| 1. |
- 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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| 2. |
- Källberg, David, 1982-
(författare)
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Nonparametric Statistical Inference for Entropy-type Functionals
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In this thesis, we study statistical inference for entropy, divergence, and related functionals of one or two probability distributions. Asymptotic properties of particular nonparametric estimators of such functionals are investigated. We consider estimation from both independent and dependent observations. The thesis consists of an introductory survey of the subject and some related theory and four papers (A-D).In Paper A, we consider a general class of entropy-type functionals which includes, for example, integer order Rényi entropy and certain Bregman divergences. We propose U-statistic estimators of these functionals based on the coincident or epsilon-close vector observations in the corresponding independent and identically distributed samples. We prove some asymptotic properties of the estimators such as consistency and asymptotic normality. Applications of the obtained results related to entropy maximizing distributions, stochastic databases, and image matching are discussed.In Paper B, we provide some important generalizations of the results for continuous distributions in Paper A. The consistency of the estimators is obtained under weaker density assumptions. Moreover, we introduce a class of functionals of quadratic order, including both entropy and divergence, and prove normal limit results for the corresponding estimators which are valid even for densities of low smoothness. The asymptotic properties of a divergence-based two-sample test are also derived.In Paper C, we consider estimation of the quadratic Rényi entropy and some related functionals for the marginal distribution of a stationary m-dependent sequence. We investigate asymptotic properties of the U-statistic estimators for these functionals introduced in Papers A and B when they are based on a sample from such a sequence. We prove consistency, asymptotic normality, and Poisson convergence under mild assumptions for the stationary m-dependent sequence. Applications of the results to time-series databases and entropy-based testing for dependent samples are discussed.In Paper D, we further develop the approach for estimation of quadratic functionals with m-dependent observations introduced in Paper C. We consider quadratic functionals for one or two distributions. The consistency and rate of convergence of the corresponding U-statistic estimators are obtained under weak conditions on the stationary m-dependent sequences. Additionally, we propose estimators based on incomplete U-statistics and show their consistency properties under more general assumptions.
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| 3. |
- Källberg, David, et al.
(författare)
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Statistical estimation of quadratic Rényi entropy for a stationary m-dependent sequence
- 2014
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Ingår i: Journal of nonparametric statistics (Print). - : Taylor & Francis. - 1048-5252 .- 1029-0311. ; 26:2, s. 385-411
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Tidskriftsartikel (refereegranskat)abstract
- The Rényi entropy is a generalization of the Shannon entropy and is widely used in mathematical statistics and applied sciences for quantifying the uncertainty in a probability distribution. We consider estimation of the quadratic Rényi entropy and related functionals for the marginal distribution of a stationary m-dependent sequence. The U-statistic estimators under study are based on the number of ε-close vector observations in the corresponding sample. A variety of asymptotic properties for these estimators are obtained (e.g., consistency, asymptotic normality, Poisson convergence). The results can be used in diverse statistical and computer science problems whenever the conventional independence assumption is too strong (e.g., ε-keys in time series databases, distribution identication problems for dependent samples).
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| 4. |
- Källberg, David, 1982-, et al.
(författare)
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Statistical inference for Rényi entropy functionals
- 2012
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Ingår i: Conceptual modelling and its theoretical foundations. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642282782 - 9783642282799 ; , s. 36-51
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Bokkapitel (refereegranskat)abstract
- Numerous entropy-type characteristics (functionals) generalizing Rényi entropy are widely used in mathematical statistics, physics, information theory, and signal processing for characterizing uncertainty in probability distributions and distribution identification problems. We consider estimators of some entropy (integral) functionals for discrete and continuous distributions based on the number of epsilon-close vector records in the corresponding independent and identically distributed samples from two distributions. The proposed estimators are generalized U-statistics. We show the asymptotic properties of these estimators (e.g., consistency and asymptotic normality). The results can be applied in various problems in computer science and mathematical statistics (e.g., approximate matching for random databases, record linkage, image matching).
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| 5. |
- Källberg, David, 1982-, et al.
(författare)
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Statistical modeling for image matching in large image databases
- 2011
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Ingår i: 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing. - : IEEE. - 9780769545806 ; , s. 648-652
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Konferensbidrag (refereegranskat)abstract
- Matching a query (reference) image to an image extracted from a database containing (possibly) transformed image copies is an important retrieval task. In this paper we present a general method based on matching densities of the corresponding image feature vectors by using the Bregman distances. We consider statistical estimators for some quEDratic entropy-type characteristics. In particular, the quEDratic Bregman distances can be evaluated in image matching problems whenever images are modeled by random feature vectors in large image databases. Moreover, this method can be used for average case analysis for optimization of joining large databases. © 2011 IEEE.
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| 6. |
- Källberg, Eva, et al.
(författare)
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CD11b(+)Ly6C(++)Ly6G(-) cells show distinct function in mice with chronic inflammation or tumor burden
- 2012
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Ingår i: BMC Immunology. - : Springer Science and Business Media LLC. - 1471-2172. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Background: S100A9 has been shown to be important for the function of so called Myeloid Derived Suppressor Cells (MDSC). Cells with a similar phenotype are also involved in pro-inflammatory processes, and we therefore wanted to investigate the gene expression and function of these cells in animals that were either subjected to chronic inflammation, or inoculated with tumors. Methods: CD11b(+)Ly6C(++) and Ly6G(+) cells were isolated from spleen, tumor tissue or inflammatory granulomas. S100A9, Arginase 1 and iNOS gene expression in the various CD11b(+) cell populations was analyzed using Q-PCR. The suppressive activity of the CD11b(+) cell populations from different donors was studied in co-culture experiments. Results: S100A9 was shown to be expressed mainly in splenic CD11b(+)Ly6C(+)G(+) cells both at the RNA and protein level. Arginase I and iNOS expression could be detected in both CD11b(+)Ly6C(+)Ly6G(+) and CD11b(+)Ly6C(+)G(-)/C(++)G(-) derived from tumors or a site of chronic inflammation, but was very low in the same cell populations isolated from the spleen. CD11b(+) cells isolated from mice with peritoneal chronic inflammation were able to stimulate T lymphocytes, while CD11b(+) cells from mice with peritoneal tumors suppressed T cell growth. Conclusion: An identical CD11b(+)Ly6C(++)G(-) cell population appears to have the ability to adopt immune stimulatory or immune suppressive functions dependent on the presence of a local inflammatory or tumor microenvironment. Thus, there is a functional plasticity in the CD11b(+)Ly6C(++)G(-) cell population that cannot be distinguished with the current molecular markers.
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| 7. |
- Källberg, Eva, et al.
(författare)
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S100A9 Interaction with TLR4 Promotes Tumor Growth
- 2012
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Ingår i: PLOS ONE. - San Francisco : Public Library of Science. - 1932-6203. ; 7:3, s. e34207-
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Tidskriftsartikel (refereegranskat)abstract
- By breeding TRAMP mice with S100A9 knock-out (S100A9(-/-)) animals and scoring the appearance of palpable tumors we observed a delayed tumor growth in animals devoid of S100A9 expression. CD11b(+) S100A9 expressing cells were not observed in normal prostate tissue from control C57BL/6 mice but were readily detected in TRAMP prostate tumors. Also, S100A9 expression was observed in association with CD68(+) macrophages in biopsies from human prostate tumors. Delayed growth of TRAMP tumors was also observed in mice lacking the S100A9 ligand TLR4. In the EL-4 lymphoma model tumor growth inhibition was observed in S100A9(-/-) and TLR4(-/-), but not in RAGE(-/-) animals lacking an alternative S100A9 receptor. When expression of immune-regulating genes was analyzed using RT-PCR the only common change observed in mice lacking S100A9 and TLR4 was a down-regulation of TGF beta expression in splenic CD11b(+) cells. Lastly, treatment of mice with a small molecule (ABR-215050) that inhibits S100A9 binding to TLR4 inhibited EL4 tumor growth. Thus, S100A9 and TLR4 appear to be involved in promoting tumor growth in two different tumor models and pharmacological inhibition of S100A9-TLR4 interactions is a novel and promising target for anti-tumor therapies.
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