One-sample aggregate data meta-analysis of medians

An aggregate data meta-analysis is a statistical method that pools the summary statistics of several selected studies to estimate the outcome of interest. When considering a continuous outcome, typically each study must report the same measure of the outcome variable and its spread (e.g., the sample mean and its standard error). However, some studies may instead report the median along with various measures of spread. Recently, the task of incorporating medians in meta-analysis has been achieved by estimating the sample mean and its standard error from each study that reports a median in order to meta-analyze the means. In this paper, we propose two alternative approaches to meta-analyze data that instead rely on medians. We systematically compare these approaches via simulation study to each other and to methods that transform the study-specific medians and spread into sample means and their standard errors. We demonstrate that the proposed median-based approaches perform better than the transformation-based approaches, especially when applied to skewed data and data with high inter-study variance. In addition, when meta-analyzing data that consists of medians, we show that the median-based approaches perform considerably better than or comparably to the best-case scenario for a transformation approach: conducting a meta-analysis using the actual sample mean and standard error of the mean of each study. Finally, we illustrate these approaches in a meta-analysis of patient delay in tuberculosis diagnosis

Functional organization and its implication in evolution of the human protein-protein interaction network

<p>Abstract</p> <p>Background</p> <p>Based on the distinguishing properties of protein-protein interaction networks such as power-law degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolve. More importantly, there is already evidence suggesting functional organization and significance of these networks. The current stochastic models of evolution, however, grow the network without consideration for biological function and natural selection.</p> <p>Results</p> <p>To test whether protein interaction networks are functionally organized and their impacts on the evolution of these networks, we analyzed their evolution at both the topological and functional level. We find that the human network is shown to be functionally organized, and its function evolves with the topological properties of the network. Our analysis suggests that function most likely affects local modularity of the network. Consistently, we further found that the topological unit is also the functional unit of the network.</p> <p>Conclusion</p> <p>We have demonstrated functional organization of a protein interaction network. Given our observations, we suggest that its significance should not be overlooked when studying network evolution.</p

Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis

Researchers increasingly use meta-analysis to synthesize the results of several studies in order to estimate a common effect. When the outcome variable is continuous, standard meta-analytic approaches assume that the primary studies report the sample mean and standard deviation of the outcome. However, when the outcome is skewed, authors sometimes summarize the data by reporting the sample median and one or both of (i) the minimum and maximum values and (ii) the first and third quartiles, but do not report the mean or standard deviation. To include these studies in meta-analysis, several methods have been developed to estimate the sample mean and standard deviation from the reported summary data. A major limitation of these widely used methods is that they assume that the outcome distribution is normal, which is unlikely to be tenable for studies reporting medians. We propose two novel approaches to estimate the sample mean and standard deviation when data are suspected to be non-normal. Our simulation results and empirical assessments show that the proposed methods often perform better than the existing methods when applied to non-normal data

Variational Quantum Gate Optimization at the Pulse Level

We experimentally investigate the viability of a variational quantum gate optimization protocol informed by the underlying physical Hamiltonian of fixed-frequency transmon qubits. The utility of the scheme is demonstrated through the successful experimental optimization of two and three qubit quantum gates tailored on the native cross-resonance interaction. The limits of such a strategy are investigated through the optimization of a gate based on Floquet-engineered three-qubit interactions, however parameter drift is identified as a key limiting factor preventing the implementation of such a scheme which the variational optimization protocol is unable to overcome.Comment: 19 pages, 13 figure

The Research Object Suite of Ontologies: Sharing and Exchanging Research Data and Methods on the Open Web

Research in life sciences is increasingly being conducted in a digital and online environment. In particular, life scientists have been pioneers in embracing new computational tools to conduct their investigations. To support the sharing of digital objects produced during such research investigations, we have witnessed in the last few years the emergence of specialized repositories, e.g., DataVerse and FigShare. Such repositories provide users with the means to share and publish datasets that were used or generated in research investigations. While these repositories have proven their usefulness, interpreting and reusing evidence for most research results is a challenging task. Additional contextual descriptions are needed to understand how those results were generated and/or the circumstances under which they were concluded. Because of this, scientists are calling for models that go beyond the publication of datasets to systematically capture the life cycle of scientific investigations and provide a single entry point to access the information about the hypothesis investigated, the datasets used, the experiments carried out, the results of the experiments, the people involved in the research, etc. In this paper we present the Research Object (RO) suite of ontologies, which provide a structured container to encapsulate research data and methods along with essential metadata descriptions. Research Objects are portable units that enable the sharing, preservation, interpretation and reuse of research investigation results. The ontologies we present have been designed in the light of requirements that we gathered from life scientists. They have been built upon existing popular vocabularies to facilitate interoperability. Furthermore, we have developed tools to support the creation and sharing of Research Objects, thereby promoting and facilitating their adoption.Comment: 20 page

Structure of Cdc4p, a Contractile Ring Protein Essential for Cytokinesis in Schizosaccharomyces pombe

The Schizosaccharomyces pombe Cdc4 protein is required for the formation and function of the contractile ring, presumably acting as a myosin light chain. By using NMR spectroscopy, we demonstrate that purified Cdc4p is a monomeric protein with two structurally independent domains, each exhibiting a fold reminiscent of the EF-hand class of calcium-binding proteins. Although Cdc4p has one potentially functional calcium-binding site, it does not bind calcium in vitro. Three variants of Cdc4p containing single point mutations responsible for temperature-sensitive arrest of the cell cycle at cytokinesis (Gly-19 to Glu, Gly-82 to Asp, and Gly-107 to Ser) were also characterized by NMR and circular dichroism spectroscopy. In each case, the amino acid substitution only leads to small perturbations in the conformation of the protein. Furthermore, thermal unfolding studies indicate that, like wild-type Cdc4p, the three mutant forms are all extremely stable, remaining completely folded at temperatures significantly above those causing failure of cytokinesis in intact cells. Therefore, the altered phenotype must arise directly from a disruption of the function of Cdc4p rather than indirectly through a disruption of its overall structure. Several mutant alleles of Cdc4p also show interallelic complementation in diploid cells. This phenomenon can be explained if Cdcp4 has more than one essential function or, alternatively, if two mutant proteins assemble to form a functional complex. Based on the structure of Cdc4p, possible models for interallelic complementation including interactions with partner proteins and the formation of a myosin complex with Cdc4p fulfilling the role of both an essential and regulatory light chain are proposed

A single-input binary counting module based on serine integrase site-specific recombination

A device that counts and records the number of events experienced by an individual cell could have many uses in experimental biology and biotechnology. Here, we report a DNA-based ‘latch’ that switches between two states upon each exposure to a repeated stimulus. The key component of the latch is a DNA segment whose orientation is inverted by the actions of ϕC31 integrase and its recombination directionality factor (RDF). Integrase expression is regulated by an external input, while RDF expression is controlled by the state of the latch, such that the orientation of the invertible segment switches efficiently each time the device receives an input pulse. Recombination occurs over a time scale of minutes after initiation of integrase expression. The latch requires a delay circuit, implemented with a transcriptional repressor expressed in only one state, to ensure that each input pulse results in only one inversion of the DNA segment. Development and optimization of the latch in living cells was driven by mathematical modelling of the recombination reactions and gene expression regulated by the switch. We discuss how N latches built with orthogonal site-specific recombination systems could be chained together to form a binary ripple counter that could count to 2N − 1

Inhibition of NAADP signalling on reperfusion protects the heart by preventing lethal calcium oscillations via two-pore channel 1 and opening of the mitochondrial permeability transition pore

Aims In the heart, a period of ischaemia followed by reperfusion evokes powerful cytosolic Ca2+ oscillations that can cause lethal cell injury. These signals represent attractive cardioprotective targets, but the underlying mechanisms of genesis are ill-defined. Here, we investigated the role of the second messenger nicotinic acid adenine dinucleotide phosphate (NAADP), which is known in several cell types to induce Ca2+ oscillations that initiate from acidic stores such as lysosomes, likely via two-pore channels (TPCs, TPC1 and 2). Methods and results An NAADP antagonist called Ned-K was developed by rational design based on a previously existing scaffold. Ned-K suppressed Ca2+ oscillations and dramatically protected cardiomyocytes from cell death in vitro after ischaemia and reoxygenation, preventing opening of the mitochondrial permeability transition pore. Ned-K profoundly decreased infarct size in mice in vivo. Transgenic mice lacking the endo-lysosomal TPC1 were also protected from injury. Conclusion NAADP signalling plays a major role in reperfusion-induced cell death and represents a potent pathway for protection against reperfusion injury

Prescription channeling of COX-2 inhibitors and traditional nonselective nonsteroidal anti-inflammatory drugs: a population-based case–control study

This pharmacoepidemiologic study was conducted to determine whether risk factors for upper gastrointestinal bleeding influenced the prescription of cyclo-oxygenase (COX)-2 inhibitors and traditional nonselective nonsteroidal anti-inflammatory drugs (NSAIDs) at the time when COX-2 inhibitors were first included in the formulary of reimbursed medications. A population-based case–control study was conducted in which the prevalence of risk factors and the medical histories of patients prescribed COX-2 inhibitors and traditional nonselective NSAIDs were compared. The study population consisted of a random sample of members of the Quebec drug plan (age 18 years or older) who received at least one dispensation of celecoxib (n = 42,422; cases), rofecoxib (n = 25,674; cases), or traditional nonselective NSAIDs (n = 12,418; controls) during the year 2000. All study data were obtained from the Quebec health care databases. Adjusting for income level, Chronic Disease Score, prior use of low-dose acetylsalicylic acid, acetaminophen, antidepressants, benzodiazepines, prescriber specialty, and time period, the following factors were significantly associated with the prescription of COX-2 inhibitors: age 75 years or older (odds ratio [OR] 4.22, 95% confidence interval [CI] 3.95–4.51), age 55–74 years (OR 3.23, 95% CI 3.06–3.40), female sex (OR 1.52, 95% CI 1.45–1.58), prior diagnosis of gastropathy (OR 1.21, 95% CI 1.08–1.36) and prior dispensation of gastroprotective agents (OR 1.57, 95% CI 1.47–1.67). Patients who received a traditional nonselective NSAID recently were more likely to switch to a coxib, especially first-time users (OR 2.17, 95% CI 1.93–2.43). Associations were significantly greater for celecoxib than rofecoxib for age, chronic NSAID use, and last NSAID use between 1 and 3 months before the index date. At the time of introduction of COX-2 inhibitors into the formulary, prescription channeling could confound risk comparisons across products