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5th FPGAworld CONFERENCE Book 2008
- 2008
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- The FPGAworld Conference addresses aspects of digital and hardware/software system engineering on FPGA technology. It is a discussion and network forum for students, researchers and engineers working on industrial and research projects, state-of-the-art investigations, development and applications. The book contains some presentations; for more information see (www.fpgaworld.com/conference).
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| 3. |
- Andersson-Evelönn, Emma, 1983-, et al.
(författare)
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Combining epigenetic and clinicopathological variables improves specificity in prognostic prediction in clear cell renal cell carcinoma
- 2020
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Ingår i: Journal of Translational Medicine. - : Springer Science and Business Media LLC. - 1479-5876 .- 1479-5876. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Metastasized clear cell renal cell carcinoma (ccRCC) is associated with a poor prognosis. Almost one-third of patients with non-metastatic tumors at diagnosis will later progress with metastatic disease. These patients need to be identified already at diagnosis, to undertake closer follow up and/or adjuvant treatment. Today, clinicopathological variables are used to risk classify patients, but molecular biomarkers are needed to improve risk classification to identify the high-risk patients which will benefit most from modern adjuvant therapies. Interestingly, DNA methylation profiling has emerged as a promising prognostic biomarker in ccRCC. This study aimed to derive a model for prediction of tumor progression after nephrectomy in non-metastatic ccRCC by combining DNA methylation profiling with clinicopathological variables.Methods: A novel cluster analysis approach (Directed Cluster Analysis) was used to identify molecular biomarkers from genome-wide methylation array data. These novel DNA methylation biomarkers, together with previously identified CpG-site biomarkers and clinicopathological variables, were used to derive predictive classifiers for tumor progression.Results: The “triple classifier” which included both novel and previously identified DNA methylation biomarkers together with clinicopathological variables predicted tumor progression more accurately than the currently used Mayo scoring system, by increasing the specificity from 50% in Mayo to 64% in our triple classifier at 85% fixed sensitivity. The cumulative incidence of progress (pCIP5yr) was 7.5% in low-risk vs 44.7% in high-risk in M0 patients classified by the triple classifier at diagnosis.Conclusions: The triple classifier panel that combines clinicopathological variables with genome-wide methylation data has the potential to improve specificity in prognosis prediction for patients with non-metastatic ccRCC.
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| 4. |
- Björkman, Per, et al.
(författare)
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Common Interactions between S100A4 and S100A9 Defined by a Novel Chemical Probe.
- 2013
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:5
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Tidskriftsartikel (refereegranskat)abstract
- S100A4 and S100A9 proteins have been described as playing roles in the control of tumor growth and metastasis. We show here that a chemical probe, oxyclozanide (OX), selected for inhibiting the interaction between S100A9 and the receptor for advanced glycation end-products (RAGE) interacts with both S100A9 and S100A4. Furthermore, we show that S100A9 and S100A4 interact with RAGE and TLR4; interactions that can be inhibited by OX. Hence, S100A4 and S100A9 display similar functional elements despite their primary sequence diversity. This was further confirmed by showing that S100A4 and S100A9 dimerize both in vitro and in vivo. All of these interactions required levels of Zn(++) that are found in the extracellular space but not intracellularly. Interestingly, S100A4 and S100A9 are expressed by distinct CD11b(+) subpopulations both in healthy animals and in animals with either inflammatory disease or tumor burden. The functions of S100A9 and S100A4 described in this paper, including heterodimerization, may therefore reflect S100A9 and S100A4 that are released into the extra-cellular milieu.
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| 5. |
- Chakraborty, Paramita, et al.
(författare)
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Vesicular Location and Transport of S100A8 and S100A9 Proteins in Monocytoid Cells.
- 2015
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:12
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Tidskriftsartikel (refereegranskat)abstract
- We show here, by using surface biotinylation, followed by Western blotting or surface plasmon resonance analysis, that very low levels of S100A8 and/or S100A9 can be detected on the surface of THP-1 cells or freshly isolated human monocytes. This was supported by immune-electron microscopy where we observed membrane-associated expression of the proteins restricted to small patches. By using confocal microscopy we could determine that S100A8 and S100A9 protein in THP-1 cells or freshly isolated human monocytes was mostly present in vesicular structures. This finding was confirmed using immune-electron microscopy. Subcellular fractionation and confocal microscopy showed that these vesicular structures are mainly early endosomes and endolysosomes. Our subsequent studies showed that accumulation of S100A8 and S100A9 in the endolysosomal compartment is associated with induction of their release from the cells. Furthermore, an inhibitor of lysosomal activity could modulate the release of S100A8 and S100A9 in the extracellular milieu. Our current results suggest that the S100A8 and S100A9 proteins are primarily associated with certain kinds of cytosolic vesicles and may be secreted via an endolysosomal pathway.
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| 6. |
- Crilly, Julia, et al.
(författare)
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Factors predictive of hospital admission for children via emergency departments in Australia and Sweden: an observational cross-sectional study
- 2024
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Ingår i: BMC Health Services Research. - : Springer Nature. - 1472-6963. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Identifying factors predictive of hospital admission can be useful to prospectively inform bed management and patient flow strategies and decrease emergency department (ED) crowding. It is largely unknown if admission rate or factors predictive of admission vary based on the population to which the ED served (i.e., children only, or both adults and children). This study aimed to describe the profile and identify factors predictive of hospital admission for children who presented to four EDs in Australia and one ED in Sweden.Methods: A multi-site observational cross-sectional study using routinely collected data pertaining to ED presentations made by children < 18 years of age between July 1, 2011 and October 31, 2012. Univariate and multivariate analysis were undertaken to determine factors predictive of hospital admission.Results: Of the 151,647 ED presentations made during the study period, 22% resulted in hospital admission. Admission rate varied by site; the children's EDs in Australia had higher admission rates (South Australia: 26%, Queensland: 23%) than the mixed (adult and children's) EDs (South Australia: 13%, Queensland: 17%, Sweden: 18%). Factors most predictive of hospital admission for children, after controlling for triage category, included hospital type (children's only) adjusted odds ratio (aOR):2.3 (95%CI: 2.2-2.4), arrival by ambulance aOR:2.8 (95%CI: 2.7-2.9), referral from primary health aOR:1.5 (95%CI: 1.4-1.6) and presentation with a respiratory or gastrointestinal condition (aOR:2.6, 95%CI: 2.5-2.8 and aOR:1.5, 95%CI: 1.4-1.6, respectively). Predictors were similar when each site was considered separately.Conclusions: Although the characteristics of children varied by site, factors predictive of hospital admission were mostly similar. The awareness of these factors predicting the need for hospital admission can support the development of clinical pathways.
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| 7. |
- Källberg, David, et al.
(författare)
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A moment-distance hybrid method for estimating a mixture of two symmetric densities
- 2018
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Ingår i: Modern Stochastics: Theory and Applications. - 2351-6054. ; 5:1, s. 1-36
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Tidskriftsartikel (refereegranskat)abstract
- In clustering of high-dimensional data a variable selection is commonly applied to obtain an accurate grouping of the samples. For two-class problems this selection may be carried out by fitting a mixture distribution to each variable. We propose a hybrid method for estimating a parametric mixture of two symmetric densities. The estimator combines the method of moments with the minimum distance approach. An evaluation study including both extensive simulations and gene expression data from acute leukemia patients shows that the hybrid method outperforms a maximum-likelihood estimator in model-based clustering. The hybrid estimator is flexible and performs well also under imprecise model assumptions, suggesting that it is robust and suited for real problems.
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| 8. |
- Källberg, David, 1982-, et al.
(författare)
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Comparison of Methods for Feature Selection in Clustering of High-Dimensional RNA-Sequencing Data to Identify Cancer Subtypes
- 2021
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Ingår i: Frontiers in Genetics. - : Frontiers Media S.A.. - 1664-8021. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Cancer subtype identification is important to facilitate cancer diagnosis and select effective treatments. Clustering of cancer patients based on high-dimensional RNA-sequencing data can be used to detect novel subtypes, but only a subset of the features (e.g., genes) contains information related to the cancer subtype. Therefore, it is reasonable to assume that the clustering should be based on a set of carefully selected features rather than all features. Several feature selection methods have been proposed, but how and when to use these methods are still poorly understood. Thirteen feature selection methods were evaluated on four human cancer data sets, all with known subtypes (gold standards), which were only used for evaluation. The methods were characterized by considering mean expression and standard deviation (SD) of the selected genes, the overlap with other methods and their clustering performance, obtained comparing the clustering result with the gold standard using the adjusted Rand index (ARI). The results were compared to a supervised approach as a positive control and two negative controls in which either a random selection of genes or all genes were included. For all data sets, the best feature selection approach outperformed the negative control and for two data sets the gain was substantial with ARI increasing from (−0.01, 0.39) to (0.66, 0.72), respectively. No feature selection method completely outperformed the others but using the dip-rest statistic to select 1000 genes was overall a good choice. The commonly used approach, where genes with the highest SDs are selected, did not perform well in our study.
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| 10. |
- Källberg, David, 1982-, et al.
(författare)
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Estimation of entropy-type integral functionals
- 2016
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Ingår i: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 45:4, s. 887-905
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Entropy-type integral functionals of densities are widely used in mathematical statistics, information theory, and computer science. Examples include measures of closeness between distributions (e.g., density power divergence) and uncertainty characteristics for a random variable (e.g., Renyi entropy). In this paper, we study U-statistic estimators for a class of such functionals. The estimators are based on ε-close vector observations in the corresponding independent and identically distributed samples. We prove asymptotic properties of the estimators (consistency and asymptotic normality) under mild integrability and smoothness conditions for the densities. The results can be applied in diverse problems in mathematical statistics and computer science (e.g., distribution identication problems, approximate matching for random databases, two-sample problems).
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