126 research outputs found
An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding
Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant 0645960)National Institutes of Health (U.S.) (grant P01 NS055923)Pennsylvania State University. Center for Eukaryotic Gene Regulatio
Top Ten epilepsy research priorities: A UK priority setting partnership
\ua9 2024 The Author(s)Purpose: Research into epilepsy has experienced decades of chronic underfunding compared to other neurological conditions despite its prevalence and seriousness. To evidence the need for greater investment, the Epilepsy Research Institute (formerly Epilepsy Research UK) funded, led and managed a James Lind Alliance (JLA) Priority Setting Partnership (PSP). This “industry standard” methodology brings together healthcare professionals, patients, carers and patient group representatives to identify and prioritise research uncertainties within a defined area of health or care. Methods: The UK Epilepsy PSP is a once-in-a-generation, national consensus that collated and ranked the research priorities of the UK epilepsy and associated condition community. Following JLA methodology, this 18-month project engaged over 100 patient groups and 5000 people affected by and working in epilepsy, including medics and allied healthcare professionals, from across the UK. Results: Over 5400 priorities were received, with anti-seizure medication, sudden unexpected death in epilepsy (SUDEP) and epilepsy in women among the most frequently reported themes. The responses received were categorised and translated into distinct, researchable questions. Questions were excluded if deemed to be “answered” following an evidence check, while research uncertainties (i.e. unanswered and partially answered questions) formed the basis of a second, shortlisting survey. The shortlisted questions were then discussed and debated at the final workshop by participants that broadly represented the UK epilepsy and associated condition community. The final ranking and Top Ten priorities for research into epilepsy were then agreed. Conclusion: The aim of the UK Epilepsy PSP is to encourage and inspire researchers to investigate the research areas prioritised by those most affected by the condition and provide the evidence of need to aid future policy making discussions and support research funding applications
Simultaneous quantification of artesunate and mefloquine in fixed-dose combination tablets by multivariate calibration with middle infrared spectroscopy and partial least squares regression
Imbalanced expression of functional surface molecules in regulatory and effector T cells in systemic lupus erythematosus
Enhancing access to reports of randomized trials published world-wide – the contribution of EMBASE records to the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library
<p>Abstract</p> <p>Background</p> <p>Randomized trials are essential in assessing the effects of healthcare interventions and are a key component in systematic reviews of effectiveness. Searching for reports of randomized trials in databases is problematic due to the absence of appropriate indexing terms until the 1990s and inconsistent application of these indexing terms thereafter.</p> <p>Objectives</p> <p>The objectives of this study are to devise a search strategy for identifying reports of randomized trials in EMBASE which are not already indexed as trials in MEDLINE and to make these reports easily accessible by including them in the Cochrane Central Register of Controlled Trials (CENTRAL) in <it>The Cochrane Library</it>, with the permission of Elsevier, the publishers of EMBASE.</p> <p>Methods</p> <p>A highly sensitive search strategy was designed for EMBASE based on free-text and thesaurus terms which occurred frequently in the titles, abstracts, EMTREE terms (or some combination of these) of reports of trials indexed in EMBASE. This search strategy was run against EMBASE from 1980 to 2005 (1974 to 2005 for four of the terms) and records retrieved by the search, which were not already indexed as randomized trials in MEDLINE, were downloaded from EMBASE, printed and read. An analysis of the language of publication was conducted for the reports of trials published in 2005 (the most recent year completed at the time of this study).</p> <p>Results</p> <p>Twenty-two search terms were used (including nine which were later rejected due to poor cumulative precision). More than a third of a million records were downloaded and scanned and approximately 80,000 reports of trials were identified which were not already indexed as randomized trials in MEDLINE. These are now easily identifiable in CENTRAL, in <it>The Cochrane Library</it>. Cumulative sensitivity ranged from 0.1% to 60% and cumulative precision ranged from 8% to 61%. The truncated term 'random$' identified 60% of the total number of reports of trials but only 35% of the more than 130,000 records retrieved by this term were reports of trials. The language analysis for the sample year 2005 indicated that of the 18,427 reports indexed as randomized trials in MEDLINE, 959 (5%) were in languages other than English. The EMBASE search identified an additional 658 reports in languages other than English, of which the highest number were in Chinese (320).</p> <p>Conclusion</p> <p>The results of the search to date have greatly increased access to reports of trials in EMBASE, especially in some languages other than English. The search strategy used was subjectively derived from a small 'gold standard' set of test records and was not validated in an independent test set. We intend to design an objectively-derived validated search strategy using logistic regression based on the frequency of occurrence of terms in the approximately 80,000 reports of randomized trials identified compared with the frequency of these terms across the entire EMBASE database.</p
Top Ten epilepsy research priorities: A UK priority setting partnership.
PURPOSE: Research into epilepsy has experienced decades of chronic underfunding compared to other neurological conditions despite its prevalence and seriousness. To evidence the need for greater investment, the Epilepsy Research Institute (formerly Epilepsy Research UK) funded, led and managed a James Lind Alliance (JLA) Priority Setting Partnership (PSP). This "industry standard" methodology brings together healthcare professionals, patients, carers and patient group representatives to identify and prioritise research uncertainties within a defined area of health or care. METHODS: The UK Epilepsy PSP is a once-in-a-generation, national consensus that collated and ranked the research priorities of the UK epilepsy and associated condition community. Following JLA methodology, this 18-month project engaged over 100 patient groups and 5000 people affected by and working in epilepsy, including medics and allied healthcare professionals, from across the UK. RESULTS: Over 5400 priorities were received, with anti-seizure medication, sudden unexpected death in epilepsy (SUDEP) and epilepsy in women among the most frequently reported themes. The responses received were categorised and translated into distinct, researchable questions. Questions were excluded if deemed to be "answered" following an evidence check, while research uncertainties (i.e. unanswered and partially answered questions) formed the basis of a second, shortlisting survey. The shortlisted questions were then discussed and debated at the final workshop by participants that broadly represented the UK epilepsy and associated condition community. The final ranking and Top Ten priorities for research into epilepsy were then agreed. CONCLUSION: The aim of the UK Epilepsy PSP is to encourage and inspire researchers to investigate the research areas prioritised by those most affected by the condition and provide the evidence of need to aid future policy making discussions and support research funding applications
Elective surgery system strengthening: development, measurement, and validation of the surgical preparedness index across 1632 hospitals in 119 countries
Background: The 2015 Lancet Commission on global surgery identified surgery and anaesthesia as indispensable parts of holistic health-care systems. However, COVID-19 exposed the fragility of planned surgical services around the world, which have also been neglected in pandemic recovery planning. This study aimed to develop and validate a novel index to support local elective surgical system strengthening and address growing backlogs. Methods: First, we performed an international consultation through a four-stage consensus process to develop a multidomain index for hospital-level assessment (surgical preparedness index; SPI). Second, we measured surgical preparedness across a global network of hospitals in high-income countries (HICs), middle-income countries (MICs), and low-income countries (LICs) to explore the distribution of the SPI at national, subnational, and hospital levels. Finally, using COVID-19 as an example of an external system shock, we compared hospitals' SPI to their planned surgical volume ratio (SVR; ie, operations for which the decision for surgery was made before hospital admission), calculated as the ratio of the observed surgical volume over a 1-month assessment period between June 6 and Aug 5, 2021, against the expected surgical volume based on hospital administrative data from the same period in 2019 (ie, a pre-pandemic baseline). A linear mixed-effects regression model was used to determine the effect of increasing SPI score. Findings: In the first phase, from a longlist of 103 candidate indicators, 23 were prioritised as core indicators of elective surgical system preparedness by 69 clinicians (23 [33%] women; 46 [67%] men; 41 from HICs, 22 from MICs, and six from LICs) from 32 countries. The multidomain SPI included 11 indicators on facilities and consumables, two on staffing, two on prioritisation, and eight on systems. Hospitals were scored from 23 (least prepared) to 115 points (most prepared). In the second phase, surgical preparedness was measured in 1632 hospitals by 4714 clinicians from 119 countries. 745 (45·6%) of 1632 hospitals were in MICs or LICs. The mean SPI score was 84·5 (95% CI 84·1–84·9), which varied between HIC (88·5 [89·0–88·0]), MIC (81·8 [82·5–81·1]), and LIC (66·8 [64·9–68·7]) settings. In the third phase, 1217 (74·6%) hospitals did not maintain their expected SVR during the COVID-19 pandemic, of which 625 (51·4%) were from HIC, 538 (44·2%) from MIC, and 54 (4·4%) from LIC settings. In the mixed-effects model, a 10-point increase in SPI corresponded to a 3·6% (95% CI 3·0–4·1; p<0·0001) increase in SVR. This was consistent in HIC (4·8% [4·1–5·5]; p<0·0001), MIC (2·8 [2·0–3·7]; p<0·0001), and LIC (3·8 [1·3–6·7%]; p<0·0001) settings. Interpretation: The SPI contains 23 indicators that are globally applicable, relevant across different system stressors, vary at a subnational level, and are collectable by front-line teams. In the case study of COVID-19, a higher SPI was associated with an increased planned surgical volume ratio independent of country income status, COVID-19 burden, and hospital type. Hospitals should perform annual self-assessment of their surgical preparedness to identify areas that can be improved, create resilience in local surgical systems, and upscale capacity to address elective surgery backlogs. Funding: National Institute for Health Research (NIHR) Global Health Research Unit on Global Surgery, NIHR Academy, Association of Coloproctology of Great Britain and Ireland, Bowel Research UK, British Association of Surgical Oncology, British Gynaecological Cancer Society, and Medtronic
Identification of Novel Targets of CSL-Dependent Notch Signaling in Hematopoiesis
Somatic activating mutations in the Notch1 receptor result in the overexpression of activated Notch1, which can be tumorigenic. The goal of this study is to understand the molecular mechanisms underlying the phenotypic changes caused by the overexpression of ligand independent Notch 1 by using a tetracycline inducible promoter in an in vitro embryonic stem (ES) cells/OP9 stromal cells coculture system, recapitulating normal hematopoiesis. First, an in silico analysis of the promoters of Notch regulated genes (previously determined by microarray analysis) revealed that the motifs recognized by regulatory proteins known to mediate hematopoiesis were overrepresented. Notch 1 does not bind DNA but instead binds the CSL transcription factor to regulate gene expression. The in silico analysis also showed that there were putative CSL binding sites observed in the promoters of 28 out of 148 genes. A custom ChIP-chip array was used to assess the occupancy of CSL in the promoter regions of the Notch1 regulated genes in vivo and showed that 61 genes were bound by activated Notch responsive CSL. Then, comprehensive mapping of the CSL binding sites genome-wide using ChIP-seq analysis revealed that over 10,000 genes were bound within 10 kb of the TSS (transcription start site). The majority of the targets discovered by ChIP-seq belong to pathways that have been shown by others to crosstalk with Notch signaling. Finally, 83 miRNAs were significantly differentially expressed by greater than 1.5-fold during the course of in vitro hematopoiesis. Thirty one miRNA were up-regulated and fifty two were down-regulated. Overexpression of Notch1 altered this pattern of expression of microRNA: six miRNAs were up-regulated and four were down regulated as a result of activated Notch1 overexpression during the course of hematopoiesis. Time course analysis of hematopoietic development revealed that cells with Notch 1 overexpression mimic miRNA expression of cells in a less mature stage, which is consistent with our previous biological characterization
A statistical framework for cross-tissue transcriptome-wide association analysis
Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene–trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies
Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study
We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05-1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4-7 days or ≥ 8 days of 1.25 (1.04-1.48), p = 0.015 and 1.31 (1.11-1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care
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