Shape analysis and tracking of migrating macrophages

Cell migration is important in many human processes of development and disease. In Cancer, migration can be related to metastasis or cell defects. A precise analysis of the cell shapes in biological studies could lead to insights about migration. Therefore, this paper describes an algorithm to iteratively segment, track and analyse the shape of macrophages from fluorescent microscopy image sequences. This process allows observation of shape variations as the cells migrate. The algorithm identifies and separates overlapping and non-overlapping cells, then for the non-overlapping cases analyses the shape and extracts a series of measurements, including the number of "corner" or pointy edges through a multiscale angle variation matrix, anglegram. The shape evolution algorithm was tested on fluorescently labelled macrophages observed on embryos of Drosophila melanogaster

Analysis of the Interactions of Migrating Macrophages

Understanding the migrating patterns of cells in the immune system is of great importance; especially the changes of direction and its cause. For macrophages and other immune cells, excessive migration could be related to autoimmune diseases and cancer. In this work, an algorithm to analyse the change in direction of cells before and after they interact with another cell is proposed. The main objective is to provide insights into the notion that interactions between cell structures appear to anticipate migration. Such interactions are determined when the cells overlap and form clumps of two or more cells. The algorithm integrates a segmentation technique capable of detecting overlapping cells and a tracking framework into a tool for the analysis of the trajectories of cells before and after they overlap. The preliminary results show promise into the analysis and the hypothesis proposed, and it lays the ground work for further developments

Segmentation of Overlapping Macrophages Using Anglegram Analysis

This paper describes the automatic segmentation of overlapping cells through different algorithms. As the first step, the algorithm detects junctions between the boundaries of overlapping objects based on the angles between points of the overlapping boundary. For this purpose, a novel 2D matrix with multiscale angle variation is introduced, i.e anglegram. The anglegram is used to find junctions of overlapping cells. The algorithm to retrieve junctions from the boundary was tested and validated with synthetic data and fluorescently labelled macrophages observed on embryos of Drosophila melanogaster. Then, four different segmentation techniques were evaluated: (i) a Voronoi partition based on the nuclei positions, (ii) a slicing method, which joined the clumps together (junction slicing), (iii) a partition based on the following of the edges from the junctions (edge following), and (iv) a custom self-organising map to fit to the area of overlap between the cells. Only (ii)-(iv) were based on the junctions. The segmentation results were compared based on precision, recall and Jaccard similarity. The algorithm that reported the best segmentation was the junction slicing

Do software models based on the UML aid in source-code comprehensibility? Aggregating evidence from 12 controlled experiments

In this paper, we present the results of long-term research conducted in order to study the contribution made by software models based on the Unified Modeling Language (UML) to the comprehensibility of Java source-code deprived of comments. We have conducted 12 controlled experiments in different experimental contexts and on different sites with participants with different levels of expertise (i.e., Bachelor’s, Master’s, and PhD students and software practitioners from Italy and Spain). A total of 333 observations were obtained from these experiments. The UML models in our experiments were those produced in the analysis and design phases. The models produced in the analysis phase were created with the objective of abstracting the environment in which the software will work (i.e., the problem domain), while those produced in the design phase were created with the goal of abstracting implementation aspects of the software (i.e., the solution/application domain). Source-code comprehensibility was assessed with regard to correctness of understanding, time taken to accomplish the comprehension tasks, and efficiency as regards accomplishing those tasks. In order to study the global effect of UML models on source-code comprehensibility, we aggregated results from the individual experiments using a meta-analysis. We made every effort to account for the heterogeneity of our experiments when aggregating the results obtained from them. The overall results suggest that the use of UML models affects the comprehensibility of source-code, when it is deprived of comments. Indeed, models produced in the analysis phase might reduce source-code comprehensibility, while increasing the time taken to complete comprehension tasks. That is, browsing source code and this kind of models together negatively impacts on the time taken to complete comprehension tasks without having a positive effect on the comprehensibility of source code. One plausible justification for this is that the UML models produced in the analysis phase focus on the problem domain. That is, models produced in the analysis phase say nothing about source code and there should be no expectation that they would, in any way, be beneficial to comprehensibility. On the other hand, UML models produced in the design phase improve source-code comprehensibility. One possible justification for this result is that models produced in the design phase are more focused on implementation details. Therefore, although the participants had more material to read and browse, this additional effort was paid back in the form of an improved comprehension of source code

Capital allocation for credit portfolios with kernel estimators

Determining contributions by sub-portfolios or single exposures to portfolio-wide economic capital for credit risk is an important risk measurement task. Often economic capital is measured as Value-at-Risk (VaR) of the portfolio loss distribution. For many of the credit portfolio risk models used in practice, the VaR contributions then have to be estimated from Monte Carlo samples. In the context of a partly continuous loss distribution (i.e. continuous except for a positive point mass on zero), we investigate how to combine kernel estimation methods with importance sampling to achieve more efficient (i.e. less volatile) estimation of VaR contributions.Comment: 22 pages, 12 tables, 1 figure, some amendment

Photo-detection using Bose-condensed atoms in a micro trap

A model of photo-detection using a Bose--Einstein condensate in an atom-chip based micro trap is analyzed. Atoms absorb photons from the incident light field, receive part of the photon momentum and leave the trap potential. Upon counting of escaped atoms within predetermined time intervals, the photon statistics of the incident light is mapped onto the atom-count statistics. Whereas traditional photo-detection theory treats the emission centers of photo electrons as distinguishable, here the centers of escaping atoms are condensed and thus indistinguishable atoms. From this an enhancement of the photon-number resolution as compared to the commonly known counting formula is derived.Comment: 11 pages, 5 figures; revised versio

Group Approach to the Quantization of the P\"oschl-Teller dynamics

The quantum dynamics of a particle in the Modified P\"oschl-Teller potential is derived from the group $SL(2,R)$ by applying a Group Approach to Quantization (GAQ). The explicit form of the Hamiltonian as well as the ladder operators is found in the enveloping algebra of this basic symmetry group. The present algorithm provides a physical realization of the non-unitary, finite-dimensional, irreducible representations of the $SL(2,R)$ group. The non-unitarity manifests itself in that only half of the states are normalizable, in contrast with the representations of SU(2) where all the states are physical.Comment: 17 pages, LaTe

Polymorphism of the prolactin gene (PRL) and its relationship with milk production in American Swiss cattle

The modern dairy cattle breeding strategy in the Mexican tropic is to identify genes or allelic variants that can be incorporated into selection programs such as the prolactin gene (PRL) which is associated with milk production and quality. The aim of this study is to screen an American Swiss population in Chiapas, Mexico, in order to analyze the polymorphism of the prolactin gene as well as its relationship with milk production in blood samples of 417 American Swiss cattle. The genotypes were determined through the polymerase chain reaction-restriction fragments length polymorphism (PCR-RFLP) technique, using RsaI restriction endonuclease, showing a 156 bp fragment located in exon 3. Allele frequencies in the studied breed were: A = 0.8765 and B = 0.1235. The genotype frequencies of AA, AB and BB were 0.776, 0.174 and 0.026, respectively. The Chi-square indicated that genotype distributions were not in the Hardy-Weinberg equilibrium (P<0.05). The results show that animals with genotype AA had a greater milk production during lactation than genotypes AB and BB (P<0.05), with genotype BB being the one that had the lowest production (P<0.05). It was concluded that the identification of the prolactin polymorphism in this population will allow the achievement of a better efficiency in the selection of breeding animals.Keywords: Brown Swiss, prolactin, polymorphism, milk, RFLP-RsaI.African Journal of Biotechnology Vol. 11(29), pp. 7338-7343, 10 April, 201