Development of an in silico methodology for the multiscale modelling of atherosclerosis

Atherosclerosis is the main cause of mortality and morbidity in Western World, causing more death and disability than all the types of cancer. Given its high potential danger it is of major importance to better understand the causes of atherosclerosis, which are linked to both the lipoprotein metabolism and haemodynamics in arteries. Together with in vivo and in vitro experiments, in silico models and simulations allow for a better insight and understanding of the mechanisms of atherosclerosis formation. A multiscale model coming from the integration of a fluid dynamics model, and a biochemical model is here presented for the modelling of atherosclerosis at its early stage. An artery-specific approach was used in the fluid dynamics model for modelling the interaction between arterial endothelium and blood flow. The low density Lipoprotein (LDL) oxidation leading to immune-response (cytokines, monocytes/macrophages) and foam cell formation and accumulation at the basis of plaque formation was described in the biochemical model. Integration of these modelling approaches led to the creation of an effective tool for the modelling of atherosclerosis plaque development, the atherosclerosis remodelling cycle. The impact on the disease development of different mean blood LDL concentrations and arterial geometries was analysed. The atherosclerosis remodelling cycle was applied for patient-specific simulation of plaque formations in a patient presenting with atherosclerosis formations in the aorta and peripheral arteries. When compared with the multi-slice computed tomography (MSCT) images, the model highlighted atherosclerosis-prone areas, where plaques were found in vivo, with 91.7% accuracy and replicated 41.7% of the plaques presenting in the patients

Anomalous RR Lyrae stars(?). III. CM Leonis

Time series of B,V,I CCD photometry and radial velocity measurements from high resolution spectroscopy (R=30,000) covering the full pulsation cycle are presented for the field RR Lyrae star CM Leonis. The photometric data span a 6 year interval from 1994 to 1999, and allow us to firmly establish the pulsation mode and periodicity of the variable. The derived period P=0.361699 days (+/- 0.000001) is very close to the value published in the Fourth Edition of the General Catalogue of Variable Stars (P=0.361732 days). However, contrary to what was previously found, the amplitude and shape of the light curve qualify CM Leo as a very regular first overtone pulsator with a prominent hump on the rising branch of its multicolour light curves. According to an abundace analysis performed on three spectra taken near minimum light (0.42 < phase < 0.61), CM Leo is a metal-poor star with metal abundance [Fe/H]=-1.93 +/- 0.20. The photometric and radial velocity curves of CM Leo have been compared with the predictions of suitable pulsational models to infer tight constraints on the stellar mass, effective temperature, and distance modulus of the star. We derive a true distance modulus of CM Leo of (m-M)0=13.11 +/- 0.02 mag and a corresponding absolute magnitude of Mv=0.47 +/- 0.04. This absolute magnitude, once corrected for evolutionary and metallicity effects, leads to a true distance modulus of the Large Magellanic Cloud of (m-M)0=18.43 +/- 0.06 mag, in better agreement with the long astronomical distance scale.Comment: 14 pages, 10 figures, accepted for publication in MNRA

Exploring complex networks via topological embedding on surfaces

We demonstrate that graphs embedded on surfaces are a powerful and practical tool to generate, characterize and simulate networks with a broad range of properties. Remarkably, the study of topologically embedded graphs is non-restrictive because any network can be embedded on a surface with sufficiently high genus. The local properties of the network are affected by the surface genus which, for example, produces significant changes in the degree distribution and in the clustering coefficient. The global properties of the graph are also strongly affected by the surface genus which is constraining the degree of interwoveness, changing the scaling properties from large-world-kind (small genus) to small- and ultra-small-world-kind (large genus). Two elementary moves allow the exploration of all networks embeddable on a given surface and naturally introduce a tool to develop a statistical mechanics description. Within such a framework, we study the properties of topologically-embedded graphs at high and low `temperatures' observing the formation of increasingly regular structures by cooling the system. We show that the cooling dynamics is strongly affected by the surface genus with the manifestation of a glassy-like freezing transitions occurring when the amount of topological disorder is low.Comment: 18 pages, 7 figure

Towards personalised management of atherosclerosis via computational models in vascular clinics: technology based on patient-specific simulation approach

The development of a new technology based on patient-specific modelling for personalised healthcare in the case of atherosclerosis is presented. Atherosclerosis is the main cause of death in the world and it has become a burden on clinical services as it manifests itself in many diverse forms, such as coronary artery disease, cerebrovascular disease/stroke and peripheral arterial disease. It is also a multifactorial, chronic and systemic process that lasts for a lifetime, putting enormous financial and clinical pressure on national health systems. In this Letter, the postulate is that the development of new technologies for healthcare using computer simulations can, in the future, be developed as in-silico management and support systems. These new technologies will be based on predictive models (including the integration of observations, theories and predictions across a range of temporal and spatial scales, scientific disciplines, key risk factors and anatomical sub-systems) combined with digital patient data and visualisation tools. Although the problem is extremely complex, a simulation workflow and an exemplar application of this type of technology for clinical use is presented, which is currently being developed by a multidisciplinary team following the requirements and constraints of the Vascular Service Unit at the University College Hospital, London

CU Comae: a new field double-mode RR Lyrae, the most metal poor discovered to date

We report the discovery of a new double-mode RR Lyrae variable (RRd) in the field of our Galaxy: CU Comae. CU Comae is the sixth such RRd identified to date and is the most metal-poor RRd ever detected. Based on BVI CCD photometry spanning eleven years of observations, we find that CU Comae has periods P0=0.5441641 +/-0.0000049d and P1=0.4057605 +/-0.0000018d. The amplitude of the primary (first-overtone) period of CU Comae is about twice the amplitude of the secondary (fundamental) period. The combination of the fundamental period of pulsation P0 and the period ratio of P1/P0=0.7457 places the variable on the metal-poor side of the Petersen diagram, in the region occupied by M68 and M15 RRd's. A mass of 0.83 solar masses is estimated for CU Comae using an updated theoretical calibration of the Petersen diagram. High resolution spectroscopy (R=30,000) covering the full pulsation cycle of CU Comae was obtained with the 2.7 m telescope of the Mc Donald Observatory, and has been used to build up the radial velocity curve of the variable. Abundance analysis done on the four spectra taken near minimum light (phase: 0.54 -- 0.71) confirms the metal poor nature of CU Comae, for which we derive [Fe/H]=-2.38 +/-0.20. This value places this new RRd at the extreme metal-poor edge of the metallicity distribution of the RR Lyrae variables in our Galaxy.Comment: 21 pages including 8 Tables, Latex, 11 Figures. Accepted for publication in The Astronomical Journal, October 2000 issu

A multi-Lorentzian timing study of the atoll sources 4U 0614+09 and 4U 1728-34

We present the results of a multi-Lorentzian fit to the power spectra of two kilohertz QPO sources; 4U 0614+09 and 4U 1728-34. This work was triggered by recent results of a similar fit to the black-hole candidates (BHCs) GX 339-4 and Cyg X-1 by Nowak in 2000. We find that one to six Lorentzians are needed to fit the power spectra of our two sources. The use of exactly the same fit function reveals that the timing behaviour of 4U 0614+09 and 4U 1728-34 is almost identical at luminosities which are about a factor 5 different. As the characteristic frequency of the Lorentzians we use the frequency, nu_max, at which each component contributes most of its variance per log frequency as proposed by Belloni, Psaltis & van der Klis in 2001. When using nu_max instead of the centroid frequency of the Lorentzian, the recently discovered hectohertz Lorentzian is practically constant in frequency. We use our results to test the suggestions by, respectively, Psaltis Belloni and van der Klis in 1999 and Nowak in 2000 that the two Lorentzians describing the high-frequency end of the broad-band noise in BHCs in the low state can be identified with the kilohertz QPOs in the neutron star low mass X-ray binaries. We find, that when the two kilohertz QPOs are clearly present, the low-frequency part of the power spectrum is too complicated to draw immediate conclusions from the nature of the components detected in any one power spectrum. However, the relations we observe between the characteristic frequencies of the kilohertz QPOs and the band-limited noise, when compared to the corresponding relations in BHCs, hint towards the identification of the second-highest frequency Lorentzian in the BHCs with the lower kilohertz QPO. They do not confirm the identification of the highest-frequency Lorentzian with the upper kilohertz QPO.Comment: 30 pages, 35 figures, ApJ accepted; changed name of BLN QPO into very low-frequency Lorentzian, removed table 4 and figure 8 from previous versio

Cancer-Initiating Cells from Colorectal cancer Patients Escape from T Cell-Mediated Immunosurveillance In Vitro through Membrane-Bound IL-4

Cancer-initiating cells (CICs) that are responsible for tumor initiation, propagation, and resistance to standard therapies have been isolated from human solid tumors, including colorectal cancer (CRC). The aim of this study was to obtain an immunological profile of CRC-derived CICs and to identify CIC-associated target molecules for T cell immunotherapy. We have isolated cells with CIC properties along with their putative non-CIC autologous counterparts from human primary CRC tissues. These CICs have been shown to display “tumor-initiating/stemness” properties, including the expression of CIC-associated markers (e.g., CD44, CD24, ALDH-1, EpCAM, Lgr5), multipotency, and tumorigenicity following injection in immunodeficient mice. The immune profile of these cells was assessed by phenotype analysis and by in vitro stimulation of PBMCs with CICs as a source of Ags. CICs, compared with non-CIC counterparts, showed weak immunogenicity. This feature correlated with the expression of high levels of immu- nomodulatory molecules, such as IL-4, and with CIC-mediated inhibitory activity for anti-tumor T cell responses. CIC-associated IL-4 was found to be responsible for this negative function, which requires cell-to-cell contact with T lymphocytes and which is impaired by blocking IL-4 signaling. In addition, the CRC-associated Ag COA-1 was found to be expressed by CICs and to represent, in an autologous setting, a target molecule for anti-tumor T cells. Our study provides relevant information that may contribute to designing new immunotherapy protocols to target CICs in CRC patient

Hierarchical information clustering by means of topologically embedded graphs

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network structure. For a planar embedding, this method provides both the intra-cluster hierarchy, which describes the way clusters are composed, and the inter-cluster hierarchy which describes how clusters gather together. We discuss performance, robustness and reliability of this method by first investigating several artificial data-sets, finding that it can outperform significantly other established approaches. Then we show that our method can successfully differentiate meaningful clusters and hierarchies in a variety of real data-sets. In particular, we find that the application to gene expression patterns of lymphoma samples uncovers biologically significant groups of genes which play key-roles in diagnosis, prognosis and treatment of some of the most relevant human lymphoid malignancies.Comment: 33 Pages, 18 Figures, 5 Table

Direct Evidence that Bevacizumab, an Anti-VEGF Antibody, Up-regulates SDF1 , CXCR4, CXCL6, and Neuropilin 1 in Tumors from Patients with Rectal Cancer

Clinical studies converge on the observation that circulating cytokines are elevated in most cancer patients by anti-vascular endothelial growth factor (VEGF) therapy. However, the source of these molecules and their relevance in tumor escape remain unknown. We examined the gene expression profiles of cancer cells and tumor-associated macrophages in tumor biopsies before and 12 days after monotherapy with the anti-VEGF antibody bevacizumab in patients with rectal carcinoma. Bevacizumab up-regulated stromal cell-derived factor 1alpha (SDF1alpha), its receptor CXCR4, and CXCL6, and down-regulated PlGF, Ang1, and Ang2 in cancer cells. In addition, bevacizumab decreased Ang1 and induced neuropilin 1 (NRP1) expression in tumor-associated macrophages. Higher SDF1alpha plasma levels during bevacizumab treatment significantly associated with distant metastasis at three years. These data show that VEGF blockade up-regulates inflammatory pathways and NRP1, which should be evaluated as potential targets for improving anti-VEGF therapy