Subdural haematoma in infancy

A 1950's medical research paper on Subdural Haematoma during a child's infancy

MedZIM: Mediation analysis for Zero-Inflated Mediators with applications to microbiome data

The human microbiome can contribute to the pathogenesis of many complex diseases such as cancer and Alzheimer's disease by mediating disease-leading causal pathways. However, standard mediation analysis is not adequate in the context of microbiome data due to the excessive number of zero values in the data. Zero-valued sequencing reads, commonly observed in microbiome studies, arise for technical and/or biological reasons. Mediation analysis approaches for analyzing zero-inflated mediators are still lacking largely because of challenges raised by the zero-inflated data structure: (a) disentangling the mediation effect induced by the point mass at zero; and (b) identifying the observed zero-valued data points that are actually not zero (i.e., false zeros). We develop a novel mediation analysis method under the potential-outcomes framework to fill this gap. We show that the mediation effect of the microbiome can be decomposed into two components that are inherent to the two-part nature of zero-inflated distributions. The first component corresponds to the mediation effect attributable to a unit-change over the positive relative abundance and the second component corresponds to the mediation effect attributable to discrete binary change of the mediator from zero to a non-zero state. With probabilistic models to account for observing zeros, we also address the challenge with false zeros. A comprehensive simulation study and the applications in two real microbiome studies demonstrate that our approach outperforms existing mediation analysis approaches.Comment: Corresponding: Zhigang L

Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network.

BACKGROUND: Multiple waves of transmission during infectious disease epidemics represent a major public health challenge, but the ecological and behavioral drivers of epidemic resurgence are poorly understood. In theory, community structure—aggregation into highly intraconnected and loosely interconnected social groups—within human populations may lead to punctuated outbreaks as diseases progress from one community to the next. However, this explanation has been largely overlooked in favor of temporal shifts in environmental conditions and human behavior and because of the difficulties associated with estimating large-scale contact patterns. OBJECTIVE: The aim was to characterize naturally arising patterns of human contact that are capable of producing simulated epidemics with multiple wave structures. METHODS: We used an extensive dataset of proximal physical contacts between users of a public Wi-Fi Internet system to evaluate the epidemiological implications of an empirical urban contact network. We characterized the modularity (community structure) of the network and then estimated epidemic dynamics under a percolation-based model of infectious disease spread on the network. We classified simulated epidemics as multiwave using a novel metric and we identified network structures that were critical to the network's ability to produce multiwave epidemics. RESULTS: We identified robust community structure in a large, empirical urban contact network from which multiwave epidemics may emerge naturally. This pattern was fueled by a special kind of insularity in which locally popular individuals were not the ones forging contacts with more distant social groups. CONCLUSIONS: Our results suggest that ordinary contact patterns can produce multiwave epidemics at the scale of a single urban area without the temporal shifts that are usually assumed to be responsible. Understanding the role of community structure in epidemic dynamics allows officials to anticipate epidemic resurgence without having to forecast future changes in hosts, pathogens, or the environment

Phylogeography of Lyme borreliosis-group spirochetes and methicillin-resistant <em>Staphylococcus aureus</em>

SUMMARYMultilocus sequence typing (MLST) and multilocus sequence analysis (MLSA) have revolutionized understanding the global epidemiology of many medically relevant bacteria utilizing a number, mostly seven, of housekeeping genes. A more recent introduction, single nucleotide polymorphisms (SNPs), constitutes an even more powerful tool for bacterial typing, population genetic studies and phylogeography. The introduction of massive parallel sequencing has made genome re-sequencing and SNP discovery more economical for investigations of microbial organisms. In this paper we review phylogeographic studies on Lyme borreliosis (LB)-group spirochetes and methicillin-resistantStaphylococcus aureus(MRSA). Members of the LB-group spirochetes are tick-transmitted zoonotic bacteria that have many hosts and differ in their degree of host specialism, constituting a highly complex system. MRSA is a directly transmitted pathogen that may be acquired by contact with infected people, animals or MRSA-contaminated objects. For the LB-group spirochetes, MLSA has proved a powerful tool for species assignment and phylogeographic investigations while forS. aureus, genome-wide SNP data have been used to study the very short-term evolution of two important MRSA lineages, ST239 and ST225. These data are detailed in this review.</jats:p

Refining the Global Spatial Limits of Dengue Virus Transmission by Evidence-Based Consensus

Background: Dengue is a growing problem both in its geographical spread and in its intensity, and yet current global distribution remains highly uncertain. Challenges in diagnosis and diagnostic methods as well as highly variable national health systems mean no single data source can reliably estimate the distribution of this disease. As such, there is a lack of agreement on national dengue status among international health organisations. Here we bring together all available information on dengue occurrence using a novel approach to produce an evidence consensus map of the disease range that highlights nations with an uncertain dengue status. Methods/Principle Findings: A baseline methodology was used to assess a range of evidence for each country. In regions where dengue status was uncertain, additional evidence types were included to either clarify dengue status or confirm that it is unknown at this time. An algorithm was developed that assesses evidence quality and consistency, giving each country an evidence consensus score. Using this approach, we were able to generate a contemporary global map of national-level dengue status that assigns a relative measure of certainty and identifies gaps in the available evidence

Effect of density of state on isotope effect exponent of two-band superconductors

The exact formula of Tc's equation and the isotope effect exponent of two-band s-wave superconductors in weak-coupling limit are derived by considering the influence of two kinds of density of state : constant and van Hove singularity. The pairing interaction in each band consisted of 2 parts : the electron-phonon interaction and non-electron-phonon interaction are included in our model. We find that the interband interaction of electron-phonon show more effect on isotope exponent than the intraband interaction and the isotope effect exponent with constant density of state can fit to an experimental data,MgB2, and high-Tc superconductors, better than van Hove singularity density of state.Comment: 11 pages. accepted in Physica

Evidence-based Tool for Triggering School Closures during Influenza Outbreaks, Japan

Guidelines available to school administrators to support school closure decisions during influenza outbreaks are usually not evidence-based. Using empirical data on absentee rates of elementary school students in Japan, we developed a simple and practical algorithm for determining the optimal timing of school closures for control of influenza outbreaks