Patient-specific quality assurance and plan dose errors on breast intensity-modulated proton therapy

PurposeTo investigate, in proton therapy, whether the Gamma passing rate (GPR) is related to the patient dose error and whether MU scaling can improve dose accuracy.MethodsAmong 20 consecutively treated breast patients selected for analysis, two IMPT plans were retrospectively generated: (1) the pencil-beam (PB) plan and (2) the Monte Carlo (MC) plan. Patient-specific QA was performed. A 3%/3-mm Gamma analysis was conducted to compare the TPS-calculated PB algorithm dose distribution with the measured 2D dose. Dose errors were compared between the plans that passed the Gamma testing and those that failed. The MU was then scaled to obtain a better GPR. MU-scaled PB plan dose errors were compared to the original PB plan.ResultsOf the 20 PB plans, 8 were passed Gamma testing (G_pass_group) and 12 failed (G_fail_group). Surprisingly, the G_pass_group had a greater dose error than the G_fail_group. The median (range) of the PTV DVH RMSE and PTV ΔDmean were 1.36 (1.00–1.91) Gy vs 1.18 (1.02–1.80) Gy and 1.23 (0.92–1.71) Gy vs 1.10 (0.87–1.49) Gy for the G_pass_group and the G_fail_group, respectively. MU scaling reduced overall dose error. However, for PTV D99 and D95, MU scaling worsened some cases.ConclusionFor breast IMPT, the PB plans that passed the Gamma testing did not show smaller dose errors compared to the plans that failed. For individual plans, the MU scaling technique leads to overall smaller dose errors. However, we do not suggest use of the MU scaling technique to replace the MC plans when the MC algorithm is available.     

Computer-Aided Topological Analysis of the Faujasite Lattice I: Exact Solution for Zeolite-X

Abstract

In order to study the possible configurations of Aluminum and Silicon atoms on a Faujasite lattice, two different methods of analysis are presented. The first method is based on the study of the physical properties of different lattice structures: the energy and the dipolar moment. The second one examines the topological properties of the configurations in order to count the inequivalent lattice structures. An original algorithm selects the configurations to be generated and compared in order to keep the computer time required at an acceptable level. The results from the two methods are compared and found to be in agreement.

In this paper we specialize our study to zeolite-X but the methods are general and can be applied to other types of lattices.     

Analyzing Taylor’s Scaling Law: qualitative differences of social and territorial behavior on colonization/extinction dynamics

The power law relation between the mean population count and its variance (Taylor’s Power Law, TPL) is among the few general patterns in population ecology. While the TPL has been described to be pervasive across taxa, the causes of variation of the exponent describing this relation is not well understood. We compare the TPL exponents for two species with different social systems and behavior: Piñon jays (Gymnorhinus cyanocephalus) and Western scrub-jays (Aphelocoma californica). We analyze the underlying processes that generate the expected values of population size and its variance. Using a probabilistic model, we identify and estimate important processes involved in the generation of the TPL exponents. While both species show a scaling relationship between their mean and abundance, share a common negative relation between mean abundance and colonization–extinction rates, they differ greatly in the statistical distributions of colonization, extinction, the mean number of colonists, the probability of zero abundance and population sizes. We show how different aspects of the processes that generate abundance affect the TPL exponent, thereby providing empirical guidelines to interpret differences in the scaling relation between mean and variance of population size.     

Behavior of Slaughter Plant and Auction Employees Toward the Animals

Abstract

Abuses of animals at auctions and slaughter plants occur often. Commonly observed abuses include the dragging of crippled animals, hitting, and excessive prodding of animals. In both auctions and slaughter plants, employees are under pressure to maintain a steady flow of animals to the auction ring or slaughter lines. In both types of facilities large numbers of animals must be moved rapidly. The purpose of this study was to determine the behavior of people handling livestock in these types of facilities. Observations of the behavior of slaughter plant managers were also made to gain a better understanding of how management behavior affects employee behavior.     

Quantitative Evaluation of the Clinical Effects of S-Adenosylmethionine on Mood and Behavior in Lesch-Nyhan Patients

Background, rationale, and methods . Lesch-Nyhan disease is a rare, X-linked disorder due to hypoxanthine phosphoribosyltransferase deficiency. To evaluate reported benefit on mood and behavior obtained by the administration of S-adenosyl-l-methionine in this condition, we developed 2 quantitative evaluation tools, and used them to assess the effects of the drug in our population: the weekly questionnaire and the resistance to self-injurious behavior test. We performed an open-label, dose-escalation trial of the drug on 14 patients.

Results. Four patients tolerated the drug and reported beneficial effects. The majority experienced worsened behavior. The 2 assessment tools demonstrated effectiveness in quantitatively evaluating the self-injurious behavior.     

Generalised Sandpile Dynamics on Artificial and Real-World Directed Networks

The main finding of this paper is a novel avalanche-size exponent τ ≈ 1.87 when the generalised sandpile dynamics evolves on the real-world Japanese inter-firm network. The topology of this network is non-layered and directed, displaying the typical bow tie structure found in real-world directed networks, with cycles and triangles. We show that one can move from a strictly layered regular lattice to a more fluid structure of the inter-firm network in a few simple steps. Relaxing the regular lattice structure by introducing an interlayer distribution for the interactions, forces the scaling exponent of the avalanche-size probability density function τ out of the two-dimensional directed sandpile universality class τ = 4/3, into the mean field universality class τ = 3/2. Numerical investigation shows that these two classes are the only that exist on the directed sandpile, regardless of the underlying topology, as long as it is strictly layered. Randomly adding a small proportion of links connecting non adjacent layers in an otherwise layered network takes the system out of the mean field regime to produce non-trivial avalanche-size probability density function. Although these do not display proper scaling, they closely reproduce the behaviour observed on the Japanese inter-firm network.     

Fluctuation Scaling,Taylor’s Law,and Crime

Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor’s law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor’s law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057±0.026) while burglary exhibited a greater exponent (α = 1.292±0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor’s law exponents from 1.43±0.12 (Drugs) to 2.094±0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation.     

Genomic duplication problems for unrooted gene trees

Background

Discovering the location of gene duplications and multiple gene duplication episodes is a fundamental issue in evolutionary molecular biology. The problem introduced by Guigó et al. in 1996 is to map gene duplication events from a collection of rooted, binary gene family trees onto theirs corresponding rooted binary species tree in such a way that the total number of multiple gene duplication episodes is minimized. There are several models in the literature that specify how gene duplications from gene families can be interpreted as one duplication episode. However, in all duplication episode problems gene trees are rooted. This restriction limits the applicability, since unrooted gene family trees are frequently inferred by phylogenetic methods.

Results

In this article we show the first solution to the open problem of episode clustering where the input gene family trees are unrooted. In particular, by using theoretical properties of unrooted reconciliation, we show an efficient algorithm that reduces this problem into the episode clustering problems defined for rooted trees. We show theoretical properties of the reduction algorithm and evaluation of empirical datasets.

Conclusions

We provided algorithms and tools that were successfully applied to several empirical datasets. In particular, our comparative study shows that we can improve known results on genomic duplication inference from real datasets.

     

A Parallel Algorithm for Nonequilibrium Molecular Dynamics Simulation of Shear Flow on Distributed Memory Machines

Abstract

An algorithm is described which allows Nonequilibrium Molecular Dynamics (NEMD) simulations of a fluid undergoing planar Couette flow (shear flow) to be carried out on a distributed memory parallel processor using a (spatial) domain decomposition technique. Unlike previous algorithms, this algorithm uses a co-moving, or Lagrangian, simulation box. Also, the shape of the simulation box changes throughout the course of the simulation. The algorithm, which can be used for two or three dimensional systems, has been tested on a Fujitsu AP1000 Parallel computer with 128 processors.     

Scalable optimal Bayesian classification of single-cell trajectories under regulatory model uncertainty

Background

Biological networks describes the mechanisms which govern cellular functions. Temporal networks show how these networks evolve over time. Studying the temporal progression of network topologies is of utmost importance since it uncovers how a network evolves and how it resists to external stimuli and internal variations. Two temporal networks have co-evolving subnetworks if the evolving topologies of these subnetworks remain similar to each other as the network topology evolves over a period of time. In this paper, we consider the problem of identifying co-evolving subnetworks given a pair of temporal networks, which aim to capture the evolution of molecules and their interactions over time. Although this problem shares some characteristics of the well-known network alignment problems, it differs from existing network alignment formulations as it seeks a mapping of the two network topologies that is invariant to temporal evolution of the given networks. This is a computationally challenging problem as it requires capturing not only similar topologies between two networks but also their similar evolution patterns.

Results

We present an efficient algorithm, Tempo, for solving identifying co-evolving subnetworks with two given temporal networks. We formally prove the correctness of our method. We experimentally demonstrate that Tempo scales efficiently with the size of network as well as the number of time points, and generates statistically significant alignments—even when evolution rates of given networks are high. Our results on a human aging dataset demonstrate that Tempo identifies novel genes contributing to the progression of Alzheimer’s, Huntington’s and Type II diabetes, while existing methods fail to do so.

Conclusions

Studying temporal networks in general and human aging specifically using Tempo enables us to identify age related genes from non age related genes successfully. More importantly, Tempo takes the network alignment problem one huge step forward by moving beyond the classical static network models.

     

Capturing the bursting dynamics of a two-cell inhibitory network using a one-dimensional map

Out-of-phase bursting is a functionally important behavior displayed by central pattern generators and other neural circuits. Understanding this complex activity requires the knowledge of the interplay between the intrinsic cell properties and the properties of synaptic coupling between the cells. Here we describe a simple method that allows us to investigate the existence and stability of anti-phase bursting solutions in a network of two spiking neurons, each possessing a T-type calcium current and coupled by reciprocal inhibition. We derive a one-dimensional map which fully characterizes the genesis and regulation of anti-phase bursting arising from the interaction of the T-current properties with the properties of synaptic inhibition. This map is the burst length return map formed as the composition of two distinct one-dimensional maps that are each regulated by a different set of model parameters. Although each map is constructed using the properties of a single isolated model neuron, the composition of the two maps accurately captures the behavior of the full network. We analyze the parameter sensitivity of these maps to determine the influence of both the intrinsic cell properties and the synaptic properties on the burst length, and to find the conditions under which multistability of several bursting solutions is achieved. Although the derivation of the map relies on a number of simplifying assumptions, we discuss how the principle features of this dimensional reduction method could be extended to more realistic model networks. Action Editor: John Rinzel     

Probing the Average Local Structure of Biomolecules Using Small-Angle Scattering and Scaling Laws

Small-angle neutron and x-ray scattering have become invaluable tools for probing the nanostructure of molecules in solution. It was recently shown that the definite integral of the scattering profile exhibits a scaling (power-law) behavior with respect to molecular mass. We derive the origin of this relationship, and discuss how the integrated scattering profile can be used to identify differing levels of disorder over local ?30 Å length scales. We apply our analysis to globular and intrinsically disordered proteins.     

Dynamical modeling of collective behavior from pigeon flight data: flock cohesion and dispersion

Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons, and how it is affected by changing the initial conditions of the system. Our results demonstrate that this approach may be applied to construct models capable of simulating trajectories and collective dynamics using experimental field measurements of herd movement. From these models, the behavior of the individual agents (animals) may be inferred.     

趋流行为下斑马鱼幼鱼的全脑成像

目的 趋流,意即在水中调整身体方向并逆流而上的能力,是一种在大多数鱼类与两栖类动物中存在的保守行为。虽然关于趋流的研究已有一段很长的历史,并且近年来斑马鱼幼鱼趋流行为的理论机制也被提出,但是分布式的神经环路是如何整合多感知信息、做出决策、并实现行为控制仍然是个未知数。对自由运动的斑马鱼进行全脑神经活动成像为理解这一困难的问题提供了特殊的机会。方法 本文开发了一种微流控装置精确控制环境水流并激发斑马鱼的趋流行为。将该微流控芯片与扩增视野光场显微镜以及追踪系统整合,从而记录自由行为下斑马鱼全脑的神经活动。结果 在整合的微流控装置中稳定观察到了斑马鱼在水流中保持自身位置不变、逆流而上等刻板的趋流行为现象。与此同时,实现了对斑马鱼幼鱼趋流行为过程中的全脑钙活动记录。本文初步发现了几个脑区的神经活动与趋流行为相关。结论 本研究第一次展示了在斑马鱼幼鱼趋流行为的同时记录全脑神经活动的技术。接下来对神经活动和行为数据的分析与建模将有助于更好地理解一种重要自然行为背后的感觉运动转换机制。     

Accelerating multiple replica molecular dynamics simulations using the Intel® Xeon Phi™ coprocessor

We investigate the performance increase provided by the Intel^® Xeon Phi? coprocessor in multiple replica molecular dynamics applications using a novel parallelisation scheme. The benefits of the proposed parallelisation scheme are demonstrated by glycine in water, a system of significant interest in the crystallisation simulation community. The molecular dynamics (MD) engine consists of initially serial LAMMPS and NAMD subroutines, and is subsequently modified and parallelised using a heterogeneous programming model, where each MPI rank is paired with a unique Intel^® Xeon Phi? coprocessor and CPU socket. The MD engine is parallelised using an OpenMP atom domain decomposition algorithm on the Intel^® Xeon Phi? coprocessor and OpenMP task parallelism on the host CPU socket. Using nodes with two Intel^® Xeon Phi? coprocessors, one per socket, we demonstrate that a factor of five reduction in the required computational resources is achieved per replica with the coprocessor, when compared against employing the standard spatial domain decomposition algorithm with no accelerator. Furthermore, the proposed parallelisation scheme achieves ideal weak scaling with respect to the number of employed MPI ranks (replicas). The Intel^® Xeon Phi? coprocessor not only allows us to the increase performance output per socket by a factor of five, when compared against no accelerators, but also significantly reduces the parallelisation complexity necessary to achieve this performance, as the Intel^® Xeon Phi? coprocessor operates using the simple OpenMP programming language.     

Precision of allometric scaling equations for trees can be improved by including the effect of ecological interactions

Allometric scaling relationships of the form Y = aX ^b are widely utilized in many types of models and analyses of tree structure. They are often viewed as static relationships where both the scaling exponent (b) and the normalization constant (a) obtain empirical values that are fixed within a single set of data. Among different sets of data, their values can show environmental variability. However, there have been only few attempts to give a mechanistic interpretation for this variability. We used field data to demonstrate how the scaling relationships in trees can be modified by ecological interactions. Moreover, we show how such processes can be incorporated into the scaling models to improve the fit and the information content of the scaling equations. When fixed theoretical scaling exponents were used instead of empirical exponents and when the effect of competitive interactions between trees was described by separate submodels that predicted the value of the normalisation constant in the scaling equations, it was possible to obtain 4–10% improvement in the model fit of three different structural scaling relationships. Our results suggest that unexplained variation in the values of the scaling parameters can be substituted by an identified effect of ecological factors on the value of the normalisation constant. This agrees with recent theoretical suggestions stating that ecological factors can directly influence the value of normalisation constants.     

Investigation of the XCAT phantom as a validation tool in cardiac MRI tracking algorithms

PurposeTo describe our magnetic resonance imaging (MRI) simulated implementation of the 4D digital extended cardio torso (XCAT) phantom to validate our previously developed cardiac tracking techniques. Real-time tracking will play an important role in the non-invasive treatment of atrial fibrillation with MRI-guided radiosurgery. In addition, to show how quantifiable measures of tracking accuracy and patient-specific physiology could influence MRI tracking algorithm design.MethodsTwenty virtual patients were subjected to simulated MRI scans that closely model the proposed real-world scenario to allow verification of the tracking technique’s algorithm. The generated phantoms provide ground-truth motions which were compared to the target motions output from our tracking algorithm. The patient-specific tracking error, e_p, was the 3D difference (vector length) between the ground-truth and algorithm trajectories. The tracking errors of two combinations of new tracking algorithm functions that were anticipated to improve tracking accuracy were studied. Additionally, the correlation of key physiological parameters with tracking accuracy was investigated.ResultsOur original cardiac tracking algorithm resulted in a mean tracking error of 3.7 ± 0.6 mm over all virtual patients. The two combinations of tracking functions demonstrated comparable mean tracking errors however indicating that the optimal tracking algorithm may be patient-specific.ConclusionsCurrent and future MRI tracking strategies are likely to benefit from this virtual validation method since no time-resolved 4D ground-truth signal can currently be derived from purely image-based studies.     

The observed range for temporal mean-variance scaling exponents can be explained by reproductive correlation

The mean-variance scaling relationship known as Taylor's power law has been well documented empirically over the past four decades but a general theoretical explanation for the phenomenon does not exist. Here we provide an explanation that relates empirical patterns of temporal mean-variance scaling to individual level reproductive behavior. Initially, we review the scaling behavior of population growth models to establish theoretical limits for the scaling exponent b that is in agreement with the empirically observed range (1≤b≤2). We go on to show that the degree of reproductive covariance among individuals determines the scaling exponent b. Independent reproduction results in an exponent of one, while completely correlated reproduction results in the upper limit of two. Intermediate exponents, which are common empirically, can be generated through the decay of reproductive covariance with increasing population size. Finally, we describe how the link between reproductive correlation and the scaling exponent provides a way to infer properties of individual-level reproductive behavior, such as the relative influence of demographic stochasticity, from a macroecological pattern.     

Probing the Average Local Structure of Biomolecules Using Small-Angle Scattering and Scaling Laws

Small-angle neutron and x-ray scattering have become invaluable tools for probing the nanostructure of molecules in solution. It was recently shown that the definite integral of the scattering profile exhibits a scaling (power-law) behavior with respect to molecular mass. We derive the origin of this relationship, and discuss how the integrated scattering profile can be used to identify differing levels of disorder over local ≲30 Å length scales. We apply our analysis to globular and intrinsically disordered proteins.     

Irreversibility and Interatomic Potentials in One-dimensional Lattice Models

Abstract

Since the computational work on the relaxation process toward the equilibrium state by Fermi, Pasta, and Ulam (FPU) [1], the stochastic behaviors in one dimensional lattice models have been studied by many physicists numerically and theoretically. The objective of those studies is to understand the origin of thermodynamical properties from the microscopic particle motions which are determined by the deterministic equations of motion. In the FPU work, since the given energy was too small and anharmonicity was too weak, thermodynamic irreversibility phenomena, which lead to the equipartition of energy among modes, were not observed. Many studies after this work confirmed the existence of the threshold for the chaotic motions [2] [3]. However, the relation of the chaotic motion in the system with many degrees of freedom to the thermodynamical properties is not well understood [4]. The steady lattice thermal conduction in one dimensional lattice poses an interesting problem in this; respect. A clear linear internal temperature gradient was not observed in the FPU model [5], while it was observed in the the ding-a-ling model by Casati et al. [6] and the diatomic Toda lattice (DTL) by Mokross and Büttner [7]. Recently, the system size dependence of the coefficient of thermal conductivity has been studied [8][9] and the Fourier's law of heat conduction is begining to be confirmed in the DTL.