On Kinematic Substructure in the Sextans Dwarf Spheroidal Galaxy

We present multifiber echelle radial velocity results for 551 stars in the Sextans dwarf spheroidal galaxy and identify 294 stars as probable Sextans members. The projected velocity dispersion profile of the binned data remains flat to a maximum angular radius of $30^{\prime}$. We introduce a nonparametric technique for estimating the projected velocity dispersion surface, and use this to search for kinematic substructure. Our data do not confirm previous reports of a kinematically distinct stellar population at the Sextans center. Instead we detect a region near the Sextans core radius that is kinematically colder than the overall Sextans sample with 95% confidence.Comment: accepted for publication in ApJ Letters; 4 figures (2 color

Lipidomic UPLC-MS/MS Profiles of Normal-Appearing White Matter Differentiate Primary and Secondary Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a neurodegenerative inflammatory disease where an autoimmune response to components of the central nervous system leads to a loss of myelin and subsequent neurological deterioration. People with MS can develop primary or secondary progressive disease (PPMS, SPMS) and differentiation of the specific differences in the pathogenesis of these two courses, at the molecular level, is currently unclear. Recently, lipidomics studies using human biofluids, mainly plasma and cerebrospinal fluid, have highlighted a possible role for lipids in the initiation and progression of MS. However, there is a lack of lipidomics studies in MS on CNS tissues, such as normal-appearing white matter (NAWM), where local inflammation initially occurs. Herein, we developed an untargeted reverse phase ultra-performance liquid chromatography time of flight tandem mass spectrometry (RP-UPLC-TOF MSE)-based workflow, in combination with multivariate and univariate statistical analysis, to assess significant differences in lipid profiles in brain NAWM from post-mortem cases of PPMS, SPMS and controls. Groups of eight control, nine PPMS and seven SPMS NAWM samples were used. Correlation analysis of the identified lipids by RP-UPLC-TOF MSE was undertaken to remove those lipids that correlated with age, gender and post-mortem interval as confounding factors. We demonstrate that there is a significantly altered lipid profile of control cases compared with MS cases and that progressive disease, PPMS and SPMS, can be differentiated on the basis of the lipidome of NAWM with good sensitivity, specificity and prediction accuracy based on receiver operating characteristic (ROC) curve analysis. Metabolic pathway analysis revealed that the most altered lipid pathways between PPMS and SPMS were glycerophospholipid metabolism, glycerophosphatidyl inositol (GPI) anchor synthesis and linoleic acid metabolism. Further understanding of the impact of these lipid alterations described herein associated with progression will provide an increased understanding of the mechanisms underpinning progression and highlight possible new therapeutic targets

Estimating Dark Matter Distributions

Thanks to instrumental advances, new, very large kinematic datasets for nearby dwarf spheroidal (dSph) galaxies are on the horizon. A key aim of these datasets is to help determine the distribution of dark matter in these galaxies. Past analyses have generally relied on specific dynamical models or highly restrictive dynamical assumptions. We describe a new, non-parametric analysis of the kinematics of nearby dSph galaxies designed to take full advantage of the future large datasets. The method takes as input the projected positions and radial velocities of stars known to be members of the galaxies, but does not use any parametric dynamical model, nor the assumption that the mass distribution follows that of the visible matter. The problem of estimating the radial mass distribution, M(r) (the mass interior to true radius r), is converted into a problem of estimating a regression function non-parametrically. From the Jeans Equation we show that the unknown regression function is subject to fundamental shape restrictions which we exploit in our analysis using statistical techniques borrowed from isotonic estimation and spline smoothing. Simulations indicate that M(r) can be estimated to within a factor of two or better with samples as small as 1000 stars over almost the entire radial range sampled by the kinematic data. The technique is applied to a sample of 181 stars in the Fornax dSph galaxy. We show that the galaxy contains a significant, extended dark halo some ten times more massive than its baryonic component. Though applied here to dSph kinematics, this approach can be used in the analysis of any kinematically hot stellar system in which the radial velocity field is discretely sampled.Comment: Accepted for publication in The Astrophysical Journa

The use of vibrational spectroscopy to study the pathogenesis multiple sclerosis and other neurological conditions

Spectroscopy techniques are valuable tools in biomedical research and have been used extensively in the study of disease. However, neurological conditions such as multiple sclerosis (MS) have received little attention and the available spectroscopy studies are limited, both in overall numbers of patients studied and the disease samples considered. MS is a complex immune-mediated disease, with variable clinical courses and limited therapeutic options. This review aims to summarize current literature in the area, demonstrating how spectroscopy techniques can provide valuable information to inform and advance research into the most common neurological condition affecting young adults

Regularity of Edge Ideals and Their Powers

We survey recent studies on the Castelnuovo-Mumford regularity of edge ideals of graphs and their powers. Our focus is on bounds and exact values of $\text{ reg } I(G)$ and the asymptotic linear function $\text{ reg } I(G)^q$, for $q \geq 1,$ in terms of combinatorial data of the given graph $G.$Comment: 31 pages, 15 figure

On the weak convergence of stochastic processes without discontinuities of the second kind

Subspaces D α , α > 0, of D [0, 1] are defined and given complete metrics d α which are stronger than the Prokhorov metric. The spaces ( D α d α ) are shown to be separable, and their pre-compact subsets are characterized. A condition which is known to guarantee weak pre-compactness of sets of probability measures over D [0, 1] is shown to also guarantee weak pre-compactness of probability measures over D α for appropriate values of α. Applications are made to the weak convergence of measures induced by stochastic processes, and some examples are included.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47645/1/440_2004_Article_BF00538382.pd

Antichain cutsets of strongly connected posets

Rival and Zaguia showed that the antichain cutsets of a finite Boolean lattice are exactly the level sets. We show that a similar characterization of antichain cutsets holds for any strongly connected poset of locally finite height. As a corollary, we get such a characterization for semimodular lattices, supersolvable lattices, Bruhat orders, locally shellable lattices, and many more. We also consider a generalization to strongly connected hypergraphs having finite edges.Comment: 12 pages; v2 contains minor fixes for publicatio

Inference for bounded parameters

The estimation of signal frequency count in the presence of background noise has had much discussion in the recent physics literature, and Mandelkern [1] brings the central issues to the statistical community, leading in turn to extensive discussion by statisticians. The primary focus however in [1] and the accompanying discussion is on the construction of a confidence interval. We argue that the likelihood function and $p$-value function provide a comprehensive presentation of the information available from the model and the data. This is illustrated for Gaussian and Poisson models with lower bounds for the mean parameter

Evaluation of ADAMTS-9 Expression in Post-Mortem Brain Tissue

Background: Extracellular Matrix (ECM) modifications have been reported in the Central Nervous System (CNS) of multiple sclerosis (MS) within post mortem brain tissue due to both the increased synthesis of ECM proteoglycans, and release activation of matrix metalloproteinase (MMPs). Multiple sclerosis (MS) is chronic inflammatory demyelinating disease written off as inflammation and demyelination disease, mainly located in central nervous system (CNS) white matter (WM). This study aims to clarify the potential pathophysiologic role of adisintegrin And metalloproteinase with thromboSpondin motif-9 (ADAMTS-9) in MS. Materials and methods: Immunohistochemistry was performed to study the expression of ADAMTS-9 in both normal and MS white matter by confocal microscopic using specific antibodies. Fifty frozen blocks of brain tissue were obtained from the UK MS Society Tissue. All tissues blocks were marked by immunohistological material including antibodies to Human leukocyte antigen (HLA-DR) to assess the macrophage activation, Glial fibrillary acidic protein (GFAP) for astrocyte, neurofilaments (NF) for neurons and Von Willbrand factor (VWF) for endothelial. Results: In MS lesions, ADMTS-9 expression was increased in comparison to control samples. The expression of ADAMTS-9 was increased in active lesions as well as was associated with different cells from neuron, endothelial covering blood vessels astrocyte and microglia. Conclusion: The expression of ADAMTS-9 at the protein level was increased in active inflammatory lesions with evidence of myelin breakdown, suggesting that up-regulation of ADAMTS-9 may be a general phenomenon induced by CNS injurie