Synthesis, Purification and Pharacterization of Small Mono(ADP-Ribosyl)ated Molecules in the ADP-Ribose Elongation Reaction Catalyzed by Poly(ADP-ribose)Polymerase

The ADP-ribose elongation catalyzed by poly(ADP-ribose) polymerase (PARP) [EC 2.2.2.30] has been partially characterized utilizing mono (ADP-ribosyl)ated polyamines. Arginine methyl ester (AME)-(ADP-ribose) and agmatine (AGMT)-(ADP-ribose) were synthesized enzymatically with a eukarytic mono(ADP-ribosyl) transferase and cholera toxin, respectively

Detección de outliers aplicando algoritmo de optimización basado en el apareo de abejas

Este trabajo tiene el objetivo de sumar una propuesta para la detección de casos atípicos. Es decir, detectar datos pertenecientes a una muestra que posean valores extremos que los diferencia del resto y permitan al investigador sospechar acerca del origen de los mismos. En cuanto a la metodología utilizada en este trabajo, se ha optado por un método heurístico, ya que se pretende alcanzar el objetivo antes señalado a través del estudio teórico y empírico recogido de la literatura sobre algoritmos heurísticos. En esta propuesta presentamos una heurística conocido como Algoritmo de Optimización basado en el Apareo de Abejas, con el propósito de encontrar soluciones factibles eficazmente. Los resultados experimentales sobre distintos datasets de la literatura, demuestran la calidad de nuestro algoritmo comparado con el algoritmo heurístico basado en búsqueda local (LSA) de Zengyou HeThis work has the objective of adding a proposition for the detection of outliers. That is to say, to detect data belonging to a sample that possess extreme values that the difference of the rest and allow the investigator to suspect about the origin of the same ones. As for the methodology used in this work, it has been opted by a heuristic method, since it is sought to reach the objective before signal through the picked up theoretical and empiric study of the literature it has more than enough heuristic algorithms. In this proposal we present a heuristic one well-known as Honey Bee Mating Optimization Algorithm, with the purpose of finding feasible solutions efficiently. The experimental results on different datasets of the literature, demonstrate the quality of our algorithm compared with the heuristic algorithm based on local search (LSA) of Zengyou HePresentado en el Congreso GeneralRed de Universidades con Carreras en Informática (RedUNCI

Detección de outliers aplicando algoritmo de optimización basado en el apareo de abejas

Este trabajo tiene el objetivo de sumar una propuesta para la detección de casos atípicos. Es decir, detectar datos pertenecientes a una muestra que posean valores extremos que los diferencia del resto y permitan al investigador sospechar acerca del origen de los mismos. En cuanto a la metodología utilizada en este trabajo, se ha optado por un método heurístico, ya que se pretende alcanzar el objetivo antes señalado a través del estudio teórico y empírico recogido de la literatura sobre algoritmos heurísticos. En esta propuesta presentamos una heurística conocido como Algoritmo de Optimización basado en el Apareo de Abejas, con el propósito de encontrar soluciones factibles eficazmente. Los resultados experimentales sobre distintos datasets de la literatura, demuestran la calidad de nuestro algoritmo comparado con el algoritmo heurístico basado en búsqueda local (LSA) de Zengyou HeThis work has the objective of adding a proposition for the detection of outliers. That is to say, to detect data belonging to a sample that possess extreme values that the difference of the rest and allow the investigator to suspect about the origin of the same ones. As for the methodology used in this work, it has been opted by a heuristic method, since it is sought to reach the objective before signal through the picked up theoretical and empiric study of the literature it has more than enough heuristic algorithms. In this proposal we present a heuristic one well-known as Honey Bee Mating Optimization Algorithm, with the purpose of finding feasible solutions efficiently. The experimental results on different datasets of the literature, demonstrate the quality of our algorithm compared with the heuristic algorithm based on local search (LSA) of Zengyou HePresentado en el Congreso GeneralRed de Universidades con Carreras en Informática (RedUNCI

MCP-1 overexpressed in tuberous sclerosis lesions acts as a paracrine factor for tumor development

Patients with tuberous sclerosis complex (TSC) develop hamartomatous tumors showing loss of function of the tumor suppressor TSC1 (hamartin) or TSC2 (tuberin) and increased angiogenesis, fibrosis, and abundant mononuclear phagocytes. To identify soluble factors with potential roles in TSC tumorigenesis, we screened TSC skin tumor–derived cells for altered gene and protein expression. Fibroblast-like cells from 10 angiofibromas and five periungual fibromas produced higher levels of monocyte chemoattractant protein-1 (MCP-1) mRNA and protein than did fibroblasts from the same patient's normal skin. Conditioned medium from angiofibroma cells stimulated chemotaxis of a human monocytic cell line to a greater extent than conditioned medium from TSC fibroblasts, an effect blocked by neutralizing MCP-1–specific antibody. Overexpression of MCP-1 seems to be caused by loss of tuberin function because Eker rat embryonic fibroblasts null for Tsc2 (EEF Tsc2 (−/−)) produced 28 times as much MCP-1 protein as did EEF Tsc2 (+/+) cells; transient expression of WT but not mutant human TSC2 by EEF Tsc2 (−/−) cells inhibited MCP-1 production; and pharmacological inhibition of the Rheb-mTOR pathway, which is hyperactivated after loss of TSC2, decreased MCP-1 production by EEF Tsc2 (−/−) cells. Together these findings suggest that MCP-1 is an important paracrine factor for TSC tumorigenesis and may be a new therapeutic target

Osteoprotegerin Contributes to the Metastatic Potential of Cells with a Dysfunctional TSC2 Tumor-Suppressor Gene

In addition to its effects on bone metabolism, osteoprotegerin (OPG), a soluble member of the tumor necrosis factor family of receptors, promotes smooth muscle cell proliferation and migration and may act as a survival factor for tumor cells. We hypothesized that these cellular mechanisms of OPG may be involved in the growth and proliferation of lymphangioleiomyomatosis (LAM) cells, abnormal smooth muscle-like cells with mutations in one of the tuberous sclerosis complex tumor-suppressor genes (TSC1/TSC2) that cause LAM, a multisystem disease characterized by cystic lung destruction, lymphatic infiltration, and abdominal tumors. Herein, we show that OPG stimulated proliferation of cells cultured from explanted LAM lungs, and selectively induced migration of LAM cells identified by the loss of heterozygosity for TSC2. Consistent with these observations, cells with TSC2 loss of heterozygosity expressed the OPG receptors, receptor activator of NF-κB ligand, syndecan-1, and syndecan-2. LAM lung nodules showed reactivities to antibodies to tumor necrosis factor–related apoptosis-inducing ligand, receptor activator of NF-κB ligand, syndecan-1, and syndecan-2. LAM lung nodules also produced OPG, as shown by expression of OPG mRNA and colocalization of reactivities to anti-OPG and anti-gp100 (HMB45) antibodies in LAM lung nodules. Serum OPG was significantly higher in LAM patients than in normal volunteers. Based on these data, it appears that OPG may have tumor-promoting roles in the pathogenesis of lymphangioleiomyomatosis, perhaps acting as both autocrine and paracrine factors

When the optimal is not the best: parameter estimation in complex biological models

Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system, and point to the need of a theory that addresses this problem more generally

Integrated analysis of microRNA regulation and its interaction with mechanisms of epigenetic regulation in the etiology of systemic lupus erythematosus

The aim of this study was to identity in silico the relationships among microRNAs (miRNAs) and genes encoding transcription factors, ubiquitylation, DNA methylation, and histone modifications in systemic lupus erythematosus (SLE). To identify miRNA dysregulation in SLE, we used miR2Disease and PhenomiR for information about miRNAs exhibiting differential regulation in disease and other biological processes, and HMDD for information about experimentally supported human miRNA-disease association data from genetics, epigenetics, circulating miRNAs, and miRNA-target interactions. This information was incorporated into the miRNA analysis. High-throughput sequencing revealed circulating miRNAs associated with kidney damage in patients with SLE. As the main finding of our in silico analysis of miRNAs differentially expressed in SLE and their interactions with disease-susceptibility genes, post-translational modifications, and transcription factors; we highlight 226 miRNAs associated with genes and processes. Moreover, we highlight that alterations of miRNAs such as hsa-miR-30a-5p, hsa-miR-16-5p, hsa-miR-142-5p, and hsa-miR-324-3p are most commonly associated with post-translational modifications. In addition, altered miRNAs that are most frequently associated with susceptibility-related genes are hsa-miR-16-5p, hsa-miR-374a-5p, hsa-miR-34a-5p, hsa-miR-31-5p, and hsa-miR-1-3p

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO