A non-invasive method for in situ quantification of subpopulation behaviour in mixed cell culture.

Ongoing advances in quantitative molecular- and cellular-biology highlight the need for correspondingly quantitative methods in tissue-biology, in which the presence and activity of specific cell-subpopulations can be assessed in situ. However, many experimental techniques disturb the natural tissue balance, making it difficult to draw realistic conclusions concerning in situ cell behaviour. In this study, we present a widely applicable and minimally invasive method which combines fluorescence cell labelling, retrospective image analysis and mathematical data processing to detect the presence and activity of cell subpopulations, using adhesion patterns in STRO-1 immunoselected human mesenchymal populations and the homogeneous osteoblast-like MG63 continuous cell line as an illustration. Adhesion is considered on tissue culture plastic and fibronectin surfaces, using cell area as a readily obtainable and individual cell specific measure of spreading. The underlying statistical distributions of cell areas are investigated and mappings between distributions are examined using a combination of graphical and non-parametric statistical methods. We show that activity can be quantified in subpopulations as small as 1% by cell number, and outline behaviour of significant subpopulations in both STRO-1+/- fractions. This method has considerable potential to understand in situ cell behaviour and thus has wide applicability, for example in developmental biology and tissue engineering.     

A self-learning fuzzy discrete event system for HIV/AIDS treatment regimen selection.

The U.S. Department of Health and Human Services Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) treatment guidelines are modified several times per year to reflect the rapid evolution of the field (e.g., emergence of new antiretroviral drugs). As such, a treatment-decision support system that is capable of self-learning is highly desirable. Based on the fuzzy discrete event system (FDES) theory that we recently created, we have developed a self-learning HIV/AIDS regimen selection system for the initial round of combination antiretroviral therapy, one of the most complex therapies in medicine. The system consisted of a treatment objectives classifier, fuzzy finite state machine models for treatment regimens, and a genetic-algorithm-based optimizer. Supervised learning was achieved through automatically adjusting the parameters of the models by the optimizer. We focused on the four historically popular regimens with 32 associated treatment objectives involving the four most important clinical variables (potency, adherence, adverse effects, and future drug options). The learning targets for the objectives were produced by two expert AIDS physicians on the project, and their averaged overall agreement rate was 70.6%. The system's learning ability and new regimen suitability prediction capability were tested under various conditions of clinical importance. The prediction accuracy was found between 84.4% and 100%. Finally, we retrospectively evaluated the system using 23 patients treated by 11 experienced nonexpert faculty physicians and 12 patients treated by the two experts at our AIDS Clinical Center in 2001. The overall exact agreement between the 13 physicians' selections and the system's choices was 82.9% with the agreement for the two experts being both 100%. For the seven mismatched cases, the system actually chose more appropriate regimens in four cases and equivalent regimens in another two cases. It made a mistake in one case. These (preliminary) results show that 1) the System outperformed the nonexpert physicians and 2) it performed as well as the expert physicians did. This learning and prediction approach, as well as our original FDESs theory, is general purpose and can be applied to other medical or nonmedical problems.     

关于MES性能与应用的疑惑、诀窍和前景

文献报道了MES的许多优点,也提到其性质上可能存在的某些缺点。比如,研究表明纯组分MES的浊点高于其他阴离子表面活性剂,于是怀疑MES的溶解性可能会限制其在冷水中的洗涤。再则,MES的水解稳定性低于其他阴离子表面活性剂,这可能是MES的另一个主要缺点。拟探讨这些问题,并将提出一些证据,以表明MES实际上是一种卓越的表面活性剂,完全可以配方出适用于低温洗涤的洗涤剂产品。介绍了一些采用MES为主要表面活性剂生产洗衣粉和液洗剂的工艺。     

Application of numerical methods for predicting energy transport in earth contact systems

Methods for analysing conductive heat flow with applications to underground earth contact systems are reviewed. A discussion and comparison of both the finite difference and finite element methods are presented. The effect of domain discretisation on accuracy for both methods is presented. One- and two-dimensional models are derived and used to solve selected problems. The results for various discretisation domains are compared and constrasted. The application of both the finite difference and finite element approaches to the analysis of heat transfers in an underground building is given. Recommendations are made to aid in the selection of the numerical techniques that are the most appropriate for analysing conductive heat flow problems. Finally, a statement is made on the analysis of the three-dimensional heat and moisture transport problem associated with underground earth contact systems.     

A biotelemetry system for monitoring heart rates in unrestrained ungulates

An EKG telemetry system has been designed for use on free-living ungulates. An FM transmitter with a battery life of 2 +/-0.5 months and a range of 2-6 km is mounted on the back of the animal by means of an adjustable harness. The EKG signal is detected by subdermal electrodes overlying the sternum and transmitted to an FM receiver equipped with a frequency down-converter. The output of the receiver is the modulated audio carrier which is recorded on magnetic tape. The EKG waveform is recovered from the tape-recorded signal using an FM demodulator connected to a strip chart recorder.     

SIMULATION MODELING FOR BPR Steps to Effective Decision Support

Simulation modeling can be used to assess the potential value and feasibility of alternative designs, providing an objective basis for the redesign decision making inherent in BPR. This article presents an eight-step approach to help structure the myriad management considerations critical to an effective, goal-driven simulation, and reviews modeling simulation's potential to stimulate ongoing organizational self-improvement and analysis.     

A new approach for nonlinear process identification using orthonormal bases and ordinal splines

A new gray-box method for nonlinear process identification is presented. Industrial deployment for model predictive control (MPC) is the primary focus of this development. For flexibility, the identification accommodates Hammerstein, Wiener and the more general N–L–N block-oriented structures. Instruments comprised of linear and nonlinear combinations of inputs and outputs are also accommodated. Unique to this approach is the utilization of two sets of bases. One is constructed using an estimate of the process poles and the other is constructed using a predefined set of special cubic splines. An intriguing aspect of this formulation is that nonlinear dynamics are implicitly accommodated. In addition, problems associated with identifying the linear portion of the model in conventional block oriented formulations are removed. Because of the bases formulation, it is possible to solve the identification problem for many supported structures by convex optimization and hence avoid the inherent problems of iterative solutions. To insure open-loop unbiased estimates, any structures using output nonlinearities do require an iterative solution. Two test cases from the open literature are presented as are results from plant step-test data on a problematic air separation unit.