Detecting the signature of natural selection with microsatellites

Natural selection is one of the major factors in the evolution of all organisms. Detecting the signature of natural selection has been a central theme in evolutionary genetics. With the availability of microsatellite data, it is of interest to study how natural selection can be detected with microsatellites. ^ The overall aim of this research is to detect signatures of natural selection with data on genetic variation at microsatellite loci. The null hypothesis to be tested is the neutral mutation theory of molecular evolution, which states that different alleles at a locus have equivalent effects on fitness. Currently used tests of this hypothesis based on data on genetic polymorphism in natural populations presume that mutations at the loci follow the infinite allele/site models (IAM, ISM), in the sense that at each site at most only one mutation event is recorded, and each mutation leads to an allele not seen before in the population. Microsatellite loci, which are abundant in the genome, do not obey these mutation models, since the new alleles at such loci can be created either by contraction or expansion of tandem repeat sizes of core motifs. Since the current genome map is mainly composed of microsatellite loci and this class of loci is still most commonly studied in the context of human genome diversity, this research explores how the current test procedures for testing the neutral mutation hypothesis should be modified to take into account a generalized model of forward-backward stepwise mutations. In addition, recent literature also suggested that past demographic history of populations, presence of population substructure, and varying rates of mutations across loci all have confounding effects for detecting signatures of natural selection. ^ The effects of the stepwise mutation model and other confounding factors on detecting signature of natural selection are the main results of the research. ^

ROLE OF MIR-19A RELEASED BY INFLAMMATORY BREAST CANCER CELLS IN THE REGULATION OF DENDRITIC CELL FUNCTIONS: IN VITRO MODEL OF CROSSTALK IN THE TUMOR MICROENVIRONMENT OF INFLAMMATORY BREAST CANCER

Inflammatory breast cancer (IBC) is a rare but very aggressive form of locally advanced breast cancer (1-6% of total breast cancer patients in United States), with a 5-year overall survival rate of only 40.5%, compared with 85% of the non-IBC patients. So far, a unique molecular signature for IBC able to explain the dramatic differences in the tumor biology between IBC and non-IBC has not been identified. As immune cells in the tumor microenvironment plays an important role in regulating tumor progression, we hypothesized that tumor-associated dendritic cells (TADC) may be responsible for regulating the development of the aggressive characteristics of IBC. MiRNAs can be released into the extracellular space and mediate the intercellular communication by regulating target gene expression beyond their cells of origin. We hypothesized that miRNAs released by IBC cells can induce an increased activation status, secretion of pro-inflammatory cytokines and migration ability of TADC. In an in vitro model of IBC tumor microenvironment, we found that the co-cultured of the IBC cell line SUM-149 with immature dendritic cells (iDCSUM-149) induced a higher degree of activation and maturation of iDCSUM-149 upon stimulation with lipopolysaccharide (LPS) compared with iDCs co-cultured with the non-IBC cell line SUM-159 (iDCSUM-159), resulting in: increased expression of the costimulatory and activation markers; higher production of pro-inflammatory cytokines (TNF-a, IL-6); and 3) higher migratory ability. These differences were due to the exosome-mediated transfer of miR-19a and miR-146a from SUM-149 and SUM-159, respectively, to iDCs, causing the downregulation of the miR-19a target genes PTEN, SOCS-1 and the miR-146a target genes IRAK1, TRAF6. PTEN, SOCS-1 and IRAK1, TRAF6 are important negative and positive regulator of cytokine- and TLR-mediated activation/maturation signaling pathway in DCs. Increased levels of IL-6 induced the upregulation of miR-19a synthesis in SUM-149 cells that was associated with the induction of CD44+CD24-ALDH1+ cancer stem cells (CSCs) with epithelial-to-mesenchymal transition (EMT) characteristics. In conclusion, in IBC tumor microenvironment IL-6/miR-19a axis can represent a self-sustaining loop able to maintain a pro-inflammatory status of DCs, leading to the development of tumor cells with high metastatic potential (EMT CSCs) responsible of the poor prognosis in IBC patients.

Instability and topology bifurcations on a hemisphere-cylinder at high angle of attack

La configuración de un cilindro acoplado a una semi-esfera, conocida como ’hemispherecylinder’, se considera como un modelo simplificado para numerosas aplicaciones industriales tales como fuselaje de aviones o submarinos. Por tanto, el estudio y entendimiento de los fenómenos fluidos que ocurren alrededor de dicha geometría presenta gran interés. En esta tesis se muestra la investigación del origen y evolución de los, ya conocidos, patrones de flujo (burbuja de separación, vórtices ’horn’ y vórtices ’leeward’) que se dan en esta geometría bajo condiciones de flujo separado. Para ello se han llevado a cabo simulaciones numéricas (DNS) y ensayos experimentales usando la técnica de Particle Image Velocimetry (PIV), para una variedad de números de Reynolds (Re) y ángulos de ataque (AoA). Se ha aplicado sobre los resultados numéricos la teoría de puntos críticos obteniendo, por primera vez para esta geometría, un diagrama de bifurcaciones que clasifica los diferentes regímenes topológicos en función del número de Reynolds y del ángulo de ataque. Se ha llevado a cabo una caracterización completa sobre el origen y la evolución de los patrones estructurales característicos del cuerpo estudiado. Puntos críticos de superficie y líneas de corriente tridimensionales han ayudado a describir el origen y la evolución de las principales estructuras presentes en el flujo hasta alcanzar un estado de estabilidad desde el punto de vista topológico. Este estado se asocia con el patrón de los vórtices ’horn’, definido por una topología característica que se encuentra en un rango de números de Reynolds muy amplio y en regímenes compresibles e incompresibles. Por otro lado, con el objeto de determinar las estructuras presentes en el flujo y sus frecuencias asociadas, se han usado distintas técnicas de análisis: Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD) y análisis de Fourier. Dichas técnicas se han aplicado sobre los datos experimentales y numéricos, demostrándose la buena concordancia entre ambos resultados. Finalmente, se ha encontrado en ambos casos, una frecuencia dominante asociada con una inestabilidad de los vórtices ’leeward’. ABSTRACT The hemisphere-cylinder may be considered as a simplified model for several geometries found in industrial applications such as aircrafts’ fuselages or submarines. Understanding the complex flow phenomena that surrounds this particular geometry is therefore of major industrial interest. This thesis presents an investigation of the origin and evolution of the complex flow pattern; i.e. separation bubbles, horn vortices and leeward vortices, around the hemisphere-cylinder under separated flow conditions. To this aim, threedimensional Direct Numerical Simulations (DNS) and experimental tests, using Particle Image Velocimetry (PIV) techniques, have been performed for a variety of Reynolds numbers (Re) and angles of attack (AoA). Critical point theory has been applied to the numerical simulations to provide, for the first time for this geometry, a bifurcation diagram that classifies the different flow topology regimes as a function of the Reynolds number and the angle of attack. A complete characterization about the origin and evolution of the complex structural patterns of this geometry has been put in evidence. Surface critical points and surface and volume streamlines were able to describe the main flow structures and their strong dependence with the flow conditions up to reach the structurally stable state. This state was associated with the pattern of the horn vortices, found on ranges from low to high Reynolds numbers and from incompressible to compressible regimes. In addition, different structural analysis techniques have been employed: Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD) and Fourier analysis. These techniques have been applied to the experimental and numerical data to extract flow structure information (i.e. modes and frequencies). Experimental and numerical modes are shown to be in good agreement. A dominant frequency associated with an instability of the leeward vortices has been identified in both, experimental and numerical results.

A signature of the T → R transition in human hemoglobin

Allosteric effects in hemoglobin arise from the equilibrium between at least two energetic states of the molecule: a tense state, T, and a relaxed state, R. The two states differ from each other in the number and energy of the interactions between hemoglobin subunits. In the T state, constraints between subunits oppose the structural changes resulting from ligand binding. In the R state, these constraints are released, thus enhancing ligand-binding affinity. In the present work, we report the presence of four sites in hemoglobin that are structurally stabilized in the R relative to the T state. These sites are Hisα103(G10) and Hisα122(H5) in each α subunit of hemoglobin. They are located at the α1β1 and α2β2 interfaces of the hemoglobin tetramer, where the histidine side chains form hydrogen bonds with specific residues from the β chains. We have measured the solvent exchange rates of side chain protons of Hisα103(G10) and Hisα122(H5) in both deoxygenated and ligated hemoglobin by NMR spectroscopy. The exchange rates were found to be higher in the deoxygenated-T than in ligated-R state. Analysis of exchange rates in terms of the local unfolding model revealed that the structural stabilization free energy at each of these two histidines is larger by ≈1.5 kcal/(mol tetramer) in the R relative to the T state. The location of these histidines at the intradimeric α1β1 and α2β2 interfaces also suggests a role for these interfaces in the allosteric equilibrium of hemoglobin.

Light-generated nuclear quantum beats: a signature of photosynthesis.

Light-induced radical pairs in deuterated and deuterated plus 15N-substituted Synechococcus lividus cyanobacteria have been studied by transient EPR following pulsed laser excitation. Nuclear quantum beats are observed in the transverse electron magnetization at lower temperatures. Model calculations for the time profiles, evaluated at the high-field emissive maximum of the spectrum, indicate assignment of these coherences to nitrogen nuclei in the primary donor. Thorough investigation of the nuclear modulation patterns can provide detailed information on the electronic structure of the primary donor, providing insight into the mechanism of the primary events of plant photosynthesis.

Off-line signature verification and forgery detection using fuzzy modeling

Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Template model for blur coding: the role of early nonlinearity in edge segmentation

We describe a template model for perception of edge blur and identify a crucial early nonlinearity in this process. The main principle is to spatially filter the edge image to produce a 'signature', and then find which of a set of templates best fits that signature. Psychophysical blur-matching data strongly support the use of a second-derivative signature, coupled to Gaussian first-derivative templates. The spatial scale of the best-fitting template signals the edge blur. This model predicts blur-matching data accurately for a wide variety of Gaussian and non-Gaussian edges, but it suffers a bias when edges of opposite sign come close together in sine-wave gratings and other periodic images. This anomaly suggests a second general principle: the region of an image that 'belongs' to a given edge should have a consistent sign or direction of luminance gradient. Segmentation of the gradient profile into regions of common sign is achieved by implementing the second-derivative 'signature' operator as two first-derivative operators separated by a half-wave rectifier. This multiscale system of nonlinear filters predicts perceived blur accurately for periodic and aperiodic waveforms. We also outline its extension to 2-D images and infer the 2-D shape of the receptive fields.

Government preparedness:using simulation to prepare for a terrorist attack

The heightened threat of terrorism has caused governments worldwide to plan for responding to large-scale catastrophic incidents. In England the New Dimension Programme supplies equipment, procedures and training to the Fire and Rescue Service to ensure the country's preparedness to respond to a range of major critical incidents. The Fire and Rescue Service is involved partly by virtue of being able to very quickly mobilize a large skilled workforce and specialist equipment. This paper discusses the use of discrete event simulation modeling to understand how a fire and rescue service might position its resources before an incident takes place, to best respond to a combination of different incidents at different locations if they happen. Two models are built for this purpose. The first model deals with mass decontamination of a population following a release of a hazardous substance—aiming to study resource requirements (vehicles, equipment and manpower) necessary to meet performance targets. The second model deals with the allocation of resources across regions—aiming to study cover level and response times, analyzing different allocations of resources, both centralized and decentralized. Contributions to theory and practice in other contexts (e.g. the aftermath of natural disasters such as earthquakes) are outlined.

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.

Attack simulation based software protection assessment method

Software protection is an essential aspect of information security to withstand malicious activities on software, and preserving software assets. However, software developers still lacks a methodology for the assessment of the deployed protections. To solve these issues, we present a novel attack simulation based software protection assessment method to assess and compare various protection solutions. Our solution relies on Petri Nets to specify and visualize attack models, and we developed a Monte Carlo based approach to simulate attacking processes and to deal with uncertainty. Then, based on this simulation and estimation, a novel protection comparison model is proposed to compare different protection solutions. Lastly, our attack simulation based software protection assessment method is presented. We illustrate our method by means of a software protection assessment process to demonstrate that our approach can provide a suitable software protection assessment for developers and software companies.

Development of a model to predict the life of pneumatic conveyor bends subject to erosive wear

The erosion processes resulting from flow of fluids (gas-solid or liquid-solid) are encountered in nature and many industrial processes. The common feature of these erosion processes is the interaction of the fluid (particle) with its boundary thus resulting in the loss of material from the surface. This type of erosion in detrimental to the equipment used in pneumatic conveying systems. The puncture of pneumatic conveyor bends in industry causes several problems. Some of which are: (1) Escape of the conveyed product causing health and dust hazard; (2) Repairing and cleaning up after punctures necessitates shutting down conveyors, which will affect the operation of the plant, thus reducing profitability. The most common occurrence of process failure in pneumatic conveying systems is when pipe sections at the bends wear away and puncture. The reason for this is particles of varying speed, shape, size and material properties strike the bend wall with greater intensity than in straight sections of the pipe. Currently available models for predicting the lifetime of bends are inaccurate (over predict by 80%. The provision of an accurate predictive method would lead to improvements in the structure of the planned maintenance programmes of processes, thus reducing unplanned shutdowns and ultimately the downtime costs associated with these unplanned shutdowns. This is the main motivation behind the current research. The paper reports on two aspects of the first phases of the study-undertaken for the current project. These are (1) Development and implementation; and (2) Testing of the modelling environment. The model framework encompasses Computational Fluid Dynamics (CFD) related engineering tools, based on Eulerian (gas) and Lagrangian (particle) approaches to represent the two distinct conveyed phases, to predict the lifetime of conveyor bends. The method attempts to account for the effect of erosion on the pipe wall via particle impacts, taking into account the angle of attack, impact velocity, shape/size and material properties of the wall and conveyed material, within a CFD framework. Only a handful of researchers use CFD as the basis of predicting the particle motion, see for example [1-4] . It is hoped that this would lead to more realistic predictions of the wear profile. Results, for two, three-dimensional test cases using the commercially available CFD PHOENICS are presented. These are reported in relation to the impact intensity and sensitivity to the inlet particle distributions.

Analysis of Automotive Cybersecurity - Attack surfaces and users’ privacy concerns

Modern automobiles are no longer just mechanical tools. The electronics and computing services they are shipping with are making them not less than a computer. They are massive kinetic devices with sophisticated computing power. Most of the modern vehicles are made with the added connectivity in mind which may be vulnerable to outside attack. Researchers have shown that it is possible to infiltrate into a vehicle’s internal system remotely and control the physical entities such as steering and brakes. It is quite possible to experience such attacks on a moving vehicle and unable to use the controls. These massive connected computers can be life threatening as they are related to everyday lifestyle. First part of this research studied the attack surfaces in the automotive cybersecurity domain. It also illustrated the attack methods and capabilities of the damages. Online survey has been deployed as data collection tool to learn about the consumers’ usage of such vulnerable automotive services. The second part of the research portrayed the consumers’ privacy in automotive world. It has been found that almost hundred percent of modern vehicles has the capabilities to send vehicle diagnostic data as well as user generated data to their manufacturers, and almost thirty five percent automotive companies are collecting them already. Internet privacy has been studies before in many related domain but no privacy scale were matched for automotive consumers. It created the research gap and motivation for this thesis. A study has been performed to use well established consumers privacy scale – IUIPC to match with the automotive consumers’ privacy situation. Hypotheses were developed based on the IUIPC model for internet consumers’ privacy and they were studied by the finding from the data collection methods. Based on the key findings of the research, all the hypotheses were accepted and hence it is found that automotive consumers’ privacy did follow the IUIPC model under certain conditions. It is also found that a majority of automotive consumers use the services and devices that are vulnerable and prone to cyber-attacks. It is also established that there is a market for automotive cybersecurity services and consumers are willing to pay certain fees to avail that.