99 research outputs found
Repeatability of brain phase-based magnetic resonance electric properties tomography methods and effect of compressed SENSE and RF shimming
Magnetic resonance electrical properties tomography (MREPT) is an emerging imaging modality to noninvasively measure tissue conductivity and permittivity. Implementation of MREPT in the clinic requires repeatable measurements at a short scan time and an appropriate protocol. The aim of this study was to investigate the repeatability of conductivity measurements using phase-based MREPT and the effects of compressed SENSE (CS), and RF shimming on the precision of conductivity measurements. Conductivity measurements using turbo spin echo (TSE) and three-dimensional balanced fast field echo (bFFE) with CS factors were repeatable. Conductivity measurement using bFFE phase showed smaller mean and variance that those measured by TSE. The conductivity measurements using bFFE showed minimal deviation with CS factors up to 8, with deviation increasing at CS factors > 8. Subcortical structures produced less consistent measurements than cortical parcellations at higher CS factors. RF shimming using full slice coverage 2D dual refocusing echo acquisition mode (DREAM) and full coverage 3D dual TR approaches further improved measurement precision. BFFE is a more optimal sequence than TSE for phase-based MREPT in brain. Depending on the area of the brain being measured, the scan can be safely accelerated with compressed SENSE without sacrifice of precision, offering the potential to employ MREPT in clinical research and applications. RF shimming with better field mapping further improves precision of the conductivity measures
The relationship between mandibular advancement, tongue movement, and treatment outcome in obstructive sleep apnea
Study Objectives: To characterize how mandibular advancement enlarges the upper airway via posterior tongue advancement in people with obstructive sleep apnea (OSA) and whether this is associated with mandibular advancement splint (MAS) treatment outcome. Methods: One-hundred and one untreated people with OSA underwent a 3T magnetic resonance (MRI) scan. Dynamic mid-sagittal posterior tongue and mandible movements during passive jaw advancement were measured with tagged MRI. Upper airway cross-sectional areas were measured with the mandible in a neutral position and advanced to 70% of maximum advancement. Treatment outcome was determined after a minimum of 9 weeks of therapy. Results: Seventy-one participants completed the study: 33 were responders (AHI50% AHI reduction), 11 were partial responders (>50% AHI reduction but AHI>10 events/hr), and 27 nonresponders (AHI reduction 4 mm). In comparison, a model using only baseline AHI correctly classified 50.0% of patients (5-fold cross-validated 52.5%, n = 40). Conclusions: Tongue advancement and upper airway enlargement with mandibular advancement in conjunction with baseline AHI improve treatment response categorization to a satisfactory level (69.2%, 5-fold cross-validated 62.5%)
The impact of COVID-19 and associated lockdowns on traumatic spinal cord injury incidence: a population based study
Study design
Natural experiment
Objectives
To determine whether COVID-19 restrictions were associated with changes in the incidence of traumatic spinal cord injury (TSCI) in Scotland.
Setting
The Queen Elizabeth National Spinal Injuries Unit (QENSIU), the sole provider of treatment for TSCI in Scotland.
Methods
Time series analysis of all admissions for TSCI between 1st January 2015 and 31st August 2022.
Results
Over the 8-year study period, 745 patients were admitted to the QENSIU with a TSCI. Interrupted time series analysis showed that level 3 and 4 COVID-19 lockdown restrictions (the most severe levels) were associated with lower incidence of TSCI (RR 0.63, CI% CI 0.47, 0.82, p < 0.001). The associations were stronger in people aged over 45 (additive interaction p = 0.001), males (additive interaction p = 0.01) and non-tetraplegia (additive interaction p = 0.002). The incidence of TSCI due to deliberate self-harm was higher (0.41 versus 0.23 per month) during restrictions.
Conclusions
Overall, TSCI incidence reduced in Scotland when lockdowns were implemented, presumably due to lower engagement in risky activities. The increase in TSCI due to deliberate self-harm may reflect increased mental health problems and social isolation and should be anticipated and targeted in future pandemics. The change in incidence during the COVID-19 pandemic may have an economic impact and see a temporary reduction in the burden on health and social care. The results of this study will be useful for resource planning in future pandemics
Shared and Distinct Aspects of the Sepsis Transcriptomic Response to Fecal Peritonitis and Pneumonia.
Non-commercial use onlyRATIONALE: Heterogeneity in the septic response has hindered efforts to understand pathophysiology and develop targeted therapies. Source of infection, with different causative organisms and temporal changes, might influence this heterogeneity. OBJECTIVES: To investigate individual and temporal variations in the transcriptomic response to sepsis due to fecal peritonitis, and to compare these with the same parameters in community-acquired pneumonia. METHODS: We performed genome-wide gene expression profiling in peripheral blood leukocytes of adult patients admitted to intensive care with sepsis due to fecal peritonitis (n = 117) or community-acquired pneumonia (n = 126), and of control subjects without sepsis (n = 10). MEASUREMENTS AND MAIN RESULTS: A substantial portion of the transcribed genome (18%) was differentially expressed compared with that of control subjects, independent of source of infection, with eukaryotic initiation factor 2 signaling being the most enriched canonical pathway. We identified two sepsis response signature (SRS) subgroups in fecal peritonitis associated with early mortality (P = 0.01; hazard ratio, 4.78). We defined gene sets predictive of SRS group, and serial sampling demonstrated that subgroup membership is dynamic during intensive care unit admission. We found that SRS is the major predictor of transcriptomic variation; a small number of genes (n = 263) were differentially regulated according to the source of infection, enriched for IFN signaling and antigen presentation. We define temporal changes in gene expression from disease onset involving phagosome formation as well as natural killer cell and IL-3 signaling. CONCLUSIONS: The majority of the sepsis transcriptomic response is independent of the source of infection and includes signatures reflecting immune response state and prognosis. A modest number of genes show evidence of specificity. Our findings highlight opportunities for patient stratification and precision medicine in sepsis.Supported by the National Institute for Health Research (NIHR) through the Comprehensive Clinical Research Network for patient recruitment, the Wellcome Trust (grants 074318 [J.C.K.] and 090532/Z/09/Z [core facilities Wellcome Trust Centre for Human Genetics including High-Throughput Genomics Group]), the European Research Council (ERC) under the European Union’s Seventh Framework Program (FP7/2007–2013)/ERC grant agreement 281824 (J.C.K.), the Medical Research Council (98082 [J.C.K.]), the UK Intensive Care Society, and the NIHR Oxford Biomedical Research Centre. A.V.S.H. is supported by a Wellcome Trust Senior Investigator Award (HCUZZ0), and A.C.G. is supported by an NIHR Clinician Scientist Fellowship
A Continuum of Inductive Methods Arising from a Generalized Principle of Instantial Relevance
Podbat: A Novel Genomic Tool Reveals Swr1-Independent H2A.Z Incorporation at Gene Coding Sequences through Epigenetic Meta-Analysis
Epigenetic regulation consists of a multitude of different modifications that determine active and inactive states of chromatin. Conditions such as cell differentiation or exposure to environmental stress require concerted changes in gene expression. To interpret epigenomics data, a spectrum of different interconnected datasets is needed, ranging from the genome sequence and positions of histones, together with their modifications and variants, to the transcriptional output of genomic regions. Here we present a tool, Podbat (Positioning database and analysis tool), that incorporates data from various sources and allows detailed dissection of the entire range of chromatin modifications simultaneously. Podbat can be used to analyze, visualize, store and share epigenomics data. Among other functions, Podbat allows data-driven determination of genome regions of differential protein occupancy or RNA expression using Hidden Markov Models. Comparisons between datasets are facilitated to enable the study of the comprehensive chromatin modification system simultaneously, irrespective of data-generating technique. Any organism with a sequenced genome can be accommodated. We exemplify the power of Podbat by reanalyzing all to-date published genome-wide data for the histone variant H2A.Z in fission yeast together with other histone marks and also phenotypic response data from several sources. This meta-analysis led to the unexpected finding of H2A.Z incorporation in the coding regions of genes encoding proteins involved in the regulation of meiosis and genotoxic stress responses. This incorporation was partly independent of the H2A.Z-incorporating remodeller Swr1. We verified an Swr1-independent role for H2A.Z following genotoxic stress in vivo. Podbat is open source software freely downloadable from www.podbat.org, distributed under the GNU LGPL license. User manuals, test data and instructions are available at the website, as well as a repository for third party–developed plug-in modules. Podbat requires Java version 1.6 or higher
Parameter estimation for robust HMM analysis of ChIP-chip data
Tiling arrays are an important tool for the study of transcriptional activity, protein-DNA interactions and chromatin structure on a genome-wide scale at high resolution. Although hidden Markov models have been used successfully to analyse tiling array data, parameter estimation for these models is typically ad hoc. Especially in the context of ChIP-chip experiments, no standard procedures exist to obtain parameter estimates from the data. Common methods for the calculation of maximum likelihood estimates such as the Baum-Welch algorithm or Viterbi training are rarely applied in the context of tiling array analysis. Results: Here we develop a hidden Markov model for the analysis of chromatin structure ChIP-chip tiling array data, using t emission distributions to increase robustness towards outliers. Maximum likelihood estimates are used for all model parameters. Two different approaches to parameter estimation are investigated and combined into an efficient procedure. Conclusion: We illustrate an efficient parameter estimation procedure that can be used for HMM based methods in general and leads to a clear increase in performance when compared to the use of ad hoc estimates. The resulting hidden Markov model outperforms established methods like TileMap in the context of histone modification studies.13 page(s
ChIPseqR: analysis of ChIP-seq experiments
<p>Abstract</p> <p>Background</p> <p>The use of high-throughput sequencing in combination with chromatin immunoprecipitation (ChIP-seq) has enabled the study of genome-wide protein binding at high resolution. While the amount of data generated from such experiments is steadily increasing, the methods available for their analysis remain limited. Although several algorithms for the analysis of ChIP-seq data have been published they focus almost exclusively on transcription factor studies and are usually not well suited for the analysis of other types of experiments.</p> <p>Results</p> <p>Here we present ChIPseqR, an algorithm for the analysis of nucleosome positioning and histone modification ChIP-seq experiments. The performance of this novel method is studied on short read sequencing data of <it>Arabidopsis thaliana </it>mononucleosomes as well as on simulated data.</p> <p>Conclusions</p> <p>ChIPseqR is shown to improve sensitivity and spatial resolution over existing methods while maintaining high specificity. Further analysis of predicted nucleosomes reveals characteristic patterns in nucleosome sequences and placement.</p
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The limits of higher education institutions as sites of work skill development, the cases of software engineers, laboratory scientists, financial analysts and press officers
Where do workers with Higher Education (HE) degrees develop their work skills? Although few would expect these to be developed in HE exclusively, there exists an assumption that the core skills of those working in graduate occupations are predominantly formed at HE. This article examines how within four graduate occupations, employers and workers assess the extent HE is thought to develop the skills and knowledge used within the work process. It draws on occupational case studies on the work of laboratory-based scientists, software engineers, financial analysts and press officers, using interview data with workers, employers and stakeholders. The study shows that structural barriers prevent HE to take a significant part in work-skill and knowledge development, but also that HE is not necessarily heavily relied upon for skill formation. More precaution is required for those who would like to directly link the skills demands for graduate work with the skills that are developed or associated at university
An integrated ChIP-seq analysis platform with customizable workflows
<p>Abstract</p> <p>Background</p> <p>Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks.</p> <p>Results</p> <p>To address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset.</p> <p>Conclusions</p> <p>ChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.</p
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