Mapping between measurement scales in meta-analysis, with application to measures of body mass index in children

Quantitative evidence synthesis methods aim to combine data from multiple medical trials to infer relative effects of different interventions. A challenge arises when trials report continuous outcomes on different measurement scales. To include all evidence in one coherent analysis, we require methods to `map' the outcomes onto a single scale. This is particularly challenging when trials report aggregate rather than individual data. We are motivated by a meta-analysis of interventions to prevent obesity in children. Trials report aggregate measurements of body mass index (BMI) either expressed as raw values or standardised for age and sex. We develop three methods for mapping between aggregate BMI data using known relationships between individual measurements on different scales. The first is an analytical method based on the mathematical definitions of z-scores and percentiles. The other two approaches involve sampling individual participant data on which to perform the conversions. One method is a straightforward sampling routine, while the other involves optimization with respect to the reported outcomes. In contrast to the analytical approach, these methods also have wider applicability for mapping between any pair of measurement scales with known or estimable individual-level relationships. We verify and contrast our methods using trials from our data set which report outcomes on multiple scales. We find that all methods recreate mean values with reasonable accuracy, but for standard deviations, optimization outperforms the other methods. However, the optimization method is more likely to underestimate standard deviations and is vulnerable to non-convergence.Comment: Main text: 15 pages, 3 figures, 2 tables Supplementary material: 10 pages, 10 figures, 3 table

Balanced multi-shot EPI for accelerated Cartesian MRF: An alternative to spiral MRF

The main purpose of this study is to show that a highly accelerated Cartesian MRF scheme using a multi-shot EPI readout (i.e. multi-shot EPI-MRF) can produce good quality multi-parametric maps such as T1, T2 and proton density (PD) in a sufficiently short scan duration that is similar to conventional MRF. This multi-shot approach allows considerable subsampling while traversing the entire k-space trajectory, can yield better SNR, reduced blurring, less distortion and can also be used to collect higher resolution data compared to existing single-shot EPI-MRF implementations. The generated parametric maps are compared to an accelerated spiral MRF implementation with the same acquisition parameters to evaluate the performance of this method. Additionally, an iterative reconstruction algorithm is applied to improve the accuracy of parametric map estimations and the fast convergence of EPI-MRF is also demonstrated.Comment: Proceedings of the Joint Annual Meeting ISMRM-ESMRMB 2018 - Pari

Chemical signaling in the gastrointestinal tract

Chemical signaling via the production of small molecules such as hormones has been studied in detail in higher organisms. These molecules have important functions in maintaining physiological homeostasis as well as allowing organisms to respond to external insults. Virtually every living cell produces hormone-like diffusible small molecules that can be used to convey messages to neighboring cells—a vital step in adaptation, development, and survival within populations. Although most of our knowledge on cellular chemical communication comes from studies of multicellular eukaryotes, it is now understood that bacteria can also communicate using sophisticated signaling systems, in a way analogous to those used by higher organisms. Many of these microbes live in close association with higher eukaryotes, in mutualistic or commensal relationships. We suggest that there may be a wealth of unidentified bioactive small molecules in the human body, originating from both microbial and human cells and that have important biological functions. Because chemical signaling has important roles for the biology of both microbes and humans, detecting, identifying, and studying these chemical signals can further our understanding of the chemical interplay between microbiota and their hosts and provide us with an unexplored source of molecules that could be used for human benefit

Experimental habitat fragmentation disrupts nematode infections in Australian skinks

Habitat conversion and fragmentation threaten biodiversity and disrupt species interactions. While parasites are recognized as ecologically important, the impacts of fragmentation on parasitism are poorly understood relative to other species interactions. This lack of understanding is in part due to confounding landscape factors that accompany fragmentation. Fragmentation experiments provide the opportunity to fill this knowledge gap by mechanistically testing how fragmentation affects parasitism while controlling landscape factors. In a large‐scale, long‐term experiment, we asked how fragmentation affects a host–parasite interaction between a skink and a parasitic nematode, which is trophically transmitted via a terrestrial amphipod intermediate host. We expected that previously observed amphipod declines resulting from fragmentation would result in decreased transmission of nematodes to skinks. In agreement, we found that nematodes were absent among skinks in the cleared matrix and that infections in fragments were about one quarter of those in continuous forest. Amphipods found in gut contents of skinks and collected from pitfall traps mirrored this pattern. A structural equation model supported the expectation that fragmentation disrupted this interaction by altering the abundance of amphipods and suggested that other variables are likely also important in mediating this effect. These findings advance understanding of how landscape change affects parasitism.This work was funded by an NSF Postdoctoral Research Fellowship in Biology (1309192) to J. Resasco and NSF funding to K. F. Davies (DEB-0841892

Robust 3D Reconstruction of Dynamic Scenes From Single-Photon Lidar Using Beta-Divergences

In this paper, we present a new algorithm for fast, online 3D reconstruction of dynamic scenes using times of arrival of photons recorded by single-photon detector arrays. One of the main challenges in 3D imaging using single-photon lidar in practical applications is the presence of strong ambient illumination which corrupts the data and can jeopardize the detection of peaks/surface in the signals. This background noise not only complicates the observation model classically used for 3D reconstruction but also the estimation procedure which requires iterative methods. In this work, we consider a new similarity measure for robust depth estimation, which allows us to use a simple observation model and a non-iterative estimation procedure while being robust to mis-specification of the background illumination model. This choice leads to a computationally attractive depth estimation procedure without significant degradation of the reconstruction performance. This new depth estimation procedure is coupled with a spatio-temporal model to capture the natural correlation between neighboring pixels and successive frames for dynamic scene analysis. The resulting online inference process is scalable and well suited for parallel implementation. The benefits of the proposed method are demonstrated through a series of experiments conducted with simulated and real single-photon lidar videos, allowing the analysis of dynamic scenes at 325 m observed under extreme ambient illumination conditions.Comment: 12 page

Bacterial Signaling Nucleotides Inhibit Yeast Cell Growth by Impacting Mitochondrial and Other Specifically Eukaryotic Functions

We have engineered $\textit{Saccharomyces cerevisiae}$ to inducibly synthesize the prokaryotic signaling nucleotides cyclic di-GMP (cdiGMP), cdiAMP, and ppGpp in order to characterize the range of effects these nucleotides exert on eukaryotic cell function during bacterial pathogenesis. Synthetic genetic array (SGA) and transcriptome analyses indicated that, while these compounds elicit some common reactions in yeast, there are also complex and distinctive responses to each of the three nucleotides. All three are capable of inhibiting eukaryotic cell growth, with the guanine nucleotides exhibiting stronger effects than cdiAMP. Mutations compromising mitochondrial function and chromatin remodeling show negative epistatic interactions with all three nucleotides. In contrast, certain mutations that cause defects in chromatin modification and ribosomal protein function show positive epistasis, alleviating growth inhibition by at least two of the three nucleotides. Uniquely, cdiGMP is lethal both to cells growing by respiration on acetate and to obligately fermentative petite mutants. cdiGMP is also synthetically lethal with the ribonucleotide reductase (RNR) inhibitor hydroxyurea. Heterologous expression of the human ppGpp hydrolase Mesh1p prevented the accumulation of ppGpp in the engineered yeast and restored cell growth. Extensive $\textit{in vivo}$ interactions between bacterial signaling molecules and eukaryotic gene function occur, resulting in outcomes ranging from growth inhibition to death. cdiGMP functions through a mechanism that must be compensated by unhindered RNR activity or by functionally competent mitochondria. Mesh1p may be required for abrogating the damaging effects of ppGpp in human cells subjected to bacterial infection.This work was supported by grant BB/J0/1821X/1 from the Biotechnology & Biological Sciences Research Council (UK)

The XMM Cluster Survey: Evidence for energy injection at high redshift from evolution of the X-ray luminosity-temperature relation

We measure the evolution of the X-ray luminosity-temperature (L_X-T) relation since z~1.5 using a sample of 211 serendipitously detected galaxy clusters with spectroscopic redshifts drawn from the XMM Cluster Survey first data release (XCS-DR1). This is the first study spanning this redshift range using a single, large, homogeneous cluster sample. Using an orthogonal regression technique, we find no evidence for evolution in the slope or intrinsic scatter of the relation since z~1.5, finding both to be consistent with previous measurements at z~0.1. However, the normalisation is seen to evolve negatively with respect to the self-similar expectation: we find E(z)^{-1} L_X = 10^{44.67 +/- 0.09} (T/5)^{3.04 +/- 0.16} (1+z)^{-1.5 +/- 0.5}, which is within 2 sigma of the zero evolution case. We see milder, but still negative, evolution with respect to self-similar when using a bisector regression technique. We compare our results to numerical simulations, where we fit simulated cluster samples using the same methods used on the XCS data. Our data favour models in which the majority of the excess entropy required to explain the slope of the L_X-T relation is injected at high redshift. Simulations in which AGN feedback is implemented using prescriptions from current semi-analytic galaxy formation models predict positive evolution of the normalisation, and differ from our data at more than 5 sigma. This suggests that more efficient feedback at high redshift may be needed in these models.Comment: Accepted for publication in MNRAS; 12 pages, 6 figures; added references to match published versio

Functional magnetic resonance imaging outcomes from a comprehensive magnetic resonance study of children with fetal alcohol spectrum disorders

A comprehensive neuropsychological/psychiatric, MR imaging, (MRI), MR spectroscopy (MRS), and functional MRI (fMRI) assessment was administered to children with fetal alcohol spectrum disorders (FASD) to determine if global and/or focal abnormalities could be identified, and distinguish diagnostic subclassifications across the spectrum. The four study groups included: 1. FAS/Partial FAS; 2. Static Encephalopathy/Alcohol Exposed (SE/AE); 3. Neurobehavioral Disorder/Alcohol Exposed (ND/AE); and 4. healthy peers with no prenatal alcohol exposure. fMRI outcomes are reported here. The neuropsychological/psychiatric, MRI, and MRS outcomes are reported separately. fMRI was used to assess activation in seven brain regions during performance of N-back working memory tasks. Children across the full spectrum of FASD exhibited significant working memory deficits and altered activation patterns in brain regions that are known to be involved in working memory. These results demonstrate the potential research and diagnostic value of this non-invasive MR tool in the field of FASD

Microevolution during the emergence of a monophasic Salmonella Typhimurium epidemic in the United Kingdom

Microevolutionary events associated with the emergence and clonal expansion of new 27 epidemic clones of bacterial pathogens hold the key to understanding the drivers of 28 epidemiological success. We describe a comparative whole genome sequence and 29 phylogenomic analysis of monophasic Salmonella Typhimurium isolates from the UK 30 and Italy from 2005-2012. Monophasic isolates from this time formed a single clade 31 distinct from recent monophasic epidemic clones described previously from North 32 America and Spain. The current UK monophasic epidemic clones encode a novel 33 genomic island encoding resistance to heavy metals (SGI-3), and composite transposon 34 encoding antibiotic resistance genes not present in other Typhimurium isolates, that 35 may have contributed to the epidemiological success. We also report a remarkable 36 degree of genotypic variation that accumulated during clonal expansion of a UK 37 epidemic including multiple independent acquisitions of a novel prophage carrying the 38 sopE gene and multiple deletion events affecting the phase II flagellin locus

Mechanisms of Myocardial Ischemia in Hypertrophic Cardiomyopathy : Insights From Wave Intensity Analysis and Magnetic Resonance

Background: Angina is common in hypertrophic cardiomyopathy (HCM) and is associated with abnormal myocardial perfusion. Wave intensity analysis improves the understanding of the mechanics of myocardial ischemia. Objectives: Wave intensity analysis was used to describe the mechanisms underlying perfusion abnormalities in patients with HCM. Methods: Simultaneous pressure and flow were measured in the proximal left anterior descending artery in 33 patients with HCM and 20 control patients at rest and during hyperemia, allowing calculation of wave intensity. Patients also underwent quantitative first-pass perfusion cardiac magnetic resonance to measure myocardial perfusion reserve. Results: Patients with HCM had a lower coronary flow reserve than control subjects (1.9 ± 0.8 vs. 2.7 ± 0.9; p = 0.01). Coronary hemodynamics in HCM were characterized by a very large backward compression wave during systole (38 ± 11% vs. 21 ± 6%; p < 0.001) and a proportionately smaller backward expansion wave (27% ± 8% vs. 33 ± 6%; p = 0.006) compared with control subjects. Patients with severe left ventricular outflow tract obstruction had a bisferiens pressure waveform resulting in an additional proximally originating deceleration wave during systole. The proportion of waves acting to accelerate coronary flow increased with hyperemia, and the magnitude of change was proportional to the myocardial perfusion reserve (rho = 0.53; p < 0.01). Conclusions: Coronary flow in patients with HCM is deranged. Distally, compressive deformation of intramyocardial blood vessels during systole results in an abnormally large backward compression wave, whereas proximally, severe left ventricular outflow tract obstruction is associated with an additional deceleration wave. Perfusion abnormalities in HCM are not simply a consequence of supply/demand mismatch or remodeling of the intramyocardial blood vessels; they represent a dynamic interaction with the mechanics of myocardial ischemia that may be amenable to treatment