140 research outputs found

    Dimension reduction for systems with slow relaxation

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    We develop reduced, stochastic models for high dimensional, dissipative dynamical systems that relax very slowly to equilibrium and can encode long term memory. We present a variety of empirical and first principles approaches for model reduction, and build a mathematical framework for analyzing the reduced models. We introduce the notions of universal and asymptotic filters to characterize `optimal' model reductions for sloppy linear models. We illustrate our methods by applying them to the practically important problem of modeling evaporation in oil spills.Comment: 48 Pages, 13 figures. Paper dedicated to the memory of Leo Kadanof

    Genetically-Based Olfactory Signatures Persist Despite Dietary Variation

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    Individual mice have a unique odor, or odortype, that facilitates individual recognition. Odortypes, like other phenotypes, can be influenced by genetic and environmental variation. The genetic influence derives in part from genes of the major histocompatibility complex (MHC). A major environmental influence is diet, which could obscure the genetic contribution to odortype. Because odortype stability is a prerequisite for individual recognition under normal behavioral conditions, we investigated whether MHC-determined urinary odortypes of inbred mice can be identified in the face of large diet-induced variation. Mice trained to discriminate urines from panels of mice that differed both in diet and MHC type found the diet odor more salient in generalization trials. Nevertheless, when mice were trained to discriminate mice with only MHC differences (but on the same diet), they recognized the MHC difference when tested with urines from mice on a different diet. This indicates that MHC odor profiles remain despite large dietary variation. Chemical analyses of urinary volatile organic compounds (VOCs) extracted by solid phase microextraction (SPME) and analyzed by gas chromatography/mass spectrometry (GC/MS) are consistent with this inference. Although diet influenced VOC variation more than MHC, with algorithmic training (supervised classification) MHC types could be accurately discriminated across different diets. Thus, although there are clear diet effects on urinary volatile profiles, they do not obscure MHC effects

    Age-dependent alteration of TGF-β signalling in osteoarthritis

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    Osteoarthritis (OA) is a disease of articular cartilage, with aging as the main risk factor. In OA, changes in chondrocytes lead to the autolytic destruction of cartilage. Transforming growth factor-β has recently been demonstrated to signal not only via activin receptor-like kinase 5 (ALK5)-induced Smad2/3 phosphorylation, but also via ALK1-induced Smad1/5/8 phosphorylation in articular cartilage. In aging cartilage and experimental OA, the ratio ALK1/ALK5 has been found to be increased, and the expression of ALK1 is correlated with matrix metalloproteinase-13 expression. The age-dependent shift towards Smad1/5/8 signalling might trigger the differentiation of articular chondrocytes with an autolytic phenotype

    Identification of Loci Controlling Restriction of Parasite Growth in Experimental Taenia crassiceps Cysticercosis

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    Human neurocysticercosis (NC) caused by Taenia solium is a parasitic disease of the central nervous system that is endemic in many developing countries. In this study, a genetic approach using the murine intraperitoneal cysticercosis caused by the related cestode Taenia crassiceps was employed to identify host factors that regulate the establishment and proliferation of the parasite. A/J mice are permissive to T. crassiceps infection while C57BL/6J mice (B6) are comparatively restrictive, with a 10-fold difference in numbers of peritoneal cysticerci recovered 30 days after infection. The genetic basis of this inter-strain difference was explored using 34 AcB/BcA recombinant congenic strains derived from A/J and B6 progenitors, that were phenotyped for T. crassiceps replication. In agreement with their genetic background, most AcB strains (A/J-derived) were found to be permissive to infection while most BcA strains (B6-derived) were restrictive with the exception of a few discordant strains, together suggesting a possible simple genetic control. Initial haplotype association mapping using >1200 informative SNPs pointed to linkages on chromosomes 2 (proximal) and 6 as controlling parasite replication in the AcB/BcA panel. Additional linkage analysis by genome scan in informative [AcB55xDBA/2]F1 and F2 mice (derived from the discordant AcB55 strain), confirmed the effect of chromosome 2 on parasite replication, and further delineated a major locus (LOD = 4.76, p<0.01; peak marker D2Mit295, 29.7 Mb) that we designate Tccr1 (T. crassiceps cysticercosis restrictive locus 1). Resistance alleles at Tccr1 are derived from AcB55 and are inherited in a dominant fashion. Scrutiny of the minimal genetic interval reveals overlap of Tccr1 with other host resistance loci mapped to this region, most notably the defective Hc/C5 allele which segregates both in the AcB/BcA set and in the AcB55xDBA/2 cross. These results strongly suggest that the complement component 5 (C5) plays a critical role in early protective inflammatory response to infection with T. crassiceps

    Problems with Using the Normal Distribution – and Ways to Improve Quality and Efficiency of Data Analysis

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    Background: The Gaussian or normal distribution is the most established model to characterize quantitative variation of original data. Accordingly, data are summarized using the arithmetic mean and the standard deviation, by x 6 SD, or with the standard error of the mean, x 6 SEM. This, together with corresponding bars in graphical displays has become the standard to characterize variation. Methodology/Principal Findings: Here we question the adequacy of this characterization, and of the model. The published literature provides numerous examples for which such descriptions appear inappropriate because, based on the ‘‘95 % range check’’, their distributions are obviously skewed. In these cases, the symmetric characterization is a poor description and may trigger wrong conclusions. To solve the problem, it is enlightening to regard causes of variation. Multiplicative causes are by far more important than additive ones, in general, and benefit from a multiplicative (or log-) normal approach. Fortunately, quite similar to the normal, the log-normal distribution can now be handled easily and characterized at the level of the original data with the help of both, a new sign, x /, times-divide, and notation. Analogous to x 6 SD, it connects the multiplicative (or geometric) mean x * and the multiplicative standard deviation s * in the form x * x /s*, that is advantageous and recommended. Conclusions/Significance: The corresponding shift from the symmetric to the asymmetric view will substantially increas
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