Structure-activity relationship and mechanism of action studies of manzamine analogues for the control of neuroinflammation and cerebral infections

Structure-activity relationship studies were carried out by chemical modification of manzamine A (1), 8-hydroxymanzamine A (2), manzamine F (14), and ircinal isolated from the sponge Acanthostrongylophora. The derived analogues were evaluated for antimalarial, antimicrobial, and antineuroinflammatory activities. Several modified products exhibited potent and improved in vitro antineuroinflammatory, antimicrobial, and antimalarial activity. 1 showed improved activity against malaria compared to chloroquine in both multi- and single-dose in vivo experiments. The significant antimalarial potential was revealed by a 100% cure rate of malaria in mice with one administration of 100 mg/kg of 1. The potent antineuroinflammatory activity of the manzamines will provide great benefit for the prevention and treatment of cerebral infections (e.g., Cryptococcus and Plasmodium). In addition, 1 was shown to permeate across the blood-brain barrier (BBB) in an in vitro model using a MDR-MDCK monolayer. Docking studies support that 2 binds to the ATP-noncompetitive pocket of glycogen synthesis kinase-3beta (GSK-3beta), which is a putative target of manzamines. On the basis of the results presented here, it will be possible to initiate rational drug design efforts around this natural product scaffold for the treatment of several different diseases.

Early non-invasive cardiac output monitoring in hemodynamically unstable intensive care patients: A multi-center randomized controlled trial

Introduction Acute hemodynamic instability increases morbidity and mortality. We investigated whether early non-invasive cardiac output monitoring enhances hemodynamic stabilization and improves outcome. Methods A multicenter, randomized controlled trial was conducted in three European university hospital intensive care units in 2006 and 2007. A total of 388 hemodynamically unstable patients identified during their first six hours in the intensive care unit (ICU) were randomized to receive either non-invasive cardiac output monitoring for 24 hrs (minimally invasive cardiac output/MICO group; n = 201) or usual care (control group; n = 187). The main outcome measure was the proportion of patients achieving hemodynamic stability within six hours of starting the study. Results The number of hemodynamic instability criteria at baseline (MICO group mean 2.0 (SD 1.0), control group 1.8 (1.0); P = .06) and severity of illness (SAPS II score; MICO group 48 (18), control group 48 (15); P = .86)) were similar. At 6 hrs, 45 patients (22%) in the MICO group and 52 patients (28%) in the control group were hemodynamically stable (mean difference 5%; 95% confidence interval of the difference -3 to 14%; P = .24). Hemodynamic support with fluids and vasoactive drugs, and pulmonary artery catheter use (MICO group: 19%, control group: 26%; P = .11) were similar in the two groups. The median length of ICU stay was 2.0 (interquartile range 1.2 to 4.6) days in the MICO group and 2.5 (1.1 to 5.0) days in the control group (P = .38). The hospital mortality was 26% in the MICO group and 21% in the control group (P = .34). Conclusions Minimally-invasive cardiac output monitoring added to usual care does not facilitate early hemodynamic stabilization in the ICU, nor does it alter the hemodynamic support or outcome. Our results emphasize the need to evaluate technologies used to measure stroke volume and cardiac output--especially their impact on the process of care--before any large-scale outcome studies are attempted.

Myoelectric activity of the ileum, cecum, proximal loop of the ascending colon, and spiral colon in cows with naturally occurring cecal dilatation-dislocation

OBJECTIVE: To analyze myoelectric activity of the ileum, cecum, proximal loop of the ascending colon (PLAC), and spiral colon in cows with naturally occurring cecal dilatation-dislocation (CDD) and compare findings with those in healthy cows. ANIMALS: 8 CDD-affected and 6 healthy control cows. PROCEDURES: Immediately after diagnosis, CDD-affected cows underwent surgery; control cows underwent a similar surgical procedure. Before completion of surgery, 8 bipolar silver electrodes were implanted in the ileum (n = 2), cecum (1), PLAC (1), and spiral colon (4) of each cow. Beginning the day after surgery, intestinal myoelectric activity was recorded daily (8-hour period) for 4 days; data were analyzed by use of specialized software programs. Quantitative variables of myoelectric activity were compared between groups. RESULTS: Cows of both groups recovered without complications after surgery. In control cows, physiologic myoelectric activity was recorded in all intestinal segments on all days after surgery. Apparently normal myoelectric activity was evident in the ileum of CDD-affected cows on the first day after surgery, but myoelectric activity patterns in the cecum, PLAC, and spiral colon were variable with no organized cyclic myoelectric patterns, incomplete or normally organized migrating myoelectric complexes, and slow normalization over time. CONCLUSIONS AND CLINICAL RELEVANCE: After surgery for CDD, normal myoelectric patterns were disrupted in the large intestine of cows, especially in the spiral colon. Clinical recovery with effective transit of ingesta occurred before normalization of myoelectric activity in the large intestine. Therapeutic protocols for restoration or normalization of spiral colon motility should be developed for treatment of CDD-affected cattle.

Regulatory mechanism of the light-activable allosteric switch LOV-TAP for the control of DNA binding: a computer simulation study

The spatio-temporal control of gene expression is fundamental to elucidate cell proliferation and deregulation phenomena in living systems. Novel approaches based on light-sensitive multiprotein complexes have recently been devised, showing promising perspectives for the noninvasive and reversible modulation of the DNA-transcriptional activity in vivo. This has lately been demonstrated in a striking way through the generation of the artificial protein construct light-oxygen-voltage (LOV)-tryptophan-activated protein (TAP), in which the LOV-2-Jα photoswitch of phototropin1 from Avena sativa (AsLOV2-Jα) has been ligated to the tryptophan-repressor (TrpR) protein from Escherichia coli. Although tremendous progress has been achieved on the generation of such protein constructs, a detailed understanding of their functioning as opto-genetical tools is still in its infancy. Here, we elucidate the early stages of the light-induced regulatory mechanism of LOV-TAP at the molecular level, using the noninvasive molecular dynamics simulation technique. More specifically, we find that Cys450-FMN-adduct formation in the AsLOV2-Jα-binding pocket after photoexcitation induces the cleavage of the peripheral Jα-helix from the LOV core, causing a change of its polarity and electrostatic attraction of the photoswitch onto the DNA surface. This goes along with the flexibilization through unfolding of a hairpin-like helix-loop-helix region interlinking the AsLOV2-Jα- and TrpR-domains, ultimately enabling the condensation of LOV-TAP onto the DNA surface. By contrast, in the dark state the AsLOV2-Jα photoswitch remains inactive and exerts a repulsive electrostatic force on the DNA surface. This leads to a distortion of the hairpin region, which finally relieves its tension by causing the disruption of LOV-TAP from the DNA.

Real-time closed-loop electrophysiology: towards new frontiers in in vitro investigations in the neurosciences

Reflected at any level of organization of the central nervous system, most of the processes ranging from ion channels to neuronal networks occur in a closed loop, where the input to the system depends on its output. In contrast, most in vitro preparations and experimental protocols operate autonomously, and do not depend on the output of the studied system. Thanks to the progress in digital signal processing and real-time computing, it is now possible to artificially close the loop and investigate biophysical processes and mechanisms under increased realism. In this contribution, we review some of the most relevant examples of a new trend in in vitro electrophysiology, ranging from the use of dynamic-clamp to multi-electrode distributed feedback stimulation. We are convinced these represents the beginning of new frontiers for the in vitro investigation of the brain, promising to open the still existing borders between theoretical and experimental approaches while taking advantage of cutting edge technologies.

Diesel spray mixing limited vaporization with non-ideal and multi-component fuel thermophysical property effects

Internal combustion engines are, and will continue to be, a primary mode of power generation for ground transportation. Challenges exist in meeting fuel consumption regulations and emission standards while upholding performance, as fuel prices rise, and resource depletion and environmental impacts are of increasing concern. Diesel engines are advantageous due to their inherent efficiency advantage over spark ignition engines; however, their NOx and soot emissions can be difficult to control and reduce due to an inherent tradeoff. Diesel combustion is spray and mixing controlled providing an intrinsic link between spray and emissions, motivating detailed, fundamental studies on spray, vaporization, mixing, and combustion characteristics under engine relevant conditions. An optical combustion vessel facility has been developed at Michigan Technological University for these studies, with detailed tests and analysis being conducted. In this combustion vessel facility a preburn procedure for thermodynamic state generation is used, and validated using chemical kinetics modeling both for the MTU vessel, and institutions comprising the Engine Combustion Network international collaborative research initiative. It is shown that minor species produced are representative of modern diesel engines running exhaust gas recirculation and do not impact the autoignition of n-heptane. Diesel spray testing of a high-pressure (2000 bar) multi-hole injector is undertaken including non-vaporizing, vaporizing, and combusting tests, with sprays characterized using Mie back scatter imaging diagnostics. Liquid phase spray parameter trends agree with literature. Fluctuations in liquid length about a quasi-steady value are quantified, along with plume to plume variations. Hypotheses are developed for their causes including fuel pressure fluctuations, nozzle cavitation, internal injector flow and geometry, chamber temperature gradients, and turbulence. These are explored using a mixing limited vaporization model with an equation of state approach for thermopyhysical properties. This model is also applied to single and multi-component surrogates. Results include the development of the combustion research facility and validated thermodynamic state generation procedure. The developed equation of state approach provides application for improving surrogate fuels, both single and multi-component, in terms of diesel spray liquid length, with knowledge of only critical fuel properties. Experimental studies are coupled with modeling incorporating improved thermodynamic non-ideal gas and fuel

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Risk assessment for invasive exotic plants using multi-criteria risk models

Invasive exotic plants have altered natural ecosystems across much of North America. In the Midwest, the presence of invasive plants is increasing rapidly, causing changes in ecosystem patterns and processes. Early detection has become a key component in invasive plant management and in the detection of ecosystem change. Risk assessment through predictive modeling has been a useful resource for monitoring and assisting with treatment decisions for invasive plants. Predictive models were developed to assist with early detection of ten target invasive plants in the Great Lakes Network of the National Park Service and for garlic mustard throughout the Upper Peninsula of Michigan. These multi-criteria risk models utilize geographic information system (GIS) data to predict the areas at highest risk for three phases of invasion: introduction, establishment, and spread. An accuracy assessment of the models for the ten target plants in the Great Lakes Network showed an average overall accuracy of 86.3%. The model developed for garlic mustard in the Upper Peninsula resulted in an accuracy of 99.0%. Used as one of many resources, the risk maps created from the model outputs will assist with the detection of ecosystem change, the monitoring of plant invasions, and the management of invasive plants through prioritized control efforts.

Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study

The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain and its complex structures. Hardware-In-the-Loop (HIL) simulation provides an open and convenient environment for the modeling, prototyping, testing and analyzing HEV control systems. This thesis focuses on the development of such a HIL system for the hybrid electric vehicle study. The hardware architecture of the HIL system, including dSPACE eDrive HIL simulator, MicroAutoBox II and MotoTron Engine Control Module (ECM), is introduced. Software used in the system includes dSPACE Real-Time Interface (RTI) blockset, Automotive Simulation Models (ASM), Matlab/Simulink/Stateflow, Real-time Workshop, ControlDesk Next Generation, ModelDesk and MotoHawk/MotoTune. A case study of the development of control systems for a single shaft parallel hybrid electric vehicle is presented to summarize the functionality of this HIL system.

MULTIDIMENSIONAL OPTIMAL DROOP CONTROL FOR WIND RESOURCES IN DC MICROGRIDS

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

STOCHASTIC CHARGE TRANSPORT IN MULTI-ISLAND SINGLE-ELECTRON TUNNELING DEVICES

The physics of the operation of singe-electron tunneling devices (SEDs) and singe-electron tunneling transistors (SETs), especially of those with multiple nanometer-sized islands, has remained poorly understood in spite of some intensive experimental and theoretical research. This computational study examines the current-voltage (IV) characteristics of multi-island single-electron devices using a newly developed multi-island transport simulator (MITS) that is based on semi-classical tunneling theory and kinetic Monte Carlo simulation. The dependence of device characteristics on physical device parameters is explored, and the physical mechanisms that lead to the Coulomb blockade (CB) and Coulomb staircase (CS) characteristics are proposed. Simulations using MITS demonstrate that the overall IV characteristics in a device with a random distribution of islands are a result of a complex interplay among those factors that affect the tunneling rates that are fixed a priori (e.g. island sizes, island separations, temperature, gate bias, etc.), and the evolving charge state of the system, which changes as the source-drain bias (VSD) is changed. With increasing VSD, a multi-island device has to overcome multiple discrete energy barriers (up-steps) before it reaches the threshold voltage (Vth). Beyond Vth, current flow is rate-limited by slow junctions, which leads to the CS structures in the IV characteristic. Each step in the CS is characterized by a unique distribution of island charges with an associated distribution of tunneling probabilities. MITS simulation studies done on one-dimensional (1D) disordered chains show that longer chains are better suited for switching applications as Vth increases with increasing chain length. They are also able to retain CS structures at higher temperatures better than shorter chains. In sufficiently disordered 2D systems, we demonstrate that there may exist a dominant conducting path (DCP) for conduction, which makes the 2D device behave as a quasi-1D device. The existence of a DCP is sensitive to the device structure, but is robust with respect to changes in temperature, gate bias, and VSD. A side gate in 1D and 2D systems can effectively control Vth. We argue that devices with smaller island sizes and narrower junctions may be better suited for practical applications, especially at room temperature.

STATE OF CHARGE BASED DROOP SURFACE FOR OPTIMAL CONTROL OF DC MICROGRIDS

For a microgrid with a high penetration level of renewable energy, energy storage use becomes more integral to the system performance due to the stochastic nature of most renewable energy sources. This thesis examines the use of droop control of an energy storage source in dc microgrids in order to optimize a global cost function. The approach involves using a multidimensional surface to determine the optimal droop parameters based on load and state of charge. The optimal surface is determined using knowledge of the system architecture and can be implemented with fully decentralized source controllers. The optimal surface control of the system is presented. Derivations of a cost function along with the implementation of the optimal control are included. Results were verified using a hardware-in-the-loop system.

Multi-parametric classification of Alzheimer's disease and mild cognitive impairment: the impact of quantitative magnetization transfer MR imaging

Multi-parametric and quantitative magnetic resonance imaging (MRI) techniques have come into the focus of interest, both as a research and diagnostic modality for the evaluation of patients suffering from mild cognitive decline and overt dementia. In this study we address the question, if disease related quantitative magnetization transfer effects (qMT) within the intra- and extracellular matrices of the hippocampus may aid in the differentiation between clinically diagnosed patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI) and healthy controls. We evaluated 22 patients with AD (n=12) and MCI (n=10) and 22 healthy elderly (n=12) and younger (n=10) controls with multi-parametric MRI. Neuropsychological testing was performed in patients and elderly controls (n=34). In order to quantify the qMT effects, the absorption spectrum was sampled at relevant off-resonance frequencies. The qMT-parameters were calculated according to a two-pool spin-bath model including the T1- and T2 relaxation parameters of the free pool, determined in separate experiments. Histograms (fixed bin-size) of the normalized qMT-parameter values (z-scores) within the anterior and posterior hippocampus (hippocampal head and body) were subjected to a fuzzy-c-means classification algorithm with downstreamed PCA projection. The within-cluster sums of point-to-centroid distances were used to examine the effects of qMT- and diffusion anisotropy parameters on the discrimination of healthy volunteers, patients with Alzheimer and MCIs. The qMT-parameters T2(r) (T2 of the restricted pool) and F (fractional pool size) differentiated between the three groups (control, MCI and AD) in the anterior hippocampus. In our cohort, the MT ratio, as proposed in previous reports, did not differentiate between MCI and AD or healthy controls and MCI, but between healthy controls and AD.

Use of a computerized closed-loop sodium nitroprusside titration system for antihypertensive treatment after open heart surgery

This study evaluates the clinical applicability of administering sodium nitroprusside by a closed-loop titration system compared with a manually adjusted system. The mean arterial pressure (MAP) was registered every 10 and 30 sec during the first 150 min after open heart surgery in 20 patients (group 1: computer regulation) and in ten patients (group 2: manual regulation). The results (16,343 and 2,912 data points in groups 1 and 2, respectively), were then analyzed in four time frames and five pressure ranges to indicate clinical efficacy. Sixty percent of the measured MAP in both groups was within the desired +/- 10% during the first 10 min. Thereafter until the end of observation, the MAP was maintained within +/- 10% of the desired set-point 90% of the time in group 1 vs. 60% of the time in group 2. One percent and 11% of data points were +/- 20% from the set-point in groups 1 and 2, respectively (p less than .05, chi-square test). The computer-assisted therapy provided better control of MAP, was safe to use, and helped to reduce nursing demands.