An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.     

Sofosbuvir Selects for Drug-Resistant Amino Acid Variants in the Zika Virus RNA-Dependent RNA-Polymerase Complex In Vitro

The nucleotide analog sofosbuvir, licensed for the treatment of hepatitis C, recently revealed activity against the Zika virus (ZIKV) in vitro and in animal models. However, the ZIKV genetic barrier to sofosbuvir has not yet been characterized. In this study, in vitro selection experiments were performed in infected human hepatoma cell lines. Increasing drug pressure significantly delayed viral breakthrough (p = 0.029). A double mutant in the NS5 gene (V360L/V607I) emerged in 3 independent experiments at 40–80 µM sofosbuvir resulting in a 3.9 ± 0.9-fold half- maximal inhibitory concentration (IC₅₀) shift with respect to the wild type (WT) virus. A triple mutant (C269Y/V360L/V607I), detected in one experiment at 80 µM, conferred a 6.8-fold IC₅₀ shift with respect to the WT. Molecular dynamics simulations confirmed that the double mutant V360L/V607I impacts the binding mode of sofosbuvir, supporting its role in sofosbuvir resistance. Due to the distance from the catalytic site and to the lack of reliable structural data, the contribution of C269Y was not investigated in silico. By a combination of sequence analysis, phenotypic susceptibility testing, and molecular modeling, we characterized a double ZIKV NS5 mutant with decreased sofosbuvir susceptibility. These data add important information to the profile of sofosbuvir as a possible lead for anti-ZIKV drug development.     

Numerical analysis of Augmented Lagrangian algorithms in complementary elastoplasticity

The main subject of the paper is the investigation of Augmented Lagrangian algorithms and update formulas in the solution of elastoplastic problems. A stress rate formulation for elastoplastic models with internal variables and its finite increment form is employed to state the mechanical problem. In this formulation the Augmented Lagrangian is used to enforce the constraint of plastic admissibility directly on the stresses and thermodynamic forces. This is not a limitation of the Augmented Lagrangian approach, and the same framework can be built on more classical displacement formulations as well. The meaning and the derivation of various first and second order Lagrangian multipliers update formulas and iterative schemes is shown. A new diagonal iteration algorithm and the introduction of a scale factor for the Augmented Lagrangian term are proposed. Numerical examples compare the efficiency of several forms of Augmented Lagrangian algorithms and illustrate the influence of the scale factor and of the penalty parameter. Copyright © 2004 John Wiley & Sons, Ltd.     

Evaluation of Textile Bobbins Drying Processes: Experimental and Modelling Studies

Drying of textile bobbins was carried out on two kinds of laboratory-scale dryers: in a cross circulation drying rig, atmospheric pressure heating air is used, while in the through circulation drying apparatus, the heating air is pressurized before the drying process takes place. In both cases, a bobbin was fitted with seven thermocouples, placed in a plane normal to the bobbin axis but at different radial distances, in order to provide temperature data during the drying process. In cross circulation drying, plots of temperature against time indicated the presence of two moving fronts, one starting from inside the bobbin, another from the outside, while in through circulation drying, similar plots showed the presence of an evaporation front, moving from inside the bobbin to the outside. In both canes, numerical models were developed to simulate the drying processes.     

Early-Life Development of the Bifidobacterial Community in the Infant Gut

The establishment of the gut microbiota poses implications for short and long-term health. Bifidobacterium is an important taxon in early life, being one of the most abundant genera in the infant intestinal microbiota and carrying out key functions for maintaining host-homeostasis. Recent metagenomic studies have shown that different factors, such as gestational age, delivery mode, or feeding habits, affect the gut microbiota establishment at high phylogenetic levels. However, their impact on the specific bifidobacterial populations is not yet well understood. Here we studied the impact of these factors on the different Bifidobacterium species and subspecies at both the quantitative and qualitative levels. Fecal samples were taken from 85 neonates at 2, 10, 30, 90 days of life, and the relative proportions of the different bifidobacterial populations were assessed by 16S rRNA–23S rRNA internal transcribed spacer (ITS) region sequencing. Absolute levels of the main species were determined by q-PCR. Our results showed that the bifidobacterial population establishment is affected by gestational age, delivery mode, and infant feeding, as it is evidenced by qualitative and quantitative changes. These data underline the need for understanding the impact of perinatal factors on the gut microbiota also at low taxonomic levels, especially in the case of relevant microbial populations such as Bifidobacterium. The data obtained provide indications for the selection of the species best suited for the development of bifidobacteria-based products for different groups of neonates and will help to develop rational strategies for favoring a healthy early microbiota development when this process is challenged.     

Improving retrieval accuracy of Hierarchical Cellular Trees for generic metric spaces

Metric Access Methods (MAMs) are indexing techniques which allow working in generic metric spaces. Therefore, MAMs are specially useful for Content-Based Image Retrieval systems based on features which use non L _p norms as similarity measures. MAMs naturally allow the design of image browsers due to their inherent hierarchical structure. The Hierarchical Cellular Tree (HCT), a MAM-based indexing technique, provides the starting point of our work. In this paper, we describe some limitations detected in the original formulation of the HCT and propose some modifications to both the index building and the search algorithm. First, the covering radius, which is defined as the distance from the representative to the furthest element in a node, may not cover all the elements belonging to the node’s subtree. Therefore, we propose to redefine the covering radius as the distance from the representative to the furthest element in the node’s subtree. This new definition is essential to guarantee a correct construction of the HCT. Second, the proposed Progressive Query retrieval scheme can be redesigned to perform the nearest neighbor operation in a more efficient way. We propose a new retrieval scheme which takes advantage of the benefits of the search algorithm used in the index building. Furthermore, while the evaluation of the HCT in the original work was only subjective, we propose an objective evaluation based on two aspects which are crucial in any approximate search algorithm: the retrieval time and the retrieval accuracy. Finally, we illustrate the usefulness of the proposal by presenting some actual applications.     

Spike train decoding without spike sorting

We propose a novel paradigm for spike train decoding, which avoids entirely spike sorting based on waveform measurements. This paradigm directly uses the spike train collected at recording electrodes from thresholding the bandpassed voltage signal. Our approach is a paradigm, not an algorithm, since it can be used with any of the current decoding algorithms, such as population vector or likelihood-based algorithms. Based on analytical results and an extensive simulation study, we show that our paradigm is comparable to, and sometimes more efficient than, the traditional approach based on well-isolated neurons and that it remains efficient even when all electrodes are severely corrupted by noise, a situation that would render spike sorting particularly difficult. Our paradigm will also save time and computational effort, both of which are crucially important for successful operation of real-time brain-machine interfaces. Indeed, in place of the lengthy spike-sorting task of the traditional approach, it involves an exact expectation EM algorithm that is fast enough that it could also be left to run during decoding to capture potential slow changes in the states of the neurons.