolutionary variability of body size; that is, that micro- and macroevolution are decoupled, which theory suggests is not likely to be the case.

Drosophila models of amyotrophic lateral sclerosis with defects in RNA metabolism.

PubMed

Zhang, Ke; Coyne, Alyssa N; Lloyd, Thomas E

2018-05-09

The fruit fly Drosophila Melanogaster has been widely used to study neurodegenerative diseases. The conservation of nervous system biology coupled with the rapid life cycle and powerful genetic tools in the fly have enabled the identification of novel therapeutic targets that have been validated in vertebrate model systems and human patients. A recent example is in the study of the devastating motor neuron degenerative disease amyotrophic lateral sclerosis (ALS). Mutations in genes that regulate RNA metabolism are a major cause of inherited ALS, and functional analysis of these genes in the fly nervous system has shed light on how mutations cause disease. Importantly, unbiased genetic screens have identified key pathways that contribute to ALS pathogenesis such as nucleocytoplasmic transport and stress granule assembly. In this review, we will discuss the utilization of Drosophila models of ALS with defects in RNA metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker.

PubMed

Fadini, Gian Paolo; Albiero, Mattia; Millioni, Renato; Poncina, Nicol; Rigato, Mauro; Scotton, Rachele; Boscari, Federico; Brocco, Enrico; Arrigoni, Giorgio; Villano, Gianmarco; Turato, Cristian; Biasiolo, Alessandra; Pontisso, Patrizia; Avogaro, Angelo

2014-09-01

Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with α1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patients.

Genetics of Sleep and Sleep disorders

PubMed Central

Sehgal, Amita; Mignot, Emmanuel

2011-01-01

Sleep remains one of the least understood phenomena in biology – even its role in synaptic plasticity remains debatable. Since sleep was recognized to be regulated genetically, intense research has launched on two fronts: the development of model organisms for deciphering the molecular mechanisms of sleep and attempts to identify genetic underpinnings of human sleep disorders. In this Review, we describe how unbiased, high-throughput screens in model organisms are uncovering sleep regulatory mechanisms and how pathways, such as the circadian clock network and specific neurotransmitter signals, have conserved effects on sleep from Drosophila to humans. At the same time, genome-wide association (GWA) studies have uncovered ~14 loci increasing susceptibility to sleep disorders, such as narcolepsy and restless leg syndrome. To conclude, we discuss how these different strategies will be critical to unambiguously defining the function of sleep. PMID:21784243

A novel mouse model identifies cooperating mutations and therapeutic targets critical for chronic myeloid leukemia progression

PubMed Central

Giotopoulos, George; van der Weyden, Louise; Osaki, Hikari; Rust, Alistair G.; Gallipoli, Paolo; Meduri, Eshwar; Horton, Sarah J.; Chan, Wai-In; Foster, Donna; Prinjha, Rab K.; Pimanda, John E.; Tenen, Daniel G.; Vassiliou, George S.; Koschmieder, Steffen; Adams, David J.

2015-01-01

The introduction of highly selective ABL-tyrosine kinase inhibitors (TKIs) has revolutionized therapy for chronic myeloid leukemia (CML). However, TKIs are only efficacious in the chronic phase of the disease and effective therapies for TKI-refractory CML, or after progression to blast crisis (BC), are lacking. Whereas the chronic phase of CML is dependent on BCR-ABL, additional mutations are required for progression to BC. However, the identity of these mutations and the pathways they affect are poorly understood, hampering our ability to identify therapeutic targets and improve outcomes. Here, we describe a novel mouse model that allows identification of mechanisms of BC progression in an unbiased and tractable manner, using transposon-based insertional mutagenesis on the background of chronic phase CML. Our BC model is the first to faithfully recapitulate the phenotype, cellular and molecular biology of human CML progression. We report a heterogeneous and unique pattern of insertions identifying known and novel candidate genes and demonstrate that these pathways drive disease progression and provide potential targets for novel therapeutic strategies. Our model greatly informs the biology of CML progression and provides a potent resource for the development of candidate therapies to improve the dismal outcomes in this highly aggressive disease. PMID:26304963

An Unbiased Approach to Identifying Tau Kinases That Phosphorylate Tau at Sites Associated with Alzheimer Disease

PubMed Central

Cavallini, Annalisa; Brewerton, Suzanne; Bell, Amanda; Sargent, Samantha; Glover, Sarah; Hardy, Clare; Moore, Roger; Calley, John; Ramachandran, Devaki; Poidinger, Michael; Karran, Eric; Davies, Peter; Hutton, Michael; Szekeres, Philip; Bose, Suchira

2013-01-01

Neurofibrillary tangles, one of the hallmarks of Alzheimer disease (AD), are composed of paired helical filaments of abnormally hyperphosphorylated tau. The accumulation of these proteinaceous aggregates in AD correlates with synaptic loss and severity of dementia. Identifying the kinases involved in the pathological phosphorylation of tau may identify novel targets for AD. We used an unbiased approach to study the effect of 352 human kinases on their ability to phosphorylate tau at epitopes associated with AD. The kinases were overexpressed together with the longest form of human tau in human neuroblastoma cells. Levels of total and phosphorylated tau (epitopes Ser(P)-202, Thr(P)-231, Ser(P)-235, and Ser(P)-396/404) were measured in cell lysates using AlphaScreen assays. GSK3α, GSK3β, and MAPK13 were found to be the most active tau kinases, phosphorylating tau at all four epitopes. We further dissected the effects of GSK3α and GSK3β using pharmacological and genetic tools in hTau primary cortical neurons. Pathway analysis of the kinases identified in the screen suggested mechanisms for regulation of total tau levels and tau phosphorylation; for example, kinases that affect total tau levels do so by inhibition or activation of translation. A network fishing approach with the kinase hits identified other key molecules putatively involved in tau phosphorylation pathways, including the G-protein signaling through the Ras family of GTPases (MAPK family) pathway. The findings identify novel tau kinases and novel pathways that may be relevant for AD and other tauopathies. PMID:23798682

Matrix metalloproteinase proteomics: substrates, targets, and therapy.

PubMed

Morrison, Charlotte J; Butler, Georgina S; Rodríguez, David; Overall, Christopher M

2009-10-01

Proteomics encompasses powerful techniques termed 'degradomics' for unbiased high-throughput protease substrate discovery screens that have been applied to an important family of extracellular proteases, the matrix metalloproteinases (MMPs). Together with the data generated from genetic deletion and transgenic mouse models and genomic profiling, these screens can uncover the diverse range of MMP functions, reveal which MMPs and MMP-mediated pathways exacerbate pathology, and which are involved in protection and the resolution of disease. This information can be used to identify and validate candidate drug targets and antitargets, and is critical for the development of new inhibitors of MMP function. Such inhibitors may target either the MMP directly in a specific manner or pathways upstream and downstream of MMP activity that are mediating deleterious effects in disease. Since MMPs do not operate alone but are part of the 'protease web', it is necessary to use system-wide approaches to understand MMP proteolysis in vivo, to discover new biological roles and their potential for therapeutic modification.

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

Unbiased Metabolite Profiling of Schizophrenia Fibroblasts under Stressful Perturbations Reveals Dysregulation of Plasmalogens and Phosphatidylcholines.

PubMed

Huang, Joanne H; Park, Hyoungjun; Iaconelli, Jonathan; Berkovitch, Shaunna S; Watmuff, Bradley; McPhie, Donna; Öngür, Dost; Cohen, Bruce M; Clish, Clary B; Karmacharya, Rakesh

2017-02-03

We undertook an unbiased metabolite profiling of fibroblasts from schizophrenia patients and healthy controls to identify metabolites and pathways that are dysregulated in disease, seeking to gain new insights into the disease biology of schizophrenia and to discover potential disease-related biomarkers. We measured polar and nonpolar metabolites in the fibroblasts under normal conditions and under two stressful physiological perturbations: growth in low-glucose media and exposure to the steroid hormone dexamethasone. We found that metabolites that were significantly different between schizophrenia and control subjects showed separation of the two groups by partial least-squares discriminant analysis methods. This separation between schizophrenia and healthy controls was more robust with metabolites identified under the perturbation conditions. The most significant individual metabolite differences were also found in the perturbation experiments. Metabolites that were significantly different between schizophrenia and healthy controls included a number of plasmalogens and phosphatidylcholines. We present these results in the context of previous reports of metabolic profiling of brain tissue and plasma in schizophrenia. These results show the applicability of metabolite profiling under stressful perturbations to reveal cellular pathways that may be involved in disease biology.

Unbiased Estimates of Variance Components with Bootstrap Procedures

ERIC Educational Resources Information Center

Brennan, Robert L.

2007-01-01

This article provides general procedures for obtaining unbiased estimates of variance components for any random-model balanced design under any bootstrap sampling plan, with the focus on designs of the type typically used in generalizability theory. The results reported here are particularly helpful when the bootstrap is used to estimate standard…

Definition and Measurement of Selection Bias: From Constant Ratio to Constant Difference

ERIC Educational Resources Information Center

Cahan, Sorel; Gamliel, Eyal

2006-01-01

Despite its intuitive appeal and popularity, Thorndike's constant ratio (CR) model for unbiased selection is inherently inconsistent in "n"-free selection. Satisfaction of the condition for unbiased selection, when formulated in terms of success/acceptance probabilities, usually precludes satisfaction by the converse probabilities of…

Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation

PubMed Central

2014-01-01

Introduction Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory or degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Methods Three multi-center genome-wide transcriptomic data sets (Affymetrix HG-U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule-based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendl’s statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio. Results The optimized rule sets for the three centers contained a total of 29, 20, and 8 rules (including 10, 8, and 4 rules for ‘RA’), respectively. The mean sensitivity for the prediction of RA based on six center-to-center tests was 96% (range 90% to 100%), that for OA 86% (range 40% to 100%). The mean specificity for RA prediction was 94% (range 80% to 100%), that for OA 96% (range 83.3% to 100%). The average overall accuracy of the three different rule-based classifiers was 91% (range 80% to 100%). Unbiased analyses by Pathway Studio of the gene sets obtained by discrimination of RA from OA and CG with rule-based classifiers resulted in the identification of the pathogenetically and/or therapeutically relevant interferon-gamma and GM-CSF pathways. Conclusion First-time application of rule-based classifiers for the discrimination of RA resulted in high performance, with means for all assessment parameters close to or higher than 90%. In addition, this unbiased, new approach resulted in the identification not only of pathways known to be critical to RA, but also of novel molecules such as serine/threonine kinase 10. PMID:24690414

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

PubMed Central

2016-01-01

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography. PMID:28004573

Convergence of Free Energy Profile of Coumarin in Lipid Bilayer

PubMed Central

2012-01-01

Atomistic molecular dynamics (MD) simulations of druglike molecules embedded in lipid bilayers are of considerable interest as models for drug penetration and positioning in biological membranes. Here we analyze partitioning of coumarin in dioleoylphosphatidylcholine (DOPC) bilayer, based on both multiple, unbiased 3 μs MD simulations (total length) and free energy profiles along the bilayer normal calculated by biased MD simulations (∼7 μs in total). The convergences in time of free energy profiles calculated by both umbrella sampling and z-constraint techniques are thoroughly analyzed. Two sets of starting structures are also considered, one from unbiased MD simulation and the other from “pulling” coumarin along the bilayer normal. The structures obtained by pulling simulation contain water defects on the lipid bilayer surface, while those acquired from unbiased simulation have no membrane defects. The free energy profiles converge more rapidly when starting frames from unbiased simulations are used. In addition, z-constraint simulation leads to more rapid convergence than umbrella sampling, due to quicker relaxation of membrane defects. Furthermore, we show that the choice of RESP, PRODRG, or Mulliken charges considerably affects the resulting free energy profile of our model drug along the bilayer normal. We recommend using z-constraint biased MD simulations based on starting geometries acquired from unbiased MD simulations for efficient calculation of convergent free energy profiles of druglike molecules along bilayer normals. The calculation of free energy profile should start with an unbiased simulation, though the polar molecules might need a slow pulling afterward. Results obtained with the recommended simulation protocol agree well with available experimental data for two coumarin derivatives. PMID:22545027

Convergence of Free Energy Profile of Coumarin in Lipid Bilayer.

PubMed

Paloncýová, Markéta; Berka, Karel; Otyepka, Michal

2012-04-10

Atomistic molecular dynamics (MD) simulations of druglike molecules embedded in lipid bilayers are of considerable interest as models for drug penetration and positioning in biological membranes. Here we analyze partitioning of coumarin in dioleoylphosphatidylcholine (DOPC) bilayer, based on both multiple, unbiased 3 μs MD simulations (total length) and free energy profiles along the bilayer normal calculated by biased MD simulations (∼7 μs in total). The convergences in time of free energy profiles calculated by both umbrella sampling and z-constraint techniques are thoroughly analyzed. Two sets of starting structures are also considered, one from unbiased MD simulation and the other from "pulling" coumarin along the bilayer normal. The structures obtained by pulling simulation contain water defects on the lipid bilayer surface, while those acquired from unbiased simulation have no membrane defects. The free energy profiles converge more rapidly when starting frames from unbiased simulations are used. In addition, z-constraint simulation leads to more rapid convergence than umbrella sampling, due to quicker relaxation of membrane defects. Furthermore, we show that the choice of RESP, PRODRG, or Mulliken charges considerably affects the resulting free energy profile of our model drug along the bilayer normal. We recommend using z-constraint biased MD simulations based on starting geometries acquired from unbiased MD simulations for efficient calculation of convergent free energy profiles of druglike molecules along bilayer normals. The calculation of free energy profile should start with an unbiased simulation, though the polar molecules might need a slow pulling afterward. Results obtained with the recommended simulation protocol agree well with available experimental data for two coumarin derivatives.

Four photon parametric amplification. [in unbiased Josephson junction

NASA Technical Reports Server (NTRS)

Parrish, P. T.; Feldman, M. J.; Ohta, H.; Chiao, R. Y.

1974-01-01

An analysis is presented describing four-photon parametric amplification in an unbiased Josephson junction. Central to the theory is the model of the Josephson effect as a nonlinear inductance. Linear, small signal analysis is applied to the two-fluid model of the Josephson junction. The gain, gain-bandwidth product, high frequency limit, and effective noise temperature are calculated for a cavity reflection amplifier. The analysis is extended to multiple (series-connected) junctions and subharmonic pumping.

A zebrafish model of PINK1 deficiency reveals key pathway dysfunction including HIF signaling.

PubMed

Priyadarshini, M; Tuimala, J; Chen, Y C; Panula, P

2013-06-01

The PTEN induced putative kinase 1 (PINK1) gene is mutated in patients with hereditary early onset Parkinson's disease (PD). The targets of PINK1 and the mechanisms in PD are still not fully understood. Here, we carried out a high-throughput and unbiased microarray study to identify novel functions and pathways for PINK1. In larval zebrafish, the function of pink1 was inhibited using splice-site morpholino oligonucleotides and the samples were hybridized on a two-color gene expression array. We found 177 significantly altered genes in pink1 morphants compared with the uninjected wildtype controls (log fold change values from -1.6 to +0.9). The five most prominent pathways based on critical biological processes and key toxicological responses were hypoxia-inducible factor (HIF) signaling, TGF-β signaling, mitochondrial dysfunction, RAR activation, and biogenesis of mitochondria. Furthermore, we verified that potentially important genes such as hif1α, catalase, SOD3, and atp1a2a were downregulated in pink1 morphants, whereas genes such as fech, pax2a, and notch1a were upregulated. Some of these genes have been found to play important roles in HIF signaling pathways. The pink1 morphants were found to have heart dysfunction, increased erythropoiesis, increased expression of vascular endothelial growth factors, and increased ROS. Our findings suggest that a lack of pink1 in zebrafish alters many vital and critical pathways in addition to the HIF signaling pathway. Copyright © 2013 Elsevier Inc. All rights reserved.

Dissecting the transcriptional phenotype of ribosomal protein deficiency: implications for Diamond-Blackfan Anemia

PubMed Central

Aspesi, Anna; Pavesi, Elisa; Robotti, Elisa; Crescitelli, Rossella; Boria, Ilenia; Avondo, Federica; Moniz, Hélène; Da Costa, Lydie; Mohandas, Narla; Roncaglia, Paola; Ramenghi, Ugo; Ronchi, Antonella; Gustincich, Stefano; Merlin, Simone; Marengo, Emilio; Ellis, Steven R.; Follenzi, Antonia; Santoro, Claudio; Dianzani, Irma

2014-01-01

Defects in genes encoding ribosomal proteins cause Diamond Blackfan Anemia (DBA), a red cell aplasia often associated with physical abnormalities. Other bone marrow failure syndromes have been attributed to defects in ribosomal components but the link between erythropoiesis and the ribosome remains to be fully defined. Several lines of evidence suggest that defects in ribosome synthesis lead to “ribosomal stress” with p53 activation and either cell cycle arrest or induction of apoptosis. Pathways independent of p53 have also been proposed to play a role in DBA pathogenesis. We took an unbiased approach to identify p53-independent pathways activated by defects in ribosome synthesis by analyzing global gene expression in various cellular models of DBA. Ranking-Principal Component Analysis (Ranking-PCA) was applied to the identified datasets to determine whether there are common sets of genes whose expression is altered in these different cellular models. We observed consistent changes in the expression of genes involved in cellular amino acid metabolic process, negative regulation of cell proliferation and cell redox homeostasis. These data indicate that cells respond to defects in ribosome synthesis by changing the level of expression of a limited subset of genes involved in critical cellular processes. Moreover, our data support a role for p53-independent pathways in the pathophysiology of DBA. PMID:24835311

Modeling Molecular and Cellular Aspects of Human Disease using the Nematode Caenorhabditis elegans

PubMed Central

Silverman, Gary A.; Luke, Cliff J.; Bhatia, Sangeeta R.; Long, Olivia S.; Vetica, Anne C.; Perlmutter, David H.; Pak, Stephen C.

2009-01-01

As an experimental system, Caenorhabditis elegans, offers a unique opportunity to interrogate in vivo the genetic and molecular functions of human disease-related genes. For example, C. elegans has provided crucial insights into fundamental biological processes such as cell death and cell fate determinations, as well as pathological processes such as neurodegeneration and microbial susceptibility. The C. elegans model has several distinct advantages including a completely sequenced genome that shares extensive homology with that of mammals, ease of cultivation and storage, a relatively short lifespan and techniques for generating null and transgenic animals. However, the ability to conduct unbiased forward and reverse genetic screens in C. elegans remains one of the most powerful experimental paradigms for discovering the biochemical pathways underlying human disease phenotypes. The identification of these pathways leads to a better understanding of the molecular interactions that perturb cellular physiology, and forms the foundation for designing mechanism-based therapies. To this end, the ability to process large numbers of isogenic animals through automated work stations suggests that C. elegans, manifesting different aspects of human disease phenotypes, will become the platform of choice for in vivo drug discovery and target validation using high-throughput/content screening technologies. PMID:18852689

PathwaySplice: An R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

PubMed

Yan, Aimin; Ban, Yuguang; Gao, Zhen; Chen, Xi; Wang, Lily

2018-04-24

Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the "significant" gene list in alternative splicing. We present PathwaySplice, an R package that (1) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (2) Visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (3) Supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (4) Identifies the significant genes driving pathway significance and (5) Organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph. https://bioconductor.org/packages/release/bioc/html/PathwaySplice.html. lily.wangg@gmail.com, xi.steven.chen@gmail.com.

Kinetics of Huperzine A Dissociation from Acetylcholinesterase via Multiple Unbinding Pathways.

PubMed

Rydzewski, J; Jakubowski, R; Nowak, W; Grubmüller, H

2018-06-12

The dissociation of huperzine A (hupA) from Torpedo californica acetylcholinesterase ( TcAChE) was investigated by 4 μs unbiased and biased all-atom molecular dynamics (MD) simulations in explicit solvent. We performed our study using memetic sampling (MS) for the determination of reaction pathways (RPs), metadynamics to calculate free energy, and maximum-likelihood estimation (MLE) to recover kinetic rates from unbiased MD simulations. Our simulations suggest that the dissociation of hupA occurs mainly via two RPs: a front door along the axis of the active-site gorge (pwf) and through a new transient side door (pws), i.e., formed by the Ω-loop (residues 67-94 of TcAChE). An analysis of the inhibitor unbinding along the RPs suggests that pws is opened transiently after hupA and the Ω-loop reach a low free-energy transition state characterized by the orientation of the pyridone group of the inhibitor directed toward the Ω-loop plane. Unlike pws, pwf does not require large structural changes in TcAChE to be accessible. The estimated free energies and rates agree well with available experimental data. The dissociation rates along the unbinding pathways are similar, suggesting that the dissociation of hupA along pws is likely to be relevant. This indicates that perturbations to hupA- TcAChE interactions could potentially induce pathway hopping. In summary, our results characterize the slow-onset inhibition of TcAChE by hupA, which may provide the structural and energetic bases for the rational design of the next-generation slow-onset inhibitors with optimized pharmacokinetic properties for the treatment of Alzheimer's disease.

Five instruments for measuring tree height: an evaluation

Treesearch

Michael S. Williams; William A. Bechtold; V.J. LaBau

1994-01-01

Five instruments were tested for reliability in measuring tree heights under realistic conditions. Four linear models were used to determine if tree height can be measured unbiasedly over all tree sizes and if any of the instruments were more efficient in estimating tree height. The laser height finder was the only instrument to produce unbiased estimates of the true...

Conformational Transition Pathways of Epidermal Growth Factor Receptor Kinase Domain from Multiple Molecular Dynamics Simulations and Bayesian Clustering.

PubMed

Li, Yan; Li, Xiang; Ma, Weiya; Dong, Zigang

2014-08-12

The epidermal growth factor receptor (EGFR) is aberrantly activated in various cancer cells and an important target for cancer treatment. Deep understanding of EGFR conformational changes between the active and inactive states is of pharmaceutical interest. Here we present a strategy combining multiply targeted molecular dynamics simulations, unbiased molecular dynamics simulations, and Bayesian clustering to investigate transition pathways during the activation/inactivation process of EGFR kinase domain. Two distinct pathways between the active and inactive forms are designed, explored, and compared. Based on Bayesian clustering and rough two-dimensional free energy surfaces, the energy-favorable pathway is recognized, though DFG-flip happens in both pathways. In addition, another pathway with different intermediate states appears in our simulations. Comparison of distinct pathways also indicates that disruption of the Lys745-Glu762 interaction is critically important in DFG-flip while movement of the A-loop significantly facilitates the conformational change. Our simulations yield new insights into EGFR conformational transitions. Moreover, our results verify that this approach is valid and efficient in sampling of protein conformational changes and comparison of distinct pathways.

Unbiased screen for interactors of leucine-rich repeat kinase 2 supports a common pathway for sporadic and familial Parkinson disease

PubMed Central

Beilina, Alexandria; Rudenko, Iakov N.; Kaganovich, Alice; Civiero, Laura; Chau, Hien; Kalia, Suneil K.; Kalia, Lorraine V.; Lobbestael, Evy; Chia, Ruth; Ndukwe, Kelechi; Ding, Jinhui; Nalls, Mike A.; Olszewski, Maciej; Hauser, David N.; Kumaran, Ravindran; Lozano, Andres M.; Baekelandt, Veerle; Greene, Lois E.; Taymans, Jean-Marc; Greggio, Elisa; Cookson, Mark R.; Nalls, Mike A.; Plagnol, Vincent; Martinez, Maria; Hernandez, Dena G; Sharma, Manu; Sheerin, Una-Marie; Saad, Mohamad; Simón-Sánchez, Javier; Schulte, Claudia; Lesage, Suzanne; Sveinbjörnsdóttir, Sigurlaug; Arepalli, Sampath; Barker, Roger; Ben-Shlomo, Yoav; Berendse, Henk W; Berg, Daniela; Bhatia, Kailash; de Bie, Rob M A; Biffi, Alessandro; Bloem, Bas; Bochdanovits, Zoltan; Bonin, Michael; Bras, Jose M; Brockmann, Kathrin; Brooks, Janet; Burn, David J; Charlesworth, Gavin; Chen, Honglei; Chong, Sean; Clarke, Carl E; Cookson, Mark R; Cooper, J Mark; Corvol, Jean Christophe; Counsell, Carl; Damier, Philippe; Dartigues, Jean-François; Deloukas, Panos; Deuschl, Günther; Dexter, David T; van Dijk, Karin D; Dillman, Allissa; Durif, Frank; Dürr, Alexandra; Edkins, Sarah; Evans, Jonathan R; Foltynie, Thomas; Gao, Jianjun; Gardner, Michelle; Gibbs, J Raphael; Goate, Alison; Gray, Emma; Guerreiro, Rita; Gústafsson, Ómar; Harris, Clare; van Hilten, Jacobus J; Hofman, Albert; Hollenbeck, Albert; Holton, Janice; Hu, Michele; Huang, Xuemei; Huber, Heiko; Hudson, Gavin; Hunt, Sarah E; Huttenlocher, Johanna; Illig, Thomas; München, Helmholtz Zentrum; Jónsson, Pálmi V; Lambert, Jean-Charles; Langford, Cordelia; Lees, Andrew; Lichtner, Peter; München, Helmholtz Zentrum; Limousin, Patricia; Lopez, Grisel; Lorenz, Delia; McNeill, Alisdair; Moorby, Catriona; Moore, Matthew; Morris, Huw R; Morrison, Karen E; Mudanohwo, Ese; O’Sullivan, Sean S; Pearson, Justin; Perlmutter, Joel S; Pétursson, Hjörvar; Pollak, Pierre; Post, Bart; Potter, Simon; Ravina, Bernard; Revesz, Tamas; Riess, Olaf; Rivadeneira, Fernando; Rizzu, Patrizia; Ryten, Mina; Sawcer, Stephen; Schapira, Anthony; Scheffer, Hans; Shaw, Karen; Shoulson, Ira; Sidransky, Ellen; Smith, Colin; Spencer, Chris C A; Stefánsson, Hreinn; Steinberg, Stacy; Stockton, Joanna D; Strange, Amy; Talbot, Kevin; Tanner, Carlie M; Tashakkori-Ghanbaria, Avazeh; Tison, François; Trabzuni, Daniah; Traynor, Bryan J; Uitterlinden, André G; Velseboer, Daan; Vidailhet, Marie; Walker, Robert; van de Warrenburg, Bart; Wickremaratchi, Mirdhu; Williams, Nigel; Williams-Gray, Caroline H; Winder-Rhodes, Sophie; Stefánsson, Kári; Hardy, John; Heutink, Peter; Brice, Alexis; Gasser, Thomas; Singleton, Andrew B; Wood, Nicholas W; Chinnery, Patrick F; Arepalli, Sampath; Cookson, Mark R; Dillman, Allissa; Ferrucci, Luigi; Gibbs, J Raphael; Hernandez, Dena G; Johnson, Robert; Longo, Dan L; Majounie, Elisa; Nalls, Michael A; O’Brien, Richard; Singleton, Andrew B; Traynor, Bryan J; Troncoso, Juan; van der Brug, Marcel; Zielke, H Ronald; Zonderman, Alan B

2014-01-01

Mutations in leucine-rich repeat kinase 2 (LRRK2) cause inherited Parkinson disease (PD), and common variants around LRRK2 are a risk factor for sporadic PD. Using protein–protein interaction arrays, we identified BCL2-associated athanogene 5, Rab7L1 (RAB7, member RAS oncogene family-like 1), and Cyclin-G–associated kinase as binding partners of LRRK2. The latter two genes are candidate genes for risk for sporadic PD identified by genome-wide association studies. These proteins form a complex that promotes clearance of Golgi-derived vesicles through the autophagy–lysosome system both in vitro and in vivo. We propose that three different genes for PD have a common biological function. More generally, data integration from multiple unbiased screens can provide insight into human disease mechanisms. PMID:24510904

Quantification of Cysteinyl-S-Nitrosylation by Fluorescence in Unbiased Proteomic Studies*

PubMed Central

Wiktorowicz, John E.; Stafford, Susan; Rea, Harriet; Urvil, Petri; Soman, Kizhake; Kurosky, Alexander; Perez-Polo, J. Regino; Savidge, Tor C.

2011-01-01

Cysteinyl-S-nitrosylation has emerged as an important post-translational modification affecting protein function in health and disease. Great emphasis has been placed on global, unbiased quantification of S-nitrosylated proteins due to physiologic and oxidative stimuli. However, current strategies have been hampered by sample loss and altered protein electrophoretic mobility. Here, we describe a novel quantitative approach that combines accurate, sensitive fluorescence modification of cysteine S-nitrosylation that leaves electrophoretic mobility unaffected (SNOFlo), and introduce unique concepts for measuring changes in S-nitrosylation status relative to protein abundance. Its efficacy in defining the functional S-nitrosoproteome is demonstrated in two diverse biological applications: an in vivo rat hypoxia-ischemia reperfusion model, and antimicrobial S-nitrosoglutathione-driven transnitrosylation of an enteric microbial pathogen. The suitability of this approach for investigating endogenous S-nitrosylation is further demonstrated using Ingenuity Pathways analysis that identified nervous system and cellular development networks as the top two networks. Functional analysis of differentially S-nitrosylated proteins indicated their involvement in apoptosis, branching morphogenesis of axons, cortical neurons, and sympathetic neurites, neurogenesis, and calcium signaling. Major abundance changes were also observed for fibrillar proteins known to be stress-responsive in neurons and glia. Thus, both examples demonstrate the technique’s power in confirming the widespread involvement of S-nitrosylation in hypoxia-ischemia/reperfusion injury and in antimicrobial host responses. PMID:21615140

Gut microbiome may contribute to insulin resistance and systemic inflammation in obese rodents: a meta-analysis.

PubMed

Jiao, Na; Baker, Susan S; Nugent, Colleen A; Tsompana, Maria; Cai, Liting; Wang, Yong; Buck, Michael J; Genco, Robert J; Baker, Robert D; Zhu, Ruixin; Zhu, Lixin

2018-04-01

A number of studies have associated obesity with altered gut microbiota, although results are discordant regarding compositional changes in the gut microbiota of obese animals. Herein we used a meta-analysis to obtain an unbiased evaluation of structural and functional changes of the gut microbiota in diet-induced obese rodents. The raw sequencing data of nine studies generated from high-fat diet (HFD)-induced obese rodent models were processed with QIIME to obtain gut microbiota compositions. Biological functions were predicted and annotated with KEGG pathways with PICRUSt. No significant difference was observed for alpha diversity and Bacteroidetes-to-Firmicutes ratio between obese and lean rodents. Bacteroidia, Clostridia, Bacilli, and Erysipelotrichi were dominant classes, but gut microbiota compositions varied among studies. Meta-analysis of the nine microbiome data sets identified 15 differential taxa and 57 differential pathways between obese and lean rodents. In obese rodents, increased abundance was observed for Dorea, Oscillospira, and Ruminococcus, known for fermenting polysaccharide into short chain fatty acids (SCFAs). Decreased Turicibacter and increased Lactococcus are consistent with elevated inflammation in the obese status. Differential functional pathways of the gut microbiome in obese rodents included enriched pyruvate metabolism, butanoate metabolism, propanoate metabolism, pentose phosphate pathway, fatty acid biosynthesis, and glycerolipid metabolism pathways. These pathways converge in the function of carbohydrate metabolism, SCFA metabolism, and biosynthesis of lipid. HFD-induced obesity results in structural and functional dysbiosis of gut microbiota. The altered gut microbiome may contribute to obesity development by promoting insulin resistance and systemic inflammation.

Silencing of Tuberin Enhances Photoreceptor Survival and Function in a Preclinical Model of Retinitis Pigmentosa (An American Ophthalmological Society Thesis)

PubMed Central

Tsang, Stephen H.; Chan, Lawrence; Tsai, Yi-Ting; Wu, Wen-Hsuan; Hsu, Chun-Wei; Yang, Jin; Tosi, Joaquin; Wert, Katherine J.; Davis, Richard J.; Mahajan, Vinit B.

2014-01-01

Purpose: To assess the functional consequences of silencing of tuberin, an inhibitor of the mTOR signaling pathway, in a preclinical model of retinitis pigmentosa (RP) in order to test the hypothesis that insufficient induction of the protein kinase B (PKB)-regulated tuberin/mTOR self-survival pathway initiates apoptosis. Methods: In an unbiased genome-scale approach, kinase peptide substrate arrays were used to analyze self-survival pathways at the onset of photoreceptor degeneration. The mutant Pde6bH620Q/Pde6bH620Q at P14 and P18 photoreceptor outer segment (OS) lysates were labeled with P-ATP and hybridized to an array of 1,164 different synthetic peptide substrates. At this stage, OS of Pde6bH620Q/Pde6bH620Q rods are morphologically normal. In vitro kinase assays and immunohistochemistry were used to validate phosphorylation. Short hairpin RNA (shRNA) gene silencing was used to validate tuberin’s role in regulating survival. Results: At the onset of degeneration, 162 peptides were differentially phosphorylated. Protein kinases A, G, C (AGC kinases), and B exhibited increased activity in both peptide array and in vitro kinase assays. Immunohistochemical data confirmed altered phosphorylation patterns for phosphoinositide-dependent kinase-1 (PDK1), ribosomal protein S6 (RPS6), and tuberin. Tuberin gene silencing rescued photoreceptors from degeneration. Conclusions: Phosphorylation of tuberin and RPS6 is due to the upregulated activity of PKB. PKB/tuberin cell growth/survival signaling is activated before the onset of degeneration. Substrates of the AGC kinases in the PKB/tuberin pathway are phosphorylated to promote cell survival. Knockdown of tuberin, the inhibitor of the mTOR pathway, increased photoreceptor survival and function in a preclinical model of RP. PMID:25646031

Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.

PubMed

Xia, Jie; Tilahun, Ermias Lemma; Kebede, Eyob Hailu; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-02-23

Histone deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases, and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors (HDACIs). To facilitate the process, we constructed maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs cover all four classes including Class III (Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors and 24609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of "artificial enrichment" and "analogue bias". We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the "2D bias" and "LBVS favorable" effect within the benchmarking sets. In summary, MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that are available so far. MUBD-HDACs are freely available at http://www.xswlab.org/ .

Reply to ''Comment on 'Mutually unbiased bases, orthogonal Latin squares, and hidden-variable models'''

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paterek, Tomasz; Dakic, Borivoje; Brukner, Caslav

In this Reply to the preceding Comment by Hall and Rao [Phys. Rev. A 83, 036101 (2011)], we motivate terminology of our original paper and point out that further research is needed in order to (dis)prove the claimed link between every orthogonal Latin square of order being a power of a prime and a mutually unbiased basis.

Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment.

PubMed

Costello, Fintan; Watts, Paul

2018-01-01

We describe a computational model of two central aspects of people's probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people's reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti-regressive effect in inferential judgement, however. These regressive and anti-regressive effects explain various reliable and systematic biases seen in people's descriptive probability estimation and inferential probability judgment. This model predicts that these contrary effects will tend to cancel out in tasks that involve both descriptive estimation and inferential judgement, leading to unbiased responses in those tasks. We test this model by applying it to one such task, described by Gallistel et al. ). Participants' median responses in this task were unbiased, agreeing with normative probability theory over the full range of responses. Our model captures the pattern of unbiased responses in this task, while simultaneously explaining systematic biases away from normatively correct probabilities seen in other tasks. Copyright © 2018 Cognitive Science Society, Inc.

Unbiased multi-fidelity estimate of failure probability of a free plane jet

NASA Astrophysics Data System (ADS)

Marques, Alexandre; Kramer, Boris; Willcox, Karen; Peherstorfer, Benjamin

2017-11-01

Estimating failure probability related to fluid flows is a challenge because it requires a large number of evaluations of expensive models. We address this challenge by leveraging multiple low fidelity models of the flow dynamics to create an optimal unbiased estimator. In particular, we investigate the effects of uncertain inlet conditions in the width of a free plane jet. We classify a condition as failure when the corresponding jet width is below a small threshold, such that failure is a rare event (failure probability is smaller than 0.001). We estimate failure probability by combining the frameworks of multi-fidelity importance sampling and optimal fusion of estimators. Multi-fidelity importance sampling uses a low fidelity model to explore the parameter space and create a biasing distribution. An unbiased estimate is then computed with a relatively small number of evaluations of the high fidelity model. In the presence of multiple low fidelity models, this framework offers multiple competing estimators. Optimal fusion combines all competing estimators into a single estimator with minimal variance. We show that this combined framework can significantly reduce the cost of estimating failure probabilities, and thus can have a large impact in fluid flow applications. This work was funded by DARPA.

Proteomic interactions in the mouse vitreous-retina complex.

PubMed

Skeie, Jessica M; Mahajan, Vinit B

2013-01-01

Human vitreoretinal diseases are due to presumed abnormal mechanical interactions between the vitreous and retina, and translational models are limited. This study determined whether nonstructural proteins and potential retinal biomarkers were expressed by the normal mouse vitreous and retina. Vitreous and retina samples from mice were collected by evisceration and analyzed by liquid chromatography-tandem mass spectrometry. Identified proteins were further analyzed for differential expression and functional interactions using bioinformatic software. We identified 1,680 unique proteins in the retina and 675 unique proteins in the vitreous. Unbiased clustering identified protein pathways that distinguish retina from vitreous including oxidative phosphorylation and neurofilament cytoskeletal remodeling, whereas the vitreous expressed oxidative stress and innate immunology pathways. Some intracellular protein pathways were found in both retina and vitreous, such as glycolysis and gluconeogenesis and neuronal signaling, suggesting proteins might be shuttled between the retina and vitreous. We also identified human disease biomarkers represented in the mouse vitreous and retina, including carbonic anhydrase-2 and 3, crystallins, macrophage inhibitory factor, glutathione peroxidase, peroxiredoxins, S100 precursors, and von Willebrand factor. Our analysis suggests the vitreous expresses nonstructural proteins that functionally interact with the retina to manage oxidative stress, immune reactions, and intracellular proteins may be exchanged between the retina and vitreous. This novel proteomic dataset can be used for investigating human vitreoretinopathies in mouse models. Validation of vitreoretinal biomarkers for human ocular diseases will provide a critical tool for diagnostics and an avenue for therapeutics.

Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks.

PubMed

Tan, Jie; Doing, Georgia; Lewis, Kimberley A; Price, Courtney E; Chen, Kathleen M; Cady, Kyle C; Perchuk, Barret; Laub, Michael T; Hogan, Deborah A; Greene, Casey S

2017-07-26

Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, but because ADAGE models, like many neural networks, are over-parameterized, different ADAGE models perform equally well. To enhance model robustness and better build signatures consistent with biological pathways, we developed an ensemble ADAGE (eADAGE) that integrated stable signatures across models. We applied eADAGE to a compendium of Pseudomonas aeruginosa gene expression profiling experiments performed in 78 media. eADAGE revealed a phosphate starvation response controlled by PhoB in media with moderate phosphate and predicted that a second stimulus provided by the sensor kinase, KinB, is required for this PhoB activation. We validated this relationship using both targeted and unbiased genetic approaches. eADAGE, which captures stable biological patterns, enables cross-experiment comparisons that can highlight measured but undiscovered relationships. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Metadynamics Enhanced Markov Modeling of Protein Dynamics.

PubMed

Biswas, Mithun; Lickert, Benjamin; Stock, Gerhard

2018-05-31

Enhanced sampling techniques represent a versatile approach to account for rare conformational transitions in biomolecules. A particularly promising strategy is to combine massive parallel computing of short molecular dynamics (MD) trajectories (to sample the free energy landscape of the system) with Markov state modeling (to rebuild the kinetics from the sampled data). To obtain well-distributed initial structures for the short trajectories, it is proposed to employ metadynamics MD, which quickly sweeps through the entire free energy landscape of interest. Being only used to generate initial conformations, the implementation of metadynamics can be simple and fast. The conformational dynamics of helical peptide Aib 9 is adopted to discuss various technical issues of the approach, including metadynamics settings, minimal number and length of short MD trajectories, and the validation of the resulting Markov models. Using metadynamics to launch some thousands of nanosecond trajectories, several Markov state models are constructed that reveal that previous unbiased MD simulations of in total 16 μs length cannot provide correct equilibrium populations or qualitative features of the pathway distribution of the short peptide.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

PubMed

Yu, Sheng; Liao, Katherine P; Shaw, Stanley Y; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Cai, Tianxi

2015-09-01

Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy. Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype. The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features. Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable. The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Joint modelling compared with two stage methods for analysing longitudinal data and prospective outcomes: A simulation study of childhood growth and BP.

PubMed

Sayers, A; Heron, J; Smith, Adac; Macdonald-Wallis, C; Gilthorpe, M S; Steele, F; Tilling, K

2017-02-01

There is a growing debate with regards to the appropriate methods of analysis of growth trajectories and their association with prospective dependent outcomes. Using the example of childhood growth and adult BP, we conducted an extensive simulation study to explore four two-stage and two joint modelling methods, and compared their bias and coverage in estimation of the (unconditional) association between birth length and later BP, and the association between growth rate and later BP (conditional on birth length). We show that the two-stage method of using multilevel models to estimate growth parameters and relating these to outcome gives unbiased estimates of the conditional associations between growth and outcome. Using simulations, we demonstrate that the simple methods resulted in bias in the presence of measurement error, as did the two-stage multilevel method when looking at the total (unconditional) association of birth length with outcome. The two joint modelling methods gave unbiased results, but using the re-inflated residuals led to undercoverage of the confidence intervals. We conclude that either joint modelling or the simpler two-stage multilevel approach can be used to estimate conditional associations between growth and later outcomes, but that only joint modelling is unbiased with nominal coverage for unconditional associations.

Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families

PubMed Central

Xia, Jie; Tilahun, Ermias Lemma; Kebede, Eyob Hailu; Reid, Terry-Elinor; Zhang, Liangren; Wang, Xiang Simon

2015-01-01

Histone Deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective Histone Deacetylases Inhibitors (HDACIs). To facilitate the process, we constructed the Maximal Unbiased Benchmarking Data Sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs covers all 4 Classes including Class III (Sirtuins family) and 14 HDACs isoforms, composed of 631 inhibitors and 24,609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of “artificial enrichment” and “analogue bias”. We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets, and demonstrate that our MUBD-HDACs is unique in that it can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the “2D bias” and “LBVS favorable” effect within the benchmarking sets. In summary, MUBD-HDACs is the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that is available so far. MUBD-HDACs is freely available at http://www.xswlab.org/. PMID:25633490

Metabolomic studies identify changes in transmethylation and polyamine metabolism in a brain-specific mouse model of tuberous sclerosis complex.

PubMed

McKenna, James; Kapfhamer, David; Kinchen, Jason M; Wasek, Brandi; Dunworth, Matthew; Murray-Stewart, Tracy; Bottiglieri, Teodoro; Casero, Robert A; Gambello, Michael J

2018-06-15

Tuberous sclerosis complex (TSC) is an autosomal dominant neurodevelopmental disorder and the quintessential disorder of mechanistic Target of Rapamycin Complex 1 (mTORC1) dysregulation. Loss of either causative gene, TSC1 or TSC2, leads to constitutive mTORC1 kinase activation and a pathologically anabolic state of macromolecular biosynthesis. Little is known about the organ-specific metabolic reprogramming that occurs in TSC-affected organs. Using a mouse model of TSC in which Tsc2 is disrupted in radial glial precursors and their neuronal and glial descendants, we performed an unbiased metabolomic analysis of hippocampi to identify Tsc2-dependent metabolic changes. Significant metabolic reprogramming was found in well-established pathways associated with mTORC1 activation, including redox homeostasis, glutamine/tricarboxylic acid cycle, pentose and nucleotide metabolism. Changes in two novel pathways were identified: transmethylation and polyamine metabolism. Changes in transmethylation included reduced methionine, cystathionine, S-adenosylmethionine (SAM-the major methyl donor), reduced SAM/S-adenosylhomocysteine ratio (cellular methylation potential), and elevated betaine, an alternative methyl donor. These changes were associated with alterations in SAM-dependent methylation pathways and expression of the enzymes methionine adenosyltransferase 2A and cystathionine beta synthase. We also found increased levels of the polyamine putrescine due to increased activity of ornithine decarboxylase, the rate-determining enzyme in polyamine synthesis. Treatment of Tsc2+/- mice with the ornithine decarboxylase inhibitor α-difluoromethylornithine, to reduce putrescine synthesis dose-dependently reduced hippocampal astrogliosis. These data establish roles for SAM-dependent methylation reactions and polyamine metabolism in TSC neuropathology. Importantly, both pathways are amenable to nutritional or pharmacologic therapy.

Prestroke Proteomic Changes in Cerebral Microvessels in Stroke-Prone, Transgenic[hCETP]-Hyperlipidemic, Dahl Salt-Sensitive Hypertensive Rats

PubMed Central

Bergerat, Agnes; Decano, Julius; Wu, Chang-Jiun; Choi, Hyungwon; Nesvizhskii, Alexey I; Moran, Ann Marie; Ruiz-Opazo, Nelson; Steffen, Martin; Herrera, Victoria LM

2011-01-01

Stroke is the third leading cause of death in the United States with high rates of morbidity among survivors. The search to fill the unequivocal need for new therapeutic approaches would benefit from unbiased proteomic analyses of animal models of spontaneous stroke in the prestroke stage. Since brain microvessels play key roles in neurovascular coupling, we investigated prestroke microvascular proteome changes. Proteomic analysis of cerebral cortical microvessels (cMVs) was done by tandem mass spectrometry comparing two prestroke time points. Metaprotein-pathway analyses of proteomic spectral count data were done to identify risk factor–induced changes, followed by QSPEC-analyses of individual protein changes associated with increased stroke susceptibility. We report 26 cMV proteome profiles from male and female stroke-prone and non–stroke-prone rats at 2 months and 4.5 months of age prior to overt stroke events. We identified 1,934 proteins by two or more peptides. Metaprotein pathway analysis detected age-associated changes in energy metabolism and cell-to-microenvironment interactions, as well as sex-specific changes in energy metabolism and endothelial leukocyte transmigration pathways. Stroke susceptibility was associated independently with multiple protein changes associated with ischemia, angiogenesis or involved in blood brain barrier (BBB) integrity. Immunohistochemical analysis confirmed aquaporin-4 and laminin-α1 induction in cMVs, representative of proteomic changes with >65 Bayes factor (BF), associated with stroke susceptibility. Altogether, proteomic analysis demonstrates significant molecular changes in ischemic cerebral microvasculature in the prestroke stage, which could contribute to the observed model phenotype of microhemorrhages and postischemic hemorrhagic transformation. These pathways comprise putative targets for translational research of much needed novel diagnostic and therapeutic approaches for stroke. PMID:21519634

Minimum mean squared error (MSE) adjustment and the optimal Tykhonov-Phillips regularization parameter via reproducing best invariant quadratic uniformly unbiased estimates (repro-BIQUUE)

NASA Astrophysics Data System (ADS)

Schaffrin, Burkhard

2008-02-01

In a linear Gauss-Markov model, the parameter estimates from BLUUE (Best Linear Uniformly Unbiased Estimate) are not robust against possible outliers in the observations. Moreover, by giving up the unbiasedness constraint, the mean squared error (MSE) risk may be further reduced, in particular when the problem is ill-posed. In this paper, the α-weighted S-homBLE (Best homogeneously Linear Estimate) is derived via formulas originally used for variance component estimation on the basis of the repro-BIQUUE (reproducing Best Invariant Quadratic Uniformly Unbiased Estimate) principle in a model with stochastic prior information. In the present model, however, such prior information is not included, which allows the comparison of the stochastic approach (α-weighted S-homBLE) with the well-established algebraic approach of Tykhonov-Phillips regularization, also known as R-HAPS (Hybrid APproximation Solution), whenever the inverse of the “substitute matrix” S exists and is chosen as the R matrix that defines the relative impact of the regularizing term on the final result.

Unbiased plasma metabolomics reveal the correlation of metabolic pathways and Prakritis of humans.

PubMed

Shirolkar, Amey; Chakraborty, Sutapa; Mandal, Tusharkanti; Dabur, Rajesh

2017-11-25

Ayurveda, an ancient Indian medicinal system, has categorized human body constitutions in three broad constitutional types (prakritis) i.e. Vata, Pitta and Kapha. Analysis of plasma metabolites and related pathways to classify Prakriti specific dominant marker metabolites and metabolic pathways. 38 healthy male individuals were assessed for dominant Prakritis and their fasting blood samples were collected. The processed plasma samples were subjected to rapid resolution liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (RRLC-ESI-QTOFMS). Mass profiles were aligned and subjected to multivariate analysis. Partial least square discriminant analysis (PLS-DA) model showed 97.87% recognition capability. List of PLS-DA metabolites was subjected to permutative Benjamini-Hochberg false discovery rate (FDR) correction and final list of 76 metabolites with p < 0.05 and fold-change > 2.0 was identified. Pathway analysis using metascape and JEPETTO plugins in Cytoscape revealed that steroidal hormone biosynthesis, amino acid, and arachidonic acid metabolism are major pathways varying with different constitution. Biological Go processes analysis showed that aromatic amino acids, sphingolipids, and pyrimidine nucleotides metabolic processes were dominant in kapha type of body constitution. Fat soluble vitamins, cellular amino acid, and androgen biosynthesis process along with branched chain amino acid and glycerolipid catabolic processes were dominant in pitta type individuals. Vata Prakriti was found to have dominant catecholamine, arachidonic acid and hydrogen peroxide metabolomics processes. The neurotransmission and oxidative stress in vata, BCAA catabolic, androgen, xenobiotics metabolic processes in pitta, and aromatic amino acids, sphingolipid, and pyrimidine metabolic process in kaphaPrakriti were the dominant marker pathways. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights reserved.

Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism.

PubMed

Tabe-Bordbar, Shayan; Marashi, Sayed-Amir

2013-12-01

Elementary modes (EMs) are steady-state metabolic flux vectors with minimal set of active reactions. Each EM corresponds to a metabolic pathway. Therefore, studying EMs is helpful for analyzing the production of biotechnologically important metabolites. However, memory requirements for computing EMs may hamper their applicability as, in most genome-scale metabolic models, no EM can be computed due to running out of memory. In this study, we present a method for computing randomly sampled EMs. In this approach, a network reduction algorithm is used for EM computation, which is based on flux balance-based methods. We show that this approach can be used to recover the EMs in the medium- and genome-scale metabolic network models, while the EMs are sampled in an unbiased way. The applicability of such results is shown by computing “estimated” control-effective flux values in Escherichia coli metabolic network.

Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex.

PubMed

Pollen, Alex A; Nowakowski, Tomasz J; Shuga, Joe; Wang, Xiaohui; Leyrat, Anne A; Lui, Jan H; Li, Nianzhen; Szpankowski, Lukasz; Fowler, Brian; Chen, Peilin; Ramalingam, Naveen; Sun, Gang; Thu, Myo; Norris, Michael; Lebofsky, Ronald; Toppani, Dominique; Kemp, Darnell W; Wong, Michael; Clerkson, Barry; Jones, Brittnee N; Wu, Shiquan; Knutsson, Lawrence; Alvarado, Beatriz; Wang, Jing; Weaver, Lesley S; May, Andrew P; Jones, Robert C; Unger, Marc A; Kriegstein, Arnold R; West, Jay A A

2014-10-01

Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been investigated directly. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In the developing cortex, we identify diverse cell types, including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.

Serum Metabolomic Profiling in Acute Alcoholic Hepatitis Identifies Multiple Dysregulated Pathways

PubMed Central

Rachakonda, Vikrant; Gabbert, Charles; Raina, Amit; Bell, Lauren N.; Cooper, Sara; Malik, Shahid; Behari, Jaideep

2014-01-01

Background and Objectives While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH), the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. Methods This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. Results Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA) cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. Conclusion Severe AAH is characterized by a distinct metabolic phenotype spanning multiple pathways. Metabolomics profiling revealed a panel of biomarkers for disease prognosis, and future studies are planned to validate these findings in larger cohorts of patients with severe AAH. PMID:25461442

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches.

PubMed

Arazi, Arnon; Pendergraft, William F; Ribeiro, Ruy M; Perelson, Alan S; Hacohen, Nir

2013-10-31

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology. Copyright © 2012 Elsevier Ltd. All rights reserved.

A cross-correlation-based estimate of the galaxy luminosity function

NASA Astrophysics Data System (ADS)

van Daalen, Marcel P.; White, Martin

2018-06-01

We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased redshift distributions and, for the first time, redshift-dependent luminosity functions, using only clustering information and the apparent magnitudes of the galaxies as input. In contrast to many existing techniques for recovering unbiased redshift distributions, the output of our method is not degenerate with the galaxy bias b(z), which is achieved by modelling the shape of the luminosity bias. We successfully apply our method to a mock galaxy survey and discuss improvements to be made before applying our model to real data.

Molecular pathogenesis of splenic and nodal marginal zone lymphoma.

PubMed

Spina, Valeria; Rossi, Davide

Genomic studies have improved our understanding of the biological basis of splenic (SMZL) and nodal (NMZL) marginal zone lymphoma by providing a comprehensive and unbiased view of the genes/pathways that are deregulated in these diseases. Consistent with the physiological involvement of NOTCH, NF-κB, B-cell receptor and toll-like receptor signaling in mature B-cells differentiation into the marginal zone B-cells, many oncogenic mutations of genes involved in these pathways have been identified in SMZL and NMZL. Beside genetic lesions, also epigenetic and post-transcriptional modifications contribute to the deregulation of marginal zone B-cell differentiation pathways in SMZL and NMZL. This review describes the progress in understanding the molecular mechanism underlying SMZL and NMZL, including molecular and post-transcriptional modifications, and discusses how information gained from these efforts has provided new insights on potential targets of diagnostic, prognostic and therapeutic relevance in SMZL and NMZL. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pyroptosis by caspase11/4-gasdermin-D pathway in alcoholic hepatitis in mice and patients.

PubMed

Khanova, Elena; Wu, Raymond; Wang, Wen; Yan, Rui; Chen, Yibu; French, Samuel W; Llorente, Cristina; Pan, Stephanie Q; Yang, Qihong; Li, Yuchang; Lazaro, Raul; Ansong, Charles; Smith, Richard D; Bataller, Ramon; Morgan, Timothy; Schnabl, Bernd; Tsukamoto, Hidekazu

2018-05-01

Alcoholic hepatitis (AH) continues to be a disease with high mortality and no efficacious medical treatment. Although severe AH is presented as acute on chronic liver failure, what underlies this transition from chronic alcoholic steatohepatitis (ASH) to AH is largely unknown. To address this question, unbiased RNA sequencing and proteomic analyses were performed on livers of the recently developed AH mouse model, which exhibits the shift to AH from chronic ASH upon weekly alcohol binge, and these results are compared to gene expression profiling data from AH patients. This cross-analysis has identified Casp11 (CASP4 in humans) as a commonly up-regulated gene known to be involved in the noncanonical inflammasome pathway. Immunoblotting confirms CASP11/4 activation in AH mice and patients, but not in chronic ASH mice and healthy human livers. Gasdermin-D (GSDMD), which induces pyroptosis (lytic cell death caused by bacterial infection) downstream of CASP11/4 activation, is also activated in AH livers in mice and patients. CASP11 deficiency reduces GSDMD activation, bacterial load in the liver, and severity of AH in the mouse model. Conversely, the deficiency of interleukin-18, the key antimicrobial cytokine, aggravates hepatic bacterial load, GSDMD activation, and AH. Furthermore, hepatocyte-specific expression of constitutively active GSDMD worsens hepatocellular lytic death and polymorphonuclear leukocyte inflammation. These results implicate pyroptosis induced by the CASP11/4-GSDMD pathway in the pathogenesis of AH. (Hepatology 2018;67:1737-1753). © 2017 by the American Association for the Study of Liver Diseases.

Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4.

PubMed

Bouillon-Pichault, Marion; Jullien, Vincent; Bazzoli, Caroline; Pons, Gérard; Tod, Michel

2011-02-01

The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Large deviations in the presence of cooperativity and slow dynamics

NASA Astrophysics Data System (ADS)

Whitelam, Stephen

2018-06-01

We study simple models of intermittency, involving switching between two states, within the dynamical large-deviation formalism. Singularities appear in the formalism when switching is cooperative or when its basic time scale diverges. In the first case the unbiased trajectory distribution undergoes a symmetry breaking, leading to a change in shape of the large-deviation rate function for a particular dynamical observable. In the second case the symmetry of the unbiased trajectory distribution remains unbroken. Comparison of these models suggests that singularities of the dynamical large-deviation formalism can signal the dynamical equivalent of an equilibrium phase transition but do not necessarily do so.

Comparison of estimators of standard deviation for hydrologic time series

USGS Publications Warehouse

Tasker, Gary D.; Gilroy, Edward J.

1982-01-01

Unbiasing factors as a function of serial correlation, ρ, and sample size, n for the sample standard deviation of a lag one autoregressive model were generated by random number simulation. Monte Carlo experiments were used to compare the performance of several alternative methods for estimating the standard deviation σ of a lag one autoregressive model in terms of bias, root mean square error, probability of underestimation, and expected opportunity design loss. Three methods provided estimates of σ which were much less biased but had greater mean square errors than the usual estimate of σ: s = (1/(n - 1) ∑ (xi −x¯)2)½. The three methods may be briefly characterized as (1) a method using a maximum likelihood estimate of the unbiasing factor, (2) a method using an empirical Bayes estimate of the unbiasing factor, and (3) a robust nonparametric estimate of σ suggested by Quenouille. Because s tends to underestimate σ, its use as an estimate of a model parameter results in a tendency to underdesign. If underdesign losses are considered more serious than overdesign losses, then the choice of one of the less biased methods may be wise.

Haem-activated promiscuous targeting of artemisinin in Plasmodium falciparum.

PubMed

Wang, Jigang; Zhang, Chong-Jing; Chia, Wan Ni; Loh, Cheryl C Y; Li, Zhengjun; Lee, Yew Mun; He, Yingke; Yuan, Li-Xia; Lim, Teck Kwang; Liu, Min; Liew, Chin Xia; Lee, Yan Quan; Zhang, Jianbin; Lu, Nianci; Lim, Chwee Teck; Hua, Zi-Chun; Liu, Bin; Shen, Han-Ming; Tan, Kevin S W; Lin, Qingsong

2015-12-22

The mechanism of action of artemisinin and its derivatives, the most potent of the anti-malarial drugs, is not completely understood. Here we present an unbiased chemical proteomics analysis to directly explore this mechanism in Plasmodium falciparum. We use an alkyne-tagged artemisinin analogue coupled with biotin to identify 124 artemisinin covalent binding protein targets, many of which are involved in the essential biological processes of the parasite. Such a broad targeting spectrum disrupts the biochemical landscape of the parasite and causes its death. Furthermore, using alkyne-tagged artemisinin coupled with a fluorescent dye to monitor protein binding, we show that haem, rather than free ferrous iron, is predominantly responsible for artemisinin activation. The haem derives primarily from the parasite's haem biosynthesis pathway at the early ring stage and from haemoglobin digestion at the latter stages. Our results support a unifying model to explain the action and specificity of artemisinin in parasite killing.

Haem-activated promiscuous targeting of artemisinin in Plasmodium falciparum

PubMed Central

Wang, Jigang; Zhang, Chong-Jing; Chia, Wan Ni; Loh, Cheryl C. Y.; Li, Zhengjun; Lee, Yew Mun; He, Yingke; Yuan, Li-Xia; Lim, Teck Kwang; Liu, Min; Liew, Chin Xia; Lee, Yan Quan; Zhang, Jianbin; Lu, Nianci; Lim, Chwee Teck; Hua, Zi-Chun; Liu, Bin; Shen, Han-Ming; Tan, Kevin S. W.; Lin, Qingsong

2015-01-01

The mechanism of action of artemisinin and its derivatives, the most potent of the anti-malarial drugs, is not completely understood. Here we present an unbiased chemical proteomics analysis to directly explore this mechanism in Plasmodium falciparum. We use an alkyne-tagged artemisinin analogue coupled with biotin to identify 124 artemisinin covalent binding protein targets, many of which are involved in the essential biological processes of the parasite. Such a broad targeting spectrum disrupts the biochemical landscape of the parasite and causes its death. Furthermore, using alkyne-tagged artemisinin coupled with a fluorescent dye to monitor protein binding, we show that haem, rather than free ferrous iron, is predominantly responsible for artemisinin activation. The haem derives primarily from the parasite's haem biosynthesis pathway at the early ring stage and from haemoglobin digestion at the latter stages. Our results support a unifying model to explain the action and specificity of artemisinin in parasite killing. PMID:26694030

A systems biology-led insight into the role of the proteome in neurodegenerative diseases.

PubMed

Fasano, Mauro; Monti, Chiara; Alberio, Tiziana

2016-09-01

Multifactorial disorders are the result of nonlinear interactions of several factors; therefore, a reductionist approach does not appear to be appropriate. Proteomics is a global approach that can be efficiently used to investigate pathogenetic mechanisms of neurodegenerative diseases. Here, we report a general introduction about the systems biology approach and mechanistic insights recently obtained by over-representation analysis of proteomics data of cellular and animal models of Alzheimer's disease, Parkinson's disease and other neurodegenerative disorders, as well as of affected human tissues. Expert commentary: As an inductive method, proteomics is based on unbiased observations that further require validation of generated hypotheses. Pathway databases and over-representation analysis tools allow researchers to assign an expectation value to pathogenetic mechanisms linked to neurodegenerative diseases. The systems biology approach based on omics data may be the key to unravel the complex mechanisms underlying neurodegeneration.

Mutually unbiased product bases for multiple qudits

DOE Office of Scientific and Technical Information (OSTI.GOV)

McNulty, Daniel; Pammer, Bogdan; Weigert, Stefan

We investigate the interplay between mutual unbiasedness and product bases for multiple qudits of possibly different dimensions. A product state of such a system is shown to be mutually unbiased to a product basis only if each of its factors is mutually unbiased to all the states which occur in the corresponding factors of the product basis. This result implies both a tight limit on the number of mutually unbiased product bases which the system can support and a complete classification of mutually unbiased product bases for multiple qubits or qutrits. In addition, only maximally entangled states can be mutuallymore » unbiased to a maximal set of mutually unbiased product bases.« less

An Electrostatic Funnel in the GABA-Binding Pathway

PubMed Central

Lightstone, Felice C.

2016-01-01

The γ-aminobutyric acid type A receptor (GABAA-R) is a major inhibitory neuroreceptor that is activated by the binding of GABA. The structure of the GABAA-R is well characterized, and many of the binding site residues have been identified. However, most of these residues are obscured behind the C-loop that acts as a cover to the binding site. Thus, the mechanism by which the GABA molecule recognizes the binding site, and the pathway it takes to enter the binding site are both unclear. Through the completion and detailed analysis of 100 short, unbiased, independent molecular dynamics simulations, we have investigated this phenomenon of GABA entering the binding site. In each system, GABA was placed quasi-randomly near the binding site of a GABAA-R homology model, and atomistic simulations were carried out to observe the behavior of the GABA molecules. GABA fully entered the binding site in 19 of the 100 simulations. The pathway taken by these molecules was consistent and non-random; the GABA molecules approach the binding site from below, before passing up behind the C-loop and into the binding site. This binding pathway is driven by long-range electrostatic interactions, whereby the electrostatic field acts as a ‘funnel’ that sweeps the GABA molecules towards the binding site, at which point more specific atomic interactions take over. These findings define a nuanced mechanism whereby the GABAA-R uses the general zwitterionic features of the GABA molecule to identify a potential ligand some 2 nm away from the binding site. PMID:27119953

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

PubMed Central

Rosenblum, Michael; van der Laan, Mark J.

2010-01-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

Impact of using scatterometer and altimeter data on storm surge forecasting

NASA Astrophysics Data System (ADS)

Bajo, Marco; De Biasio, Francesco; Umgiesser, Georg; Vignudelli, Stefano; Zecchetto, Stefano

2017-05-01

Satellite data are rarely used in storm surge models because of the lack of established methodologies. Nevertheless, they can provide useful information on surface wind and sea level, which can potentially improve the forecast. In this paper satellite wind data are used to correct the bias of wind originating from a global atmospheric model, while satellite sea level data are used to improve the initial conditions of the model simulations. In a first step, the capability of global winds (biased and unbiased) to adequately force a storm surge model are assessed against that of a high resolution local wind. Then, the added value of direct assimilation of satellite altimeter data in the storm surge model is tested. Eleven storm surge events, recorded in Venice from 2008 to 2012, are simulated using different configurations of wind forcing and altimeter data assimilation. Focusing on the maximum surge peak, results show that the relative error, averaged over the eleven cases considered, decreases from 13% to 7%, using both the unbiased wind and assimilating the altimeter data, while, if the high resolution local wind is used to force the hydrodynamic model, the altimeter data assimilation reduces the error from 9% to 6%. Yet, the overall capabilities in reproducing the surge in the first day of forecast, measured by the correlation and by the rms error, improve only with the use of the unbiased global wind and not with the use of high resolution local wind and altimeter data assimilation.

Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data

PubMed Central

2011-01-01

Background With the advent of high-throughput targeted metabolic profiling techniques, the question of how to interpret and analyze the resulting vast amount of data becomes more and more important. In this work we address the reconstruction of metabolic reactions from cross-sectional metabolomics data, that is without the requirement for time-resolved measurements or specific system perturbations. Previous studies in this area mainly focused on Pearson correlation coefficients, which however are generally incapable of distinguishing between direct and indirect metabolic interactions. Results In our new approach we propose the application of a Gaussian graphical model (GGM), an undirected probabilistic graphical model estimating the conditional dependence between variables. GGMs are based on partial correlation coefficients, that is pairwise Pearson correlation coefficients conditioned against the correlation with all other metabolites. We first demonstrate the general validity of the method and its advantages over regular correlation networks with computer-simulated reaction systems. Then we estimate a GGM on data from a large human population cohort, covering 1020 fasting blood serum samples with 151 quantified metabolites. The GGM is much sparser than the correlation network, shows a modular structure with respect to metabolite classes, and is stable to the choice of samples in the data set. On the example of human fatty acid metabolism, we demonstrate for the first time that high partial correlation coefficients generally correspond to known metabolic reactions. This feature is evaluated both manually by investigating specific pairs of high-scoring metabolites, and then systematically on a literature-curated model of fatty acid synthesis and degradation. Our method detects many known reactions along with possibly novel pathway interactions, representing candidates for further experimental examination. Conclusions In summary, we demonstrate strong signatures of intracellular pathways in blood serum data, and provide a valuable tool for the unbiased reconstruction of metabolic reactions from large-scale metabolomics data sets. PMID:21281499

[Application of ordinary Kriging method in entomologic ecology].

PubMed

Zhang, Runjie; Zhou, Qiang; Chen, Cuixian; Wang, Shousong

2003-01-01

Geostatistics is a statistic method based on regional variables and using the tool of variogram to analyze the spatial structure and the patterns of organism. In simulating the variogram within a great range, though optimal simulation cannot be obtained, the simulation method of a dialogue between human and computer can be used to optimize the parameters of the spherical models. In this paper, the method mentioned above and the weighted polynomial regression were utilized to simulate the one-step spherical model, the two-step spherical model and linear function model, and the available nearby samples were used to draw on the ordinary Kriging procedure, which provided a best linear unbiased estimate of the constraint of the unbiased estimation. The sum of square deviation between the estimating and measuring values of varying theory models were figured out, and the relative graphs were shown. It was showed that the simulation based on the two-step spherical model was the best simulation, and the one-step spherical model was better than the linear function model.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

Impact of Transcriptomics on Our Understanding of Pulmonary Fibrosis

PubMed Central

Vukmirovic, Milica; Kaminski, Naftali

2018-01-01

Idiopathic pulmonary fibrosis (IPF) is a lethal fibrotic lung disease characterized by aberrant remodeling of the lung parenchyma with extensive changes to the phenotypes of all lung resident cells. The introduction of transcriptomics, genome scale profiling of thousands of RNA transcripts, caused a significant inversion in IPF research. Instead of generating hypotheses based on animal models of disease, or biological plausibility, with limited validation in humans, investigators were able to generate hypotheses based on unbiased molecular analysis of human samples and then use animal models of disease to test their hypotheses. In this review, we describe the insights made from transcriptomic analysis of human IPF samples. We describe how transcriptomic studies led to identification of novel genes and pathways involved in the human IPF lung such as: matrix metalloproteinases, WNT pathway, epithelial genes, role of microRNAs among others, as well as conceptual insights such as the involvement of developmental pathways and deep shifts in epithelial and fibroblast phenotypes. The impact of lung and transcriptomic studies on disease classification, endotype discovery, and reproducible biomarkers is also described in detail. Despite these impressive achievements, the impact of transcriptomic studies has been limited because they analyzed bulk tissue and did not address the cellular and spatial heterogeneity of the IPF lung. We discuss new emerging technologies and applications, such as single-cell RNAseq and microenvironment analysis that may address cellular and spatial heterogeneity. We end by making the point that most current tissue collections and resources are not amenable to analysis using the novel technologies. To take advantage of the new opportunities, we need new efforts of sample collections, this time focused on access to all the microenvironments and cells in the IPF lung. PMID:29670881

Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data

PubMed Central

Gritsenko, Alexey A.; Hulsman, Marc; Reinders, Marcel J. T.; de Ridder, Dick

2015-01-01

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates. PMID:26275099

Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data.

PubMed

Gritsenko, Alexey A; Hulsman, Marc; Reinders, Marcel J T; de Ridder, Dick

2015-08-01

Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates.

Characterization of Ciprofloxacin Permeation Pathways across the Porin OmpC Using Metadynamics and a String Method.

PubMed

Prajapati, Jigneshkumar Dahyabhai; Fernández Solano, Carlos José; Winterhalter, Mathias; Kleinekathöfer, Ulrich

2017-09-12

The rapid spreading of antimicrobial resistance in Gram-negative bacteria has become a major threat for humans as well as animals. As one of the main factors involved, the permeability of the outer membrane has attracted a great deal of attention recently. However, the knowledge regarding the translocation mechanisms for most available antibiotics is so far rather limited. Here, a theoretical study concerning the diffusion route of ciprofloxacin across the outer membrane porin OmpC from E. coli is presented. To this end, we establish a protocol to characterize meaningful permeation pathways by combining metadynamics with the zero-temperature string method. It was found that the lowest-energy pathway requires a reorientation of ciprofloxacin in the extracellular side of the porin before reaching the constriction region with its carboxyl group ahead. Several affinity sites have been identified, and their metastability has been evaluated using unbiased simulations. Such a detailed understanding is potentially very helpful in guiding the development of next generation antibiotics.

Sampling the multiple folding mechanisms of Trp-cage in explicit solvent

PubMed Central

Juraszek, J.; Bolhuis, P. G.

2006-01-01

We investigate the kinetic pathways of folding and unfolding of the designed miniprotein Trp- cage in explicit solvent. Straightforward molecular dynamics and replica exchange methods both have severe convergence problems, whereas transition path sampling allows us to sample unbiased dynamical pathways between folded and unfolded states and leads to deeper understanding of the mechanisms of (un)folding. In contrast to previous predictions employing an implicit solvent, we find that Trp-cage folds primarily (80% of the paths) via a pathway forming the tertiary contacts and the salt bridge, before helix formation. The remaining 20% of the paths occur in the opposite order, by first forming the helix. The transition states of the rate-limiting steps are solvated native-like structures. Water expulsion is found to be the last step upon folding for each route. Committor analysis suggests that the dynamics of the solvent is not part of the reaction coordinate. Nevertheless, during the transition, specific water molecules are strongly bound and can play a structural role in the folding. PMID:17035504

The Quantitative-MFG Test: A Linear Mixed Effect Model to Detect Maternal-Offspring Gene Interactions.

PubMed

Clark, Michelle M; Blangero, John; Dyer, Thomas D; Sobel, Eric M; Sinsheimer, Janet S

2016-01-01

Maternal-offspring gene interactions, aka maternal-fetal genotype (MFG) incompatibilities, are neglected in complex diseases and quantitative trait studies. They are implicated in birth to adult onset diseases but there are limited ways to investigate their influence on quantitative traits. We present the quantitative-MFG (QMFG) test, a linear mixed model where maternal and offspring genotypes are fixed effects and residual correlations between family members are random effects. The QMFG handles families of any size, common or general scenarios of MFG incompatibility, and additional covariates. We develop likelihood ratio tests (LRTs) and rapid score tests and show they provide correct inference. In addition, the LRT's alternative model provides unbiased parameter estimates. We show that testing the association of SNPs by fitting a standard model, which only considers the offspring genotypes, has very low power or can lead to incorrect conclusions. We also show that offspring genetic effects are missed if the MFG modeling assumptions are too restrictive. With genome-wide association study data from the San Antonio Family Heart Study, we demonstrate that the QMFG score test is an effective and rapid screening tool. The QMFG test therefore has important potential to identify pathways of complex diseases for which the genetic etiology remains to be discovered. © 2015 John Wiley & Sons Ltd/University College London.

Maximum likelihood: Extracting unbiased information from complex networks

NASA Astrophysics Data System (ADS)

Garlaschelli, Diego; Loffredo, Maria I.

2008-07-01

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the maximum likelihood (ML) principle indicates a unique, statistically rigorous parameter choice, associated with a well-defined topological feature. We then find that, if the ML condition is incompatible with the built-in parameter choice, network models turn out to be intrinsically ill defined or biased. To overcome this problem, we construct a class of safely unbiased models. We also propose an extension of these results that leads to the fascinating possibility to extract, only from topological data, the “hidden variables” underlying network organization, making them “no longer hidden.” We test our method on World Trade Web data, where we recover the empirical gross domestic product using only topological information.

Using Maximum Entropy to Find Patterns in Genomes

NASA Astrophysics Data System (ADS)

Liu, Sophia; Hockenberry, Adam; Lancichinetti, Andrea; Jewett, Michael; Amaral, Luis

The existence of over- and under-represented sequence motifs in genomes provides evidence of selective evolutionary pressures on biological mechanisms such as transcription, translation, ligand-substrate binding, and host immunity. To accurately identify motifs and other genome-scale patterns of interest, it is essential to be able to generate accurate null models that are appropriate for the sequences under study. There are currently no tools available that allow users to create random coding sequences with specified amino acid composition and GC content. Using the principle of maximum entropy, we developed a method that generates unbiased random sequences with pre-specified amino acid and GC content. Our method is the simplest way to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. This approach can also be easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes. National Institute of General Medical Science, Northwestern University Presidential Fellowship, National Science Foundation, David and Lucile Packard Foundation, Camille Dreyfus Teacher Scholar Award.

Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches.

PubMed

Guenole, Nigel

2018-01-01

The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository.

Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches

PubMed Central

Guenole, Nigel

2018-01-01

The test for item level cluster bias examines the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and between level residual variances fixed at zero. A potential problem is that this approach may include a misspecified unrestricted model if any non-invariance is present, but the log-likelihood difference test requires that the unrestricted model is correctly specified. A free baseline approach where the unrestricted model includes only the restrictions needed for model identification should lead to better decision accuracy, but no studies have examined this yet. We ran a Monte Carlo study to investigate this issue. When the referent item is unbiased, compared to the free baseline approach, the constrained baseline approach led to similar true positive (power) rates but much higher false positive (Type I error) rates. The free baseline approach should be preferred when the referent indicator is unbiased. When the referent assumption is violated, the false positive rate was unacceptably high for both free and constrained baseline approaches, and the true positive rate was poor regardless of whether the free or constrained baseline approach was used. Neither the free or constrained baseline approach can be recommended when the referent indicator is biased. We recommend paying close attention to ensuring the referent indicator is unbiased in tests of cluster bias. All Mplus input and output files, R, and short Python scripts used to execute this simulation study are uploaded to an open access repository. PMID:29551985

Regression calibration for models with two predictor variables measured with error and their interaction, using instrumental variables and longitudinal data.

PubMed

Strand, Matthew; Sillau, Stefan; Grunwald, Gary K; Rabinovitch, Nathan

2014-02-10

Regression calibration provides a way to obtain unbiased estimators of fixed effects in regression models when one or more predictors are measured with error. Recent development of measurement error methods has focused on models that include interaction terms between measured-with-error predictors, and separately, methods for estimation in models that account for correlated data. In this work, we derive explicit and novel forms of regression calibration estimators and associated asymptotic variances for longitudinal models that include interaction terms, when data from instrumental and unbiased surrogate variables are available but not the actual predictors of interest. The longitudinal data are fit using linear mixed models that contain random intercepts and account for serial correlation and unequally spaced observations. The motivating application involves a longitudinal study of exposure to two pollutants (predictors) - outdoor fine particulate matter and cigarette smoke - and their association in interactive form with levels of a biomarker of inflammation, leukotriene E4 (LTE 4 , outcome) in asthmatic children. Because the exposure concentrations could not be directly observed, we used measurements from a fixed outdoor monitor and urinary cotinine concentrations as instrumental variables, and we used concentrations of fine ambient particulate matter and cigarette smoke measured with error by personal monitors as unbiased surrogate variables. We applied the derived regression calibration methods to estimate coefficients of the unobserved predictors and their interaction, allowing for direct comparison of toxicity of the different pollutants. We used simulations to verify accuracy of inferential methods based on asymptotic theory. Copyright © 2013 John Wiley & Sons, Ltd.

Stochastic loss and gain of symmetric divisions in the C. elegans epidermis perturbs robustness of stem cell number

PubMed Central

Katsanos, Dimitris; Koneru, Sneha L.; Mestek Boukhibar, Lamia; Gritti, Nicola; Ghose, Ritobrata; Appleford, Peter J.; Doitsidou, Maria; Woollard, Alison; van Zon, Jeroen S.; Poole, Richard J.

2017-01-01

Biological systems are subject to inherent stochasticity. Nevertheless, development is remarkably robust, ensuring the consistency of key phenotypic traits such as correct cell numbers in a certain tissue. It is currently unclear which genes modulate phenotypic variability, what their relationship is to core components of developmental gene networks, and what is the developmental basis of variable phenotypes. Here, we start addressing these questions using the robust number of Caenorhabditis elegans epidermal stem cells, known as seam cells, as a readout. We employ genetics, cell lineage tracing, and single molecule imaging to show that mutations in lin-22, a Hes-related basic helix-loop-helix (bHLH) transcription factor, increase seam cell number variability. We show that the increase in phenotypic variability is due to stochastic conversion of normally symmetric cell divisions to asymmetric and vice versa during development, which affect the terminal seam cell number in opposing directions. We demonstrate that LIN-22 acts within the epidermal gene network to antagonise the Wnt signalling pathway. However, lin-22 mutants exhibit cell-to-cell variability in Wnt pathway activation, which correlates with and may drive phenotypic variability. Our study demonstrates the feasibility to study phenotypic trait variance in tractable model organisms using unbiased mutagenesis screens. PMID:29108019

Lipid body accumulation alters calcium signaling dynamics in immune cells

PubMed Central

Greineisen, William E.; Speck, Mark; Shimoda, Lori M.N.; Sung, Carl; Phan, Nolwenn; Maaetoft-Udsen, Kristina; Stokes, Alexander J.; Turner, Helen

2014-01-01

Summary There is well-established variability in the numbers of lipid bodies (LB) in macrophages, eosinophils, and neutrophils. Similarly to the steatosis observed in adipocytes and hepatocytes during hyperinsulinemia and nutrient overload, immune cell LB hyper-accumulate in response to bacterial and parasitic infection and inflammatory presentations. Recently we described that hyperinsulinemia, both in vitro and in vivo, drives steatosis and phenotypic changes in primary and transformed mast cells and basophils. LB reach high numbers in these steatotic cytosols, and here we propose that they could dramatically impact the transcytoplasmic signaling pathways. We compared calcium release and influx responses at the population and single cell level in normal and steatotic model mast cells. At the population level, all aspects of FcεRI-dependent calcium mobilization, as well as activation of calcium-dependent downstream signalling targets such as NFATC1 phosphorylation are suppressed. At the single cell level, we demonstrate that LB are both sources and sinks of calcium following FcεRI cross-linking. Unbiased analysis of the impact of the presence of LB on the rate of trans-cytoplasmic calcium signals suggest that LB enrichment accelerates calcium propagation, which may reflect a Bernoulli effect. LB abundance thus impacts this fundamental signalling pathway and its downstream targets. PMID:25016314

NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins.

PubMed

Krüger, Dennis M; Ahmed, Aqeel; Gohlke, Holger

2012-07-01

The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.

Application of toxicogenomic profiling to evaluate effects of benzene and formaldehyde: from yeast to human

PubMed Central

McHale, Cliona M.; Smith, Martyn T.; Zhang, Luoping

2014-01-01

Genetic variation underlies a significant proportion of the individual variation in human susceptibility to toxicants. The primary current approaches to identify gene–environment (GxE) associations, genome-wide association studies (GWAS) and candidate gene association studies, require large exposed and control populations and an understanding of toxicity genes and pathways, respectively. This limits their application in the study of GxE associations for the leukemogens benzene and formaldehyde, whose toxicity has long been a focus of our research. As an alternative approach, we applied innovative in vitro functional genomics testing systems, including unbiased functional screening assays in yeast and a near-haploid human bone marrow cell line (KBM7). Through comparative genomic and computational analyses of the resulting data, we have identified human genes and pathways that may modulate susceptibility to benzene and formaldehyde. We have validated the roles of several genes in mammalian cell models. In populations occupationally exposed to low levels of benzene, we applied peripheral blood mononuclear cell transcriptomics and chromosome-wide aneuploidy studies (CWAS) in lymphocytes. In this review of the literature, we describe our comprehensive toxicogenomic approach and the potential mechanisms of toxicity and susceptibility genes identified for benzene and formaldehyde, as well as related studies conducted by other researchers. PMID:24571325

Peripheral Blood Gene Expression as a Novel Genomic Biomarker in Complicated Sarcoidosis

PubMed Central

Sweiss, Nadera J.; Chen, Edward S.; Moller, David R.; Knox, Kenneth S.; Ma, Shwu-Fan; Wade, Michael S.; Noth, Imre; Machado, Roberto F.; Garcia, Joe G. N.

2012-01-01

Sarcoidosis, a systemic granulomatous syndrome invariably affecting the lung, typically spontaneously remits but in ∼20% of cases progresses with severe lung dysfunction or cardiac and neurologic involvement (complicated sarcoidosis). Unfortunately, current biomarkers fail to distinguish patients with remitting (uncomplicated) sarcoidosis from other fibrotic lung disorders, and fail to identify individuals at risk for complicated sarcoidosis. We utilized genome-wide peripheral blood gene expression analysis to identify a 20-gene sarcoidosis biomarker signature distinguishing sarcoidosis (n = 39) from healthy controls (n = 35, 86% classification accuracy) and which served as a molecular signature for complicated sarcoidosis (n = 17). As aberrancies in T cell receptor (TCR) signaling, JAK-STAT (JS) signaling, and cytokine-cytokine receptor (CCR) signaling are implicated in sarcoidosis pathogenesis, a 31-gene signature comprised of T cell signaling pathway genes associated with sarcoidosis (TCR/JS/CCR) was compared to the unbiased 20-gene biomarker signature but proved inferior in prediction accuracy in distinguishing complicated from uncomplicated sarcoidosis. Additional validation strategies included significant association of single nucleotide polymorphisms (SNPs) in signature genes with sarcoidosis susceptibility and severity (unbiased signature genes - CX3CR1, FKBP1A, NOG, RBM12B, SENS3, TSHZ2; T cell/JAK-STAT pathway genes such as AKT3, CBLB, DLG1, IFNG, IL2RA, IL7R, ITK, JUN, MALT1, NFATC2, PLCG1, SPRED1). In summary, this validated peripheral blood molecular gene signature appears to be a valuable biomarker in identifying cases with sarcoidoisis and predicting risk for complicated sarcoidosis. PMID:22984568

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

Elevation of adenylate energy charge by angiopoietin-like 4 enhances epithelial-mesenchymal transition by inducing 14-3-3γ expression.

PubMed

Teo, Z; Sng, M K; Chan, J S K; Lim, M M K; Li, Y; Li, L; Phua, T; Lee, J Y H; Tan, Z W; Zhu, P; Tan, N S

2017-11-16

Metastatic cancer cells acquire energy-intensive processes including increased invasiveness and chemoresistance. However, how the energy demand is met and the molecular drivers that coordinate an increase in cellular metabolic activity to drive epithelial-mesenchymal transition (EMT), the first step of metastasis, remain unclear. Using different in vitro and in vivo EMT models with clinical patient's samples, we showed that EMT is an energy-demanding process fueled by glucose metabolism-derived adenosine triphosphate (ATP). We identified angiopoietin-like 4 (ANGPTL4) as a key player that coordinates an increase in cellular energy flux crucial for EMT via an ANGPTL4/14-3-3γ signaling axis. This augmented cellular metabolic activity enhanced metastasis. ANGPTL4 knockdown suppresses an adenylate energy charge elevation, delaying EMT. Using an in vivo dual-inducible EMT model, we found that ANGPTL4 deficiency reduces cancer metastasis to the lung and liver. Unbiased kinase inhibitor screens and Ingenuity Pathway Analysis revealed that ANGPTL4 regulates the expression of 14-3-3γ adaptor protein via the phosphatidylinositol-3-kinase/AKT and mitogen-activated protein kinase signaling pathways that culminate to activation of transcription factors, CREB, cFOS and STAT3. Using a different mode of action, as compared with protein kinases, the ANGPTL4/14-3-3γ signaling axis consolidated cellular bioenergetics and stabilized critical EMT proteins to coordinate energy demand and enhanced EMT competency and metastasis, through interaction with specific phosphorylation signals on target proteins.

Building unbiased estimators from non-gaussian likelihoods with application to shear estimation

DOE PAGES

Madhavacheril, Mathew S.; McDonald, Patrick; Sehgal, Neelima; ...

2015-01-15

We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore » of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors Δg/g for shears up to |g| = 0.2.« less

Building unbiased estimators from non-Gaussian likelihoods with application to shear estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Madhavacheril, Mathew S.; Sehgal, Neelima; McDonald, Patrick

2015-01-01

We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore » of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong's estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors Δg/g for shears up to |g|=0.2.« less

Mutually unbiased projectors and duality between lines and bases in finite quantum systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shalaby, M.; Vourdas, A., E-mail: a.vourdas@bradford.ac.uk

2013-10-15

Quantum systems with variables in the ring Z(d) are considered, and the concepts of weak mutually unbiased bases and mutually unbiased projectors are discussed. The lines through the origin in the Z(d)×Z(d) phase space, are classified into maximal lines (sets of d points), and sublines (sets of d{sub i} points where d{sub i}|d). The sublines are intersections of maximal lines. It is shown that there exists a duality between the properties of lines (resp., sublines), and the properties of weak mutually unbiased bases (resp., mutually unbiased projectors). -- Highlights: •Lines in discrete phase space. •Bases in finite quantum systems. •Dualitymore » between bases and lines. •Weak mutually unbiased bases.« less

Atomic resolution mechanism of ligand binding to a solvent inaccessible cavity in T4 lysozyme

PubMed Central

Ahalawat, Navjeet; Pandit, Subhendu; Kay, Lewis E.

2018-01-01

Ligand binding sites in proteins are often localized to deeply buried cavities, inaccessible to bulk solvent. Yet, in many cases binding of cognate ligands occurs rapidly. An intriguing system is presented by the L99A cavity mutant of T4 Lysozyme (T4L L99A) that rapidly binds benzene (~106 M-1s-1). Although the protein has long served as a model system for protein thermodynamics and crystal structures of both free and benzene-bound T4L L99A are available, the kinetic pathways by which benzene reaches its solvent-inaccessible binding cavity remain elusive. The current work, using extensive molecular dynamics simulation, achieves this by capturing the complete process of spontaneous recognition of benzene by T4L L99A at atomistic resolution. A series of multi-microsecond unbiased molecular dynamics simulation trajectories unequivocally reveal how benzene, starting in bulk solvent, diffuses to the protein and spontaneously reaches the solvent inaccessible cavity of T4L L99A. The simulated and high-resolution X-ray derived bound structures are in excellent agreement. A robust four-state Markov model, developed using cumulative 60 μs trajectories, identifies and quantifies multiple ligand binding pathways with low activation barriers. Interestingly, none of these identified binding pathways required large conformational changes for ligand access to the buried cavity. Rather, these involve transient but crucial opening of a channel to the cavity via subtle displacements in the positions of key helices (helix4/helix6, helix7/helix9) leading to rapid binding. Free energy simulations further elucidate that these channel-opening events would have been unfavorable in wild type T4L. Taken together and via integrating with results from experiments, these simulations provide unprecedented mechanistic insights into the complete ligand recognition process in a buried cavity. By illustrating the power of subtle helix movements in opening up multiple pathways for ligand access, this work offers an alternate view of ligand recognition in a solvent-inaccessible cavity, contrary to the common perception of a single dominant pathway for ligand binding. PMID:29775455

A Model of the Temporal Dynamics of Knowledge Brokerage in Sustainable Development

ERIC Educational Resources Information Center

Hukkinen, Janne I.

2016-01-01

I develop a conceptual model of the temporal dynamics of knowledge brokerage for sustainable development. Brokerage refers to efforts to make research and policymaking more accessible to each other. The model enables unbiased and systematic consideration of knowledge brokerage as part of policy evolution. The model is theoretically grounded in…

Entropic uncertainty relations and locking: Tight bounds for mutually unbiased bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballester, Manuel A.; Wehner, Stephanie

We prove tight entropic uncertainty relations for a large number of mutually unbiased measurements. In particular, we show that a bound derived from the result by Maassen and Uffink [Phys. Rev. Lett. 60, 1103 (1988)] for two such measurements can in fact be tight for up to {radical}(d) measurements in mutually unbiased bases. We then show that using more mutually unbiased bases does not always lead to a better locking effect. We prove that the optimal bound for the accessible information using up to {radical}(d) specific mutually unbiased bases is log d/2, which is the same as can be achievedmore » by using only two bases. Our result indicates that merely using mutually unbiased bases is not sufficient to achieve a strong locking effect and we need to look for additional properties.« less

SIRAH: a structurally unbiased coarse-grained force field for proteins with aqueous solvation and long-range electrostatics.

PubMed

Darré, Leonardo; Machado, Matías Rodrigo; Brandner, Astrid Febe; González, Humberto Carlos; Ferreira, Sebastián; Pantano, Sergio

2015-02-10

Modeling of macromolecular structures and interactions represents an important challenge for computational biology, involving different time and length scales. However, this task can be facilitated through the use of coarse-grained (CG) models, which reduce the number of degrees of freedom and allow efficient exploration of complex conformational spaces. This article presents a new CG protein model named SIRAH, developed to work with explicit solvent and to capture sequence, temperature, and ionic strength effects in a topologically unbiased manner. SIRAH is implemented in GROMACS, and interactions are calculated using a standard pairwise Hamiltonian for classical molecular dynamics simulations. We present a set of simulations that test the capability of SIRAH to produce a qualitatively correct solvation on different amino acids, hydrophilic/hydrophobic interactions, and long-range electrostatic recognition leading to spontaneous association of unstructured peptides and stable structures of single polypeptides and protein-protein complexes.

Conformational free energy modeling of druglike molecules by metadynamics in the WHIM space.

PubMed

Spiwok, Vojtěch; Hlat-Glembová, Katarína; Tvaroška, Igor; Králová, Blanka

2012-03-26

Protein-ligand affinities can be significantly influenced not only by the interaction itself but also by conformational equilibrium of both binding partners, free ligand and free protein. Identification of important conformational families of a ligand and prediction of their thermodynamics is important for efficient ligand design. Here we report conformational free energy modeling of nine small-molecule drugs in explicitly modeled water by metadynamics with a bias potential applied in the space of weighted holistic invariant molecular (WHIM) descriptors. Application of metadynamics enhances conformational sampling compared to unbiased molecular dynamics simulation and allows to predict relative free energies of key conformations. Selected free energy minima and one example of transition state were tested by a series of unbiased molecular dynamics simulation. Comparison of free energy surfaces of free and target-bound Imatinib provides an estimate of free energy penalty of conformational change induced by its binding to the target. © 2012 American Chemical Society

Eicosanomic profiling reveals dominance of the epoxygenase pathway in human amniotic fluid at term in spontaneous labor.

PubMed

Maddipati, Krishna Rao; Romero, Roberto; Chaiworapongsa, Tinnakorn; Zhou, Sen-Lin; Xu, Zhonghui; Tarca, Adi L; Kusanovic, Juan Pedro; Munoz, Hernan; Honn, Kenneth V

2014-11-01

Lipid mediators play an important role in reproductive biology, especially, in parturition. Enhanced biosynthesis of eicosanoids, such as prostaglandin E2 (PGE2) and PGF2α, precedes the onset of labor as a result of increased expression of inducible cyclooxygenase 2 (COX-2) in placental tissues. Metabolism of arachidonic acid results in bioactive lipid mediators beyond prostaglandins that could significantly influence myometrial activity. Therefore, an unbiased lipidomic approach was used to profile the arachidonic acid metabolome of amniotic fluid. In this study, liquid chromatography-mass spectrometry was used for the first time to quantitate these metabolites in human amniotic fluid by comparing patients at midtrimester, at term but not in labor, and at term and in spontaneous labor. In addition to exposing novel aspects of COX pathway metabolism, this lipidomic study revealed a dramatic increase in epoxygenase- and lipoxygenase-pathway-derived lipid mediators in spontaneous labor with remarkable product selectivity. Despite their recognition as anti-inflammatory lipid mediators and regulators of ion channels, little is known about the epoxygenase pathway in labor. Epoxygenase pathway metabolites are established regulators of vascular homeostasis in cardiovascular and renal physiology. Their presence as the dominant lipid mediators in spontaneous labor at term portends a yet undiscovered physiological function in parturition. © FASEB.

Rasch-family models are more valuable than score-based approaches for analysing longitudinal patient-reported outcomes with missing data.

PubMed

de Bock, Élodie; Hardouin, Jean-Benoit; Blanchin, Myriam; Le Neel, Tanguy; Kubis, Gildas; Bonnaud-Antignac, Angélique; Dantan, Étienne; Sébille, Véronique

2016-10-01

The objective was to compare classical test theory and Rasch-family models derived from item response theory for the analysis of longitudinal patient-reported outcomes data with possibly informative intermittent missing items. A simulation study was performed in order to assess and compare the performance of classical test theory and Rasch model in terms of bias, control of the type I error and power of the test of time effect. The type I error was controlled for classical test theory and Rasch model whether data were complete or some items were missing. Both methods were unbiased and displayed similar power with complete data. When items were missing, Rasch model remained unbiased and displayed higher power than classical test theory. Rasch model performed better than the classical test theory approach regarding the analysis of longitudinal patient-reported outcomes with possibly informative intermittent missing items mainly for power. This study highlights the interest of Rasch-based models in clinical research and epidemiology for the analysis of incomplete patient-reported outcomes data. © The Author(s) 2013.

Extending unbiased stereology of brain ultrastructure to three-dimensional volumes

NASA Technical Reports Server (NTRS)

Fiala, J. C.; Harris, K. M.; Koslow, S. H. (Principal Investigator)

2001-01-01

OBJECTIVE: Analysis of brain ultrastructure is needed to reveal how neurons communicate with one another via synapses and how disease processes alter this communication. In the past, such analyses have usually been based on single or paired sections obtained by electron microscopy. Reconstruction from multiple serial sections provides a much needed, richer representation of the three-dimensional organization of the brain. This paper introduces a new reconstruction system and new methods for analyzing in three dimensions the location and ultrastructure of neuronal components, such as synapses, which are distributed non-randomly throughout the brain. DESIGN AND MEASUREMENTS: Volumes are reconstructed by defining transformations that align the entire area of adjacent sections. Whole-field alignment requires rotation, translation, skew, scaling, and second-order nonlinear deformations. Such transformations are implemented by a linear combination of bivariate polynomials. Computer software for generating transformations based on user input is described. Stereological techniques for assessing structural distributions in reconstructed volumes are the unbiased bricking, disector, unbiased ratio, and per-length counting techniques. A new general method, the fractional counter, is also described. This unbiased technique relies on the counting of fractions of objects contained in a test volume. A volume of brain tissue from stratum radiatum of hippocampal area CA1 is reconstructed and analyzed for synaptic density to demonstrate and compare the techniques. RESULTS AND CONCLUSIONS: Reconstruction makes practicable volume-oriented analysis of ultrastructure using such techniques as the unbiased bricking and fractional counter methods. These analysis methods are less sensitive to the section-to-section variations in counts and section thickness, factors that contribute to the inaccuracy of other stereological methods. In addition, volume reconstruction facilitates visualization and modeling of structures and analysis of three-dimensional relationships such as synaptic connectivity.

Integrating Candida albicans metabolism with biofilm heterogeneity by transcriptome mapping

NASA Astrophysics Data System (ADS)

Rajendran, Ranjith; May, Ali; Sherry, Leighann; Kean, Ryan; Williams, Craig; Jones, Brian L.; Burgess, Karl V.; Heringa, Jaap; Abeln, Sanne; Brandt, Bernd W.; Munro, Carol A.; Ramage, Gordon

2016-10-01

Candida albicans biofilm formation is an important virulence factor in the pathogenesis of disease, a characteristic which has been shown to be heterogeneous in clinical isolates. Using an unbiased computational approach we investigated the central metabolic pathways driving biofilm heterogeneity. Transcripts from high (HBF) and low (LBF) biofilm forming isolates were analysed by RNA sequencing, with 6312 genes identified to be expressed in these two phenotypes. With a dedicated computational approach we identified and validated a significantly differentially expressed subnetwork of genes associated with these biofilm phenotypes. Our analysis revealed amino acid metabolism, such as arginine, proline, aspartate and glutamate metabolism, were predominantly upregulated in the HBF phenotype. On the contrary, purine, starch and sucrose metabolism was generally upregulated in the LBF phenotype. The aspartate aminotransferase gene AAT1 was found to be a common member of these amino acid pathways and significantly upregulated in the HBF phenotype. Pharmacological inhibition of AAT1 enzyme activity significantly reduced biofilm formation in a dose-dependent manner. Collectively, these findings provide evidence that biofilm phenotype is associated with differential regulation of metabolic pathways. Understanding and targeting such pathways, such as amino acid metabolism, is potentially useful for developing diagnostics and new antifungals to treat biofilm-based infections.

Development of a High-Throughput Gene Expression Screen for Modulators of RAS-MAPK Signaling in a Mutant RAS Cellular Context.

PubMed

Severyn, Bryan; Nguyen, Thi; Altman, Michael D; Li, Lixia; Nagashima, Kumiko; Naumov, George N; Sathyanarayanan, Sriram; Cook, Erica; Morris, Erick; Ferrer, Marc; Arthur, Bill; Benita, Yair; Watters, Jim; Loboda, Andrey; Hermes, Jeff; Gilliland, D Gary; Cleary, Michelle A; Carroll, Pamela M; Strack, Peter; Tudor, Matt; Andersen, Jannik N

2016-10-01

The RAS-MAPK pathway controls many cellular programs, including cell proliferation, differentiation, and apoptosis. In colorectal cancers, recurrent mutations in this pathway often lead to increased cell signaling that may contribute to the development of neoplasms, thereby making this pathway attractive for therapeutic intervention. To this end, we developed a 26-member gene signature of RAS-MAPK pathway activity utilizing the Affymetrix QuantiGene Plex 2.0 reagent system and performed both primary and confirmatory gene expression-based high-throughput screens (GE-HTSs) using KRAS mutant colon cancer cells (SW837) and leveraging a highly annotated chemical library. The screen achieved a hit rate of 1.4% and was able to enrich for hit compounds that target RAS-MAPK pathway members such as MEK and EGFR. Sensitivity and selectivity performance measurements were 0.84 and 1.00, respectively, indicating high true-positive and true-negative rates. Active compounds from the primary screen were confirmed in a dose-response GE-HTS assay, a GE-HTS assay using 14 additional cancer cell lines, and an in vitro colony formation assay. Altogether, our data suggest that this GE-HTS assay will be useful for larger unbiased chemical screens to identify novel compounds and mechanisms that may modulate the RAS-MAPK pathway. © 2016 Society for Laboratory Automation and Screening.

Defining the human deubiquitinating enzyme interaction landscape.

PubMed

Sowa, Mathew E; Bennett, Eric J; Gygi, Steven P; Harper, J Wade

2009-07-23

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

Defining the Human Deubiquitinating Enzyme Interaction Landscape

PubMed Central

Sowa, Mathew E.; Bennett, Eric J.; Gygi, Steven P.; Harper, J. Wade

2009-01-01

Summary Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform, called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel non-reciprocal proteomic datasets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, sub-cellular localization and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway. PMID:19615732

Proteome and Secretome Analysis Reveals Differential Post-transcriptional Regulation of Toll-like Receptor Responses*

PubMed Central

Koppenol-Raab, Marijke; Sjoelund, Virginie; Manes, Nathan P.; Gottschalk, Rachel A.; Dutta, Bhaskar; Benet, Zachary L.; Fraser, Iain D. C.

2017-01-01

The innate immune system is the organism's first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level. PMID:28235783

ATG proteins: Are we always looking at autophagy?

PubMed

Mauthe, Mario; Reggiori, Fulvio

2016-12-01

Autophagy is an intracellular degradation pathway that is regulated by the autophagy-related (ATG) proteins. For a long time it has been thought that ATG proteins were exclusively required for autophagy, but recent experimental evidence has revealed that these proteins are part of other cellular pathways, individually or as a functional group. To estimate the extent of these so-called unconventional functions of the ATG proteins, we decided to perform an unbiased siRNA screen targeting the entire ATG proteome and used viral replication as the readout. Our results have uncovered that a surprisingly high number of ATG proteins (36%) have a positive or negative role in promoting virus replication outside their classical role in autophagy. With the increasing knowledge about ATG protein unconventional functions and our investigation results, the interpretations about the possible involvement of autophagy in cellular or organismal functions that solely rely on the depletion of a single ATG protein, should be considered cautiously.

A normal mode-based geometric simulation approach for exploring biologically relevant conformational transitions in proteins.

PubMed

Ahmed, Aqeel; Rippmann, Friedrich; Barnickel, Gerhard; Gohlke, Holger

2011-07-25

A three-step approach for multiscale modeling of protein conformational changes is presented that incorporates information about preferred directions of protein motions into a geometric simulation algorithm. The first two steps are based on a rigid cluster normal-mode analysis (RCNMA). Low-frequency normal modes are used in the third step (NMSim) to extend the recently introduced idea of constrained geometric simulations of diffusive motions in proteins by biasing backbone motions of the protein, whereas side-chain motions are biased toward favorable rotamer states. The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. When applied to a data set of proteins with experimentally observed conformational changes, conformational variabilities are reproduced very well for 4 out of 5 proteins that show domain motions, with correlation coefficients r > 0.70 and as high as r = 0.92 in the case of adenylate kinase. In 7 out of 8 cases, NMSim simulations starting from unbound structures are able to sample conformations that are similar (root-mean-square deviation = 1.0-3.1 Å) to ligand bound conformations. An NMSim generated pathway of conformational change of adenylate kinase correctly describes the sequence of domain closing. The NMSim approach is a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or as starting points for more sophisticated sampling techniques.

Grade of Membership Response Time Model for Detecting Guessing Behaviors

ERIC Educational Resources Information Center

Pokropek, Artur

2016-01-01

A response model that is able to detect guessing behaviors and produce unbiased estimates in low-stake conditions using timing information is proposed. The model is a special case of the grade of membership model in which responses are modeled as partial members of a class that is affected by motivation and a class that responds only according to…

Untargeted Metabolomics Reveals Predominant Alterations in Lipid Metabolism Following Light Exposure in Broccoli Sprouts

PubMed Central

Maldini, Mariateresa; Natella, Fausta; Baima, Simona; Morelli, Giorgio; Scaccini, Cristina; Langridge, James; Astarita, Giuseppe

2015-01-01

The consumption of vegetables belonging to the family Brassicaceae (e.g., broccoli and cauliflower) is linked to a reduced incidence of cancer and cardiovascular diseases. The molecular composition of such plants is strongly affected by growing conditions. Here we developed an unbiased metabolomics approach to investigate the effect of light and dark exposure on the metabolome of broccoli sprouts and we applied such an approach to provide a bird’s-eye view of the overall metabolic response after light exposure. Broccoli seeds were germinated and grown hydroponically for five days in total darkness or with a light/dark photoperiod (16 h light/8 h dark cycle). We used an ultra-performance liquid-chromatography system coupled to an ion-mobility, time-of-flight mass spectrometer to profile the large array of metabolites present in the sprouts. Differences at the metabolite level between groups were analyzed using multivariate statistical analyses, including principal component analysis and correlation analysis. Altered metabolites were identified by searching publicly available and in-house databases. Metabolite pathway analyses were used to support the identification of subtle but significant changes among groups of related metabolites that may have gone unnoticed with conventional approaches. Besides the chlorophyll pathway, light exposure activated the biosynthesis and metabolism of sterol lipids, prenol lipids, and polyunsaturated lipids, which are essential for the photosynthetic machinery. Our results also revealed that light exposure increased the levels of polyketides, including flavonoids, and oxylipins, which play essential roles in the plant’s developmental processes and defense mechanism against herbivores. This study highlights the significant contribution of light exposure to the ultimate metabolic phenotype, which might affect the cellular physiology and nutritional value of broccoli sprouts. Furthermore, this study highlights the potential of an unbiased omics approach for the comprehensive study of the metabolism. PMID:26084047

Midbrain dopamine neurons in Parkinson's disease exhibit a dysregulated miRNA and target-gene network.

PubMed

Briggs, Christine E; Wang, Yulei; Kong, Benjamin; Woo, Tsung-Ung W; Iyer, Lakshmanan K; Sonntag, Kai C

2015-08-27

The degeneration of substantia nigra (SN) dopamine (DA) neurons in sporadic Parkinson׳s disease (PD) is characterized by disturbed gene expression networks. Micro(mi)RNAs are post-transcriptional regulators of gene expression and we recently provided evidence that these molecules may play a functional role in the pathogenesis of PD. Here, we document a comprehensive analysis of miRNAs in SN DA neurons and PD, including sex differences. Our data show that miRNAs are dysregulated in disease-affected neurons and differentially expressed between male and female samples with a trend of more up-regulated miRNAs in males and more down-regulated miRNAs in females. Unbiased Ingenuity Pathway Analysis (IPA) revealed a network of miRNA/target-gene associations that is consistent with dysfunctional gene and signaling pathways in PD pathology. Our study provides evidence for a general association of miRNAs with the cellular function and identity of SN DA neurons, and with deregulated gene expression networks and signaling pathways related to PD pathogenesis that may be sex-specific. Copyright © 2015 Elsevier B.V. All rights reserved.

Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.

PubMed

Xie, Yanmei; Zhang, Biao

2017-04-20

Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and Nutrition Examination Survey (NHANES).

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials

PubMed Central

Diaz-Ordaz, Karla; Bartlett, Jonathan W

2016-01-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group. PMID:27177885

NullSeq: A Tool for Generating Random Coding Sequences with Desired Amino Acid and GC Contents.

PubMed

Liu, Sophia S; Hockenberry, Adam J; Lancichinetti, Andrea; Jewett, Michael C; Amaral, Luís A N

2016-11-01

The existence of over- and under-represented sequence motifs in genomes provides evidence of selective evolutionary pressures on biological mechanisms such as transcription, translation, ligand-substrate binding, and host immunity. In order to accurately identify motifs and other genome-scale patterns of interest, it is essential to be able to generate accurate null models that are appropriate for the sequences under study. While many tools have been developed to create random nucleotide sequences, protein coding sequences are subject to a unique set of constraints that complicates the process of generating appropriate null models. There are currently no tools available that allow users to create random coding sequences with specified amino acid composition and GC content for the purpose of hypothesis testing. Using the principle of maximum entropy, we developed a method that generates unbiased random sequences with pre-specified amino acid and GC content, which we have developed into a python package. Our method is the simplest way to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. Furthermore, this approach can easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes as well as more effective engineering of biological systems.

Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.

PubMed

Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W

2017-06-01

Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.

Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease.

PubMed

Alkallas, Rached; Fish, Lisa; Goodarzi, Hani; Najafabadi, Hamed S

2017-10-13

The abundance of mRNA is mainly determined by the rates of RNA transcription and decay. Here, we present a method for unbiased estimation of differential mRNA decay rate from RNA-sequencing data by modeling the kinetics of mRNA metabolism. We show that in all primary human tissues tested, and particularly in the central nervous system, many pathways are regulated at the mRNA stability level. We present a parsimonious regulatory model consisting of two RNA-binding proteins and four microRNAs that modulate the mRNA stability landscape of the brain, which suggests a new link between RBFOX proteins and Alzheimer's disease. We show that downregulation of RBFOX1 leads to destabilization of mRNAs encoding for synaptic transmission proteins, which may contribute to the loss of synaptic function in Alzheimer's disease. RBFOX1 downregulation is more likely to occur in older and female individuals, consistent with the association of Alzheimer's disease with age and gender."mRNA abundance is determined by the rates of transcription and decay. Here, the authors propose a method for estimating the rate of differential mRNA decay from RNA-seq data and model mRNA stability in the brain, suggesting a link between mRNA stability and Alzheimer's disease."

Molecular Dynamics Simulations of the Human Glucose Transporter GLUT1

PubMed Central

Park, Min-Sun

2015-01-01

Glucose transporters (GLUTs) provide a pathway for glucose transport across membranes. Human GLUTs are implicated in devastating diseases such as heart disease, hyper- and hypo-glycemia, type 2 diabetes and caner. The human GLUT1 has been recently crystalized in the inward-facing open conformation. However, there is no other structural information for other conformations. The X-ray structures of E. coli Xylose permease (XylE), a glucose transporter homolog, are available in multiple conformations with and without the substrates D-xylose and D-glucose. XylE has high sequence homology to human GLUT1 and key residues in the sugar-binding pocket are conserved. Here we construct a homology model for human GLUT1 based on the available XylE crystal structure in the partially occluded outward-facing conformation. A long unbiased all atom molecular dynamics simulation starting from the model can capture a new fully opened outward-facing conformation. Our investigation of molecular interactions at the interface between the transmembrane (TM) domains and the intracellular helices (ICH) domain in the outward- and inward-facing conformation supports that the ICH domain likely stabilizes the outward-facing conformation in GLUT1. Furthermore, inducing a conformational transition, our simulations manifest a global asymmetric rocker switch motion and detailed molecular interactions between the substrate and residues through the water-filled selective pore along a pathway from the extracellular to the intracellular side. The results presented here are consistent with previously published biochemical, mutagenesis and functional studies. Together, this study shed light on the structure and functional relationships of GLUT1 in multiple conformational states. PMID:25919356

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

An Integrated Proteomics and Bioinformatics Approach Reveals the Anti-inflammatory Mechanism of Carnosic Acid

PubMed Central

Wang, Li-Chao; Wei, Wen-Hui; Zhang, Xiao-Wen; Liu, Dan; Zeng, Ke-Wu; Tu, Peng-Fei

2018-01-01

Drastic macrophages activation triggered by exogenous infection or endogenous stresses is thought to be implicated in the pathogenesis of various inflammatory diseases. Carnosic acid (CA), a natural phenolic diterpene extracted from Salvia officinalis plant, has been reported to possess anti-inflammatory activity. However, its role in macrophages activation as well as potential molecular mechanism is largely unexplored. In the current study, we sought to elucidate the anti-inflammatory property of CA using an integrated approach based on unbiased proteomics and bioinformatics analysis. CA significantly inhibited the robust increase of nitric oxide and TNF-α, downregulated COX2 protein expression, and lowered the transcriptional level of inflammatory genes including Nos2, Tnfα, Cox2, and Mcp1 in LPS-stimulated RAW264.7 cells, a murine model of peritoneal macrophage cell line. The LC-MS/MS-based shotgun proteomics analysis showed CA negatively regulated 217 LPS-elicited proteins which were involved in multiple inflammatory processes including MAPK, nuclear factor (NF)-κB, and FoxO signaling pathways. A further molecular biology analysis revealed that CA effectually inactivated IKKβ/IκB-α/NF-κB, ERK/JNK/p38 MAPKs, and FoxO1/3 signaling pathways. Collectively, our findings demonstrated the role of CA in regulating inflammation response and provide some insights into the proteomics-guided pharmacological mechanism study of natural products. PMID:29713284

Gang membership and substance use: guilt as a gendered causal pathway

PubMed Central

Coffman, Donna L.; Melde, Chris; Esbensen, Finn-Aage

2014-01-01

Objectives We examine whether anticipated guilt for substance use is a gendered mechanism underlying the noted enhancement effect of gang membership on illegal drug use. We also demonstrate a method for making stronger causal inferences when assessing mediation in the presence of moderation and time-varying confounding. Methods We estimate a series of inverse propensity weighted models to obtain unbiased estimates of mediation in the presence of confounding of the exposure (i.e., gang membership) and mediator (i.e., anticipated guilt) using three waves of data from a multi-site panel study of a law-related education program for youth (N=1,113). Results The onset of gang membership significantly decreased anticipated substance use guilt among both male and female respondents. This reduction was significantly associated with increased frequency of substance use only for female respondents, however, suggesting that gender moderates the mechanism through which gang membership influences substance use. Conclusions Criminologists are often concerned with identifying causal pathways for antisocial and/or delinquent behavior, but confounders of the exposure, mediator, and outcome often interfere with efforts to assess mediation. Many new approaches have been proposed for strengthening causal inference for mediation effects. After controlling for confounding using inverse propensity weighting, our results suggest that interventions aimed at reducing substance use by current and former female gang members should focus on the normative aspects of these behaviors. PMID:26190954

Adenine alleviates iron overload by cAMP/PKA mediated hepatic hepcidin in mice.

PubMed

Zhang, Yingqi; Wang, Xudong; Wu, Qian; Wang, Hao; Zhao, Lu; Wang, Xinhui; Mu, Mingdao; Xie, Enjun; He, Xuyan; Shao, Dandan; Shang, Yanna; Lai, Yongrong; Ginzburg, Yelena; Min, Junxia; Wang, Fudi

2018-03-30

Hemochromatosis is prevalent and often associated with high rates of morbidity and mortality worldwide. The safe alternative iron-reducing approaches are urgently needed in order to better control iron overload. Our unbiased vitamin screen for modulators of hepcidin, a master iron regulatory hormone, identifies adenine (vitamin B4) as a potent hepcidin agonist. Adenine significantly induced hepcidin mRNA level and promoter activity activation in human cell lines, possibly through BMP/SMAD pathway. Further studies in mice validated the effect of adenine on hepcidin upregulation. Consistently, adenine dietary supplement in mice led to an increase of hepatic hepcidin expression compared with normal diet-fed mice via BMP/SMAD pathway. Notably, adenine-rich diet significantly ameliorated iron overload accompanied by the enhanced hepcidin expression in both high iron-fed mice and in Hfe -/- mice, a murine model of hereditary hemochromatosis. To further validate this finding, we selected pharmacological inhibitors against BMP (LDN193189). We found LDN193189 strongly blocked the hepcidin induction by adenine. Moreover, we uncovered an essential role of cAMP/PKA-dependent axis in triggering adenine-induced hepcidin expression in primary hepatocytes by using 8 br cAMP, a cAMP analog, and H89, a potent inhibitor for PKA signaling. These findings suggest a potential therapeutic role of adenine for hereditary hemochromatosis. © 2018 Wiley Periodicals, Inc.

Gang membership and substance use: guilt as a gendered causal pathway.

PubMed

Coffman, Donna L; Melde, Chris; Esbensen, Finn-Aage

2015-03-01

We examine whether anticipated guilt for substance use is a gendered mechanism underlying the noted enhancement effect of gang membership on illegal drug use. We also demonstrate a method for making stronger causal inferences when assessing mediation in the presence of moderation and time-varying confounding. We estimate a series of inverse propensity weighted models to obtain unbiased estimates of mediation in the presence of confounding of the exposure (i.e., gang membership) and mediator (i.e., anticipated guilt) using three waves of data from a multi-site panel study of a law-related education program for youth ( N =1,113). The onset of gang membership significantly decreased anticipated substance use guilt among both male and female respondents. This reduction was significantly associated with increased frequency of substance use only for female respondents, however, suggesting that gender moderates the mechanism through which gang membership influences substance use. Criminologists are often concerned with identifying causal pathways for antisocial and/or delinquent behavior, but confounders of the exposure, mediator, and outcome often interfere with efforts to assess mediation. Many new approaches have been proposed for strengthening causal inference for mediation effects. After controlling for confounding using inverse propensity weighting, our results suggest that interventions aimed at reducing substance use by current and former female gang members should focus on the normative aspects of these behaviors.

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Ligand-directed profiling of organelles with internalizing phage libraries

PubMed Central

Dobroff, Andrey S.; Rangel, Roberto; Guzman-Roja, Liliana; Salmeron, Carolina C.; Gelovani, Juri G.; Sidman, Richard L.; Bologa, Cristian G.; Oprea, Tudor I.; Brinker, C. Jeffrey; Pasqualini, Renata; Arap, Wadih

2015-01-01

Phage display is a resourceful tool to, in an unbiased manner, discover and characterize functional protein-protein interactions, to create vaccines, and to engineer peptides, antibodies, and other proteins as targeted diagnostic and/or therapeutic agents. Recently, our group has developed a new class of internalizing phage (iPhage) for ligand-directed targeting of organelles and/or to identify molecular pathways within live cells. This unique technology is suitable for applications ranging from fundamental cell biology to drug development. Here we describe the method for generating and screening the iPhage display system, and explain how to select and validate candidate internalizing homing peptide. PMID:25640897

Unbiased mean direction of paleomagnetic data and better estimate of paleolatitude

NASA Astrophysics Data System (ADS)

Hatakeyama, T.; Shibuya, H.

2010-12-01

In paleomagnetism, when we obtain only paleodirection data without paleointensities we calculate Fisher-mean directions (I, D) and Fisher-mean VGP positions as the description of the mean field. However, Kono (1997) and Hatakeyama and Kono (2001) indicated that these averaged directions does not show the unbiased estimated mean directions derived from the time-averaged field (TAF). Hatakeyama and Kono (2002) calculated the TAF and paleosecular variation (PSV) models for the past 5My with considering the biases due to the averaging of the nonlinear functions such as the summation of the unit vectors in the Fisher statistics process. Here we will show a zonal TAF model based on the Hatakeyama and Kono TAF model. Moreover, we will introduce the biased angles due to the PSV in the mean direction and a method for determining true paleolatitudes, which represents the TAF, from paleodirections. This method will helps tectonics studies, especially in the estimation of the accurate paleolatitude in the middle latitude regions.

Unbiased Sampling of Globular Lattice Proteins in Three Dimensions

NASA Astrophysics Data System (ADS)

Jacobsen, Jesper Lykke

2008-03-01

We present a Monte Carlo method that allows efficient and unbiased sampling of Hamiltonian walks on a cubic lattice. Such walks are self-avoiding and visit each lattice site exactly once. They are often used as simple models of globular proteins, upon adding suitable local interactions. Our algorithm can easily be equipped with such interactions, but we study here mainly the flexible homopolymer case where each conformation is generated with uniform probability. We argue that the algorithm is ergodic and has dynamical exponent z=0. We then use it to study polymers of size up to 643=262144 monomers. Results are presented for the effective interaction between end points, and the interaction with the boundaries of the system.

Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

PubMed

Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

2011-10-04

Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

Pathway Distiller - multisource biological pathway consolidation

PubMed Central

2012-01-01

Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636

Pathway Distiller - multisource biological pathway consolidation.

PubMed

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

Treatment effects model for assessing disease management: measuring outcomes and strengthening program management.

PubMed

Wendel, Jeanne; Dumitras, Diana

2005-06-01

This paper describes an analytical methodology for obtaining statistically unbiased outcomes estimates for programs in which participation decisions may be correlated with variables that impact outcomes. This methodology is particularly useful for intraorganizational program evaluations conducted for business purposes. In this situation, data is likely to be available for a population of managed care members who are eligible to participate in a disease management (DM) program, with some electing to participate while others eschew the opportunity. The most pragmatic analytical strategy for in-house evaluation of such programs is likely to be the pre-intervention/post-intervention design in which the control group consists of people who were invited to participate in the DM program, but declined the invitation. Regression estimates of program impacts may be statistically biased if factors that impact participation decisions are correlated with outcomes measures. This paper describes an econometric procedure, the Treatment Effects model, developed to produce statistically unbiased estimates of program impacts in this type of situation. Two equations are estimated to (a) estimate the impacts of patient characteristics on decisions to participate in the program, and then (b) use this information to produce a statistically unbiased estimate of the impact of program participation on outcomes. This methodology is well-established in economics and econometrics, but has not been widely applied in the DM outcomes measurement literature; hence, this paper focuses on one illustrative application.

GTARG - The TOPEX/Poseidon ground track maintenance maneuver targeting program

NASA Technical Reports Server (NTRS)

Shapiro, Bruce E.; Bhat, Ramachandra S.

1993-01-01

GTARG is a computer program used to design orbit maintenance maneuvers for the TOPEX/Poseidon satellite. These maneuvers ensure that the ground track is kept within +/-1 km with of an = 9.9 day exact repeat pattern. Maneuver parameters are determined using either of two targeting strategies: longitude targeting, which maximizes the time between maneuvers, and time targeting, in which maneuvers are targeted to occur at specific intervals. The GTARG algorithm propagates nonsingular mean elements, taking into account anticipated error sigma's in orbit determination, Delta v execution, drag prediction and Delta v quantization. A satellite unique drag model is used which incorporates an approximate mean orbital Jacchia-Roberts atmosphere and a variable mean area model. Maneuver Delta v magnitudes are targeted to precisely maintain either the unbiased ground track itself, or a comfortable (3 sigma) error envelope about the unbiased ground track.

Microarray RNA expression analysis of cerebral white matter lesions reveals changes in multiple functional pathways.

PubMed

Simpson, Julie E; Hosny, Ola; Wharton, Stephen B; Heath, Paul R; Holden, Hazel; Fernando, Malee S; Matthews, Fiona; Forster, Gill; O'Brien, John T; Barber, Robert; Kalaria, Raj N; Brayne, Carol; Shaw, Pamela J; Lewis, Claire E; Ince, Paul G

2009-02-01

White matter lesions (WML) in brain aging are linked to dementia and depression. Ischemia contributes to their pathogenesis but other mechanisms may contribute. We used RNA microarray analysis with functional pathway grouping as an unbiased approach to investigate evidence for additional pathogenetic mechanisms. WML were identified by MRI and pathology in brains donated to the Medical Research Council Cognitive Function and Ageing Study Cognitive Function and Aging Study. RNA was extracted to compare WML with nonlesional white matter samples from cases with lesions (WM[L]), and from cases with no lesions (WM[C]) using RNA microarray and pathway analysis. Functional pathways were validated for selected genes by quantitative real-time polymerase chain reaction and immunocytochemistry. We identified 8 major pathways in which multiple genes showed altered RNA transcription (immune regulation, cell cycle, apoptosis, proteolysis, ion transport, cell structure, electron transport, metabolism) among 502 genes that were differentially expressed in WML compared to WM[C]. In WM[L], 409 genes were altered involving the same pathways. Genes selected to validate this microarray data all showed the expected changes in RNA levels and immunohistochemical expression of protein. WML represent areas with a complex molecular phenotype. From this and previous evidence, WML may arise through tissue ischemia but may also reflect the contribution of additional factors like blood-brain barrier dysfunction. Differential expression of genes in WM[L] compared to WM[C] indicate a "field effect" in the seemingly normal surrounding white matter.

Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias

NASA Astrophysics Data System (ADS)

Nüske, Feliks; Wu, Hao; Prinz, Jan-Hendrik; Wehmeyer, Christoph; Clementi, Cecilia; Noé, Frank

2017-03-01

Many state-of-the-art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of relatively short trajectories are integrated. In this context, Markov state models (MSMs) are extremely popular because they can be used to compute stationary quantities and long-time kinetics from ensembles of short simulations, provided that these short simulations are in "local equilibrium" within the MSM states. However, over the last 15 years since the inception of MSMs, it has been controversially discussed and not yet been answered how deviations from local equilibrium can be detected, whether these deviations induce a practical bias in MSM estimation, and how to correct for them. In this paper, we address these issues: We systematically analyze the estimation of MSMs from short non-equilibrium simulations, and we provide an expression for the error between unbiased transition probabilities and the expected estimate from many short simulations. We show that the unbiased MSM estimate can be obtained even from relatively short non-equilibrium simulations in the limit of long lag times and good discretization. Further, we exploit observable operator model (OOM) theory to derive an unbiased estimator for the MSM transition matrix that corrects for the effect of starting out of equilibrium, even when short lag times are used. Finally, we show how the OOM framework can be used to estimate the exact eigenvalues or relaxation time scales of the system without estimating an MSM transition matrix, which allows us to practically assess the discretization quality of the MSM. Applications to model systems and molecular dynamics simulation data of alanine dipeptide are included for illustration. The improved MSM estimator is implemented in PyEMMA of version 2.3.

Estimation and application of a growth and yield model for uneven-aged mixed conifer stands in California.

Treesearch

Jingjing Liang; J. Buongiorno; R.A. Monserud

2005-01-01

A growth model for uneven-aged mixed-conifer stands in California was developed with data from 205 permanent plots. The model predicts the number of softwood and hardwood trees in nineteen diameter classes, based on equations for diameter growth rates, mortality arid recruitment. The model gave unbiased predictions of the expected number of trees by diameter class and...

High resolution Chromatin Immunoprecipitation (ChIP) sequencing reveals novel bindings targets and prognostic role for SOX11 in Mantle cell lymphoma

PubMed Central

Kuo, Pei-Yu; Leshchenko, Violetta V.; Fazzari, Melissa J.; Perumal, Deepak; Gellen, Tobias; He, Tianfang; Iqbal, Javeed; Baumgartner-Wennerholm, Stefanie; Nygren, Lina; Zhang, Fan; Zhang, Weijia; Suh, K. Stephen; Goy, Andre; Yang, David T.; Chan, Wing-Chung; Kahl, Brad S.; Verma, Amit K.; Gascoyne, Randy D.; Kimby, Eva; Sander, Birgitta; Ye, B. Hilda; Melnick, Ari M.; Parekh, Samir

2015-01-01

SOX11 (Sex determining region Y-box 11) expression is specific for MCL as compared to other Non-Hodgkin's lymphomas. However, the function and direct binding targets of SOX11 in MCL are largely unknown. We used high-resolution ChIP-Seq to identify the direct target genes of SOX11 in a genome-wide, unbiased manner and elucidate its functional significance. Pathway analysis identified WNT, PKA and TGF-beta signaling pathways as significantly enriched by SOX11 target genes. qCHIP and promoter reporter assays confirmed that SOX11 directly binds to individual genes and modulates their transcription activities in these pathways in MCL. Functional studies using RNA interference demonstrate that SOX11 directly regulates WNT in MCL. We analyzed SOX11 expression in three independent well-annotated tissue microarrays from the University of Wisconsin (UW), Karolinska Institute and British Columbia Cancer Agency (BCCA). Our findings suggest that high SOX11 expression is associated with improved survival in a subset of MCL patients, particularly those treated with intensive chemotherapy. Transcriptional regulation of WNT and other biological pathways affected by SOX11 target genes may help explain the impact of SOX11 expression on patient outcomes. PMID:24681958

Mutually unbiased bases and semi-definite programming

NASA Astrophysics Data System (ADS)

Brierley, Stephen; Weigert, Stefan

2010-11-01

A complex Hilbert space of dimension six supports at least three but not more than seven mutually unbiased bases. Two computer-aided analytical methods to tighten these bounds are reviewed, based on a discretization of parameter space and on Gröbner bases. A third algorithmic approach is presented: the non-existence of more than three mutually unbiased bases in composite dimensions can be decided by a global optimization method known as semidefinite programming. The method is used to confirm that the spectral matrix cannot be part of a complete set of seven mutually unbiased bases in dimension six.

A Comparison of Latent Growth Models for Constructs Measured by Multiple Items

ERIC Educational Resources Information Center

Leite, Walter L.

2007-01-01

Univariate latent growth modeling (LGM) of composites of multiple items (e.g., item means or sums) has been frequently used to analyze the growth of latent constructs. This study evaluated whether LGM of composites yields unbiased parameter estimates, standard errors, chi-square statistics, and adequate fit indexes. Furthermore, LGM was compared…

Social Cognitive Predictors of College Students' Academic Performance and Persistence: A Meta-Analytic Path Analysis

ERIC Educational Resources Information Center

Brown, Steven D.; Tramayne, Selena; Hoxha, Denada; Telander, Kyle; Fan, Xiaoyan; Lent, Robert W.

2008-01-01

This study tested Social Cognitive Career Theory's (SCCT) academic performance model using a two-stage approach that combined meta-analytic and structural equation modeling methodologies. Unbiased correlations obtained from a previously published meta-analysis [Robbins, S. B., Lauver, K., Le, H., Davis, D., & Langley, R. (2004). Do psychosocial…

Bias and Efficiency in Structural Equation Modeling: Maximum Likelihood versus Robust Methods

ERIC Educational Resources Information Center

Zhong, Xiaoling; Yuan, Ke-Hai

2011-01-01

In the structural equation modeling literature, the normal-distribution-based maximum likelihood (ML) method is most widely used, partly because the resulting estimator is claimed to be asymptotically unbiased and most efficient. However, this may not hold when data deviate from normal distribution. Outlying cases or nonnormally distributed data,…

The influence of SO4 and NO3 to the acidity (pH) of rainwater using minimum variance quadratic unbiased estimation (MIVQUE) and maximum likelihood methods

NASA Astrophysics Data System (ADS)

Dilla, Shintia Ulfa; Andriyana, Yudhie; Sudartianto

2017-03-01

Acid rain causes many bad effects in life. It is formed by two strong acids, sulfuric acid (H2SO4) and nitric acid (HNO3), where sulfuric acid is derived from SO2 and nitric acid from NOx {x=1,2}. The purpose of the research is to find out the influence of So4 and NO3 levels contained in the rain to the acidity (pH) of rainwater. The data are incomplete panel data with two-way error component model. The panel data is a collection of some of the observations that observed from time to time. It is said incomplete if each individual has a different amount of observation. The model used in this research is in the form of random effects model (REM). Minimum variance quadratic unbiased estimation (MIVQUE) is used to estimate the variance error components, while maximum likelihood estimation is used to estimate the parameters. As a result, we obtain the following model: Ŷ* = 0.41276446 - 0.00107302X1 + 0.00215470X2.

Response: Reading between the lines of cancer screening trials: using modeling to understand the evidence.

PubMed

Etzioni, Ruth; Gulati, Roman

2013-04-01

In our article about limitations of basing screening policy on screening trials, we offered several examples of ways in which modeling, using data from large screening trials and population trends, provided insights that differed somewhat from those based only on empirical trial results. In this editorial, we take a step back and consider the general question of whether randomized screening trials provide the strongest evidence for clinical guidelines concerning population screening programs. We argue that randomized trials provide a process that is designed to protect against certain biases but that this process does not guarantee that inferences based on empirical results from screening trials will be unbiased. Appropriate quantitative methods are key to obtaining unbiased inferences from screening trials. We highlight several studies in the statistical literature demonstrating that conventional survival analyses of screening trials can be misleading and list a number of key questions concerning screening harms and benefits that cannot be answered without modeling. Although we acknowledge the centrality of screening trials in the policy process, we maintain that modeling constitutes a powerful tool for screening trial interpretation and screening policy development.

The Misspecification of the Covariance Structures in Multilevel Models for Single-Case Data: A Monte Carlo Simulation Study

ERIC Educational Resources Information Center

Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim

2016-01-01

The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…

Genome-wide chemical mutagenesis screens allow unbiased saturation of the cancer genome and identification of drug resistance mutations.

PubMed

Brammeld, Jonathan S; Petljak, Mia; Martincorena, Inigo; Williams, Steven P; Alonso, Luz Garcia; Dalmases, Alba; Bellosillo, Beatriz; Robles-Espinoza, Carla Daniela; Price, Stacey; Barthorpe, Syd; Tarpey, Patrick; Alifrangis, Constantine; Bignell, Graham; Vidal, Joana; Young, Jamie; Stebbings, Lucy; Beal, Kathryn; Stratton, Michael R; Saez-Rodriguez, Julio; Garnett, Mathew; Montagut, Clara; Iorio, Francesco; McDermott, Ultan

2017-04-01

Drug resistance is an almost inevitable consequence of cancer therapy and ultimately proves fatal for the majority of patients. In many cases, this is the consequence of specific gene mutations that have the potential to be targeted to resensitize the tumor. The ability to uniformly saturate the genome with point mutations without chromosome or nucleotide sequence context bias would open the door to identify all putative drug resistance mutations in cancer models. Here, we describe such a method for elucidating drug resistance mechanisms using genome-wide chemical mutagenesis allied to next-generation sequencing. We show that chemically mutagenizing the genome of cancer cells dramatically increases the number of drug-resistant clones and allows the detection of both known and novel drug resistance mutations. We used an efficient computational process that allows for the rapid identification of involved pathways and druggable targets. Such a priori knowledge would greatly empower serial monitoring strategies for drug resistance in the clinic as well as the development of trials for drug-resistant patients. © 2017 Brammeld et al.; Published by Cold Spring Harbor Laboratory Press.

The kinase DYRK1A reciprocally regulates the differentiation of Th17 and regulatory T cells

PubMed Central

Khor, Bernard; Gagnon, John D; Goel, Gautam; Roche, Marly I; Conway, Kara L; Tran, Khoa; Aldrich, Leslie N; Sundberg, Thomas B; Paterson, Alison M; Mordecai, Scott; Dombkowski, David; Schirmer, Melanie; Tan, Pauline H; Bhan, Atul K; Roychoudhuri, Rahul; Restifo, Nicholas P; O'Shea, John J; Medoff, Benjamin D; Shamji, Alykhan F; Schreiber, Stuart L; Sharpe, Arlene H; Shaw, Stanley Y; Xavier, Ramnik J

2015-01-01

The balance between Th17 and T regulatory (Treg) cells critically modulates immune homeostasis, with an inadequate Treg response contributing to inflammatory disease. Using an unbiased chemical biology approach, we identified a novel role for the dual specificity tyrosine-phosphorylation-regulated kinase DYRK1A in regulating this balance. Inhibition of DYRK1A enhances Treg differentiation and impairs Th17 differentiation without affecting known pathways of Treg/Th17 differentiation. Thus, DYRK1A represents a novel mechanistic node at the branch point between commitment to either Treg or Th17 lineages. Importantly, both Treg cells generated using the DYRK1A inhibitor harmine and direct administration of harmine itself potently attenuate inflammation in multiple experimental models of systemic autoimmunity and mucosal inflammation. Our results identify DYRK1A as a physiologically relevant regulator of Treg cell differentiation and suggest a broader role for other DYRK family members in immune homeostasis. These results are discussed in the context of human diseases associated with dysregulated DYRK activity. DOI: http://dx.doi.org/10.7554/eLife.05920.001 PMID:25998054

Equilibrium thermodynamics and folding kinetics of a short, fast-folding, beta-hairpin.

PubMed

Jimenez-Cruz, Camilo A; Garcia, Angel E

2014-04-14

Equilibrium thermodynamics of a short beta-hairpin are studied using unbiased all-atom replica exchange molecular dynamics simulations in explicit solvent. An exploratory analysis of the free energy landscape of the system is provided in terms of various structural characteristics, for both the folded and unfolded ensembles. We find that the favorable interactions between the ends introduced by the tryptophan cap, along with the flexibility of the turn region, explain the remarkable stability of the folded state. Charging of the N termini results in effective roughening of the free energy landscape and stabilization of non-native contacts. Folding-unfolding dynamics are further discussed using a set of 2413 independent molecular dynamics simulations, 2 ns to 20 ns long, at the melting temperature of the beta-hairpin. A novel method for the construction of Markov models consisting of an iterative refinement of the discretization in reduced dimensionality is presented and used to generate a detailed kinetic network of the system. The hairpin is found to fold heterogeneously on sub-microsecond timescales, with the relative position of the tryptophan side chains driving the selection of the specific pathway.

Unbiasedness

USGS Publications Warehouse

Link, W.A.; Armitage, Peter; Colton, Theodore

1998-01-01

Unbiasedness is probably the best known criterion for evaluating the performance of estimators. This note describes unbiasedness, demonstrating various failings of the criterion. It is shown that unbiased estimators might not exist, or might not be unique; an example of a unique but clearly unacceptable unbiased estimator is given. It is shown that unbiased estimators are not translation invariant. Various alternative criteria are described, and are illustrated through examples.

FAST TRACK COMMUNICATION: Affine constellations without mutually unbiased counterparts

NASA Astrophysics Data System (ADS)

Weigert, Stefan; Durt, Thomas

2010-10-01

It has been conjectured that a complete set of mutually unbiased bases in a space of dimension d exists if and only if there is an affine plane of order d. We introduce affine constellations and compare their existence properties with those of mutually unbiased constellations. The observed discrepancies make a deeper relation between the two existence problems unlikely.

Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism.

PubMed

Gevi, Federica; Zolla, Lello; Gabriele, Stefano; Persico, Antonio M

2016-01-01

Autism spectrum disorder (ASD) is still diagnosed through behavioral observation, due to a lack of laboratory biomarkers, which could greatly aid clinicians in providing earlier and more reliable diagnoses. Metabolomics on human biofluids provides a sensitive tool to identify metabolite profiles potentially usable as biomarkers for ASD. Initial metabolomic studies, analyzing urines and plasma of ASD and control individuals, suggested that autistic patients may share some metabolic abnormalities, despite several inconsistencies stemming from differences in technology, ethnicity, age range, and definition of "control" status. ASD-specific urinary metabolomic patterns were explored at an early age in 30 ASD children and 30 matched controls (age range 2-7, M:F = 22:8) using hydrophilic interaction chromatography (HILIC)-UHPLC and mass spectrometry, a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway. Urinary metabolites displaying the largest differences between young ASD and control children belonged to the tryptophan and purine metabolic pathways. Also, vitamin B 6 , riboflavin, phenylalanine-tyrosine-tryptophan biosynthesis, pantothenate and CoA, and pyrimidine metabolism differed significantly. ASD children preferentially transform tryptophan into xanthurenic acid and quinolinic acid (two catabolites of the kynurenine pathway), at the expense of kynurenic acid and especially of melatonin. Also, the gut microbiome contributes to altered tryptophan metabolism, yielding increased levels of indolyl 3-acetic acid and indolyl lactate. The metabolic pathways most distinctive of young Italian autistic children largely overlap with those found in rodent models of ASD following maternal immune activation or genetic manipulations. These results are consistent with the proposal of a purine-driven cell danger response, accompanied by overproduction of epileptogenic and excitotoxic quinolinic acid, large reductions in melatonin synthesis, and gut dysbiosis. These metabolic abnormalities could underlie several comorbidities frequently associated to ASD, such as seizures, sleep disorders, and gastrointestinal symptoms, and could contribute to autism severity. Their diagnostic sensitivity, disease-specificity, and interethnic variability will merit further investigation.

Prediction and measurement results of radiation damage to CMOS devices on board spacecraft

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.; Danchenko, V.; Cliff, R. A.; Sing, M.; Brucker, G. J.; Ohanian, R. S.

1977-01-01

Final results from the CMOS Radiation Effects Measurement (CREM) experiment flown on Explorer 55 are presented and discussed, based on about 15 months of observations and measurements. Conclusions are given relating to long-range annealing, effects of operating temperature on semiconductor performance in space, biased and unbiased P-MOS device degradation, unbiased n-channel device performance, changes in device transconductance, and the difference in ionization efficiency between Co-60 gamma rays and 1-Mev Van de Graaff electrons. The performance of devices in a heavily shielded electronic subsystem box within the spacecraft is evaluated and compared. Environment models and computational methods and their impact on device-degradation estimates are being reviewed to determine whether they permit cost-effective design of spacecraft.

Evidence for SH2 Domain-Containing 5′-Inositol Phosphatase-2 (SHIP2) Contributing to a Lymphatic Dysfunction

PubMed Central

Agollah, Germaine D.; Gonzalez-Garay, Manuel L.; Rasmussen, John C.; Tan, I-Chih; Aldrich, Melissa B.; Darne, Chinmay; Fife, Caroline E.; Guilliod, Renie; Maus, Erik A.; King, Philip D.; Sevick-Muraca, Eva M.

2014-01-01

The lymphatic vasculature plays a critical role in a number of disease conditions of increasing prevalence, such as autoimmune disorders, obesity, blood vascular diseases, and cancer metastases. Yet, unlike the blood vasculature, the tools available to interrogate the molecular basis of lymphatic dysfunction/disease have been lacking. More recently, investigators have reported that dysregulation of the PI3K pathway is involved in syndromic human diseases that involve abnormal lymphatic vasculatures, but there have been few compelling results that show the direct association of this molecular pathway with lymphatic dysfunction in humans. Using near-infrared fluorescence lymphatic imaging (NIRFLI) to phenotype and next generation sequencing (NGS) for unbiased genetic discovery in a family with non-syndromic lymphatic disease, we discovered a rare, novel mutation in INPPL1 that encodes the protein SHIP2, which is a negative regulator of the PI3K pathway, to be associated with lymphatic dysfunction in the family. In vitro interrogation shows that SHIP2 is directly associated with impairment of normal lymphatic endothelial cell (LEC) behavior and that SHIP2 associates with receptors that are associated in lymphedema, implicating its direct involvement in the lymphatic vasculature. PMID:25383712

NF-κB deregulation in splenic marginal zone lymphoma.

PubMed

Spina, Valeria; Rossi, Davide

2016-08-01

Splenic marginal zone lymphoma is a rare mature B-cell malignancy involving the spleen, bone marrow and blood. Over the past years, the rapid expansion of sequencing technologies allowing the genome-wide assessment of genomic, epigenetic and transcriptional changes has revolutionized our understanding of the biological basis of splenic marginal zone lymphoma by providing a comprehensive and unbiased view of the genes/pathways that are deregulated in this disease. NF-κB is a family of transcription factors that plays critical roles in development, survival, and activation of B lymphocytes. Consistent with the physiological involvement of NF-κB signalling in proliferation and commitment of mature B-cells to the marginal zone of the spleen, many oncogenic mutations involved in constitutive activation of the NF-κB pathway were recently identified in splenic marginal zone lymphoma. This review describes the progress in understanding the mechanism of NF-κB activation in splenic marginal zone lymphoma, including molecular, epigenetic and post-transcriptional modifications of NF-κB genes and of upstream pathways, and discusses how information gained from these efforts has provided new insights on potential targets of diagnostic, prognostic and therapeutic relevance for splenic marginal zone lymphoma. Copyright © 2016. Published by Elsevier Ltd.

Creating a RAW264.7 CRISPR-Cas9 Genome Wide Library

PubMed Central

Napier, Brooke A; Monack, Denise M

2017-01-01

The bacterial clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 genome editing tools are used in mammalian cells to knock-out specific genes of interest to elucidate gene function. The CRISPR-Cas9 system requires that the mammalian cell expresses Cas9 endonuclease, guide RNA (gRNA) to lead the endonuclease to the gene of interest, and the PAM sequence that links the Cas9 to the gRNA. CRISPR-Cas9 genome wide libraries are used to screen the effect of each gene in the genome on the cellular phenotype of interest, in an unbiased high-throughput manner. In this protocol, we describe our method of creating a CRISPR-Cas9 genome wide library in a transformed murine macrophage cell-line (RAW264.7). We have employed this library to identify novel mediators in the caspase-11 cell death pathway (Napier et al., 2016); however, this library can then be used to screen the importance of specific genes in multiple murine macrophage cellular pathways. PMID:28868328

Investigation on biochemical compositional changes during the microbial fermentation process of Fu brick tea by LC-MS based metabolomics.

PubMed

Xu, Jie; Hu, Feng-Lin; Wang, Wei; Wan, Xiao-Chun; Bao, Guan-Hu

2015-11-01

Fu brick tea (FBT) is a unique post-fermented tea product which is fermented with fungi during the manufacturing process. In this study, we investigated the biochemical compositional changes occurring during the microbial fermentation process (MFP) of FBT based on non-targeted LC-MS, which was a comprehensive and unbiased methodology. Our data analysis took a two-phase approach: (1) comparison of FBT with other tea products using PCA analysis to exhibit the characteristic effect of MFP on the formation of Fu brick tea and (2) comparison of tea samples throughout the MFP of FBT to elucidate the possible key metabolic pathways produced by the fungi. Non-targeted LC-MS analysis clearly distinguished FBT with other tea samples and highlighted some interesting metabolic pathways during the MFP including B ring fission catechin. Our study demonstrated that those fungi had a significant influence on the biochemical profiles in the FBT and consequently contributed to its unique quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spaceflight Activates Autophagy Programs and the Proteasome in Mouse Liver

PubMed Central

Blaber, Elizabeth A.; Pecaut, Michael J.

2017-01-01

Increased oxidative stress is an unavoidable consequence of exposure to the space environment. Our previous studies showed that mice exposed to space for 13.5 days had decreased glutathione levels, suggesting impairments in oxidative defense. Here we performed unbiased, unsupervised and integrated multi-‘omic analyses of metabolomic and transcriptomic datasets from mice flown aboard the Space Shuttle Atlantis. Enrichment analyses of metabolite and gene sets showed significant changes in osmolyte concentrations and pathways related to glycerophospholipid and sphingolipid metabolism, likely consequences of relative dehydration of the spaceflight mice. However, we also found increased enrichment of aminoacyl-tRNA biosynthesis and purine metabolic pathways, concomitant with enrichment of genes associated with autophagy and the ubiquitin-proteasome. When taken together with a downregulation in nuclear factor (erythroid-derived 2)-like 2-mediated signaling, our analyses suggest that decreased hepatic oxidative defense may lead to aberrant tRNA post-translational processing, induction of degradation programs and senescence-associated mitochondrial dysfunction in response to the spaceflight environment. PMID:28953266

Spaceflight Activates Autophagy Programs and the Proteasome in Mouse Liver.

PubMed

Blaber, Elizabeth A; Pecaut, Michael J; Jonscher, Karen R

2017-09-27

Increased oxidative stress is an unavoidable consequence of exposure to the space environment. Our previous studies showed that mice exposed to space for 13.5 days had decreased glutathione levels, suggesting impairments in oxidative defense. Here we performed unbiased, unsupervised and integrated multi-'omic analyses of metabolomic and transcriptomic datasets from mice flown aboard the Space Shuttle Atlantis. Enrichment analyses of metabolite and gene sets showed significant changes in osmolyte concentrations and pathways related to glycerophospholipid and sphingolipid metabolism, likely consequences of relative dehydration of the spaceflight mice. However, we also found increased enrichment of aminoacyl-tRNA biosynthesis and purine metabolic pathways, concomitant with enrichment of genes associated with autophagy and the ubiquitin-proteasome. When taken together with a downregulation in nuclear factor (erythroid-derived 2)-like 2-mediated signaling, our analyses suggest that decreased hepatic oxidative defense may lead to aberrant tRNA post-translational processing, induction of degradation programs and senescence-associated mitochondrial dysfunction in response to the spaceflight environment.

Power Generation from a Radiative Thermal Source Using a Large-Area Infrared Rectenna

NASA Astrophysics Data System (ADS)

Shank, Joshua; Kadlec, Emil A.; Jarecki, Robert L.; Starbuck, Andrew; Howell, Stephen; Peters, David W.; Davids, Paul S.

2018-05-01

Electrical power generation from a moderate-temperature thermal source by means of direct conversion of infrared radiation is important and highly desirable for energy harvesting from waste heat and micropower applications. Here, we demonstrate direct rectified power generation from an unbiased large-area nanoantenna-coupled tunnel diode rectifier called a rectenna. Using a vacuum radiometric measurement technique with irradiation from a temperature-stabilized thermal source, a generated power density of 8 nW /cm2 is observed at a source temperature of 450 °C for the unbiased rectenna across an optimized load resistance. The optimized load resistance for the peak power generation for each temperature coincides with the tunnel diode resistance at zero bias and corresponds to the impedance matching condition for a rectifying antenna. Current-voltage measurements of a thermally illuminated large-area rectenna show current zero crossing shifts into the second quadrant indicating rectification. Photon-assisted tunneling in the unbiased rectenna is modeled as the mechanism for the large short-circuit photocurrents observed where the photon energy serves as an effective bias across the tunnel junction. The measured current and voltage across the load resistor as a function of the thermal source temperature represents direct current electrical power generation.

Prioritizing causal disease genes using unbiased genomic features.

PubMed

Deo, Rahul C; Musso, Gabriel; Tasan, Murat; Tang, Paul; Poon, Annie; Yuan, Christiana; Felix, Janine F; Vasan, Ramachandran S; Beroukhim, Rameen; De Marco, Teresa; Kwok, Pui-Yan; MacRae, Calum A; Roth, Frederick P

2014-12-03

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM. Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

Multicenter external validation of two malignancy risk prediction models in patients undergoing 18F-FDG-PET for solitary pulmonary nodule evaluation.

PubMed

Perandini, Simone; Soardi, G A; Larici, A R; Del Ciello, A; Rizzardi, G; Solazzo, A; Mancino, L; Zeraj, F; Bernhart, M; Signorini, M; Motton, M; Montemezzi, S

2017-05-01

To achieve multicentre external validation of the Herder and Bayesian Inference Malignancy Calculator (BIMC) models. Two hundred and fifty-nine solitary pulmonary nodules (SPNs) collected from four major hospitals which underwent 18-FDG-PET characterization were included in this multicentre retrospective study. The Herder model was tested on all available lesions (group A). A subgroup of 180 SPNs (group B) was used to provide unbiased comparison between the Herder and BIMC models. Receiver operating characteristic (ROC) area under the curve (AUC) analysis was performed to assess diagnostic accuracy. Decision analysis was performed by adopting the risk threshold stated in British Thoracic Society (BTS) guidelines. Unbiased comparison performed In Group B showed a ROC AUC for the Herder model of 0.807 (95 % CI 0.742-0.862) and for the BIMC model of 0.822 (95 % CI 0.758-0.875). Both the Herder and the BIMC models were proven to accurately predict the risk of malignancy when tested on a large multicentre external case series. The BIMC model seems advantageous on the basis of a more favourable decision analysis. • The Herder model showed a ROC AUC of 0.807 on 180 SPNs. • The BIMC model showed a ROC AUC of 0.822 on 180 SPNs. • Decision analysis is more favourable to the BIMC model.

Minimum variance geographic sampling

NASA Technical Reports Server (NTRS)

Terrell, G. R. (Principal Investigator)

1980-01-01

Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

Sensitivity to PI3K and AKT inhibitors is mediated by divergent molecular mechanisms in subtypes of DLBCL.

PubMed

Erdmann, Tabea; Klener, Pavel; Lynch, James T; Grau, Michael; Vočková, Petra; Molinsky, Jan; Tuskova, Diana; Hudson, Kevin; Polanska, Urszula M; Grondine, Michael; Mayo, Michele; Dai, Beiying; Pfeifer, Matthias; Erdmann, Kristian; Schwammbach, Daniela; Zapukhlyak, Myroslav; Staiger, Annette M; Ott, German; Berdel, Wolfgang E; Davies, Barry R; Cruzalegui, Francisco; Trneny, Marek; Lenz, Peter; Barry, Simon T; Lenz, Georg

2017-07-20

Activated B-cell-like (ABC) and germinal center B-cell-like diffuse large B-cell lymphoma (DLBCL) represent the 2 major molecular DLBCL subtypes. They are characterized by differences in clinical course and by divergent addiction to oncogenic pathways. To determine activity of novel compounds in these 2 subtypes, we conducted an unbiased pharmacologic in vitro screen. The phosphatidylinositol-3-kinase (PI3K) α/δ (PI3Kα/δ) inhibitor AZD8835 showed marked potency in ABC DLBCL models, whereas the protein kinase B (AKT) inhibitor AZD5363 induced apoptosis in PTEN-deficient DLBCLs irrespective of their molecular subtype. These in vitro results were confirmed in various cell line xenograft and patient-derived xenograft mouse models in vivo. Treatment with AZD8835 induced inhibition of nuclear factor κB signaling, prompting us to combine AZD8835 with the Bruton's tyrosine kinase inhibitor ibrutinib. This combination was synergistic and effective both in vitro and in vivo. In contrast, the AKT inhibitor AZD5363 was effective in PTEN-deficient DLBCLs through downregulation of the oncogenic transcription factor MYC. Collectively, our data suggest that patients should be stratified according to their oncogenic dependencies when treated with PI3K and AKT inhibitors. © 2017 by The American Society of Hematology.

Analysis of the Free-Energy Surface of Proteins from Reversible Folding Simulations

PubMed Central

Allen, Lucy R.; Krivov, Sergei V.; Paci, Emanuele

2009-01-01

Computer generated trajectories can, in principle, reveal the folding pathways of a protein at atomic resolution and possibly suggest general and simple rules for predicting the folded structure of a given sequence. While such reversible folding trajectories can only be determined ab initio using all-atom transferable force-fields for a few small proteins, they can be determined for a large number of proteins using coarse-grained and structure-based force-fields, in which a known folded structure is by construction the absolute energy and free-energy minimum. Here we use a model of the fast folding helical λ-repressor protein to generate trajectories in which native and non-native states are in equilibrium and transitions are accurately sampled. Yet, representation of the free-energy surface, which underlies the thermodynamic and dynamic properties of the protein model, from such a trajectory remains a challenge. Projections over one or a small number of arbitrarily chosen progress variables often hide the most important features of such surfaces. The results unequivocally show that an unprojected representation of the free-energy surface provides important and unbiased information and allows a simple and meaningful description of many-dimensional, heterogeneous trajectories, providing new insight into the possible mechanisms of fast-folding proteins. PMID:19593364

Analysis of the free-energy surface of proteins from reversible folding simulations.

PubMed

Allen, Lucy R; Krivov, Sergei V; Paci, Emanuele

2009-07-01

Computer generated trajectories can, in principle, reveal the folding pathways of a protein at atomic resolution and possibly suggest general and simple rules for predicting the folded structure of a given sequence. While such reversible folding trajectories can only be determined ab initio using all-atom transferable force-fields for a few small proteins, they can be determined for a large number of proteins using coarse-grained and structure-based force-fields, in which a known folded structure is by construction the absolute energy and free-energy minimum. Here we use a model of the fast folding helical lambda-repressor protein to generate trajectories in which native and non-native states are in equilibrium and transitions are accurately sampled. Yet, representation of the free-energy surface, which underlies the thermodynamic and dynamic properties of the protein model, from such a trajectory remains a challenge. Projections over one or a small number of arbitrarily chosen progress variables often hide the most important features of such surfaces. The results unequivocally show that an unprojected representation of the free-energy surface provides important and unbiased information and allows a simple and meaningful description of many-dimensional, heterogeneous trajectories, providing new insight into the possible mechanisms of fast-folding proteins.

Optimal reconstruction of the states in qutrit systems

NASA Astrophysics Data System (ADS)

Yan, Fei; Yang, Ming; Cao, Zhuo-Liang

2010-10-01

Based on mutually unbiased measurements, an optimal tomographic scheme for the multiqutrit states is presented explicitly. Because the reconstruction process of states based on mutually unbiased states is free of information waste, we refer to our scheme as the optimal scheme. By optimal we mean that the number of the required conditional operations reaches the minimum in this tomographic scheme for the states of qutrit systems. Special attention will be paid to how those different mutually unbiased measurements are realized; that is, how to decompose each transformation that connects each mutually unbiased basis with the standard computational basis. It is found that all those transformations can be decomposed into several basic implementable single- and two-qutrit unitary operations. For the three-qutrit system, there exist five different mutually unbiased-bases structures with different entanglement properties, so we introduce the concept of physical complexity to minimize the number of nonlocal operations needed over the five different structures. This scheme is helpful for experimental scientists to realize the most economical reconstruction of quantum states in qutrit systems.

Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction.

PubMed

Cheng, Hao; Garrick, Dorian J; Fernando, Rohan L

2017-01-01

A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to quantify the predictive ability of a statistical model. Naive application of Leave-one-out cross validation is computationally intensive because the training and validation analyses need to be repeated n times, once for each observation. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis. Efficient Leave-one-out cross validation strategies is 786 times faster than the naive application for a simulated dataset with 1,000 observations and 10,000 markers and 99 times faster with 1,000 observations and 100 markers. These efficiencies relative to the naive approach using the same model will increase with increases in the number of observations. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis.

Eicosanomic profiling reveals dominance of the epoxygenase pathway in human amniotic fluid at term in spontaneous labor

PubMed Central

Maddipati, Krishna Rao; Romero, Roberto; Chaiworapongsa, Tinnakorn; Zhou, Sen-Lin; Xu, Zhonghui; Tarca, Adi L.; Kusanovic, Juan Pedro; Munoz, Hernan; Honn, Kenneth V.

2014-01-01

Lipid mediators play an important role in reproductive biology, especially, in parturition. Enhanced biosynthesis of eicosanoids, such as prostaglandin E2 (PGE2) and PGF2α, precedes the onset of labor as a result of increased expression of inducible cyclooxygenase 2 (COX-2) in placental tissues. Metabolism of arachidonic acid results in bioactive lipid mediators beyond prostaglandins that could significantly influence myometrial activity. Therefore, an unbiased lipidomic approach was used to profile the arachidonic acid metabolome of amniotic fluid. In this study, liquid chromatography–mass spectrometry was used for the first time to quantitate these metabolites in human amniotic fluid by comparing patients at midtrimester, at term but not in labor, and at term and in spontaneous labor. In addition to exposing novel aspects of COX pathway metabolism, this lipidomic study revealed a dramatic increase in epoxygenase- and lipoxygenase-pathway-derived lipid mediators in spontaneous labor with remarkable product selectivity. Despite their recognition as anti-inflammatory lipid mediators and regulators of ion channels, little is known about the epoxygenase pathway in labor. Epoxygenase pathway metabolites are established regulators of vascular homeostasis in cardiovascular and renal physiology. Their presence as the dominant lipid mediators in spontaneous labor at term portends a yet undiscovered physiological function in parturition.—Maddipati, K. R., Romero, R., Chaiworapongsa, T., Zhou, S.-L., Xu, Z., Tarca, A. L., Kusanovic, J. P., Munoz, H., Honn, K. V. Eicosanomic profiling reveals dominance of the epoxygenase pathway in human amniotic fluid at term in spontaneous labor. PMID:25059230

An approach to checking case-crossover analyses based on equivalence with time-series methods.

PubMed

Lu, Yun; Symons, James Morel; Geyh, Alison S; Zeger, Scott L

2008-03-01

The case-crossover design has been increasingly applied to epidemiologic investigations of acute adverse health effects associated with ambient air pollution. The correspondence of the design to that of matched case-control studies makes it inferentially appealing for epidemiologic studies. Case-crossover analyses generally use conditional logistic regression modeling. This technique is equivalent to time-series log-linear regression models when there is a common exposure across individuals, as in air pollution studies. Previous methods for obtaining unbiased estimates for case-crossover analyses have assumed that time-varying risk factors are constant within reference windows. In this paper, we rely on the connection between case-crossover and time-series methods to illustrate model-checking procedures from log-linear model diagnostics for time-stratified case-crossover analyses. Additionally, we compare the relative performance of the time-stratified case-crossover approach to time-series methods under 3 simulated scenarios representing different temporal patterns of daily mortality associated with air pollution in Chicago, Illinois, during 1995 and 1996. Whenever a model-be it time-series or case-crossover-fails to account appropriately for fluctuations in time that confound the exposure, the effect estimate will be biased. It is therefore important to perform model-checking in time-stratified case-crossover analyses rather than assume the estimator is unbiased.

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

Evolution of learning strategies in temporally and spatially variable environments: A review of theory

PubMed Central

Aoki, Kenichi; Feldman, Marcus W.

2013-01-01

The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change – coevolutionary, two-timescale, and information decay – are compared and shown to sometimes yield contradictory results. The so-called Rogers’ paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers’ paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. PMID:24211681

Evolution of learning strategies in temporally and spatially variable environments: a review of theory.

PubMed

Aoki, Kenichi; Feldman, Marcus W

2014-02-01

The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change--coevolutionary, two-timescale, and information decay--are compared and shown to sometimes yield contradictory results. The so-called Rogers' paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers' paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. Copyright © 2013 Elsevier Inc. All rights reserved.

Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories

PubMed Central

Donovan, Rory M.; Tapia, Jose-Juan; Sullivan, Devin P.; Faeder, James R.; Murphy, Robert F.; Dittrich, Markus; Zuckerman, Daniel M.

2016-01-01

The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE) strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane) and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation—by orders of magnitude for some observables. PMID:26845334

Grand canonical validation of the bipartite international trade network.

PubMed

Straka, Mika J; Caldarelli, Guido; Saracco, Fabio

2017-08-01

Devising strategies for economic development in a globally competitive landscape requires a solid and unbiased understanding of countries' technological advancements and similarities among export products. Both can be addressed through the bipartite representation of the International Trade Network. In this paper, we apply the recently proposed grand canonical projection algorithm to uncover country and product communities. Contrary to past endeavors, our methodology, based on information theory, creates monopartite projections in an unbiased and analytically tractable way. Single links between countries or products represent statistically significant signals, which are not accounted for by null models such as the bipartite configuration model. We find stable country communities reflecting the socioeconomic distinction in developed, newly industrialized, and developing countries. Furthermore, we observe product clusters based on the aforementioned country groups. Our analysis reveals the existence of a complicated structure in the bipartite International Trade Network: apart from the diversification of export baskets from the most basic to the most exclusive products, we observe a statistically significant signal of an export specialization mechanism towards more sophisticated products.

Grand canonical validation of the bipartite international trade network

NASA Astrophysics Data System (ADS)

Straka, Mika J.; Caldarelli, Guido; Saracco, Fabio

2017-08-01

Devising strategies for economic development in a globally competitive landscape requires a solid and unbiased understanding of countries' technological advancements and similarities among export products. Both can be addressed through the bipartite representation of the International Trade Network. In this paper, we apply the recently proposed grand canonical projection algorithm to uncover country and product communities. Contrary to past endeavors, our methodology, based on information theory, creates monopartite projections in an unbiased and analytically tractable way. Single links between countries or products represent statistically significant signals, which are not accounted for by null models such as the bipartite configuration model. We find stable country communities reflecting the socioeconomic distinction in developed, newly industrialized, and developing countries. Furthermore, we observe product clusters based on the aforementioned country groups. Our analysis reveals the existence of a complicated structure in the bipartite International Trade Network: apart from the diversification of export baskets from the most basic to the most exclusive products, we observe a statistically significant signal of an export specialization mechanism towards more sophisticated products.

An unbiased risk estimator for image denoising in the presence of mixed poisson-gaussian noise.

PubMed

Le Montagner, Yoann; Angelini, Elsa D; Olivo-Marin, Jean-Christophe

2014-03-01

The behavior and performance of denoising algorithms are governed by one or several parameters, whose optimal settings depend on the content of the processed image and the characteristics of the noise, and are generally designed to minimize the mean squared error (MSE) between the denoised image returned by the algorithm and a virtual ground truth. In this paper, we introduce a new Poisson-Gaussian unbiased risk estimator (PG-URE) of the MSE applicable to a mixed Poisson-Gaussian noise model that unifies the widely used Gaussian and Poisson noise models in fluorescence bioimaging applications. We propose a stochastic methodology to evaluate this estimator in the case when little is known about the internal machinery of the considered denoising algorithm, and we analyze both theoretically and empirically the characteristics of the PG-URE estimator. Finally, we evaluate the PG-URE-driven parametrization for three standard denoising algorithms, with and without variance stabilizing transforms, and different characteristics of the Poisson-Gaussian noise mixture.

Dynamic properties of molecular motors in burnt-bridge models

NASA Astrophysics Data System (ADS)

Artyomov, Maxim N.; Morozov, Alexander Yu; Pronina, Ekaterina; Kolomeisky, Anatoly B.

2007-08-01

Dynamic properties of molecular motors that fuel their motion by actively interacting with underlying molecular tracks are studied theoretically via discrete-state stochastic 'burnt-bridge' models. The transport of the particles is viewed as an effective diffusion along one-dimensional lattices with periodically distributed weak links. When an unbiased random walker passes the weak link it can be destroyed ('burned') with probability p, providing a bias in the motion of the molecular motor. We present a theoretical approach that allows one to calculate exactly all dynamic properties of motor proteins, such as velocity and dispersion, under general conditions. It is found that dispersion is a decreasing function of the concentration of bridges, while the dependence of dispersion on the burning probability is more complex. Our calculations also show a gap in dispersion for very low concentrations of weak links or for very low burning probabilities which indicates a dynamic phase transition between unbiased and biased diffusion regimes. Theoretical findings are supported by Monte Carlo computer simulations.

Functional renormalization group and bosonization as a solver for 2D fermionic Hubbard models

NASA Astrophysics Data System (ADS)

Schuetz, Florian; Marston, Brad

2007-03-01

The functional renormalization group (fRG) provides an unbiased framework to analyze competing instabilities in two-dimensional electron systems and has been used extensively over the past decade [1]. In order to obtain an equally unbiased tool to interprete the flow, we investigate the combination of a many-patch, one-loop calculation with higher dimensional bosonization [2] of the resulting low-energy action. Subsequently a semi-classical approximation [3] can be used to describe the resulting phases. The spinless Hubbard model on a square lattice with nearest neighbor repulsion is investigated as a test case. [1] M. Salmhofer and C. Honerkamp, Prog. Theor. Phys. 105, 1 (2001). [2] A. Houghton, H.-J. Kwon, J. B. Marston, Adv.Phys. 49, 141 (2000); P. Kopietz, Bosonization of interacting fermions in arbitrary dimensions, (Springer, Berlin, 1997). [3] H.-H. Lin, L. Balents, M. P. A. Fisher, Phys. Rev. B 56, 6569 6593 (1997); J. O. Fjaerestad, J. B. Marston, U. Schollwoeck, Ann. Phys. (N.Y.) 321, 894 (2006).

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis.

PubMed

Liu, Qun; Peng, Yong-Bo; Qi, Lian-Wen; Cheng, Xiao-Lan; Xu, Xiao-Jun; Liu, Le-Le; Liu, E-Hu; Li, Ping

2012-01-01

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism.

PAGER 2.0: an update to the pathway, annotated-list and gene-signature electronic repository for Human Network Biology

PubMed Central

Yue, Zongliang; Zheng, Qi; Neylon, Michael T; Yoo, Minjae; Shin, Jimin; Zhao, Zhiying; Tan, Aik Choon

2018-01-01

Abstract Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug–gene, miRNA–gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. PMID:29126216

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis

PubMed Central

Liu, Qun; Peng, Yong-Bo; Qi, Lian-Wen; Cheng, Xiao-Lan; Xu, Xiao-Jun; Liu, Le-Le; Liu, E-Hu; Li, Ping

2012-01-01

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism. PMID:23243437

Aspects of mutually unbiased bases in odd-prime-power dimensions

NASA Astrophysics Data System (ADS)

Chaturvedi, S.

2002-04-01

We rephrase the Wootters-Fields construction [W. K. Wootters and B. C. Fields, Ann. Phys. 191, 363 (1989)] of a full set of mutually unbiased bases in a complex vector space of dimensions N=pr, where p is an odd prime, in terms of the character vectors of the cyclic group G of order p. This form may be useful in explicitly writing down mutually unbiased bases for N=pr.

Targeted next-generation sequencing makes new molecular diagnoses and expands genotype-phenotype relationship in Ehlers-Danlos syndrome.

PubMed

Weerakkody, Ruwan A; Vandrovcova, Jana; Kanonidou, Christina; Mueller, Michael; Gampawar, Piyush; Ibrahim, Yousef; Norsworthy, Penny; Biggs, Jennifer; Abdullah, Abdulshakur; Ross, David; Black, Holly A; Ferguson, David; Cheshire, Nicholas J; Kazkaz, Hanadi; Grahame, Rodney; Ghali, Neeti; Vandersteen, Anthony; Pope, F Michael; Aitman, Timothy J

2016-11-01

Ehlers-Danlos syndrome (EDS) comprises a group of overlapping hereditary disorders of connective tissue with significant morbidity and mortality, including major vascular complications. We sought to identify the diagnostic utility of a next-generation sequencing (NGS) panel in a mixed EDS cohort. We developed and applied PCR-based NGS assays for targeted, unbiased sequencing of 12 collagen and aortopathy genes to a cohort of 177 unrelated EDS patients. Variants were scored blind to previous genetic testing and then compared with results of previous Sanger sequencing. Twenty-eight pathogenic variants in COL5A1/2, COL3A1, FBN1, and COL1A1 and four likely pathogenic variants in COL1A1, TGFBR1/2, and SMAD3 were identified by the NGS assays. These included all previously detected single-nucleotide and other short pathogenic variants in these genes, and seven newly detected pathogenic or likely pathogenic variants leading to clinically significant diagnostic revisions. Twenty-two variants of uncertain significance were identified, seven of which were in aortopathy genes and required clinical follow-up. Unbiased NGS-based sequencing made new molecular diagnoses outside the expected EDS genotype-phenotype relationship and identified previously undetected clinically actionable variants in aortopathy susceptibility genes. These data may be of value in guiding future clinical pathways for genetic diagnosis in EDS.Genet Med 18 11, 1119-1127.

Common Variable Immunodeficiency Non-Infectious Disease Endotypes Redefined Using Unbiased Network Clustering in Large Electronic Datasets.

PubMed

Farmer, Jocelyn R; Ong, Mei-Sing; Barmettler, Sara; Yonker, Lael M; Fuleihan, Ramsay; Sullivan, Kathleen E; Cunningham-Rundles, Charlotte; Walter, Jolan E

2017-01-01

Common variable immunodeficiency (CVID) is increasingly recognized for its association with autoimmune and inflammatory complications. Despite recent advances in immunophenotypic and genetic discovery, clinical care of CVID remains limited by our inability to accurately model risk for non-infectious disease development. Herein, we demonstrate the utility of unbiased network clustering as a novel method to analyze inter-relationships between non-infectious disease outcomes in CVID using databases at the United States Immunodeficiency Network (USIDNET), the centralized immunodeficiency registry of the United States, and Partners, a tertiary care network in Boston, MA, USA, with a shared electronic medical record amenable to natural language processing. Immunophenotypes were comparable in terms of native antibody deficiencies, low titer response to pneumococcus, and B cell maturation arrest. However, recorded non-infectious disease outcomes were more substantial in the Partners cohort across the spectrum of lymphoproliferation, cytopenias, autoimmunity, atopy, and malignancy. Using unbiased network clustering to analyze 34 non-infectious disease outcomes in the Partners cohort, we further identified unique patterns of lymphoproliferative (two clusters), autoimmune (two clusters), and atopic (one cluster) disease that were defined as CVID non-infectious endotypes according to discrete and non-overlapping immunophenotypes. Markers were both previously described {high serum IgE in the atopic cluster [odds ratio (OR) 6.5] and low class-switched memory B cells in the total lymphoproliferative cluster (OR 9.2)} and novel [low serum C3 in the total lymphoproliferative cluster (OR 5.1)]. Mortality risk in the Partners cohort was significantly associated with individual non-infectious disease outcomes as well as lymphoproliferative cluster 2, specifically (OR 5.9). In contrast, unbiased network clustering failed to associate known comorbidities in the adult USIDNET cohort. Together, these data suggest that unbiased network clustering can be used in CVID to redefine non-infectious disease inter-relationships; however, applicability may be limited to datasets well annotated through mechanisms such as natural language processing. The lymphoproliferative, autoimmune, and atopic Partners CVID endotypes herein described can be used moving forward to streamline genetic and biomarker discovery and to facilitate early screening and intervention in CVID patients at highest risk for autoimmune and inflammatory progression.

A Division-Dependent Compartmental Model for Computing Cell Numbers in CFSE-based Lymphocyte Proliferation Assays

DTIC Science & Technology

2012-02-12

is the total number of data points, is an approximately unbiased estimate of the “expected relative Kullback - Leibler distance” ( information loss...possible models). Thus, after each model from Table 2 is fit to a data set, we can compute the Akaike weights for the set of candidate models and use ...computed from the OLS best- fit model solution (top), from a deconvolution of the data using normal curves (middle) and from a deconvolution of the data

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

NASA Technical Reports Server (NTRS)

Howell, L. W., Jr.

2003-01-01

A simple power law model consisting of a single spectral index, sigma(sub 2), is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index sigma(sub 2) greater than sigma(sub 1) above E(sub k). The maximum likelihood (ML) procedure was developed for estimating the single parameter sigma(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (Pl) consistency (asymptotically unbiased), (P2) efficiency (asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only be ascertained by calculating the CRB for an assumed energy spectrum- detector response function combination, which can be quite formidable in practice. However, the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are stained in practice are investigated.

Phosphorylation by PINK1 Releases the UBL Domain and Initializes the Conformational Opening of the E3 Ubiquitin Ligase Parkin

PubMed Central

Moussaud-Lamodière, Elisabeth L.; Dourado, Daniel F. A. R.; Flores, Samuel C.; Springer, Wolfdieter

2014-01-01

Loss-of-function mutations in PINK1 or PARKIN are the most common causes of autosomal recessive Parkinson's disease. Both gene products, the Ser/Thr kinase PINK1 and the E3 Ubiquitin ligase Parkin, functionally cooperate in a mitochondrial quality control pathway. Upon stress, PINK1 activates Parkin and enables its translocation to and ubiquitination of damaged mitochondria to facilitate their clearance from the cell. Though PINK1-dependent phosphorylation of Ser65 is an important initial step, the molecular mechanisms underlying the activation of Parkin's enzymatic functions remain unclear. Using molecular modeling, we generated a complete structural model of human Parkin at all atom resolution. At steady state, the Ub ligase is maintained inactive in a closed, auto-inhibited conformation that results from intra-molecular interactions. Evidently, Parkin has to undergo major structural rearrangements in order to unleash its catalytic activity. As a spark, we have modeled PINK1-dependent Ser65 phosphorylation in silico and provide the first molecular dynamics simulation of Parkin conformations along a sequential unfolding pathway that could release its intertwined domains and enable its catalytic activity. We combined free (unbiased) molecular dynamics simulation, Monte Carlo algorithms, and minimal-biasing methods with cell-based high content imaging and biochemical assays. Phosphorylation of Ser65 results in widening of a newly defined cleft and dissociation of the regulatory N-terminal UBL domain. This motion propagates through further opening conformations that allow binding of an Ub-loaded E2 co-enzyme. Subsequent spatial reorientation of the catalytic centers of both enzymes might facilitate the transfer of the Ub moiety to charge Parkin. Our structure-function study provides the basis to elucidate regulatory mechanisms and activity of the neuroprotective Parkin. This may open up new avenues for the development of small molecule Parkin activators through targeted drug design. PMID:25375667

Core signaling pathways in ovarian cancer stem cell revealed by integrative analysis of multi-marker genomics data.

PubMed

Zhang, Tianyu; Xu, Jielin; Deng, Siyuan; Zhou, Fengqi; Li, Jin; Zhang, Liwei; Li, Lang; Wang, Qi-En; Li, Fuhai

2018-01-01

Tumor recurrence occurs in more than 70% of ovarian cancer patients, and the majority eventually becomes refractory to treatments. Ovarian Cancer Stem Cells (OCSCs) are believed to be responsible for the tumor relapse and drug resistance. Therefore, eliminating ovarian CSCs is important to improve the prognosis of ovarian cancer patients. However, there is a lack of effective drugs to eliminate OCSCs because the core signaling pathways regulating OCSCs remain unclear. Also it is often hard for biologists to identify a few testable targets and infer driver signaling pathways regulating CSCs from a large number of differentially expression genes in an unbiased manner. In this study, we propose a straightforward and integrative analysis to identify potential core signaling pathways of OCSCs by integrating transcriptome data of OCSCs isolated based on two distinctive markers, ALDH and side population, with regulatory network (Transcription Factor (TF) and Target Interactome) and signaling pathways. We first identify the common activated TFs in two OCSC populations integrating the gene expression and TF-target Interactome; and then uncover up-stream signaling cascades regulating the activated TFs. In specific, 22 activated TFs are identified. Through literature search validation, 15 of them have been reported in association with cancer stem cells. Additionally, 10 TFs are found in the KEGG signaling pathways, and their up-stream signaling cascades are extracted, which also provide potential treatment targets. Moreover, 40 FDA approved drugs are identified to target on the up-stream signaling cascades, and 15 of them have been reported in literatures in cancer stem cell treatment. In conclusion, the proposed approach can uncover the activated up-stream signaling, activated TFs and up-regulated target genes that constitute the potential core signaling pathways of ovarian CSC. Also drugs and drug combinations targeting on the core signaling pathways might be able to eliminate OCSCs. The proposed approach can also be applied for identifying potential activated signaling pathways of other types of cancers.

Analyzing Evolving Social Network 2 (EVOLVE2)

DTIC Science & Technology

2015-04-01

Facebook friendship graph. We simulated two different interaction models: one-to-one and one-to-many interactions . Both types of models revealed...to an unbiased random walk on the reweighed “ interaction graph” W with entries wij = αiAijαj . The generalized Laplacian framework is flexible enough...Information Intelligence Systems & Analysis Division Information Directorate This report is published in the interest of scientific and technical

Cubature/ Unscented/ Sigma Point Kalman Filtering with Angular Measurement Models

DTIC Science & Technology

2015-07-06

Cubature/ Unscented/ Sigma Point Kalman Filtering with Angular Measurement Models David Frederic Crouse Naval Research Laboratory 4555 Overlook Ave...measurement and process non- linearities, such as the cubature Kalman filter , can perform ex- tremely poorly in many applications involving angular... Kalman filtering is a realization of the best linear unbiased estimator (BLUE) that evaluates certain integrals for expected values using different forms

Preface to the special volume on the second Sandia Fracture Challenge

DOE PAGES

Kramer, Sharlotte Lorraine Bolyard; Boyce, Brad

2016-01-01

In this study, ductile failure of structural metals is a pervasive issue for applications such as automotive manufacturing, transportation infrastructures, munitions and armor, and energy generation. Experimental investigation of all relevant failure scenarios is intractable, requiring reliance on computation models. Our confidence in model predictions rests on unbiased assessments of the entire predictive capability, including the mathematical formulation, numerical implementation, calibration, and execution.

Genome-wide association studies on HIV susceptibility, pathogenesis and pharmacogenomics

PubMed Central

2012-01-01

Susceptibility to HIV-1 and the clinical course after infection show a substantial heterogeneity between individuals. Part of this variability can be attributed to host genetic variation. Initial candidate gene studies have revealed interesting host factors that influence HIV infection, replication and pathogenesis. Recently, genome-wide association studies (GWAS) were utilized for unbiased searches at a genome-wide level to discover novel genetic factors and pathways involved in HIV-1 infection. This review gives an overview of findings from the GWAS performed on HIV infection, within different cohorts, with variable patient and phenotype selection. Furthermore, novel techniques and strategies in research that might contribute to the complete understanding of virus-host interactions and its role on the pathogenesis of HIV infection are discussed. PMID:22920050

Eigenstate Thermalization for Degenerate Observables

NASA Astrophysics Data System (ADS)

Anza, Fabio; Gogolin, Christian; Huber, Marcus

2018-04-01

Under unitary time evolution, expectation values of physically reasonable observables often evolve towards the predictions of equilibrium statistical mechanics. The eigenstate thermalization hypothesis (ETH) states that this is also true already for individual energy eigenstates. Here we aim at elucidating the emergence of the ETH for observables that can realistically be measured due to their high degeneracy, such as local, extensive, or macroscopic observables. We bisect this problem into two parts, a condition on the relative overlaps and one on the relative phases between the eigenbases of the observable and Hamiltonian. We show that the relative overlaps are unbiased for highly degenerate observables and demonstrate that unless relative phases conspire to cumulative effects, this makes such observables verify the ETH. Through this we elucidate potential pathways towards proofs of thermalization.

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

PubMed

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Unbiased RNAi screen for hepcidin regulators links hepcidin suppression to proliferative Ras/RAF and nutrient-dependent mTOR signaling

PubMed Central

Mleczko-Sanecka, Katarzyna; Roche, Franziska; Rita da Silva, Ana; Call, Debora; D’Alessio, Flavia; Ragab, Anan; Lapinski, Philip E.; Ummanni, Ramesh; Korf, Ulrike; Oakes, Christopher; Damm, Georg; D’Alessandro, Lorenza A.; Klingmüller, Ursula; King, Philip D.; Boutros, Michael; Hentze, Matthias W.

2014-01-01

The hepatic hormone hepcidin is a key regulator of systemic iron metabolism. Its expression is largely regulated by 2 signaling pathways: the “iron-regulated” bone morphogenetic protein (BMP) and the inflammatory JAK-STAT pathways. To obtain broader insights into cellular processes that modulate hepcidin transcription and to provide a resource to identify novel genetic modifiers of systemic iron homeostasis, we designed an RNA interference (RNAi) screen that monitors hepcidin promoter activity after the knockdown of 19 599 genes in hepatocarcinoma cells. Interestingly, many of the putative hepcidin activators play roles in signal transduction, inflammation, or transcription, and affect hepcidin transcription through BMP-responsive elements. Furthermore, our work sheds light on new components of the transcriptional machinery that maintain steady-state levels of hepcidin expression and its responses to the BMP- and interleukin-6–triggered signals. Notably, we discover hepcidin suppression mediated via components of Ras/RAF MAPK and mTOR signaling, linking hepcidin transcriptional control to the pathways that respond to mitogen stimulation and nutrient status. Thus using a combination of RNAi screening, reverse phase protein arrays, and small molecules testing, we identify links between the control of systemic iron homeostasis and critical liver processes such as regeneration, response to injury, carcinogenesis, and nutrient metabolism. PMID:24385536

The Mediator complex of Caenorhabditis elegans: insights into the developmental and physiological roles of a conserved transcriptional coregulator

PubMed Central

Grants, Jennifer M.; Goh, Grace Y. S.; Taubert, Stefan

2015-01-01

The Mediator multiprotein complex (‘Mediator’) is an important transcriptional coregulator that is evolutionarily conserved throughout eukaryotes. Although some Mediator subunits are essential for the transcription of all protein-coding genes, others influence the expression of only subsets of genes and participate selectively in cellular signaling pathways. Here, we review the current knowledge of Mediator subunit function in the nematode Caenorhabditis elegans, a metazoan in which established and emerging genetic technologies facilitate the study of developmental and physiological regulation in vivo. In this nematode, unbiased genetic screens have revealed critical roles for Mediator components in core developmental pathways such as epidermal growth factor (EGF) and Wnt/β-catenin signaling. More recently, important roles for C. elegans Mediator subunits have emerged in the regulation of lipid metabolism and of systemic stress responses, engaging conserved transcription factors such as nuclear hormone receptors (NHRs). We emphasize instances where similar functions for individual Mediator subunits exist in mammals, highlighting parallels between Mediator subunit action in nematode development and in human cancer biology. We also discuss a parallel between the association of the Mediator subunit MED12 with several human disorders and the role of its C. elegans ortholog mdt-12 as a regulatory hub that interacts with numerous signaling pathways. PMID:25634893

Modeling the functional genomics of autism using human neurons.

PubMed

Konopka, G; Wexler, E; Rosen, E; Mukamel, Z; Osborn, G E; Chen, L; Lu, D; Gao, F; Gao, K; Lowe, J K; Geschwind, D H

2012-02-01

Human neural progenitors from a variety of sources present new opportunities to model aspects of human neuropsychiatric disease in vitro. Such in vitro models provide the advantages of a human genetic background combined with rapid and easy manipulation, making them highly useful adjuncts to animal models. Here, we examined whether a human neuronal culture system could be utilized to assess the transcriptional program involved in human neural differentiation and to model some of the molecular features of a neurodevelopmental disorder, such as autism. Primary normal human neuronal progenitors (NHNPs) were differentiated into a post-mitotic neuronal state through addition of specific growth factors and whole-genome gene expression was examined throughout a time course of neuronal differentiation. After 4 weeks of differentiation, a significant number of genes associated with autism spectrum disorders (ASDs) are either induced or repressed. This includes the ASD susceptibility gene neurexin 1, which showed a distinct pattern from neurexin 3 in vitro, and which we validated in vivo in fetal human brain. Using weighted gene co-expression network analysis, we visualized the network structure of transcriptional regulation, demonstrating via this unbiased analysis that a significant number of ASD candidate genes are coordinately regulated during the differentiation process. As NHNPs are genetically tractable and manipulable, they can be used to study both the effects of mutations in multiple ASD candidate genes on neuronal differentiation and gene expression in combination with the effects of potential therapeutic molecules. These data also provide a step towards better understanding of the signaling pathways disrupted in ASD.

An Unbiased Estimator of Gene Diversity with Improved Variance for Samples Containing Related and Inbred Individuals of any Ploidy

PubMed Central

Harris, Alexandre M.; DeGiorgio, Michael

2016-01-01

Gene diversity, or expected heterozygosity (H), is a common statistic for assessing genetic variation within populations. Estimation of this statistic decreases in accuracy and precision when individuals are related or inbred, due to increased dependence among allele copies in the sample. The original unbiased estimator of expected heterozygosity underestimates true population diversity in samples containing relatives, as it only accounts for sample size. More recently, a general unbiased estimator of expected heterozygosity was developed that explicitly accounts for related and inbred individuals in samples. Though unbiased, this estimator’s variance is greater than that of the original estimator. To address this issue, we introduce a general unbiased estimator of gene diversity for samples containing related or inbred individuals, which employs the best linear unbiased estimator of allele frequencies, rather than the commonly used sample proportion. We examine the properties of this estimator, H∼BLUE, relative to alternative estimators using simulations and theoretical predictions, and show that it predominantly has the smallest mean squared error relative to others. Further, we empirically assess the performance of H∼BLUE on a global human microsatellite dataset of 5795 individuals, from 267 populations, genotyped at 645 loci. Additionally, we show that the improved variance of H∼BLUE leads to improved estimates of the population differentiation statistic, FST, which employs measures of gene diversity within its calculation. Finally, we provide an R script, BestHet, to compute this estimator from genomic and pedigree data. PMID:28040781

Preserving correlations between trajectories for efficient path sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gingrich, Todd R.; Geissler, Phillip L.; Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720

2015-06-21

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here, we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective onmore » Markov chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this “noise guidance” synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved for even very long trajectories.« less

Metabolomics profiles delineate uridine deficiency contributes to mitochondria-mediated apoptosis induced by celastrol in human acute promyelocytic leukemia cells

PubMed Central

Li, Lei; Huan, Fei; Li, Aiping; Liu, Yanqing; Xia, Yankai; Duan, Jin-ao; Ma, Shiping

2016-01-01

Celastrol, extracted from “Thunder of God Vine”, is a promising anti-cancer natural product. However, its effect on acute promyelocytic leukemia (APL) and underlying molecular mechanism are poorly understood. The purpose of this study was to explore its effect on APL and underlying mechanism based on metabolomics. Firstly, multiple assays indicated that celastrol could induce apoptosis of APL cells via p53-activated mitochondrial pathway. Secondly, unbiased metabolomics revealed that uridine was the most notable changed metabolite. Further study verified that uridine could reverse the apoptosis induced by celastrol. The decreased uridine was caused by suppressing the expression of gene encoding Dihydroorotate dehydrogenase, whose inhibitor could also induce apoptosis of APL cells. At last, mouse model confirmed that celastrol inhibited tumor growth through enhanced apoptosis. Celastrol could also decrease uridine and DHODH protein level in tumor tissues. Our in vivo study also indicated that celastrol had no systemic toxicity at pharmacological dose (2 mg/kg, i.p., 21 days). Altogether, our metabolomics study firstly reveals that uridine deficiency contributes to mitochondrial apoptosis induced by celastrol in APL cells. Celastrol shows great potential for the treatment of APL. PMID:27374097

Atomistic Simulations of the pH Induced Functional Rearrangement of Influenza Hemagglutinin

NASA Astrophysics Data System (ADS)

Lin, Xingcheng; Noel, Jeffrey; Wang, Qinghua; Ma, Jianpeng; Onuchic, Jose

Influenza hemagglutinin (HA), a surface glycoprotein responsible for the entry and replication of flu viruses in their host cells, functions by starting a dramatic conformational rearrangement, which leads to a fusion of the viral and endosomal membranes. It has been claimed that a loop-to-coiled-coil transition of the B-loop domain of HA drives the HA-induced membrane fusion. On the lack of dynamical details, however, the microscopic picture for this proposed ``spring-loaded'' movement is missing. To elaborate on the transition of the B-loop, we performed a set of unbiased all-atom molecular dynamics simulations of the full B-loop structure with the CHARMM36 force field. The complete free-energy profile constructed from our simulations reveals a slow transition rate for the B-loop that is incompatible with a downhill process. Additionally, our simulations indicate two potential sources of kinetic traps in the structural switch of the B-loop: Desolvation barriers and non-native secondary structure formation. The slow timescale of the B-loop transition also confirms our previous discovery from simulations using a coarse-grained structure-based model, which identified two competitive pathways both with a slow B-loop transition for HA to guide the membrane fusion.

CellStress - open source image analysis program for single-cell analysis

NASA Astrophysics Data System (ADS)

Smedh, Maria; Beck, Caroline; Sott, Kristin; Goksör, Mattias

2010-08-01

This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimer's or Huntington's disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.

Population control of resident and immigrant microglia by mitosis and apoptosis.

PubMed

Wirenfeldt, Martin; Dissing-Olesen, Lasse; Anne Babcock, Alicia; Nielsen, Marianne; Meldgaard, Michael; Zimmer, Jens; Azcoitia, Iñigo; Leslie, Robert Graham Quinton; Dagnaes-Hansen, Frederik; Finsen, Bente

2007-08-01

Microglial population expansion occurs in response to neural damage via processes that involve mitosis and immigration of bone marrow-derived cells. However, little is known of the mechanisms that regulate clearance of reactive microglia, when microgliosis diminishes days to weeks later. We have investigated the mechanisms of microglial population control in a well-defined model of reactive microgliosis in the mouse dentate gyrus after perforant pathway axonal lesion. Unbiased stereological methods and flow cytometry demonstrate significant lesion-induced increases in microglial numbers. Reactive microglia often occurred in clusters, some having recently incorporated bromodeoxyuridine, showing that proliferation had occurred. Annexin V labeling and staining for activated caspase-3 and terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling showed that apoptotic mechanisms participate in dissolution of the microglial response. Using bone marrow chimeric mice, we found that the lesion-induced proliferative capacity of resident microglia superseded that of immigrant microglia, whereas lesion-induced kinetics of apoptosis were comparable. Microglial numbers and responses were severely reduced in bone marrow chimeric mice. These results broaden our understanding of the microglial response to neural damage by demonstrating that simultaneously occurring mitosis and apoptosis regulate expansion and reduction of both resident and immigrant microglial cell populations.

Some New Results on Grubbs’ Estimators.

DTIC Science & Technology

1983-06-01

8217 ESTIMATORS DENNIS A. BRINDLEY AND RALPH A. BRADLEY* Consider a two-way classification with n rows and r columns and the usual model of analysis of variance...except that the error components of the model may have heterogeneous variances, by columns. -Grubbs provided unbiased estimators Q. of a . that depend...of observations yij, i = 1, ... , n, j 1, ... , r, and the model , Yij = Ili + ij + Ej, (1) when Vi represents the mean response of row i, . represents

Fast genomic predictions via Bayesian G-BLUP and multilocus models of threshold traits including censored Gaussian data.

PubMed

Kärkkäinen, Hanni P; Sillanpää, Mikko J

2013-09-04

Because of the increased availability of genome-wide sets of molecular markers along with reduced cost of genotyping large samples of individuals, genomic estimated breeding values have become an essential resource in plant and animal breeding. Bayesian methods for breeding value estimation have proven to be accurate and efficient; however, the ever-increasing data sets are placing heavy demands on the parameter estimation algorithms. Although a commendable number of fast estimation algorithms are available for Bayesian models of continuous Gaussian traits, there is a shortage for corresponding models of discrete or censored phenotypes. In this work, we consider a threshold approach of binary, ordinal, and censored Gaussian observations for Bayesian multilocus association models and Bayesian genomic best linear unbiased prediction and present a high-speed generalized expectation maximization algorithm for parameter estimation under these models. We demonstrate our method with simulated and real data. Our example analyses suggest that the use of the extra information present in an ordered categorical or censored Gaussian data set, instead of dichotomizing the data into case-control observations, increases the accuracy of genomic breeding values predicted by Bayesian multilocus association models or by Bayesian genomic best linear unbiased prediction. Furthermore, the example analyses indicate that the correct threshold model is more accurate than the directly used Gaussian model with a censored Gaussian data, while with a binary or an ordinal data the superiority of the threshold model could not be confirmed.

Fast Genomic Predictions via Bayesian G-BLUP and Multilocus Models of Threshold Traits Including Censored Gaussian Data

PubMed Central

Kärkkäinen, Hanni P.; Sillanpää, Mikko J.

2013-01-01

Because of the increased availability of genome-wide sets of molecular markers along with reduced cost of genotyping large samples of individuals, genomic estimated breeding values have become an essential resource in plant and animal breeding. Bayesian methods for breeding value estimation have proven to be accurate and efficient; however, the ever-increasing data sets are placing heavy demands on the parameter estimation algorithms. Although a commendable number of fast estimation algorithms are available for Bayesian models of continuous Gaussian traits, there is a shortage for corresponding models of discrete or censored phenotypes. In this work, we consider a threshold approach of binary, ordinal, and censored Gaussian observations for Bayesian multilocus association models and Bayesian genomic best linear unbiased prediction and present a high-speed generalized expectation maximization algorithm for parameter estimation under these models. We demonstrate our method with simulated and real data. Our example analyses suggest that the use of the extra information present in an ordered categorical or censored Gaussian data set, instead of dichotomizing the data into case-control observations, increases the accuracy of genomic breeding values predicted by Bayesian multilocus association models or by Bayesian genomic best linear unbiased prediction. Furthermore, the example analyses indicate that the correct threshold model is more accurate than the directly used Gaussian model with a censored Gaussian data, while with a binary or an ordinal data the superiority of the threshold model could not be confirmed. PMID:23821618

Understanding the EF-hand closing pathway using non-biased interatomic potentials.

PubMed

Dupuis, L; Mousseau, Normand

2012-01-21

The EF-hand superfamily of proteins is characterized by the presence of calcium binding helix-loop-helix structures. Many of these proteins undergo considerable motion responsible for a wide range of properties upon binding but the exact mechanism at the root of this motion is not fully understood. Here, we use an unbiased accelerated multiscale simulation scheme, coupled with two force fields - CHARMM-EEF1 and the extended OPEP - to explore in details the closing pathway, from the unbound holo state to the closed apo state, of two EF-hand proteins, the Calmodulin and Troponin C N-terminal nodules. Based on a number of closing simulations for these two sequences, we show that the EF-hand β-scaffold, identified as crucial by Grabarek for the EF-hand opening driven by calcium binding, is also important in closing the EF-hand. We also show the crucial importance of the phenylalanine situated at the end of first EF-hand helix, and identify an intermediate state modulating its behavior, providing a detailed picture of the closing mechanism for these two representatives of EF-hand proteins. © 2012 American Institute of Physics

Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure.

PubMed

García-Sevillano, M A; García-Barrera, T; Navarro, F; Montero-Lobato, Z; Gómez-Ariza, J L

2015-04-01

Mass spectrometry (MS)-based toxicometabolomics requires analytical approaches for obtaining unbiased metabolic profiles. The present work explores the general application of direct infusion MS using a high mass resolution analyzer (a hybrid systems triple quadrupole-time-of-flight) and a complementary gas chromatography-MS analysis to mitochondria extracts from mouse hepatic cells, emphasizing on mitochondria isolation from hepatic cells with a commercial kit, sample treatment after cell lysis, comprehensive metabolomic analysis and pattern recognition from metabolic profiles. Finally, the metabolomic platform was successfully checked on a case-study based on the exposure experiment of mice Mus musculus to inorganic arsenic during 12 days. Endogenous metabolites alterations were recognized by partial least squares-discriminant analysis. Subsequently, metabolites were identified by combining MS/MS analysis and metabolomics databases. This work reports for the first time the effects of As-exposure on hepatic mitochondria metabolic pathways based on MS, and reveals disturbances in Krebs cycle, β-oxidation pathway, amino acids degradation and perturbations in creatine levels. This non-target analysis provides extensive metabolic information from mitochondrial organelle, which could be applied to toxicology, pharmacology and clinical studies.

Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes.

PubMed

Ai, Rizi; Laragione, Teresina; Hammaker, Deepa; Boyle, David L; Wildberg, Andre; Maeshima, Keisuke; Palescandolo, Emanuele; Krishna, Vinod; Pocalyko, David; Whitaker, John W; Bai, Yuchen; Nagpal, Sunil; Bachman, Kurtis E; Ainsworth, Richard I; Wang, Mengchi; Ding, Bo; Gulko, Percio S; Wang, Wei; Firestein, Gary S

2018-05-15

Epigenetics contributes to the pathogenesis of immune-mediated diseases like rheumatoid arthritis (RA). Here we show the first comprehensive epigenomic characterization of RA fibroblast-like synoviocytes (FLS), including histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3), open chromatin, RNA expression and whole-genome DNA methylation. To address complex multidimensional relationship and reveal epigenetic regulation of RA, we perform integrative analyses using a novel unbiased method to identify genomic regions with similar profiles. Epigenomically similar regions exist in RA cells and are associated with active enhancers and promoters and specific transcription factor binding motifs. Differentially marked genes are enriched for immunological and unexpected pathways, with "Huntington's Disease Signaling" identified as particularly prominent. We validate the relevance of this pathway to RA by showing that Huntingtin-interacting protein-1 regulates FLS invasion into matrix. This work establishes a high-resolution epigenomic landscape of RA and demonstrates the potential for integrative analyses to identify unanticipated therapeutic targets.

New molecular medicine: Diagnomics and pharmacogenomics

NASA Astrophysics Data System (ADS)

Kauffman, Michael G.

1999-04-01

Millennium Predictive Medicine (MPMx), a subsidiary of Millennium Pharmaceuticals, is focusing on the discovery and clinical validation of Diagnomic and Pharmacogenomic Tests which will replace many of the subjective elements of clinical decision making. Diagnomics are molecular diagnostic markers with prognostic and economic impact. While the majority of currently available diagnostics represent data points, Diagnomics allow patients and physicians to make scientifically based, individualized decisions about their disease and its therapy. Pharmacogenomics are diagnostics that specify the use or avoidance of specific therapeutics based on an individual genotype and/or disease subtype. MPMx uses the broad Millennium genomics, proteomics, and bioinformatics technologies in the analysis of human disease and drug response. These technologies permit global and unbiased approaches towards the elucidation of disease pathways and mechanisms at the molecular level. Germline or somatic mutations, RNA levels, or protein levels comprising these pathways and mechanisms are currently being evaluated as markers for disease predisposition, stage, aggressiveness, and likely drug response or drug toxicity. Diagnomic and Pharmacogenomic Tests are part of the new molecular medicine that is transforming clinical practice forma symptom/pathology-based art into a pre-symptom, mechanism- based science.

Operational Resiliency Management: An Introduction to the Resiliency Engineering Framework

DTIC Science & Technology

2006-09-20

Maturity Model Integration (CMMI) . 5 © 2006 Carnegie Mellon University y FRB Bus Con Conference 2006 Managing Today’s Operational Risk Challenges ...Bus Con Conference 2006 A model is needed to. . . Identify and prioritize risk exposures Define a process improvement roadmap Measure and facilitate...University y FRB Bus Con Conference 2006 Why use a “model” approach? Provides an operational risk roadmap Vendor-neutral, standardized, unbiased

Free energies from dynamic weighted histogram analysis using unbiased Markov state model.

PubMed

Rosta, Edina; Hummer, Gerhard

2015-01-13

The weighted histogram analysis method (WHAM) is widely used to obtain accurate free energies from biased molecular simulations. However, WHAM free energies can exhibit significant errors if some of the biasing windows are not fully equilibrated. To account for the lack of full equilibration, we develop the dynamic histogram analysis method (DHAM). DHAM uses a global Markov state model to obtain the free energy along the reaction coordinate. A maximum likelihood estimate of the Markov transition matrix is constructed by joint unbiasing of the transition counts from multiple umbrella-sampling simulations along discretized reaction coordinates. The free energy profile is the stationary distribution of the resulting Markov matrix. For this matrix, we derive an explicit approximation that does not require the usual iterative solution of WHAM. We apply DHAM to model systems, a chemical reaction in water treated using quantum-mechanics/molecular-mechanics (QM/MM) simulations, and the Na(+) ion passage through the membrane-embedded ion channel GLIC. We find that DHAM gives accurate free energies even in cases where WHAM fails. In addition, DHAM provides kinetic information, which we here use to assess the extent of convergence in each of the simulation windows. DHAM may also prove useful in the construction of Markov state models from biased simulations in phase-space regions with otherwise low population.

Oncogenic Properties of Apoptotic Tumor Cells in Aggressive B Cell Lymphoma

PubMed Central

Ford, Catriona A.; Petrova, Sofia; Pound, John D.; Voss, Jorine J.L.P.; Melville, Lynsey; Paterson, Margaret; Farnworth, Sarah L.; Gallimore, Awen M.; Cuff, Simone; Wheadon, Helen; Dobbin, Edwina; Ogden, Carol Anne; Dumitriu, Ingrid E.; Dunbar, Donald R.; Murray, Paul G.; Ruckerl, Dominik; Allen, Judith E.; Hume, David A.; van Rooijen, Nico; Goodlad, John R.; Freeman, Tom C.; Gregory, Christopher D.

2015-01-01

Summary Background Cells undergoing apoptosis are known to modulate their tissue microenvironments. By acting on phagocytes, notably macrophages, apoptotic cells inhibit immunological and inflammatory responses and promote trophic signaling pathways. Paradoxically, because of their potential to cause death of tumor cells and thereby militate against malignant disease progression, both apoptosis and tumor-associated macrophages (TAMs) are often associated with poor prognosis in cancer. We hypothesized that, in progression of malignant disease, constitutive loss of a fraction of the tumor cell population through apoptosis could yield tumor-promoting effects. Results Here, we demonstrate that apoptotic tumor cells promote coordinated tumor growth, angiogenesis, and accumulation of TAMs in aggressive B cell lymphomas. Through unbiased “in situ transcriptomics” analysis—gene expression profiling of laser-captured TAMs to establish their activation signature in situ—we show that these cells are activated to signal via multiple tumor-promoting reparatory, trophic, angiogenic, tissue remodeling, and anti-inflammatory pathways. Our results also suggest that apoptotic lymphoma cells help drive this signature. Furthermore, we demonstrate that, upon induction of apoptosis, lymphoma cells not only activate expression of the tumor-promoting matrix metalloproteinases MMP2 and MMP12 in macrophages but also express and process these MMPs directly. Finally, using a model of malignant melanoma, we show that the oncogenic potential of apoptotic tumor cells extends beyond lymphoma. Conclusions In addition to its profound tumor-suppressive role, apoptosis can potentiate cancer progression. These results have important implications for understanding the fundamental biology of cell death, its roles in malignant disease, and the broader consequences of apoptosis-inducing anti-cancer therapy. PMID:25702581

Cancer Drug Addiction is Relayed by an ERK2-Dependent Phenotype Switch

PubMed Central

Kong, Xiangjun; Kuilman, Thomas; Shahrabi, Aida; Boshuizen, Julia; Kemper, Kristel; Song, Ji-Ying; Niessen, Hans W.M.; Rozeman, Elisa A.; Geukes Foppen, Marnix H.; Blank, Christian U.; Peeper, Daniel S.

2017-01-01

Drug addiction denotes the dependency of tumors on the same therapeutic drugs to which they have acquired resistance. Observations from cultured cells1–3, animal models4 and patients5–7 raise the possibility that cancer drug addiction can instigate a potential cancer vulnerability, which may be used therapeutically. However, for this trait to become of clinical interest, it is imperative to first define the underlying mechanism. Therefore, we performed an unbiased CRISPR-Cas9 knockout screen to functionally mine the genome of melanoma cells that are both resistant and addicted to BRAF inhibition for “addiction genes”. Here, we describe a signaling pathway comprising ERK2, JUNB and FRA1, disruption of which allows tumor cells to reverse addiction and survive upon treatment discontinuation. This occurred both in culture and mice, and was irrespective of the acquired drug resistance mechanism. In melanoma and lung cancer cells, death induced by drug withdrawal was preceded by a specific ERK2-dependent phenotype switch, alongside transcriptional reprogramming reminiscent of EMT. In melanoma, this caused shutdown of the lineage survival oncoprotein MITF, restoration of which reversed both phenotype switching and drug addiction-associated lethality. In melanoma patients who had progressed on BRAF inhibition, treatment cessation was followed by increased expression of the phenotype switch-associated receptor tyrosine kinase AXL. Drug discontinuation synergized with the melanoma chemotherapeutic dacarbazine by further suppressing MITF and its prosurvival target BCL2 while inducing DNA damage. Our results uncover a pathway driving cancer drug addiction, which may guide alternating therapeutic strategies for enhanced clinical responses of drug-resistant cancers. PMID:28976960

Identification of specific metabolic pathways as druggable targets regulating the sensitivity to cyanide poisoning.

PubMed

Sips, Patrick Y; Shi, Xu; Musso, Gabriel; Nath, Anjali K; Zhao, Yanbin; Nielson, Jason; Morningstar, Jordan; Kelly, Amy E; Mikell, Brittney; Buys, Eva; Bebarta, Vikhyat; Rutter, Jared; Davisson, V Jo; Mahon, Sari; Brenner, Matthew; Boss, Gerry R; Peterson, Randall T; Gerszten, Robert E; MacRae, Calum A

2018-01-01

Cyanide is a potent toxic agent, and the few available antidotes are not amenable to rapid deployment in mass exposures. As a result, there are ongoing efforts to exploit different animal models to identify novel countermeasures. We have created a pipeline that combines high-throughput screening in zebrafish with subsequent validation in two mammalian small animal models as well as a porcine large animal model. We found that zebrafish embryos in the first 3 days post fertilization (dpf) are highly resistant to cyanide, becoming progressively more sensitive thereafter. Unbiased analysis of gene expression in response to several hours of ultimately lethal doses of cyanide in both 1 and 7 dpf zebrafish revealed modest changes in iron-related proteins associated with the age-dependent cyanide resistance. Metabolomics measurements demonstrated significant age-dependent differences in energy metabolism during cyanide exposure which prompted us to test modulators of the tricarboxylic acid cycle and related metabolic processes as potential antidotes. In cyanide-sensitive 7 dpf larvae, we identified several such compounds that offer significant protection against cyanide toxicity. Modulators of the pyruvate dehydrogenase complex, as well as the small molecule sodium glyoxylate, consistently protected against cyanide toxicity in 7 dpf zebrafish larvae. Together, our results indicate that the resistance of zebrafish embryos to cyanide toxicity during early development is related to an altered regulation of cellular metabolism, which we propose may be exploited as a potential target for the development of novel antidotes against cyanide poisoning.

Spectroscopic observation of SN2017gkk by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Onori, F.; Benetti, S.; Cappellaro, E.; Losada, Illa R.; Gafton, E.; NUTS Collaboration

2017-09-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of supernova SN2017gkk (=MASTER OT J091344.71762842.5) in host galaxy NGC 2748.

Spectroscopic observation of ASASSN-17he by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Kostrzewa-Rutkowska, Z.; Benetti, S.; Dong, S.; Stritzinger, M.; Stanek, K.; Brimacombe, J.; Sagues, A.; Galindo, P.; Losada, I. Rivero

2017-10-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ASASSN-17he. The candidate was discovered by by the All-Sky Automated Survey for Supernovae.

Lifting the Differentiation Embargo.

PubMed

Latif, Anne-Louise; Holyoake, Tessa L

2016-09-22

Effective differentiation therapy for acute myeloid leukemia (AML) has been restricted to a small subset of patients with one defined genetic abnormality. Using an unbiased small molecule screen, Sykes et al. now identify a mechanism of de-repression of differentiation in several models of AML driven by distinct genetic drivers. Copyright © 2016 Elsevier Inc. All rights reserved.

A Test-Length Correction to the Estimation of Extreme Proficiency Levels

ERIC Educational Resources Information Center

Magis, David; Beland, Sebastien; Raiche, Gilles

2011-01-01

In this study, the estimation of extremely large or extremely small proficiency levels, given the item parameters of a logistic item response model, is investigated. On one hand, the estimation of proficiency levels by maximum likelihood (ML), despite being asymptotically unbiased, may yield infinite estimates. On the other hand, with an…

Bayesian whole-genome prediction and genome-wide association analysis with missing genotypes using variable selection

USDA-ARS?s Scientific Manuscript database

Single-step Genomic Best Linear Unbiased Predictor (ssGBLUP) has become increasingly popular for whole-genome prediction (WGP) modeling as it utilizes any available pedigree and phenotypes on both genotyped and non-genotyped individuals. The WGP accuracy of ssGBLUP has been demonstrated to be greate...

Category-Based Errors and the Accessibility of Unbiased Spatial Memories: A Retrieval Model

ERIC Educational Resources Information Center

Sampaio, Cristina; Wang, Ranxiao Frances

2009-01-01

Studies have consistently shown a spatial memory bias such that a target location is remembered toward the prototypical location of the region to which the target belongs, indicating a blending between the target's specific information and the generic information of its region. The authors investigated whether people retain a veridical…

Gene–Environment Correlation: Difficulties and a Natural Experiment–Based Strategy

PubMed Central

Li, Jiang; Liu, Hexuan; Guo, Guang

2013-01-01

Objectives. We explored how gene–environment correlations can result in endogenous models, how natural experiments can protect against this threat, and if unbiased estimates from natural experiments are generalizable to other contexts. Methods. We compared a natural experiment, the College Roommate Study, which measured genes and behaviors of college students and their randomly assigned roommates in a southern public university, with observational data from the National Longitudinal Study of Adolescent Health in 2008. We predicted exposure to exercising peers using genetic markers and estimated environmental effects on alcohol consumption. A mixed-linear model estimated an alcohol consumption variance that was attributable to genetic markers and across peer environments. Results. Peer exercise environment was associated with respondent genotype in observational data, but not in the natural experiment. The effects of peer drinking and presence of a general gene–environment interaction were similar between data sets. Conclusions. Natural experiments, like random roommate assignment, could protect against potential bias introduced by gene–environment correlations. When combined with representative observational data, unbiased and generalizable causal effects could be estimated. PMID:23927502

Spectroscopic classification of Gaia18adv by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Gall, C.; Benetti, S.; Wyrzykowski, L.; Stritzinger, M.; Holmbo, S.; Dong, S.; Siltala, Lauri; NUTS Collaboration

2018-01-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) collaboration reports the spectroscopic classification of Gaia18adv (SN2018hh) near the host galaxy SDSS J121341.37+282640.0.

Unbiased split variable selection for random survival forests using maximally selected rank statistics.

PubMed

Wright, Marvin N; Dankowski, Theresa; Ziegler, Andreas

2017-04-15

The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption may not always be fulfilled. An alternative approach for survival prediction is random forests for survival outcomes. The standard split criterion for random survival forests is the log-rank test statistic, which favors splitting variables with many possible split points. Conditional inference forests avoid this split variable selection bias. However, linear rank statistics are utilized by default in conditional inference forests to select the optimal splitting variable, which cannot detect non-linear effects in the independent variables. An alternative is to use maximally selected rank statistics for the split point selection. As in conditional inference forests, splitting variables are compared on the p-value scale. However, instead of the conditional Monte-Carlo approach used in conditional inference forests, p-value approximations are employed. We describe several p-value approximations and the implementation of the proposed random forest approach. A simulation study demonstrates that unbiased split variable selection is possible. However, there is a trade-off between unbiased split variable selection and runtime. In benchmark studies of prediction performance on simulated and real datasets, the new method performs better than random survival forests if informative dichotomous variables are combined with uninformative variables with more categories and better than conditional inference forests if non-linear covariate effects are included. In a runtime comparison, the method proves to be computationally faster than both alternatives, if a simple p-value approximation is used. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Express path analysis identifies a tyrosine kinase Src-centric network regulating divergent host responses to Mycobacterium tuberculosis infection.

PubMed

Karim, Ahmad Faisal; Chandra, Pallavi; Chopra, Aanchal; Siddiqui, Zaved; Bhaskar, Ashima; Singh, Amit; Kumar, Dhiraj

2011-11-18

Global gene expression profiling has emerged as a major tool in understanding complex response patterns of biological systems to perturbations. However, a lack of unbiased analytical approaches has restricted the utility of complex microarray data to gain novel system level insights. Here we report a strategy, express path analysis (EPA), that helps to establish various pathways differentially recruited to achieve specific cellular responses under contrasting environmental conditions in an unbiased manner. The analysis superimposes differentially regulated genes between contrasting environments onto the network of functional protein associations followed by a series of iterative enrichments and network analysis. To test the utility of the approach, we infected THP1 macrophage cells with a virulent Mycobacterium tuberculosis strain (H37Rv) or the attenuated non-virulent strain H37Ra as contrasting perturbations and generated the temporal global expression profiles. EPA of the results provided details of response-specific and time-dependent host molecular network perturbations. Further analysis identified tyrosine kinase Src as the major regulatory hub discriminating the responses between wild-type and attenuated Mtb infection. We were then able to verify this novel role of Src experimentally and show that Src executes its role through regulating two vital antimicrobial processes of the host cells (i.e. autophagy and acidification of phagolysosome). These results bear significant potential for developing novel anti-tuberculosis therapy. We propose that EPA could prove extremely useful in understanding complex cellular responses for a variety of perturbations, including pathogenic infections.

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Urrego-Blanco, Jorge R.; Hunke, Elizabeth C.; Urban, Nathan M.

Here, we implement a variance-based distance metric (D n) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased andmore » can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.« less

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

DOE PAGES

Urrego-Blanco, Jorge R.; Hunke, Elizabeth C.; Urban, Nathan M.; ...

2017-04-01

Here, we implement a variance-based distance metric (D n) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased andmore » can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.« less

The effects of aging on the BTBR mouse model of autism spectrum disorder

PubMed Central

Jasien, Joan M.; Daimon, Caitlin M.; Wang, Rui; Shapiro, Bruce K.; Martin, Bronwen; Maudsley, Stuart

2014-01-01

Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder characterized by alterations in social functioning, communicative abilities, and engagement in repetitive or restrictive behaviors. The process of aging in individuals with autism and related neurodevelopmental disorders is not well understood, despite the fact that the number of individuals with ASD aged 65 and older is projected to increase by over half a million individuals in the next 20 years. To elucidate the effects of aging in the context of a modified central nervous system, we investigated the effects of age on the BTBR T + tf/j mouse, a well characterized and widely used mouse model that displays an ASD-like phenotype. We found that a reduction in social behavior persists into old age in male BTBR T + tf/j mice. We employed quantitative proteomics to discover potential alterations in signaling systems that could regulate aging in the BTBR mice. Unbiased proteomic analysis of hippocampal and cortical tissue of BTBR mice compared to age-matched wild-type controls revealed a significant decrease in brain derived neurotrophic factor and significant increases in multiple synaptic markers (spinophilin, Synapsin I, PSD 95, NeuN), as well as distinct changes in functional pathways related to these proteins, including “Neural synaptic plasticity regulation” and “Neurotransmitter secretion regulation.” Taken together, these results contribute to our understanding of the effects of aging on an ASD-like mouse model in regards to both behavior and protein alterations, though additional studies are needed to fully understand the complex interplay underlying aging in mouse models displaying an ASD-like phenotype. PMID:25225482

Genotype-based association models of complex diseases to detect gene-gene and gene-environment interactions.

PubMed

Lobach, Iryna; Fan, Ruzong; Manga, Prashiela

A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.

Motor activity as an unbiased variable to assess anaphylaxis in allergic rats

PubMed Central

Abril-Gil, Mar; Garcia-Just, Alba; Cambras, Trinitat; Pérez-Cano, Francisco J; Castellote, Cristina; Franch, Àngels

2015-01-01

The release of mediators by mast cells triggers allergic symptoms involving various physiological systems and, in the most severe cases, the development of anaphylactic shock compromising mainly the nervous and cardiovascular systems. We aimed to establish variables to objectively study the anaphylactic response (AR) after an oral challenge in an allergy model. Brown Norway rats were immunized by intraperitoneal injection of ovalbumin with alum and toxin from Bordetella pertussis. Specific immunoglobulin (Ig) E antibodies were developed in immunized animals. Forty days after immunization, the rats were orally challenged with the allergen, and motor activity, body temperature and serum mast cell protease concentration were determined. The anaphylaxis induced a reduction in body temperature and a decrease in the number of animal movements, which was inversely correlated with serum mast cell protease release. In summary, motor activity is a reliable tool for assessing AR and also an unbiased method for screening new anti-allergic drugs. PMID:25716015

On the degrees of freedom of reduced-rank estimators in multivariate regression

PubMed Central

Mukherjee, A.; Chen, K.; Wang, N.; Zhu, J.

2015-01-01

Summary We study the effective degrees of freedom of a general class of reduced-rank estimators for multivariate regression in the framework of Stein's unbiased risk estimation. A finite-sample exact unbiased estimator is derived that admits a closed-form expression in terms of the thresholded singular values of the least-squares solution and hence is readily computable. The results continue to hold in the high-dimensional setting where both the predictor and the response dimensions may be larger than the sample size. The derived analytical form facilitates the investigation of theoretical properties and provides new insights into the empirical behaviour of the degrees of freedom. In particular, we examine the differences and connections between the proposed estimator and a commonly-used naive estimator. The use of the proposed estimator leads to efficient and accurate prediction risk estimation and model selection, as demonstrated by simulation studies and a data example. PMID:26702155

Directed current in the Holstein system.

PubMed

Hennig, D; Burbanks, A D; Osbaldestin, A H

2011-03-01

We propose a mechanism to rectify charge transport in the semiclassical Holstein model. It is shown that localized initial conditions associated with a polaron solution, in conjunction with static electron on-site potential not having inversion symmetry, constitute minimal prerequisites for the emergence of a directed current in the underlying periodic lattice system. In particular, we demonstrate that for unbiased spatially localized initial conditions (constituted by kicked static polaron states), violation of parity prevents the existence of pairs of counterpropagating trajectories, thus allowing for a directed current despite the time reversibility of the equations of motion. Nevertheless, propagating polaron solutions associated with sets of unbiased localized initial conditions which eventually leave the region of localized initial conditions do not exhibit time reversibility. Since the initial conditions belonging to the corresponding counterpropagating, current-compensating polaron solutions are not contained in the set, this gives rise to the emergence of a current. Occurrence of long-range coherent charge transport is demonstrated.

The Swift GRB Host Galaxy Legacy Survey

NASA Astrophysics Data System (ADS)

Perley, Daniel A.

2015-01-01

I introduce the Swift Host Galaxy Legacy Survey (SHOALS), a comprehensive multiwavelength program to characterize the demographics of the GRB host population across its entire redshift range. Using unbiased selection criteria we have designated a subset of 130 Swift gamma-ray bursts which are now being targeted with intensive observational follow-up. Deep Spitzer imaging of every field has already been obtained and analyzed, with major programs ongoing at Keck, GTC, and Gemini to obtain complementary optical/NIR photometry to enable full SED modeling and derivation of fundamental physical parameters such as mass, extinction, and star-formation rate. Using these data I will present an unbiased measurement of the GRB host-galaxy luminosity and mass functions and their evolution with redshift between z=0 and z=5, compare GRB hosts to other star-forming galaxy populations, and discuss implications for the nature of the GRB progenitor and the ability of GRBs to probe cosmic star-formation.

Sodium Binding Sites and Permeation Mechanism in the NaChBac Channel: A Molecular Dynamics Study.

PubMed

Guardiani, Carlo; Rodger, P Mark; Fedorenko, Olena A; Roberts, Stephen K; Khovanov, Igor A

2017-03-14

NaChBac was the first discovered bacterial sodium voltage-dependent channel, yet computational studies are still limited due to the lack of a crystal structure. In this work, a pore-only construct built using the NavMs template was investigated using unbiased molecular dynamics and metadynamics. The potential of mean force (PMF) from the unbiased run features four minima, three of which correspond to sites IN, CEN, and HFS discovered in NavAb. During the run, the selectivity filter (SF) is spontaneously occupied by two ions, and frequent access of a third one is often observed. In the innermost sites IN and CEN, Na + is fully hydrated by six water molecules and occupies an on-axis position. In site HFS sodium interacts with a glutamate and a serine from the same subunit and is forced to adopt an off-axis placement. Metadynamics simulations biasing one and two ions show an energy barrier in the SF that prevents single-ion permeation. An analysis of the permeation mechanism was performed both computing minimum energy paths in the axial-axial PMF and through a combination of Markov state modeling and transition path theory. Both approaches reveal a knock-on mechanism involving at least two but possibly three ions. The currents predicted from the unbiased simulation using linear response theory are in excellent agreement with single-channel patch-clamp recordings.

Updated biological roles for matrix metalloproteinases and new "intracellular" substrates revealed by degradomics.

PubMed

Butler, Georgina S; Overall, Christopher M

2009-11-24

Shotgun proteomics techniques are conceptually unbiased, but data interpretation and follow-up experiments are often constrained by dogma, established beliefs that are accepted without question, that can dilute the power of proteomics and hinder scientific progress. Proteomics and degradomics, the characterization of all proteases, inhibitors, and protease substrates by genomic and proteomic techniques, have exponentially expanded the known substrate repertoire of the matrix metalloproteinases (MMPs), even to include intracellular proteins with newly recognized extracellular functions. Thus, the dogma that MMPs are dowdy degraders of extracellular matrix has been resolutely overturned, and the metamorphosis of MMPs into modulators of multiple signaling pathways has been facilitated. Here we review progress made in the field of degradomics and present a current view of the MMP degradome.

Coco is a dual activity modulator of TGFβ signaling

PubMed Central

Deglincerti, Alessia; Haremaki, Tomomi; Warmflash, Aryeh; Sorre, Benoit; Brivanlou, Ali H.

2015-01-01

The TGFβ signaling pathway is a crucial regulator of developmental processes and disease. The activity of TGFβ ligands is modulated by various families of soluble inhibitors that interfere with the interactions between ligands and receptors. In an unbiased, genome-wide RNAi screen to identify genes involved in ligand-dependent signaling, we unexpectedly identified the BMP/Activin/Nodal inhibitor Coco as an enhancer of TGFβ1 signaling. Coco synergizes with TGFβ1 in both cell culture and Xenopus explants. Molecularly, Coco binds to TGFβ1 and enhances TGFβ1 binding to its receptor Alk5. Thus, Coco acts as both an inhibitor and an enhancer of signaling depending on the ligand it binds. This finding raises the need for a global reconsideration of the molecular mechanisms regulating TGFβ signaling. PMID:26116664

Summary Diagrams for Coupled Hydrodynamic-Ecosystem Model Skill Assessment

DTIC Science & Technology

2009-01-01

reference point have the smallest unbiased RMSD value (Fig. 3). It would appear that the cluster of model points closest to the reference point may...total RMSD values. This is particularly the case for phyto- plankton absorption (Fig. 3B) where the cluster of points closest to the reference...pattern statistics and the bias (difference of mean values) each magnitude of the total Root-Mean-Square Difference ( RMSD ). An alternative skill score and

Spectroscopic classification of supernovae SN 2018aei and SN 2018aej by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Cannizzaro, G.; Kuncarayakti, H.; Fraser, M.; Hamanowicz, A.; Jonker, P.; Kankare, E.; Kostrzewa-Rutkowska, Z.; Onori, F.; Wevers, T.; Wyrzykowski, L.; Galbany, L.

2018-03-01

The NOT Unbiased Transient Survey (NUTS; ATel #8992) collaboration reports the spectroscopic classification of supernovae SN 2018aei and SN 2018aej, discovered by PanSTARSS Survey for Transients (ATel #11408).

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen

Here, we propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator–coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

DOE PAGES

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen; ...

2018-03-12

Here, we propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator–coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Reconfigurable generation and measurement of mutually unbiased bases for time-bin qudits

NASA Astrophysics Data System (ADS)

Lukens, Joseph M.; Islam, Nurul T.; Lim, Charles Ci Wen; Gauthier, Daniel J.

2018-03-01

We propose a method for implementing mutually unbiased generation and measurement of time-bin qudits using a cascade of electro-optic phase modulator-coded fiber Bragg grating pairs. Our approach requires only a single spatial mode and can switch rapidly between basis choices. We obtain explicit solutions for dimensions d = 2, 3, and 4 that realize all d + 1 possible mutually unbiased bases and analyze the performance of our approach in quantum key distribution. Given its practicality and compatibility with current technology, our approach provides a promising springboard for scalable processing of high-dimensional time-bin states.

Examinations of tRNA Range of Motion Using Simulations of Cryo-EM Microscopy and X-Ray Data.

PubMed

Caulfield, Thomas R; Devkota, Batsal; Rollins, Geoffrey C

2011-01-01

We examined tRNA flexibility using a combination of steered and unbiased molecular dynamics simulations. Using Maxwell's demon algorithm, molecular dynamics was used to steer X-ray structure data toward that from an alternative state obtained from cryogenic-electron microscopy density maps. Thus, we were able to fit X-ray structures of tRNA onto cryogenic-electron microscopy density maps for hybrid states of tRNA. Additionally, we employed both Maxwell's demon molecular dynamics simulations and unbiased simulation methods to identify possible ribosome-tRNA contact areas where the ribosome may discriminate tRNAs during translation. Herein, we collected >500 ns of simulation data to assess the global range of motion for tRNAs. Biased simulations can be used to steer between known conformational stop points, while unbiased simulations allow for a general testing of conformational space previously unexplored. The unbiased molecular dynamics data describes the global conformational changes of tRNA on a sub-microsecond time scale for comparison with steered data. Additionally, the unbiased molecular dynamics data was used to identify putative contacts between tRNA and the ribosome during the accommodation step of translation. We found that the primary contact regions were H71 and H92 of the 50S subunit and ribosomal proteins L14 and L16.

Initial Correction versus Negative Marking in Multiple Choice Examinations

ERIC Educational Resources Information Center

Van Hecke, Tanja

2015-01-01

Optimal assessment tools should measure in a limited time the knowledge of students in a correct and unbiased way. A method for automating the scoring is multiple choice scoring. This article compares scoring methods from a probabilistic point of view by modelling the probability to pass: the number right scoring, the initial correction (IC) and…

Ethnic Group Bias in Intelligence Test Items.

ERIC Educational Resources Information Center

Scheuneman, Janice

In previous studies of ethnic group bias in intelligence test items, the question of bias has been confounded with ability differences between the ethnic group samples compared. The present study is based on a conditional probability model in which an unbiased item is defined as one where the probability of a correct response to an item is the…

Chemical & Biological Point Detection Decontamination

DTIC Science & Technology

2002-04-01

high priority in biological defense. Research on multivalent assays is also ongoing. Biased libraries, generated from immunized animals, or unbiased ...2003 TBD decontamination and modeling and simulation I I The Chem-Bio Point Detection Roadmap The summary level updated and expanded Bio Point... Molecular Imprinted Polymer Sensor, Dendrimer-based Antibody Assays, Pyrolysis-GC-ion mobility spectrometry, and surface enhanced Raman spectroscopy. Data

Cannabinoid transmission in the prelimbic cortex bidirectionally controls opiate reward and aversion signaling through dissociable kappa versus μ-opiate receptor dependent mechanisms.

PubMed

Ahmad, Tasha; Lauzon, Nicole M; de Jaeger, Xavier; Laviolette, Steven R

2013-09-25

Cannabinoid, dopamine (DA), and opiate receptor pathways play integrative roles in emotional learning, associative memory, and sensory perception. Modulation of cannabinoid CB1 receptor transmission within the medial prefrontal cortex (mPFC) regulates the emotional valence of both rewarding and aversive experiences. Furthermore, CB1 receptor substrates functionally interact with opiate-related motivational processing circuits, particularly in the context of reward-related learning and memory. Considerable evidence demonstrates functional interactions between CB1 and DA signaling pathways during the processing of motivationally salient information. However, the role of mPFC CB1 receptor transmission in the modulation of behavioral opiate-reward processing is not currently known. Using an unbiased conditioned place preference paradigm with rats, we examined the role of intra-mPFC CB1 transmission during opiate reward learning. We report that activation or inhibition of CB1 transmission within the prelimbic cortical (PLC) division of the mPFC bidirectionally regulates the motivational valence of opiates; whereas CB1 activation switched morphine reward signaling into an aversive stimulus, blockade of CB1 transmission potentiated the rewarding properties of normally sub-reward threshold conditioning doses of morphine. Both of these effects were dependent upon DA transmission as systemic blockade of DAergic transmission prevented CB1-dependent modulation of morphine reward and aversion behaviors. We further report that CB1-mediated intra-PLC opiate motivational signaling is mediated through a μ-opiate receptor-dependent reward pathway, or a κ-opiate receptor-dependent aversion pathway, directly within the ventral tegmental area. Our results provide evidence for a novel CB1-mediated motivational valence switching mechanism within the PLC, controlling dissociable subcortical reward and aversion pathways.

On using scatterometer and altimeter data to improve storm surge forecasting in the Adriatic Sea

NASA Astrophysics Data System (ADS)

Bajo, Marco; Umgiesser, Georg; De Biasio, Francesco; Vignudelli, Stefano; Zecchetto, Stefano

2017-04-01

Satellite data are seldom used in storm surge forecasting. Among the most important issues related to the storm surge forecasting are the quality of the model wind forcing and the initial condition of the sea surface elevation. In this work, focused on storm surge forecasting in the Adriatic Sea, satellite scatterometer wind data are used to correct the wind speed and direction biases of the ECMWF global atmospheric model by tuning the spatial fields, as an alternative to data assimilation. The capability of such an unbiased wind is tested against that of a high resolution wind, produced by a regional non-hydrostatic model. On the other hand, altimeter Total Water Level Envelope (TWLE) data, which provide the sea level elevation, are used to improve the accuracy of the initial state of the model simulations. This is done by assimilating into a storm surge model the TWLE obtained by the altimeter observations along ground tracks, after subtraction of the tidal components. In order to test the methodology, eleven storm surge events recorded in Venice, from 2008 to 2012, have been simulated using different configurations of forcing wind and altimeter data assimilation. Results show that the relative error on the estimation of the maximum surge peak, averaged over the cases considered, decreases from 13% to 7% using both the unbiased wind and the altimeter data assimilation, while forcing the hydrodynamic model with the high resolution wind (no tuning), the altimeter data assimilation reduces the error from 9% to 6%.

Spectroscopic observation of SN 2017jzp and SN 2018bf by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Kuncarayakti, H.; Mattila, S.; Kotak, R.; Harmanen, J.; Reynolds, T.; Wyrzykowski, L.; Stritzinger, M.; Onori, F.; Somero, A.; Kangas, T.; Lundqvist, P.; Taddia, F.; Ergon, M.

2018-01-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of SNe 2017jzp and 2018bf in host galaxies KUG 1326+679 and SDSS J225746.53+253833.5, respectively.

Spectroscopic observation of ASASSN-17nb and CSS170922:172546+342249 by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Harmanen, J.; Mattila, S.; Kuncarayakti, H.; Reynolds, T.; Somero, A.; Kangas, T.; Lundqvist, P.; Taddia, F.; Ergon, M.; Dong, S.; Pastorello, A.; Pursimo, T.; NUTS Collaboration

2017-10-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ASASSN-17nb in MCG+06-17-007 and CSS170922:172546+342249 in an unknown host galaxy.

Losing the rose tinted glasses: neural substrates of unbiased belief updating in depression

PubMed Central

Garrett, Neil; Sharot, Tali; Faulkner, Paul; Korn, Christoph W.; Roiser, Jonathan P.; Dolan, Raymond J.

2014-01-01

Recent evidence suggests that a state of good mental health is associated with biased processing of information that supports a positively skewed view of the future. Depression, on the other hand, is associated with unbiased processing of such information. Here, we use brain imaging in conjunction with a belief update task administered to clinically depressed patients and healthy controls to characterize brain activity that supports unbiased belief updating in clinically depressed individuals. Our results reveal that unbiased belief updating in depression is mediated by strong neural coding of estimation errors in response to both good news (in left inferior frontal gyrus and bilateral superior frontal gyrus) and bad news (in right inferior parietal lobule and right inferior frontal gyrus) regarding the future. In contrast, intact mental health was linked to a relatively attenuated neural coding of bad news about the future. These findings identify a neural substrate mediating the breakdown of biased updating in major depression disorder, which may be essential for mental health. PMID:25221492

Allowable SEM noise for unbiased LER measurement

NASA Astrophysics Data System (ADS)

Papavieros, George; Constantoudis, Vassilios; Gogolides, Evangelos

2018-03-01

Recently, a novel method for the calculation of unbiased Line Edge Roughness based on Power Spectral Density analysis has been proposed. In this paper first an alternative method is discussed and investigated, utilizing the Height-Height Correlation Function (HHCF) of edges. The HHCF-based method enables the unbiased determination of the whole triplet of LER parameters including besides rms the correlation length and roughness exponent. The key of both methods is the sensitivity of PSD and HHCF on noise at high frequencies and short distance respectively. Secondly, we elaborate a testbed of synthesized SEM images with controlled LER and noise to justify the effectiveness of the proposed unbiased methods. Our main objective is to find out the boundaries of the method in respect to noise levels and roughness characteristics, for which the method remains reliable, i.e the maximum amount of noise allowed, for which the output results cope with the controllable known inputs. At the same time, we will also set the extremes of roughness parameters for which the methods hold their accuracy.

Conformational transition in signal transduction: metastable states and transition pathways in the activation of a signaling protein.

PubMed

Banerjee, Rahul; Yan, Honggao; Cukier, Robert I

2015-06-04

Signal transduction is of vital importance to the growth and adaptation of living organisms. The key to understand mechanisms of biological signal transduction is elucidation of the conformational dynamics of its signaling proteins, as the activation of a signaling protein is fundamentally a process of conformational transition from an inactive to an active state. A predominant form of signal transduction for bacterial sensing of environmental changes in the wild or inside their hosts is a variety of two-component systems, in which the conformational transition of a response regulator (RR) from an inactive to an active state initiates responses to the environmental changes. Here, RR activation has been investigated using RR468 as a model system by extensive unbiased all-atom molecular dynamics (MD) simulations in explicit solvent, starting from snapshots along a targeted MD trajectory that covers the conformational transition. Markov state modeling, transition path theory, and geometric analyses of the wealth of the MD data have provided a comprehensive description of the RR activation. It involves a network of metastable states, with one metastable state essentially the same as the inactive state and another very similar to the active state that are connected via a small set of intermediates. Five major pathways account for >75% of the fluxes of the conformational transition from the inactive to the active-like state. The thermodynamic stability of the states and the activation barriers between states are found, to identify rate-limiting steps. The conformal transition is initiated predominantly by movements of the β3α3 loop, followed by movements of the β4α4-loop and neighboring α4 helix region, and capped by additional movements of the β3α3 loop. A number of transient hydrophobic and hydrogen bond interactions are revealed, and they may be important for the conformational transition.

Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

NASA Astrophysics Data System (ADS)

Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

2018-04-01

A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.

A genome-wide loss-of-function screen identifies SLC26A2 as a novel mediator of TRAIL resistance

PubMed Central

Dimberg, Lina Y.; Towers, Christina G.; Behbakht, Kian; Hotz, Taylor J.; Kim, Jihye; Fosmire, Susan; Porter, Christopher C.; Tan, Aik-Choon; Thorburn, Andrew; Ford, Heide L.

2017-01-01

TNF-related apoptosis inducing ligand (TRAIL) is a potent death-inducing ligand that mediates apoptosis through the extrinsic pathway and serves as an important endogenous tumor suppressor mechanism. Because tumor cells are often killed by TRAIL and normal cells are not, drugs that activate the TRAIL pathway have been thought to have potential clinical value. However, to date, most TRAIL-related clinical trials have largely failed due to the tumor cells having intrinsic or acquired resistance to TRAIL-induced apoptosis. Previous studies to identify resistance mechanisms have focused on targeted analysis of the canonical apoptosis pathway and other known regulators of TRAIL receptor signaling. To identify novel mechanisms of TRAIL resistance in an unbiased way, we performed a genome wide shRNA screen for genes that regulate TRAIL sensitivity in sub-lines that had been selected for acquired TRAIL resistance. This screen identified previously unknown mediators of TRAIL resistance including Angiotensin II Receptor 2, Crk-like protein, T-Box Transcription Factor 2 and solute carrier family 26 member 2 (SLC26A2). SLC26A2 downregulates the TRAIL receptors, DR4 and DR5, and this downregulation is associated with resistance to TRAIL. Its expression is high in numerous tumor types compared to normal cells, and in breast cancer, SLC26A2 is associated with a significant decrease in relapse free survival. PMID:28108622

Activity screening of carrier domains within nonribosomal peptide synthetases using complex substrate mixtures and large molecule mass spectrometry.

PubMed

Dorrestein, Pieter C; Blackhall, Jonathan; Straight, Paul D; Fischbach, Michael A; Garneau-Tsodikova, Sylvie; Edwards, Daniel J; McLaughlin, Shaun; Lin, Myat; Gerwick, William H; Kolter, Roberto; Walsh, Christopher T; Kelleher, Neil L

2006-02-14

For screening a pool of potential substrates that load carrier domains found in nonribosomal peptide synthetases, large molecule mass spectrometry is shown to be a new, unbiased assay. Combining the high resolving power of Fourier transform mass spectrometry with the ability of adenylation domains to select their own substrates, the mass change that takes place upon formation of a covalent intermediate thus identifies the substrate. This assay has an advantage over traditional radiochemical assays in that many substrates, the substrate pool, can be screened simultaneously. Using proteins on the nikkomycin, clorobiocin, coumermycin A1, yersiniabactin, pyochelin, and enterobactin biosynthetic pathways as proof of principle, preferred substrates are readily identified from substrate pools. Furthermore, this assay can be used to provide insight into the timing of tailoring events of biosynthetic pathways as demonstrated using the bromination reaction found on the jamaicamide biosynthetic pathway. Finally, this assay can provide insight into the role and function of orphan gene clusters for which the encoded natural product is unknown. This is demonstrated by identifying the substrates for two NRPS modules from the pksN and pksJ genes that are found on an orphan NRPS/PKS hybrid cluster from Bacillus subtilis. This new assay format is especially timely for activity screening in an era when new types of thiotemplate assembly lines that defy classification are being discovered at an accelerating rate.

ALDH2 protects against stroke by clearing 4-HNE

PubMed Central

Guo, Jin-Min; Liu, Ai-Jun; Zang, Pu; Dong, Wen-Zhe; Ying, Li; Wang, Wei; Xu, Pu; Song, Xu-Rui; Cai, Jun; Zhang, She-Qing; Duan, Jun-Li; Mehta, Jawahar L; Su, Ding-Feng

2013-01-01

Aldehyde dehydrogenase 2 (ALDH2) is a mitochondrial enzyme that metabolizes ethanol and toxic aldehydes such as 4-hydroxy-2-nonenal (4-HNE). Using an unbiased proteomic search, we identified ALDH2 deficiency in stroke-prone spontaneously hypertensive rats (SHR-SP) as compared with spontaneously hypertensive rats (SHR). We concluded the causative role of ALDH2 deficiency in neuronal injury as overexpression or activation of ALDH2 conferred neuroprotection by clearing 4-HNE in in vitro studies. Further, ALDH2-knockdown rats revealed the absence of neuroprotective effects of PKCε. Moderate ethanol administration that is known to exert protection against stroke was shown to enhance the detoxification of 4-HNE, and to protect against ischemic cerebral injury through the PKCε-ALDH2 pathway. In SHR-SP, serum 4-HNE level was persistently elevated and correlated inversely with the lifespan. The role of 4-HNE in stroke in humans was also suggested by persistent elevation of its plasma levels for at least 6 months after stroke. Lastly, we observed that 21 of 1 242 subjects followed for 8 years who developed stroke had higher initial plasma 4-HNE levels than those who did not develop stroke. These findings suggest that activation of the ALDH2 pathway may serve as a useful index in the identification of stroke-prone subjects, and the ALDH2 pathway may be a potential target of therapeutic intervention in stroke. PMID:23689279

Systems view of adipogenesis via novel omics-driven and tissue-specific activity scoring of network functional modules

NASA Astrophysics Data System (ADS)

Nassiri, Isar; Lombardo, Rosario; Lauria, Mario; Morine, Melissa J.; Moyseos, Petros; Varma, Vijayalakshmi; Nolen, Greg T.; Knox, Bridgett; Sloper, Daniel; Kaput, Jim; Priami, Corrado

2016-07-01

The investigation of the complex processes involved in cellular differentiation must be based on unbiased, high throughput data processing methods to identify relevant biological pathways. A number of bioinformatics tools are available that can generate lists of pathways ranked by statistical significance (i.e. by p-value), while ideally it would be desirable to functionally score the pathways relative to each other or to other interacting parts of the system or process. We describe a new computational method (Network Activity Score Finder - NASFinder) to identify tissue-specific, omics-determined sub-networks and the connections with their upstream regulator receptors to obtain a systems view of the differentiation of human adipocytes. Adipogenesis of human SBGS pre-adipocyte cells in vitro was monitored with a transcriptomic data set comprising six time points (0, 6, 48, 96, 192, 384 hours). To elucidate the mechanisms of adipogenesis, NASFinder was used to perform time-point analysis by comparing each time point against the control (0 h) and time-lapse analysis by comparing each time point with the previous one. NASFinder identified the coordinated activity of seemingly unrelated processes between each comparison, providing the first systems view of adipogenesis in culture. NASFinder has been implemented into a web-based, freely available resource associated with novel, easy to read visualization of omics data sets and network modules.

The Mediator complex of Caenorhabditis elegans: insights into the developmental and physiological roles of a conserved transcriptional coregulator.

PubMed

Grants, Jennifer M; Goh, Grace Y S; Taubert, Stefan

2015-02-27

The Mediator multiprotein complex ('Mediator') is an important transcriptional coregulator that is evolutionarily conserved throughout eukaryotes. Although some Mediator subunits are essential for the transcription of all protein-coding genes, others influence the expression of only subsets of genes and participate selectively in cellular signaling pathways. Here, we review the current knowledge of Mediator subunit function in the nematode Caenorhabditis elegans, a metazoan in which established and emerging genetic technologies facilitate the study of developmental and physiological regulation in vivo. In this nematode, unbiased genetic screens have revealed critical roles for Mediator components in core developmental pathways such as epidermal growth factor (EGF) and Wnt/β-catenin signaling. More recently, important roles for C. elegans Mediator subunits have emerged in the regulation of lipid metabolism and of systemic stress responses, engaging conserved transcription factors such as nuclear hormone receptors (NHRs). We emphasize instances where similar functions for individual Mediator subunits exist in mammals, highlighting parallels between Mediator subunit action in nematode development and in human cancer biology. We also discuss a parallel between the association of the Mediator subunit MED12 with several human disorders and the role of its C. elegans ortholog mdt-12 as a regulatory hub that interacts with numerous signaling pathways. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Neutral sphingomyelinase (SMPD3) deficiency disrupts the Golgi secretory pathway and causes growth inhibition

PubMed Central

Stoffel, Wilhelm; Hammels, Ina; Jenke, Bitta; Binczek, Erika; Schmidt-Soltau, Inga; Brodesser, Susanne; Schauss, Astrid; Etich, Julia; Heilig, Juliane; Zaucke, Frank

2016-01-01

Systemic loss of neutral sphingomyelinase (SMPD3) in mice leads to a novel form of systemic, juvenile hypoplasia (dwarfism). SMPD3 deficiency in mainly two growth regulating cell types contributes to the phenotype, in chondrocytes of skeletal growth zones to skeletal malformation and chondrodysplasia, and in hypothalamic neurosecretory neurons to systemic hypothalamus–pituitary–somatotropic hypoplasia. The unbiased smpd3−/− mouse mutant and derived smpd3−/− primary chondrocytes were instrumental in defining the enigmatic role underlying the systemic and cell autonomous role of SMPD3 in the Golgi compartment. Here we describe the unprecedented role of SMPD3. SMPD3 deficiency disrupts homeostasis of sphingomyelin (SM), ceramide (Cer) and diacylglycerol (DAG) in the Golgi SMPD3-SMS1 (SM-synthase1) cycle. Cer and DAG, two fusogenic intermediates, modify the membrane lipid bilayer for the initiation of vesicle formation and transport. Dysproteostasis, unfolded protein response, endoplasmic reticulum stress and apoptosis perturb the Golgi secretory pathway in the smpd3−/− mouse. Secretion of extracellular matrix proteins is arrested in chondrocytes and causes skeletal malformation and chondrodysplasia. Similarly, retarded secretion of proteo-hormones in hypothalamic neurosecretory neurons leads to hypothalamus induced combined pituitary hormone deficiency. SMPD3 in the regulation of the protein vesicular secretory pathway may become a diagnostic target in the etiology of unknown forms of juvenile growth and developmental inhibition. PMID:27882938

Neutral sphingomyelinase (SMPD3) deficiency disrupts the Golgi secretory pathway and causes growth inhibition.

PubMed

Stoffel, Wilhelm; Hammels, Ina; Jenke, Bitta; Binczek, Erika; Schmidt-Soltau, Inga; Brodesser, Susanne; Schauss, Astrid; Etich, Julia; Heilig, Juliane; Zaucke, Frank

2016-11-24

Systemic loss of neutral sphingomyelinase (SMPD3) in mice leads to a novel form of systemic, juvenile hypoplasia (dwarfism). SMPD3 deficiency in mainly two growth regulating cell types contributes to the phenotype, in chondrocytes of skeletal growth zones to skeletal malformation and chondrodysplasia, and in hypothalamic neurosecretory neurons to systemic hypothalamus-pituitary-somatotropic hypoplasia. The unbiased smpd3-/- mouse mutant and derived smpd3-/- primary chondrocytes were instrumental in defining the enigmatic role underlying the systemic and cell autonomous role of SMPD3 in the Golgi compartment. Here we describe the unprecedented role of SMPD3. SMPD3 deficiency disrupts homeostasis of sphingomyelin (SM), ceramide (Cer) and diacylglycerol (DAG) in the Golgi SMPD3-SMS1 (SM-synthase1) cycle. Cer and DAG, two fusogenic intermediates, modify the membrane lipid bilayer for the initiation of vesicle formation and transport. Dysproteostasis, unfolded protein response, endoplasmic reticulum stress and apoptosis perturb the Golgi secretory pathway in the smpd3-/- mouse. Secretion of extracellular matrix proteins is arrested in chondrocytes and causes skeletal malformation and chondrodysplasia. Similarly, retarded secretion of proteo-hormones in hypothalamic neurosecretory neurons leads to hypothalamus induced combined pituitary hormone deficiency. SMPD3 in the regulation of the protein vesicular secretory pathway may become a diagnostic target in the etiology of unknown forms of juvenile growth and developmental inhibition.

Systems-wide RNAi analysis of CASP8AP2/FLASH shows transcriptional deregulation of the replication-dependent histone genes and extensive effects on the transcriptome of colorectal cancer cells

PubMed Central

2012-01-01

Background Colorectal carcinomas (CRC) carry massive genetic and transcriptional alterations that influence multiple cellular pathways. The study of proteins whose loss-of-function (LOF) alters the growth of CRC cells can be used to further understand the cellular processes cancer cells depend upon for survival. Results A small-scale RNAi screen of ~400 genes conducted in SW480 CRC cells identified several candidate genes as required for the viability of CRC cells, most prominently CASP8AP2/FLASH. To understand the function of this gene in maintaining the viability of CRC cells in an unbiased manner, we generated gene specific expression profiles following RNAi. Silencing of CASP8AP2/FLASH resulted in altered expression of over 2500 genes enriched for genes associated with cellular growth and proliferation. Loss of CASP8AP2/FLASH function was significantly associated with altered transcription of the genes encoding the replication-dependent histone proteins as a result of the expression of the non-canonical polyA variants of these transcripts. Silencing of CASP8AP2/FLASH also mediated enrichment of changes in the expression of targets of the NFκB and MYC transcription factors. These findings were confirmed by whole transcriptome analysis of CASP8AP2/FLASH silenced cells at multiple time points. Finally, we identified and validated that CASP8AP2/FLASH LOF increases the expression of neurofilament heavy polypeptide (NEFH), a protein recently linked to regulation of the AKT1/ß-catenin pathway. Conclusions We have used unbiased RNAi based approaches to identify and characterize the function of CASP8AP2/FLASH, a protein not previously reported as required for cell survival. This study further defines the role CASP8AP2/FLASH plays in the regulating expression of the replication-dependent histones and shows that its LOF results in broad and reproducible effects on the transcriptome of colorectal cancer cells including the induction of expression of the recently described tumor suppressor gene NEFH. PMID:22216762

Systems-wide RNAi analysis of CASP8AP2/FLASH shows transcriptional deregulation of the replication-dependent histone genes and extensive effects on the transcriptome of colorectal cancer cells.

PubMed

Hummon, Amanda B; Pitt, Jason J; Camps, Jordi; Emons, Georg; Skube, Susan B; Huppi, Konrad; Jones, Tamara L; Beissbarth, Tim; Kramer, Frank; Grade, Marian; Difilippantonio, Michael J; Ried, Thomas; Caplen, Natasha J

2012-01-04

Colorectal carcinomas (CRC) carry massive genetic and transcriptional alterations that influence multiple cellular pathways. The study of proteins whose loss-of-function (LOF) alters the growth of CRC cells can be used to further understand the cellular processes cancer cells depend upon for survival. A small-scale RNAi screen of ~400 genes conducted in SW480 CRC cells identified several candidate genes as required for the viability of CRC cells, most prominently CASP8AP2/FLASH. To understand the function of this gene in maintaining the viability of CRC cells in an unbiased manner, we generated gene specific expression profiles following RNAi. Silencing of CASP8AP2/FLASH resulted in altered expression of over 2500 genes enriched for genes associated with cellular growth and proliferation. Loss of CASP8AP2/FLASH function was significantly associated with altered transcription of the genes encoding the replication-dependent histone proteins as a result of the expression of the non-canonical polyA variants of these transcripts. Silencing of CASP8AP2/FLASH also mediated enrichment of changes in the expression of targets of the NFκB and MYC transcription factors. These findings were confirmed by whole transcriptome analysis of CASP8AP2/FLASH silenced cells at multiple time points. Finally, we identified and validated that CASP8AP2/FLASH LOF increases the expression of neurofilament heavy polypeptide (NEFH), a protein recently linked to regulation of the AKT1/ß-catenin pathway. We have used unbiased RNAi based approaches to identify and characterize the function of CASP8AP2/FLASH, a protein not previously reported as required for cell survival. This study further defines the role CASP8AP2/FLASH plays in the regulating expression of the replication-dependent histones and shows that its LOF results in broad and reproducible effects on the transcriptome of colorectal cancer cells including the induction of expression of the recently described tumor suppressor gene NEFH.

Comprehensive analysis of gene expression patterns in Friedreich's ataxia fibroblasts by RNA sequencing reveals altered levels of protein synthesis factors and solute carriers

PubMed Central

Li, Yanjie; Lu, Yue; Lin, Kevin; Hauser, Lauren A.; Lynch, David R.

2017-01-01

ABSTRACT Friedreich's ataxia (FRDA) is an autosomal recessive neurodegenerative disease usually caused by large homozygous expansions of GAA repeat sequences in intron 1 of the frataxin (FXN) gene. FRDA patients homozygous for GAA expansions have low FXN mRNA and protein levels when compared with heterozygous carriers or healthy controls. Frataxin is a mitochondrial protein involved in iron–sulfur cluster synthesis, and many FRDA phenotypes result from deficiencies in cellular metabolism due to lowered expression of FXN. Presently, there is no effective treatment for FRDA, and biomarkers to measure therapeutic trial outcomes and/or to gauge disease progression are lacking. Peripheral tissues, including blood cells, buccal cells and skin fibroblasts, can readily be isolated from FRDA patients and used to define molecular hallmarks of disease pathogenesis. For instance, FXN mRNA and protein levels as well as FXN GAA-repeat tract lengths are routinely determined using all of these cell types. However, because these tissues are not directly involved in disease pathogenesis, their relevance as models of the molecular aspects of the disease is yet to be decided. Herein, we conducted unbiased RNA sequencing to profile the transcriptomes of fibroblast cell lines derived from 18 FRDA patients and 17 unaffected control individuals. Bioinformatic analyses revealed significantly upregulated expression of genes encoding plasma membrane solute carrier proteins in FRDA fibroblasts. Conversely, the expression of genes encoding accessory factors and enzymes involved in cytoplasmic and mitochondrial protein synthesis was consistently decreased in FRDA fibroblasts. Finally, comparison of genes differentially expressed in FRDA fibroblasts to three previously published gene expression signatures defined for FRDA blood cells showed substantial overlap between the independent datasets, including correspondingly deficient expression of antioxidant defense genes. Together, these results indicate that gene expression profiling of cells derived from peripheral tissues can, in fact, consistently reveal novel molecular pathways of the disease. When performed on statistically meaningful sample group sizes, unbiased global profiling analyses utilizing peripheral tissues are critical for the discovery and validation of FRDA disease biomarkers. PMID:29125828

A New Model for the Estimation of Cell Proliferation Dynamics Using CFSE Data

DTIC Science & Technology

2011-08-20

cells, and hence into the resulting division and death rates . Alternatively, we propose that there is information to be learned not only from...meaningful estimation of population proliferation and death rates in a manner which is unbiased and mechanistically sound. Significantly, this new model is...change in permitting the dependence of the proliferation and death rates (α and β) and the label loss rate (v) on both time t and measured FI x. This

Quantification of birefringence readily measures the level of muscle damage in zebrafish

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berger, Joachim, E-mail: Joachim.Berger@Monash.edu; Sztal, Tamar; Currie, Peter D.

2012-07-13

Highlights: Black-Right-Pointing-Pointer Report of an unbiased quantification of the birefringence of muscle of fish larvae. Black-Right-Pointing-Pointer Quantification method readily identifies level of overall muscle damage. Black-Right-Pointing-Pointer Compare zebrafish muscle mutants for level of phenotype severity. Black-Right-Pointing-Pointer Proposed tool to survey treatments that aim to ameliorate muscular dystrophy. -- Abstract: Muscular dystrophies are a group of genetic disorders that progressively weaken and degenerate muscle. Many zebrafish models for human muscular dystrophies have been generated and analysed, including dystrophin-deficient zebrafish mutants dmd that model Duchenne Muscular Dystrophy. Under polarised light the zebrafish muscle can be detected as a bright area in anmore » otherwise dark background. This light effect, called birefringence, results from the diffraction of polarised light through the pseudo-crystalline array of the muscle sarcomeres. Muscle damage, as seen in zebrafish models for muscular dystrophies, can readily be detected by a reduction in the birefringence. Therefore, birefringence is a very sensitive indicator of overall muscle integrity within larval zebrafish. Unbiased documentation of the birefringence followed by densitometric measurement enables the quantification of the birefringence of zebrafish larvae. Thereby, the overall level of muscle integrity can be detected, allowing the identification and categorisation of zebrafish muscle mutants. In addition, we propose that the establish protocol can be used to analyse treatments aimed at ameliorating dystrophic zebrafish models.« less

Disruption of Protein Processing in the Endoplasmic Reticulum of DYT1 Knock-in Mice Implicates Novel Pathways in Dystonia Pathogenesis.

PubMed

Beauvais, Genevieve; Bode, Nicole M; Watson, Jaime L; Wen, Hsiang; Glenn, Kevin A; Kawano, Hiroyuki; Harata, N Charles; Ehrlich, Michelle E; Gonzalez-Alegre, Pedro

2016-10-05

Dystonia type 1 (DYT1) is a dominantly inherited neurological disease caused by mutations in TOR1A, the gene encoding the endoplasmic reticulum (ER)-resident protein torsinA. Previous work mostly completed in cell-based systems suggests that mutant torsinA alters protein processing in the secretory pathway. We hypothesized that inducing ER stress in the mammalian brain in vivo would trigger or exacerbate mutant torsinA-induced dysfunction. To test this hypothesis, we crossed DYT1 knock-in with p58(IPK)-null mice. The ER co-chaperone p58(IPK) interacts with BiP and assists in protein maturation by helping to fold ER cargo. Its deletion increases the cellular sensitivity to ER stress. We found a lower generation of DYT1 knock-in/p58 knock-out mice than expected from this cross, suggesting a developmental interaction that influences viability. However, surviving animals did not exhibit abnormal motor function. Analysis of brain tissue uncovered dysregulation of eiF2α and Akt/mTOR translational control pathways in the DYT1 brain, a finding confirmed in a second rodent model and in human brain. Finally, an unbiased proteomic analysis identified relevant changes in the neuronal protein landscape suggesting abnormal ER protein metabolism and calcium dysregulation. Functional studies confirmed the interaction between the DYT1 genotype and neuronal calcium dynamics. Overall, these findings advance our knowledge on dystonia, linking translational control pathways and calcium physiology to dystonia pathogenesis and identifying potential new pharmacological targets. Dystonia type 1 (DYT1) is one of the different forms of inherited dystonia, a neurological disorder characterized by involuntary, disabling movements. DYT1 is caused by mutations in the gene that encodes the endoplasmic reticulum (ER)-resident protein torsinA. How mutant torsinA causes neuronal dysfunction remains unknown. Here, we show the behavioral and molecular consequences of stressing the ER in DYT1 mice by increasing the amount of misfolded proteins. This resulted in the generation of a reduced number of animals, evidence of abnormal ER protein processing and dysregulation of translational control pathways. The work described here proposes a shared mechanism for different forms of dystonia, links for the first time known biological pathways to dystonia pathogenesis, and uncovers potential pharmacological targets for its treatment. Copyright © 2016 the authors 0270-6474/16/3610245-12$15.00/0.

Block-circulant matrices with circulant blocks, Weil sums, and mutually unbiased bases. II. The prime power case

DOE Office of Scientific and Technical Information (OSTI.GOV)

Combescure, Monique

2009-03-15

In our previous paper [Combescure, M., 'Circulant matrices, Gauss sums and the mutually unbiased bases. I. The prime number case', Cubo A Mathematical Journal (unpublished)] we have shown that the theory of circulant matrices allows to recover the result that there exists p+1 mutually unbiased bases in dimension p, p being an arbitrary prime number. Two orthonormal bases B, B{sup '} of C{sup d} are said mutually unbiased if for all b(set-membership sign)B, for all b{sup '}(set-membership sign)B{sup '} one has that |b{center_dot}b{sup '}|=1/{radical}(d) (b{center_dot}b{sup '} Hermitian scalar product in C{sup d}). In this paper we show that the theorymore » of block-circulant matrices with circulant blocks allows to show very simply the known result that if d=p{sup n} (p a prime number and n any integer) there exists d+1 mutually unbiased bases in C{sup d}. Our result relies heavily on an idea of Klimov et al. [''Geometrical approach to the discrete Wigner function,'' J. Phys. A 39, 14471 (2006)]. As a subproduct we recover properties of quadratic Weil sums for p{>=}3, which generalizes the fact that in the prime case the quadratic Gauss sum properties follow from our results.« less

Examinations of tRNA Range of Motion Using Simulations of Cryo-EM Microscopy and X-Ray Data

PubMed Central

Caulfield, Thomas R.; Devkota, Batsal; Rollins, Geoffrey C.

2011-01-01

We examined tRNA flexibility using a combination of steered and unbiased molecular dynamics simulations. Using Maxwell's demon algorithm, molecular dynamics was used to steer X-ray structure data toward that from an alternative state obtained from cryogenic-electron microscopy density maps. Thus, we were able to fit X-ray structures of tRNA onto cryogenic-electron microscopy density maps for hybrid states of tRNA. Additionally, we employed both Maxwell's demon molecular dynamics simulations and unbiased simulation methods to identify possible ribosome-tRNA contact areas where the ribosome may discriminate tRNAs during translation. Herein, we collected >500 ns of simulation data to assess the global range of motion for tRNAs. Biased simulations can be used to steer between known conformational stop points, while unbiased simulations allow for a general testing of conformational space previously unexplored. The unbiased molecular dynamics data describes the global conformational changes of tRNA on a sub-microsecond time scale for comparison with steered data. Additionally, the unbiased molecular dynamics data was used to identify putative contacts between tRNA and the ribosome during the accommodation step of translation. We found that the primary contact regions were H71 and H92 of the 50S subunit and ribosomal proteins L14 and L16. PMID:21716650

Whole-genome expression analyses of type 2 diabetes in human skin reveal altered immune function and burden of infection.

PubMed

Wu, Chun; Chen, Xiaopan; Shu, Jing; Lee, Chun-Ting

2017-05-23

Skin disorders are among most common complications associated with type 2 diabetes mellitus (T2DM). Although T2DM patients are known to have increased risk of infections and other T2DM-related skin disorders, their molecular mechanisms are largely unknown. This study aims to identify dysregulated genes and gene networks that are associated with T2DM in human skin. We compared the expression profiles of 56,318 transcribed genes on 74 T2DM cases and 148 gender- age-, and race-matched non-diabetes controls from the Genotype-Tissue Expression (GTEx) database. RNA-Sequencing data indicates that diabetic skin is characterized by increased expression of genes that are related to immune responses (CCL20, CXCL9, CXCL10, CXCL11, CXCL13, and CCL18), JAK/STAT signaling pathway (JAK3, STAT1, and STAT2), tumor necrosis factor superfamily (TNFSF10 and TNFSF15), and infectious disease pathways (OAS1, OAS2, OAS3, and IFIH1). Genes in cell adhesion molecules pathway (NCAM1 and L1CAM) and collagen family (PCOLCE2 and COL9A3) are downregulated, suggesting structural changes in the skin of T2DM. For the first time, to the best of our knowledge, this pioneer analytic study reports comprehensive unbiased gene expression changes and dysregulated pathways in the non-diseased skin of T2DM patients. This comprehensive understanding derived from whole-genome expression profiles could advance our knowledge in determining molecular targets for the prevention and treatment of T2DM-associated skin disorders.

Spectroscopic observation of Gaia17dht and Gaia17diu by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Fraser, M.; Dyrbye, S.; Cappella, E.

2017-12-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of Gaia17dht/SN2017izz and Gaia17diu/SN2017jdb (in host galaxies SDSS J145121.24+283521.6 and LEDA 2753585 respectively).

Statistics as Unbiased Estimators: Exploring the Teaching of Standard Deviation

ERIC Educational Resources Information Center

Wasserman, Nicholas H.; Casey, Stephanie; Champion, Joe; Huey, Maryann

2017-01-01

This manuscript presents findings from a study about the knowledge for and planned teaching of standard deviation. We investigate how understanding variance as an unbiased (inferential) estimator--not just a descriptive statistic for the variation (spread) in data--is related to teachers' instruction regarding standard deviation, particularly…

Generalized approach for using unbiased symmetric metrics with negative values: normalized mean bias factor and normalized mean absolute error factor

EPA Science Inventory

Unbiased symmetric metrics provide a useful measure to quickly compare two datasets, with similar interpretations for both under and overestimations. Two examples include the normalized mean bias factor and normalized mean absolute error factor. However, the original formulations...

Correcting for Measurement Error in Time-Varying Covariates in Marginal Structural Models.

PubMed

Kyle, Ryan P; Moodie, Erica E M; Klein, Marina B; Abrahamowicz, Michał

2016-08-01

Unbiased estimation of causal parameters from marginal structural models (MSMs) requires a fundamental assumption of no unmeasured confounding. Unfortunately, the time-varying covariates used to obtain inverse probability weights are often error-prone. Although substantial measurement error in important confounders is known to undermine control of confounders in conventional unweighted regression models, this issue has received comparatively limited attention in the MSM literature. Here we propose a novel application of the simulation-extrapolation (SIMEX) procedure to address measurement error in time-varying covariates, and we compare 2 approaches. The direct approach to SIMEX-based correction targets outcome model parameters, while the indirect approach corrects the weights estimated using the exposure model. We assess the performance of the proposed methods in simulations under different clinically plausible assumptions. The simulations demonstrate that measurement errors in time-dependent covariates may induce substantial bias in MSM estimators of causal effects of time-varying exposures, and that both proposed SIMEX approaches yield practically unbiased estimates in scenarios featuring low-to-moderate degrees of error. We illustrate the proposed approach in a simple analysis of the relationship between sustained virological response and liver fibrosis progression among persons infected with hepatitis C virus, while accounting for measurement error in γ-glutamyltransferase, using data collected in the Canadian Co-infection Cohort Study from 2003 to 2014. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

When Unbiased Probabilistic Learning Is Not Enough: Acquiring a Parametric System of Metrical Phonology

ERIC Educational Resources Information Center

Pearl, Lisa S.

2011-01-01

Parametric systems have been proposed as models of how humans represent knowledge about language, motivated in part as a way to explain children's rapid acquisition of linguistic knowledge. Given this, it seems reasonable to examine if children with knowledge of parameters could in fact acquire the adult system from the data available to them.…

Figuring fact from fiction: unbiased polling of memory T cells.

PubMed

Gerlach, Carmen; Loughhead, Scott M; von Andrian, Ulrich H

2015-05-07

Immunization generates several memory T cell subsets that differ in their migratory properties, anatomic distribution, and, hence, accessibility to investigation. In this issue, Steinert et al. demonstrate that what was believed to be a minor memory cell subset in peripheral tissues has been dramatically underestimated. Thus, current models of protective immunity require revision. Copyright © 2015 Elsevier Inc. All rights reserved.

Proof of Concept for an Approach to a Finer Resolution Inventory

Treesearch

Chris J. Cieszewski; Kim Iles; Roger C. Lowe; Michal Zasada

2005-01-01

This report presents a proof of concept for a statistical framework to develop a timely, accurate, and unbiased fiber supply assessment in the State of Georgia, U.S.A. The proposed approach is based on using various data sources and modeling techniques to calibrate satellite image-based statewide stand lists, which provide initial estimates for a State inventory on a...

Using small area estimation and Lidar-derived variables for multivariate prediction of forest attributes

Treesearch

F. Mauro; Vicente Monleon; H. Temesgen

2015-01-01

Small area estimation (SAE) techniques have been successfully applied in forest inventories to provide reliable estimates for domains where the sample size is small (i.e. small areas). Previous studies have explored the use of either Area Level or Unit Level Empirical Best Linear Unbiased Predictors (EBLUPs) in a univariate framework, modeling each variable of interest...

Mechanistic Insights into the Allosteric Modulation of Opioid Receptors by Sodium Ions

PubMed Central

2015-01-01

The idea of sodium ions altering G-protein-coupled receptor (GPCR) ligand binding and signaling was first suggested for opioid receptors (ORs) in the 1970s and subsequently extended to other GPCRs. Recently published ultra-high-resolution crystal structures of GPCRs, including that of the δ-OR subtype, have started to shed light on the mechanism underlying sodium control in GPCR signaling by revealing details of the sodium binding site. Whether sodium accesses different receptor subtypes from the extra- or intracellular sides, following similar or different pathways, is still an open question. Earlier experiments in brain homogenates suggested a differential sodium regulation of ligand binding to the three major OR subtypes, in spite of their high degree of sequence similarity. Intrigued by this possibility, we explored the dynamic nature of sodium binding to δ-OR, μ-OR, and κ-OR by means of microsecond-scale, all-atom molecular dynamics (MD) simulations. Rapid sodium permeation was observed exclusively from the extracellular milieu, and following similar binding pathways in all three ligand-free OR systems, notwithstanding extra densities of sodium observed near nonconserved residues of κ-OR and δ-OR, but not in μ-OR. We speculate that these differences may be responsible for the differential increase in antagonist binding affinity of μ-OR by sodium resulting from specific ligand binding experiments in transfected cells. On the other hand, sodium reduced the level of binding of subtype-specific agonists to all OR subtypes. Additional biased and unbiased MD simulations were conducted using the δ-OR ultra-high-resolution crystal structure as a model system to provide a mechanistic explanation for this experimental observation. PMID:25073009

Mechanistic insights into the allosteric modulation of opioid receptors by sodium ions.

PubMed

Shang, Yi; LeRouzic, Valerie; Schneider, Sebastian; Bisignano, Paola; Pasternak, Gavril W; Filizola, Marta

2014-08-12

The idea of sodium ions altering G-protein-coupled receptor (GPCR) ligand binding and signaling was first suggested for opioid receptors (ORs) in the 1970s and subsequently extended to other GPCRs. Recently published ultra-high-resolution crystal structures of GPCRs, including that of the δ-OR subtype, have started to shed light on the mechanism underlying sodium control in GPCR signaling by revealing details of the sodium binding site. Whether sodium accesses different receptor subtypes from the extra- or intracellular sides, following similar or different pathways, is still an open question. Earlier experiments in brain homogenates suggested a differential sodium regulation of ligand binding to the three major OR subtypes, in spite of their high degree of sequence similarity. Intrigued by this possibility, we explored the dynamic nature of sodium binding to δ-OR, μ-OR, and κ-OR by means of microsecond-scale, all-atom molecular dynamics (MD) simulations. Rapid sodium permeation was observed exclusively from the extracellular milieu, and following similar binding pathways in all three ligand-free OR systems, notwithstanding extra densities of sodium observed near nonconserved residues of κ-OR and δ-OR, but not in μ-OR. We speculate that these differences may be responsible for the differential increase in antagonist binding affinity of μ-OR by sodium resulting from specific ligand binding experiments in transfected cells. On the other hand, sodium reduced the level of binding of subtype-specific agonists to all OR subtypes. Additional biased and unbiased MD simulations were conducted using the δ-OR ultra-high-resolution crystal structure as a model system to provide a mechanistic explanation for this experimental observation.

Oncogenic properties of apoptotic tumor cells in aggressive B cell lymphoma.

PubMed

Ford, Catriona A; Petrova, Sofia; Pound, John D; Voss, Jorine J L P; Melville, Lynsey; Paterson, Margaret; Farnworth, Sarah L; Gallimore, Awen M; Cuff, Simone; Wheadon, Helen; Dobbin, Edwina; Ogden, Carol Anne; Dumitriu, Ingrid E; Dunbar, Donald R; Murray, Paul G; Ruckerl, Dominik; Allen, Judith E; Hume, David A; van Rooijen, Nico; Goodlad, John R; Freeman, Tom C; Gregory, Christopher D

2015-03-02

Cells undergoing apoptosis are known to modulate their tissue microenvironments. By acting on phagocytes, notably macrophages, apoptotic cells inhibit immunological and inflammatory responses and promote trophic signaling pathways. Paradoxically, because of their potential to cause death of tumor cells and thereby militate against malignant disease progression, both apoptosis and tumor-associated macrophages (TAMs) are often associated with poor prognosis in cancer. We hypothesized that, in progression of malignant disease, constitutive loss of a fraction of the tumor cell population through apoptosis could yield tumor-promoting effects. Here, we demonstrate that apoptotic tumor cells promote coordinated tumor growth, angiogenesis, and accumulation of TAMs in aggressive B cell lymphomas. Through unbiased "in situ transcriptomics" analysis-gene expression profiling of laser-captured TAMs to establish their activation signature in situ-we show that these cells are activated to signal via multiple tumor-promoting reparatory, trophic, angiogenic, tissue remodeling, and anti-inflammatory pathways. Our results also suggest that apoptotic lymphoma cells help drive this signature. Furthermore, we demonstrate that, upon induction of apoptosis, lymphoma cells not only activate expression of the tumor-promoting matrix metalloproteinases MMP2 and MMP12 in macrophages but also express and process these MMPs directly. Finally, using a model of malignant melanoma, we show that the oncogenic potential of apoptotic tumor cells extends beyond lymphoma. In addition to its profound tumor-suppressive role, apoptosis can potentiate cancer progression. These results have important implications for understanding the fundamental biology of cell death, its roles in malignant disease, and the broader consequences of apoptosis-inducing anti-cancer therapy. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Project MACULA Retinal Pigment Epithelium Grading System for Histology and Optical Coherence Tomography in Age-Related Macular Degeneration

PubMed Central

Zanzottera, Emma C.; Messinger, Jeffrey D.; Ach, Thomas; Smith, R. Theodore; Freund, K. Bailey; Curcio, Christine A.

2015-01-01

Purpose. To seek pathways of retinal pigment epithelium (RPE) fate in age-related macular degeneration via a morphology grading system; provide nomenclature, visualization targets, and metrics for clinical imaging and model systems. Methods. Donor eyes with geographic atrophy (GA) or choroidal neovascularization (CNV) and one GA eye with previous clinical spectral-domain optical coherence tomography (SDOCT) imaging were processed for histology, photodocumented, and annotated at predefined locations. Retinal pigment epithelial cells contained spindle-shaped melanosomes, apposed a basal lamina or basal laminar deposit (BLamD), and exhibited recognizable morphologies. Thicknesses and unbiased estimates of frequencies were obtained. Results. In 13 GA eyes (449 locations), ‘Shedding,’ ‘Sloughed,’ and ‘Dissociated’ morphologies were abundant; 22.2% of atrophic locations had ‘Dissociated’ RPE. In 39 CNV eyes (1363 locations), 37.3% of locations with fibrovascular/fibrocellular scar had ‘Entombed’ RPE; ‘Sloughed,’ ‘Dissociated,’ and ‘Bilaminar’ morphologies were abundant. Of abnormal RPE, CNV and GA both had ∼35% ‘Sloughed’/‘Intraretinal,’ with more Intraretinal in CNV (9.5% vs. 1.8%). ‘Shedding’ cells associated with granule aggregations in BLamD. The RPE layer did not thin, and BLamD remained thick, with progression. Granule-containing material consistent with three morphologies correlated to SDOCT hyperreflective foci in the previously examined GA patient. Conclusions. Retinal pigment epithelium morphology indicates multiple pathways in GA and CNV. Atrophic/scarred areas have numerous cells capable of transcribing genes and generating imaging signals. Shed granule aggregates, possibly apoptotic, are visible in SDOCT, as are ‘Dissociated’ and ‘Sloughed’ cells. The significance of RPE phenotypes is addressable in longitudinal, high-resolution imaging in clinic populations. Data can motivate future molecular phenotyping studies. PMID:25813989

Cancer drug addiction is relayed by an ERK2-dependent phenotype switch.

PubMed

Kong, Xiangjun; Kuilman, Thomas; Shahrabi, Aida; Boshuizen, Julia; Kemper, Kristel; Song, Ji-Ying; Niessen, Hans W M; Rozeman, Elisa A; Geukes Foppen, Marnix H; Blank, Christian U; Peeper, Daniel S

2017-10-12

Observations from cultured cells, animal models and patients raise the possibility that the dependency of tumours on the therapeutic drugs to which they have acquired resistance represents a vulnerability with potential applications in cancer treatment. However, for this drug addiction trait to become of clinical interest, we must first define the mechanism that underlies it. We performed an unbiased CRISPR-Cas9 knockout screen on melanoma cells that were both resistant and addicted to inhibition of the serine/threonine-protein kinase BRAF, in order to functionally mine their genome for 'addiction genes'. Here we describe a signalling pathway comprising ERK2 kinase and JUNB and FRA1 transcription factors, disruption of which allowed addicted tumour cells to survive on treatment discontinuation. This occurred in both cultured cells and mice and was irrespective of the acquired drug resistance mechanism. In melanoma and lung cancer cells, death induced by drug withdrawal was preceded by a specific ERK2-dependent phenotype switch, alongside transcriptional reprogramming reminiscent of the epithelial-mesenchymal transition. In melanoma cells, this reprogramming caused the shutdown of microphthalmia-associated transcription factor (MITF), a lineage survival oncoprotein; restoring this protein reversed phenotype switching and prevented the lethality associated with drug addiction. In patients with melanoma that had progressed during treatment with a BRAF inhibitor, treatment cessation was followed by increased expression of the receptor tyrosine kinase AXL, which is associated with the phenotype switch. Drug discontinuation synergized with the melanoma chemotherapeutic agent dacarbazine by further suppressing MITF and its prosurvival target, B-cell lymphoma 2 (BCL-2), and by inducing DNA damage in cancer cells. Our results uncover a pathway that underpins drug addiction in cancer cells, which may help to guide the use of alternating therapeutic strategies for enhanced clinical responses in drug-resistant cancers.

Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

PubMed Central

Nishino, Jo; Kochi, Yuta; Shigemizu, Daichi; Kato, Mamoru; Ikari, Katsunori; Ochi, Hidenori; Noma, Hisashi; Matsui, Kota; Morizono, Takashi; Boroevich, Keith A.; Tsunoda, Tatsuhiko; Matsui, Shigeyuki

2018-01-01

Genome-wide association studies (GWAS) suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03)], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1). For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases. PMID:29740473

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed Central

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group. PMID:28034175

Should multiple imputation be the method of choice for handling missing data in randomized trials?

PubMed

Sullivan, Thomas R; White, Ian R; Salter, Amy B; Ryan, Philip; Lee, Katherine J

2016-01-01

The use of multiple imputation has increased markedly in recent years, and journal reviewers may expect to see multiple imputation used to handle missing data. However in randomized trials, where treatment group is always observed and independent of baseline covariates, other approaches may be preferable. Using data simulation we evaluated multiple imputation, performed both overall and separately by randomized group, across a range of commonly encountered scenarios. We considered both missing outcome and missing baseline data, with missing outcome data induced under missing at random mechanisms. Provided the analysis model was correctly specified, multiple imputation produced unbiased treatment effect estimates, but alternative unbiased approaches were often more efficient. When the analysis model overlooked an interaction effect involving randomized group, multiple imputation produced biased estimates of the average treatment effect when applied to missing outcome data, unless imputation was performed separately by randomized group. Based on these results, we conclude that multiple imputation should not be seen as the only acceptable way to handle missing data in randomized trials. In settings where multiple imputation is adopted, we recommend that imputation is carried out separately by randomized group.

Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

PubMed

Bernardo, R

1996-11-01

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

PubMed

Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

2010-02-27

Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

AN UNBIASED 1.3 mm EMISSION LINE SURVEY OF THE PROTOPLANETARY DISK ORBITING LkCa 15

DOE Office of Scientific and Technical Information (OSTI.GOV)

Punzi, K. M.; Kastner, J. H.; Hily-Blant, P.

2015-06-01

The outer (>30 AU) regions of the dusty circumstellar disk orbiting the ∼2–5 Myr old, actively accreting solar analog LkCa 15 are known to be chemically rich, and the inner disk may host a young protoplanet within its central cavity. To obtain a complete census of the brightest molecular line emission emanating from the LkCa 15 disk over the 210–270 GHz (1.4–1.1 mm) range, we have conducted an unbiased radio spectroscopic survey with the Institute de Radioastronomie Millimétrique (IRAM) 30 m telescope. The survey demonstrates that in this spectral region, the most readily detectable lines are those of CO andmore » its isotopologues {sup 13}CO and C{sup 18}O, as well as HCO{sup +}, HCN, CN, C{sub 2}H, CS, and H{sub 2}CO. All of these species had been previously detected in the LkCa 15 disk; however, the present survey includes the first complete coverage of the CN (2–1) and C{sub 2}H (3–2) hyperfine complexes. Modeling of these emission complexes indicates that the CN and C{sub 2}H either reside in the coldest regions of the disk or are subthermally excited, and that their abundances are enhanced relative to molecular clouds and young stellar object environments. These results highlight the value of unbiased single-dish line surveys in guiding future high-resolution interferometric imaging of disks.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bassuk, James; Lendvay, Thomas S.; Sweet, Robert

Diseases and conditions affecting the lower urinary tract are a leading cause of dysfunctional sexual health, incontinence, infection, and kidney failure. The growth, differentiation, and repair of the bladder's epithelial lining are regulated, in part, by fibroblast growth factor (FGF)-7 and -10 via a paracrine cascade originating in the mesenchyme (lamina propria) and targeting the receptor for FGF-7 and -10 within the transitional epithelium (urothelium). The FGF-7 gene is located at the 15q15-q21.1 locus on chromosome 15 and four exons generate a 3.852-kb mRNA. Five duplicated FGF-7 gene sequences that localized to chromosome 9 were predicted not to generate functionalmore » protein products, thus validating the use of FGF-7-null mice as an experimental model. Recombinant FGF-7 and -10 induced proliferation of human urothelial cells in vitro and transitional epithelium of wild-type and FGF-7-null mice in vivo.To determine the extent that induction of urothelial cell proliferation during the bladder response to injury is dependent on FGF-7, an animal model of partial bladder outlet obstruction was developed. Unbiased stereology was used to measure the percentage of proliferating urothelial cells between obstructed groups of wild-type and FGF-7-null mice. The stereological analysis indicated that a statistical significant difference did not exist between the two groups, suggesting that FGF-7 is not essential for urothelial cell proliferation in response to partial outlet obstruction. In contrast, a significant increase in FGF-10 expression was observed in the obstructed FGF-7-null group, indicating that the compensatory pathway that functions in this model results in urothelial repair.« less

Modeling longitudinal data, I: principles of multivariate analysis.

PubMed

Ravani, Pietro; Barrett, Brendan; Parfrey, Patrick

2009-01-01

Statistical models are used to study the relationship between exposure and disease while accounting for the potential role of other factors' impact on outcomes. This adjustment is useful to obtain unbiased estimates of true effects or to predict future outcomes. Statistical models include a systematic component and an error component. The systematic component explains the variability of the response variable as a function of the predictors and is summarized in the effect estimates (model coefficients). The error element of the model represents the variability in the data unexplained by the model and is used to build measures of precision around the point estimates (confidence intervals).

Evolving Concepts of Asthma

PubMed Central

Ray, Anuradha; Wenzel, Sally E.

2015-01-01

Our understanding of asthma has evolved over time from a singular disease to a complex of various phenotypes, with varied natural histories, physiologies, and responses to treatment. Early therapies treated most patients with asthma similarly, with bronchodilators and corticosteroids, but these therapies had varying degrees of success. Similarly, despite initial studies that identified an underlying type 2 inflammation in the airways of patients with asthma, biologic therapies targeted toward these type 2 pathways were unsuccessful in all patients. These observations led to increased interest in phenotyping asthma. Clinical approaches, both biased and later unbiased/statistical approaches to large asthma patient cohorts, identified a variety of patient characteristics, but they also consistently identified the importance of age of onset of disease and the presence of eosinophils in determining clinically relevant phenotypes. These paralleled molecular approaches to phenotyping that developed an understanding that not all patients share a type 2 inflammatory pattern. Using biomarkers to select patients with type 2 inflammation, repeated trials of biologics directed toward type 2 cytokine pathways saw newfound success, confirming the importance of phenotyping in asthma. Further research is needed to clarify additional clinical and molecular phenotypes, validate predictive biomarkers, and identify new areas for possible interventions. PMID:26161792

High-throughput combinatorial screening identifies drugs that cooperate with ibrutinib to kill activated B-cell–like diffuse large B-cell lymphoma cells

PubMed Central

Mathews Griner, Lesley A.; Guha, Rajarshi; Shinn, Paul; Young, Ryan M.; Keller, Jonathan M.; Liu, Dongbo; Goldlust, Ian S.; Yasgar, Adam; McKnight, Crystal; Boxer, Matthew B.; Duveau, Damien Y.; Jiang, Jian-Kang; Michael, Sam; Mierzwa, Tim; Huang, Wenwei; Walsh, Martin J.; Mott, Bryan T.; Patel, Paresma; Leister, William; Maloney, David J.; Leclair, Christopher A.; Rai, Ganesha; Jadhav, Ajit; Peyser, Brian D.; Austin, Christopher P.; Martin, Scott E.; Simeonov, Anton; Ferrer, Marc; Staudt, Louis M.; Thomas, Craig J.

2014-01-01

The clinical development of drug combinations is typically achieved through trial-and-error or via insight gained through a detailed molecular understanding of dysregulated signaling pathways in a specific cancer type. Unbiased small-molecule combination (matrix) screening represents a high-throughput means to explore hundreds and even thousands of drug–drug pairs for potential investigation and translation. Here, we describe a high-throughput screening platform capable of testing compounds in pairwise matrix blocks for the rapid and systematic identification of synergistic, additive, and antagonistic drug combinations. We use this platform to define potential therapeutic combinations for the activated B-cell–like subtype (ABC) of diffuse large B-cell lymphoma (DLBCL). We identify drugs with synergy, additivity, and antagonism with the Bruton’s tyrosine kinase inhibitor ibrutinib, which targets the chronic active B-cell receptor signaling that characterizes ABC DLBCL. Ibrutinib interacted favorably with a wide range of compounds, including inhibitors of the PI3K-AKT-mammalian target of rapamycin signaling cascade, other B-cell receptor pathway inhibitors, Bcl-2 family inhibitors, and several components of chemotherapy that is the standard of care for DLBCL. PMID:24469833

RhoJ Regulates Melanoma Chemoresistance by Suppressing Pathways that Sense DNA Damage

PubMed Central

Ho, Hsiang; Aruri, Jayavani; Kapadia, Rubina; Mehr, Hootan; White, Michael A.; Ganesan, Anand K.

2012-01-01

Melanomas resist conventional chemotherapeutics in part through intrinsic disrespect of apoptotic checkpoint activation. In this study, using an unbiased genome-wide RNAi screen we identified RhoJ and its effector Pak1, as key modulators of melanoma cell sensitivity to DNA damage. We find that RhoJ activates Pak1 in response to drug-induced DNA damage, which then uncouples ATR from its downstream effectors, ultimately resulting in a blunted DNA damage response (DDR). In addition, ATR suppression leads to the decreased phosphorylation of ATF2, and consequent increased expression of the melanocyte survival gene Sox10 resulting in a higher DDR threshold required to engage melanoma cell death. In the setting of normal melanocyte behavior, this regulatory relationship may facilitate appropriate epidermal melanization in response to UV-induced DNA damage. However, pathological pathway activation during oncogenic transformation produces a tumor that is intrinsically resistant to chemotherapy and has the propensity to accumulate additional mutations. These findings identify DNA damage agents and pharmacological inhibitors of RhoJ/PAK1 as novel synergistic agents that can be used to treat melanomas that are resistant to conventional chemotherapies. PMID:22971344

Glucocorticoids promote Von Hippel Lindau degradation and Hif-1α stabilization

PubMed Central

Greenald, David; Wilson, Garrick K.; Peron, Margherita; Markham, Eleanor; Sinnakaruppan, Mathavan; Matthews, Laura C.; McKeating, Jane A.; Argenton, Francesco; van Eeden, Fredericus J. M.

2017-01-01

Glucocorticoid (GC) and hypoxic transcriptional responses play a central role in tissue homeostasis and regulate the cellular response to stress and inflammation, highlighting the potential for cross-talk between these two signaling pathways. We present results from an unbiased in vivo chemical screen in zebrafish that identifies GCs as activators of hypoxia-inducible factors (HIFs) in the liver. GCs activated consensus hypoxia response element (HRE) reporters in a glucocorticoid receptor (GR)-dependent manner. Importantly, GCs activated HIF transcriptional responses in a zebrafish mutant line harboring a point mutation in the GR DNA-binding domain, suggesting a nontranscriptional route for GR to activate HIF signaling. We noted that GCs increase the transcription of several key regulators of glucose metabolism that contain HREs, suggesting a role for GC/HIF cross-talk in regulating glucose homeostasis. Importantly, we show that GCs stabilize HIF protein in intact human liver tissue and isolated hepatocytes. We find that GCs limit the expression of Von Hippel Lindau protein (pVHL), a negative regulator of HIF, and that treatment with the c-src inhibitor PP2 rescued this effect, suggesting a role for GCs in promoting c-src–mediated proteosomal degradation of pVHL. Our data support a model for GCs to stabilize HIF through activation of c-src and subsequent destabilization of pVHL. PMID:28851829

S100A6 regulates endothelial cell cycle progression by attenuating antiproliferative STAT1 signaling

PubMed Central

Lerchenmüller, Carolin; Heißenberg, Julian; Damilano, Federico; Bezzeridis, Vassilios J.; Krämer, Isabel; Bochaton-Piallat, Marie-Luce; Hirschberg, Kristóf; Busch, Martin; Katus, Hugo A.; Peppel, Karsten; Rosenzweig, Anthony; Busch, Hauke; Boerries, Melanie; Most, Patrick

2016-01-01

Objective S100A6, a member of the S100-protein family, has been described as relevant for cell cycle entry and progression in endothelial cells (ECs). The molecular mechanism conferring S100A6’s proliferative actions, however, remained elusive. Approach and Results Originating from the clinically relevant observation of enhanced S100A6 protein expression in proliferating ECs in remodeling coronary and carotid arteries, our study unveiled S100A6 as a suppressor of antiproliferative signal transducers and activators of transcription 1 (STAT1) signaling. Discovery of the molecular liaison was enabled by combining gene expression time series analysis with bioinformatic pathway modeling in S100A6 silenced human ECs stimulated with vascular endothelial growth factor A (VEGF-A). This unbiased approach led to successful identification and experimental validation of interferon-inducible transmembrane protein 1 (IFITM1) and protein inhibitors of activated STAT (PIAS) as key components of the link between S100A6 and STAT1. Conclusions Given the important role of coordinated EC cell cycle activity for integrity and reconstitution of the inner lining of arterial blood vessels in health and disease, STAT1 suppression by S100A6 may represent a promising therapeutic target to facilitate reendothelialization in damaged vessels. PMID:27386938

Extended molecular dynamics of a c-kit promoter quadruplex

PubMed Central

Islam, Barira; Stadlbauer, Petr; Krepl, Miroslav; Koca, Jaroslav; Neidle, Stephen; Haider, Shozeb; Sponer, Jiri

2015-01-01

The 22-mer c-kit promoter sequence folds into a parallel-stranded quadruplex with a unique structure, which has been elucidated by crystallographic and NMR methods and shows a high degree of structural conservation. We have carried out a series of extended (up to 10 μs long, ∼50 μs in total) molecular dynamics simulations to explore conformational stability and loop dynamics of this quadruplex. Unfolding no-salt simulations are consistent with a multi-pathway model of quadruplex folding and identify the single-nucleotide propeller loops as the most fragile part of the quadruplex. Thus, formation of propeller loops represents a peculiar atomistic aspect of quadruplex folding. Unbiased simulations reveal μs-scale transitions in the loops, which emphasizes the need for extended simulations in studies of quadruplex loops. We identify ion binding in the loops which may contribute to quadruplex stability. The long lateral-propeller loop is internally very stable but extensively fluctuates as a rigid entity. It creates a size-adaptable cleft between the loop and the stem, which can facilitate ligand binding. The stability gain by forming the internal network of GA base pairs and stacks of this loop may be dictating which of the many possible quadruplex topologies is observed in the ground state by this promoter quadruplex. PMID:26245347

Automated 4D analysis of dendritic spine morphology: applications to stimulus-induced spine remodeling and pharmacological rescue in a disease model

PubMed Central

2011-01-01

Uncovering the mechanisms that regulate dendritic spine morphology has been limited, in part, by the lack of efficient and unbiased methods for analyzing spines. Here, we describe an automated 3D spine morphometry method and its application to spine remodeling in live neurons and spine abnormalities in a disease model. We anticipate that this approach will advance studies of synapse structure and function in brain development, plasticity, and disease. PMID:21982080

Occupancy models to study wildlife

USGS Publications Warehouse

Bailey, Larissa; Adams, Michael John

2005-01-01

Many wildlife studies seek to understand changes or differences in the proportion of sites occupied by a species of interest. These studies are hampered by imperfect detection of these species, which can result in some sites appearing to be unoccupied that are actually occupied. Occupancy models solve this problem and produce unbiased estimates of occupancy and related parameters. Required data (detection/non-detection information) are relatively simple and inexpensive to collect. Software is available free of charge to aid investigators in occupancy estimation.

A Bayesian Approach to Identifying Structural Nonlinearity using Free-Decay Response: Application to Damage Detection in Composites

DTIC Science & Technology

2010-03-03

obtainable while for the free-decay problem we simply have to include the initial conditions as random variables to be predicted. A different approach that...important and useful properties of MLEs is that, under regularity conditions , they are asymptotically unbiased and possess the minimum possible...becomes pLðzjh;s2G;MiÞ (i.e. the likelihood is conditional on the specified model). However, in this work we will only consider a single model and drop the

Parameter estimation in linear models of the human operator in a closed loop with application of deterministic test signals

NASA Technical Reports Server (NTRS)

Vanlunteren, A.; Stassen, H. G.

1973-01-01

Parameter estimation techniques are discussed with emphasis on unbiased estimates in the presence of noise. A distinction between open and closed loop systems is made. A method is given based on the application of external forcing functions consisting of a sun of sinusoids; this method is thus based on the estimation of Fourier coefficients and is applicable for models with poles and zeros in open and closed loop systems.

Mutually unbiased bases in six dimensions: The four most distant bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raynal, Philippe; Lue Xin; Englert, Berthold-Georg

2011-06-15

We consider the average distance between four bases in six dimensions. The distance between two orthonormal bases vanishes when the bases are the same, and the distance reaches its maximal value of unity when the bases are unbiased. We perform a numerical search for the maximum average distance and find it to be strictly smaller than unity. This is strong evidence that no four mutually unbiased bases exist in six dimensions. We also provide a two-parameter family of three bases which, together with the canonical basis, reach the numerically found maximum of the average distance, and we conduct a detailedmore » study of the structure of the extremal set of bases.« less

Extreme Mean and Its Applications

NASA Technical Reports Server (NTRS)

Swaroop, R.; Brownlow, J. D.

1979-01-01

Extreme value statistics obtained from normally distributed data are considered. An extreme mean is defined as the mean of p-th probability truncated normal distribution. An unbiased estimate of this extreme mean and its large sample distribution are derived. The distribution of this estimate even for very large samples is found to be nonnormal. Further, as the sample size increases, the variance of the unbiased estimate converges to the Cramer-Rao lower bound. The computer program used to obtain the density and distribution functions of the standardized unbiased estimate, and the confidence intervals of the extreme mean for any data are included for ready application. An example is included to demonstrate the usefulness of extreme mean application.

Interpreting linear support vector machine models with heat map molecule coloring

PubMed Central

2011-01-01

Background Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. Results We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor. Conclusions In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor. PMID:21439031

Estimating Unbiased Treatment Effects in Education Using a Regression Discontinuity Design

ERIC Educational Resources Information Center

Smith, William C.

2014-01-01

The ability of regression discontinuity (RD) designs to provide an unbiased treatment effect while overcoming the ethical concerns plagued by Random Control Trials (RCTs) make it a valuable and useful approach in education evaluation. RD is the only explicitly recognized quasi-experimental approach identified by the Institute of Education…

Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster

PubMed Central

Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter

2016-01-01

Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308

Geophysical Interpretation of Venus Gravity Data

NASA Technical Reports Server (NTRS)

Reasenberg, R. D.

1985-01-01

The subsurface distribution of Venus was investigated through the analysis of the data from Pioneer Venus Orbiter (PVO). In particular, the Doppler tracking data were used to map the gravitational potential. These were compared to the topographic data from the PVO radar (ORAD). In order to obtain an unbiased comparison, the topography data obtained from the PVO-ORAD were filtered to introduce distortions which are the same as those of the gravity models. Both the gravity and filtered topography maps are derived by two stage processes with a common second stage. In the first stage, the topography was used to calculate a corresponding spacecraft acceleration under the assumptions that the topography has a uniform given density and no compensation. In the second stage, the acceleration measures found in the first stage were passed through a linear inverter to yield maps of gravity and topography. Because these maps are the result of the same inversion process, they contain the same distortion; a comparison between them is unbiased to first order.

Overlap between treatment and control distributions as an effect size measure in experiments.

PubMed

Hedges, Larry V; Olkin, Ingram

2016-03-01

The proportion π of treatment group observations that exceed the control group mean has been proposed as an effect size measure for experiments that randomly assign independent units into 2 groups. We give the exact distribution of a simple estimator of π based on the standardized mean difference and use it to study the small sample bias of this estimator. We also give the minimum variance unbiased estimator of π under 2 models, one in which the variance of the mean difference is known and one in which the variance is unknown. We show how to use the relation between the standardized mean difference and the overlap measure to compute confidence intervals for π and show that these results can be used to obtain unbiased estimators, large sample variances, and confidence intervals for 3 related effect size measures based on the overlap. Finally, we show how the effect size π can be used in a meta-analysis. (c) 2016 APA, all rights reserved).

The Swift GRB Host Galaxy Legacy Survey

NASA Astrophysics Data System (ADS)

Perley, Daniel

2015-08-01

I will describe the Swift Host Galaxy Legacy Survey (SHOALS), a comprehensive multiwavelength program to characterize the demographics of the GRB host population and its redshift evolution from z=0 to z=7. Using unbiased selection criteria we have designated a subset of 119 Swift gamma-ray bursts which are now being targeted with intensive observational follow-up. Deep Spitzer imaging of every field has already been obtained and analyzed, with major programs ongoing at Keck, GTC, Gemini, VLT, and Magellan to obtain complementary optical/NIR photometry and spectroscopy to enable full SED modeling and derivation of fundamental physical parameters such as mass, extinction, and star-formation rate. Using these data I will present an unbiased measurement of the GRB host-galaxy luminosity and mass distributions and their evolution with redshift, compare GRB hosts to other star-forming galaxy populations, and discuss implications for the nature of the GRB progenitor and the ability of GRBs to serve as tools for measuring and studying cosmic star-formation in the distant universe.

Motor activity as an unbiased variable to assess anaphylaxis in allergic rats.

PubMed

Abril-Gil, Mar; Garcia-Just, Alba; Cambras, Trinitat; Pérez-Cano, Francisco J; Castellote, Cristina; Franch, Àngels; Castell, Margarida

2015-10-01

The release of mediators by mast cells triggers allergic symptoms involving various physiological systems and, in the most severe cases, the development of anaphylactic shock compromising mainly the nervous and cardiovascular systems. We aimed to establish variables to objectively study the anaphylactic response (AR) after an oral challenge in an allergy model. Brown Norway rats were immunized by intraperitoneal injection of ovalbumin with alum and toxin from Bordetella pertussis. Specific immunoglobulin (Ig) E antibodies were developed in immunized animals. Forty days after immunization, the rats were orally challenged with the allergen, and motor activity, body temperature and serum mast cell protease concentration were determined. The anaphylaxis induced a reduction in body temperature and a decrease in the number of animal movements, which was inversely correlated with serum mast cell protease release. In summary, motor activity is a reliable tool for assessing AR and also an unbiased method for screening new anti-allergic drugs. © 2015 by the Society for Experimental Biology and Medicine.

Spectroscopic observations of ATLAS17lcs (SN 2017guv) and ASASSN-17mq (AT 2017gvo) by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Dong, Subo; Bose, Subhash; Stritzinger, M.; Holmbo, S.; Fraser, M.; Fedorets, G.

2017-10-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ATLAS17lcs (SN 2017guv) and ASASSN-17mq (AT 2017gvo) in host galaxies 2MASX J19132225-1648031 and CGCG 225-050, respectively.

Spectroscopic observations of ASASSN-17io and ATLAS17hpt (SN 2017faf) by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Pastorello, Andrea; Benetti, Stefano; Cappellaro, Enrico; Terreran, Giacomo; Tomasella, Lina; Fedorets, Grigori; NUTS Collaboration

2017-07-01

The Nordic Optical Telescope (NOT) Unbiased Transient Survey (NUTS; ATel #8992) reports the spectroscopic classification of ASASSN-17io in the galaxy CGCG 316-010, along with the re classification of ATLAS17hpt (SN 2017faf), which was previously classified as a SLSN-I (ATel #10549).

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Swain, P. H. (Principal Investigator); Vardeman, S. B.

1981-01-01

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

Genomic predictions across Nordic Holstein and Nordic Red using the genomic best linear unbiased prediction model with different genomic relationship matrices.

PubMed

Zhou, L; Lund, M S; Wang, Y; Su, G

2014-08-01

This study investigated genomic predictions across Nordic Holstein and Nordic Red using various genomic relationship matrices. Different sources of information, such as consistencies of linkage disequilibrium (LD) phase and marker effects, were used to construct the genomic relationship matrices (G-matrices) across these two breeds. Single-trait genomic best linear unbiased prediction (GBLUP) model and two-trait GBLUP model were used for single-breed and two-breed genomic predictions. The data included 5215 Nordic Holstein bulls and 4361 Nordic Red bulls, which was composed of three populations: Danish Red, Swedish Red and Finnish Ayrshire. The bulls were genotyped with 50 000 SNP chip. Using the two-breed predictions with a joint Nordic Holstein and Nordic Red reference population, accuracies increased slightly for all traits in Nordic Red, but only for some traits in Nordic Holstein. Among the three subpopulations of Nordic Red, accuracies increased more for Danish Red than for Swedish Red and Finnish Ayrshire. This is because closer genetic relationships exist between Danish Red and Nordic Holstein. Among Danish Red, individuals with higher genomic relationship coefficients with Nordic Holstein showed more increased accuracies in the two-breed predictions. Weighting the two-breed G-matrices by LD phase consistencies, marker effects or both did not further improve accuracies of the two-breed predictions. © 2014 Blackwell Verlag GmbH.

Nature's inordinate fondness for metabolic enzymes: why metabolic enzyme loci are so frequently targets of selection.

PubMed

Marden, James H

2013-12-01

Metabolic enzyme loci were some of the first genes accessible for molecular evolution and ecology research. New technologies now make the whole genome, transcriptome or proteome readily accessible, allowing unbiased scans for loci exhibiting significant differences in allele frequency or expression level and associated with phenotypes and/or responses to natural selection. With surprising frequency and in many cases in proportions greater than chance relative to other genes, glycolysis and TCA cycle enzyme loci appear among the genes with significant associations in these studies. Hence, there is an ongoing need to understand the basis for fitness effects of metabolic enzyme polymorphisms. Allele-specific effects on the binding affinity and catalytic rate of individual enzymes are well known, but often of uncertain significance because metabolic control theory and in vivo studies indicate that many individual metabolic enzymes do not affect pathway flux rate. I review research, so far little used in evolutionary biology, showing that metabolic enzyme substrates affect signalling pathways that regulate cell and organismal biology, and that these enzymes have moonlighting functions. To date there is little knowledge of how alleles in natural populations affect these phenotypes. I discuss an example in which alleles of a TCA enzyme locus associate with differences in a signalling pathway and development, organismal performance, and ecological dynamics. Ultimately, understanding how metabolic enzyme polymorphisms map to phenotypes and fitness remains a compelling and ongoing need for gaining robust knowledge of ecological and evolutionary processes. © 2013 John Wiley & Sons Ltd.

Protein quality control at the inner nuclear membrane

PubMed Central

Khmelinskii, Anton; Blaszczak, Ewa; Pantazopoulou, Marina; Fischer, Bernd; Omnus, Deike J.; Le Dez, Gaëlle; Brossard, Audrey; Gunnarsson, Alexander; Barry, Joseph D.; Meurer, Matthias; Kirrmaier, Daniel; Boone, Charles; Huber, Wolfgang; Rabut, Gwenaël; Ljungdahl, Per O.; Knop, Michael

2015-01-01

The nuclear envelope is a double membrane that separates the nucleus from the cytoplasm. The inner nuclear membrane (INM) functions in essential nuclear processes including chromatin organization and regulation of gene expression1. The outer nuclear membrane is continuous with the endoplasmic reticulum (ER) and is the site of membrane protein synthesis. Protein homeostasis in this compartment is ensured by ER-associated protein degradation (ERAD) pathways that in yeast involve the integral membrane E3 ubiquitin ligases Hrd1 and Doa10 operating with the E2 ubiquitin-conjugating enzymes Ubc6 and Ubc72,3. However, little is known regarding protein quality control at the INM. Here we describe a protein degradation pathway at the INM mediated by the Asi complex consisting of the RING domain proteins Asi1 and Asi34. We report that the As complex functions together with the ubiquitin conjugating enzymes Ubc6andUbc7to degrade soluble and integral membrane proteins. Genetic evidence suggest that the Asi ubiquitin ligase defines a pathway distinct from but complementary to ERAD. Using unbiased screening with a novel genome-wide yeast library based on a tandem fluorescent protein timer (tFT)5, we identify more than 50 substrates of the Asi, Hrd1 and Doa10 E3 ubiquity ligases. We show that the Asi ubiquitin ligase is involved in degradation of mislocalised integral membrane proteins, thus acting to maintain and safeguard the identity of the INM. PMID:25519137

MTBP inhibits the Erk1/2-Elk-1 signaling in hepatocellular carcinoma

PubMed Central

Ranjan, Atul; Iyer, Swathi V.; Ward, Christopher; Link, Tim; Diaz, Francisco J.; Dhar, Animesh; Tawfik, Ossama W.; Weinman, Steven A.; Azuma, Yoshiaki; Izumi, Tadahide; Iwakuma, Tomoo

2018-01-01

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and the prognosis of HCC patients, especially those with metastasis, remains extremely poor. This is partly due to unclear molecular mechanisms underlying HCC metastasis. Our previous study indicates that MDM2 Binding Protein (MTBP) suppresses migration and metastasis of HCC cells. However, signaling pathways regulated by MTBP remain unknown. To identify metastasis-associated signaling pathways governed by MTBP, we have performed unbiased luciferase reporter-based signal array analyses and found that MTBP suppresses the activity of the ETS-domain transcription factor Elk-1, a downstream target of Erk1/2 MAP kinases. MTBP also inhibits phosphorylation of Elk-1 and decreases mRNA expression of Elk-1 target genes. Reduced Elk-1 activity is caused by inhibited nuclear translocation of phosphorylated Erk1/2 (p-Erk) by MTBP and subsequent inhibition of Elk-1 phosphorylation. We also reveal that MTBP inhibits the interaction of p-Erk with importin-7/RanBP7 (IPO7), an importin family member which shuttles p-Erk into the nucleus, by binding to IPO7. Moreover, high levels of MTBP in human HCC tissues are correlated with cytoplasmic localization of p-Erk1/2. Our study suggests that MTBP suppresses metastasis, at least partially, by down-modulating the Erk1/2-Elk-1 signaling pathway, thus identifying a novel regulatory mechanism of HCC metastasis by regulating the subcellular localization of p-Erk. PMID:29765550

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

NASA Technical Reports Server (NTRS)

Howell, L. W.

2002-01-01

A simple power law model consisting of a single spectral index, a is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index alpha(sub 2) greater than alpha(sub 1) above E(sub k). The Maximum likelihood (ML) procedure was developed for estimating the single parameter alpha(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (P1) consistency (asymptotically unbiased). (P2) efficiency asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only he ascertained by calculating the CRB for an assumed energy spectrum-detector response function combination, which can be quite formidable in practice. However. the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are attained in practice are investigated. The ML technique is then extended to estimate spectra information from an arbitrary number of astrophysics data sets produced by vastly different science instruments. This theory and its successful implementation will facilitate the interpretation of spectral information from multiple astrophysics missions and thereby permit the derivation of superior spectral parameter estimates based on the combination of data sets.

Unbiased Proteomics of Early Lewy Body Formation Model Implicates Active Microtubule Affinity-Regulating Kinases (MARKs) in Synucleinopathies

PubMed Central

Riddle, Dawn M.; Zhang, Bin

2017-01-01

Parkinson's disease (PD) patients progressively accumulate intracytoplasmic inclusions formed by misfolded α-synuclein known as Lewy bodies (LBs). LBs also contain other proteins that may or may not be relevant in the disease process. To identify proteins involved early in LB formation, we performed proteomic analysis of insoluble proteins in a primary neuron culture model of α-synuclein pathology. We identified proteins previously found in authentic LBs in PD as well as several novel proteins, including the microtubule affinity-regulating kinase 1 (MARK1), one of the most enriched proteins in this model of LB formation. Activated MARK proteins (MARKs) accumulated in LB-like inclusions in this cell-based model as well as in a mouse model of LB disease and in LBs of postmortem synucleinopathy brains. Inhibition of MARKs dramatically exacerbated α-synuclein pathology. These findings implicate MARKs early in synucleinopathy pathogenesis and as potential therapeutic drug targets. SIGNIFICANCE STATEMENT Neurodegenerative diseases are diagnosed definitively only in postmortem brains by the presence of key misfolded and aggregated disease proteins, but cellular processes leading to accumulation of these proteins have not been well elucidated. Parkinson's disease (PD) patients accumulate misfolded α-synuclein in LBs, the diagnostic signatures of PD. Here, unbiased mass spectrometry was used to identify the microtubule affinity-regulating kinase family (MARKs) as activated and insoluble in a neuronal culture PD model. Aberrant activation of MARKs was also found in a PD mouse model and in postmortem PD brains. Further, inhibition of MARKs led to increased pathological α-synuclein burden. We conclude that MARKs play a role in PD pathogenesis. PMID:28522732

Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

PubMed

Xia, Jie; Reid, Terry-Elinor; Wu, Song; Zhang, Liangren; Wang, Xiang Simon

2018-05-29

Chemokine receptors (CRs) have long been druggable targets for the treatment of inflammatory diseases and HIV-1 infection. As a powerful technique, virtual screening (VS) has been widely applied to identifying small molecule leads for modern drug targets including CRs. For rational selection of a wide variety of VS approaches, ligand enrichment assessment based on a benchmarking data set has become an indispensable practice. However, the lack of versatile benchmarking sets for the whole CRs family that are able to unbiasedly evaluate every single approach including both structure- and ligand-based VS somewhat hinders modern drug discovery efforts. To address this issue, we constructed Maximal Unbiased Benchmarking Data sets for human Chemokine Receptors (MUBD-hCRs) using our recently developed tools of MUBD-DecoyMaker. The MUBD-hCRs encompasses 13 subtypes out of 20 chemokine receptors, composed of 404 ligands and 15756 decoys so far and is readily expandable in the future. It had been thoroughly validated that MUBD-hCRs ligands are chemically diverse while its decoys are maximal unbiased in terms of "artificial enrichment", "analogue bias". In addition, we studied the performance of MUBD-hCRs, in particular CXCR4 and CCR5 data sets, in ligand enrichment assessments of both structure- and ligand-based VS approaches in comparison with other benchmarking data sets available in the public domain and demonstrated that MUBD-hCRs is very capable of designating the optimal VS approach. MUBD-hCRs is a unique and maximal unbiased benchmarking set that covers major CRs subtypes so far.

SYSTEMS BIOLOGY ANALYSES OF GENE EXPRESSION AND GENOME WIDE ASSOCIATION STUDY DATA IN OBSTRUCTIVE SLEEP APNEA

PubMed Central

LIU, YU; PATEL, SANJAY; NIBBE, ROD; MAXWELL, SEAN; CHOWDHURY, SALIM A.; KOYUTURK, MEHMET; ZHU, XIAOFENG; LARKIN, EMMA K.; BUXBAUM, SARAH G; PUNJABI, NARESH M.; GHARIB, SINA A.; REDLINE, SUSAN; CHANCE, MARK R.

2015-01-01

The precise molecular etiology of obstructive sleep apnea (OSA) is unknown; however recent research indicates that several interconnected aberrant pathways and molecular abnormalities are contributors to OSA. Identifying the genes and pathways associated with OSA can help to expand our understanding of the risk factors for the disease as well as provide new avenues for potential treatment. Towards these goals, we have integrated relevant high dimensional data from various sources, such as genome-wide expression data (microarray), protein-protein interaction (PPI) data and results from genome-wide association studies (GWAS) in order to define sub-network elements that connect some of the known pathways related to the disease as well as define novel regulatory modules related to OSA. Two distinct approaches are applied to identify sub-networks significantly associated with OSA. In the first case we used a biased approach based on sixty genes/proteins with known associations with sleep disorders and/or metabolic disease to seed a search using commercial software to discover networks associated with disease followed by information theoretic (mutual information) scoring of the sub-networks. In the second case we used an unbiased approach and generated an interactome constructed from publicly available gene expression profiles and PPI databases, followed by scoring of the network with p-values from GWAS data derived from OSA patients to uncover sub-networks significant for the disease phenotype. A comparison of the approaches reveals a number of proteins that have been previously known to be associated with OSA or sleep. In addition, our results indicate a novel association of Phosphoinositide 3-kinase, the STAT family of proteins and its related pathways with OSA. PMID:21121029

Estimating unbiased economies of scale of HIV prevention projects: a case study of Avahan.

PubMed

Lépine, Aurélia; Vassall, Anna; Chandrashekar, Sudha; Blanc, Elodie; Le Nestour, Alexis

2015-04-01

Governments and donors are investing considerable resources on HIV prevention in order to scale up these services rapidly. Given the current economic climate, providers of HIV prevention services increasingly need to demonstrate that these investments offer good 'value for money'. One of the primary routes to achieve efficiency is to take advantage of economies of scale (a reduction in the average cost of a health service as provision scales-up), yet empirical evidence on economies of scale is scarce. Methodologically, the estimation of economies of scale is hampered by several statistical issues preventing causal inference and thus making the estimation of economies of scale complex. In order to estimate unbiased economies of scale when scaling up HIV prevention services, we apply our analysis to one of the few HIV prevention programmes globally delivered at a large scale: the Indian Avahan initiative. We costed the project by collecting data from the 138 Avahan NGOs and the supporting partners in the first four years of its scale-up, between 2004 and 2007. We develop a parsimonious empirical model and apply a system Generalized Method of Moments (GMM) and fixed-effects Instrumental Variable (IV) estimators to estimate unbiased economies of scale. At the programme level, we find that, after controlling for the endogeneity of scale, the scale-up of Avahan has generated high economies of scale. Our findings suggest that average cost reductions per person reached are achievable when scaling-up HIV prevention in low and middle income countries. Copyright © 2015 Elsevier Ltd. All rights reserved.

Critical point relascope sampling for unbiased volume estimation of downed coarse woody debris

Treesearch

Jeffrey H. Gove; Michael S. Williams; Mark J. Ducey; Mark J. Ducey

2005-01-01

Critical point relascope sampling is developed and shown to be design-unbiased for the estimation of log volume when used with point relascope sampling for downed coarse woody debris. The method is closely related to critical height sampling for standing trees when trees are first sampled with a wedge prism. Three alternative protocols for determining the critical...

Unbiased nonorthogonal bases for tomographic reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sainz, Isabel; Klimov, Andrei B.; Roa, Luis

2010-05-15

We have developed a general method for constructing a set of nonorthogonal bases with equal separations between all different basis states in prime dimensions. The results are that the corresponding biorthogonal counterparts are pairwise unbiased with the components of the original bases. Using these bases, we derive an explicit expression for the optimal tomography in nonorthogonal bases. A special two-dimensional case is analyzed separately.

Simultaneous unbiased estimates of multiple downed wood attributes in perpendicular distance sampling

Treesearch

Mark J. Ducey; Jeffrey H. Gove; Harry T. Valentine

2008-01-01

Perpendicular distance sampling (PDS) is a fast probability-proportional-to-size method for inventory of downed wood. However, previous development of PDS had limited the method to estimating only one variable (such as volume per hectare, or surface area per hectare) at a time. Here, we develop a general design-unbiased estimator for PDS. We then show how that...

The dependability of medical students' performance ratings as documented on in-training evaluations.

PubMed

van Barneveld, Christina

2005-03-01

To demonstrate an approach to obtain an unbiased estimate of the dependability of students' performance ratings during training, when the data-collection design includes nesting of student in rater, unbalanced nest sizes, and dependent observations. In 2003, two variance components analyses of in-training evaluation (ITE) report data were conducted using urGENOVA software. In the first analysis, the dependability for the nested and unbalanced data-collection design was calculated. In the second analysis, an approach using multiple generalizability studies was used to obtain an unbiased estimate of the student variance component, resulting in an unbiased estimate of dependability. Results suggested that there is bias in estimates of the dependability of students' performance on ITEs that are attributable to the data-collection design. When the bias was corrected, the results indicated that the dependability of ratings of student performance was almost zero. The combination of the multiple generalizability studies method and the use of specialized software provides an unbiased estimate of the dependability of ratings of student performance on ITE scores for data-collection designs that include nesting of student in rater, unbalanced nest sizes, and dependent observations.

Metabolic co-dependence drives the evolutionarily ancient Hydra-Chlorella symbiosis.

PubMed

Hamada, Mayuko; Schröder, Katja; Bathia, Jay; Kürn, Ulrich; Fraune, Sebastian; Khalturina, Mariia; Khalturin, Konstantin; Shinzato, Chuya; Satoh, Nori; Bosch, Thomas Cg

2018-05-31

Many multicellular organisms rely on symbiotic associations for support of metabolic activity, protection, or energy. Understanding the mechanisms involved in controlling such interactions remains a major challenge. In an unbiased approach we identified key players that control the symbiosis between Hydra viridissima and its photosynthetic symbiont Chlorella sp. A99. We discovered significant up-regulation of Hydra genes encoding a phosphate transporter and glutamine synthetase suggesting regulated nutrition supply between host and symbionts. Interestingly, supplementing the medium with glutamine temporarily supports in vitro growth of the otherwise obligate symbiotic Chlorella , indicating loss of autonomy and dependence on the host. Genome sequencing of Chlorella sp. A99 revealed a large number of amino acid transporters and a degenerated nitrate assimilation pathway, presumably as consequence of the adaptation to the host environment. Our observations portray ancient symbiotic interactions as a codependent partnership in which exchange of nutrients appears to be the primary driving force. © 2018, Hamada et al.

Personalised medicine in asthma: time for action: Number 1 in the Series "Personalised medicine in respiratory diseases" Edited by Renaud Louis and Nicolas Roche.

PubMed

Chung, Kian Fan

2017-09-30

Asthma is a heterogeneous disease comprising several phenotypes driven by different pathways. To define these phenotypes or endotypes (phenotypes defined by mechanisms), an unbiased approach to clustering of various omics platforms will yield molecular phenotypes from which composite biomarkers can be obtained. Biomarkers can help differentiate between these phenotypes and pinpoint patients suitable for specific targeted therapies - the basis for personalised medicine. Biomarkers need to be linked to point-of-care biomarkers that may be measured readily in exhaled breath, blood or urine. The potential for using mobile healthcare approaches will help patient enpowerment, an essential tool for personalised medicine. Personalised medicine in asthma is not far off - it is already here, but we need more tools and implements to carry it out for the benefit of our patients. Copyright ©ERS 2017.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Boundary Conditions for the Paleoenvironment: Chemical and Physical Processes in the Pre-Solar Nebula

NASA Technical Reports Server (NTRS)

Irvine, William M.; Schloerb, F. Peter

1997-01-01

The basic theme of this program is the study of molecular complexity and evolution in interstellar clouds and in primitive solar system objects. Research has included the detection and study of a number of new interstellar molecules and investigation of reaction pathways for astrochemistry from a comparison of theory and observed molecular abundances. The latter includes studies of cold, dark clouds in which ion-molecule chemistry should predominate, searches for the effects of interchange of material between the gas and solid phases in interstellar clouds, unbiased spectral surveys of particular sources, and systematic investigation of the interlinked chemistry and physics of dense interstellar clouds. In addition, the study of comets has allowed a comparison between the chemistry of such minimally thermally processed objects and that of interstellar clouds, shedding light on the evolution of the biogenic elements during the process of solar system formation.

LRRTM1 underlies synaptic convergence in visual thalamus

PubMed Central

Monavarfeshani, Aboozar; Stanton, Gail; Van Name, Jonathan; Su, Kaiwen; Mills, William A; Swilling, Kenya; Kerr, Alicia; Huebschman, Natalie A; Su, Jianmin

2018-01-01

It has long been thought that the mammalian visual system is organized into parallel pathways, with incoming visual signals being parsed in the retina based on feature (e.g. color, contrast and motion) and then transmitted to the brain in unmixed, feature-specific channels. To faithfully convey feature-specific information from retina to cortex, thalamic relay cells must receive inputs from only a small number of functionally similar retinal ganglion cells. However, recent studies challenged this by revealing substantial levels of retinal convergence onto relay cells. Here, we sought to identify mechanisms responsible for the assembly of such convergence. Using an unbiased transcriptomics approach and targeted mutant mice, we discovered a critical role for the synaptic adhesion molecule Leucine Rich Repeat Transmembrane Neuronal 1 (LRRTM1) in the emergence of retinothalamic convergence. Importantly, LRRTM1 mutant mice display impairment in visual behaviors, suggesting a functional role of retinothalamic convergence in vision. PMID:29424692

Data assimilation for groundwater flow modelling using Unbiased Ensemble Square Root Filter: Case study in Guantao, North China Plain

NASA Astrophysics Data System (ADS)

Li, N.; Kinzelbach, W.; Li, H.; Li, W.; Chen, F.; Wang, L.

2017-12-01

Data assimilation techniques are widely used in hydrology to improve the reliability of hydrological models and to reduce model predictive uncertainties. This provides critical information for decision makers in water resources management. This study aims to evaluate a data assimilation system for the Guantao groundwater flow model coupled with a one-dimensional soil column simulation (Hydrus 1D) using an Unbiased Ensemble Square Root Filter (UnEnSRF) originating from the Ensemble Kalman Filter (EnKF) to update parameters and states, separately or simultaneously. To simplify the coupling between unsaturated and saturated zone, a linear relationship obtained from analyzing inputs to and outputs from Hydrus 1D is applied in the data assimilation process. Unlike EnKF, the UnEnSRF updates parameter ensemble mean and ensemble perturbations separately. In order to keep the ensemble filter working well during the data assimilation, two factors are introduced in the study. One is called damping factor to dampen the update amplitude of the posterior ensemble mean to avoid nonrealistic values. The other is called inflation factor to relax the posterior ensemble perturbations close to prior to avoid filter inbreeding problems. The sensitivities of the two factors are studied and their favorable values for the Guantao model are determined. The appropriate observation error and ensemble size were also determined to facilitate the further analysis. This study demonstrated that the data assimilation of both model parameters and states gives a smaller model prediction error but with larger uncertainty while the data assimilation of only model states provides a smaller predictive uncertainty but with a larger model prediction error. Data assimilation in a groundwater flow model will improve model prediction and at the same time make the model converge to the true parameters, which provides a successful base for applications in real time modelling or real time controlling strategies in groundwater resources management.

Natural Hazards Observer. Volume 32, Number 2, November 2007

DTIC Science & Technology

2007-11-01

global warming plan that proposed an obligatory, market -based, cap-and-trade pro- gram that would reverse the worst-case effects of climate change by... market penetration for flood insurance, building Report (under Goal 4: "Lofty Targets"). and elevation requirements, hazard mitigation grants, The Report...reinsurance markets in subsequent years. With an unbiased perspective of all catastrophe model- 8th Pacific Conference on Earthquake Engineering-Sin- ing

Impact of rough potentials in rocked ratchet performance

NASA Astrophysics Data System (ADS)

Camargo, S.; Anteneodo, C.

2018-04-01

We consider thermal ratchets modeled by overdamped Brownian motion in a spatially periodic potential with a tilting process, both unbiased on average. We investigate the impact of the introduction of roughness in the potential profile, over the flux and efficiency of the ratchet. Both amplitude and wavelength that characterize roughness are varied. We show that depending on the ratchet parameters, rugosity can either spoil or enhance the ratchet performance.

Forest inventory predictions from individual tree crowns: regression modeling within a sample framework

Treesearch

James W. Flewelling

2009-01-01

Remotely sensed data can be used to make digital maps showing individual tree crowns (ITC) for entire forests. Attributes of the ITCs may include area, shape, height, and color. The crown map is sampled in a way that provides an unbiased linkage between ITCs and identifiable trees measured on the ground. Methods of avoiding edge bias are given. In an example from a...

Quantification of correlations in quantum many-particle systems.

PubMed

Byczuk, Krzysztof; Kuneš, Jan; Hofstetter, Walter; Vollhardt, Dieter

2012-02-24

We introduce a well-defined and unbiased measure of the strength of correlations in quantum many-particle systems which is based on the relative von Neumann entropy computed from the density operator of correlated and uncorrelated states. The usefulness of this general concept is demonstrated by quantifying correlations of interacting electrons in the Hubbard model and in a series of transition-metal oxides using dynamical mean-field theory.

Software for the grouped optimal aggregation technique

NASA Technical Reports Server (NTRS)

Brown, P. M.; Shaw, G. W. (Principal Investigator)

1982-01-01

The grouped optimal aggregation technique produces minimum variance, unbiased estimates of acreage and production for countries, zones (states), or any designated collection of acreage strata. It uses yield predictions, historical acreage information, and direct acreage estimate from satellite data. The acreage strata are grouped in such a way that the ratio model over historical acreage provides a smaller variance than if the model were applied to each individual stratum. An optimal weighting matrix based on historical acreages, provides the link between incomplete direct acreage estimates and the total, current acreage estimate.

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Fortune Favours the Bold: An Agent-Based Model Reveals Adaptive Advantages of Overconfidence in War

PubMed Central

Johnson, Dominic D. P.; Weidmann, Nils B.; Cederman, Lars-Erik

2011-01-01

Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These “adaptive advantages” of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today. PMID:21731627

Apparatus bias and place conditioning with ethanol in mice.

PubMed

Cunningham, Christopher L; Ferree, Nikole K; Howard, MacKenzie A

2003-12-01

Although the distinction between "biased" and "unbiased" is generally recognized as an important methodological issue in place conditioning, previous studies have not adequately addressed the distinction between a biased/unbiased apparatus and a biased/unbiased stimulus assignment procedure. Moreover, a review of the recent literature indicates that many reports (70% of 76 papers published in 2001) fail to provide adequate information about apparatus bias. This issue is important because the mechanisms underlying a drug's effect in the place-conditioning procedure may differ depending on whether the apparatus is biased or unbiased. The present studies were designed to assess the impact of apparatus bias and stimulus assignment procedure on ethanol-induced place conditioning in mice (DBA/2 J). A secondary goal was to compare various dependent variables commonly used to index conditioned place preference. Apparatus bias was manipulated by varying the combination of tactile (floor) cues available during preference tests. Experiment 1 used an unbiased apparatus in which the stimulus alternatives were equally preferred during a pre-test as indicated by the group average. Experiment 2 used a biased apparatus in which one of the stimuli was strongly preferred by most mice (mean % time on cue = 67%) during the pre-test. In both studies, the stimulus paired with drug (CS+) was assigned randomly (i.e., an "unbiased" stimulus assignment procedure). Experimental mice received four pairings of CS+ with ethanol (2 g/kg, i.p.) and four pairings of the alternative stimulus (CS-) with saline; control mice received saline on both types of trial. Each experiment concluded with a 60-min choice test. With the unbiased apparatus (experiment 1), significant place conditioning was obtained regardless of whether drug was paired with the subject's initially preferred or non-preferred stimulus. However, with the biased apparatus (experiment 2), place conditioning was apparent only when ethanol was paired with the initially non-preferred cue, and not when it was paired with the initially preferred cue. These conclusions held regardless of which dependent variable was used to index place conditioning, but only if the counterbalancing factor was included in statistical analyses. These studies indicate that apparatus bias plays a major role in determining whether biased assignment of an ethanol-paired stimulus affects ability to demonstrate conditioned place preference. Ethanol's ability to produce conditioned place preference in an unbiased apparatus, regardless of the direction of the initial cue bias, supports previous studies that interpret such findings as evidence of a primary rewarding drug effect. Moreover, these studies suggest that the asymmetrical outcome observed in the biased apparatus is most likely due to a measurement problem (e.g., ceiling effect) rather than to an interaction between the drug's effect and an unconditioned motivational response (e.g., "anxiety") to the initially non-preferred stimulus. More generally, these findings illustrate the importance of providing clear information on apparatus bias in all place-conditioning studies.

Biases in Metallicity Measurements from Global Galaxy Spectra: The Effects of Flux Weighting and Diffuse Ionized Gas Contamination

NASA Astrophysics Data System (ADS)

Sanders, Ryan L.; Shapley, Alice E.; Zhang, Kai; Yan, Renbin

2017-12-01

Galaxy metallicity scaling relations provide a powerful tool for understanding galaxy evolution, but obtaining unbiased global galaxy gas-phase oxygen abundances requires proper treatment of the various line-emitting sources within spectroscopic apertures. We present a model framework that treats galaxies as ensembles of H II and diffuse ionized gas (DIG) regions of varying metallicities. These models are based upon empirical relations between line ratios and electron temperature for H II regions, and DIG strong-line ratio relations from SDSS-IV MaNGA IFU data. Flux-weighting effects and DIG contamination can significantly affect properties inferred from global galaxy spectra, biasing metallicity estimates by more than 0.3 dex in some cases. We use observationally motivated inputs to construct a model matched to typical local star-forming galaxies, and quantify the biases in strong-line ratios, electron temperatures, and direct-method metallicities as inferred from global galaxy spectra relative to the median values of the H II region distributions in each galaxy. We also provide a generalized set of models that can be applied to individual galaxies or galaxy samples in atypical regions of parameter space. We use these models to correct for the effects of flux-weighting and DIG contamination in the local direct-method mass-metallicity and fundamental metallicity relations, and in the mass-metallicity relation based on strong-line metallicities. Future photoionization models of galaxy line emission need to include DIG emission and represent galaxies as ensembles of emitting regions with varying metallicity, instead of as single H II regions with effective properties, in order to obtain unbiased estimates of key underlying physical properties.

Class Enumeration and Parameter Recovery of Growth Mixture Modeling and Second-Order Growth Mixture Modeling in the Presence of Measurement Noninvariance between Latent Classes

PubMed Central

Kim, Eun Sook; Wang, Yan

2017-01-01

Population heterogeneity in growth trajectories can be detected with growth mixture modeling (GMM). It is common that researchers compute composite scores of repeated measures and use them as multiple indicators of growth factors (baseline performance and growth) assuming measurement invariance between latent classes. Considering that the assumption of measurement invariance does not always hold, we investigate the impact of measurement noninvariance on class enumeration and parameter recovery in GMM through a Monte Carlo simulation study (Study 1). In Study 2, we examine the class enumeration and parameter recovery of the second-order growth mixture modeling (SOGMM) that incorporates measurement models at the first order level. Thus, SOGMM estimates growth trajectory parameters with reliable sources of variance, that is, common factor variance of repeated measures and allows heterogeneity in measurement parameters between latent classes. The class enumeration rates are examined with information criteria such as AIC, BIC, sample-size adjusted BIC, and hierarchical BIC under various simulation conditions. The results of Study 1 showed that the parameter estimates of baseline performance and growth factor means were biased to the degree of measurement noninvariance even when the correct number of latent classes was extracted. In Study 2, the class enumeration accuracy of SOGMM depended on information criteria, class separation, and sample size. The estimates of baseline performance and growth factor mean differences between classes were generally unbiased but the size of measurement noninvariance was underestimated. Overall, SOGMM is advantageous in that it yields unbiased estimates of growth trajectory parameters and more accurate class enumeration compared to GMM by incorporating measurement models. PMID:28928691

A brain proteomic investigation of rapamycin effects in the Tsc1+/- mouse model.

PubMed

Wesseling, Hendrik; Elgersma, Ype; Bahn, Sabine

2017-01-01

Tuberous sclerosis complex (TSC) is a rare monogenic disorder characterized by benign tumors in multiple organs as well as a high prevalence of epilepsy, intellectual disability and autism. TSC is caused by inactivating mutations in the TSC1 or TSC2 genes. Heterozygocity induces hyperactivation of mTOR which can be inhibited by mTOR inhibitors, such as rapamycin, which have proven efficacy in the treatment of TSC-associated symptoms. The aim of the present study was (1) to identify molecular changes associated with social and cognitive deficits in the brain tissue of Tsc1 +/- mice and (2) to investigate the molecular effects of rapamycin treatment, which has been shown to ameliorate genotype-related behavioural deficits. Molecular alterations in the frontal cortex and hippocampus of Tsc1 +/- and control mice, with or without rapamycin treatment, were investigated. A quantitative mass spectrometry-based shotgun proteomic approach (LC-MS E ) was employed as an unbiased method to detect changes in protein levels. Changes identified in the initial profiling stage were validated using selected reaction monitoring (SRM). Protein Set Enrichment Analysis was employed to identify dysregulated pathways. LC-MS E analysis of Tsc1 +/- mice and controls ( n  = 30) identified 51 proteins changed in frontal cortex and 108 in the hippocampus. Bioinformatic analysis combined with targeted proteomic validation revealed several dysregulated molecular pathways. Using targeted assays, proteomic alterations in the hippocampus validated the pathways "myelination", "dendrite," and "oxidative stress", an upregulation of ribosomal proteins and the mTOR kinase. LC-MS E analysis was also employed on Tsc1 +/- and wildtype mice ( n  = 34) treated with rapamycin or vehicle. Rapamycin treatment exerted a stronger proteomic effect in Tsc1 +/- mice with significant changes (mainly decreased expression) in 231 and 106 proteins, respectively. The cellular pathways "oxidative stress" and "apoptosis" were found to be affected in Tsc1 +/- mice and the cellular compartments "myelin sheet" and "neurofilaments" were affected by rapamycin treatment. Thirty-three proteins which were altered in Tsc1 +/- mice were normalized following rapamycin treatment, amongst them oxidative stress related proteins, myelin-specific and ribosomal proteins. Molecular changes in the Tsc1 +/- mouse brain were more prominent in the hippocampus compared to the frontal cortex. Pathways linked to myelination and oxidative stress response were prominently affected and, at least in part, normalized following rapamycin treatment. The results could aid in the identification of novel drug targets for the treatment of cognitive, social and psychiatric symptoms in autism spectrum disorders. Similar pathways have also been implicated in other psychiatric and neurodegenerative disorders and could imply similar disease processes. Thus, the potential efficacy of mTOR inhibitors warrants further investigation not only for autism spectrum disorders but also for other neuropsychiatric and neurodegenerative diseases.

Generation and evaluation of an ultra-high-field atlas with applications in DBS planning

NASA Astrophysics Data System (ADS)

Wang, Brian T.; Poirier, Stefan; Guo, Ting; Parrent, Andrew G.; Peters, Terry M.; Khan, Ali R.

2016-03-01

Purpose Deep brain stimulation (DBS) is a common treatment for Parkinson's disease (PD) and involves the use of brain atlases or intrinsic landmarks to estimate the location of target deep brain structures, such as the subthalamic nucleus (STN) and the globus pallidus pars interna (GPi). However, these structures can be difficult to localize with conventional clinical magnetic resonance imaging (MRI), and thus targeting can be prone to error. Ultra-high-field imaging at 7T has the ability to clearly resolve these structures and thus atlases built with these data have the potential to improve targeting accuracy. Methods T1 and T2-weighted images of 12 healthy control subjects were acquired using a 7T MR scanner. These images were then used with groupwise registration to generate an unbiased average template with T1w and T2w contrast. Deep brain structures were manually labelled in each subject by two raters and rater reliability was assessed. We compared the use of this unbiased atlas with two other methods of atlas-based segmentation (single-template and multi-template) for subthalamic nucleus (STN) segmentation on 7T MRI data. We also applied this atlas to clinical DBS data acquired at 1.5T to evaluate its efficacy for DBS target localization as compared to using a standard atlas. Results The unbiased templates provide superb detail of subcortical structures. Through one-way ANOVA tests, the unbiased template is significantly (p <0.05) more accurate than a single-template in atlas-based segmentation and DBS target localization tasks. Conclusion The generated unbiased averaged templates provide better visualization of deep brain nuclei and an increase in accuracy over single-template and lower field strength atlases.

An Unbiased Method To Build Benchmarking Sets for Ligand-Based Virtual Screening and its Application To GPCRs

PubMed Central

2015-01-01

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the “artificial enrichment” and “analogue bias” of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD. PMID:24749745

An unbiased method to build benchmarking sets for ligand-based virtual screening and its application to GPCRs.

PubMed

Xia, Jie; Jin, Hongwei; Liu, Zhenming; Zhang, Liangren; Wang, Xiang Simon

2014-05-27

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the "artificial enrichment" and "analogue bias" of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns.

PubMed

Gruel, Jérémy; LeBorgne, Michel; LeMeur, Nolwenn; Théret, Nathalie

2011-09-12

Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks.

Simple Shared Motifs (SSM) in conserved region of promoters: a new approach to identify co-regulation patterns

PubMed Central

2011-01-01

Background Regulation of gene expression plays a pivotal role in cellular functions. However, understanding the dynamics of transcription remains a challenging task. A host of computational approaches have been developed to identify regulatory motifs, mainly based on the recognition of DNA sequences for transcription factor binding sites. Recent integration of additional data from genomic analyses or phylogenetic footprinting has significantly improved these methods. Results Here, we propose a different approach based on the compilation of Simple Shared Motifs (SSM), groups of sequences defined by their length and similarity and present in conserved sequences of gene promoters. We developed an original algorithm to search and count SSM in pairs of genes. An exceptional number of SSM is considered as a common regulatory pattern. The SSM approach is applied to a sample set of genes and validated using functional gene-set enrichment analyses. We demonstrate that the SSM approach selects genes that are over-represented in specific biological categories (Ontology and Pathways) and are enriched in co-expressed genes. Finally we show that genes co-expressed in the same tissue or involved in the same biological pathway have increased SSM values. Conclusions Using unbiased clustering of genes, Simple Shared Motifs analysis constitutes an original contribution to provide a clearer definition of expression networks. PMID:21910886

1H NMR-metabolomics: can they be a useful tool in our understanding of cardiac arrest?

PubMed

Chalkias, Athanasios; Fanos, Vassilios; Noto, Antonio; Castrén, Maaret; Gulati, Anil; Svavarsdóttir, Hildigunnur; Iacovidou, Nicoletta; Xanthos, Theodoros

2014-05-01

This review focuses on the presentation of the emerging technology of metabolomics, a promising tool for the detection of identifying the unrevealed biological pathways that lead to cardiac arrest. The electronic bases of PubMed, Scopus, and EMBASE were searched. Research terms were identified using the MESH database and were combined thereafter. Initial search terms were "cardiac arrest", "cardiopulmonary resuscitation", "post-cardiac arrest syndrome" combined with "metabolomics". Metabolomics allow the monitoring of hundreds of metabolites from tissues or body fluids and already influence research in the field of cardiac metabolism. This approach has elucidated several pathophysiological mechanisms and identified profiles of metabolic changes that can be used to follow the disease processes occurring in the peri-arrest period. This can be achieved through leveraging the strengths of unbiased metabolome-wide scans, which include thousands of final downstream products of gene transcription, enzyme activity and metabolic products of extraneously administered substances, in order to identify a metabolomic fingerprint associated with an increased risk of cardiac arrest. Although this technology is still under development, metabolomics is a promising tool for elucidating biological pathways and discovering clinical biomarkers, strengthening the efforts for optimizing both the prevention and treatment of cardiac arrest. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Statistical assessment of crosstalk enrichment between gene groups in biological networks.

PubMed

McCormack, Theodore; Frings, Oliver; Alexeyenko, Andrey; Sonnhammer, Erik L L

2013-01-01

Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). CrossTalkZ (available at http://sonnhammer.sbc.su.se/download/software/CrossTalkZ/) is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

Transcriptional control of the autophagy-lysosome system in pancreatic cancer

PubMed Central

Perera, Rushika M.; Stoykova, Svetlana; Nicolay, Brandon N.; Ross, Kenneth N.; Fitamant, Julien; Boukhali, Myriam; Lengrand, Justine; Deshpande, Vikram; Selig, Martin K.; Ferrone, Cristina R.; Settleman, Jeff; Stephanopoulos, Gregory; Dyson, Nicholas J.; Zoncu, Roberto; Ramaswamy, Sridhar; Haas, Wilhelm; Bardeesy, Nabeel

2016-01-01

Activation of cellular stress response pathways to maintain metabolic homeostasis is emerging as a critical growth and survival mechanism in many cancers1. The pathogenesis of pancreatic ductal adenocarcinoma (PDA) requires high levels of autophagy2–4, a conserved self-degradative process5. However, the regulatory circuits that activate autophagy and reprogram PDA cell metabolism are unknown. We now show that autophagy induction in PDA occurs as part of a broader transcriptional program that coordinates activation of lysosome biogenesis and function, and nutrient scavenging, mediated by the MiT/TFE family transcription factors. In PDA cells, the MiT/TFE proteins6 – MITF, TFE3 and TFEB – are decoupled from regulatory mechanisms that control their cytoplasmic retention. Increased nuclear import in turn drives the expression of a coherent network of genes that induce high levels of lysosomal catabolic function essential for PDA growth. Unbiased global metabolite profiling reveals that MiT/TFE-dependent autophagy-lysosomal activation is specifically required to maintain intracellular amino acid (AA) pools. These results identify the MiT/TFE transcription factors as master regulators of metabolic reprogramming in pancreatic cancer and demonstrate activation of clearance pathways converging on the lysosome as a novel hallmark of aggressive malignancy. PMID:26168401

Current and efficiency of Brownian particles under oscillating forces in entropic barriers

NASA Astrophysics Data System (ADS)

Nutku, Ferhat; Aydιner, Ekrem

2015-04-01

In this study, considering the temporarily unbiased force and different forms of oscillating forces, we investigate the current and efficiency of Brownian particles in an entropic tube structure and present the numerically obtained results. We show that different force forms give rise to different current and efficiency profiles in different optimized parameter intervals. We find that an unbiased oscillating force and an unbiased temporal force lead to the current and efficiency, which are dependent on these parameters. We also observe that the current and efficiency caused by temporal and different oscillating forces have maximum and minimum values in different parameter intervals. We conclude that the current or efficiency can be controlled dynamically by adjusting the parameters of entropic barriers and applied force. Project supported by the Funds from Istanbul University (Grant No. 45662).

An Example of an Improvable Rao-Blackwell Improvement, Inefficient Maximum Likelihood Estimator, and Unbiased Generalized Bayes Estimator.

PubMed

Galili, Tal; Meilijson, Isaac

2016-01-02

The Rao-Blackwell theorem offers a procedure for converting a crude unbiased estimator of a parameter θ into a "better" one, in fact unique and optimal if the improvement is based on a minimal sufficient statistic that is complete. In contrast, behind every minimal sufficient statistic that is not complete, there is an improvable Rao-Blackwell improvement. This is illustrated via a simple example based on the uniform distribution, in which a rather natural Rao-Blackwell improvement is uniformly improvable. Furthermore, in this example the maximum likelihood estimator is inefficient, and an unbiased generalized Bayes estimator performs exceptionally well. Counterexamples of this sort can be useful didactic tools for explaining the true nature of a methodology and possible consequences when some of the assumptions are violated. [Received December 2014. Revised September 2015.].

Quantum key distribution for composite dimensional finite systems

NASA Astrophysics Data System (ADS)

Shalaby, Mohamed; Kamal, Yasser

2017-06-01

The application of quantum mechanics contributes to the field of cryptography with very important advantage as it offers a mechanism for detecting the eavesdropper. The pioneering work of quantum key distribution uses mutually unbiased bases (MUBs) to prepare and measure qubits (or qudits). Weak mutually unbiased bases (WMUBs) have weaker properties than MUBs properties, however, unlike MUBs, a complete set of WMUBs can be constructed for systems with composite dimensions. In this paper, we study the use of weak mutually unbiased bases (WMUBs) in quantum key distribution for composite dimensional finite systems. We prove that the security analysis of using a complete set of WMUBs to prepare and measure the quantum states in the generalized BB84 protocol, gives better results than using the maximum number of MUBs that can be constructed, when they are analyzed against the intercept and resend attack.

A hidden-process model for estimating prespawn mortality using carcass survey data

USGS Publications Warehouse

DeWeber, J. Tyrell; Peterson, James T.; Sharpe, Cameron; Kent, Michael L.; Colvin, Michael E.; Schreck, Carl B.

2017-01-01

After returning to spawning areas, adult Pacific salmon Oncorhynchus spp. often die without spawning successfully, which is commonly referred to as prespawn mortality. Prespawn mortality reduces reproductive success and can thereby hamper conservation, restoration, and reintroduction efforts. The primary source of information used to estimate prespawn mortality is collected through carcass surveys, but estimation can be difficult with these data due to imperfect detection and carcasses with unknown spawning status. To facilitate unbiased estimation of prespawn mortality and associated uncertainty, we developed a hidden-process mark–recovery model to estimate prespawn mortality rates from carcass survey data while accounting for imperfect detection and unknown spawning success. We then used the model to estimate prespawn mortality and identify potential associated factors for 3,352 adult spring Chinook Salmon O. tshawytscha that were transported above Foster Dam on the South Santiam River (Willamette River basin, Oregon) from 2009 to 2013. Estimated prespawn mortality was relatively low (≤13%) in most years (interannual mean = 28%) but was especially high (74%) in 2013. Variation in prespawn mortality estimates among outplanted groups of fish within each year was also very high, and some of this variation was explained by a trend toward lower prespawn mortality among fish that were outplanted later in the year. Numerous efforts are being made to monitor and, when possible, minimize prespawn mortality in salmon populations; this model can be used to provide unbiased estimates of spawning success that account for unknown fate and imperfect detection, which are common to carcass survey data.

Flat-Sky Pseudo-Cls Analysis for Weak Gravitational Lensing

NASA Astrophysics Data System (ADS)

Asgari, Marika; Taylor, Andy; Joachimi, Benjamin; Kitching, Thomas D.

2018-05-01

We investigate the use of estimators of weak lensing power spectra based on a flat-sky implementation of the 'Pseudo-CI' (PCl) technique, where the masked shear field is transformed without regard for masked regions of sky. This masking mixes power, and 'E'-convergence and 'B'-modes. To study the accuracy of forward-modelling and full-sky power spectrum recovery we consider both large-area survey geometries, and small-scale masking due to stars and a checkerboard model for field-of-view gaps. The power spectrum for the large-area survey geometry is sparsely-sampled and highly oscillatory, which makes modelling problematic. Instead, we derive an overall calibration for large-area mask bias using simulated fields. The effects of small-area star masks can be accurately corrected for, while the checkerboard mask has oscillatory and spiky behaviour which leads to percent biases. Apodisation of the masked fields leads to increased biases and a loss of information. We find that we can construct an unbiased forward-model of the raw PCls, and recover the full-sky convergence power to within a few percent accuracy for both Gaussian and lognormal-distributed shear fields. Propagating this through to cosmological parameters using a Fisher-Matrix formalism, we find we can make unbiased estimates of parameters for surveys up to 1,200 deg2 with 30 galaxies per arcmin2, beyond which the percent biases become larger than the statistical accuracy. This implies a flat-sky PCl analysis is accurate for current surveys but a Euclid-like survey will require higher accuracy.

Unbiased total electron content (UTEC), their fluctuations, and correlation with seismic activity over Japan

NASA Astrophysics Data System (ADS)

Cornely, Pierre-Richard; Hughes, John

2018-02-01

Earthquakes are among the most dangerous events that occur on earth and many scientists have been investigating the underlying processes that take place before earthquakes occur. These investigations are fueling efforts towards developing both single and multiple parameter earthquake forecasting methods based on earthquake precursors. One potential earthquake precursor parameter that has received significant attention within the last few years is the ionospheric total electron content (TEC). Despite its growing popularity as an earthquake precursor, TEC has been under great scrutiny because of the underlying biases associated with the process of acquiring and processing TEC data. Future work in the field will need to demonstrate our ability to acquire TEC data with the least amount of biases possible thereby preserving the integrity of the data. This paper describes a process for removing biases using raw TEC data from the standard Rinex files obtained from any global positioning satellites system. The process is based on developing an unbiased TEC (UTEC) data and model that can be more adaptable to serving as a precursor signal for earthquake forecasting. The model was used during the days and hours leading to the earthquake off the coast of Tohoku, Japan on March 11, 2011 with interesting results. The model takes advantage of the large amount of data available from the GPS Earth Observation Network of Japan to display near real-time UTEC data as the earthquake approaches and for a period of time after the earthquake occurred.

Correlations of the IR Luminosity and Eddington Ratio with a Hard X-ray Selected Sample of AGN

NASA Technical Reports Server (NTRS)

Mushotzy, Richard F.; Winter, Lisa M.; McIntosh, Daniel H.; Tueller, Jack

2008-01-01

We use the SWIFT Burst Alert Telescope (BAT) sample of hard x-ray selected active galactic nuclei (AGN) with a median redshift of 0.03 and the 2MASS J and K band photometry to examine the correlation of hard x-ray emission to Eddington ratio as well as the relationship of the J and K band nuclear luminosity to the hard x-ray luminosity. The BAT sample is almost unbiased by the effects of obscuration and thus offers the first large unbiased sample for the examination of correlations between different wavelength bands. We find that the near-IR nuclear J and K band luminosity is related to the BAT (14 - 195 keV) luminosity over a factor of 10(exp 3) in luminosity (L(sub IR) approx.equals L(sub BAT)(sup 1.25) and thus is unlikely to be due to dust. We also find that the Eddington ratio is proportional to the x-ray luminosity. This new result should be a strong constraint on models of the formation of the broad band continuum.

Impurity-induced anisotropic semiconductor-semimetal transition in monolayer biased black phosphorus

NASA Astrophysics Data System (ADS)

Bui, D. H.; Yarmohammadi, Mohsen

2018-07-01

Taking into account the electron-impurity interaction within the continuum approximation of tight-binding model, the Born approximation, and the Green's function method, the main features of anisotropic electronic phase transition are investigated in monolayer biased black phosphorus (BP). To this end, we concentrated on the disordered electronic density of states (DOS), which gives useful information for electro-optical devices. Increasing the impurity concentration in both unbiased and biased impurity-infected single-layer BP, in addition to the decrease of the band gap, independent of the direction, leads to the midgap states and an extra Van Hove singularity inside and outside of the band gap, respectively. Furthermore, strong impurity scattering potentials lead to a semiconductor-semimetal transition and one more Van Hove singularity in x-direction of unbiased BP and surprisingly, this transition does not occur in biased BP. We found that there is no phase transition in y-direction. Since real applications require structures with modulated band gaps, we have studied the influence of different bias voltages on the disordered DOS in both directions, resulting in the increase of the band gap.

New Approach for Investigating Reaction Dynamics and Rates with Ab Initio Calculations.

PubMed

Fleming, Kelly L; Tiwary, Pratyush; Pfaendtner, Jim

2016-01-21

Herein, we demonstrate a convenient approach to systematically investigate chemical reaction dynamics using the metadynamics (MetaD) family of enhanced sampling methods. Using a symmetric SN2 reaction as a model system, we applied infrequent metadynamics, a theoretical framework based on acceleration factors, to quantitatively estimate the rate of reaction from biased and unbiased simulations. A systematic study of the algorithm and its application to chemical reactions was performed by sampling over 5000 independent reaction events. Additionally, we quantitatively reweighed exhaustive free-energy calculations to obtain the reaction potential-energy surface and showed that infrequent metadynamics works to effectively determine Arrhenius-like activation energies. Exact agreement with unbiased high-temperature kinetics is also shown. The feasibility of using the approach on actual ab initio molecular dynamics calculations is then presented by using Car-Parrinello MD+MetaD to sample the same reaction using only 10-20 calculations of the rare event. Owing to the ease of use and comparatively low-cost of computation, the approach has extensive potential applications for catalysis, combustion, pyrolysis, and enzymology.

A Note on NCOM Temperature Forecast Error Calibration Using the Ensemble Transform

DTIC Science & Technology

2009-01-01

Division Head Ruth H. Preller, 7300 Security, Code 1226 Office of Counsel,Code 1008.3 ADOR/Director NCST E. R. Franchi , 7000 Public Affairs...problem, local unbiased (correlation) and persistent errors (bias) of the Navy Coastal Ocean Modeling (NCOM) System nested in global ocean domains, are...system were made available in real-time without performing local data assimilation, though remote sensing and global data was assimilated on the

Equilibrium Free Energies from Nonequilibrium Metadynamics

NASA Astrophysics Data System (ADS)

Bussi, Giovanni; Laio, Alessandro; Parrinello, Michele

2006-03-01

In this Letter we propose a new formalism to map history-dependent metadynamics in a Markovian process. We apply this formalism to model Langevin dynamics and determine the equilibrium distribution of a collection of simulations. We demonstrate that the reconstructed free energy is an unbiased estimate of the underlying free energy and analytically derive an expression for the error. The present results can be applied to other history-dependent stochastic processes, such as Wang-Landau sampling.

Unbiased Estimation of Refractive State of Aberrated Eyes

PubMed Central

Martin, Jesson; Vasudevan, Balamurali; Himebaugh, Nikole; Bradley, Arthur; Thibos, Larry

2011-01-01

To identify unbiased methods for estimating the target vergence required to maximize visual acuity based on wavefront aberration measurements. Experiments were designed to minimize the impact of confounding factors that have hampered previous research. Objective wavefront refractions and subjective acuity refractions were obtained for the same monochromatic wavelength. Accommodation and pupil fluctuations were eliminated by cycloplegia. Unbiased subjective refractions that maximize visual acuity for high contrast letters were performed with a computer controlled forced choice staircase procedure, using 0.125 diopter steps of defocus. All experiments were performed for two pupil diameters (3mm and 6mm). As reported in the literature, subjective refractive error does not change appreciably when the pupil dilates. For 3 mm pupils most metrics yielded objective refractions that were about 0.1D more hyperopic than subjective acuity refractions. When pupil diameter increased to 6 mm, this bias changed in the myopic direction and the variability between metrics also increased. These inaccuracies were small compared to the precision of the measurements, which implies that most metrics provided unbiased estimates of refractive state for medium and large pupils. A variety of image quality metrics may be used to determine ocular refractive state for monochromatic (635nm) light, thereby achieving accurate results without the need for empirical correction factors. PMID:21777601

Circulating tumor cell detection: A direct comparison between negative and unbiased enrichment in lung cancer.

PubMed

Xu, Yan; Liu, Biao; Ding, Fengan; Zhou, Xiaodie; Tu, Pin; Yu, Bo; He, Yan; Huang, Peilin

2017-06-01

Circulating tumor cells (CTCs), isolated as a 'liquid biopsy', may provide important diagnostic and prognostic information. Therefore, rapid, reliable and unbiased detection of CTCs are required for routine clinical analyses. It was demonstrated that negative enrichment, an epithelial marker-independent technique for isolating CTCs, exhibits a better efficiency in the detection of CTCs compared with positive enrichment techniques that only use specific anti-epithelial cell adhesion molecules. However, negative enrichment techniques incur significant cell loss during the isolation procedure, and as it is a method that uses only one type of antibody, it is inherently biased. The detection procedure and identification of cell types also relies on skilled and experienced technicians. In the present study, the detection sensitivity of using negative enrichment and a previously described unbiased detection method was compared. The results revealed that unbiased detection methods may efficiently detect >90% of cancer cells in blood samples containing CTCs. By contrast, only 40-60% of CTCs were detected by negative enrichment. Additionally, CTCs were identified in >65% of patients with stage I/II lung cancer. This simple yet efficient approach may achieve a high level of sensitivity. It demonstrates a potential for the large-scale clinical implementation of CTC-based diagnostic and prognostic strategies.

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

Yeast Tolerance to Various Stresses Relies on the Trehalose-6P Synthase (Tps1) Protein, Not on Trehalose*

PubMed Central

Petitjean, Marjorie; Teste, Marie-Ange; François, Jean M.; Parrou, Jean-Luc

2015-01-01

Trehalose is a stable disaccharide commonly found in nature, from bacteria to fungi and plants. For the model yeast Saccharomyces cerevisiae, claims that trehalose is a stress protectant were based indirectly either on correlation between accumulation of trehalose and high resistance to various stresses or on stress hypersensitivity of mutants deleted for TPS1, which encodes the first enzyme in trehalose biosynthetic pathway. Our goal was to investigate more directly which one, between trehalose and/or the Tps1 protein, may serve yeast cells to withstand exposure to stress. By employing an original strategy that combined the use of mutant strains expressing catalytically inactive variants of Tps1, with MAL+ yeast strains able to accumulate trehalose from an exogenous supply, we bring for the first time unbiased proof that trehalose does not protect yeast cells from dying and that the stress-protecting role of trehalose in this eukaryotic model was largely overestimated. Conversely, we identified the Tps1 protein as a key player for yeast survival in response to temperature, oxidative, and desiccation stress. We also showed by robust RT-quantitative PCR and genetic interaction analysis that the role of Tps1 in thermotolerance is not dependent upon Hsf1-dependent transcription activity. Finally, our results revealed that the Tps1 protein is essential to maintain ATP levels during heat shock. Altogether, these findings supported the idea that Tps1 is endowed with a regulatory function in energy homeostasis, which is essential to withstand adverse conditions and maintain cellular integrity. PMID:25934390

Protein Expression Profile of Rat Type Two Alveolar Epithelial Cells During Hyperoxic Stress and Recovery

NASA Astrophysics Data System (ADS)

Bhargava, Maneesh

Rationale: In rodent model systems, the sequential changes in lung morphology resulting from hyperoxic injury are well characterized, and are similar to changes in human acute respiratory distress syndrome (ARDS). In the injured lung, alveolar type two (AT2) epithelial cells play a critical role restoring the normal alveolar structure. Thus characterizing the changes in AT2 cells will provide insights into the mechanisms underpinning the recovery from lung injury. Methods: We applied an unbiased systems level proteomics approach to elucidate molecular mechanisms contributing to lung repair in a rat hyperoxic lung injury model. AT2 cells were isolated from rat lungs at predetermined intervals during hyperoxic injury and recovery. Protein expression profiles were determined by using iTRAQRTM with tandem mass spectrometry. Results: Of 959 distinct proteins identified, 183 significantly changed in abundance during the injury-recovery cycle. Gene Ontology enrichment analysis identified cell cycle, cell differentiation, cell metabolism, ion homeostasis, programmed cell death, ubiquitination, and cell migration to be significantly enriched by these proteins. Gene Set Enrichment Analysis of data acquired during lung repair revealed differential expression of gene sets that control multicellular organismal development, systems development, organ development, and chemical homeostasis. More detailed analysis identified activity in two regulatory pathways, JNK and miR 374. A Short Time-series Expression Miner (STEM) algorithm identified protein clusters with coherent changes during injury and repair. Conclusion: Coherent changes occur in the AT2 cell proteome in response to hyperoxic stress. These findings offer guidance regarding the specific molecular mechanisms governing repair of the injured lung.

DPY-17 and MUA-3 Interact for Connective Tissue-Like Tissue Integrity in Caenorhabditis elegans: A Model for Marfan Syndrome.

PubMed

Fotopoulos, Pauline; Kim, Jeongho; Hyun, Moonjung; Qamari, Waiss; Lee, Inhwan; You, Young-Jai

2015-04-27

mua-3 is a Caenorhabditis elegans homolog of the mammalian fibrillin1, a monogenic cause of Marfan syndrome. We identified a new mutation of mua-3 that carries an in-frame deletion of 131 amino acids in the extracellular domain, which allows the mutants to survive in a temperature-dependent manner; at the permissive temperature, the mutants grow normally without obvious phenotypes, but at the nonpermissive temperature, more than 90% die during the L4 molt due to internal organ detachment. Using the temperature-sensitive lethality, we performed unbiased genetic screens to isolate suppressors to find genetic interactors of MUA-3. From two independent screens, we isolated mutations in dpy-17 as a suppressor. RNAi of dpy-17 in mua-3 rescued the lethality, confirming dpy-17 is a suppressor. dpy-17 encodes a collagen known to genetically interact with dpy-31, a BMP-1/Tolloid-like metalloprotease required for TGFβ activation in mammals. Human fibrillin1 mutants fail to sequester TGFβ2 leading to excess TGFβ signaling, which in turn contributes to Marfan syndrome or Marfan-related syndrome. Consistent with that, RNAi of dbl-1, a TGFβ homolog, modestly rescued the lethality of mua-3 mutants, suggesting a potentially conserved interaction between MUA-3 and a TGFβ pathway in C. elegans. Our work provides genetic evidence of the interaction between TGFβ and a fibrillin homolog, and thus provides a simple yet powerful genetic model to study TGFβ function in development of Marfan pathology. Copyright © 2015 Fotopoulos et al.

ESTIMATING TREATMENT EFFECTS ON HEALTHCARE COSTS UNDER EXOGENEITY: IS THERE A ‘MAGIC BULLET’?

PubMed Central

Polsky, Daniel; Manning, Willard G.

2011-01-01

Methods for estimating average treatment effects, under the assumption of no unmeasured confounders, include regression models; propensity score adjustments using stratification, weighting, or matching; and doubly robust estimators (a combination of both). Researchers continue to debate about the best estimator for outcomes such as health care cost data, as they are usually characterized by an asymmetric distribution and heterogeneous treatment effects,. Challenges in finding the right specifications for regression models are well documented in the literature. Propensity score estimators are proposed as alternatives to overcoming these challenges. Using simulations, we find that in moderate size samples (n= 5000), balancing on propensity scores that are estimated from saturated specifications can balance the covariate means across treatment arms but fails to balance higher-order moments and covariances amongst covariates. Therefore, unlike regression model, even if a formal model for outcomes is not required, propensity score estimators can be inefficient at best and biased at worst for health care cost data. Our simulation study, designed to take a ‘proof by contradiction’ approach, proves that no one estimator can be considered the best under all data generating processes for outcomes such as costs. The inverse-propensity weighted estimator is most likely to be unbiased under alternate data generating processes but is prone to bias under misspecification of the propensity score model and is inefficient compared to an unbiased regression estimator. Our results show that there are no ‘magic bullets’ when it comes to estimating treatment effects in health care costs. Care should be taken before naively applying any one estimator to estimate average treatment effects in these data. We illustrate the performance of alternative methods in a cost dataset on breast cancer treatment. PMID:22199462

Effects of sample size on estimates of population growth rates calculated with matrix models.

PubMed

Fiske, Ian J; Bruna, Emilio M; Bolker, Benjamin M

2008-08-28

Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.

Why do Models Overestimate Surface Ozone in the Southeastern United States?

NASA Astrophysics Data System (ADS)

Travis, K.; Jacob, D.; Fisher, J. A.; Kim, S.; Marais, E. A.; Zhu, L.; Yu, K.; Miller, C. E.; Yantosca, R.; Payer Sulprizio, M.; Thompson, A. M.; Wennberg, P. O.; Crounse, J.; St Clair, J. M.; Cohen, R. C.; Laughner, J.; Dibb, J. E.; Hall, S. R.; Ullmann, K.; Wolfe, G.; Pollack, I. B.; Peischl, J.; Neuman, J. A.; Zhou, X.

2016-12-01

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx = NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO­x from the US Environmental Protection Agency (EPA) is too high in the Southeast and nationally by a factor of 2. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Upper tropospheric NO2 from lightning makes a large contribution to the satellite observations that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This may be caused by excessively dry conditions in the model, representing another factor important in the simulation of surface ozone.

Developing Novel Therapeutics Targeting Undifferentiated and Castration-Resistant Prostate Cancer Stem Cells

DTIC Science & Technology

2016-10-01

identify PCSC- specific homing peptides ; and 2) To perform unbiased drug library screening to identify novel PCSC-targeting chemicals. In the past...display library (PDL) screening in PSA-/lo PCa cells to identify PCSC- specific homing peptides ; and 2) To perform unbiased drug library screening to...Goals of the Project (SOW): Aim 1: To perform phage display library (PDL) screening in PSA-/lo PCa cells to identify PCSC- specific homing peptides

What Do We Know about Using Value-Added to Compare Teachers Who Work in Different Schools? What We Know Series: Value-Added Methods and Applications. Knowledge Brief 10

ERIC Educational Resources Information Center

Raudenbush, Stephen

2013-01-01

This brief considers the problem of using value-added scores to compare teachers who work in different schools. The author focuses on whether such comparisons can be regarded as fair, or, in statistical language, "unbiased." An unbiased measure does not systematically favor teachers because of the backgrounds of the students they are…

Long Term Follow up of the Delayed Effects of Acute Radiation Exposure in Primates

DTIC Science & Technology

2017-10-01

66 of 94 We will then use shRNAs and/or CRISPR constructs targeting the gene of interest to knock down its expression in stem cells prior to...DLBCLs Mutational profiling identifies 150 driver genes Gene expression identifies sub- groups including cell of origin Unbiased CRISPR screen...Exome sequencing in 1,001 DLBCL patients comprehensively identifies 150 driver genes d Unbiased CRISPR screen in DLBCL cell lines identifies essential

A Simple Joint Estimation Method of Residual Frequency Offset and Sampling Frequency Offset for DVB Systems

NASA Astrophysics Data System (ADS)

Kwon, Ki-Won; Cho, Yongsoo

This letter presents a simple joint estimation method for residual frequency offset (RFO) and sampling frequency offset (STO) in OFDM-based digital video broadcasting (DVB) systems. The proposed method selects a continual pilot (CP) subset from an unsymmetrically and non-uniformly distributed CP set to obtain an unbiased estimator. Simulation results show that the proposed method using a properly selected CP subset is unbiased and performs robustly.

Test of mutually unbiased bases for six-dimensional photonic quantum systems

PubMed Central

D'Ambrosio, Vincenzo; Cardano, Filippo; Karimi, Ebrahim; Nagali, Eleonora; Santamato, Enrico; Marrucci, Lorenzo; Sciarrino, Fabio

2013-01-01

In quantum information, complementarity of quantum mechanical observables plays a key role. The eigenstates of two complementary observables form a pair of mutually unbiased bases (MUBs). More generally, a set of MUBs consists of bases that are all pairwise unbiased. Except for specific dimensions of the Hilbert space, the maximal sets of MUBs are unknown in general. Even for a dimension as low as six, the identification of a maximal set of MUBs remains an open problem, although there is strong numerical evidence that no more than three simultaneous MUBs do exist. Here, by exploiting a newly developed holographic technique, we implement and test different sets of three MUBs for a single photon six-dimensional quantum state (a “qusix”), encoded exploiting polarization and orbital angular momentum of photons. A close agreement is observed between theory and experiments. Our results can find applications in state tomography, quantitative wave-particle duality, quantum key distribution. PMID:24067548

Test of mutually unbiased bases for six-dimensional photonic quantum systems.

PubMed

D'Ambrosio, Vincenzo; Cardano, Filippo; Karimi, Ebrahim; Nagali, Eleonora; Santamato, Enrico; Marrucci, Lorenzo; Sciarrino, Fabio

2013-09-25

In quantum information, complementarity of quantum mechanical observables plays a key role. The eigenstates of two complementary observables form a pair of mutually unbiased bases (MUBs). More generally, a set of MUBs consists of bases that are all pairwise unbiased. Except for specific dimensions of the Hilbert space, the maximal sets of MUBs are unknown in general. Even for a dimension as low as six, the identification of a maximal set of MUBs remains an open problem, although there is strong numerical evidence that no more than three simultaneous MUBs do exist. Here, by exploiting a newly developed holographic technique, we implement and test different sets of three MUBs for a single photon six-dimensional quantum state (a "qusix"), encoded exploiting polarization and orbital angular momentum of photons. A close agreement is observed between theory and experiments. Our results can find applications in state tomography, quantitative wave-particle duality, quantum key distribution.

Graph-state formalism for mutually unbiased bases

NASA Astrophysics Data System (ADS)

Spengler, Christoph; Kraus, Barbara

2013-11-01

A pair of orthonormal bases is called mutually unbiased if all mutual overlaps between any element of one basis and an arbitrary element of the other basis coincide. In case the dimension, d, of the considered Hilbert space is a power of a prime number, complete sets of d+1 mutually unbiased bases (MUBs) exist. Here we present a method based on the graph-state formalism to construct such sets of MUBs. We show that for n p-level systems, with p being prime, one particular graph suffices to easily construct a set of pn+1 MUBs. In fact, we show that a single n-dimensional vector, which is associated with this graph, can be used to generate a complete set of MUBs and demonstrate that this vector can be easily determined. Finally, we discuss some advantages of our formalism regarding the analysis of entanglement structures in MUBs, as well as experimental realizations.

Mutually unbiased coarse-grained measurements of two or more phase-space variables

NASA Astrophysics Data System (ADS)

Paul, E. C.; Walborn, S. P.; Tasca, D. S.; Rudnicki, Łukasz

2018-05-01

Mutual unbiasedness of the eigenstates of phase-space operators—such as position and momentum, or their standard coarse-grained versions—exists only in the limiting case of infinite squeezing. In Phys. Rev. Lett. 120, 040403 (2018), 10.1103/PhysRevLett.120.040403, it was shown that mutual unbiasedness can be recovered for periodic coarse graining of these two operators. Here we investigate mutual unbiasedness of coarse-grained measurements for more than two phase-space variables. We show that mutual unbiasedness can be recovered between periodic coarse graining of any two nonparallel phase-space operators. We illustrate these results through optics experiments, using the fractional Fourier transform to prepare and measure mutually unbiased phase-space variables. The differences between two and three mutually unbiased measurements is discussed. Our results contribute to bridging the gap between continuous and discrete quantum mechanics, and they could be useful in quantum-information protocols.

Dynamics and Instabilities of the Shastry-Sutherland Model

NASA Astrophysics Data System (ADS)

Wang, Zhentao; Batista, Cristian D.

2018-06-01

We study the excitation spectrum in the dimer phase of the Shastry-Sutherland model by using an unbiased variational method that works in the thermodynamic limit. The method outputs dynamical correlation functions in all possible channels. This output is exploited to identify the order parameters with the highest susceptibility (single or multitriplon condensation in a specific channel) upon approaching a quantum phase transition in the magnetic field versus the J'/J phase diagram. We find four different instabilities: antiferro spin nematic, plaquette spin nematic, stripe magnetic order, and plaquette order, two of which have been reported in previous studies.

The dynamics of sex ratio evolution: from the gene perspective to multilevel selection.

PubMed

Argasinski, Krzysztof

2013-01-01

The new dynamical game theoretic model of sex ratio evolution emphasizes the role of males as passive carriers of sex ratio genes. This shows inconsistency between population genetic models of sex ratio evolution and classical strategic models. In this work a novel technique of change of coordinates will be applied to the new model. This will reveal new aspects of the modelled phenomenon which cannot be shown or proven in the original formulation. The underlying goal is to describe the dynamics of selection of particular genes in the entire population, instead of in the same sex subpopulation, as in the previous paper and earlier population genetics approaches. This allows for analytical derivation of the unbiased strategic model from the model with rigorous non-simplified genetics. In effect, an alternative system of replicator equations is derived. It contains two subsystems: the first describes changes in gene frequencies (this is an alternative unbiased formalization of the Fisher-Dusing argument), whereas the second describes changes in the sex ratios in subpopulations of carriers of genes for each strategy. An intriguing analytical result of this work is that the fitness of a gene depends on the current sex ratio in the subpopulation of its carriers, not on the encoded individual strategy. Thus, the argument of the gene fitness function is not constant but is determined by the trajectory of the sex ratio among carriers of that gene. This aspect of the modelled phenomenon cannot be revealed by the static analysis. Dynamics of the sex ratio among gene carriers is driven by a dynamic "tug of war" between female carriers expressing the encoded strategic trait value and random partners of male carriers expressing the average population strategy (a primary sex ratio). This mechanism can be called "double-level selection". Therefore, gene interest perspective leads to multi-level selection.

Nonlinear Computerized Methodology. A. Angle of Arrival Estimation. B. Data Modeling and Identification

DTIC Science & Technology

1991-06-10

essentially In the Wianer- Ville distribution ( WVD ). A preliminary analysis indicates that the simple operation of autoconvolution can enhance spectral...many troublesome cases as a supplement to MUSIC (and its adaptations) and as a simple alternative (or representation of) the Wigner - Ville ... WVD is a time-frequency distribution which provides an unbiased spectrum estimate by W(t,W) = f H,(u) X (t - u/2) X (t + u/2) e -iwu du , where the

Racial Bias and Predictive Validity in Testing for Selection.

DTIC Science & Technology

1983-07-01

the inequa - lity rR (P.C) *0 (2) must define test bias. This definition of test bias conforms to the requirements of the Civil Rights Act of 1964 as...of Educational Measurement, 1976, 13, 43-52. Einhorn, H. J., & Bass, A. R. Methodological considerations relevant to discrimination in employment ...34unbiased" selec- tion model: A question of utilities. Journal of Applied Psychology, 1975, 60, 345-351. Guion, R. M. Employment tests and discriminatory

Sparse Recovery via Differential Inclusions

DTIC Science & Technology

2014-07-01

2242. [Wai09] Martin J. Wainwright, Sharp thresholds for high-dimensional and noisy spar- sity recovery using l1 -constrained quadratic programming...solution, (1.11) βt = { 0, if t < 1/y; y(1− e−κ(t−1/y)), otherwise, which converges to the unbiased Bregman ISS estimator exponentially fast. Let us ...are not given the support set S, so the following two prop- erties are used to evaluate the performance of an estimator β̂. 1. Model selection

Assessing mediation using marginal structural models in the presence of confounding and moderation

PubMed Central

Coffman, Donna L.; Zhong, Wei

2012-01-01

This paper presents marginal structural models (MSMs) with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW can be used to take confounding into account, but IPW has several advantages. Regression adjustment of even one confounder of the mediator and outcome that has been influenced by treatment results in biased estimates of the direct effect (i.e., the effect of treatment on the outcome that does not go through the mediator). One advantage of IPW is that it can properly adjust for this type of confounding, assuming there are no unmeasured confounders. Further, we illustrate that IPW estimation provides unbiased estimates of all effects when there is a baseline moderator variable that interacts with the treatment, when there is a baseline moderator variable that interacts with the mediator, and when the treatment interacts with the mediator. IPW estimation also provides unbiased estimates of all effects in the presence of non-randomized treatments. In addition, for testing mediation we propose a test of the null hypothesis of no mediation. Finally, we illustrate this approach with an empirical data set in which the mediator is continuous, as is often the case in psychological research. PMID:22905648

Assessing mediation using marginal structural models in the presence of confounding and moderation.

PubMed

Coffman, Donna L; Zhong, Wei

2012-12-01

This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW can be used to take confounding into account, but IPW has several advantages. Regression adjustment of even one confounder of the mediator and outcome that has been influenced by treatment results in biased estimates of the direct effect (i.e., the effect of treatment on the outcome that does not go through the mediator). One advantage of IPW is that it can properly adjust for this type of confounding, assuming there are no unmeasured confounders. Further, we illustrate that IPW estimation provides unbiased estimates of all effects when there is a baseline moderator variable that interacts with the treatment, when there is a baseline moderator variable that interacts with the mediator, and when the treatment interacts with the mediator. IPW estimation also provides unbiased estimates of all effects in the presence of nonrandomized treatments. In addition, for testing mediation we propose a test of the null hypothesis of no mediation. Finally, we illustrate this approach with an empirical data set in which the mediator is continuous, as is often the case in psychological research. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Cross-Layer Resource Allocation for Wireless Visual Sensor Networks and Mobile Ad Hoc Networks

DTIC Science & Technology

2014-10-01

MMD), minimizes the maximum dis- tortion among all nodes of the network, promoting a rather unbiased treatment of the nodes. We employed the Particle...achieve the ideal tradeoff between the transmitted video quality and energy consumption. Each sensor node has a bit rate that can be used for both...Distortion (MMD), minimizes the maximum distortion among all nodes of the network, promoting a rather unbiased treatment of the nodes. For both criteria

Unbiased estimators for spatial distribution functions of classical fluids

NASA Astrophysics Data System (ADS)

Adib, Artur B.; Jarzynski, Christopher

2005-01-01

We use a statistical-mechanical identity closely related to the familiar virial theorem, to derive unbiased estimators for spatial distribution functions of classical fluids. In particular, we obtain estimators for both the fluid density ρ(r) in the vicinity of a fixed solute and the pair correlation g(r) of a homogeneous classical fluid. We illustrate the utility of our estimators with numerical examples, which reveal advantages over traditional histogram-based methods of computing such distributions.

Barotropic Tidal Predictions and Validation in a Relocatable Modeling Environment. Revised

NASA Technical Reports Server (NTRS)

Mehra, Avichal; Passi, Ranjit; Kantha, Lakshmi; Payne, Steven; Brahmachari, Shuvobroto

1998-01-01

Under funding from the Office of Naval Research (ONR), the Mississippi State University Center for Air Sea Technology (CAST) has been working on developing a Relocatable Modeling Environment (RME) to provide a uniform and unbiased infrastructure for efficiently configuring numerical models in any geographic or oceanic region. Under Naval Oceanographic Office (NAVOCEANO) funding, the model was implemented and tested for NAVOCEANO use. With our current emphasis on ocean tidal modeling, CAST has adopted the Colorado University's numerical ocean model, known as CURReNTSS (Colorado University Rapidly Relocatable Nestable Storm Surge) Model, as the model of choice. During the RME development process, CURReNTSS has been relocated to several coastal oceanic regions, providing excellent results that demonstrate its veracity. This report documents the model validation results and provides a brief description of the Graphic user Interface.

Occupancy Modeling for Improved Accuracy and Understanding of Pathogen Prevalence and Dynamics

PubMed Central

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmon Oncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population: Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/ metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%. PMID:25738709

Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics

USGS Publications Warehouse

Colvin, Michael E.; Peterson, James T.; Kent, Michael L.; Schreck, Carl B.

2015-01-01

Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmonOncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population:Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%.

Modeling Particle Exposure in US Trucking Terminals

PubMed Central

Davis, ME; Smith, TJ; Laden, F; Hart, JE; Ryan, LM; Garshick, E

2007-01-01

Multi-tiered sampling approaches are common in environmental and occupational exposure assessment, where exposures for a given individual are often modeled based on simultaneous measurements taken at multiple indoor and outdoor sites. The monitoring data from such studies is hierarchical by design, imposing a complex covariance structure that must be accounted for in order to obtain unbiased estimates of exposure. Statistical methods such as structural equation modeling (SEM) represent a useful alternative to simple linear regression in these cases, providing simultaneous and unbiased predictions of each level of exposure based on a set of covariates specific to the exposure setting. We test the SEM approach using data from a large exposure assessment of diesel and combustion particles in the US trucking industry. The exposure assessment includes data from 36 different trucking terminals across the United States sampled between 2001 and 2005, measuring PM2.5 and its elemental carbon (EC), organic carbon (OC) components, by personal monitoring, and sampling at two indoor work locations and an outdoor “background” location. Using the SEM method, we predict: 1) personal exposures as a function of work related exposure and smoking status; 2) work related exposure as a function of terminal characteristics, indoor ventilation, job location, and background exposure conditions; and 3) background exposure conditions as a function of weather, nearby source pollution, and other regional differences across terminal sites. The primary advantage of SEMs in this setting is the ability to simultaneously predict exposures at each of the sampling locations, while accounting for the complex covariance structure among the measurements and descriptive variables. The statistically significant results and high R2 values observed from the trucking industry application supports the broader use of this approach in exposure assessment modeling. PMID:16856739

Evaluating disease management programme effectiveness: an introduction to instrumental variables.

PubMed

Linden, Ariel; Adams, John L

2006-04-01

This paper introduces the concept of instrumental variables (IVs) as a means of providing an unbiased estimate of treatment effects in evaluating disease management (DM) programme effectiveness. Model development is described using zip codes as the IV. Three diabetes DM outcomes were evaluated: annual diabetes costs, emergency department (ED) visits and hospital days. Both ordinary least squares (OLS) and IV estimates showed a significant treatment effect for diabetes costs (P = 0.011) but neither model produced a significant treatment effect for ED visits. However, the IV estimate showed a significant treatment effect for hospital days (P = 0.006) whereas the OLS model did not. These results illustrate the utility of IV estimation when the OLS model is sensitive to the confounding effect of hidden bias.

Reheating-volume measure for random-walk inflation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winitzki, Sergei; Yukawa Institute of Theoretical Physics, Kyoto University, Kyoto

2008-09-15

The recently proposed 'reheating-volume' (RV) measure promises to solve the long-standing problem of extracting probabilistic predictions from cosmological multiverse scenarios involving eternal inflation. I give a detailed description of the new measure and its applications to generic models of eternal inflation of random-walk type. For those models I derive a general formula for RV-regulated probability distributions that is suitable for numerical computations. I show that the results of the RV cutoff in random-walk type models are always gauge invariant and independent of the initial conditions at the beginning of inflation. In a toy model where equal-time cutoffs lead to themore » 'youngness paradox', the RV cutoff yields unbiased results that are distinct from previously proposed measures.« less

The evolution history of the extended solar neighbourhood

NASA Astrophysics Data System (ADS)

Just, Andreas; Sysoliatina, Kseniia; Koutsouridou, Ioanna

2018-04-01

Our detailed analytic local disc model (JJ-model) quantifies the interrelation between kinematic properties (e.g. velocity dispersions and asymmetric drift), spatial parameters (scale-lengths and vertical density profiles), and properties of stellar sub-populations (age and abundance distributions). We discuss a radial extension of the disc evolution model representing an inside-out growth of the thin disc with constant thickness. Based on metallicity distributions of APOGEE red clump stars we derive the AMR as function of galactrocentric distance and show that mono-abundance as well as mono-age populations are flaring. The predictions of the JJ-model are consistent with the TGAS-RAVE data, which provide a significant improvement of the kinematic data and unbiased distances for more than 250,000 stars.

Experiences from the testing of a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Experience gained in testing a theory for modelling groundwater flow in heterogeneous media

USGS Publications Warehouse

Christensen, S.; Cooley, R.L.

2002-01-01

Usually, small-scale model error is present in groundwater modelling because the model only represents average system characteristics having the same form as the drift, and small-scale variability is neglected. These errors cause the true errors of a regression model to be correlated. Theory and an example show that the errors also contribute to bias in the estimates of model parameters. This bias originates from model nonlinearity. In spite of this bias, predictions of hydraulic head are nearly unbiased if the model intrinsic nonlinearity is small. Individual confidence and prediction intervals are accurate if the t-statistic is multiplied by a correction factor. The correction factor can be computed from the true error second moment matrix, which can be determined when the stochastic properties of the system characteristics are known.

Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors.

PubMed

Jang, In Sock; Dienstmann, Rodrigo; Margolin, Adam A; Guinney, Justin

2015-01-01

Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer. With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile. However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies. To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines--in conjunction with modern statistical learning approaches--have been used to explore the genetic underpinnings of drug response. While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, i.e. they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model. While a purely data-driven approach offers an unbiased perspective of the data--and may yield unexpected or novel insights--this strategy introduces challenges for both model interpretability and accuracy. In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion. Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss--and often an improvement--in predictive performance. We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods.

Neuronal Deletion of Caspase 8 Protects against Brain Injury in Mouse Models of Controlled Cortical Impact and Kainic Acid-Induced Excitotoxicity

PubMed Central

Krajewska, Maryla; You, Zerong; Rong, Juan; Kress, Christina; Huang, Xianshu; Yang, Jinsheng; Kyoda, Tiffany; Leyva, Ricardo; Banares, Steven; Hu, Yue; Sze, Chia-Hung; Whalen, Michael J.; Salmena, Leonardo; Hakem, Razqallah; Head, Brian P.; Reed, John C.; Krajewski, Stan

2011-01-01

Background Acute brain injury is an important health problem. Given the critical position of caspase 8 at the crossroads of cell death pathways, we generated a new viable mouse line (Ncasp8 −/−), in which the gene encoding caspase 8 was selectively deleted in neurons by cre-lox system. Methodology/Principal Findings Caspase 8 deletion reduced rates of neuronal cell death in primary neuronal cultures and in whole brain organotypic coronal slice cultures prepared from 4 and 8 month old mice and cultivated up to 14 days in vitro. Treatments of cultures with recombinant murine TNFα (100 ng/ml) or TRAIL (250 ng/mL) plus cyclohexamide significantly protected neurons against cell death induced by these apoptosis-inducing ligands. A protective role of caspase 8 deletion in vivo was also demonstrated using a controlled cortical impact (CCI) model of traumatic brain injury (TBI) and seizure-induced brain injury caused by kainic acid (KA). Morphometric analyses were performed using digital imaging in conjunction with image analysis algorithms. By employing virtual images of hundreds of brain sections, we were able to perform quantitative morphometry of histological and immunohistochemical staining data in an unbiased manner. In the TBI model, homozygous deletion of caspase 8 resulted in reduced lesion volumes, improved post-injury motor performance, superior learning and memory retention, decreased apoptosis, diminished proteolytic processing of caspases and caspase substrates, and less neuronal degeneration, compared to wild type, homozygous cre, and caspase 8-floxed control mice. In the KA model, Ncasp8 −/− mice demonstrated superior survival, reduced seizure severity, less apoptosis, and reduced caspase 3 processing. Uninjured aged knockout mice showed improved learning and memory, implicating a possible role for caspase 8 in cognitive decline with aging. Conclusions Neuron-specific deletion of caspase 8 reduces brain damage and improves post-traumatic functional outcomes, suggesting an important role for this caspase in pathophysiology of acute brain trauma. PMID:21957448

TRIPPy: Python-based Trailed Source Photometry

NASA Astrophysics Data System (ADS)

Fraser, Wesley C.; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michael E.; Pike, Rosemary E.; Kavelaars, JJ; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

2016-05-01

TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

Nature of Continuous Phase Transitions in Interacting Topological Insulators

DOE PAGES

Zeng, Tian-sheng; Zhu, Wei; Zhu, Jianxin; ...

2017-11-08

Here, we revisit the effects of the Hubbard repulsion on quantum spin Hall effects (QSHE) in two-dimensional quantum lattice models. We present both unbiased exact diagonalization and density-matrix renormalization group simulations with numerical evidence for a continuous quantum phase transition (CQPT) separating QSHE from the topologically trivial antiferromagnetic phase. Our numerical results suggest that the nature of CQPT exhibits distinct finite-size scaling behaviors, which may be consistent with either Ising or XY universality classes for different time-reversal symmetric QSHE systems.

Nature of Continuous Phase Transitions in Interacting Topological Insulators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Tian-sheng; Zhu, Wei; Zhu, Jianxin

Here, we revisit the effects of the Hubbard repulsion on quantum spin Hall effects (QSHE) in two-dimensional quantum lattice models. We present both unbiased exact diagonalization and density-matrix renormalization group simulations with numerical evidence for a continuous quantum phase transition (CQPT) separating QSHE from the topologically trivial antiferromagnetic phase. Our numerical results suggest that the nature of CQPT exhibits distinct finite-size scaling behaviors, which may be consistent with either Ising or XY universality classes for different time-reversal symmetric QSHE systems.

Propeller aircraft interior noise model. II - Scale-model and flight-test comparisons

NASA Technical Reports Server (NTRS)

Willis, C. M.; Mayes, W. H.

1987-01-01

A program for predicting the sound levels inside propeller driven aircraft arising from sidewall transmission of airborne exterior noise is validated through comparisons of predictions with both scale-model test results and measurements obtained in flight tests on a turboprop aircraft. The program produced unbiased predictions for the case of the scale-model tests, with a standard deviation of errors of about 4 dB. For the case of the flight tests, the predictions revealed a bias of 2.62-4.28 dB (depending upon whether or not the data for the fourth harmonic were included) and the standard deviation of the errors ranged between 2.43 and 4.12 dB. The analytical model is shown to be capable of taking changes in the flight environment into account.

Single-Cell RNA-Seq of Mouse Dopaminergic Neurons Informs Candidate Gene Selection for Sporadic Parkinson Disease.

PubMed

Hook, Paul W; McClymont, Sarah A; Cannon, Gabrielle H; Law, William D; Morton, A Jennifer; Goff, Loyal A; McCallion, Andrew S

2018-03-01

Genetic variation modulating risk of sporadic Parkinson disease (PD) has been primarily explored through genome-wide association studies (GWASs). However, like many other common genetic diseases, the impacted genes remain largely unknown. Here, we used single-cell RNA-seq to characterize dopaminergic (DA) neuron populations in the mouse brain at embryonic and early postnatal time points. These data facilitated unbiased identification of DA neuron subpopulations through their unique transcriptional profiles, including a postnatal neuroblast population and substantia nigra (SN) DA neurons. We use these population-specific data to develop a scoring system to prioritize candidate genes in all 49 GWAS intervals implicated in PD risk, including genes with known PD associations and many with extensive supporting literature. As proof of principle, we confirm that the nigrostriatal pathway is compromised in Cplx1-null mice. Ultimately, this systematic approach establishes biologically pertinent candidates and testable hypotheses for sporadic PD, informing a new era of PD genetic research. Copyright © 2018 American Society of Human Genetics. All rights reserved.

A Signaling Network Induced by β2 Integrin Controls the Polarization of Lytic Granulesin Cytotoxic Cells

PubMed Central

Zhang, Minggang; March, Michael E.; Lane, William S.; Long, Eric O.

2014-01-01

Cytotoxic lymphocyte skill target cells by polarized release of the content of perforin-containing granules. In natural killer cells, the binding of β2 integrin to its ligand ICAM-1 is sufficient to promote not only adhesion but also lytic granule polarization. This provided a unique opportunity to study polarization in the absence of degranulation, and β2 integrin signaling independently of inside-out signals from other receptors. Using an unbiased proteomics approach we identified a signaling network centered on an integrin-linked kinase (ILK)–Pyk2–Paxillin core that was required for granule polarization. Downstream of ILK, the highly conserved Cdc42–Par6 signaling pathway that controls cell polarity was activated and required for granule polarization. These results delineate two connected signaling networks induced upon β2 integrin engagement alone, which are integrated to control polarization of the microtubule organizing center and associated lytic granules toward the site of contact with target cells during cellular cytotoxicity. PMID:25292215

Protein-mRNA interactome capture: cartography of the mRNP landscape

PubMed Central

Ryder, Sean P.

2016-01-01

RNA-binding proteins play a variety of roles in cellular physiology. Some regulate mRNA processing, mRNA abundance, and translation efficiency. Some fight off invader RNA through small RNA-driven silencing pathways. Others sense foreign sequences in the form of double-stranded RNA and activate the innate immune response. Yet others, for example cytoplasmic aconitase, act as bi-functional proteins, processing metabolites in one conformation and regulating metabolic gene expression in another. Not all are involved in gene regulation. Some play structural roles, for example, connecting the translational machinery to the endoplasmic reticulum outer membrane. Despite their pervasive role and relative importance, it has remained difficult to identify new RNA-binding proteins in a systematic, unbiased way. A recent body of literature from several independent labs has defined robust, easily adaptable protocols for mRNA interactome discovery. In this review, I summarize the methods and review some of the intriguing findings from their application to a wide variety of biological systems. PMID:29098073

Acyl Coenzyme A Thioesterase 7 Regulates Neuronal Fatty Acid Metabolism To Prevent Neurotoxicity

PubMed Central

Ellis, Jessica M.; Wong, G. William

2013-01-01

Numerous neurological diseases are associated with dysregulated lipid metabolism; however, the basic metabolic control of fatty acid metabolism in neurons remains enigmatic. Here we have shown that neurons have abundant expression and activity of the long-chain cytoplasmic acyl coenzyme A (acyl-CoA) thioesterase 7 (ACOT7) to regulate lipid retention and metabolism. Unbiased and targeted metabolomic analysis of fasted mice with a conditional knockout of ACOT7 in the nervous system, Acot7N−/−, revealed increased fatty acid flux into multiple long-chain acyl-CoA-dependent pathways. The alterations in brain fatty acid metabolism were concomitant with a loss of lean mass, hypermetabolism, hepatic steatosis, dyslipidemia, and behavioral hyperexcitability in Acot7N−/− mice. These failures in adaptive energy metabolism are common in neurodegenerative diseases. In agreement, Acot7N−/− mice exhibit neurological dysfunction and neurodegeneration. These data show that ACOT7 counterregulates fatty acid metabolism in neurons and protects against neurotoxicity. PMID:23459938

Acyl coenzyme A thioesterase 7 regulates neuronal fatty acid metabolism to prevent neurotoxicity.

PubMed

Ellis, Jessica M; Wong, G William; Wolfgang, Michael J

2013-05-01

Numerous neurological diseases are associated with dysregulated lipid metabolism; however, the basic metabolic control of fatty acid metabolism in neurons remains enigmatic. Here we have shown that neurons have abundant expression and activity of the long-chain cytoplasmic acyl coenzyme A (acyl-CoA) thioesterase 7 (ACOT7) to regulate lipid retention and metabolism. Unbiased and targeted metabolomic analysis of fasted mice with a conditional knockout of ACOT7 in the nervous system, Acot7(N-/-), revealed increased fatty acid flux into multiple long-chain acyl-CoA-dependent pathways. The alterations in brain fatty acid metabolism were concomitant with a loss of lean mass, hypermetabolism, hepatic steatosis, dyslipidemia, and behavioral hyperexcitability in Acot7(N-/-) mice. These failures in adaptive energy metabolism are common in neurodegenerative diseases. In agreement, Acot7(N-/-) mice exhibit neurological dysfunction and neurodegeneration. These data show that ACOT7 counterregulates fatty acid metabolism in neurons and protects against neurotoxicity.

Inflammatory signaling in human Tuberculosis granulomas is spatially organized

PubMed Central

Marakalala, Mohlopheni J.; Raju, Ravikiran M.; Sharma, Kirti; Zhang, Yanjia J.; Eugenin, Eliseo A.; Prideaux, Brendan; Daudelin, Isaac B.; Chen, Pei-Yu; Booty, Matthew G.; Kim, Jin Hee; Eum, Seok Yong; Via, Laura E.; Behar, Samuel M.; Barry, Clifton E.; Mann, Matthias; Dartois, Véronique; Rubin, Eric J.

2016-01-01

Granulomas are the pathological hallmark of tuberculosis (TB). However, their function and mechanisms of formation remain poorly understood. To understand the role of granulomas in TB, we analyzed the proteomes of granulomas from subjects with tuberculosis in an unbiased fashion. Using laser capture microdissection, mass spectrometry and confocal microscopy, we generated detailed molecular maps of human granulomas. We found that the centers of granulomas possess a pro-inflammatory environment characterized by anti-microbial peptides, ROS and pro-inflammatory eicosanoids. Conversely, the tissue surrounding the caseum possesses a comparatively anti-inflammatory signature. These findings are consistent across a set of six subjects and in rabbits. While the balance between systemic pro- and anti-inflammatory signals is crucial to TB disease outcome, here we find that these signals are physically segregated within each granuloma. The protein and lipid snapshots of human and rabbit lesions analysed here suggest that the pathologic response to TB is shaped by the precise anatomical localization of these inflammatory pathways during the development of the granuloma. PMID:27043495

An Unbiased Systems Genetics Approach to Mapping Genetic Loci Modulating Susceptibility to Severe Streptococcal Sepsis

PubMed Central

Abdeltawab, Nourtan F.; Aziz, Ramy K.; Kansal, Rita; Rowe, Sarah L.; Su, Yin; Gardner, Lidia; Brannen, Charity; Nooh, Mohammed M.; Attia, Ramy R.; Abdelsamed, Hossam A.; Taylor, William L.; Lu, Lu; Williams, Robert W.; Kotb, Malak

2008-01-01

Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%–30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases. PMID:18421376

Ataxin-2 (Atxn2)-Knock-Out Mice Show Branched Chain Amino Acids and Fatty Acids Pathway Alterations.

PubMed

Meierhofer, David; Halbach, Melanie; Şen, Nesli Ece; Gispert, Suzana; Auburger, Georg

2016-05-01

Human Ataxin-2 (ATXN2) gene locus variants have been associated with obesity, diabetes mellitus type 1,and hypertension in genome-wide association studies, whereas mouse studies showed the knock-out of Atxn2 to lead to obesity, insulin resistance, and dyslipidemia. Intriguingly, the deficiency of ATXN2 protein orthologs in yeast and flies rescues the neurodegeneration process triggered by TDP-43 and Ataxin-1 toxicity. To understand the molecular effects of ATXN2 deficiency by unbiased approaches, we quantified the global proteome and metabolome of Atxn2-knock-out mice with label-free mass spectrometry. In liver tissue, significant downregulations of the proteins ACADS, ALDH6A1, ALDH7A1, IVD, MCCC2, PCCA, OTC, together with bioinformatic enrichment of downregulated pathways for branched chain and other amino acid metabolism, fatty acids, and citric acid cycle were observed. Statistical trends in the cerebellar proteome and in the metabolomic profiles supported these findings. They are in good agreement with recent claims that PBP1, the yeast ortholog of ATXN2, sequestrates the nutrient sensor TORC1 in periods of cell stress. Overall, ATXN2 appears to modulate nutrition and metabolism, and its activity changes are determinants of growth excess or cell atrophy. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

How Oliceridine (TRV-130) Binds and Stabilizes a μ-Opioid Receptor Conformational State That Selectively Triggers G Protein Signaling Pathways.

PubMed

Schneider, Sebastian; Provasi, Davide; Filizola, Marta

2016-11-22

Substantial attention has recently been devoted to G protein-biased agonism of the μ-opioid receptor (MOR) as an ideal new mechanism for the design of analgesics devoid of serious side effects. However, designing opioids with appropriate efficacy and bias is challenging because it requires an understanding of the ligand binding process and of the allosteric modulation of the receptor. Here, we investigated these phenomena for TRV-130, a G protein-biased MOR small-molecule agonist that has been shown to exert analgesia with less respiratory depression and constipation than morphine and that is currently being evaluated in human clinical trials for acute pain management. Specifically, we carried out multimicrosecond, all-atom molecular dynamics (MD) simulations of the binding of this ligand to the activated MOR crystal structure. Analysis of >50 μs of these MD simulations provides insights into the energetically preferred binding pathway of TRV-130 and its stable pose at the orthosteric binding site of MOR. Information transfer from the TRV-130 binding pocket to the intracellular region of the receptor was also analyzed, and was compared to a similar analysis carried out on the receptor bound to the classical unbiased agonist morphine. Taken together, these studies lead to a series of testable hypotheses of ligand-receptor interactions that are expected to inform the structure-based design of improved opioid analgesics.

Structural Diversity of Ligand-Binding Androgen Receptors Revealed by Microsecond Long Molecular Dynamics Simulations and Enhanced Sampling.

PubMed

Duan, Mojie; Liu, Na; Zhou, Wenfang; Li, Dan; Yang, Minghui; Hou, Tingjun

2016-09-13

Androgen receptor (AR) plays important roles in the development of prostate cancer (PCa). The antagonistic drugs, which suppress the activity of AR, are widely used in the treatment of PCa. However, the molecular mechanism of antagonism about how ligands affect the structures of AR remains elusive. To better understand the conformational variability of ARs bound with agonists or antagonists, we performed long time unbiased molecular dynamics (MD) simulations and enhanced sampling simulations for the ligand binding domain of AR (AR-LBD) in complex with various ligands. Based on the simulation results, we proposed an allosteric pathway linking ligands and helix 12 (H12) of AR-LBD, which involves the interactions among the ligands and the residues W741, H874, and I899. The interaction pathway provides an atomistic explanation of how ligands affect the structure of AR-LBD. A repositioning of H12 was observed, but it is facilitated by the C-terminal of H12, instead of by the loop between helix 11 (H11) and H12. The bias-exchange metadynamics simulations further demonstrated the above observations. More importantly, the free energy profiles constructed by the enhanced sampling simulations revealed the transition process between the antagonistic form and agonistic form of AR-LBD. Our results would be helpful for the design of more efficient antagonists of AR to combat PCa.

Fanconi Anemia complementation group C protein in metabolic disorders.

PubMed

Nepal, Manoj; Ma, Chi; Xie, Guoxiang; Jia, Wei; Fei, Peiwen

2018-06-21

Given importance of 22-Fanconi Anemia (FA) proteins together to act in a signaling pathway in preventing deleterious clinical symptoms, e.g. severe bone marrow failure, congenital defects, an early onset of aging and cancer, studies on each FA protein become increasingly attractive. However, an unbiased and systematic investigation of cellular effects resulting from each FA protein is missing. Here, we report roles of FA complementation C group protein (FANCC) in the protection from metabolic disorders. This study was prompted by the diabetes-prone feature displayed in FANCC knockout mice, which is not typically shown in patients with FA. We found that in cells expressing FANCC at different levels, there are representative alterations in metabolites associated with aging (glycine, citrulline, ornithine, L-asparagine, L-tyrosine, L-arginine, L-glutamine, L-leucine, L-isoleucine, L-valine, L-proline and L-alanine), Diabetes Mellitus (DM) (carbon monoxide, collagens, fatty acids, D-glucose, fumaric acid, 2-oxoglutaric acid, C3), inflammation (inosine, L-arginine, L-isoleucine, L-leucine, L-lysine, L-phenylalanine, hypoxanthine, L-methionine), and cancer ( L-methionine, sphingomyelin, acetyl-L-carnitine, L-aspartic acid, L-glutamic acid, niacinamide, phospho-rylethanolamine). We also found that FANCC can act in an FA-pathway-independent manner in tumor suppression. Collectively, featured-metabolic alterations are readouts of functional mechanisms underlying reduced tumorigenicity driven by FANCC, demonstrating close links among cancer, aging, inflammation and DM.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.

PubMed

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-06-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat

PubMed Central

Zhao, Y; Mette, M F; Gowda, M; Longin, C F H; Reif, J C

2014-01-01

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection. PMID:24518889

Uncertainty relation based on unbiased parameter estimations

NASA Astrophysics Data System (ADS)

Sun, Liang-Liang; Song, Yong-Shun; Qiao, Cong-Feng; Yu, Sixia; Chen, Zeng-Bing

2017-02-01

Heisenberg's uncertainty relation has been extensively studied in spirit of its well-known original form, in which the inaccuracy measures used exhibit some controversial properties and don't conform with quantum metrology, where the measurement precision is well defined in terms of estimation theory. In this paper, we treat the joint measurement of incompatible observables as a parameter estimation problem, i.e., estimating the parameters characterizing the statistics of the incompatible observables. Our crucial observation is that, in a sequential measurement scenario, the bias induced by the first unbiased measurement in the subsequent measurement can be eradicated by the information acquired, allowing one to extract unbiased information of the second measurement of an incompatible observable. In terms of Fisher information we propose a kind of information comparison measure and explore various types of trade-offs between the information gains and measurement precisions, which interpret the uncertainty relation as surplus variance trade-off over individual perfect measurements instead of a constraint on extracting complete information of incompatible observables.

Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.

Autocorrelation analysis for the unbiased determination of power-law exponents in single-quantum-dot blinking.

PubMed

Houel, Julien; Doan, Quang T; Cajgfinger, Thomas; Ledoux, Gilles; Amans, David; Aubret, Antoine; Dominjon, Agnès; Ferriol, Sylvain; Barbier, Rémi; Nasilowski, Michel; Lhuillier, Emmanuel; Dubertret, Benoît; Dujardin, Christophe; Kulzer, Florian

2015-01-27

We present an unbiased and robust analysis method for power-law blinking statistics in the photoluminescence of single nanoemitters, allowing us to extract both the bright- and dark-state power-law exponents from the emitters' intensity autocorrelation functions. As opposed to the widely used threshold method, our technique therefore does not require discriminating the emission levels of bright and dark states in the experimental intensity timetraces. We rely on the simultaneous recording of 450 emission timetraces of single CdSe/CdS core/shell quantum dots at a frame rate of 250 Hz with single photon sensitivity. Under these conditions, our approach can determine ON and OFF power-law exponents with a precision of 3% from a comparison to numerical simulations, even for shot-noise-dominated emission signals with an average intensity below 1 photon per frame and per quantum dot. These capabilities pave the way for the unbiased, threshold-free determination of blinking power-law exponents at the microsecond time scale.

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

PubMed

Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

2016-01-12

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome .

GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms.

PubMed

Jani, Saurin D; Argraves, Gary L; Barth, Jeremy L; Argraves, W Scott

2010-04-01

An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG pathway diagrams and heatmaps of expression intensity values. GeneMesh is freely available online at http://proteogenomics.musc.edu/genemesh/.

Epigenetic Library Screen Identifies Abexinostat as Novel Regulator of Adipocytic and Osteoblastic Differentiation of Human Skeletal (Mesenchymal) Stem Cells

PubMed Central

Ali, Dalia; Hamam, Rimi; Alfayez, Musaed; Kassem, Moustapha; Aldahmash, Abdullah

2016-01-01

The epigenetic mechanisms promoting lineage-specific commitment of human skeletal (mesenchymal or stromal) stem cells (hMSCs) into adipocytes or osteoblasts are still not fully understood. Herein, we performed an epigenetic library functional screen and identified several novel compounds, including abexinostat, which promoted adipocytic and osteoblastic differentiation of hMSCs. Using gene expression microarrays, chromatin immunoprecipitation for H3K9Ac combined with high-throughput DNA sequencing (ChIP-seq), and bioinformatics, we identified several key genes involved in regulating stem cell proliferation and differentiation that were targeted by abexinostat. Concordantly, ChIP-quantitative polymerase chain reaction revealed marked increase in H3K9Ac epigenetic mark on the promoter region of AdipoQ, FABP4, PPARγ, KLF15, CEBPA, SP7, and ALPL in abexinostat-treated hMSCs. Pharmacological inhibition of focal adhesion kinase (PF-573228) or insulin-like growth factor-1R/insulin receptor (NVP-AEW51) signaling exhibited significant inhibition of abexinostat-mediated adipocytic differentiation, whereas inhibition of WNT (XAV939) or transforming growth factor-β (SB505124) signaling abrogated abexinostat-mediated osteogenic differentiation of hMSCs. Our findings provide insight into the understanding of the relationship between the epigenetic effect of histone deacetylase inhibitors, transcription factors, and differentiation pathways governing adipocyte and osteoblast differentiation. Manipulating such pathways allows a novel use for epigenetic compounds in hMSC-based therapies and tissue engineering. Significance This unbiased epigenetic library functional screen identified several novel compounds, including abexinostat, that promoted adipocytic and osteoblastic differentiation of human skeletal (mesenchymal or stromal) stem cells (hMSCs). These data provide new insight into the understanding of the relationship between the epigenetic effect of histone deacetylase inhibitors, transcription factors, and differentiation pathways controlling adipocyte and osteoblast differentiation of hMSCs. Manipulating such pathways allows a novel use for epigenetic compounds in hMSC-based therapies for tissue engineering, bone disease, obesity, and metabolic-disorders. PMID:27194745

Data-driven nonlinear optimisation of a simple air pollution dispersion model generating high resolution spatiotemporal exposure

NASA Astrophysics Data System (ADS)

Yuval; Bekhor, Shlomo; Broday, David M.

2013-11-01

Spatially detailed estimation of exposure to air pollutants in the urban environment is needed for many air pollution epidemiological studies. To benefit studies of acute effects of air pollution such exposure maps are required at high temporal resolution. This study introduces nonlinear optimisation framework that produces high resolution spatiotemporal exposure maps. An extensive traffic model output, serving as proxy for traffic emissions, is fitted via a nonlinear model embodying basic dispersion properties, to high temporal resolution routine observations of traffic-related air pollutant. An optimisation problem is formulated and solved at each time point to recover the unknown model parameters. These parameters are then used to produce a detailed concentration map of the pollutant for the whole area covered by the traffic model. Repeating the process for multiple time points results in the spatiotemporal concentration field. The exposure at any location and for any span of time can then be computed by temporal integration of the concentration time series at selected receptor locations for the durations of desired periods. The methodology is demonstrated for NO2 exposure using the output of a traffic model for the greater Tel Aviv area, Israel, and the half-hourly monitoring and meteorological data from the local air quality network. A leave-one-out cross-validation resulted in simulated half-hourly concentrations that are almost unbiased compared to the observations, with a mean error (ME) of 5.2 ppb, normalised mean error (NME) of 32%, 78% of the simulated values are within a factor of two (FAC2) of the observations, and the coefficient of determination (R2) is 0.6. The whole study period integrated exposure estimations are also unbiased compared with their corresponding observations, with ME of 2.5 ppb, NME of 18%, FAC2 of 100% and R2 that equals 0.62.

Genome-wide DNA Methylation Changes in a Mouse Model of Infection-Mediated Neurodevelopmental Disorders.

PubMed

Richetto, Juliet; Massart, Renaud; Weber-Stadlbauer, Ulrike; Szyf, Moshe; Riva, Marco A; Meyer, Urs

2017-02-01

Prenatal exposure to infectious or inflammatory insults increases the risk of neurodevelopmental disorders. Using a well-established mouse model of prenatal viral-like immune activation, we examined whether this pathological association involves genome-wide DNA methylation differences at single nucleotide resolution. Prenatal immune activation was induced by maternal treatment with the viral mimetic polyriboinosinic-polyribocytidylic acid in middle or late gestation. Following behavioral and cognitive characterization of the adult offspring (n = 12 per group), unbiased capture array bisulfite sequencing was combined with subsequent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and quantitative real-time polymerase chain reaction analyses to quantify DNA methylation changes and transcriptional abnormalities in the medial prefrontal cortex of immune-challenged and control offspring. Gene ontology term enrichment analysis was used to explore shared functional pathways of genes with differential DNA methylation. Adult offspring of immune-challenged mothers displayed hyper- and hypomethylated CpGs at numerous loci and at distinct genomic regions, including genes relevant for gamma-aminobutyric acidergic differentiation and signaling (e.g., Dlx1, Lhx5, Lhx8), Wnt signaling (Wnt3, Wnt8a, Wnt7b), and neural development (e.g., Efnb3, Mid1, Nlgn1, Nrxn2). Altered DNA methylation was associated with transcriptional changes of the corresponding genes. The epigenetic and transcriptional effects were dependent on the offspring's age and were markedly influenced by the precise timing of prenatal immune activation. Prenatal viral-like immune activation is capable of inducing stable DNA methylation changes in the medial prefrontal cortex. These long-term epigenetic modifications are a plausible mechanism underlying the disruption of prefrontal gene transcription and behavioral functions in subjects with prenatal infectious histories. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Yeast Tolerance to Various Stresses Relies on the Trehalose-6P Synthase (Tps1) Protein, Not on Trehalose.

PubMed

Petitjean, Marjorie; Teste, Marie-Ange; François, Jean M; Parrou, Jean-Luc

2015-06-26

Trehalose is a stable disaccharide commonly found in nature, from bacteria to fungi and plants. For the model yeast Saccharomyces cerevisiae, claims that trehalose is a stress protectant were based indirectly either on correlation between accumulation of trehalose and high resistance to various stresses or on stress hypersensitivity of mutants deleted for TPS1, which encodes the first enzyme in trehalose biosynthetic pathway. Our goal was to investigate more directly which one, between trehalose and/or the Tps1 protein, may serve yeast cells to withstand exposure to stress. By employing an original strategy that combined the use of mutant strains expressing catalytically inactive variants of Tps1, with MAL(+) yeast strains able to accumulate trehalose from an exogenous supply, we bring for the first time unbiased proof that trehalose does not protect yeast cells from dying and that the stress-protecting role of trehalose in this eukaryotic model was largely overestimated. Conversely, we identified the Tps1 protein as a key player for yeast survival in response to temperature, oxidative, and desiccation stress. We also showed by robust RT-quantitative PCR and genetic interaction analysis that the role of Tps1 in thermotolerance is not dependent upon Hsf1-dependent transcription activity. Finally, our results revealed that the Tps1 protein is essential to maintain ATP levels during heat shock. Altogether, these findings supported the idea that Tps1 is endowed with a regulatory function in energy homeostasis, which is essential to withstand adverse conditions and maintain cellular integrity. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Barotropic Tidal Predictions and Validation in a Relocatable Modeling Environment. Revised

NASA Technical Reports Server (NTRS)

Mehra, Avichal; Passi, Ranjit; Kantha, Lakshmi; Payne, Steven; Brahmachari, Shuvobroto

1998-01-01

Under funding from the Office of Naval Research (ONR), and the Naval Oceanographic Office (NAVOCEANO), the Mississippi State University Center for Air Sea Technology (CAST) has been working on developing a Relocatable Modeling Environment(RME) to provide a uniform and unbiased infrastructure for efficiently configuring numerical models in any geographic/oceanic region. Under Naval Oceanographic Office (NAVO-CEANO) funding, the model was implemented and tested for NAVOCEANO use. With our current emphasis on ocean tidal modeling, CAST has adopted the Colorado University's numerical ocean model, known as CURReNTSS (Colorado University Rapidly Relocatable Nestable Storm Surge) Model, as the model of choice. During the RME development process, CURReNTSS has been relocated to several coastal oceanic regions, providing excellent results that demonstrate its veracity. This report documents the model validation results and provides a brief description of the Graphic user Interface (GUI).

A Simultaneous Equation Demand Model for Block Rates

NASA Astrophysics Data System (ADS)

Agthe, Donald E.; Billings, R. Bruce; Dobra, John L.; Raffiee, Kambiz

1986-01-01

This paper examines the problem of simultaneous-equations bias in estimation of the water demand function under an increasing block rate structure. The Hausman specification test is used to detect the presence of simultaneous-equations bias arising from correlation of the price measures with the regression error term in the results of a previously published study of water demand in Tucson, Arizona. An alternative simultaneous equation model is proposed for estimating the elasticity of demand in the presence of block rate pricing structures and availability of service charges. This model is used to reestimate the price and rate premium elasticities of demand in Tucson, Arizona for both the usual long-run static model and for a simple short-run demand model. The results from these simultaneous equation models are consistent with a priori expectations and are unbiased.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Genetic Circuits that Govern Bisexual and Unisexual Reproduction in Cryptococcus neoformans

PubMed Central

Feretzaki, Marianna; Heitman, Joseph

2013-01-01

Cryptococcus neoformans is a human fungal pathogen with a defined sexual cycle. Nutrient-limiting conditions and pheromones induce a dimorphic transition from unicellular yeast to multicellular hyphae and the production of infectious spores. Sexual reproduction involves cells of either opposite (bisexual) or one (unisexual) mating type. Bisexual and unisexual reproduction are governed by shared components of the conserved pheromone-sensing Cpk1 MAPK signal transduction cascade and by Mat2, the major transcriptional regulator of the pathway. However, the downstream targets of the pathway are largely unknown, and homology-based approaches have failed to yield downstream transcriptional regulators or other targets. In this study, we applied insertional mutagenesis via Agrobacterium tumefaciens transkingdom DNA delivery to identify mutants with unisexual reproduction defects. In addition to elements known to be involved in sexual development (Crg1, Ste7, Mat2, and Znf2), three key regulators of sexual development were identified by our screen: Znf3, Spo11, and Ubc5. Spo11 and Ubc5 promote sporulation during both bisexual and unisexual reproduction. Genetic and phenotypic analyses provide further evidence implicating both genes in the regulation of meiosis. Phenotypic analysis of sexual development showed that Znf3 is required for hyphal development during unisexual reproduction and also plays a central role during bisexual reproduction. Znf3 promotes cell fusion and pheromone production through a pathway parallel to and independent of the pheromone signaling cascade. Surprisingly, Znf3 participates in transposon silencing during unisexual reproduction and may serve as a link between RNAi silencing and sexual development. Our studies illustrate the power of unbiased genetic screens to reveal both novel and conserved circuits that operate sexual reproduction. PMID:23966871

Genetic circuits that govern bisexual and unisexual reproduction in Cryptococcus neoformans.

PubMed

Feretzaki, Marianna; Heitman, Joseph

2013-01-01

Cryptococcus neoformans is a human fungal pathogen with a defined sexual cycle. Nutrient-limiting conditions and pheromones induce a dimorphic transition from unicellular yeast to multicellular hyphae and the production of infectious spores. Sexual reproduction involves cells of either opposite (bisexual) or one (unisexual) mating type. Bisexual and unisexual reproduction are governed by shared components of the conserved pheromone-sensing Cpk1 MAPK signal transduction cascade and by Mat2, the major transcriptional regulator of the pathway. However, the downstream targets of the pathway are largely unknown, and homology-based approaches have failed to yield downstream transcriptional regulators or other targets. In this study, we applied insertional mutagenesis via Agrobacterium tumefaciens transkingdom DNA delivery to identify mutants with unisexual reproduction defects. In addition to elements known to be involved in sexual development (Crg1, Ste7, Mat2, and Znf2), three key regulators of sexual development were identified by our screen: Znf3, Spo11, and Ubc5. Spo11 and Ubc5 promote sporulation during both bisexual and unisexual reproduction. Genetic and phenotypic analyses provide further evidence implicating both genes in the regulation of meiosis. Phenotypic analysis of sexual development showed that Znf3 is required for hyphal development during unisexual reproduction and also plays a central role during bisexual reproduction. Znf3 promotes cell fusion and pheromone production through a pathway parallel to and independent of the pheromone signaling cascade. Surprisingly, Znf3 participates in transposon silencing during unisexual reproduction and may serve as a link between RNAi silencing and sexual development. Our studies illustrate the power of unbiased genetic screens to reveal both novel and conserved circuits that operate sexual reproduction.

Genome-Wide siRNA-Based Functional Genomics of Pigmentation Identifies Novel Genes and Pathways That Impact Melanogenesis in Human Cells

PubMed Central

Bodemann, Brian; Petersen, Sean; Aruri, Jayavani; Koshy, Shiney; Richardson, Zachary; Le, Lu Q.; Krasieva, Tatiana; Roth, Michael G.; Farmer, Pat; White, Michael A.

2008-01-01

Melanin protects the skin and eyes from the harmful effects of UV irradiation, protects neural cells from toxic insults, and is required for sound conduction in the inner ear. Aberrant regulation of melanogenesis underlies skin disorders (melasma and vitiligo), neurologic disorders (Parkinson's disease), auditory disorders (Waardenburg's syndrome), and opthalmologic disorders (age related macular degeneration). Much of the core synthetic machinery driving melanin production has been identified; however, the spectrum of gene products participating in melanogenesis in different physiological niches is poorly understood. Functional genomics based on RNA-mediated interference (RNAi) provides the opportunity to derive unbiased comprehensive collections of pharmaceutically tractable single gene targets supporting melanin production. In this study, we have combined a high-throughput, cell-based, one-well/one-gene screening platform with a genome-wide arrayed synthetic library of chemically synthesized, small interfering RNAs to identify novel biological pathways that govern melanin biogenesis in human melanocytes. Ninety-two novel genes that support pigment production were identified with a low false discovery rate. Secondary validation and preliminary mechanistic studies identified a large panel of targets that converge on tyrosinase expression and stability. Small molecule inhibition of a family of gene products in this class was sufficient to impair chronic tyrosinase expression in pigmented melanoma cells and UV-induced tyrosinase expression in primary melanocytes. Isolation of molecular machinery known to support autophagosome biosynthesis from this screen, together with in vitro and in vivo validation, exposed a close functional relationship between melanogenesis and autophagy. In summary, these studies illustrate the power of RNAi-based functional genomics to identify novel genes, pathways, and pharmacologic agents that impact a biological phenotype and operate outside of preconceived mechanistic relationships. PMID:19057677

Impact of Pyrrolidine Dithiocarbamate and Interleukin-6 on Mammalian Target of Rapamycin Complex 1 Regulation and Global Protein TranslationS⃞

PubMed Central

Song, Shaoming; Abdelmohsen, Kotb; Zhang, Yongqing; Becker, Kevin G.; Gorospe, Myriam

2011-01-01

Interleukin-6 (IL-6) is a proinflammatory cytokine that exerts a wide range of cellular, physiological, and pathophysiological responses. Pyrrolidine dithiocarbamate (PDTC) antagonizes the cellular responsiveness to IL-6 through impairment in signal transducer and activator of transcription-3 activation and downstream signaling. To further elucidate the biological properties of PDTC, global gene expression profiling of human HepG2 hepatocellular carcinoma cells was carried out after treatment with PDTC or IL-6 for up to 8 h. Through an unbiased pathway analysis method, gene array analysis showed dramatic and temporal differences in expression changes in response to PDTC versus IL-6. A significant number of genes associated with metabolic pathways, inflammation, translation, and mitochondrial function were changed, with ribosomal protein genes and DNA damage-inducible transcript 4 protein (DDIT4) primarily up-regulated with PDTC but down-regulated with IL-6. Quantitative polymerase chain reaction and Western blot analyses validated the microarray data and showed the reciprocal expression pattern of the mammalian target of rapamycin (mTOR)-negative regulator DDIT4 in response to PDTC versus IL-6. Cell treatment with PDTC resulted in a rapid and sustained activation of Akt and subsequently blocked the IL-6-mediated increase in mTOR complex 1 function through up-regulation in DDIT4 expression. Conversely, down-regulation of DDIT4 with small interfering RNA dampened the capacity of PDTC to block IL-6-dependent mTOR activation. The overall protein biosynthetic capacity of the cells was severely blunted by IL-6 but increased in a rapamycin-independent pathway by PDTC. These results demonstrate a critical effect of PDTC on mTOR complex 1 function and provide evidence that PDTC can reverse IL-6-related signaling via induction of DDIT4. PMID:21917559

Hsp90 Orchestrates Transcriptional Regulation by Hsf1 and Cell Wall Remodelling by MAPK Signalling during Thermal Adaptation in a Pathogenic Yeast

PubMed Central

Leach, Michelle D.; Budge, Susan; Walker, Louise; Munro, Carol; Cowen, Leah E.; Brown, Alistair J. P.

2012-01-01

Thermal adaptation is essential in all organisms. In yeasts, the heat shock response is commanded by the heat shock transcription factor Hsf1. Here we have integrated unbiased genetic screens with directed molecular dissection to demonstrate that multiple signalling cascades contribute to thermal adaptation in the pathogenic yeast Candida albicans. We show that the molecular chaperone heat shock protein 90 (Hsp90) interacts with and down-regulates Hsf1 thereby modulating short term thermal adaptation. In the longer term, thermal adaptation depends on key MAP kinase signalling pathways that are associated with cell wall remodelling: the Hog1, Mkc1 and Cek1 pathways. We demonstrate that these pathways are differentially activated and display cross talk during heat shock. As a result ambient temperature significantly affects the resistance of C. albicans cells to cell wall stresses (Calcofluor White and Congo Red), but not osmotic stress (NaCl). We also show that the inactivation of MAP kinase signalling disrupts this cross talk between thermal and cell wall adaptation. Critically, Hsp90 coordinates this cross talk. Genetic and pharmacological inhibition of Hsp90 disrupts the Hsf1-Hsp90 regulatory circuit thereby disturbing HSP gene regulation and reducing the resistance of C. albicans to proteotoxic stresses. Hsp90 depletion also affects cell wall biogenesis by impairing the activation of its client proteins Mkc1 and Hog1, as well as Cek1, which we implicate as a new Hsp90 client in this study. Therefore Hsp90 modulates the short term Hsf1-mediated activation of the classic heat shock response, coordinating this response with long term thermal adaptation via Mkc1- Hog1- and Cek1-mediated cell wall remodelling. PMID:23300438

Characterization of the myometrial transcriptome in women with an arrest of dilatation during labor

PubMed Central

Chaemsaithong, Piya; Madan, Ichchha; Romero, Roberto; Than, Nandor G; Tarca, Adi L; Draghici, Sorin; Bhatti, Gaurav; Mazor, Moshe; Kim, Chong Jai; Hassan, Sonia S; Chaiworapongsa, Tinnakorn

2014-01-01

Objective The molecular basis of failure to progress in labor is poorly understood. This study was undertaken to characterize the myometrial transcriptome of patients with an arrest of dilatation (AODIL). Study design Human myometrium was prospectively collected from women in the following groups: 1) spontaneous term labor (TL; n=29); and 2) arrest of dilatation (AODIL; n=14). Gene expression was characterized using Illumina® HumanHT-12 microarrays. A moderated student t-test and false discovery rate adjustment were used for analysis. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) of selected genes was performed in an independent sample set. Pathway analysis was performed on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database using Pathway Analysis with Down-weighting of Overlapping Genes (PADOG). The Metacore knowledge base was also mined for pathway analysis. Results 1) 42 genes differentially expressed were identified in women with an AODIL; 2) gene ontology analysis indicated enrichment of biological processes, which included: regulation of angiogenesis, response to hypoxia, inflammatory response, and chemokine-mediated signaling pathway. Enriched molecular functions included: transcription repressor activity, Heat shock protein (Hsp) 90 binding, and nitric oxide synthase (NOS) activity; 3) Metacore analysis identified immune response chemokine (C-C motif) ligand 2 (CCL2) signaling, muscle contraction regulation of eNOS activity in endothelial cells, and Triiodothyronine and Thyroxine signaling as significantly over-represented (FDR<0.05); 4) qRT-PCR confirmed overexpression of Nitric oxide synthase 3 NOS3; hypoxic ischemic factor (HIF1A), Chemokine (C-C motif) ligand 2 (CCL2); angiopoietin-like 4 (ANGPTL4), ADAM metallopeptidase with thrombospondin type 1, motif 9 (ADAMTS9), G protein-coupled receptor 4 (GPR4), metallothionein 1A (MT1A), MT2A, selectin E (SELE) in an AODIL. Conclusion The myometrium of women with arrest of dilatation have a stereotypic transcriptome profile. This disorder was associated with a pattern of gene expression involved in muscle contraction, an inflammatory response, and hypoxia. This is the first comprehensive and unbiased examination of the molecular basis of an AODIL. PMID:23893668

Systems analysis of apoptotic priming in ovarian cancer identifies vulnerabilities and predictors of drug response.

PubMed

Zervantonakis, Ioannis K; Iavarone, Claudia; Chen, Hsing-Yu; Selfors, Laura M; Palakurthi, Sangeetha; Liu, Joyce F; Drapkin, Ronny; Matulonis, Ursula; Leverson, Joel D; Sampath, Deepak; Mills, Gordon B; Brugge, Joan S

2017-08-28

The lack of effective chemotherapies for high-grade serous ovarian cancers (HGS-OvCa) has motivated a search for alternative treatment strategies. Here, we present an unbiased systems-approach to interrogate a panel of 14 well-annotated HGS-OvCa patient-derived xenografts for sensitivity to PI3K and PI3K/mTOR inhibitors and uncover cell death vulnerabilities. Proteomic analysis reveals that PI3K/mTOR inhibition in HGS-OvCa patient-derived xenografts induces both pro-apoptotic and anti-apoptotic signaling responses that limit cell killing, but also primes cells for inhibitors of anti-apoptotic proteins. In-depth quantitative analysis of BCL-2 family proteins and other apoptotic regulators, together with computational modeling and selective anti-apoptotic protein inhibitors, uncovers new mechanistic details about apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-X L ) and resistance (MCL-1, XIAP). Our systems-approach presents a strategy for systematic analysis of the mechanisms that limit effective tumor cell killing and the identification of apoptotic vulnerabilities to overcome drug resistance in ovarian and other cancers.High-grade serous ovarian cancers (HGS-OvCa) frequently develop chemotherapy resistance. Here, the authors through a systematic analysis of proteomic and drug response data of 14 HGS-OvCa PDXs demonstrate that targeting apoptosis regulators can improve response of these tumors to inhibitors of the PI3K/mTOR pathway.

Applying network analysis and Nebula (neighbor-edges based and unbiased leverage algorithm) to ToxCast data.

PubMed

Ye, Hao; Luo, Heng; Ng, Hui Wen; Meehan, Joe; Ge, Weigong; Tong, Weida; Hong, Huixiao

2016-01-01

ToxCast data have been used to develop models for predicting in vivo toxicity. To predict the in vivo toxicity of a new chemical using a ToxCast data based model, its ToxCast bioactivity data are needed but not normally available. The capability of predicting ToxCast bioactivity data is necessary to fully utilize ToxCast data in the risk assessment of chemicals. We aimed to understand and elucidate the relationships between the chemicals and bioactivity data of the assays in ToxCast and to develop a network analysis based method for predicting ToxCast bioactivity data. We conducted modularity analysis on a quantitative network constructed from ToxCast data to explore the relationships between the assays and chemicals. We further developed Nebula (neighbor-edges based and unbiased leverage algorithm) for predicting ToxCast bioactivity data. Modularity analysis on the network constructed from ToxCast data yielded seven modules. Assays and chemicals in the seven modules were distinct. Leave-one-out cross-validation yielded a Q(2) of 0.5416, indicating ToxCast bioactivity data can be predicted by Nebula. Prediction domain analysis showed some types of ToxCast assay data could be more reliably predicted by Nebula than others. Network analysis is a promising approach to understand ToxCast data. Nebula is an effective algorithm for predicting ToxCast bioactivity data, helping fully utilize ToxCast data in the risk assessment of chemicals. Published by Elsevier Ltd.

Using Markov state models to study self-assembly

NASA Astrophysics Data System (ADS)

Perkett, Matthew R.; Hagan, Michael F.

2014-06-01

Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude.

Tailored Codes for Small Quantum Memories

NASA Astrophysics Data System (ADS)

Robertson, Alan; Granade, Christopher; Bartlett, Stephen D.; Flammia, Steven T.

2017-12-01

We demonstrate that small quantum memories, realized via quantum error correction in multiqubit devices, can benefit substantially by choosing a quantum code that is tailored to the relevant error model of the system. For a biased noise model, with independent bit and phase flips occurring at different rates, we show that a single code greatly outperforms the well-studied Steane code across the full range of parameters of the noise model, including for unbiased noise. In fact, this tailored code performs almost optimally when compared with 10 000 randomly selected stabilizer codes of comparable experimental complexity. Tailored codes can even outperform the Steane code with realistic experimental noise, and without any increase in the experimental complexity, as we demonstrate by comparison in the observed error model in a recent seven-qubit trapped ion experiment.

Finite mixture model: A maximum likelihood estimation approach on time series data

NASA Astrophysics Data System (ADS)

Yen, Phoong Seuk; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad

2014-09-01

Recently, statistician emphasized on the fitting of finite mixture model by using maximum likelihood estimation as it provides asymptotic properties. In addition, it shows consistency properties as the sample sizes increases to infinity. This illustrated that maximum likelihood estimation is an unbiased estimator. Moreover, the estimate parameters obtained from the application of maximum likelihood estimation have smallest variance as compared to others statistical method as the sample sizes increases. Thus, maximum likelihood estimation is adopted in this paper to fit the two-component mixture model in order to explore the relationship between rubber price and exchange rate for Malaysia, Thailand, Philippines and Indonesia. Results described that there is a negative effect among rubber price and exchange rate for all selected countries.

Estimating Gravity Biases with Wavelets in Support of a 1-cm Accurate Geoid Model

NASA Astrophysics Data System (ADS)

Ahlgren, K.; Li, X.

2017-12-01

Systematic errors that reside in surface gravity datasets are one of the major hurdles in constructing a high-accuracy geoid model at high resolutions. The National Oceanic and Atmospheric Administration's (NOAA) National Geodetic Survey (NGS) has an extensive historical surface gravity dataset consisting of approximately 10 million gravity points that are known to have systematic biases at the mGal level (Saleh et al. 2013). As most relevant metadata is absent, estimating and removing these errors to be consistent with a global geopotential model and airborne data in the corresponding wavelength is quite a difficult endeavor. However, this is crucial to support a 1-cm accurate geoid model for the United States. With recently available independent gravity information from GRACE/GOCE and airborne gravity from the NGS Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, several different methods of bias estimation are investigated which utilize radial basis functions and wavelet decomposition. We estimate a surface gravity value by incorporating a satellite gravity model, airborne gravity data, and forward-modeled topography at wavelet levels according to each dataset's spatial wavelength. Considering the estimated gravity values over an entire gravity survey, an estimate of the bias and/or correction for the entire survey can be found and applied. In order to assess the accuracy of each bias estimation method, two techniques are used. First, each bias estimation method is used to predict the bias for two high-quality (unbiased and high accuracy) geoid slope validation surveys (GSVS) (Smith et al. 2013 & Wang et al. 2017). Since these surveys are unbiased, the various bias estimation methods should reflect that and provide an absolute accuracy metric for each of the bias estimation methods. Secondly, the corrected gravity datasets from each of the bias estimation methods are used to build a geoid model. The accuracy of each geoid model provides an additional metric to assess the performance of each bias estimation method. The geoid model accuracies are assessed using the two GSVS lines and GPS-leveling data across the United States.

Generating Performance Models for Irregular Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friese, Ryan D.; Tallent, Nathan R.; Vishnu, Abhinav

2017-05-30

Many applications have irregular behavior --- non-uniform input data, input-dependent solvers, irregular memory accesses, unbiased branches --- that cannot be captured using today's automated performance modeling techniques. We describe new hierarchical critical path analyses for the \\Palm model generation tool. To create a model's structure, we capture tasks along representative MPI critical paths. We create a histogram of critical tasks with parameterized task arguments and instance counts. To model each task, we identify hot instruction-level sub-paths and model each sub-path based on data flow, instruction scheduling, and data locality. We describe application models that generate accurate predictions for strong scalingmore » when varying CPU speed, cache speed, memory speed, and architecture. We present results for the Sweep3D neutron transport benchmark; Page Rank on multiple graphs; Support Vector Machine with pruning; and PFLOTRAN's reactive flow/transport solver with domain-induced load imbalance.« less

Tracking student progress in a game-like physics learning environment with a Monte Carlo Bayesian knowledge tracing model

NASA Astrophysics Data System (ADS)

Gweon, Gey-Hong; Lee, Hee-Sun; Dorsey, Chad; Tinker, Robert; Finzer, William; Damelin, Daniel

2015-03-01

In tracking student learning in on-line learning systems, the Bayesian knowledge tracing (BKT) model is a popular model. However, the model has well-known problems such as the identifiability problem or the empirical degeneracy problem. Understanding of these problems remain unclear and solutions to them remain subjective. Here, we analyze the log data from an online physics learning program with our new model, a Monte Carlo BKT model. With our new approach, we are able to perform a completely unbiased analysis, which can then be used for classifying student learning patterns and performances. Furthermore, a theoretical analysis of the BKT model and our computational work shed new light on the nature of the aforementioned problems. This material is based upon work supported by the National Science Foundation under Grant REC-1147621 and REC-1435470.

Estimation of group means when adjusting for covariates in generalized linear models.

PubMed

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

Novel Gene Expression Profile of Women with Intrinsic Skin Youthfulness by Whole Transcriptome Sequencing

PubMed Central

Xu, Jin; Spitale, Robert C.; Guan, Linna; Flynn, Ryan A.; Torre, Eduardo A.; Li, Rui; Raber, Inbar; Qu, Kun; Kern, Dale; Knaggs, Helen E.; Chang, Howard Y.; Chang, Anne Lynn S.

2016-01-01

While much is known about genes that promote aging, little is known about genes that protect against or prevent aging, particularly in human skin. The main objective of this study was to perform an unbiased, whole transcriptome search for genes that associate with intrinsic skin youthfulness. To accomplish this, healthy women (n = 122) of European descent, ages 18–89 years with Fitzpatrick skin type I/II were examined for facial skin aging parameters and clinical covariates, including smoking and ultraviolet exposure. Skin youthfulness was defined as the top 10% of individuals whose assessed skin aging features were most discrepant with their chronological ages. Skin biopsies from sun-protected inner arm were subjected to 3’-end sequencing for expression quantification, with results verified by quantitative reverse transcriptase-polymerase chain reaction. Unbiased clustering revealed gene expression signatures characteristic of older women with skin youthfulness (n = 12) compared to older women without skin youthfulness (n = 33), after accounting for gene expression changes associated with chronological age alone. Gene set analysis was performed using Genomica open-access software. This study identified a novel set of candidate skin youthfulness genes demonstrating differences between SY and non-SY group, including pleckstrin homology like domain family A member 1 (PHLDA1) (p = 2.4x10-5), a follicle stem cell marker, and hyaluronan synthase 2-anti-sense 1 (HAS2-AS1) (p = 0.00105), a non-coding RNA that is part of the hyaluronan synthesis pathway. We show that immunologic gene sets are the most significantly altered in skin youthfulness (with the most significant gene set p = 2.4x10-5), suggesting the immune system plays an important role in skin youthfulness, a finding that has not previously been recognized. These results are a valuable resource from which multiple future studies may be undertaken to better understand the mechanisms that promote skin youthfulness in humans. PMID:27829007

Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast

PubMed Central

Rossouw, Debra; Næs, Tormod; Bauer, Florian F

2008-01-01

Background 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. Results For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. Conclusion The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance. PMID:18990252

Age, environment, object recognition and morphological diversity of GFAP-immunolabeled astrocytes.

PubMed

Diniz, Daniel Guerreiro; de Oliveira, Marcus Augusto; de Lima, Camila Mendes; Fôro, César Augusto Raiol; Sosthenes, Marcia Consentino Kronka; Bento-Torres, João; da Costa Vasconcelos, Pedro Fernando; Anthony, Daniel Clive; Diniz, Cristovam Wanderley Picanço

2016-10-10

Few studies have explored the glial response to a standard environment and how the response may be associated with age-related cognitive decline in learning and memory. Here we investigated aging and environmental influences on hippocampal-dependent tasks and on the morphology of an unbiased selected population of astrocytes from the molecular layer of dentate gyrus, which is the main target of perforant pathway. Six and twenty-month-old female, albino Swiss mice were housed, from weaning, in a standard or enriched environment, including running wheels for exercise and tested for object recognition and contextual memories. Young adult and aged subjects, independent of environment, were able to distinguish familiar from novel objects. All experimental groups, except aged mice from standard environment, distinguish stationary from displaced objects. Young adult but not aged mice, independent of environment, were able to distinguish older from recent objects. Only young mice from an enriched environment were able to distinguish novel from familiar contexts. Unbiased selected astrocytes from the molecular layer of the dentate gyrus were reconstructed in three-dimensions and classified using hierarchical cluster analysis of bimodal or multimodal morphological features. We found two morphological phenotypes of astrocytes and we designated type I the astrocytes that exhibited significantly higher values of morphological complexity as compared with type II. Complexity = [Sum of the terminal orders + Number of terminals] × [Total branch length/Number of primary branches]. On average, type I morphological complexity seems to be much more sensitive to age and environmental influences than that of type II. Indeed, aging and environmental impoverishment interact and reduce the morphological complexity of type I astrocytes at a point that they could not be distinguished anymore from type II. We suggest these two types of astrocytes may have different physiological roles and that the detrimental effects of aging on memory in mice from a standard environment may be associated with a reduction of astrocytes morphological diversity.

There Is No Simple Model of the Plasma Membrane Organization

PubMed Central

Bernardino de la Serna, Jorge; Schütz, Gerhard J.; Eggeling, Christian; Cebecauer, Marek

2016-01-01

Ever since technologies enabled the characterization of eukaryotic plasma membranes, heterogeneities in the distributions of its constituents were observed. Over the years this led to the proposal of various models describing the plasma membrane organization such as lipid shells, picket-and-fences, lipid rafts, or protein islands, as addressed in numerous publications and reviews. Instead of emphasizing on one model we in this review give a brief overview over current models and highlight how current experimental work in one or the other way do not support the existence of a single overarching model. Instead, we highlight the vast variety of membrane properties and components, their influences and impacts. We believe that highlighting such controversial discoveries will stimulate unbiased research on plasma membrane organization and functionality, leading to a better understanding of this essential cellular structure. PMID:27747212

There Is No Simple Model of the Plasma Membrane Organization.

PubMed

Bernardino de la Serna, Jorge; Schütz, Gerhard J; Eggeling, Christian; Cebecauer, Marek

2016-01-01

Ever since technologies enabled the characterization of eukaryotic plasma membranes, heterogeneities in the distributions of its constituents were observed. Over the years this led to the proposal of various models describing the plasma membrane organization such as lipid shells, picket-and-fences, lipid rafts, or protein islands, as addressed in numerous publications and reviews. Instead of emphasizing on one model we in this review give a brief overview over current models and highlight how current experimental work in one or the other way do not support the existence of a single overarching model. Instead, we highlight the vast variety of membrane properties and components, their influences and impacts. We believe that highlighting such controversial discoveries will stimulate unbiased research on plasma membrane organization and functionality, leading to a better understanding of this essential cellular structure.

Revisiting AFLP fingerprinting for an unbiased assessment of genetic structure and differentiation of taurine and zebu cattle

PubMed Central

2014-01-01

Background Descendants from the extinct aurochs (Bos primigenius), taurine (Bos taurus) and zebu cattle (Bos indicus) were domesticated 10,000 years ago in Southwestern and Southern Asia, respectively, and colonized the world undergoing complex events of admixture and selection. Molecular data, in particular genome-wide single nucleotide polymorphism (SNP) markers, can complement historic and archaeological records to elucidate these past events. However, SNP ascertainment in cattle has been optimized for taurine breeds, imposing limitations to the study of diversity in zebu cattle. As amplified fragment length polymorphism (AFLP) markers are discovered and genotyped as the samples are assayed, this type of marker is free of ascertainment bias. In order to obtain unbiased assessments of genetic differentiation and structure in taurine and zebu cattle, we analyzed a dataset of 135 AFLP markers in 1,593 samples from 13 zebu and 58 taurine breeds, representing nine continental areas. Results We found a geographical pattern of expected heterozygosity in European taurine breeds decreasing with the distance from the domestication centre, arguing against a large-scale introgression from European or African aurochs. Zebu cattle were found to be at least as diverse as taurine cattle. Western African zebu cattle were found to have diverged more from Indian zebu than South American zebu. Model-based clustering and ancestry informative markers analyses suggested that this is due to taurine introgression. Although a large part of South American zebu cattle also descend from taurine cows, we did not detect significant levels of taurine ancestry in these breeds, probably because of systematic backcrossing with zebu bulls. Furthermore, limited zebu introgression was found in Podolian taurine breeds in Italy. Conclusions The assessment of cattle diversity reported here contributes an unbiased global view to genetic differentiation and structure of taurine and zebu cattle populations, which is essential for an effective conservation of the bovine genetic resources. PMID:24739206

Estimation of genetic parameters and response to selection for a continuous trait subject to culling before testing.

PubMed

Arnason, T; Albertsdóttir, E; Fikse, W F; Eriksson, S; Sigurdsson, A

2012-02-01

The consequences of assuming a zero environmental covariance between a binary trait 'test-status' and a continuous trait on the estimates of genetic parameters by restricted maximum likelihood and Gibbs sampling and on response from genetic selection when the true environmental covariance deviates from zero were studied. Data were simulated for two traits (one that culling was based on and a continuous trait) using the following true parameters, on the underlying scale: h² = 0.4; r(A) = 0.5; r(E) = 0.5, 0.0 or -0.5. The selection on the continuous trait was applied to five subsequent generations where 25 sires and 500 dams produced 1500 offspring per generation. Mass selection was applied in the analysis of the effect on estimation of genetic parameters. Estimated breeding values were used in the study of the effect of genetic selection on response and accuracy. The culling frequency was either 0.5 or 0.8 within each generation. Each of 10 replicates included 7500 records on 'test-status' and 9600 animals in the pedigree file. Results from bivariate analysis showed unbiased estimates of variance components and genetic parameters when true r(E) = 0.0. For r(E) = 0.5, variance components (13-19% bias) and especially (50-80%) were underestimated for the continuous trait, while heritability estimates were unbiased. For r(E) = -0.5, heritability estimates of test-status were unbiased, while genetic variance and heritability of the continuous trait together with were overestimated (25-50%). The bias was larger for the higher culling frequency. Culling always reduced genetic progress from selection, but the genetic progress was found to be robust to the use of wrong parameter values of the true environmental correlation between test-status and the continuous trait. Use of a bivariate linear-linear model reduced bias in genetic evaluations, when data were subject to culling. © 2011 Blackwell Verlag GmbH.

A UNIFIED FRAMEWORK FOR VARIANCE COMPONENT ESTIMATION WITH SUMMARY STATISTICS IN GENOME-WIDE ASSOCIATION STUDIES.

PubMed

Zhou, Xiang

2017-12-01

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces downward-biased estimates in case control studies. To remedy these drawbacks, we present an alternative framework for variance component estimation, which we refer to as MQS. MQS is based on the method of moments (MoM) and the minimal norm quadratic unbiased estimation (MINQUE) criterion, and brings two seemingly unrelated methods-the renowned Haseman-Elston (HE) regression and the recent LD score regression (LDSC)-into the same unified statistical framework. With this new framework, we provide an alternative but mathematically equivalent form of HE that allows for the use of summary statistics. We provide an exact estimation form of LDSC to yield unbiased and statistically more efficient estimates. A key feature of our method is its ability to pair marginal z -scores computed using all samples with SNP correlation information computed using a small random subset of individuals (or individuals from a proper reference panel), while capable of producing estimates that can be almost as accurate as if both quantities are computed using the full data. As a result, our method produces unbiased and statistically efficient estimates, and makes use of summary statistics, while it is computationally efficient for large data sets. Using simulations and applications to 37 phenotypes from 8 real data sets, we illustrate the benefits of our method for estimating and partitioning SNP heritability in population studies as well as for heritability estimation in family studies. Our method is implemented in the GEMMA software package, freely available at www.xzlab.org/software.html.

Short Course Introduction to Quantitative Mineral Resource Assessments

USGS Publications Warehouse

Singer, Donald A.

2007-01-01

This is an abbreviated text supplementing the content of three sets of slides used in a short course that has been presented by the author at several workshops. The slides should be viewed in the order of (1) Introduction and models, (2) Delineation and estimation, and (3) Combining estimates and summary. References cited in the slides are listed at the end of this text. The purpose of the three-part form of mineral resource assessments discussed in the accompanying slides is to make unbiased quantitative assessments in a format needed in decision-support systems so that consequences of alternative courses of action can be examined. The three-part form of mineral resource assessments was developed to assist policy makers evaluate the consequences of alternative courses of action with respect to land use and mineral-resource development. The audience for three-part assessments is a governmental or industrial policy maker, a manager of exploration, a planner of regional development, or similar decision-maker. Some of the tools and models presented here will be useful for selection of exploration sites, but that is a side benefit, not the goal. To provide unbiased information, we recommend the three-part form of mineral resource assessments where general locations of undiscovered deposits are delineated from a deposit type's geologic setting, frequency distributions of tonnages and grades of well-explored deposits serve as models of grades and tonnages of undiscovered deposits, and number of undiscovered deposits are estimated probabilistically by type. The internally consistent descriptive, grade and tonnage, deposit density, and economic models used in the design of the three-part form of assessments reduce the chances of biased estimates of the undiscovered resources. What and why quantitative resource assessments: The kind of assessment recommended here is founded in decision analysis in order to provide a framework for making decisions concerning mineral resources under conditions of uncertainty. What this means is that we start with the question of what kinds of questions is the decision maker trying to resolve and what forms of information would aid in resolving these questions. Some applications of mineral resource assessments: To plan and guide exploration programs, to assist in land use planning, to plan the location of infrastructure, to estimate mineral endowment, and to identify deposits that present special environmental challenges. Why not just rank prospects / areas? Need for financial analysis, need for comparison with other land uses, need for comparison with distant tracts of land, need to know how uncertain the estimates are, need for consideration of economic and environmental consequences of possible development. Our goal is to provide unbiased information useful to decision-makers.

Beyond total treatment effects in randomised controlled trials: Baseline measurement of intermediate outcomes needed to reduce confounding in mediation investigations.

PubMed

Landau, Sabine; Emsley, Richard; Dunn, Graham

2018-06-01

Random allocation avoids confounding bias when estimating the average treatment effect. For continuous outcomes measured at post-treatment as well as prior to randomisation (baseline), analyses based on (A) post-treatment outcome alone, (B) change scores over the treatment phase or (C) conditioning on baseline values (analysis of covariance) provide unbiased estimators of the average treatment effect. The decision to include baseline values of the clinical outcome in the analysis is based on precision arguments, with analysis of covariance known to be most precise. Investigators increasingly carry out explanatory analyses to decompose total treatment effects into components that are mediated by an intermediate continuous outcome and a non-mediated part. Traditional mediation analysis might be performed based on (A) post-treatment values of the intermediate and clinical outcomes alone, (B) respective change scores or (C) conditioning on baseline measures of both intermediate and clinical outcomes. Using causal diagrams and Monte Carlo simulation, we investigated the performance of the three competing mediation approaches. We considered a data generating model that included three possible confounding processes involving baseline variables: The first two processes modelled baseline measures of the clinical variable or the intermediate variable as common causes of post-treatment measures of these two variables. The third process allowed the two baseline variables themselves to be correlated due to past common causes. We compared the analysis models implied by the competing mediation approaches with this data generating model to hypothesise likely biases in estimators, and tested these in a simulation study. We applied the methods to a randomised trial of pragmatic rehabilitation in patients with chronic fatigue syndrome, which examined the role of limiting activities as a mediator. Estimates of causal mediation effects derived by approach (A) will be biased if one of the three processes involving baseline measures of intermediate or clinical outcomes is operating. Necessary assumptions for the change score approach (B) to provide unbiased estimates under either process include the independence of baseline measures and change scores of the intermediate variable. Finally, estimates provided by the analysis of covariance approach (C) were found to be unbiased under all the three processes considered here. When applied to the example, there was evidence of mediation under all methods but the estimate of the indirect effect depended on the approach used with the proportion mediated varying from 57% to 86%. Trialists planning mediation analyses should measure baseline values of putative mediators as well as of continuous clinical outcomes. An analysis of covariance approach is recommended to avoid potential biases due to confounding processes involving baseline measures of intermediate or clinical outcomes, and not simply for increased precision.

The Unbiased Velocity Distribution of Neutron Stars from a Simulation of Pulsar Surveys

NASA Astrophysics Data System (ADS)

Arzoumanian, Z.; Cordes, J. M.; Chernoff, D.

1997-12-01

We present the results of a new simulation of the Galactic population of neutron stars: their birthrate, velocity distribution, luminosities, beaming characteristics, and spin evolution. The many simulations in the literature differ from one another primarily in their treatment of the selection effects associated with pulsar detection. Our method, the most realistic to date, goes beyond earlier efforts by retaining the full kinematic, rotational, luminosity, and beaming evolution of each simulated star: ``Monte-Carlo'' neutron stars are created according to assumed distributions (at birth) in spatial coordinates, kick velocity, and magnitudes and orientations of the spin and magnetic field vectors. The neutron stars spin down following an assumed braking law, and their Galactic trajectories are traced to the present epoch. For each star, a pulse waveform is generated using a phenomenological radio-beam model, obviating the need for an arbitrary beaming fraction. Luminosity is assumed to be a parameterized function of period and spin-down rate, with no intrinsic spread, and a parameterized death-line is applied. Interstellar dispersion and scattering consistent with survey instrumentation and the galactic locales of the neutron stars are applied to the pulse waveforms, which are Fourier analyzed and tested for detection following the techniques of real-world surveys. A unique algorithm is used to compare the populations of simulated and known, non-millisecond, pulsars in the multi-dimensional space of observables (any subset of galactic coordinates, dispersion measure, period, spin-down rate, flux, and proper motion). Model parameters are varied, and statistically independent neutron star populations are created until a maximum likelihood model is found. The highlight of this effort is an unbiased determination of the velocity distribution of neutron stars. We discuss the implications of our results for supernova physics, binary evolution, and the nature of gamma -ray transients.

Implementation of a Comprehensive Curriculum in Personal Finance for Medical Fellows

PubMed Central

Bar-Or, Yuval D; Fessler, Henry E; Desai, Dipan A

2018-01-01

Introduction: Many residents and fellows complete graduate medical education having received minimal unbiased financial planning guidance. This places them at risk of making ill-informed financial decisions, which may lead to significant harm to them and their families. Therefore, we sought to provide fellows with comprehensive unbiased financial education and empower them to make timely, constructive financial decisions. Methods: A self-selected cohort of cardiovascular disease, pulmonary and critical care, and infectious disease fellows (n = 18) at a single institution attended a live, eight-hour interactive course on personal finance. The course consisted of four two-hour sessions delivered over four weeks, facilitated by an unbiased business school faculty member with expertise in personal finance. Prior to the course, all participants completed a demographic survey. After course completion, participants were offered an exit survey evaluating the course, which also asked respondents for any tangible financial decisions made as a result of the course learning.  Results: Participants included 12 women and six men, with a mean age of 33 and varying amounts of debt and financial assets. Twelve respondents completed the exit survey, and all “Strongly Agreed” that courses on financial literacy are important for trainees. In addition, 11 reported that the course helped them make important financial decisions, providing 21 examples. Conclusions: Fellows derive a significant benefit from objective financial literacy education. Graduate medical education programs should offer comprehensive financial literacy education to all graduating trainees, and that education should be provided by an unbiased expert who has no incentive to sell financial products and services. PMID:29515942

Implementation of a Comprehensive Curriculum in Personal Finance for Medical Fellows.

PubMed

Bar-Or, Yuval D; Fessler, Henry E; Desai, Dipan A; Zakaria, Sammy

2018-01-01

Many residents and fellows complete graduate medical education having received minimal unbiased financial planning guidance. This places them at risk of making ill-informed financial decisions, which may lead to significant harm to them and their families. Therefore, we sought to provide fellows with comprehensive unbiased financial education and empower them to make timely, constructive financial decisions. A self-selected cohort of cardiovascular disease, pulmonary and critical care, and infectious disease fellows (n = 18) at a single institution attended a live, eight-hour interactive course on personal finance. The course consisted of four two-hour sessions delivered over four weeks, facilitated by an unbiased business school faculty member with expertise in personal finance. Prior to the course, all participants completed a demographic survey. After course completion, participants were offered an exit survey evaluating the course, which also asked respondents for any tangible financial decisions made as a result of the course learning.  Results: Participants included 12 women and six men, with a mean age of 33 and varying amounts of debt and financial assets. Twelve respondents completed the exit survey, and all "Strongly Agreed" that courses on financial literacy are important for trainees. In addition, 11 reported that the course helped them make important financial decisions, providing 21 examples. Fellows derive a significant benefit from objective financial literacy education. Graduate medical education programs should offer comprehensive financial literacy education to all graduating trainees, and that education should be provided by an unbiased expert who has no incentive to sell financial products and services.

Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

USGS Publications Warehouse

Duarte, Adam; Adams, Michael J.; Peterson, James T.

2018-01-01

Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision making. Therefore, we also discuss alternative approaches to yield unbiased estimates of population state variables using similar data types, and we stress that there is no substitute for an effective sample design that is grounded upon well-defined management objectives.

An Analysis Method for Superconducting Resonator Parameter Extraction with Complex Baseline Removal

NASA Technical Reports Server (NTRS)

Cataldo, Giuseppe

2014-01-01

A new semi-empirical model is proposed for extracting the quality (Q) factors of arrays of superconducting microwave kinetic inductance detectors (MKIDs). The determination of the total internal and coupling Q factors enables the computation of the loss in the superconducting transmission lines. The method used allows the simultaneous analysis of multiple interacting discrete resonators with the presence of a complex spectral baseline arising from reflections in the system. The baseline removal allows an unbiased estimate of the device response as measured in a cryogenic instrumentation setting.

Data Assimilation in the Presence of Forecast Bias: The GEOS Moisture Analysis

NASA Technical Reports Server (NTRS)

Dee, Dick P.; Todling, Ricardo

1999-01-01

We describe the application of the unbiased sequential analysis algorithm developed by Dee and da Silva (1998) to the GEOS DAS moisture analysis. The algorithm estimates the persistent component of model error using rawinsonde observations and adjusts the first-guess moisture field accordingly. Results of two seasonal data assimilation cycles show that moisture analysis bias is almost completely eliminated in all observed regions. The improved analyses cause a sizable reduction in the 6h-forecast bias and a marginal improvement in the error standard deviations.

UAV Control on the Basis of 3D Landmark Bearing-Only Observations.

PubMed

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-11-27

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks' position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.

Objective Analysis of Oceanic Data for Coast Guard Trajectory Models Phase II

DTIC Science & Technology

1997-12-01

as outliers depends on the desired probability of false alarm, Pfa values, which is the probability of marking a valid point as an outlier. Table 2-2...constructed to minimize the mean-squared prediction error of the grid point estimate under the constraint that the estimate is unbiased . The...prediction error, e= Zl(S) _oizl(Si)+oC1iZz(S) (2.44) subject to the constraints of unbiasedness , • c/1 = 1,and (2.45) i SCC12 = 0. (2.46) Denoting

Detection of seizures from small samples using nonlinear dynamic system theory.

PubMed

Yaylali, I; Koçak, H; Jayakar, P

1996-07-01

The electroencephalogram (EEG), like many other biological phenomena, is quite likely governed by nonlinear dynamics. Certain characteristics of the underlying dynamics have recently been quantified by computing the correlation dimensions (D2) of EEG time series data. In this paper, D2 of the unbiased autocovariance function of the scalp EEG data was used to detect electrographic seizure activity. Digital EEG data were acquired at a sampling rate of 200 Hz per channel and organized in continuous frames (duration 2.56 s, 512 data points). To increase the reliability of D2 computations with short duration data, raw EEG data were initially simplified using unbiased autocovariance analysis to highlight the periodic activity that is present during seizures. The D2 computation was then performed from the unbiased autocovariance function of each channel using the Grassberger-Procaccia method with Theiler's box-assisted correlation algorithm. Even with short duration data, this preprocessing proved to be computationally robust and displayed no significant sensitivity to implementation details such as the choices of embedding dimension and box size. The system successfully identified various types of seizures in clinical studies.

Biased and unbiased perceptual decision-making on vocal emotions.

PubMed

Dricu, Mihai; Ceravolo, Leonardo; Grandjean, Didier; Frühholz, Sascha

2017-11-24

Perceptual decision-making on emotions involves gathering sensory information about the affective state of another person and forming a decision on the likelihood of a particular state. These perceptual decisions can be of varying complexity as determined by different contexts. We used functional magnetic resonance imaging and a region of interest approach to investigate the brain activation and functional connectivity behind two forms of perceptual decision-making. More complex unbiased decisions on affective voices recruited an extended bilateral network consisting of the posterior inferior frontal cortex, the orbitofrontal cortex, the amygdala, and voice-sensitive areas in the auditory cortex. Less complex biased decisions on affective voices distinctly recruited the right mid inferior frontal cortex, pointing to a functional distinction in this region following decisional requirements. Furthermore, task-induced neural connectivity revealed stronger connections between these frontal, auditory, and limbic regions during unbiased relative to biased decision-making on affective voices. Together, the data shows that different types of perceptual decision-making on auditory emotions have distinct patterns of activations and functional coupling that follow the decisional strategies and cognitive mechanisms involved during these perceptual decisions.

Comprehensive Mechanistic Analysis of Hits from High-Throughput and Docking Screens against β-Lactamase

PubMed Central

Babaoglu, Kerim; Simeonov, Anton; Irwin, John J.; Nelson, Michael E.; Feng, Brian; Thomas, Craig J.; Cancian, Laura; Costi, M. Paola; Maltby, David A.; Jadhav, Ajit; Inglese, James; Austin, Christopher P.; Shoichet, Brian K.

2009-01-01

High-throughput screening (HTS) is widely used in drug discovery. Especially for screens of unbiased libraries, false positives can dominate “hit lists”; their origins are much debated. Here we determine the mechanism of every active hit from a screen of 70,563 unbiased molecules against β-lactamase using quantitative HTS (qHTS). Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators. Among the 70 remaining were 25 potent, covalent-acting β-lactams. Mass spectra, counter-screens, and crystallography identified 12 as promiscuous covalent inhibitors. The remaining 33 were either aggregators or irreproducible. No specific reversible inhibitors were found. We turned to molecular docking to prioritize molecules from the same library for testing at higher concentrations. Of 16 tested, 2 were modest inhibitors. Subsequent X-ray structures corresponded to the docking prediction. Analog synthesis improved affinity to 8 µM. These results suggest that it may be the physical behavior of organic molecules, not their reactivity, that accounts for most screening artifacts. Structure-based methods may prioritize weak-but-novel chemotypes in unbiased library screens. PMID:18333608

Construction of mutually unbiased bases with cyclic symmetry for qubit systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seyfarth, Ulrich; Ranade, Kedar S.

2011-10-15

For the complete estimation of arbitrary unknown quantum states by measurements, the use of mutually unbiased bases has been well established in theory and experiment for the past 20 years. However, most constructions of these bases make heavy use of abstract algebra and the mathematical theory of finite rings and fields, and no simple and generally accessible construction is available. This is particularly true in the case of a system composed of several qubits, which is arguably the most important case in quantum information science and quantum computation. In this paper, we close this gap by providing a simple andmore » straightforward method for the construction of mutually unbiased bases in the case of a qubit register. We show that our construction is also accessible to experiments, since only Hadamard and controlled-phase gates are needed, which are available in most practical realizations of a quantum computer. Moreover, our scheme possesses the optimal scaling possible, i.e., the number of gates scales only linearly in the number of qubits.« less

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging.

PubMed

Chen, Jin-Hua; Chen, Chun-Shu; Huang, Meng-Fan; Lin, Hung-Chih

2016-10-01

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback-Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed. © 2016 Society for Risk Analysis.

Proceedings of a USGS Workshop on Facing Tomorrow's Challenges Along the U.S.-Mexico Border - Monitoring, Modeling, and Forecasting Change Within the Arizona-Sonora Transboundary Watersheds

USGS Publications Warehouse

Norman, Laura M.; Hirsch, Derrick D.; Ward, A. Wesley

2008-01-01

INTRODUCTION TO THE WORKSHOP PROCEEDINGS Competition for water resources, habitats, and urban areas in the Borderlands has become an international concern. In the United States, Department of Interior Bureaus, Native American Tribes, and other State and Federal partners rely on the U.S. Geological Survey (USGS) to provide unbiased science and leadership in the Borderlands region. Consequently, the USGS hosted a workshop, ?Facing Tomorrow?s Challenges along the U.S.-Mexico Border,? on March 20?22, 2007, in Tucson, Ariz., focused specifically on monitoring, modeling, and forecasting change within the Arizona-Sonora Transboundary Watersheds

Efficiency optimization in a correlation ratchet with asymmetric unbiased fluctuations

NASA Astrophysics Data System (ADS)

Ai, Bao-Quan; Wang, Xian-Ju; Liu, Guo-Tao; Wen, De-Hua; Xie, Hui-Zhang; Chen, Wei; Liu, Liang-Gang

2003-12-01

The efficiency of a Brownian particle moving in a periodic potential in the presence of asymmetric unbiased fluctuations is investigated. We found that even on the quasistatic limit there is a regime where the efficiency can be a peaked function of temperature, which proves that thermal fluctuations facilitate the efficiency of energy transformation, contradicting the earlier findings [H. Kamegawa et al., Phys. Rev. Lett. 80, 5251 (1998)]. It is also found that the mutual interplay between temporal asymmetry and spatial asymmetry may induce optimized efficiency at finite temperatures. The ratchet is not most efficient when it gives maximum current.

AD620SQ/883B Total Ionizing Dose Radiation Lot Acceptance Report for RESTORE-LEO

NASA Technical Reports Server (NTRS)

Burton, Noah; Campola, Michael

2017-01-01

A Radiation Lot Acceptance Test was performed on the AD620SQ/883B, Lot 1708D, in accordance with MIL-STD-883, Method 1019, Condition D. Using a Co-60 source 4 biased parts and 4 unbiased parts were irradiated at 10 mrad/s (0.036 krad/hr) in intervals of approximately 1 krad from 3-10 krads, and ones of 5 krads from 10-25 krads, where it was annealed while unbiased at 25 degrees Celsius, for 2 days, and then, subsequently, annealed while biased at 25 degrees celsius, for another 7 days.

Quasi interpolation with Voronoi splines.

PubMed

Mirzargar, Mahsa; Entezari, Alireza

2011-12-01

We present a quasi interpolation framework that attains the optimal approximation-order of Voronoi splines for reconstruction of volumetric data sampled on general lattices. The quasi interpolation framework of Voronoi splines provides an unbiased reconstruction method across various lattices. Therefore this framework allows us to analyze and contrast the sampling-theoretic performance of general lattices, using signal reconstruction, in an unbiased manner. Our quasi interpolation methodology is implemented as an efficient FIR filter that can be applied online or as a preprocessing step. We present visual and numerical experiments that demonstrate the improved accuracy of reconstruction across lattices, using the quasi interpolation framework. © 2011 IEEE

Precision medicine in the age of big data: The present and future role of large-scale unbiased sequencing in drug discovery and development.

PubMed

Vicini, P; Fields, O; Lai, E; Litwack, E D; Martin, A-M; Morgan, T M; Pacanowski, M A; Papaluca, M; Perez, O D; Ringel, M S; Robson, M; Sakul, H; Vockley, J; Zaks, T; Dolsten, M; Søgaard, M

2016-02-01

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice. © 2015 American Society for Clinical Pharmacology and Therapeutics.

When pitch Accents Encode Speaker Commitment: Evidence from French Intonation.

PubMed

Michelas, Amandine; Portes, Cristel; Champagne-Lavau, Maud

2016-06-01

Recent studies on a variety of languages have shown that a speaker's commitment to the propositional content of his or her utterance can be encoded, among other strategies, by pitch accent types. Since prior research mainly relied on lexical-stress languages, our understanding of how speakers of a non-lexical-stress language encode speaker commitment is limited. This paper explores the contribution of the last pitch accent of an intonation phrase to convey speaker commitment in French, a language that has stress at the phrasal level as well as a restricted set of pitch accents. In a production experiment, participants had to produce sentences in two pragmatic contexts: unbiased questions (the speaker had no particular belief with respect to the expected answer) and negatively biased questions (the speaker believed the proposition to be false). Results revealed that negatively biased questions consistently exhibited an additional unaccented F0 peak in the preaccentual syllable (an H+!H* pitch accent) while unbiased questions were often realized with a rising pattern across the accented syllable (an H* pitch accent). These results provide evidence that pitch accent types in French can signal the speaker's belief about the certainty of the proposition expressed in French. It also has implications for the phonological model of French intonation.

Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

PubMed Central

Ackerman, Matthew S.; Johri, Parul; Spitze, Ken; Xu, Sen; Doak, Thomas G.; Young, Kimberly; Lynch, Michael

2017-01-01

Population structure can be described by genotypic-correlation coefficients between groups of individuals, the most basic of which are the pairwise relatedness coefficients between any two individuals. There are nine pairwise relatedness coefficients in the most general model, and we show that these can be reduced to seven coefficients for biallelic loci. Although all nine coefficients can be estimated from pedigrees, six coefficients have been beyond empirical reach. We provide a numerical optimization procedure that estimates all seven reduced coefficients from population-genomic data. Simulations show that the procedure is nearly unbiased, even at 3× coverage, and errors in five of the seven coefficients are statistically uncorrelated. The remaining two coefficients have a negative correlation of errors, but their sum provides an unbiased assessment of the overall correlation of heterozygosity between two individuals. Application of these new methods to four populations of the freshwater crustacean Daphnia pulex reveal the occurrence of half siblings in our samples, as well as a number of identical individuals that are likely obligately asexual clone mates. Statistically significant negative estimates of these pairwise relatedness coefficients, including inbreeding coefficients that were typically negative, underscore the difficulties that arise when interpreting genotypic correlations as estimations of the probability that alleles are identical by descent. PMID:28341647

Empirical best linear unbiased prediction method for small areas with restricted maximum likelihood and bootstrap procedure to estimate the average of household expenditure per capita in Banjar Regency

NASA Astrophysics Data System (ADS)

Aminah, Agustin Siti; Pawitan, Gandhi; Tantular, Bertho

2017-03-01

So far, most of the data published by Statistics Indonesia (BPS) as data providers for national statistics are still limited to the district level. Less sufficient sample size for smaller area levels to make the measurement of poverty indicators with direct estimation produced high standard error. Therefore, the analysis based on it is unreliable. To solve this problem, the estimation method which can provide a better accuracy by combining survey data and other auxiliary data is required. One method often used for the estimation is the Small Area Estimation (SAE). There are many methods used in SAE, one of them is Empirical Best Linear Unbiased Prediction (EBLUP). EBLUP method of maximum likelihood (ML) procedures does not consider the loss of degrees of freedom due to estimating β with β ^. This drawback motivates the use of the restricted maximum likelihood (REML) procedure. This paper proposed EBLUP with REML procedure for estimating poverty indicators by modeling the average of household expenditures per capita and implemented bootstrap procedure to calculate MSE (Mean Square Error) to compare the accuracy EBLUP method with the direct estimation method. Results show that EBLUP method reduced MSE in small area estimation.

Using Markov state models to study self-assembly

PubMed Central

Perkett, Matthew R.; Hagan, Michael F.

2014-01-01

Markov state models (MSMs) have been demonstrated to be a powerful method for computationally studying intramolecular processes such as protein folding and macromolecular conformational changes. In this article, we present a new approach to construct MSMs that is applicable to modeling a broad class of multi-molecular assembly reactions. Distinct structures formed during assembly are distinguished by their undirected graphs, which are defined by strong subunit interactions. Spatial inhomogeneities of free subunits are accounted for using a recently developed Gaussian-based signature. Simplifications to this state identification are also investigated. The feasibility of this approach is demonstrated on two different coarse-grained models for virus self-assembly. We find good agreement between the dynamics predicted by the MSMs and long, unbiased simulations, and that the MSMs can reduce overall simulation time by orders of magnitude. PMID:24907984

Interpretation of the cosmic microwave background radiation anisotropy detected by the COBE Differential Microwave Radiometer

NASA Technical Reports Server (NTRS)

Wright, E. L.; Meyer, S. S.; Bennett, C. L.; Boggess, N. W.; Cheng, E. S.; Hauser, M. G.; Kogut, A.; Lineweaver, C.; Mather, J. C.; Smoot, G. F.

1992-01-01

The large-scale cosmic background anisotropy detected by the COBE Differential Microwave Radiometer (DMR) instrument is compared to the sensitive previous measurements on various angular scales, and to the predictions of a wide variety of models of structure formation driven by gravitational instability. The observed anisotropy is consistent with all previously measured upper limits and with a number of dynamical models of structure formation. For example, the data agree with an unbiased cold dark matter (CDM) model with H0 = 50 km/s Mpc and Delta-M/M = 1 in a 16 Mpc radius sphere. Other models, such as CDM plus massive neutrinos (hot dark matter (HDM)), or CDM with a nonzero cosmological constant are also consistent with the COBE detection and can provide the extra power seen on 5-10,000 km/s scales.

Valence-Dependent Belief Updating: Computational Validation

PubMed Central

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments. PMID:28706499

Cancer Survival Estimates Due to Non-Uniform Loss to Follow-Up and Non-Proportional Hazards

PubMed

K M, Jagathnath Krishna; Mathew, Aleyamma; Sara George, Preethi

2017-06-25

Background: Cancer survival depends on loss to follow-up (LFU) and non-proportional hazards (non-PH). If LFU is high, survival will be over-estimated. If hazard is non-PH, rank tests will provide biased inference and Cox-model will provide biased hazard-ratio. We assessed the bias due to LFU and non-PH factor in cancer survival and provided alternate methods for unbiased inference and hazard-ratio. Materials and Methods: Kaplan-Meier survival were plotted using a realistic breast cancer (BC) data-set, with >40%, 5-year LFU and compared it using another BC data-set with <15%, 5-year LFU to assess the bias in survival due to high LFU. Age at diagnosis of the latter data set was used to illustrate the bias due to a non-PH factor. Log-rank test was employed to assess the bias in p-value and Cox-model was used to assess the bias in hazard-ratio for the non-PH factor. Schoenfeld statistic was used to test the non-PH of age. For the non-PH factor, we employed Renyi statistic for inference and time dependent Cox-model for hazard-ratio. Results: Five-year BC survival was 69% (SE: 1.1%) vs. 90% (SE: 0.7%) for data with low vs. high LFU respectively. Age (<45, 46-54 & >54 years) was a non-PH factor (p-value: 0.036). However, survival by age was significant (log-rank p-value: 0.026), but not significant using Renyi statistic (p=0.067). Hazard ratio (HR) for age using Cox-model was 1.012 (95%CI: 1.004 -1.019) and the same using time-dependent Cox-model was in the other direction (HR: 0.997; 95% CI: 0.997- 0.998). Conclusion: Over-estimated survival was observed for cancer with high LFU. Log-rank statistic and Cox-model provided biased results for non-PH factor. For data with non-PH factors, Renyi statistic and time dependent Cox-model can be used as alternate methods to obtain unbiased inference and estimates. Creative Commons Attribution License

Valence-Dependent Belief Updating: Computational Validation.

PubMed

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments.

Why do Models Overestimate Surface Ozone in the Southeastern United States?

NASA Technical Reports Server (NTRS)

Travis, Katherine R.; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Zhu, Lei; Yu, Karen; Miller, Christopher C.; Yantosca, Robert M.; Sulprizio, Melissa P.;

Why do models overestimate surface ozone in the Southeast United States?

NASA Astrophysics Data System (ADS)

Travis, Katherine R.; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Zhu, Lei; Yu, Karen; Miller, Christopher C.; Yantosca, Robert M.; Sulprizio, Melissa P.; Thompson, Anne M.; Wennberg, Paul O.; Crounse, John D.; St. Clair, Jason M.; Cohen, Ronald C.; Laughner, Joshua L.; Dibb, Jack E.; Hall, Samuel R.; Ullmann, Kirk; Wolfe, Glenn M.; Pollack, Illana B.; Peischl, Jeff; Neuman, Jonathan A.; Zhou, Xianliang

2016-11-01

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx ≡ NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25° × 0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30-60 %, dependent on the assumption of the contribution by soil NOx emissions. Upper-tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 6 ± 14 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Why do Models Overestimate Surface Ozone in the Southeastern United States?

PubMed

Travis, Katherine R; Jacob, Daniel J; Fisher, Jenny A; Kim, Patrick S; Marais, Eloise A; Zhu, Lei; Yu, Karen; Miller, Christopher C; Yantosca, Robert M; Sulprizio, Melissa P; Thompson, Anne M; Wennberg, Paul O; Crounse, John D; St Clair, Jason M; Cohen, Ronald C; Laughner, Joshua L; Dibb, Jack E; Hall, Samuel R; Ullmann, Kirk; Wolfe, Glenn M; Pollack, Illana B; Peischl, Jeff; Neuman, Jonathan A; Zhou, Xianliang

2016-01-01

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NO x ≡ NO + NO 2 ) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC 4 RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO x from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC 4 RS observations of NO x and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO 2 columns. Our results indicate that NEI NO x emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NO x emissions. Upper tropospheric NO 2 from lightning makes a large contribution to satellite observations of tropospheric NO 2 that must be accounted for when using these data to estimate surface NO x emissions. We find that only half of isoprene oxidation proceeds by the high-NO x pathway to produce ozone; this fraction is only moderately sensitive to changes in NO x emissions because isoprene and NO x emissions are spatially segregated. GEOS-Chem with reduced NO x emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NO x oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Why do Models Overestimate Surface Ozone in the Southeastern United States?

PubMed Central

Travis, Katherine R.; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Zhu, Lei; Yu, Karen; Miller, Christopher C.; Yantosca, Robert M.; Sulprizio, Melissa P.; Thompson, Anne M.; Wennberg, Paul O.; Crounse, John D.; St Clair, Jason M.; Cohen, Ronald C.; Laughner, Joshua L.; Dibb, Jack E.; Hall, Samuel R.; Ullmann, Kirk; Wolfe, Glenn M.; Pollack, Illana B.; Peischl, Jeff; Neuman, Jonathan A.; Zhou, Xianliang

2018-01-01

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NOx ≡ NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC4RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25°×0.3125° horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NOx from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC4RS observations of NOx and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NOx emissions from mobile and industrial sources must be reduced by 30–60%, dependent on the assumption of the contribution by soil NOx emissions. Upper tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NOx emissions. We find that only half of isoprene oxidation proceeds by the high-NOx pathway to produce ozone; this fraction is only moderately sensitive to changes in NOx emissions because isoprene and NOx emissions are spatially segregated. GEOS-Chem with reduced NOx emissions provides an unbiased simulation of ozone observations from the aircraft, and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NOx oxidation products. However, the model is still biased high by 8±13 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer. PMID:29619045

Semi-quantitative proteomics of mammalian cells upon short-term exposure to non-ionizing electromagnetic fields.

PubMed

Kuzniar, Arnold; Laffeber, Charlie; Eppink, Berina; Bezstarosti, Karel; Dekkers, Dick; Woelders, Henri; Zwamborn, A Peter M; Demmers, Jeroen; Lebbink, Joyce H G; Kanaar, Roland

2017-01-01

The potential effects of non-ionizing electromagnetic fields (EMFs), such as those emitted by power-lines (in extremely low frequency range), mobile cellular systems and wireless networking devices (in radio frequency range) on human health have been intensively researched and debated. However, how exposure to these EMFs may lead to biological changes underlying possible health effects is still unclear. To reveal EMF-induced molecular changes, unbiased experiments (without a priori focusing on specific biological processes) with sensitive readouts are required. We present the first proteome-wide semi-quantitative mass spectrometry analysis of human fibroblasts, osteosarcomas and mouse embryonic stem cells exposed to three types of non-ionizing EMFs (ELF 50 Hz, UMTS 2.1 GHz and WiFi 5.8 GHz). We performed controlled in vitro EMF exposures of metabolically labeled mammalian cells followed by reliable statistical analyses of differential protein- and pathway-level regulations using an array of established bioinformatics methods. Our results indicate that less than 1% of the quantitated human or mouse proteome responds to the EMFs by small changes in protein abundance. Further network-based analysis of the differentially regulated proteins did not detect significantly perturbed cellular processes or pathways in human and mouse cells in response to ELF, UMTS or WiFi exposure. In conclusion, our extensive bioinformatics analyses of semi-quantitative mass spectrometry data do not support the notion that the short-time exposures to non-ionizing EMFs have a consistent biologically significant bearing on mammalian cells in culture.

Ventral tegmental area GABA neurons and opiate motivation

PubMed Central

Vargas-Perez, Hector; Mabey, Jennifer K.; Shin, Samuel I.; Steffensen, Scott C.; van der Kooy, Derek

2013-01-01

Rational Past research has demonstrated that when an animal changes from a previously drug-naive to an opiate-dependent and withdrawn state, morphine’s motivational effects are switched from a tegmental pedunculopontine nucleus (TPP)-dependent to a dopamine-dependent pathway. Interestingly, a corresponding change is observed in ventral tegmental area (VTA) GABAA receptors, which change from mediating hyperpolarization of VTA GABA neurons to mediating depolarization. Objectives The present study investigated whether pharmacological manipulation of VTA GABAA receptor activity could directly influence the mechanisms underlying opiate motivation. Results Using an unbiased place conditioning procedure, we demonstrated that in Wistar rats, intra-VTA administration of furosemide, a Cl− cotransporter inhibitor, was able to promote a switch in the mechanisms underlying morphine’s motivational properties, one which is normally observed only after chronic opiate exposure. This behavioral switch was prevented by intra-VTA administration of acetazolamide, an inhibitor of the bicarbonate ion-producing carbonic anhydrase enzyme. Electrophysiological recordings of mouse VTA showed that furosemide reduced the sensitivity of VTA GABA neurons to inhibition by the GABAA receptor agonist muscimol, instead increasing the firing rate of a significant subset of these GABA neurons. Conclusion Our results suggest that the carbonic anhydrase enzyme may constitute part of a common VTA GABA neuron-based biological pathway responsible for controlling the mechanisms underlying opiate motivation, supporting the hypothesis that VTA GABAA receptor hyperpolarization or depolarization is responsible for selecting TPP- or dopamine-dependent motivational outputs, respectively. PMID:23392354