Selecting Essential Information for Biosurveillance—A Multi-Criteria Decision Analysis

The National Strategy for Biosurveillancedefines biosurveillance as “the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels.” However, the strategy does not specify how “essential information” is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being “essential”. Thequestion of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of “essential information” for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.     

Independence of the Sodium and Potassium Conductance Channels: A Kinetic Argument

Tightly coupled models for the sodium and potassium conductance changes, in which the potassium “on” process is intimately related to the sodium “on” and “off” processes, are studied. It is shown that such coupled models are incapable of simultaneously showing the observed effects of conditioning potentials on sodium inactivation and on the translation of the potassium conductance in time. It is concluded that the primary mechanisms for the sodium and potassium channels are probably independent.     

Confidence Intervals for fMRI Activation Maps

Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experimental results. First, no information is represented about trends at voxels that do not pass the statistical test. Second, no information is given about the range of probable effect sizes at voxels that do pass the statistical test. This leads to a fundamental error in interpreting activation maps by naïve viewers, where it is assumed that colored, “active” voxels are reliably different from uncolored “inactive” voxels. In other domains, confidence intervals have been added to data graphics to reduce such errors. Here, we first document the prevalence of the fundamental error of interpretation, and then present a method for solving it by depicting confidence intervals in fMRI activation maps. Presenting images where the bounds of confidence intervals at each voxel are coded as color allows readers to visually test for differences between “active” and “inactive” voxels, and permits for more proper interpretation of neuroimaging data. Our specific graphical methods are intended as initial proposals to spur broader discussion of how to present confidence intervals for fMRI data.     

Tyrosine Phosphorylation of Dbl Regulates GTPase Signaling

Rho GTPases are molecular “switches” that cycle between “on” (GTP-bound) and “off” (GDP-bound) states and regulate numerous cellular activities such as gene expression, protein synthesis, cytoskeletal rearrangements, and metabolic responses. Dysregulation of GTPases is a key feature of many diseases, especially cancers. Guanine nucleotide exchange factors (GEFs) of the Dbl family are activated by mitogenic cell surface receptors and activate the Rho family GTPases Cdc42, Rac1, and RhoA. The molecular mechanisms that regulate GEFs from the Dbl family are poorly understood. Our studies reveal that Dbl is phosphorylated on tyrosine residues upon stimulation by growth factors and that this event is critical for the regulated activation of the GEF. These findings uncover a novel layer of complexity in the physiological regulation of this protein.     

X-Ray Solution Scattering of Squid Heavy Meromyosin: Strengthening the Evidence for an Ancient Compact off State

The overall conformations of regulated myosins or heavy meromyosins from chicken/turkey, scallop, tarantula, limulus, and scorpion sources have been studied by a number of techniques, including electron microscopy, sedimentation, and pulsed electron paramagnetic resonance. These studies have indicated that the binding of regulatory ions changes the conformation of the molecule from a compact shape found in the “off” state of the muscle to extended relationships between the tail and independently mobile heads that predominate in the “on” state. Here we strengthen the argument for the generality of this conformational change by using small angle X-ray scattering on heavy meromyosin from squid. Small angle X-ray scattering allows the protein to be visualized in solution under mild and relatively physiological conditions, and squid differs from the other species studied by at least 500 million years of evolution. Analysis of the data indicates that upon addition of Ca²⁺ the radius of gyration increases. Differences in the squid “on” and “off” states are clearly distinguishable as bimodal and unimodal pair distance distribution functions respectively. These observations are consistent with a Ca²⁺-free squid heavy meromyosin that is compact, but which becomes extended when Ca²⁺ is bound. Further, the scattering profile derived from the current model of tarantula heavy meromyosin in the “off” state is in excellent agreement with the measured “off” state scattering profile for squid heavy meromyosin. The previous and current studies together provide significant evidence that regulated myosin''s compact off-state conformation is an ancient trait, inherited from a common ancestor during divergent evolution.     

The Role of Informative and Ambiguous Feedback in Avoidance Behavior: Empirical and Computational Findings

Avoidance behavior is a critical component of many psychiatric disorders, and as such, it is important to understand how avoidance behavior arises, and whether it can be modified. In this study, we used empirical and computational methods to assess the role of informational feedback and ambiguous outcome in avoidance behavior. We adapted a computer-based probabilistic classification learning task, which includes positive, negative and no-feedback outcomes; the latter outcome is ambiguous as it might signal either a successful outcome (missed punishment) or a failure (missed reward). Prior work with this task suggested that most healthy subjects viewed the no-feedback outcome as strongly positive. Interestingly, in a later version of the classification task, when healthy subjects were allowed to opt out of (i.e. avoid) responding, some subjects (“avoiders”) reliably avoided trials where there was a risk of punishment, but other subjects (“non-avoiders”) never made any avoidance responses at all. One possible interpretation is that the “non-avoiders” valued the no-feedback outcome so positively on punishment-based trials that they had little incentive to avoid. Another possible interpretation is that the outcome of an avoided trial is unspecified and that lack of information is aversive, decreasing subjects’ tendency to avoid. To examine these ideas, we here tested healthy young adults on versions of the task where avoidance responses either did or did not generate informational feedback about the optimal response. Results showed that provision of informational feedback decreased avoidance responses and also decreased categorization performance, without significantly affecting the percentage of subjects classified as “avoiders.” To better understand these results, we used a modified Q-learning model to fit individual subject data. Simulation results suggest that subjects in the feedback condition adjusted their behavior faster following better-than-expected outcomes, compared to subjects in the no-feedback condition. Additionally, in both task conditions, “avoiders” adjusted their behavior faster following worse-than-expected outcomes, and treated the ambiguous no-feedback outcome as less rewarding, compared to non-avoiders. Together, results shed light on the important role of ambiguous and informative feedback in avoidance behavior.     

Genome Wide Association for Addiction: Replicated Results and Comparisons of Two Analytic Approaches

Background

Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. “Nontemplate” genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance.

Methodology/Principal Findings

We report pooled “nontemplate” genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both “converge then cluster” and “cluster then converge” analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals.

Conclusions/Significance

These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to “cell adhesion” processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. “Nontemplate” GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, “template” GWA approaches in which “genome wide” levels of significance are sought for SNP data from single case vs control comparisons.     

Limitations on the Equivalent Cardiac Generator

This paper is a critical summary of the implications of potential theory in electrocardiography with particular attention to the “inverse problem.” It is emphasized that potential measurements on the human torso serve to determine only the multipole coefficients of the heart sources and that no additional information is available. An interpretation of these coefficients with respect to the actual electrophysiological sources is considered further on the basis of distribution theory.     

Variant Association Tools for Quality Control and Analysis of Large-Scale Sequence and Genotyping Array Data

Currently there is great interest in detecting associations between complex traits and rare variants. In this report, we describe Variant Association Tools (VAT) and the VAT pipeline, which implements best practices for rare-variant association studies. Highlights of VAT include variant-site and call-level quality control (QC), summary statistics, phenotype- and genotype-based sample selection, variant annotation, selection of variants for association analysis, and a collection of rare-variant association methods for analyzing qualitative and quantitative traits. The association testing framework for VAT is regression based, which readily allows for flexible construction of association models with multiple covariates and weighting themes based on allele frequencies or predicted functionality. Additionally, pathway analyses, conditional analyses, and analyses of gene-gene and gene-environment interactions can be performed. VAT is capable of rapidly scanning through data by using multi-process computation, adaptive permutation, and simultaneously conducting association analysis via multiple methods. Results are available in text or graphic file formats and additionally can be output to relational databases for further annotation and filtering. An interface to R language also facilitates user implementation of novel association methods. The VAT''s data QC and association-analysis pipeline can be applied to sequence, imputed, and genotyping array, e.g., “exome chip,” data, providing a reliable and reproducible computational environment in which to analyze small- to large-scale studies with data from the latest genotyping and sequencing technologies. Application of the VAT pipeline is demonstrated through analysis of data from the 1000 Genomes project.     

Powerful Sequence Similarity Search Methods and In-Depth Manual Analyses Can Identify Remote Homologs in Many Apparently “Orphan” Viral Proteins

The genome sequences of new viruses often contain many “orphan” or “taxon-specific” proteins apparently lacking homologs. However, because viral proteins evolve very fast, commonly used sequence similarity detection methods such as BLAST may overlook homologs. We analyzed a data set of proteins from RNA viruses characterized as “genus specific” by BLAST. More powerful methods developed recently, such as HHblits or HHpred (available through web-based, user-friendly interfaces), could detect distant homologs of a quarter of these proteins, suggesting that these methods should be used to annotate viral genomes. In-depth manual analyses of a subset of the remaining sequences, guided by contextual information such as taxonomy, gene order, or domain cooccurrence, identified distant homologs of another third. Thus, a combination of powerful automated methods and manual analyses can uncover distant homologs of many proteins thought to be orphans. We expect these methodological results to be also applicable to cellular organisms, since they generally evolve much more slowly than RNA viruses. As an application, we reanalyzed the genome of a bee pathogen, Chronic bee paralysis virus (CBPV). We could identify homologs of most of its proteins thought to be orphans; in each case, identifying homologs provided functional clues. We discovered that CBPV encodes a domain homologous to the Alphavirus methyltransferase-guanylyltransferase; a putative membrane protein, SP24, with homologs in unrelated insect viruses and insect-transmitted plant viruses having different morphologies (cileviruses, higreviruses, blunerviruses, negeviruses); and a putative virion glycoprotein, ORF2, also found in negeviruses. SP24 and ORF2 are probably major structural components of the virions.     

Assessment of the Reporting Quality of Randomized Controlled Trials on the Treatment of Diabetes Mellitus with Traditional Chinese Medicine: A Systematic Review

Background

After the publication of the CONSORT 2010 statement, few studies have been conducted to assess the reporting quality of randomized clinical trials (RCTs) on treatment of diabetes mellitus with Traditional Chinese Medicine (TCM) published in Chinese journals.

Objective

To investigate the current situation of the reporting quality of RCTs in leading medical journals in China with the CONSORT 2010 statement as criteria.

Methods

The China National Knowledge Infrastructure (CNKI) electronic database was searched for RCTs on the treatment of diabetes mellitus with TCM published in the Journal of Traditional Chinese Medicine, Chinese Journal of Integrated Traditional & Western Medicine, and the China Journal of Chinese Materia Medica from January to December 2011. We excluded trials reported as “animal studies”, “in vitro studies”, “case studies”, or “systematic reviews”. The CONSORT checklist was applied by two independent raters to evaluate the reporting quality of all eligible trials after discussing and comprehending the items thoroughly. Each item in the checklist was graded as either “yes” or “no” depending on whether it had been reported by the authors.

Results

We identified 27 RCTs. According to the 37 items in the CONSORT checklist, the average reporting percentage was 45.0%, in which the average reporting percentage for the “title and abstract”, the “introduction”, the “methods”, the “results”, the “discussion” and the “other information” was 33.3%, 88.9%, 36.4%, 54.4%, 71.6% and 14.8%, respectively. In the Journal of Traditional Chinese Medicine, Chinese Journal of Integrated Traditional & Western Medicine, and the China Journal of Chinese Materia Medica the average reporting percentage was 42.2%, 56.8%, and 46.0%, respectively.

Conclusions

The reporting quality of RCTs in these three journals was insufficient to allow readers to assess the validity of the trials. We recommend that editors require authors to use the CONSORT statement when reporting their trial results as a condition of publication.     

Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain

Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. Here, using data-driven analyses of resting-state functional magnetic resonance imaging (fMRI) data, we identified the networks that interact with the hippocampus—the default mode network (DMN) and a “medial temporal network” (MTN) that included regions in the medial temporal lobe (MTL) and precuneus. We observed that the MTN plays a critical role in connecting the visual network to the DMN and hippocampus. The DMN could be further divided into 3 subnetworks: a “posterior medial” (PM) subnetwork comprised of posterior cingulate and lateral parietal cortices; an “anterior temporal” (AT) subnetwork comprised of regions in the temporopolar and dorsomedial prefrontal cortex; and a “medial prefrontal” (MP) subnetwork comprised of regions primarily in the medial prefrontal cortex (mPFC). These networks vary in their functional connectivity (FC) along the hippocampal long axis and represent different kinds of information during memory-guided decision-making. Finally, a Neurosynth meta-analysis of fMRI studies suggests new hypotheses regarding the functions of the MTN and DMN subnetworks, providing a framework to guide future research on the neural architecture of episodic memory.

Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. This study uses network analyses of intrinsic brain networks at rest to identify and characterize brain networks that interact with the hippocampus and have distinct functions during memory-guided decision making.     

Assessment of Intraocular Measurements in Neonatal Foals and Association with Gender,Laterality, and Body Weight: A Clinical Study

Objective of this study was to describe intraocular measurements in newly born foals (1–7 days of age) and assess the association between globe measurements and gender, laterality, and body weight. B-scan ultrasonographic biometry was performed on both eyes of 22 healthy foals (44 eyes) ages 1–7 days using a 10-MHz transducer. Intraocular measurements (anterior chamber depth, central lens thickness, vitreous chamber depth, axial globe length, longitudinal globe length, lens poles distance) were carried out using the ultrasound internal calipers. The influence of gender (male or female), laterality (right or left eye), and body weight (“light” <48 kg; “heavy” ≥48 kg) on ocular measurements was analysed by the Student t test. Values of P<0.05 were accepted as significant for all analyses. Mean anterior chamber depth was 2.2±0.5 mm (Standard Deviation); central lens thickness was 9.9±0.8 mm; vitreous chamber depth was 15.5±1.1 mm; axial globe length was 27.6±1.6 mm; longitudinal globe length was 35.8±1.2 mm, and lens poles distance was 16.4±1.0 mm. Intraocular measurements were not influenced by gender, laterality nor body weight. This study provides reference values for intraocular measurements in neonatal foals and may be useful in the diagnosis and treatment of congenital and acquired pathologies involving the globe.     

Hippo Pathway Phylogenetics Predicts Monoubiquitylation of Salvador and Merlin/Nf2

Recently we employed phylogenetics to predict that the cellular interpretation of TGF-β signals is modulated by monoubiquitylation cycles affecting the Smad4 signal transducer/tumor suppressor. This prediction was subsequently validated by experiments in flies, frogs and mammalian cells. Here we apply a phylogenetic approach to the Hippo pathway and predict that two of its signal transducers, Salvador and Merlin/Nf2 (also a tumor suppressor) are regulated by monoubiquitylation. This regulatory mechanism does not lead to protein degradation but instead serves as a highly efficient “off/on” switch when the protein is subsequently deubiquitylated. Overall, our study shows that the creative application of phylogenetics can predict new roles for pathway components and new mechanisms for regulating intercellular signaling pathways.     

On the validation of crystallographic symmetry and the quality of structures

In 2008, Zwart and colleagues observed that the fraction of the structures deposited in the PDB alleged to have “pseudosymmetry” or “special noncrystallographic symmetry” (NCS) was about 6%, and that this percentage was rising annually. A few years later, Poon and colleagues found that 2% of all the crystal structures in the PDB belonged to higher symmetry space groups than those assigned to them. Here, I report an analysis of the X-ray diffraction data deposited for this class of structures, which shows that most of the “pseudosymmetry” and “special NCS” that has been reported is in fact true crystallographic symmetry (CS). This distinction is important because the credibility of crystal structures depends heavily on quality control statistics such as R_free that are unreliable when they are computed incorrectly, which they often are when CS is misidentified as “special NCS” or “pseudosymmetry”. When mistakes of this kind are made, artificially low values of R_free can give unjustified confidence in the accuracy of the reported structures.     

Statistical Analysis of Individual Participant Data Meta-Analyses: A Comparison of Methods and Recommendations for Practice

Background

Individual participant data (IPD) meta-analyses that obtain “raw” data from studies rather than summary data typically adopt a “two-stage” approach to analysis whereby IPD within trials generate summary measures, which are combined using standard meta-analytical methods. Recently, a range of “one-stage” approaches which combine all individual participant data in a single meta-analysis have been suggested as providing a more powerful and flexible approach. However, they are more complex to implement and require statistical support. This study uses a dataset to compare “two-stage” and “one-stage” models of varying complexity, to ascertain whether results obtained from the approaches differ in a clinically meaningful way.

Methods and Findings

We included data from 24 randomised controlled trials, evaluating antiplatelet agents, for the prevention of pre-eclampsia in pregnancy. We performed two-stage and one-stage IPD meta-analyses to estimate overall treatment effect and to explore potential treatment interactions whereby particular types of women and their babies might benefit differentially from receiving antiplatelets. Two-stage and one-stage approaches gave similar results, showing a benefit of using anti-platelets (Relative risk 0.90, 95% CI 0.84 to 0.97). Neither approach suggested that any particular type of women benefited more or less from antiplatelets. There were no material differences in results between different types of one-stage model.

Conclusions

For these data, two-stage and one-stage approaches to analysis produce similar results. Although one-stage models offer a flexible environment for exploring model structure and are useful where across study patterns relating to types of participant, intervention and outcome mask similar relationships within trials, the additional insights provided by their usage may not outweigh the costs of statistical support for routine application in syntheses of randomised controlled trials. Researchers considering undertaking an IPD meta-analysis should not necessarily be deterred by a perceived need for sophisticated statistical methods when combining information from large randomised trials.