Modeling cell proliferation in human acute myeloid leukemia xenografts

Motivation: Acute myeloid leukemia (AML) is one of the most common hematological malignancies, characterized by high relapse and mortality rates. The inherent intra-tumor heterogeneity in AML is thought to play an important role in disease recurrence and resistance to chemotherapy. Although experimental protocols for cell proliferation studies are well established and widespread, they are not easily applicable to in vivo contexts, and the analysis of related time-series data is often complex to achieve. To overcome these limitations, model-driven approaches can be exploited to investigate different aspects of cell population dynamics. Results: In this work, we present ProCell, a novel modeling and simulation framework to investigate cell proliferation dynamics that, differently from other approaches, takes into account the inherent stochasticity of cell division events. We apply ProCell to compare different models of cell proliferation in AML, notably leveraging experimental data derived from human xenografts in mice. ProCell is coupled with Fuzzy Self-Tuning Particle Swarm Optimization, a swarm-intelligence settings-free algorithm used to automatically infer the models parameterizations. Our results provide new insights on the intricate organization of AML cells with highly heterogeneous proliferative potential, highlighting the important role played by quiescent cells and proliferating cells characterized by different rates of division in the progression and evolution of the disease, thus hinting at the necessity to further characterize tumor cell subpopulations. Availability and implementation: The source code of ProCell and the experimental data used in this work are available under the GPL 2.0 license on GITHUB at the following URL: https://github.com/aresio/ProCell

Computational strategies for a system-level understanding of metabolism

Cell metabolism is the biochemical machinery that provides energy and building blocks to sustain life. Understanding its fine regulation is of pivotal relevance in several fields, from metabolic engineering applications to the treatment of metabolic disorders and cancer. Sophisticated computational approaches are needed to unravel the complexity of metabolism. To this aim, a plethora of methods have been developed, yet it is generally hard to identify which computational strategy is most suited for the investigation of a specific aspect of metabolism. This review provides an up-to-date description of the computational methods available for the analysis of metabolic pathways, discussing their main advantages and drawbacks. In particular, attention is devoted to the identification of the appropriate scale and level of accuracy in the reconstruction of metabolic networks, and to the inference of model structure and parameters, especially when dealing with a shortage of experimental measurements. The choice of the proper computational methods to derive in silico data is then addressed, including topological analyses, constraint-based modeling and simulation of the system dynamics. A description of some computational approaches to gain new biological knowledge or to formulate hypotheses is finally provided

Mathematical modeling of gallic acid release from chitosan films with grape seed extract and carvacrol

Controlled release of antimicrobial and antioxidant compounds from packaging films is of utmost importance for extending the shelf-life of perishable foods. This study focused on the mathematical modeling of gallic acid release into an aqueous medium from three chitosan films, formulated with grape seed extract (GSE) and carvacrol. We quantified the release by HPLC technique during 30days at three temperatures (5, 25 and 45°C). The diffusion coefficients, varying with temperature according to an Arrhenius-type relationship, and the respective activation energies for Film-1 and Film-2 were, respectively [Formula: see text] m2s-1 and [Formula: see text] m2s-1, Ea1=58kJmol-1 and Ea2=60kJmol-1 as obtained from the Fickian fit. The low concentrations of gallic acid released by Film-3 could not be detected by HPLC, therefore the respective diffusion coefficient was not estimated. This study will help with the development and optimization of active packaging (AP) films aiming at improved food preservation and shelf-life extension.Javiera F. Rubilar gratefully acknowledges her Ph.D. grant from ErasmusMundus 2008-1022/001 Frame ECW/17, EACEA(European Union), financial support of the Fondecyt-Postdoctoral #3140349 project from CONICYT, and also “Dirección de Investigación e Innovación Escuela de Ingeniería” at Pontificia Universidad Católica de Chile. Rui M. S. Cruz acknowledges grant SFRH/BPD/70036/2010 from Fundac¸ ão para a Ciência e Tecnologia, Portugalinfo:eu-repo/semantics/publishedVersio

Giorgio Vasari a Palazzo Abatellis. Percorsi del Rinascimento in Sicilia

La mostra si inserisce nell'ambito delle celebrazioni per i 500 anni della nascita di Giorgio Vasari (1511-2011), ricorrenza che, nel corso dell'anno, \ue8 stata oggetto di numerosi eventi culturali italiani e internazionali. L'iniziativa nasce dalla collaborazione tra la Biblioteca Centrale della Regione siciliana "A. Bombace", la sezione "Sfera" del Dipartimento di Architettura dell'Universit\ue0 degli Studi di Palermo, e la Galleria Interdisciplinare Regionale della Sicilia, istituzione che custodisce, nella prestigiosa sede di Palazzo Abatellis, due grandi dipinti su tavola di Vasari, costituenti le ricurve parti laterali del trittico della "Caduta della manna" realizzato nel 1545 per il refettorio di Santa Maria di Monteoliveto a Napoli. Le lunette vasariane, esposte in modo permanente dal 2009 ma ancora quasi del tutto sconosciute a studiosi e pubblico, per l'occasione sono state ricollocate secondo gli originali rapporti dimensionali con il perduto quadro centrale e poste in relazione con il disegno preparatorio dello stesso Vasari, oggi custodito presso l'Ecole nationale superieure des beaux-arts di Parigi. Il percorso analitico, che si \ue8 avvalso anche del prezioso contributo di Claudia Conforti, tra le pi\uf9 autorevoli studiose dell'artista aretino, e delle competenze tecniche dell'Associazione culturale LapiS, \ue8 stato svolto secondo tre tematiche connesse alla poliedrica attivit\ue0 vasariana e al suo contesto culturale: la pittura e l'arte del disegno, la produzione letteraria, l'architettura. Al patrimonio pittorico e grafico della Galleria, riconducibile a quella che lo stesso Vasari definisce \uabmaniera moderna\ubb, sono stati quindi associati preziosi volumi a stampa, a partire dalla rara edizione del 1568 delle "Vite de' pi\uf9 eccellenti architetti, pittori e scultori italiani", e pannelli illustrativi riferiti a opere siciliane di architetti e scultori citati nelle "Vite" vasariane, costituenti alcune pregnanti testimonianze del Rinascimento in Sicili

GPU-accelerated simulations of mass-action kinetics models with cupSODA

In the last years, graphics processing units (GPUs) witnessed ever growing applications for a wide range of computational analyses in the field of life sciences. Despite its large potentiality, GPU computing risks remaining a niche for specialists, due to the programming and optimization skills it requires. In this work we present cupSODA, a simulator of biological systems that exploits the remarkable memory bandwidth and computational capability of GPUs. cupSODA allows to efficiently execute in parallel large numbers of simulations, which are usually required to investigate the emergent dynamics of a given biological system under different conditions. cupSODA works by automatically deriving the system of ordinary differential equations from a reaction-based mechanistic model, defined according to the mass-action kinetics, and then exploiting the numerical integration algorithm, LSODA. We show that cupSODA can achieve a 86 7 speedup on GPUs with respect to equivalent executions of LSODA on the CPU. \ua9 2014 Springer Science+Business Media New York

Tritium processing at the Savannah River Site (SRS): Present and future

Tritium handling equipment and methods at the Savannah River Site Tritium Facilities have been continually improved since tritium processing operations began in 1955. Several new technologies were introduced into the Tritium Facilities in the 1980's. One of these is the use of fluidless, mechanical pumps (Normetex and Metal Bellows) to replace mercury pumps. A second is the use of metal hydride technology to store, purify, isotopically separate, pump, and compress hydrogen isotopes. Metal hydrides, such as La-Ni-Al alloys and Pd loaded on kieselguhr, offer significant flexibility and size advantages compared with conventional tritium handling technology, such as gas tanks, thermal diffusion columns, and mechanical compressors. Metal hydrides have been used in the Tritium Facilities since 1984 with the most important application of this technology being planned for the Replacement Tritium Facility, a $140 million facility scheduled for completion in 1990 and startup in 1991. 11 refs., 9 figs

Massive exploration of perturbed conditions of the blood coagulation cascade through GPU parallelization

The introduction of general-purpose Graphics Processing Units (GPUs) is boosting scientific applications in Bioinformatics, Systems Biology, and Computational Biology. In these fields, the use of high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers. In this work we present coagSODA, a CUDA-powered computational tool that was purposely developed for the analysis of a large mechanistic model of the blood coagulation cascade (BCC), defined according to both mass-action kinetics and Hill functions. coagSODA allows the execution of parallel simulations of the dynamics of the BCC by automatically deriving the system of ordinary differential equations and then exploiting the numerical integration algorithm LSODA. We present the biological results achieved with a massive exploration of perturbed conditions of the BCC, carried out with one-dimensional and bi-dimensional parameter sweep analysis, and show that GPU-accelerated parallel simulations of this model can increase the computational performances up to a 181 7 speedup compared to the corresponding sequential simulations. \ua9 2014 Paolo Cazzaniga et al

cupSODA: a CUDA-powered simulator of mass-action kinetics

The computational investigation of a biological system often requires the execution of a large number of simulations to analyze its dynamics, and to derive useful knowledge on its behavior under physiological and perturbed conditions. This analysis usually turns out into very high computational costs when simulations are run on central processing units (CPUs), therefore demanding a shift to the use of high-performance processors. In this work we present a simulator of biological systems, called cupSODA, which exploits the higher memory bandwidth and computational capability of graphics processing units (GPUs). This software allows to execute parallel simulations of the dynamics of biological systems, by first deriving a set of ordinary differential equations from reaction-based mechanistic models defined according to the mass-action kinetics, and then exploiting the numerical integration algorithm LSODA. We show that cupSODA can achieve a 112 7 speedup on GPUs with respect to equivalent executions of LSODA on CPUs

Simulation and analysis of the blood coagulation cascade accelerated on GPU

The use of Graphics Processing Units (GPUs) has recently witnessed ever growing applications for different computational analyses in the field of Life Sciences. In this work we present a CUDA-powered computational tool, named coagSODA, that was purposely developed and applied for the analysis of a large model of the blood coagulation cascade defined as a system of ordinary differential equations, based on both mass-action kinetics and Hill functions. We discuss the biological results of the parameter sweep analyses of this model, and show that GPUs can boost the computational performances up to 177x speedup. \ua9 2014 IEEE

Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs

We present a parameter estimation method, based on particle swarm optimization (PSO) and embedding the tau-leaping algorithm, for the efficient estimation of reaction constants in stochastic models of biological systems, using as target a set of discrete-time measurements of molecular amounts sampled in different experimental conditions. To account for the multiplicity of data, we consider a multi-swarm formulation of PSO. The whole method is developed for GPGPU architecture to reduce the computational costs