Activation of effector immune cells promotes tumor stochastic extinction: A homotopy analysis approach

In this article we provide homotopy solutions of a cancer nonlinear model describing the dynamics of tumor cells in interaction with healthy and effector immune cells. We apply a semi-analytic technique for solving strongly nonlinear systems – the Step Homotopy Analysis Method (SHAM). This algorithm, based on a modification of the standard homotopy analysis method (HAM), allows to obtain a one-parameter family of explicit series solutions. By using the homotopy solutions, we first investigate the dynamical effect of the activation of the effector immune cells in the deterministic dynamics, showing that an increased activation makes the system to enter into chaotic dynamics via a period-doubling bifurcation scenario. Then, by adding demographic stochasticity into the homotopy solutions, we show, as a difference from the deterministic dynamics, that an increased activation of the immune cells facilitates cancer clearance involving tumor cells extinction and healthy cells persistence. Our results highlight the importance of therapies activating the effector immune cells at early stages of cancer progression.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Structural characterization and immunogenicity in wildtype and immune tolerant mice of degraded recombinant human interferon alpha2b

Purpose - To study the influence of protein structure on the immunogenicity in wildtype and immune tolerant mice of well-characterized degradation products of recombinant human interferon alpha2b (rhIFNα2b). Methods - RhIFNα2b was degraded by metal catalyzed oxidation (M), crosslinking with glutaraldehyde (G), oxidation with hydrogen peroxide (H) and incubation in a boiling water bath (B). The products were characterized with UV absorption, circular dichroism and fluorescence spectroscopy, gel permeation chromatography, reversed-phase HPLC, SDS-PAGE, Western blotting and mass spectrometry. The immunogenicity of the products was evaluated in wildtype mice and in transgenic mice immune tolerant for hIFNα2. Serum antibodies were detected by ELISA or surface plasmon resonance. Results - M-rhIFNα2b contained covalently aggregated rhIFNα2b with three methionines partly oxidized to methionine sulfoxides. G-rhIFNα2b contained covalent aggregates and did not show changes in secondary structure. H-rhIFNα2b was only chemically changed with four partly oxidized methionines. B-rhIFNα2b was largely unfolded and heavily aggregated. Native (N) rhIFNα2b was immunogenic in the wildtype mice but not in the transgenic mice, showing that the latter were immune tolerant for rhIFNα2b. The antirhIFNα2b antibody levels in the wildtype mice depended on the degradation product: M-rhIFNα2b > H-rhIFNα2b ~ N-rhIFNα2b >> B-rhIFNα2b; G-rhIFNα2b did not induce anti-rhIFNα2b antibodies. In the transgenic mice, only M-rhIFNα2b could break the immune tolerance. Conclusions - RhIFNα2b immunogenicity is related to its structural integrity. Moreover, the immunogenicity of aggregated rhIFNα2b depends on the structure and orientation of the constituent protein molecules and/or on the aggregate size.

Structural characterization and immunogenicity in wild-type and immune tolerant mice of degraded recombinant human interferon Alpha2b

Purpose: This study was conducted to study the influence of protein structure on the immunogenicity in wild-type and immune tolerant mice of well-characterized degradation products of recombinant human interferon alpha2b (rhIFNα2b). Methods: RhIFNα2b was degraded by metal-catalyzed oxidation (M), cross-linking with glutaraldehyde (G), oxidation with hydrogen peroxide (H), and incubation in a boiling water bath (B). The products were characterized with UV absorption, circular dichroism and fluorescence spectroscopy, gel permeation chromatography, reverse-phase high-pressure liquid chromatography, sodium dodecyl sulfate polyacrylamide gel electrophoresis, Western blotting, and mass spectrometry. The immunogenicity of the products was evaluated in wild-type mice and in transgenic mice immune tolerant for hIFNα2. Serum antibodies were detected by enzyme-linked immunosorbent assay or surface plasmon resonance. Results: M-rhIFNα2b contained covalently aggregated rhIFNα2b with three methionines partly oxidized to methionine sulfoxides. G-rhIFNα2b contained covalent aggregates and did not show changes in secondary structure. H-rhIFNα2b was only chemically changed with four partly oxidized methionines. B-rhIFNα2b was largely unfolded and heavily aggregated. Nontreated (N) rhIFNα2b was immunogenic in the wild-type mice but not in the transgenic mice, showing that the latter were immune tolerant for rhIFNα2b. The anti-rhIFNα2b antibody levels in the wild-type mice depended on the degradation product: M-rhIFNα2b > H-rhIFNα2b ∼ N-rhIFNα2b ≫ B-rhIFNα2b; G-rhIFNα2b did not induce anti-rhIFNα2b antibodies. In the transgenic mice, only M-rhIFNα2b could break the immune tolerance. Conclusions: RhIFNα2b immunogenicity is related to its structural integrity. Moreover, the immunogenicity of aggregated rhIFNα2b depends on the structure and orientation of the constituent protein molecules and/or on the aggregate size.

Comparação do cálculo de dose com os algoritmos Analytical Anisotropic Algorithm e Pencil Beam Convolution na patologia de pulmão

Mestrado em Radioterapia.

Cellular uptake of BCG-loaded chitosan microparticles and in vivo evaluation of immune response following intranasal immunisation

Attenuated Mycobacterium bovis bacillus Calmette-Guérin (BCG) is the only currently available vaccine against tuberculosis. It is highly effective in pre-exposure immunisation against TB in children when administered by subcutaneous route to newborns. However, it does not provide permanent protection in adults. In this work, polymeric chitosan-alginate microparticles have been evaluated as potential nasal delivery systems and mucosal adjuvants for live attenuated BCG. Chitosan (CS) has been employed as adjuvant and mucosal permeation-enhancer, and, together with alginate (ALG), as additive to enhance BCG-loaded microparticles (MPs) cellular uptake in a human monocyte cell line, by particle surface modification. The most suitable particles were used for vaccine formulation and evaluation of immune response following intranasal immunisation of BALB/c mice.

Comparação entre o pencil beam convolution algorithm e o analytical anisotropic algorithm em tumores de mama

Mestrado em Radioterapia

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

Comparison of the pencil beam convolution algorithm and the analytical anisotropic algorithm in breast tumors

The calculation of the dose is one of the key steps in radiotherapy planning1-5. This calculation should be as accurate as possible, and over the years it became feasible through the implementation of new algorithms to calculate the dose on the treatment planning systems applied in radiotherapy. When a breast tumour is irradiated, it is fundamental a precise dose distribution to ensure the planning target volume (PTV) coverage and prevent skin complications. Some investigations, using breast cases, showed that the pencil beam convolution algorithm (PBC) overestimates the dose in the PTV and in the proximal region of the ipsilateral lung. However, underestimates the dose in the distal region of the ipsilateral lung, when compared with analytical anisotropic algorithm (AAA). With this study we aim to compare the performance in breast tumors of the PBC and AAA algorithms.

A SON Enhanced Algorithm for Observed Time Differences Based Geolocation in Real 3G Networks

Conferência - 16th International Symposium on Wireless Personal Multimedia Communications (WPMC)- Jun 24-27, 2013

Comparação entre o pencil beam convolution algorithm e o analytical anisotropic algorithm em tumores de mama

Objectivo do estudo: comparar o desempenho dos algoritmos Pencil Beam Convolution (PBC) e do Analytical Anisotropic Algorithm (AAA) no planeamento do tratamento de tumores de mama com radioterapia conformacional a 3D.

Coding mode decision algorithm for binary descriptor coding

In visual sensor networks, local feature descriptors can be computed at the sensing nodes, which work collaboratively on the data obtained to make an efficient visual analysis. In fact, with a minimal amount of computational effort, the detection and extraction of local features, such as binary descriptors, can provide a reliable and compact image representation. In this paper, it is proposed to extract and code binary descriptors to meet the energy and bandwidth constraints at each sensing node. The major contribution is a binary descriptor coding technique that exploits the correlation using two different coding modes: Intra, which exploits the correlation between the elements that compose a descriptor; and Inter, which exploits the correlation between descriptors of the same image. The experimental results show bitrate savings up to 35% without any impact in the performance efficiency of the image retrieval task. © 2014 EURASIP.

Algorithm-oriented design of efficient many-core architectures applied to dense matrix multiplication

Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.