Network theory and SARS: predicting outbreak diversity

Many infectious diseases spread through populations via the networks formed by physical contacts among individuals. The patterns of these contacts tend to be highly heterogeneous. Traditional "compartmental" modeling in epidemiology, however, assumes that population groups are fully mixed, that is, every individual has an equal chance of spreading the disease to every other. Applications of compartmental models to Severe Acute Respiratory Syndrome (SARS) resulted in estimates of the fundamental quantity called the basic reproductive number R0--the number of new cases of SARS resulting from a single initial case--above one, implying that, without public health intervention, most outbreaks should spark large-scale epidemics. Here we compare these predictions to the early epidemiology of SARS. We apply the methods of contact network epidemiology to illustrate that for a single value of R0, any two outbreaks, even in the same setting, may have very different epidemiological outcomes. We offer quantitative insight into the heterogeneity of SARS outbreaks worldwide, and illustrate the utility of this approach for assessing public health strategies.     

Quantification of atherosclerotic plaque activity and vascular inflammation using [18-F] fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT)

Conventional non-invasive imaging modalities of atherosclerosis such as coronary artery calcium (CAC) and carotid intimal medial thickness (C-IMT) provide information about the burden of disease. However, despite multiple validation studies of CAC, and C-IMT, these modalities do not accurately assess plaque characteristics, and the composition and inflammatory state of the plaque determine its stability and, therefore, the risk of clinical events. [(18)F]-2-fluoro-2-deoxy-D-glucose (FDG) imaging using positron-emission tomography (PET)/computed tomography (CT) has been extensively studied in oncologic metabolism. Studies using animal models and immunohistochemistry in humans show that FDG-PET/CT is exquisitely sensitive for detecting macrophage activity, an important source of cellular inflammation in vessel walls. More recently, we and others have shown that FDG-PET/CT enables highly precise, novel measurements of inflammatory activity of activity of atherosclerotic plaques in large and medium-sized arteries. FDG-PET/CT studies have many advantages over other imaging modalities: 1) high contrast resolution; 2) quantification of plaque volume and metabolic activity allowing for multi-modal atherosclerotic plaque quantification; 3) dynamic, real-time, in vivo imaging; 4) minimal operator dependence. Finally, vascular inflammation detected by FDG-PET/CT has been shown to predict cardiovascular (CV) events independent of traditional risk factors and is also highly associated with overall burden of atherosclerosis. Plaque activity by FDG-PET/CT is modulated by known beneficial CV interventions such as short term (12 week) statin therapy as well as longer term therapeutic lifestyle changes (16 months). The current methodology for quantification of FDG uptake in atherosclerotic plaque involves measurement of the standardized uptake value (SUV) of an artery of interest and of the venous blood pool in order to calculate a target to background ratio (TBR), which is calculated by dividing the arterial SUV by the venous blood pool SUV. This method has shown to represent a stable, reproducible phenotype over time, has a high sensitivity for detection of vascular inflammation, and also has high inter-and intra-reader reliability. Here we present our methodology for patient preparation, image acquisition, and quantification of atherosclerotic plaque activity and vascular inflammation using SUV, TBR, and a global parameter called the metabolic volumetric product (MVP). These approaches may be applied to assess vascular inflammation in various study samples of interest in a consistent fashion as we have shown in several prior publications.     

Elucidating the exact role of engineered CRABPII residues for the formation of a retinal protonated Schiff base

Cellular Retinoic Acid Binding Protein II (CRABPII) has been reengineered to specifically bind and react with all‐trans‐retinal to form a protonated Schiff base. Each step of this process has been dissected and four residues (Lys132, Tyr134, Arg111, and Glu121) within the CRABPII binding site have been identified as crucial for imine formation and/or protonation. The precise role of each residue has been examined through site directed mutagenesis and crystallographic studies. The crystal structure of the R132K:L121E‐CRABPII (PDB‐3I17) double mutant suggests a direct interaction between engineered Glu121 and the native Arg111, which is critical for both Schiff base formation and protonation. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Estimation of anisotropy coefficient of swine pancreas,liver and muscle at 1064 nm based on goniometric technique

Optical properties of tissues are required for theoretical modeling of Laser Ablation in tumor therapy. The light scattering characteristic of tissues is described by the anisotropy coefficient, g. The relationship between the angular distribution of scattered light and g is given by the Henyey‐Greenstein (HG) phase function. This work describes the estimation of anisotropy coefficients of ex vivo swine pancreas, liver and muscle at 1064 nm. The intensities of scattered light at fixed angles were measured under repeatability conditions. Experimental data were fitted with a two‐term HG, estimating the anisotropy coefficients for the forward (e.g., 0.956 for pancreas, 0.964 for liver and 0.968 for muscle) and the backward (e.g., –0.481 for pancreas, –0.414 for liver and –0.372 for muscle) scattering.

Experimental set up employed to estimate the anisotropy coefficient of biological tissues. The image on the left depicts the holder used to house tissue, laser fiber and photodetector; on the left an example of scattered light beam is shown, as well as the effect due to Snell's law.     

Protein secondary structure prediction using NMR chemical shift data

Accurate determination of protein secondary structure from the chemical shift information is a key step for NMR tertiary structure determination. Relatively few work has been done on this subject. There needs to be a systematic investigation of algorithms that are (a) robust for large datasets; (b) easily extendable to (the dynamic) new databases; and (c) approaching to the limit of accuracy. We introduce new approaches using k-nearest neighbor algorithm to do the basic prediction and use the BCJR algorithm to smooth the predictions and combine different predictions from chemical shifts and based on sequence information only. Our new system, SUCCES, improves the accuracy of all existing methods on a large dataset of 805 proteins (at 86% Q(3) accuracy and at 92.6% accuracy when the boundary residues are ignored), and it is easily extendable to any new dataset without requiring any new training. The software is publicly available at http://monod.uwaterloo.ca/nmr/succes.     

The dynamic nature of contact networks in infectious disease epidemiology

Although contact network models have yielded important insights into infectious disease transmission and control throughout the last decade, researchers have just begun to explore the dynamic nature of contact patterns and their epidemiological significance. Most network models have assumed that contacts are static through time. Developing more realistic models of the social interactions that underlie the spread of infectious diseases thus remains an important challenge for both data gatherers and modelers. In this article, we review some recent data-driven and process-driven approaches that capture the dynamics of human contact, and discuss future challenges for the field.     

Features analysis for identification of date and party hubs in protein interaction network of <Emphasis Type="Italic">Saccharomyces Cerevisiae</Emphasis>

Background  

It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae 's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes.     

Advanced therapeutic modalities in hepatocellular carcinoma: Novel insights

Hepatocellular carcinoma (HCC), the most common type of liver cancer, is usually a latent and asymptomatic malignancy caused by different aetiologies, which is a result of various aberrant molecular heterogeneity and often diagnosed at advanced stages. The incidence and prevalence have significantly increased because of sedentary lifestyle, diabetes, chronic infection with hepatotropic viruses and exposure to aflatoxins. Due to advanced intra- or extrahepatic metastasis, recurrence is very common even after radical resection. In this paper, we highlighted novel therapeutic modalities, such as molecular-targeted therapies, targeted radionuclide therapies and epigenetic modification-based therapies. These topics are trending headlines and their combination with cell-based immunotherapies, and gene therapy has provided promising prospects for the future of HCC treatment. Moreover, a comprehensive overview of current and advanced therapeutic approaches is discussed and the advantages and limitations of each strategy are described. Finally, very recent and approved novel combined therapies and their promising results in HCC treatment have been introduced.