Quantifying the limits of CAR T-cell delivery in mice and men

CAR (Chimeric Antigen Receptor) T cells have demonstrated clinical success for the treatment of multiple lymphomas and leukaemias, but not for various solid tumours, despite promising data from murine models. Lower effective CAR T-cell delivery rates to human solid tumours compared to haematological malignancies in humans and solid tumours in mice might partially explain these divergent outcomes. We used anatomical and physiological data for human and rodent circulatory systems to calculate the typical perfusion of healthy and tumour tissues, and estimated the upper limits of immune cell delivery rates across different organs, tumour types and species. Estimated maximum delivery rates were up to 10 000-fold greater in mice than humans yet reported CAR T-cell doses are typically only 10–100-fold lower in mice, suggesting that the effective delivery rates of CAR T cells into tumours in clinical trials are far lower than in corresponding mouse models. Estimated delivery rates were found to be consistent with published positron emission tomography data. Results suggest that higher effective human doses may be needed to drive efficacy comparable to mouse solid tumour models, and that lower doses should be tested in mice. We posit that quantitation of species and organ-specific delivery and homing of engineered T cells will be key to unlocking their potential for solid tumours.     

把DAC的输出从单端模式转换到差分模式的电路

高速DAC,比如模拟器件(AnalogDevices)公司的AD9776/78/79TxDAC系列,能提供差分输出,但对于低端交流电应用或高精度电平设置应用,配备差分转换电路的单端电流输出DAC提供了一种新颖的方法来生成差分波形控制功能。图1中的基本电路组合了电流输出DAC(即IC1,如8位AD5424D A C)和一个单端至差分运算放大级IC2、IC3A、IC3B——来产生要求的输出。对于双电源应用,可选择DAC的单极工作模式来达到DAC的最优性能。DAC利用单一运算放大器提供了双象限倍增或单极输出电压摆动。DAC的输出需要缓冲器,这是因为对施加到DAC输入端的代…     

Maximum Cardinality Search for Computing Minimal Triangulations of Graphs

We present a new algorithm, called MCS-M, for computing minimal triangulations of graphs. Lex-BFS, a seminal algorithm for recognizing chordal graphs, was the genesis for two other classical algorithms: LEX M and MCS. LEX M extends the fundamental concept used in Lex-BFS, resulting in an algorithm that not only recognizes chordality, but also computes a minimal triangulation of an arbitrary graph. MCS simplifies the fundamental concept used in Lex-BFS, resulting in a simpler algorithm for recognizing chordal graphs. The new algorithm MCS-M combines the extension of LEX M with the simplification of MCS, achieving all the results of LEX M in the same time complexity.     

Eddy current measurements of electrical conductivity and magnetic permeability of porous metals

This paper presents a method, which simultaneously estimates the electrical conductivity and magnetic permeability of porous metals. Porous Cu and Fe manufactured by the lost carbonate sintering process have been tested. An air-cored solenoid coil was designed for the measurements of rod-shaped samples when inserted coaxially with the coil. It was theoretically found that the phase-frequency response of the normalised eddy current signal of the coil is virtually independent of the radius, electrical conductivity and magnetic permeability of the test samples. For non-magnetic, conductive porous Cu, the electrical conductivity was measured with a calibration curve of the coil relating the impedance change and the electrical conductivity of the sample. For magnetic porous Fe, the imaginary part of the signal at the lowest frequencies can be used to estimate the permeability. The measured conductivity values of the porous Cu are shown in the paper in comparison with that of bulk materials with known conductivity. The measured permeability values of the porous Fe are given and the sample-length effect on the measurements is also discussed.     

Moving from the Consortium to the Reference Desk: Keeping Chat and Improving Reference at the MSU Libraries

The experience of the Mississippi State University (MSU) Libraries illustrates the challenges presented by moving from consortial to local chat, as well as an evaluation of the advantages of chat reference in an academic setting. Countering the consortial, instant-messaging model prevalent in virtual reference today, the MSU Libraries have found chat offers advantages in an academic community. Moving to a local setting, it was possible for the MSU Libraries to maintain quality control over chat transactions while building relationships with faculty and students across campus.     

New integer linear programming approaches for course timetabling

The most complete form of academic timetabling problem is the population and course timetabling problem. In this problem, there may be multiple classes of each subject, and the decision on which students are to constitute each class is made in concert with the decision on the timetable for each class. In order to solve this problem, it is normally simplified or decomposed in some fashion. One simplification commonly used in practice is known as blocking: it is assumed that the classes can be partitioned into sets of classes (or blocks) that will be timetabled in parallel. This restricts clashing to occur only between classes in the same block, and essentially removes the timetabling aspect of the problem, which can be carried out once the blocks are constituted and the classes populated. The problem of constituting the blocks and populating the classes, known as the course blocking and population problem, is nevertheless a challenging problem, and provides the focus of this paper. We demonstrate, using data provided by a local high school, that integer linear programming approaches can solve the problem in a matter of seconds. Key features include remodelling to remove symmetry caused by students with identical subject selection, and the observation that in practice, only integrality of the block composition variables needs to be enforced; the class population aspects of the model have strong integrality properties.     

Business process management with the user requirements notation

A number of recent initiatives in both academia and industry have sought to achieve improvements in e-businesses through the utilization of Business Process Management (BPM) methodologies and tools. However there are still some inadequacies that need to be addressed when it comes to achieving alignment between business goals and business processes. The User Requirements Notation (URN), recently standardized by ITU-T, has some unique features and capabilities beyond what is available in other notations that can help address alignment issues. In this paper, a URN-based framework and its supporting toolset are introduced which provide business process monitoring and performance management capabilities integrated across the BPM lifecycle. The framework extends the URN notation with Key Performance Indicators (KPIs) and other concepts to measure and align processes and goals. An example process for controlling access to a healthcare data warehouse is used to illustrate and evaluate the framework. Early results indicate the feasibility of the approach.     

Collaborative writing in multiple discourse contexts

Research in computer-supported writing has traditionally compared electronic communication with oral, face-to-face communication to identify the benefits and weaknesses of each, as if they entailed dichotomous choices. In this article, we challenge that view and argue instead that any form of communication and its educational usefulness is shaped by the situation in which it is used, the backgrounds and goals of the participants, the institutional and technological setup, and the intended purpose of the medium. Three modes of communication in one graduate course are examined — oral discussion, synchronous written discussion on a local area network, and asynchronous written postings on an email list set up for the class. It was found that patterns of participation, topic introduction, and topic development differed across the three communication modes, but that the three were interwoven with each other and embedded within the larger classroom context and forms of knowledge creation in the class. Thus, rather than examining different communication media separately, researchers interested in understanding computer-supported collaborative writing need to look at how different media are used to create a meta-medium, which is established by the discourse community involved.     

Hidden Markov models for the stimulus-response relationships of multistate neural systems

Given recent experimental results suggesting that neural circuits may evolve through multiple firing states, we develop a framework for estimating state-dependent neural response properties from spike train data. We modify the traditional hidden Markov model (HMM) framework to incorporate stimulus-driven, non-Poisson point-process observations. For maximal flexibility, we allow external, time-varying stimuli and the neurons' own spike histories to drive both the spiking behavior in each state and the transitioning behavior between states. We employ an appropriately modified expectation-maximization algorithm to estimate the model parameters. The expectation step is solved by the standard forward-backward algorithm for HMMs. The maximization step reduces to a set of separable concave optimization problems if the model is restricted slightly. We first test our algorithm on simulated data and are able to fully recover the parameters used to generate the data and accurately recapitulate the sequence of hidden states. We then apply our algorithm to a recently published data set in which the observed neuronal ensembles displayed multistate behavior and show that inclusion of spike history information significantly improves the fit of the model. Additionally, we show that a simple reformulation of the state space of the underlying Markov chain allows us to implement a hybrid half-multistate, half-histogram model that may be more appropriate for capturing the complexity of certain data sets than either a simple HMM or a simple peristimulus time histogram model alone.     

Selecting critical patterns based on local geometrical and statistical information

Pattern selection methods have been traditionally developed with a dependency on a specific classifier. In contrast, this paper presents a method that selects critical patterns deemed to carry essential information applicable to train those types of classifiers which require spatial information of the training data set. Critical patterns include those edge patterns that define the boundary and those border patterns that separate classes. The proposed method selects patterns from a new perspective, primarily based on their location in input space. It determines class edge patterns with the assistance of the approximated tangent hyperplane of a class surface. It also identifies border patterns between classes using local probability. The proposed method is evaluated on benchmark problems using popular classifiers, including multilayer perceptrons, radial basis functions, support vector machines, and nearest neighbors. The proposed approach is also compared with four state-of-the-art approaches and it is shown to provide similar but more consistent accuracy from a reduced data set. Experimental results demonstrate that it selects patterns sufficient to represent class boundary and to preserve the decision surface.