Leptin Induces Proliferation and Notch Expression In Pancreatic Cancer

Pancreatic adenocarcinoma (PA) is an aggressive cancer. It develops in a way that causes almost no detectable symptoms, which leads to a rapid progression and a short survival rate. Researchers have discovered a link between pancreatic cancer (and other cancer types) and obesity. High levels of leptin, an appetite hormone secreted by adipocytes, have been found in obese people. Studies have shown that the absence of leptin in the body or severe leptin resistance can lead to uncontrolled eating and weight gain, hence, its connection to obesity. Consequently, our lab is analyzing the relationship between obesity and leptin and what effects they have on pancreatic cancer progression. We hypothesize that in PA cells, leptin induces proliferation, tumorigenesis, and increased levels of Notch and related molecules. These effects are reversed by our leptin antagonist linked to iron nanoparticles, IONP-LPrA2 (iron oxidized nanoparticles leptin peptide receptor antagonist). We’re mainly focused on 4 cell lines: Panc-1, MiaPaCa-2, and BxPc3 (derived from primary tumors) and AsPc-1 (from a metastatic tumor). Of the primary tumors, Panc-1 and MiaPaCa-2 are more aggressive and BxPc-3 is less aggressive. We expect results validating that leptin will induce proliferation (in Panc-1 and AsPc-1cells by MTT assay), expression of Notch and other molecules (in BxPc3 and MiaPaCa-2 cells by flow cytometry and Western Blot), and tumorsphere formation (in Panc-1). Leptin may also induce Notch expression in Panc-1 tumorspheres. In conclusion, this project will demonstrate the involvement of leptin in PA progression. Leptin\u27s effects will be abrogated by the inhibitor of leptin signaling, IONP-LPrA2

Stereo visual odometry by combining points and lines

Poster presented at ICVSS2016: international Computer Vision Summer SchoolMost approaches to stereo visual odometry reconstruct the motion based on the tracking of point features along a sequence of images. However, in low-textured scenes it is often difficult to encounter a large set of point features, or it may happen that they are not well distributed over the image, so that the behavior of these algorithms deteriorates. This paper proposes a probabilistic approach to stereo visual odometry based on the combination of both point and line segment that works robustly in a wide variety of scenarios. The camera motion is recovered through non-linear minimization of the projection errors of both point and line segment features. The method, of course, is computationally more expensive that using only one type of feature, but still can run in real-time on a standard computer and provides interesting advantages, including a straightforward integration into any probabilistic framework commonly employed in mobile robotics.Universidad de Málag

Robust Stereo Visual Odometry through a Probabilistic Combination of Points and Line Segments

Most approaches to stereo visual odometry reconstruct the motion based on the tracking of point features along a sequence of images. However, in low-textured scenes it is often difficult to encounter a large set of point features, or it may happen that they are not well distributed over the image, so that the behavior of these algorithms deteriorates. This paper proposes a probabilistic approach to stereo visual odometry based on the combination of both point and line segment that works robustly in a wide variety of scenarios. The camera motion is recovered through non-linear minimization of the projection errors of both point and line segment features. In order to effectively combine both types of features, their associated errors are weighted according to their covariance matrices, computed from the propagation of Gaussian distribution errors in the sensor measurements. The method, of course, is computationally more expensive that using only one type of feature, but still can run in real-time on a standard computer and provides interesting advantages, including a straightforward integration into any probabilistic framework commonly employed in mobile robotics.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Project "PROMOVE: Advances in mobile robotics for promoting independent life of elders", funded by the Spanish Government and the "European Regional Development Fund ERDF" under contract DPI2014-55826-R

An equation of state for purely kinetic k-essence inspired by cosmic topological defects

We investigate the physical properties of a purely kinetic k-essence model with an equation of state motivated in superconducting membranes. We compute the equation of state parameter $w$ and discuss its physical evolution via a nonlinear equation of state. Using the adiabatic speed of sound and energy density, we restrict the range of parameters of the model in order to have an acceptable physical behavior. Furthermore, we analyze the evolution of the luminosity distance $d_{L}$ with redshift $z$ by comparing (normalizing) it with the $\Lambda$CDM model. Since the equation of state parameter is $z$-dependent the evolution of the luminosity distance is also analyzed using the Alcock-Paczy\'{n}ski test.Comment: 19 pages, 13 figures, typos corrected and references adde

Geometric-based Line Segment Tracking for HDR Stereo Sequences

In this work, we propose a purely geometrical approach for the robust matching of line segments for challenging stereo streams with severe illumination changes or High Dynamic Range (HDR) environments. To that purpose, we exploit the univocal nature of the matching problem, i.e. every observation must be corresponded with a single feature or not corresponded at all. We state the problem as a sparse, convex, `1-minimization of the matching vector regularized by the geometric constraints. This formulation allows for the robust tracking of line segments along sequences where traditional appearance-based matching techniques tend to fail due to dynamic changes in illumination conditions. Moreover, the proposed matching algorithm also results in a considerable speed-up of previous state of the art techniques making it suitable for real-time applications such as Visual Odometry (VO). This, of course, comes at expense of a slightly lower number of matches in comparison with appearance based methods, and also limits its application to continuous video sequences, as it is rather constrained to small pose increments between consecutive frames.We validate the claimed advantages by first evaluating the matching performance in challenging video sequences, and then testing the method in a benchmarked point and line based VO algorithm.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.This work has been supported by the Spanish Government (project DPI2017-84827-R and grant BES-2015-071606) and by the Andalucian Government (project TEP2012-530)

Where are my followers? Understanding the Locality Effect in Twitter

Twitter is one of the most used applications in the current Internet with more than 200M accounts created so far. As other large-scale systems Twitter can obtain enefit by exploiting the Locality effect existing among its users. In this paper we perform the first comprehensive study of the Locality effect of Twitter. For this purpose we have collected the geographical location of around 1M Twitter users and 16M of their followers. Our results demonstrate that language and cultural characteristics determine the level of Locality expected for different countries. Those countries with a different language than English such as Brazil typically show a high intra-country Locality whereas those others where English is official or co-official language suffer from an external Locality effect. This is, their users have a larger number of followers in US than within their same country. This is produced by two reasons: first, US is the dominant country in Twitter counting with around half of the users, and second, these countries share a common language and cultural characteristics with US

Synalpheus shrimp from Carrie Bow Cay, Belize. Systematics, phylogenetics and biological observations (Crustacea: Decapoda: ; Alpheidae)

Snapping shrimp in the family Alpheidae are remarkably abundant in coral reef ecosystems worldwide. The second most speciose genus, Synalpheus , includes species usually small and reclusive, and their general morphology is notably uniform, yet the number of species is staggeringly high, as is the intraspecific variability. These features have contributed to a poorly resolved taxonomic status, as evidenced both by recurring lumping and splitting of species and by lack of proper definition of several common species. I examined western Atlantic species of Synalpheus in the large and regionally dominant Gambarelloides group of species , an informal but widely used guild within the genus. Analysis of external anatomical features of preserved and live specimens enabled a reassessment of morphological characters traditionally used in taxonomy, and incorporation of novel characters. Identity and validity of every species described from the western Atlantic has been reevaluated. Detailed ecological records and observations on live specimens under laboratory conditions yielded ancillary data useful in distinguishing the species. Seven new species are preliminarily described. Recognition of the Gambarelloides group as a distinct subgenus within Synalpheus is recommended. A systematic account of 17 species with selected illustrations and color photographs is included, together with a dichotomous identification key. The evolution of morphological characters was traced onto the current best reconstruction of the phylogenetic relationships among the species of the Gambarelloides group. The phylogenetic tree was obtained by analyzing molecular data from segments of two mitochondrial genes (COI and 16S) from 39 species of Synalpheus, with Alpheus cylindricus as the outgroup. Most of the morphological characters studied bore weak phylogenetic signal and homoplasies were frequent. Nevertheless, two characters provided consistent synapomorphies defining the Gambarelloides group: the dorsal brush of setae (used in feeding) on the dactyl of the minor first chela, and the coxal lamella on the third pereiopods. Evolution studies of Synalpheus are particularly interesting because of the high number of closely related species, similar general ecological preferences with microhabitat specificity, and variation in social organization. This reassessment of western Atlantic species provides a solid taxonomy and an important frame of reference for future studies of Synalpheus

Google+ or Google-?: Dissecting the Evolution of the New OSN in its First Year

In the era when Facebook and Twitter dominate the market for social media, Google has introduced Google+ (G+) and reported a significant growth in its size while others called it a ghost town. This begs the question that "whether G+ can really attract a significant number of connected and active users despite the dominance of Facebook and Twitter?". This paper tackles the above question by presenting a detailed characterization of G+ based on large scale measurements. We identify the main components of G+ structure, characterize the key features of their users and their evolution over time. We then conduct detailed analysis on the evolution of connectivity and activity among users in the largest connected component (LCC) of G+ structure, and compare their characteristics with other major OSNs. We show that despite the dramatic growth in the size of G+, the relative size of LCC has been decreasing and its connectivity has become less clustered. While the aggregate user activity has gradually increased, only a very small fraction of users exhibit any type of activity. To our knowledge, our study offers the most comprehensive characterization of G+ based on the largest collected data sets.Comment: WWW 201

Accurate Stereo Visual Odometry with Gamma Distributions

Point-based stereo visual odometry systems typically estimate the camera motion by minimizing a cost function of the projection residuals between consecutive frames. Under some mild assumptions, such minimization is equivalent to maximizing the probability of the measured residuals given a certain pose change, for which a suitable model of the error distribution (sensor model) becomes of capital importance in order to obtain accurate results. This paper proposes a robust probabilistic model for projection errors, based on real world data. For that, we argue that projection distances follow Gamma distributions, and hence, the introduction of these models in a probabilistic formulation of the motion estimation process increases both precision and accuracy. Our approach has been validated through a series of experiments with both synthetic and real data, revealing an improvement in accuracy while not increasing the computational burden.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Project "PROMOVE: Advances in mobile robotics for promoting independent life of elders", funded by the Spanish Government and the "European Regional Development Fund ERDF" under contract DPI2014-55826-R