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Träfflista för sökning "WFRF:(Fisher FM) "

Sökning: WFRF:(Fisher FM)

  • Resultat 1-35 av 35
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  • 2021
  • swepub:Mat__t
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  • Glasbey, JC, et al. (författare)
  • 2021
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  • 2021
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  • Kanai, M, et al. (författare)
  • 2023
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  • Campbell, PJ, et al. (författare)
  • Pan-cancer analysis of whole genomes
  • 2020
  • Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
  • Tidskriftsartikel (refereegranskat)abstract
    • Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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  • Fisher, AI, et al. (författare)
  • The first example of cobalt(III) mu-oxoacetate with water molecules in apical positions
  • 2008
  • Ingår i: Russian journal of general chemistry. - New York : Maik Nauka/Interperiodica. - 1070-3632 .- 1608-3350. ; 78:11, s. 2006-2012
  • Tidskriftsartikel (refereegranskat)abstract
    • Oxidation of Co(MeCOO)(2)center dot 4H(2)O with ozone in acetic acid followed by the treatment with nitric acid results in the formation of the trinuclear oxo-centered acetate complex [Co(III) (3)(mu(3)-O)(mu-O(2)CMe)(6)(OH(2))(3)] NO(3)center dot MeCOOH ([I]NO(3)center dot MeCOOH). Reasons of a decrease in the idealized symmetry of molecular structure (D (3h) -> D (3)) of the complex cation [I](+) were analyzed by means of quantum-chemical calculations. The complex does not retain its structure in solutions (in water, methanol, and ethanol).
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  • Ge, R, et al. (författare)
  • Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
  • 2023
  • Ingår i: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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  • Khatri, C, et al. (författare)
  • Outcomes after perioperative SARS-CoV-2 infection in patients with proximal femoral fractures: an international cohort study
  • 2021
  • Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 11:11, s. e050830-
  • Tidskriftsartikel (refereegranskat)abstract
    • Studies have demonstrated high rates of mortality in people with proximal femoral fracture and SARS-CoV-2, but there is limited published data on the factors that influence mortality for clinicians to make informed treatment decisions. This study aims to report the 30-day mortality associated with perioperative infection of patients undergoing surgery for proximal femoral fractures and to examine the factors that influence mortality in a multivariate analysis.SettingProspective, international, multicentre, observational cohort study.ParticipantsPatients undergoing any operation for a proximal femoral fracture from 1 February to 30 April 2020 and with perioperative SARS-CoV-2 infection (either 7 days prior or 30-day postoperative).Primary outcome30-day mortality. Multivariate modelling was performed to identify factors associated with 30-day mortality.ResultsThis study reports included 1063 patients from 174 hospitals in 19 countries. Overall 30-day mortality was 29.4% (313/1063). In an adjusted model, 30-day mortality was associated with male gender (OR 2.29, 95% CI 1.68 to 3.13, p<0.001), age >80 years (OR 1.60, 95% CI 1.1 to 2.31, p=0.013), preoperative diagnosis of dementia (OR 1.57, 95% CI 1.15 to 2.16, p=0.005), kidney disease (OR 1.73, 95% CI 1.18 to 2.55, p=0.005) and congestive heart failure (OR 1.62, 95% CI 1.06 to 2.48, p=0.025). Mortality at 30 days was lower in patients with a preoperative diagnosis of SARS-CoV-2 (OR 0.6, 95% CI 0.6 (0.42 to 0.85), p=0.004). There was no difference in mortality in patients with an increase to delay in surgery (p=0.220) or type of anaesthetic given (p=0.787).ConclusionsPatients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and anaesthetic care, including medical optimisation before theatre. Careful preoperative counselling is needed for those with a proximal femoral fracture and SARS-CoV-2, especially those in the highest risk groups.Trial registration numberNCT04323644
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  • Krapivner, S, et al. (författare)
  • Insulin-induced gene 2 involvement in human adipocyte metabolism and body weight regulation
  • 2008
  • Ingår i: The Journal of clinical endocrinology and metabolism. - : The Endocrine Society. - 0021-972X .- 1945-7197. ; 93:5, s. 1995-2001
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Insulin-induced genes (INSIGs) encode proteins that block proteolytic activation of sterol regulatory element-binding proteins, transcription factors that regulate lipogenic enzymes, and adipocyte differentiation.Objective: Here, we analyzed the relative significance of INSIG1 and INSIG2 in human liver and adipocyte metabolism, and defined a novel, functional polymorphism in the promoter of INSIG2 associated with body mass index.Research Methods: Variations in gene expression of different human tissues, of hepatoma cells exposed to INSIG1 and INSIG2 gene silencing probes, and of differentiating 3T3-L1 adipocytes were determined by real-time quantitative PCR. The functional significance of a novel polymorphism in the promoter of INSIG2 was analyzed using in vitro methods and gene expression analysis of human adipose tissue, whereas the phenotype associated with this polymorphism was studied in two cohorts of middle-aged men.Results: Gene expression analysis of 17 human tissues demonstrated that INSIG1 is highly expressed in the liver, whereas INSIG2 is ubiquitously expressed. Gene silencing experiments confirmed that INSIG1, but not INSIG2, regulates the expression of sterol regulatory element-binding proteins target genes in human hepatoma cells. In contrast, adipocyte differentiation of 3T3-L1 cells was associated with a 13-fold increase in expression of INSIG2. Significant relationships between the INSIG2–102G/A polymorphism and body mass index were observed in two cohorts of middle-aged men (ANOVA P = 0.017 and 0.044, respectively). In vitro studies and analysis of allele-specific expression in human adipose tissue substantiated the functional significance of the INSIG2–102G/A polymorphism.Conclusion: INSIG2 is involved in adipocyte metabolism and body weight regulation.
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  • Pantazis, N, et al. (författare)
  • Determining the likely place of HIV acquisition for migrants in Europe combining subject-specific information and biomarkers data
  • 2019
  • Ingår i: Statistical methods in medical research. - : SAGE Publications. - 1477-0334 .- 0962-2802. ; 28:7, s. 1979-1997
  • Tidskriftsartikel (refereegranskat)abstract
    • In most HIV-positive individuals, infection time is only known to lie between the time an individual started being at risk for HIV and diagnosis time. However, a more accurate estimate of infection time is very important in certain cases. For example, one of the objectives of the Advancing Migrant Access to Health Services in Europe (aMASE) study was to determine if HIV-positive migrants, diagnosed in Europe, were infected pre- or post-migration. We propose a method to derive subject-specific estimates of unknown infection times using information from HIV biomarkers’ measurements, demographic, clinical, and behavioral data. We assume that CD4 cell count (CD4) and HIV-RNA viral load trends after HIV infection follow a bivariate linear mixed model. Using post-diagnosis CD4 and viral load measurements and applying the Bayes’ rule, we derived the posterior distribution of the HIV infection time, whereas the prior distribution was informed by AIDS status at diagnosis and behavioral data. Parameters of the CD4–viral load and time-to-AIDS models were estimated using data from a large study of individuals with known HIV infection times (CASCADE). Simulations showed substantial predictive ability (e.g. 84% of the infections were correctly classified as pre- or post-migration). Application to the aMASE study ( n = 2009) showed that 47% of African migrants and 67% to 72% of migrants from other regions were most likely infected post-migration. Applying a Bayesian method based on bivariate modeling of CD4 and viral load, and subject-specific information, we found that the majority of HIV-positive migrants in aMASE were most likely infected after their migration to Europe.
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  • Bravo, L, et al. (författare)
  • 2021
  • swepub:Mat__t
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  • Tabiri, S, et al. (författare)
  • 2021
  • swepub:Mat__t
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