A Canadian Critical Care Trials Group project in collaboration with the international forum for acute care trialists - Collaborative H1N1 Adjuvant Treatment pilot trial (CHAT): study protocol and design of a randomized controlled trial

Background

The Vaccine Assessment using Linked Data (VALiD) trial compared opt-in and opt-out parental consent for a population-based childhood vaccine safety surveillance program using data linkage. A subsequent telephone interview of all households enrolled in the trial elicited parental intent regarding the return or non-return of reply forms for opt-in and opt-out consent. This paper describes the rationale for the trial and provides an overview of the design and methods.

Methods/Design

Single-centre, single-blind, randomised controlled trial (RCT) stratified by firstborn status. Mothers who gave birth at one tertiary South Australian hospital were randomised at six weeks post-partum to receive an opt-in or opt-out reply form, along with information explaining data linkage. The primary outcome at 10 weeks post-partum was parental participation in each arm, as indicated by the respective return or non-return of a reply form (or via telephone or email response). A subsequent telephone interview at 10 weeks post-partum elicited parental intent regarding the return or non-return of the reply form, and attitudes and knowledge about data linkage, vaccine safety, consent preferences and vaccination practices. Enrolment began in July 2009 and 1,129 households were recruited in a three-month period. Analysis has not yet been undertaken. The participation rate and selection bias for each method of consent will be compared when the data are analysed.

Discussion

The VALiD RCT represents the first trial of opt-in versus opt-out consent for a data linkage study that assesses consent preferences and intent compared with actual opting in or opting out behaviour, and socioeconomic factors. The limitations to generalisability are discussed.

Trial registration

Australian New Zealand Clinical Trials Registry ACTRN12610000332022     

White matter changes and word finding failures with increasing age

Background

Increasing life expectancy necessitates the better understanding of the neurophysiological underpinnings of age-related cognitive changes. The majority of research examining structural-cognitive relationships in aging focuses on the role of age-related changes to grey matter integrity. In the current study, we examined the relationship between age-related changes in white matter and language production. More specifically, we concentrated on word-finding failures, which increase with age.

Methodology/Principal Findings

We used Diffusion tensor MRI (a technique used to image, in vivo, the diffusion of water molecules in brain tissue) to relate white matter integrity to measures of successful and unsuccessful picture naming. Diffusion tensor images were used to calculate Fractional Anisotropy (FA) images. FA is considered to be a measure of white matter organization/integrity. FA images were related to measures of successful picture naming and to word finding failures using voxel-based linear regression analyses. Successful naming rates correlated positively with white matter integrity across a broad range of regions implicated in language production. However, word finding failure rates correlated negatively with a more restricted region in the posterior aspect of superior longitudinal fasciculus.

Conclusions/Significance

The use of DTI-MRI provides evidence for the relationship between age-related white matter changes in specific language regions and word finding failures in old age.     

Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits

In vivo optogenetic strategies have redefined our ability to assay how neural circuits govern behavior. Although acutely implanted optical fibers have previously been used in such studies, long-term control over neuronal activity has been largely unachievable. Here we describe a method to construct implantable optical fibers to readily manipulate neural circuit elements with minimal tissue damage or change in light output over time (weeks to months). Implanted optical fibers readily interface with in vivo electrophysiological arrays or electrochemical detection electrodes. The procedure described here, from implant construction to the start of behavioral experimentation, can be completed in approximately 2-6 weeks. Successful use of implantable optical fibers will allow for long-term control of mammalian neural circuits in vivo, which is integral to the study of the neurobiology of behavior.     

Enhanced neuronal plasticity and elevated endogenous sAPPα levels in mice over-expressing MMP9

Evidence accumulating during the past few years points to a significant role of matrix metalloproteinase 9 (MMP9) enzymatic activity in synaptic plasticity and cognitive processes. We have previously demonstrated that MMP9 is involved in receptor-mediated α-secretase-like cleavage of APP in vitro, resulting in increased secretion of sAPPα, the soluble N-terminal product of the non-amyloidogenic pathway known to be involved in neuronal plasticity and memory formation. To study the in vivo role of MMP9, we have generated transgenic mice over-expressing MMP9 in the brain. Herein, we demonstrate that MMP9 transgenic animals display enhanced performance in the non-spatial novel object recognition and the spatial water-maze task and that their enhanced performance was accompanied by increased dendritic spine density in the hippocampus and cortex following behavioural testing. Consistent with the above observations, the electrophysiological analysis revealed prolonged maintenance of long-term synaptic potentiation in hippocampal slices from MMP9 transgenic mice. Moreover, elevated sAPPα levels in the hippocampus and cortex of MPP9 transgenic animals were also observed. Overall, our results extend previous findings on the physiological role of MMP9 in neuronal plasticity and furthermore reveal that, APP may be one of the physiological proteolytic targets of MMP9 in vivo.     

Pancrustacean phylogeny in the light of new phylogenomic data: support for Remipedia as the possible sister group of Hexapoda

Remipedes are a small and enigmatic group of crustaceans, first described only 30 years ago. Analyses of both morphological and molecular data have recently suggested a close relationship between Remipedia and Hexapoda. If true, the remipedes occupy an important position in pancrustacean evolution and may be pivotal for understanding the evolutionary history of crustaceans and hexapods. However, it is important to test this hypothesis using new data and new types of analytical approaches. Here, we assembled a phylogenomic data set of 131 taxa, incorporating newly generated 454 expressed sequence tag (EST) data from six species of crustaceans, representing five lineages (Remipedia, Laevicaudata, Spinicaudata, Ostracoda, and Malacostraca). This data set includes all crustacean species for which EST data are available (46 species), and our largest alignment encompasses 866,479 amino acid positions and 1,886 genes. A series of phylogenomic analyses was performed to evaluate pancrustacean relationships. We significantly improved the quality of our data for predicting putative orthologous genes and for generating data subsets by matrix reduction procedures, thereby improving the signal to noise ratio in the data. Eight different data sets were constructed, representing various combinations of orthologous genes, data subsets, and taxa. Our results demonstrate that the different ways to compile an initial data set of core orthologs and the selection of data subsets by matrix reduction can have marked effects on the reconstructed phylogenetic trees. Nonetheless, all eight data sets strongly support Pancrustacea with Remipedia as the sister group to Hexapoda. This is the first time that a sister group relationship of Remipedia and Hexapoda has been inferred using a comprehensive phylogenomic data set that is based on EST data. We also show that selecting data subsets with increased overall signal can help to identify and prevent artifacts in phylogenetic analyses.     

Psychological distress as a risk factor for death from cerebrovascular disease

Background:

Little is known about psychological risk factors in cerebrovascular disease. We examined the association between psychological distress and risk of death due to cerebrovascular disease.

Methods:

We obtained data from 68 652 adult participants of the Health Survey for England (mean age 54.9 [standard deviation 13.9] yr, 45.0% male sex) with no known history of cardiovascular diseases at baseline. We used the 12-item General Health Questionnaire (GHQ-12) to assess the presence of psychological distress. We followed participants for eight years for cause-specific death using linkage to national registers.

Results:

There were 2367 deaths due to cardiovascular disease during follow-up. Relative to participants with no symptoms of psychological distress (GHQ-12 score 0) at baseline, people with psychological distress (GHQ-12 score ≥ 4, 14.7% of participants) had an increased risk of death from cerebrovascular disease (adjusted hazard ratio [HR] 1.66, 95% confidence interval [CI] 1.32–2.08) and ischemic heart disease (adjusted HR 1.59, 95% CI 1.34–1.88). There was also evidence of a dose–response effect with increasing GHQ-12 score (p for trend < 0.001 in all analyses). Associations were only marginally attenuated after we adjusted for possible confounders, including socioeconomic status, smoking and use of antihypertensive medications.

Interpretation:

Psychological distress was associated with increased risk of death due to cerebrovascular disease in a large population-representative cohort. These data suggest that the cardiovascular effects of psychological distress are not limited to coronary artery disease.Psychological constructs are becoming increasingly recognized as risk factors and triggers for cardiovascular events.¹ To date, most cardiovascular research has focused on coronary artery disease rather than cerebrovascular disease. Several studies have examined the association between symptoms of depression and risk of stroke,^2–11 although the results have been inconsistent, and effect sizes are generally modest.¹² For example, some evidence from epidemiological studies has shown a relation between depression and incident stroke.^2–7 However, a recent study showed an association between depression and coronary artery disease but not cerebrovascular disease.¹¹ This finding is consistent with other analyses that have also found null associations for stroke outcomes.^8–10 Other investigators have suggested that psychological distress is a more robust predictor of stroke than are symptoms of depression.¹³In addition to a paucity of evidence linking psychological distress with risk of stroke, extant evidence is hampered by a series of methodological problems. These limitations include small sample sizes (including rarity of outcome), a limited range of confounding data, an unknown influence of existing comorbidity on psychological distress (reverse causality) and few data from women. We addressed these shortcomings by examining the association between psychological distress and risk of death due to cerebrovascular disease in a large, well-characterized cohort of men and women representative of the general population.     

A critical assessment of storytelling: gene ontology categories and the importance of validating genomic scans

In the age of whole-genome population genetics, so-called genomic scan studies often conclude with a long list of putatively selected loci. These lists are then further scrutinized to annotate these regions by gene function, corresponding biological processes, expression levels, or gene networks. Such annotations are often used to assess and/or verify the validity of the genome scan and the statistical methods that have been used to perform the analyses. Furthermore, these results are frequently considered to validate "true-positives" if the identified regions make biological sense a posteriori. Here, we show that this approach can be potentially misleading. By simulating neutral evolutionary histories, we demonstrate that it is possible not only to obtain an extremely high false-positive rate but also to make biological sense out of the false-positives and construct a sensible biological narrative. Results are compared with a recent polymorphism data set from Drosophila melanogaster.     

Assessing the root of bilaterian animals with scalable phylogenomic methods

A clear picture of animal relationships is a prerequisite to understand how the morphological and ecological diversity of animals evolved over time. Among others, the placement of the acoelomorph flatworms, Acoela and Nemertodermatida, has fundamental implications for the origin and evolution of various animal organ systems. Their position, however, has been inconsistent in phylogenetic studies using one or several genes. Furthermore, Acoela has been among the least stable taxa in recent animal phylogenomic analyses, which simultaneously examine many genes from many species, while Nemertodermatida has not been sampled in any phylogenomic study. New sequence data are presented here from organisms targeted for their instability or lack of representation in prior analyses, and are analysed in combination with other publicly available data. We also designed new automated explicit methods for identifying and selecting common genes across different species, and developed highly optimized supercomputing tools to reconstruct relationships from gene sequences. The results of the work corroborate several recently established findings about animal relationships and provide new support for the placement of other groups. These new data and methods strongly uphold previous suggestions that Acoelomorpha is sister clade to all other bilaterian animals, find diminishing evidence for the placement of the enigmatic Xenoturbella within Deuterostomia, and place Cycliophora with Entoprocta and Ectoprocta. The work highlights the implications that these arrangements have for metazoan evolution and permits a clearer picture of ancestral morphologies and life histories in the deep past.     

Importing statistical measures into Artemis enhances gene identification in the <Emphasis Type="Italic">Leishmania</Emphasis> genome project

Background

Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces.

Results

Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODON USAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence.

Conclusion

An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.