The contribution of a murine CNS-TB model for the understanding of the host-pathogen interactions in the formation of granulomas

Central nervous system (CNS) tuberculosis (TB) is the most severe form of TB, characterized morphologically by brain granulomas and tuberculous meningitis (TBM). Experimental strategies for the study of the host-pathogen interaction through the analysis of granulomas and its intrinsic molecular mechanisms could provide new insights into the neuropathology of TB. To verify whether cerebellar mycobacterial infection induces the main features of the disease in human CNS and better understand the physiological mechanisms underlying the disease, we injected bacillus Calmette-Guerin (BCG) into the mouse cerebellum. BCG-induced CNS-TB is characterized by the formation of granulomas and TBM, a build up of bacterial loads in these lesions, and microglial recruitment into the lesion sites. In addition, there is an enhanced expression of signaling molecules such as nuclear factor-kappa B (NF-kappa B) and there is a presence of inducible nitric oxide synthase (iNOS) in the lesions and surrounding areas. This murine model of cerebellar CNS-TB was characterized by cellular and biochemical immune responses typically found in the human disease. This model could expand our knowledge about granulomas in TB infection of the cerebellum, and help characterize the physiological mechanisms involved with the progression of this serious illness that is responsible for killing millions people every year. (C) 2012 Elsevier B.V. All rights reserved.

In-Flight Collision Avoidance Controller Based Only on OS4 Embedded Sensors

The major goal of this research was the development and implementation of a control system able to avoid collisions during the flight for a mini-quadrotor helicopter, based only on its embedded sensors without changing the environment. However, it is important to highlight that the design aspects must be seriously considered in order to overcome hardware limitations and achieve control simplification. The controllers of a UAV (Unmanned Aerial Vehicle) robot deal with highly unstable dynamics and strong axes coupling. Furthermore, any additional embedded sensor increases the robot total weight and therefore, decreases its operating time. The best balance between embedded electronics and robot operating time is desired. This paper focuses not only on the development and implementation of a collision avoidance controller for a mini-robotic helicopter using only its embedded sensors, but also on the mathematical model that was essential for the controller developing phases. Based on this model we carried out the development of a simulation tool based on MatLab/Simulink that was fundamental for setting the controllers' parameters. This tool allowed us to simulate and improve the OS4 controllers in different modeled environments and test different approaches. After that, the controllers were embedded in the real robot and the results proved to be very robust and feasible. In addition to this, the controller has the advantage of being compatible with future path planners that we are developing.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

Model and control of tendon actuated robots

The use of tendons for the transmission of the forces and the movements in robotic devices has been investigated from several researchers all over the world. The interest in this kind of actuation modality is based on the possibility of optimizing the position of the actuators with respect to the moving part of the robot, in the reduced weight, high reliability, simplicity in the mechanic design and, finally, in the reduced cost of the resulting kinematic chain. After a brief discussion about the benefits that the use of tendons can introduce in the motion control of a robotic device, the design and control aspects of the UB Hand 3 anthropomorphic robotic hand are presented. In particular, the tendon-sheaths transmission system adopted in the UB Hand 3 is analyzed and the problem of force control and friction compensation is taken into account. The implementation of a tendon based antagonistic actuated robotic arm is then investigated. With this kind of actuation modality, and by using transmission elements with nonlinear force/compression characteristic, it is possible to achieve simultaneous stiffness and position control, improving in this way the safety of the device during the operation in unknown environments and in the case of interaction with other robots or with humans. The problem of modeling and control of this type of robotic devices is then considered and the stability analysis of proposed controller is reported. At the end, some tools for the realtime simulation of dynamic systems are presented. This realtime simulation environment has been developed with the aim of improving the reliability of the realtime control applications both for rapid prototyping of controllers and as teaching tools for the automatic control courses.

Neuroprotective strategies against neurodegeneration in cellular model systems

In the present study we analyzed new neuroprotective therapeutical strategies in PD (Parkinson’s disease) and AD (Alzheimer’s disease). Current therapeutic strategies for treating PD and AD offer mainly transient symptomatic relief but it is still impossible to block the loss of neuron and then the progression of PD and AD. There is considerable consensus that the increased production and/or aggregation of α- synuclein (α-syn) and β-amyloid peptide (Aβ), plays a central role in the pathogenesis of PD, related synucleinopathies and AD. Therefore, we identified antiamyloidogenic compounds and we tested their effect as neuroprotective drug-like molecules against α-syn and β-amyloid cytotoxicity in PC12. Herein, we show that two nitro-catechol compounds (entacapone and tolcapone) and 5 cathecol-containing compounds (dopamine, pyrogallol, gallic acid, caffeic acid and quercetin) with antioxidant and anti-inflammatory properties, are potent inhibitors of α-syn and β-amyloid oligomerization and fibrillization. Subsequently, we show that the inhibition of α-syn and β-amyloid oligomerization and fibrillization is correlated with the neuroprotection of these compounds against the α-syn and β-amyloid-induced cytotoxicity in PC12. Finally, we focused on the study of the neuroprotective role of microglia and on the possibility that the neuroprotection properties of these cells could be use as therapeutical strategy in PD and AD. Here, we have used an in vitro model to demonstrate neuroprotection of a 48 h-microglial conditioned medium (MCM) towards cerebellar granule neurons (CGNs) challenged with the neurotoxin 6-hydroxydopamine (6-OHDA), which induces a Parkinson-like neurodegeneration, with Aβ42, which induces a Alzheimer-like neurodegeneration, and glutamate, involved in the major neurodegenerative diseases. We show that MCM nearly completely protects CGNs from 6-OHDA neurotoxicity, partially from glutamate excitotoxicity but not from Aβ42 toxin.

Model predictive flight control systems for rotorcraft UAS

Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the development of a model predictive control system for small scale rotorcraft UAS. Several different predictive architectures have been evaluated and tested by means of simulation, as a result of this analysis the most promising one has been used to implement three different control systems: a Stability and Control Augmentation System, a trajectory tracking and a path following system. The systems have been compared with a corresponding baseline controller and showed several advantages in terms of performance, stability and robustness.

The characterization of the Atxn2-CAG42-knock-in mouse as a model for Spinocerebellar Ataxia Type 2

Die Ursache der neurodegenerativen Erkrankung Spinozerebelläre Ataxie Typ 2 (SCA2) ist eine expandierte Polyglutamin-Domäne im humanen ATXN2-Gen von normalerweise 22 auf über 31 CAGs. Von der Degeneration sind vorwiegend die zerebellären Purkinje Neuronen betroffen, in denen zunehmend zytoplasmatische Aggregate sichtbar werden. Auch wenn die genaue Funktion von ATXN2 und die zugrunde liegenden molekularen Mechanismen noch immer ungeklärt sind, werden ein toxischer Funktionsgewinn sowie der Verlust der normalen Proteinfunktion als mögliche Ursachen diskutiert.rnUm ein wirklichkeitsgetreues Tiermodell für die SCA2 zu haben, wurde eine knock-in Maus generiert, deren einzelnes CAG im Atxn2-Gen durch 42 CAGs ersetzt wurde. Dieses Mausmodell ist durch eine stabile Vererbung der Expansion charakterisiert. Weiterhin zeigt sie ein verringertes Körpergewicht sowie eine spät beginnende motorische Inkoordination, was dem Krankheitsbild von SCA2 entspricht. rnIm Weiteren konnte gezeigt werden, dass, obwohl die Atxn2 mRNA-Spiegel in Großhirn und Kleinhirn erhöht waren, die Menge an löslichem ATXN2 im Laufe der Zeit abnahm und dies mit einem Auftreten an unlöslichem ATXN2 korrelierte. Dieser im Kleinhirn progressive Prozess resultierte schließlich in zytoplasmatischen Aggregaten innerhalb der Purkinje Neuronen alter Mäuse. Der Verlust an löslichem ATXN2 könnte Effekte erklären, die auf einen partiellen Funktionsverlust von ATXN2 zurückzuführen sind, wobei die Aggregatbildung einen toxischen Funktionsgewinn wiederspiegeln könnte. Neben ATXN2 wurde auch sein Interaktor PABPC1 zunehmend unlöslich. Während dies im Großhirn eine Erhöhung der PABPC1 mRNA- und löslichen Proteinspiegel zur Folge hatte, konnte keine kompensatorische Veränderung seiner mRNA und zudem eine Verminderung an löslichem PABPC1 im Kleinhirn beobachtet werden. Auch PABPC1 wurde in Aggregate sequestriert. Diese Unterschiede zwischen Großhirn und Kleinhirn könnten zu der spezifischen Vulnerabilität des Kleinhirns beitragen.rnUm die Folgen auf mRNA-Prozessierung zu untersuchen, wurde ein Transkriptomprofil im mittleren sowie fortgeschrittenen Alter der Mäuse erstellt. Hierbei war eine erhöhte Expression von Fbxw8 im Kleinhirn alter Mäuse auffällig. Als Komponente eines Ubiquitin-E3-Ligase-Komplexes, hilft FBXW8 in der Degradierung von Zielproteinen und könnte somit die Toxizität des expandieren ATXN2 verringern. rnZur näheren Beschreibung der physiologischen Funktion von ATXN2, konnte in ATXN2-knock-out Mäusen gezeigt werden, dass das Fehlen von ATXN2 zu einer reduzierten globalen Proteinsyntheserate führte und somit eine Rolle als Translationsaktivator möglich erscheint. Kompensatorisch wurde eine erhöhte S6-Phosphorylierung gemessen.

Model Predictive Control for Vehicle Stabilization at the Limits of Handling

Recent developments in vehicle steering systems offer new opportunities to measure the steering torque and reliably estimate the vehicle sideslip and the tire-road friction coefficient. This paper presents an approach to vehicle stabilization that leverages these estimates to define state boundaries that exclude unstable vehicle dynamics and utilizes a model predictive envelope controller to bound the vehicle motion within this stable region of the state space. This approach provides a large operating region accessible by the driver and smooth interventions at the stability boundaries. Experimental results obtained with a steer-by-wire vehicle and a proof of envelope invariance demonstrate the efficacy of the envelope controller in controlling the vehicle at the limits of handling.

Ruminant organotypic brain-slice cultures as a model for the investigation of CNS listeriosis

Central nervous system (CNS) infections in ruminant livestock, such as listeriosis, are of major concern for veterinary and public health. To date, no host-specific in vitro models for ruminant CNS infections are available. Here, we established and evaluated the suitability of organotypic brain-slices of ruminant origin as in vitro model to study mechanisms of Listeria monocytogenes CNS infection. Ruminants are frequently affected by fatal listeric rhombencephalitis that closely resembles the same condition occurring in humans. Better insight into host-pathogen interactions in ruminants is therefore of interest, not only from a veterinary but also from a public health perspective. Brains were obtained at the slaughterhouse, and hippocampal and cerebellar brain-slices were cultured up to 49 days. Viability as well as the composition of cell populations was assessed weekly. Viable neurons, astrocytes, microglia and oligodendrocytes were observed up to 49 days in vitro. Slice cultures were infected with L. monocytogenes, and infection kinetics were monitored. Infected brain cells were identified by double immunofluorescence, and results were compared to natural cases of listeric rhombencephalitis. Similar to the natural infection, infected brain-slices showed focal replication of L. monocytogenes and bacteria were predominantly observed in microglia, but also in astrocytes, and associated with axons. These results demonstrate that organotypic brain-slice cultures of bovine origin survive for extended periods and can be infected easily with L. monocytogenes. Therefore, they are a suitable model to study aspects of host-pathogen interaction in listeric encephalitis and potentially in other neuroinfectious diseases.

Stochastic knock detection model for spark ignited engines

This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.

The antioxidant glutathione in the fish cell lines EPC and BCF-2: response to model pro-oxidants as measured by three different fluorescent dyes

Reduced glutathione (GSH) protects cells against injury by oxidative stress and maintains a range of vital functions. In vitro cell cultures have been used as experimental models to study the role of GSH in chemical toxicity in mammals; however, this approach has been rarely used with fish cells to date. The present study aimed to evaluate sensitivity and specificity of three fluorescent dyes for measuring pro-oxidant-induced changes of GSH contents in fish cell lines: monochlorobimane (mBCl), 5-chloromethylfluorescein diacetate (CMFDA) and 7-amino-4-chloromethylcoumarin (CMAC-blue). Two cell lines were studied, the EPC line established from a skin tumour of carp Cyprinus carpio, and BF-2 cells established from fins of bluegill sunfish Lepomis macrochirus. The cells were exposed for 6 and 24 h to low cytotoxic concentrations of pro-oxidants including hydrogen peroxide, paraquat (PQ), copper and the GSH synthesis inhibitor, L-buthionine-SR-sulfoximine (BSO). The results indicate moderate differences in the GSH response between EPC and BF-2 cells, but distinct differences in the magnitude of the GSH response for the four pro-oxidants. Further, the choice of GSH dye can critically affect the results, with CMFDA appearing to be less specific for GSH than mBCl and CMAC-blue.

Cerebellar cortex involvement in classical eyelid conditioning

A model for cerebellar involvement in motor learning was tested using classical eyelid conditioning in the rabbit. Briefly, we assume that modifications of the strength of granule cell synapses at Purkinje cells in the cerebellar cortex and mossy fiber (MF) synapses at cerebellar interpositus nuclei are responsible for the acquisition, adaptively-timed expression, and extinction of conditioned eyelid responses (CRs). A corollary of these assumptions is that the cerebellar cortex is necessary for acquisition and extinction. This model also suggests a mechanism whereby the cerebellar cortex can discriminate different times during a conditioned stimulus (CS) and thus mediate the learned timing of CRs. Therefore, experiments were done to determine the role of the cerebellar cortex in the timing, extinction, and acquisition of CRs. Lesions of the cerebellar cortex that included the anterior lobe disrupted the learned timing of CRs such that they occurred at extremely short latencies. Stimulation of MFs in the middle cerebellar peduncle as the CS could support differently timed CRs in the same animal. These data indicate that synaptic plasticity in the cerebellar cortex mediates the learned timing of CRs. These short-latency CRs which resulted from anterior lobe damage did not extinguish, while CRs in animals receiving lesions which did not include the anterior lobe extinguished normally. Preliminary data suggests that lesions of the anterior lobe which produce short-latency responses prevent the acquisition of CRs to a novel CS. These findings indicate that the anterior lobe of cerebellar cortex is necessary for eyelid conditioning. The involvement of the anterior lobe in eyelid conditioning has not been previously reported, however, the anterior lobe has generally been spared in lesion studies examining cerebellar cortex involvement in eyelid conditioning due to its relatively inaccessible location. The observation that the anterior lobe of the cerebellar cortex is not always required for the basic expression of CRs, but is necessary for response timing, extinction, and acquisition, is consistent with the hypothesis that eyelid conditioning can involve plasticity in both the cerebellar cortex and interpositus nucleus and that plasticity in the nucleus is controlled by Purkinje cell activity. ^

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

CHARACTERIZATION AND TREATMENT OF A NOVEL MOUSE MODEL OF TSC-ASSOCIATED AUTISM

Tuberous sclerosis complex (TSC) is a dominant tumor suppressor disorder caused by mutations in either TSC1 or TSC2. The proteins of these genes form a complex to inhibit the mammalian target of rapamycin complex 1 (mTORC1), which controls protein translation and cell growth. TSC causes substantial neuropathology, often leading to autism spectrum disorders (ASDs) in up to 60% of patients. The anatomic and neurophysiologic links between these two disorders are not well understood. However, both disorders share cerebellar abnormalities. Therefore, we have characterized a novel mouse model in which the Tsc2 gene was selectively deleted from cerebellar Purkinje cells (Tsc2f/-;Cre). These mice exhibit progressive Purkinje cell degeneration. Since loss of Purkinje cells is a well-reported postmortem finding in patients with ASD, we conducted a series of behavior tests to assess if Tsc2f/-;Cre mice displayed autistic-like deficits. Using the three chambered social choice assay, we found that Tsc2f/-;Cre mice showed behavioral deficits, exhibiting no preference between a stranger mouse and an inanimate object, or between a novel and a familiar mouse. Tsc2f/-;Cre mice also demonstrated increased repetitive behavior as assessed with marble burying activity. Altogether, these results demonstrate that loss of Tsc2 in Purkinje cells in a haploinsufficient background lead to behavioral deficits that are characteristic of human autism. Therefore, Purkinje cells loss and/or dysfunction may be an important link between TSC and ASD. Additionally, we have examined some of the cellular mechanisms resulting from mutations in Tsc2 leading to Purkinje cell death. Loss of Tsc2 led to upregulation of mTORC1 and increased cell size. As a consequence of increased protein synthesis, several cellular stress pathways were upregulated. Principally, these included altered calcium signaling, oxidative stress, and ER stress. Likely as a consequence of ER stress, there was also upregulation of ubiquitin and autophagy. Excitingly, treatment with an mTORC1 inhibitor, rapamycin attenuated mTORC1 activity and prevented Purkinje cell death by reducing of calcium signaling, the ER stress response, and ubiquitin. Remarkably, rapamycin treatment also reversed the social behavior deficits, thus providing a promising potential therapy for TSC-associated ASD.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.