Evaluation of Vibration Analysis to Assess Bone Mineral Density in Children

The effectiveness of vibration analysis to assess bone mineral density (BMD) in children with suspected reduction in bone density was studied. A system was designed that measured the ulna's vibration responses in vivo. The system was evaluated on the ulnae of 48 children (mean age=12.0, std=3.5 years), 31 of whom had been confirmed to have osteogenesis imperfecta (OI). All children had dual energy X-ray absorptiometry (DXA) scan as part of their routine clinical care and vibration analysis was performed on the same day. Frequency spectra of the ulnae's vibration responses were obtained and processed by principal component analysis. Four main principal components were selected and together with age, sex and right hand ulna's length were used in a regression analysis to estimate BMD. Regression analysis was repeated using the children's leave-one-out and partitioning methods. The percentage similarity and correlation between the DXA-derived and vibration analysis estimated BMDs using the leave-one-out were 80.34% and 0.59 and for partitioning were 74.2% and 0.64 respectively. There was correlation between vibration analysis BMD readings and those derived from DXA however a larger study will be needed to better establish the extent to which vibration analysis can assist in assessing bone density in clinical environments

Transcriptomic profiling of skeletal muscle adaptations to exercise and inactivity

The authors are supported by grants from the Novo Nordisk Foundation (NNF14OC0011493, NNF17OC0030088 and NNF14OC0009941), Swedish Diabetes Foundation (DIA2018-357, DIA2018-336), Swedish Research Council (2015-00165, 2018-02389), the Strategic Research Program in Diabetes at Karolinska Institutet (2009-1068), the Stockholm County Council (SLL20150517, SLL20170159), the Swedish Research Council for Sport Science (P2018-0097), and the EFSD European Research Programme on New Targets for Type 2 Diabetes supported by an educational research grant from MSD. L.D. was supported by a Novo Nordisk postdoctoral fellowship run in partnership with Karolinska Institutet. B.M.G. was supported by a fellowship from the Wenner-Gren Foundation (Sweden). N.J.P. was supported by an Individual Fellowship from the Marie Skłodowska-Curie Actions (European Commission, 704978, 675610) and grants from the Sigurd och Elsa Goljes Minne and Lars Hiertas Minne Foundations (Sweden). D.J.B. was supported by the ANZ Mason Foundation and Australian Research Council Discovery Program (ARC DP140104165). Additional support was received from the Novo Nordisk Foundation Center for Basic Metabolic Research at the University of Copenhagen (NNF18CC0034900) (to J.R.Z.). We thank Dr. Nanjiang Shu from National Bioinformatics Infrastructure Sweden (NBIS) for setting up the web-server. We also thank EGI federated cloud for providing the computer resource for hosting the web-server. We acknowledge the Beta Cell in-vivo Imaging/Extracellular Flux Analysis core facility supported by the Strategic Research Program (SRP) in Diabetes for the usage of the Seahorse flux analyzer. Open access funding provided by Karolinska Institute.Peer reviewedPublisher PD

Genome sequence of human papillomavirus type 20, strain HPV-20/Lancaster/2015

The genome sequence of human papillomavirus type 20 (HPV-20; family Papillomaviridae, genus Betapapillomavirus, species Betapapillomavirus 1, type 20) was assembled by deep sequencing from nasopharyngeal swabs. The assembled genome is 0.37% divergent over its full length from the single complete genome of HPV-20 in GenBank (U31778). We named the strain HPV-20/Lancaster/2015

The Human Phenotype Ontology in 2024: phenotypes around the world

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Losartan alters osteoblast differentiation and increases bone mass through inhibition of TGFB signalling in vitro and in an OIM mouse model

Excessive production of Transforming Growth Factor β (TGFβ) is commonly associated with dominant and recessive forms of OI. Previous reports have indicated that administration of TGFβ-targeted antibodies maybe of potential therapeutic benefit to OI patients. However, direct targeting of TGFβ is likely to cause multiple adverse effects including simulation of autoimmunity. In the current study we use patient-derived normal and OI fibroblasts, osteoblasts and OIM mouse models to determine the effects of Losartan, an angiotensin II receptor type 1 (AT1) antagonist, on TGFβ signalling and bone morphology in OI. In OIM mice bred on a mixed background administration of 0.6 g/L losartan for 4 weeks was associated with a significant reduction in TGFβ from 79.2 g/L in the control to 60.0 ng/ml following losartan (p < 0.05), reduced osteoclast activity as measured by CTX from 275.9 ng/ml in the control to 157.2 ng/ml following 0.6 g/L of losartan (p < 0.05) and increased cortical bone thickness (P < 0.001). Furthermore in OIM mice bred on a C57BL/6 background 0.6 g/L losartan increased trabecular bone volume in the tibiae (P < 0.05) and the vertebrae (P < 0.01), increased cortical bone thickness (P < 0.001) reduced the trabecular pattern factor (P < 0.01 and P < 0.001 for the tibiae and vertebrae respectively), reduced osteoclast (P < 0.05) and osteoblast (P < 0.01) numbers as well as reducing the area of bone covered by these cell types. Interestingly, losartan did not affect immune cells infiltrating into bone, nor did this drug alter TGFβ signalling in normal or OI fibroblasts. Instead, losartan reduced SMAD2 phosphorylation in osteoblasts, inhibiting their ability to differentiate. Our data suggest that losartan may be an effective treatment for the bone-associated dysmorphia displayed in OI whilst minimising potential adverse immune cell-related effects

The ASAS-SN Bright Supernova Catalog I: 2013-2014

We present basic statistics for all supernovae discovered by the All-Sky Automated Survey for SuperNovae (ASAS-SN) during its first year-and-a-half of operations, spanning 2013 and 2014. We also present the same information for all other bright ($m_V\leq17$), spectroscopically confirmed supernovae discovered from 2014 May 1 through the end of 2014, providing a comparison to the ASAS-SN sample starting from the point where ASAS-SN became operational in both hemispheres. In addition, we present collected redshifts and near-UV through IR magnitudes, where available, for all host galaxies of the bright supernovae in both samples. This work represents a comprehensive catalog of bright supernovae and their hosts from multiple professional and amateur sources, allowing for population studies that were not previously possible because the all-sky emphasis of ASAS-SN redresses most previously existing biases. In particular, ASAS-SN systematically finds supernovae closer to the centers of host galaxies than either other professional surveys or amateurs, a remarkable result given ASAS-SN's poorer angular resolution. This is the first of a series of yearly papers on bright supernovae and their hosts that will be released by the ASAS-SN team

ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis

<p>Abstract</p> <p>Background</p> <p>Chromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of <it>Drosophila melanogaster</it>.</p> <p>Results</p> <p>Both technologies produce highly reproducible profiles within each platform, ChIP-seq generally produces profiles with a better signal-to-noise ratio, and allows detection of more peaks and narrower peaks. The set of peaks identified by the two technologies can be significantly different, but the extent to which they differ varies depending on the factor and the analysis algorithm. Importantly, we found that there is a significant variation among multiple sequencing profiles of input DNA libraries and that this variation most likely arises from both differences in experimental condition and sequencing depth. We further show that using an inappropriate input DNA profile can impact the average signal profiles around genomic features and peak calling results, highlighting the importance of having high quality input DNA data for normalization in ChIP-seq analysis.</p> <p>Conclusions</p> <p>Our findings highlight the biases present in each of the platforms, show the variability that can arise from both technology and analysis methods, and emphasize the importance of obtaining high quality and deeply sequenced input DNA libraries for ChIP-seq analysis.</p

The ASAS-SN bright supernova catalogue - III. 2016

This catalogue summarizes information for all supernovae discovered by the All-Sky Automated Survey for SuperNovae (ASAS-SN) and all other bright (mpeak ≤ 17), spectroscopically confirmed supernovae discovered in 2016. We then gather the near-infrared through ultraviolet magnitudes of all host galaxies and the offsets of the supernovae from the centres of their hosts from public data bases. We illustrate the results using a sample that now totals 668 supernovae discovered since 2014 May 1, including the supernovae from our previous catalogues, with type distributions closely matching those of the ideal magnitude limited sample from Li et al. This is the third of a series of yearly papers on bright supernovae and their hosts from the ASAS-SN team

The ASAS-SN Bright Supernova Catalog - II. 2015

This manuscript presents information for all supernovae discovered by the All-Sky Automated Survey for SuperNovae (ASAS-SN) during 2015, its second full year of operations. The same information is presented for bright ($m_V\leq17$), spectroscopically confirmed supernovae discovered by other sources in 2015. As with the first ASAS-SN bright supernova catalog, we also present redshifts and near-UV through IR magnitudes for all supernova host galaxies in both samples. Combined with our previous catalog, this work comprises a complete catalog of 455 supernovae from multiple professional and amateur sources, allowing for population studies that were previously impossible. This is the second of a series of yearly papers on bright supernovae and their hosts from the ASAS-SN team

Influenza C in Lancaster, UK, in the winter of 2014-2015.

Influenza C is not included in the annual seasonal influenza vaccine, and has historically been regarded as a minor respiratory pathogen. However, recent work has highlighted its potential role as a cause of pneumonia in infants. We performed nasopharyngeal or nasal swabbing and/or serum sampling (n=148) in Lancaster, UK, over the winter of 2014-2015. Using enzyme-linked immunosorbent assay (ELISA), we obtain seropositivity of 77%. By contrast, only 2 individuals, both asymptomatic adults, were influenza C-positive by polymerase chain reaction (PCR). Deep sequencing of nasopharyngeal samples produced partial sequences for 4 genome segments in one of these patients. Bayesian phylogenetic analysis demonstrated that the influenza C genome from this individual is evolutionarily distant to those sampled in recent years and represents a novel genome constellation, indicating that it may be a product of a decades-old reassortment event. Although we find no evidence that influenza C was a significant respiratory pathogen during the winter of 2014-2015 in Lancaster, we confirm previous observations of seropositivity in the majority of the population