A microphysiological model of bone development and regeneration

Endochondral ossification (EO) is an essential biological process than underpins how human bones develop, grow, and heal in the event of a fracture. So much is unknown about this process, thus clinical manifestations of dysregulated EO cannot be adequately treated. This can be partially attributed to the absence of predictive in vitro models of musculoskeletal tissue development and healing, which are integral to the development and preclinical evaluation of novel therapeutics. Microphysiological systems, or organ-on-chip devices, are advanced in vitro models designed for improved biological relevance compared to traditional in vitro culture models. Here we develop a microphysiological model of vascular invasion into developing/regenerating bone, thereby mimicking the process of EO. This is achieved by integrating endothelial cells and organoids mimicking different stages of endochondral bone development within a microfluidic chip. This microphysiological model is able to recreate key events in EO, such as the changing angiogenic profile of a maturing cartilage analogue, and vascular induced expression of the pluripotent transcription factors SOX2 and OCT4 in the cartilage analogue. This system represents an advanced in vitro platform to further EO research, and may also serve as a modular unit to monitor drug responses on such processes as part of a multi-organ system

Eosinophilic esophagitis-associated epithelial remodeling may limit esophageal carcinogenesis

IntroductionUnder homeostatic conditions, esophageal epithelium displays a proliferation/differentiation gradient that is generated as proliferative basal cells give rise to suprabasal cells then terminally differentiated superficial cells. This proliferation/differentiation gradient is often perturbed in esophageal pathologies. Basal cell hyperplasia may occur in patients with gastroesophageal reflux disease (GERD), a condition in which acid from the stomach enters the esophagus, or eosinophilic esophagitis (EoE), an emerging form of food allergy. While GERD is a primary risk factor for esophageal cancer, epidemiological data suggests that EoE patients do not develop esophageal cancer.MethodsIn order to investigate the impact of EoE and esophageal cancer specifically on the cellular landscape of esophageal epithelium, we perform single cell RNA-sequencing in murine models of EoE and esophageal cancer, specifically esophageal squamous cell carcinoma (ESCC). We further evaluate modules of co-expressed genes in EoE- and ESCC-enriched epithelial cell clusters. Finally, we pair EoE and ESCC murine models to examine the functional relationship between these pathologies.ResultsIn mice with either EoE or ESCC, we find expansion of cell populations as compared to normal esophageal epithelium. In mice with EoE, we detect distinct expansion of 4 suprabasal populations coupled with depletion of 2 basal populations. By contrast, mice with ESCC display unique expansion of 2 basal populations and 1 suprabasal population, as well as depletion of 2 suprabasal populations. Senescence, glucocorticoid receptor signaling, and granulocyte-macrophage colony-stimulating factor pathways are associated with EoE-enriched clusters while pathways associated with cell proliferation and metabolism are identified in ESCC-enriched clusters. Finally, our in vivo data demonstrate that exposure to EoE inflammation limits tumor burden of esophageal carcinogenesis.DiscussionOur findings provide the first functional investigation of the relationship between EoE and esophageal cancer and suggest that esophageal epithelial remodeling events occurring in response to EoE inflammation may limit esophageal carcinogenesis. This investigation may have future implications for leveraging allergic inflammation-associated alterations in epithelial biology to prevent and/or treat esophageal cancer

Heritability and reliability of automatically segmented human hippocampal formation subregions

The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test-retest reliability and transplatform reliability (1.5 T versus 3 T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N=39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N=163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N=598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h(2)) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test-retest reliability was high for all twelve subregions in the 3 T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70-0.97) and moderate-to-high in the 4 TQTIM sample (ICC=0.5-0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC=0.66-0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5 T and 3 T field strengths (ICC=0.47-0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC=0.78-0.84; Dice Similarity Coefficient (DSC)=0.55-0.70), and poor for all other subregions (ICC=0.34-0.81; DSC=0.28-0.51). All hippocampal subregion volumes were highly heritable (h(2)=0.67-0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium. (C) 2016 The Authors. Published by Elsevier Inc

Status of NINJA: the Numerical INJection Analysis project

The 2008 NRDA conference introduced the Numerical INJection Analysis project (NINJA), a new collaborative effort between the numerical relativity community and the data analysis community. NINJA focuses on modeling and searching for gravitational wave signatures from the coalescence of binary system of compact objects. We review the scope of this collaboration and the components of the first NINJA project, where numerical relativity groups shared waveforms and data analysis teams applied various techniques to detect them when embedded in colored Gaussian noise

Diarrhoea in the critically ill is common, associated with poor outcome, and rarely due to Clostridium difficile

Diarrhoea is common in Intensive Care Unit (ICU) patients, with a reported prevalence of 15-38%. Many factors may cause diarrhoea, including Clostridium difficile, drugs (e.g. laxatives, antibiotics) and enteral feeds. Diarrhoea impacts on patient dignity, increases nursing workload and healthcare costs, and exacerbates morbidity through dermal injury, impaired enteral uptake and subsequent fluid imbalance. We analysed a cohort of 9331 consecutive patients admitted to a mixed general intensive care unit to establish the prevalence of diarrhoea in intensive care unit patients, and its relationship with infective aetiology and clinical outcomes. We provide evidence that diarrhoea is common (12.9% (1207/9331) prevalence) in critically ill patients, independently associated with increased intensive care unit length of stay (mean (standard error) 14.8 (0.26) vs 3.2 (0.09) days, p < 0.001) and mortality (22.0% (265/1207) vs 8.7% (705/8124), p < 0.001; adjusted hazard ratio 1.99 (95% CI 1.70-2.32), p < 0.001) compared to patients without diarrhoea even after adjusting for potential confounding factors, and infrequently caused by infective aetiology (112/1207 (9.2%)) such as Clostridium difficile (97/1048 (9.3%) tested) or virological causes (9/172 (5.7%) tested). Our findings suggest non-infective causes of diarrhoea in ICU predominate and pathophysiology of diarrhoea in critically ill patients warrants further investigation

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Type Ia Supernova host galaxies as seen with IFU spectroscopy

(abridged) We used the wide-field IFU spectrograph PMAS/PPAK at the 3.5m telescope of Calar Alto Observatory to observe six nearby spiral galaxies that hosted SNe Ia. Spatially resolved 2D maps of the properties of the ionized gas and the stellar populations were derived. Five of the observed galaxies have an ongoing star formation rate of 1-5 M_sun/yr and mean stellar population ages ~5 Gyr. The sixth galaxy shows no star formation and has an about 12 Gyr old stellar population. All galaxies have stellar masses larger than 2E+10 M_sun and metallicities above solar. Four galaxies show negative radial metallicity gradients of the ionized gas up to -0.058 dex/kpc and one has nearly uniform metallicity with a possible shallow positive slope. The stellar components show shallower negative metallicity gradients up to -0.03 dex/kpc. We find no clear correlation between the properties of the galaxy and those of the supernovae, which may be because of the small ranges spanned by the galaxy parameters. However, we note that the Hubble residuals are on average positive while negative Hubble residuals are expected for SNe Ia in massive hosts such as the galaxies in our sample. In conclusion, IFU spectroscopy on 4-m telescopes is a viable technique for studying host galaxies of nearby SNe Ia. It allows one to correlate the supernova properties with the properties of their host galaxies at the projected positions of the supernovae. Our current sample of six galaxies is too small to draw conclusions about the SN Ia progenitors or correlations with the galaxy properties, but the ongoing CALIFA IFU survey will provide a solid basis to exploit this technique more and improve our understanding of SNe Ia as cosmological standard candles.Comment: accepted by A&A, final language-edited version, layout change

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A