Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation

Gene expression is controlled primarily by interactions between transcription factor proteins (TFs) and the regulatory DNA sequence, a process that can be captured well by thermodynamic models of regulation. These models, however, neglect regulatory crosstalk: the possibility that non-cognate TFs could initiate transcription, with potentially disastrous effects for the cell. Here we estimate the importance of crosstalk, suggest that its avoidance strongly constrains equilibrium models of TF binding, and propose an alternative non-equilibrium scheme that implements kinetic proofreading to suppress erroneous initiation. This proposal is consistent with the observed covalent modifications of the transcriptional apparatus and would predict increased noise in gene expression as a tradeoff for improved specificity. Using information theory, we quantify this tradeoff to find when optimal proofreading architectures are favored over their equilibrium counterparts.Comment: 5 pages, 3 figure

Feature Selection and Improving Classification Performance for Malware Detection

The ubiquitous advance of technology has been conducive to the proliferation of cyber threats, resulting in attacks that have grown exponentially. Consequently, researchers have developed models based on machine learning algorithms for detecting malware. However, these methods require significant amount of extracted features for correct malware classification, making that feature extraction, training, and testing take significant time; even more, it has been unexplored which are the most important features for accomplish the correct classification. In this Thesis, it is created and analyzed a dataset of malware and clean files (goodware) from the static and dynamic features provided by the online framework VirusTotal. The purpose was to select the smallest number of features that keep the classification accuracy as high as the state of the art researches. Selecting the most representative features for malware detection relies on the possibility reducing the training time, given that it increases in O(n2) with respect to the number of features, and creating an embedded program that monitors processes executed by the OS. Thus, feature selection was made taking the most important features. In addition, classification algorithms such as Random Forest, Support Vector Machine and Neural Networks were used in a novel combination that not only showed an increase in accuracy, but also in the training speed from hours to just minutes. Next, the model was tested on one additional dataset of unseen malware files. Results showed that “9” features were enough to distinguish malware from goodware files within an accuracy of 99.60%

Una mirada geométrica a la transformación de Box-Cox

En el análisis de los datos, cuando la normalidad no es un supuesto viable, una alternativa es ignorar los resultados del chequeo de normalidad y proceder como si los datos estuvieran normalmente distribuidos. Este procedimiento no es recomendable puesto que, en la mayoría de los casos, lleva a conclusiones incorrectas. Una segunda alternativa consiste en convertir los datos no normales en unos que tengan más apariencia de normales considerando transformaciones de los datos. Estas transformaciones son simplemente reexpresiones de los datos en diferentes unidades, frecuentemente sucede que las nuevas unidades proporcionan expresiones más naturales a las características que se están estudiando. Para datos normalmente distribuidos, las transformaciones lineales de los datos son comúnmente usadas para crear una variable con distribución normal estándar

Bulk power system availability assessment with multiple wind power plants

The use of renewable non-conventional energy sources, as wind electric power energy and photovoltaic solar energy, has introduced uncertainties in the performance of bulk power systems. The power system availability has been employed as a useful tool for planning power systems; however, traditional methodologies model generation units as a component with two states: in service or out of service. Nevertheless, this model is not useful to model wind power plants for availability assessment of the power system. This paper used a statistical representation to model the uncertainty of power injection of wind power plants based on the central moments: mean value, variance, skewness and kurtosis. In addition, this paper proposed an availability assessment methodology based on application of this statistical model, and based on the 2m+1 point estimate method the availability assessment is performed. The methodology was tested on the IEEE-RTS assuming the connection of two wind power plants and different correlation among the behavior of these plants

Analysis of the MMP-dependent and independent functions of tissue inhibitor of metalloproteinase-2 on the invasiveness of breast cancer cells

Matrix metalloproteinases (MMPs) are secreted endopeptidases that play an essential role in remodeling the extracellular matrix (ECM). MMPs are primarily active during development, when the majority of ECM remodeling events occurs. In adults, elevated MMP activity has been observed in many pathological conditions such as cancer and osteoarthritis. The proteolytic activity of MMPs is controlled by their natural inhibitors - the tissue inhibitor of metalloproteinases (TIMPs). In addition to blocking MMP-mediated proteolysis, TIMPs have a number of MMP-independent functions including binding to cell surface proteins thereby stimulating signaling cascades. TIMP-2, the most studied member of the family, can both inhibit and activate MMPs directly, as well as inhibit MMP activity indirectly by upregulating expression of RECK, a membrane anchored MMP regulator. While TIMP-2 has been shown to play important roles in breast cancer, we describe how the MMP-independent effects of TIMP-2 can modulate the invasiveness of MCF-7, T47D and MDA-MB-231 breast cancer cells. Using an ALA + TIMP-2 mutant which is devoid of MMP inhibition, but still capable of initiating specific cell signaling cascades, we show that TIMP-2 can differentially affect MMP activity and cellular invasiveness in both an MMP dependent and independent manner. More specifically, MMP activity and invasiveness is increased with the addition of exogenous TIMP-2 in poorly invasive cell lines whereas it is decreased in highly invasive cells lines (MDA-MB-231). Conversely, the addition of ALA + TIMP-2 resulted in decreased invasiveness regardless of cell line. © The International CCN Society 2012

Invariants sets for a class of discrete-time lur'e Systems

16th IFAC World Congress. 03/07/2005. Praga (República Checa)We present a method to estimate the domain of attraction of a class of discrete-time Lur'e systems. A new notion of LNL-invariance, stronger than the traditional invariance concept, is introduced. An algorithm to determinate the largest LNL-invariant set for this class of systems is proposed. Moreover, it is proven that the LNL-invariant sets provided by this algorithm are polyhedral convex sets and constitute an estimation of the domain of attraction of the non-linear system

Colitis linfoplasmocitaria canina : un hallazgo frecuente en la exploración colonoscópica

En este trabajo se describen los hallazgos clínicos, laboratoriales y colonoscópicos de la colitis linfoplasmocitaria canina, aparte de tratar los aspectos más relevantes sobre su etiopatogenia y diagnóstico, para describir finalmente las pautas de tratamiento del proceso

Functional characterization of tissue inhibitor of metalloproteinase-1 (TIMP-1) N- and C-terminal domains during xenopus laevis development

Extracellular matrix (ECM) remodeling is essential for facilitating developmental processes. ECM remodeling, accomplished by matrix metalloproteinases (MMPs), is regulated by endogenous tissue inhibitors of metalloproteinases (TIMPs). While the TIMP N-terminal domain is involved in inhibition of MMP activity, the C-terminal domain exhibits cell-signaling activity, which is TIMP and cell type dependent. We have previously examined the distinct roles of the Xenopus laevis TIMP-2 and -3 C-terminal domains during development and here examined the unique roles of TIMP-1 N- and C-terminal domains in early X. laevis embryos. mRNA microinjection was used to overexpress full-length TIMP-1 or its individual N- or C-terminal domains in embryos. Full-length and C-terminal TIMP-1 resulted in increased lethality compared to N-terminal TIMP-1. Overexpression of C-terminal TIMP-1 resulted in significant decreases in mRNA levels of proteolytic genes including TIMP-2, RECK, MMP-2, and MMP-9, corresponding to decreases in MMP-2 and -9 protein levels, as well as decreased MMP-2 and MMP-9 activities. These trends were not observed with the N-terminus. Our research suggests that the individual domains of TIMP-1 are capable of playing distinct roles in regulating the ECM proteolytic network during development and that the unique functions of these domains are moderated in the endogenous full-length TIMP-1 molecule. © 2014 M. A. Nieuwesteeg et al