Parasitic helminths induce fetal-like reversion in the intestinal stem cell niche.

Epithelial surfaces form critical barriers to the outside world and are continuously renewed by adult stem cells1. Whereas dynamics of epithelial stem cells during homeostasis are increasingly well understood, how stem cells are redirected from a tissue-maintenance program to initiate repair after injury remains unclear. Here we examined infection by Heligmosomoides polygyrus, a co-evolved pathosymbiont of mice, to assess the epithelial response to disruption of the mucosal barrier. H. polygyrus disrupts tissue integrity by penetrating the duodenal mucosa, where it develops while surrounded by a multicellular granulomatous infiltrate2. Crypts overlying larvae-associated granulomas did not express intestinal stem cell markers, including Lgr53, in spite of continued epithelial proliferation. Granuloma-associated Lgr5- crypt epithelium activated an interferon-gamma (IFN-γ)-dependent transcriptional program, highlighted by Sca-1 expression, and IFN-γ-producing immune cells were found in granulomas. A similar epithelial response accompanied systemic activation of immune cells, intestinal irradiation, or ablation of Lgr5+ intestinal stem cells. When cultured in vitro, granuloma-associated crypt cells formed spheroids similar to those formed by fetal epithelium, and a sub-population of H. polygyrus-induced cells activated a fetal-like transcriptional program, demonstrating that adult intestinal tissues can repurpose aspects of fetal development. Therefore, re-initiation of the developmental program represents a fundamental mechanism by which the intestinal crypt can remodel itself to sustain function after injury

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/

Physical activity screening to recruit inactive randomized controlled trial participants: how much is too much?

Citation: Vandelanotte, C., Stanton, R., Rebar, A. L., Van Itallie, A. K., Caperchione, C. M., Duncan, M. J., . . . Kolt, G. S. (2015). Physical activity screening to recruit inactive randomized controlled trial participants: how much is too much? Trials, 16, 3. doi:10.1186/s13063-015-0976-7Screening physical activity levels is common in trials to increase physical activity in inactive populations. Commonly applied single-item screening tools might not always be effective in identifying those who are inactive. We applied the more extensive Active Australia Survey to identify inactive people among those who had initially been misclassified as too active using a single-item measure. Those enrolled after the Active Australia Survey screening had significantly higher physical activity levels at subsequent baseline assessment. Thus, more extensive screening measures might result in the inclusion of participants who would otherwise be excluded, possibly introducing unwanted bias

Breathomics—exhaled volatile organic compound analysis to detect hepatic encephalopathy : a pilot study

he current diagnostic challenge with diagnosing hepatic encephalopathy (HE) is identifying those with minimal HE as opposed to the more clinically apparent covert/overt HE. Rifaximin, is an effective therapy but earlier identification and treatment of HE could prevent liver disease progression and hospitalization. Our pilot study aimed to analyse breath samples of patients with different HE grades, and controls, using a portable electronic (e) nose. 42 patients were enrolled; 22 with HE and 20 controls. Bedside breath samples were captured and analysed using an uvFAIMS machine (portable e-nose). West Haven criteria applied and MELD scores calculated. We classify HE patients from controls with a sensitivity and specificity of 0.88 (0.73-0.95) and 0.68 (0.51-0.81) respectively, AUROC 0.84 (0.75-0.93). Minimal HE was distinguishable from covert/overt HE with sensitivity of 0.79 and specificity of 0.5, AUROC 0.71 (0.57-0.84). This pilot study has highlighted the potential of breathomics to identify VOCs signatures in HE patients for diagnostic purposes. Importantly this was performed utilizing a non-invasive, portable bedside device and holds potential for future early HE diagnosis

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

The Molonglo Reference Catalog 1-Jy radio source survey IV. Optical spectroscopy of a complete quasar sample

Optical spectroscopic data are presented here for quasars from the Molonglo Quasar Sample (MQS), which forms part of a complete survey of 1-Jy radio sources from the Molonglo Reference Catalogue. The combination of low-frequency selection and complete identifications means that the MQS is relatively free from the orientation biases which affect most other quasar samples. To date, the sample includes 105 quasars and 6 BL Lac objects, 106 of which have now been confirmed spectroscopically. This paper presents a homogenous set of low-resolution optical spectra for 79 MQS quasars, the majority of which have been obtained at the Anglo-Australian Telescope. Full observational details are given and redshifts, continuum and emission-line data tabulated for all confirmed quasars.Comment: 40 pages, ApJS in pres

Multiplex PCR and Next Generation Sequencing for the Non-Invasive Detection of Bladder Cancer

Highly sensitive and specific urine-based tests to detect either primary or recurrent bladder cancer have proved elusive to date. Our ever increasing knowledge of the genomic aberrations in bladder cancer should enable the development of such tests based on urinary DNA

Cosmological parameter estimation using Very Small Array data out to l=1500

We estimate cosmological parameters using data obtained by the Very Small Array (VSA) in its extended configuration, in conjunction with a variety of other CMB data and external priors. Within the flat $\Lambda$CDM model, we find that the inclusion of high resolution data from the VSA modifies the limits on the cosmological parameters as compared to those suggested by WMAP alone, while still remaining compatible with their estimates. We find that $\Omega_{\rm b}h^2=0.0234^{+0.0012}_{-0.0014}$, $\Omega_{\rm dm}h^2=0.111^{+0.014}_{-0.016}$, $h=0.73^{+0.09}_{-0.05}$, $n_{\rm S}=0.97^{+0.06}_{-0.03}$, $10^{10}A_{\rm S}=23^{+7}_{-3}$ and $\tau=0.14^{+0.14}_{-0.07}$ for WMAP and VSA when no external prior is included.On extending the model to include a running spectral index of density fluctuations, we find that the inclusion of VSA data leads to a negative running at a level of more than 95% confidence ($n_{\rm run}=-0.069\pm 0.032$), something which is not significantly changed by the inclusion of a stringent prior on the Hubble constant. Inclusion of prior information from the 2dF galaxy redshift survey reduces the significance of the result by constraining the value of $\Omega_{\rm m}$. We discuss the veracity of this result in the context of various systematic effects and also a broken spectral index model. We also constrain the fraction of neutrinos and find that $f_{\nu}< 0.087$ at 95% confidence which corresponds to $m_\nu<0.32{\rm eV}$ when all neutrino masses are the equal. Finally, we consider the global best fit within a general cosmological model with 12 parameters and find consistency with other analyses available in the literature. The evidence for $n_{\rm run}<0$ is only marginal within this model

The systematic development of a novel integrated spiral undergraduate course in general practice

In 2007 Keele University School of Medicine rolled out its novel curriculum to which general practice makes a major contribution. In this paper we describe the systematic approach we took to developing the GP curriculum; from the underlying educational principles which guided its development, the subsequent decisions we made to the curriculum itself. This consists of 23 weeks of clinical placements in general practice; four weeks in year 3, four weeks in year 4 and 15 weeks in year 5. We describe the steps which were necessary to prepare for the implementation of the GP curriculum. We consider that the successful implementation of our general practice contribution is a result of our systematic identification of these principles, the clearly articulated design decisions and the systematic preparation for implementation involving the academic GP team and all our potential teaching practices

Is the High-resolution Coronal Imager Resolving Coronal Strands? Results from AR 12712

Following the success of the first mission, the High-Resolution Coronal Imager (Hi-C) was launched for a third time (Hi-C 2.1) on 2018 May 29 from the White Sands Missile Range, NM, USA. On this occasion, 329 s of 17.2 nm data of target active region AR 12712 were captured with a cadence of ≈4 s, and a plate scale of 0farcs129 pixel−1. Using data captured by Hi-C 2.1 and co-aligned observations from SDO/AIA 17.1 nm, we investigate the widths of 49 coronal strands. We search for evidence of substructure within the strands that is not detected by AIA, and further consider whether these strands are fully resolved by Hi-C 2.1. With the aid of multi-scale Gaussian normalization, strands from a region of low emission that can only be visualized against the contrast of the darker, underlying moss are studied. A comparison is made between these low-emission strands and those from regions of higher emission within the target active region. It is found that Hi-C 2.1 can resolve individual strands as small as ≈202 km, though the more typical strand widths seen are ≈513 km. For coronal strands within the region of low emission, the most likely width is significantly narrower than the high-emission strands at ≈388 km. This places the low-emission coronal strands beneath the resolving capabilities of SDO/AIA, highlighting the need for a permanent solar observatory with the resolving power of Hi-C