86,934 research outputs found
An oscillation-free fully staggered algorithm for velocity-dependent active models of cardiac mechanics
No full textIn this paper we address an unresolved problem in the numerical modeling of cardiac electromechanics, that is the onset of numerical oscillations due to the dependence of force generation models on the fibers shortening velocity. A way to avoid numerical oscillations is to use monolithic schemes for the solution of the coupled problem of active-passive mechanics. However, staggered strategies, which foresee the sequential solution of the models of force generation and of tissue mechanics, are preferable, due to their reduced computational cost and low implementation effort. In this paper we propose a cure for this issue, by introducing, with respect to the standard staggered scheme, a numerically consistent stabilization term. This term is derived in virtue of the identification of the cause of instability in the mismatch between macroscopic and microscopic strains, inconsistently expressed in Lagrangian and Eulerian coordinates, respectively. By considering a model problem of active mechanics we prove that the proposed scheme is unconditionally absolutely stable (i.e. it is stable for any time step size), yet within a fully staggered framework. As such, the new scheme removes the non-physical oscillations, as we prove by applying it to three force generation models, namely the Niederer-Hunter-Smith model, the model by Land and coworkers, and the mean-field force generation model that we have recently proposed. (C) 2020 The Author(s). Published by Elsevier B.V.CMC
Accelerating the convergence to a limit cycle in 3D cardiac electromechanical simulations through a data-driven 0D emulator
No full textThe results of numerical simulations of cardiac electromechanics are typically characterized by a long transient before reaching a periodic solution known as limit cycle. This yields a serious computational overhead, as the only clinically relevant output is associated with such limit cycle. To accelerate the convergence to the limit cycle, we propose a strategy based on a surrogate model, wherein the computationally demanding 3D components are replaced by a 0D emulator, built through an automated data-driven algorithm on the basis of pressurevolume transients of as few as three heartbeats simulated with the 3D model. The 0D emulator, consisting of a time-dependent pressure-volume relationship, can provide the 3D model with an initial guess, such that in just two heartbeats a solution is reached that is as close to the limit cycle as the one obtained after more than 20 heartbeats with the 3D model. The 0D emulator is also recommended in many-query settings (e.g. when performing sensitivity analysis, parameter estimation and uncertainty quantification), that call for the repeated solution of the model for different values of the parameters. Indeed, the construction of the emulator does not have to be repeated when the parameters of the circulation model it is coupled with vary. Finally, should the parameters of the 3D electromechanical model vary as well, we propose a parametric emulator, obtained by interpolation of emulators constructed for given values of the parameters. This paper is accompanied by a Python library implementing the proposed algorithm, open to integration with existing cardiac solvers.CMC
Benzothiadiazole derivatives endowed with STAT3 inhibition
No full textBENZOTHIADIAZOLE DERIVATIVES ENDOWED WITH STAT3
INHIBITION
Arianna Gelain (1), Matteo Mori (1), Ettore Gilardoni (1), Luca Regazzoni (1), Alessandro Pedretti (1),
Diego Colombo (2), Gary Parkinson (3), Akira Asai (4), Fiorella Meneghetti (1), Stefania Villa (1)
1) Department of Pharmaceutical Sciences, University of Milan, via L. Mangiagalli 25, 20133 Milan, Italy
2) Department of Medical Biotechnology and Translational Medicine, University of Milan, via C. Saldini 50, 20133 Milan,
Italy
3) Department of Pharmaceutical and Biological Chemistry – UCL School of Pharmacy, University College London, 29/39
Brunswick Square, WC1N 1AX London, United Kingdom
4) Center for Drug Discovery – Graduate School of Pharmaceutical Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku,
422-8526 Shizuoka, Japan
Signal Transducer and Activator of Transcription 3 (STAT3) is a latent cytoplasmic protein over-expressed in
various cancer cell lines1,2. As a part of our ongoing research focused on compounds showing STAT3 SH2
domain inhibiting activity3,4, by a virtual screening approach, we identified 5,6-dimethyl-1H,3H
-2,1,3-benzothiadiazole-2,2-dioxide (1) as potential inhibitor. Several derivatives were synthesized (Figure 1)
and tested. Since compound 1 exhibited the most interesting activity (IC50 = 15.8 ± 0.6 μM by
AlphaScreen-based assay), we decided to investigate the mechanism of its activity by liquid chromatography,
MS and UV studies, discovering compound 1 unexpected interaction also with cysteine residues5.
Figure 1 . Benzothiadiazole-2,2-dioxide derivatives set
References
1) Darnell, J. Jr Science, 1997, 277, 1630-1635
2) Turkson, J. and Jove R. Oncogene, 2000, 19, 6613-6626
3) Meneghetti, F.; Villa, S.; Masciocchi, D.; Barlocco, D.; Toma, L.; Han, D.C.; Kwon, B.M.; Ogo, N.; Asai, A.; Legnani, L.;
Gelain, A. European J. Org. Chem. 2015, 2015, 4907–4912
4) Porta, F.; Facchetti, G.; Ferri, N.; Gelain, A.; Meneghetti, F.; Villa, S.; Barlocco, D.; Masciocchi, D.; Asai, A.; Miyoshi,
N.; Marchianò, S.; Kwon, B.M.; Jin, Y.; Gandin, V.; Marzano, C.; Rimoldi, Eur. J. Med. Chem. 2017, 131, 196–206
5) Mori, M.; Gilardoni, E.; Regazzoni, L.; Pedretti, A.; Colombo, D.; Parkinson, G.; Asai, A,; Meneghetti, F.; Villa, S.;
Gelain, A., Molecules 2020, 25(15), 3509
Adaptive tracking of multiple non rigid objects in cluttered scenes
No full textTracking of non-rigid objects (e.g. humans) is a crucial application for understanding the behavior of objects. Different methods have been presented in literature, whose main drawback is low robustness or high computational load in analysis of cluttered scenes. In the paper a low computational algorithm for tracking non-rigid objects in cluttered scenes is presented. The proposed approach models the shape of the objects by using corners. A learning algorithm is introduced in order to automatically extract the model of the object from a short video sequence acquired immediately before merging of more objects in the scene. The adaptive model extraction mechanism strongly improves method robustness. The method is tested on an existing video-surveillance system in order to track moving objects in cluttered scenes. Results show that the proposed approach gives good performances with low-processing times
F. Moya Pons, Después de Colón; E. Galeano, El descubrimiento de América que todavía no fue y otros cuentos
No full textGHT based implementation of the expectation maximization for mixtures of multi-Gaussians and its applications to video tracking
No full textIn this work, the problem of the estimation of parameters in case of mixtures of models composed of the sum of multiple Gaussians is considered. It will be shown how this estimation can be performed efficiently by using the Generalized Hough Transform (GHT). The theoretical results will be applied to a corner-based object tracking application considering, in particular, the case of two or more objects that come into proximity and occlude each other. Quantitative results show the performances of the derived algorithm both on synthetically generated data and real tracking sequences
Real-time robust detection of moving objects in cluttered scenes
No full textObject recognition is a very important task in computer vision and different techniques have been presented to solve it. In this paper a Hough-type low-computational algorithm for detection of objects in cluttered scenes is presented. The approach is based on the detection of the shape of an object, modeled by means of a set of corners. An automatically model learning method is introduced. The method is used in an existing video-surveillance system in order to increase its detection performances. Results show that the proposed approach provides good performances with low processing times
Adaptive post-processing error concealment based on feedback from a video-surveillance system
No full textAn effective real-time post-processing algorithm for error recovery in noise corrupted JPEG bit streams integrated into an existing remote video-surveillance system is presented(1). The algorithm exploits information extracted by the video-surveillance system in order to detect corrupted frames and to recover them, enhancing the performances of the system, without compromising the real-time behavior of the application. Results show the validity of the presented approach
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