Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>Interfractional geometric uncertainties can lead to deviations of the actual delivered dose from the prescribed dose distribution. To better handle these uncertainties during the course of treatment, the authors propose a framework for robust adaptive radiation therapy in which a variety of robust adaptive treatment strategies are introduced and evaluated. This variety is a result of optimization variables with various degrees of freedom within robust optimization models that vary in their grade of conservativeness. The different degrees of freedom in the optimization variables are expressed through either time-and-uncertainty-scenario-independence, time-dependence or time-and-uncertainty-scenario-dependence, while the robust models are either based on expected-value-, worst-case- or conditional value-at-risk-optimization. The goal of this study is to understand which mathematical properties of the proposed robust adaptive strategies are relevant such that the accumulated dose can be steered as close as possible to the prescribed dose as the treatment progresses. We apply a result from convex analysis to show that the robust non-adaptive approach under conditions of convexity and permutation-invariance is at least as good as the time-dependent robust adaptive approach, which implies that the time-dependent problem can be solved by dynamically solving the corresponding time-independent problem. According to the computational study, non-adaptive robust strategies may provide sufficient target coverage comparable to robust adaptive strategies if the occurring uncertainties follow the same distribution as those included in the robust model. Moreover, the results indicate that time-and-uncertainty-scenario-dependent optimization variables are most compatible with worst-case-optimization, while time-and-uncertainty-scenario-independent variables find their best match with expected value optimization. In conclusion, the authors introduced a novel framework for robust adaptive radiation therapy and identified mathematical requirements to further develop robust adaptive strategies in order to improve treatment outcome in the presence of interfractional uncertainties.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Moving fronts of cells are essential for development, repair and disease progression. Therefore, understanding and quantifying the details of the mechanisms that drive the movement of cell fronts is of wide interest. Quantitatively identifying the role of intercellular interactions, and in particular the role of cell pushing, remains an open question. In this work, we report a combined experimental-modelling approach showing that intercellular interactions contribute significantly to the spatial spreading of a population of cells. We use a novel experimental data set with PC-3 prostate cancer cells that have been pretreated with Mitomycin-C to suppress proliferation. This allows us to experimentally separate the effects of cell migration from cell proliferation, thereby enabling us to focus on the migration process in detail as the population of cells recolonizes an initially-vacant region in a series of two-dimensional experiments. We quantitatively model the experiments using a stochastic modelling framework, based on Langevin dynamics, which explicitly incorporates random motility and various intercellular forces including: (i) long range attraction (adhesion); and (ii) finite size effects that drive short range repulsion (pushing). Quantitatively comparing the ability of this model to describe the experimentally observed population-level behaviour provides us with quantitative insight into the roles of random motility and intercellular interactions. To quantify the mechanisms at play, we calibrate the stochastic model to match experimental cell density profiles to obtain estimates of cell diffusivity, <jats:italic>D</jats:italic>, and the amplitude of intercellular forces, <jats:italic>f</jats:italic> <jats:sub>0</jats:sub>. Our analysis shows that taking a standard modelling approach which ignores intercellular forces provides a poor match to the experimental data whereas incorporating intercellular forces, including short-range pushing and longer range attraction, leads to a faithful representation of the experimental observations. These results demonstrate a significant role of cell pushing during cell front movement and invasion.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Developments in micro-manufacture as well as biofabrication technologies are driving our ability to create complex tissue models such as ‘<jats:italic>organ-on-a-chip</jats:italic>’ devices. The complexity of neural tissue, however, requires precisely specific cellular connectivity across many neuronal populations, and thus there have been limited reports of complex ‘<jats:italic>brain-on-a-chip</jats:italic>’ technologies modelling specific cellular circuit function. Here we describe the development of a model of <jats:italic>in vitro</jats:italic> brain circuitry designed to accurately reproduce part of the complex circuitry involved in neurodegenerative diseases; using segregated co-culture of specific basal ganglia (BG) neuronal subtypes to model central nervous system circuitry. Lithographic methods and chemical modification were used to form structured micro-channels, which were populated by specifically cultured neuronal sub-types to represent parts of the inter-communicating neural circuit. Cell morphological assessment and immunostaining showed connectivity, which was supported by electrophysiology measurements. Electrical activity of cells was measured using patch-clamp, showing voltage dependant Na<jats:sup>+</jats:sup> and K<jats:sup>+</jats:sup> currents, and blocking of Na<jats:sup>+</jats:sup> current by TTX, and calcium imaging showing TTX-sensitive slow Ca<jats:sup>2+</jats:sup> oscillations resulting from action potentials. Monitoring cells across connected ports post-TTX addition demonstrated both upstream and downstream changes in activity, indicating network connectivity. The model developed herein provides a platform technology that could be used to better understand neurological function and dysfunction, contributing to a growing urgency for better treatments of neurodegenerative disease. We anticipate the use of this advancing technology for the assessment of pharmaceutical and cellular therapies as a means of pre-clinical assessment, and further for the advancement of neural engineering approaches for tissue engineering.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The quench of a human magnetic resonance imaging system is a critical event that may occur spontaneously, as an accident or purposely in response to an emergency. Although a magnet’s quench presents its own risks, little experimental data is available in this respect. In this study, the programmed quench of a human MRI scanner was used to measure the induced time varying magnetic fields (<jats:inline-formula> <jats:tex-math> <?CDATA ${\rm{d}}B/{\rm{d}}t$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="normal">d</mml:mi> <mml:mi>B</mml:mi> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:mi mathvariant="normal">d</mml:mi> <mml:mi>t</mml:mi> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bpexab2300ieqn1.gif" xlink:type="simple" /> </jats:inline-formula>) inside the bore in order to evaluate cardiac stimulation risks during a quench. Additionally, we measured the exit temperature of the helium gas, to evaluate potential implications in quench pipe design. The maximum <jats:inline-formula> <jats:tex-math> <?CDATA ${\rm{d}}B/{\rm{d}}t$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="normal">d</mml:mi> <mml:mi>B</mml:mi> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:mi mathvariant="normal">d</mml:mi> <mml:mi>t</mml:mi> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bpexab2300ieqn2.gif" xlink:type="simple" /> </jats:inline-formula> was 360 mT s<jats:sup>−1</jats:sup> at the center of the magnet, far below the cardiac stimulation threshold (20 T s<jats:sup>−1</jats:sup>). The helium exit temperature reached 35 K, perhaps implying further considerations about quench pipe designs. Replication of similar experiments on programmed quenches, specially in high-field MRI systems, will be useful to further characterize quench risks.</jats:p>