MHC Class II Transactivator Is an In Vivo Regulator of Osteoclast Differentiation and Bone Homeostasis Co-opted From Adaptive Immunity.

The molecular networks controlling bone homeostasis are not fully understood. The common evolution of bone and adaptive immunity encourages the investigation of shared regulatory circuits. MHC Class II Transactivator (CIITA) is a master transcriptional co-activator believed to be exclusively dedicated for antigen presentation. CIITA is expressed in osteoclast precursors, and its expression is accentuated in osteoporotic mice. We thus asked whether CIITA plays a role in bone biology. To this aim, we fully characterized the bone phenotype of two mouse models of CIITA overexpression, respectively systemic and restricted to the monocyte-osteoclast lineage. Both CIITA-overexpressing mouse models revealed severe spontaneous osteoporosis, as assessed by micro-computed tomography and histomorphometry, associated with increased osteoclast numbers and enhanced in vivo bone resorption, whereas osteoblast numbers and in vivo bone-forming activity were unaffected. To understand the underlying cellular and molecular bases, we investigated ex vivo the differentiation of mutant bone marrow monocytes into osteoclasts and immune effectors, as well as osteoclastogenic signaling pathways. CIITA-overexpressing monocytes differentiated normally into effector macrophages or dendritic cells but showed enhanced osteoclastogenesis, whereas CIITA ablation suppressed osteoclast differentiation. Increased c-fms and receptor activator of NF-κB (RANK) signaling underlay enhanced osteoclast differentiation from CIITA-overexpressing precursors. Moreover, by extending selected phenotypic and cellular analyses to additional genetic mouse models, namely MHC Class II deficient mice and a transgenic mouse line lacking a specific CIITA promoter and re-expressing CIITA in the thymus, we excluded MHC Class II expression and T cells from contributing to the observed skeletal phenotype. Altogether, our study provides compelling genetic evidence that CIITA, the molecular switch of antigen presentation, plays a novel, unexpected function in skeletal homeostasis, independent of MHC Class II expression and T cells, by exerting a selective and intrinsic control of osteoclast differentiation and bone resorption in vivo. © 2014 American Society for Bone and Mineral Research.

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

HIV-1 vaccines and adaptive trial designs.

Developing a vaccine against the human immunodeficiency virus (HIV) poses an exceptional challenge. There are no documented cases of immune-mediated clearance of HIV from an infected individual, and no known correlates of immune protection. Although nonhuman primate models of lentivirus infection have provided valuable data about HIV pathogenesis, such models do not predict HIV vaccine efficacy in humans. The combined lack of a predictive animal model and undefined biomarkers of immune protection against HIV necessitate that vaccines to this pathogen be tested directly in clinical trials. Adaptive clinical trial designs can accelerate vaccine development by rapidly screening out poor vaccines while extending the evaluation of efficacious ones, improving the characterization of promising vaccine candidates and the identification of correlates of immune protection.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

On sliding mode control ofhydraulic servo systems and a manipulator

The aim of the study is to developa novel robust controller based on sliding mode control technique for the hydraulic servo system with flexible load and for a flexible manipulator with the lift and jib hydraulic actuators. For the purpose of general control design, a dynamic model is derived describing the principle physical behavior for both the hydraulic servo system and the flexible hydraulic manipulator. The mechanism of hydraulic servo systems is described by basic mathematical equations of fluid powersystems and the dynamics of flexible manipulator is modeled by the assumed modemethod. The controller is constructed so as to track desired trajectories in the presence of model imprecision. Experimental and simulation results demonstratethat sliding mode control has benefits which can be used to guarantee stabilityin uncertain systems and improve the system performance and load tolerance.

Direct torque control of permanent magnet synchronous machines - analysis and implementation

Thedirect torque control (DTC) has become an accepted vector control method besidethe current vector control. The DTC was first applied to asynchronous machines,and has later been applied also to synchronous machines. This thesis analyses the application of the DTC to permanent magnet synchronous machines (PMSM). In order to take the full advantage of the DTC, the PMSM has to be properly dimensioned. Therefore the effect of the motor parameters is analysed taking the control principle into account. Based on the analysis, a parameter selection procedure is presented. The analysis and the selection procedure utilize nonlinear optimization methods. The key element of a direct torque controlled drive is the estimation of the stator flux linkage. Different estimation methods - a combination of current and voltage models and improved integration methods - are analysed. The effect of an incorrect measured rotor angle in the current model is analysed andan error detection and compensation method is presented. The dynamic performance of an earlier presented sensorless flux estimation method is made better by improving the dynamic performance of the low-pass filter used and by adapting the correction of the flux linkage to torque changes. A method for the estimation ofthe initial angle of the rotor is presented. The method is based on measuring the inductance of the machine in several directions and fitting the measurements into a model. The model is nonlinear with respect to the rotor angle and therefore a nonlinear least squares optimization method is needed in the procedure. A commonly used current vector control scheme is the minimum current control. In the DTC the stator flux linkage reference is usually kept constant. Achieving the minimum current requires the control of the reference. An on-line method to perform the minimization of the current by controlling the stator flux linkage reference is presented. Also, the control of the reference above the base speed is considered. A new estimation flux linkage is introduced for the estimation of the parameters of the machine model. In order to utilize the flux linkage estimates in off-line parameter estimation, the integration methods are improved. An adaptive correction is used in the same way as in the estimation of the controller stator flux linkage. The presented parameter estimation methods are then used in aself-commissioning scheme. The proposed methods are tested with a laboratory drive, which consists of a commercial inverter hardware with a modified software and several prototype PMSMs.

Direct to consumer advertising : the case for greater consumer control

A nyone traveling to the United States from countries other than New Zealand will be surprised by the prevalence of health-related advertisements on television, including ads for drugs. Typically, these TV ads follow a pattern: an ad for a burger at only 99 cents, followed by one for a proton-pump inhibitor, then an ad on healthy home-cooked food delivered directly to your home and an ad for a home-based abdominal workout DVD, followed by an ad for a lipid-lowering drug. There are, however, nuances. After 8 pm, the visitor might encounter an ad for the "little blue pill." This sequence sometimes includes an ad featuring antihistamines for allergic rhinitis in spring and one promoting antidepressants in the winter. Such direct-to-consumer advertising (DTCA) of prescription drugs is usual business in the United States and New Zealand but is prohibited in the rest of the world. Why? Because DTCA for prescribing drugs has pros and cons (discussed elsewhere,1-3 including in JGIM4) that are balanced differently in different countries. Constitutional factors-such as the First Amendment protections on speech, including commercial speech, in the United States5 -as well as patient and population safety considerations, which all differ across countries, modulate reactions to DTCA. Additionally, lack of robust data on the impact of DTCA on prescription drug use adds to the confusion. Evidence, though limited, suggests that DTCA increases drug sales. However, whether the increase in sales corrects existing underuse or encourages over/misuse is not clear.

Variaciones dimensionales en piezas plásticas de inyección y análisis de los medios de control

En la industria de la automoción, así como en todas las que se dedican a fabricar piezas, ya sean plásticas o de otros materiales, es tan importante la Producción como la Calidad. No sirve de nada fabricar mucho si no son piezas de una calidad adecuada, y del mismo modo no es rentable fabricar muy poco volumen por mucho que tenga una calidad excelente. Por ello hay que buscar siempre el equilibrio entre ambos conceptos. La finalidad es tener procesos lo más robustos posibles que nos permitan fabricar cantidad con una buena calidad. La finalidad de este trabajo es buscar los parámetros que más afectan en un proceso de inyección, es decir, saber cuáles son los que debemos tener bajo control para lograr una calidad de piezas buena y un proceso estable y controlado. Para ver si el proceso es capaz de lograr ese objetivo utilizamos gráficos basados en la teoría de 6- sigma que nos calculan el coeficiente de capacidad del proceso (Cpk). A su vez analizaremos los sistemas de medida que utilizamos en cada una de las piezas analizadas para evaluar si son los correctos y nos permiten discriminar piezas buenas de malas en el proceso productivo. La conclusión del trabajo es que hay que prestar especial atención en controlar aquellos aspectos de un proceso que nos aportan variación, y no invertir tiempo ni dinero en aquellos otros que no nos aportan valor añadido y que no afectan sustancialmente al proceso. Este análisis por supuesto lleva su coste, que he analizado y plasmado en las conclusiones para saber lo que le cuesta aproximadamente a una empresa realizarlo.

Innate and Adaptive Immunity in Orolabial Herpes Simplex

Oral mucosa is a frequent site of primary herpes simplex virus type 1 (HSV-1) infection, whereas intraoral recurrent disease is very rare. Instead, reactivation from latency predominantly results in asymptomatic HSV shedding to saliva or recurrent labial herpes (RLH) with highly individual frequency. The current study aimed to elucidate the role of human oral innate and acquired immune mechanisms in modulation of HSV infection in orolabial region. Saliva was found to neutralize HSV-1, and to protect cells from infection independently of salivary antibodies. Neutralization capacity was higher in saliva from asymptomatic HSV-seropositive individuals compared to subjects with history of RLH or seronegative controls. Neutralization was at least partially associated with salivary lactoferrin content. Further, lactoferrin and peroxidase-generated hypothiocyanite were found to either neutralize HSV-1 or interfere with HSV-1 replication, whereas lysozyme displayed no anti-HSV-1 activity. Lactoferrin was also shown to modulate HSV-1 infection by inhibiting keratinocyte proliferation. RLH susceptibility was further found to be associated with Th2 biased cytokine responses against HSV, and a higher level of anti- HSV-IgG with Th2 polarization, indicating lack of efficiency of humoral response in the control of HSV disease. In a three-dimensional cell culture, keratinocytes were found to support both lytic and nonproductive infection, suggesting HSV persistence in epithelial cells, and further emphasizing the importance of peripheral immune control of HSV. These results suggest that certain innate salivary antimicrobial compounds and Th1 type cellular responses are critically important in protecting the host against HSV disease, implying possible applications in drug, vaccine and gene therapy design.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Spontaneous cell polarization: Feedback control of Cdc42 GTPase breaks cellular symmetry.

Spontaneous polarization without spatial cues, or symmetry breaking, is a fundamental problem of spatial organization in biological systems. This question has been extensively studied using yeast models, which revealed the central role of the small GTPase switch Cdc42. Active Cdc42-GTP forms a coherent patch at the cell cortex, thought to result from amplification of a small initial stochastic inhomogeneity through positive feedback mechanisms, which induces cell polarization. Here, I review and discuss the mechanisms of Cdc42 activity self-amplification and dynamic turnover. A robust Cdc42 patch is formed through the combined effects of Cdc42 activity promoting its own activation and active Cdc42-GTP displaying reduced membrane detachment and lateral diffusion compared to inactive Cdc42-GDP. I argue the role of the actin cytoskeleton in symmetry breaking is not primarily to transport Cdc42 to the active site. Finally, negative feedback and competition mechanisms serve to control the number of polarization sites.

Investigation and data adaptive analysis of CARS spectra

In this diploma work advantages of coherent anti-Stokes Raman scattering spectrometry (CARS) and various methods of the quantitative analysis of substance structure with its help are considered. The basic methods and concepts of the adaptive analysis are adduced. On the basis of these methods the algorithm of automatic measurement of a scattering strip size of a target component in CARS spectrum is developed. The algorithm uses known full spectrum of target substance and compares it with a CARS spectrum. The form of a differential spectrum is used as a feedback to control the accuracy of matching. To exclude the influence of a background in CARS spectra the differential spectrum is analysed by means of its second derivative. The algorithm is checked up on the simulated simple spectra and on the spectra of organic compounds received experimentally.

Multilevel control of arabidopsis 3-hydroxy-3-methylglutaryl coenzyme A reductase by protein phosphatase 2A

Plants synthesize a myriad of isoprenoid products that are required both for essential constitutive processes and for adaptive responses to the environment. The enzyme 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) catalyzes a key regulatory step of the mevalonate pathway for isoprenoid biosynthesis and is modulated by many endogenous and external stimuli. In spite of that, no protein factor interacting with and regulating plant HMGR in vivo has been described so far. Here, we report the identification of two B99 regulatory subunits of protein phosphatase 2A (PP2A), designated B99a and B99b, that interact with HMGR1S and HMGR1L, the major isoforms of Arabidopsis thaliana HMGR. B99a and B99b are Ca2+ binding proteins of the EF-hand type. We show that HMGR transcript, protein, and activity levels are modulated by PP2A in Arabidopsis. When seedlings are transferred to salt-containing medium, B99a and PP2A mediate the decrease and subsequent increase of HMGR activity, which results from a steady rise of HMGR1-encoding transcript levels and an initial sharper reduction of HMGR protein level. In unchallenged plants, PP2A is a posttranslational negative regulator of HMGR activity with the participation of B99b. Our data indicate that PP2A exerts multilevel control on HMGR through the fivemember B99 protein family during normal development and in response to a variety of stress conditions.

SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper