Formaldehyde Metabolism and Formaldehyde-induced Alterations in Glucose and Glutathione Metabolism of Cultured Brain Cells

Formaldehyde is an environmental pollutant that is also generated in the body during normal metabolic processes. Interestingly, several pathological conditions are associated with an increase in formaldehyde-generating enzymes in the body. The level of formaldehyde in the brain is elevated with increasing age and in neurodegenerative conditions which may contribute to lowered cognitive functions. Although the neurotoxic potential of formaldehyde is well established, the molecular mechanisms involved remain, to a great extent, obscure. Also, the ability of the different types of brain cells to metabolize formaldehyde has not been reported so far. This thesis investigated the capacity of cultured brain cells to metabolize formaldehyde and studied the effects of a formaldehyde exposure on the glucose and the glutathione metabolism by using primary cultures of cerebellar granule neurons or astrocytes as well as the oligodendroglial cell-line OLN-93 as model systems. These cultured cells were remarkably resistant towards acute toxicity of formaldehyde and expressed the mRNAs for enzymes that are known to be involved in formaldehyde generation and disposal, suggesting that brain cells are able to metabolize this aldehyde. Furthermore, all three types of cultures cleared exogenously applied formaldehyde with almost identical rates, but differed in the extent of the formation of the formaldehyde oxidation product, formate. Since formate is a known inhibitor of the cytochrome c oxidase of the mitochondrial respiratory chain and since the metabolism of formaldehyde involves the important antioxidant glutathione, the effect of an exposure of cultured brain cells to formaldehyde on their glucose and glutathione metabolism was also investigated. Formaldehyde application accelerated the export of glycolysis-derived lactate and induced a rapid multidrug-resistance protein 1-mediated export of glutathione from cultured brain cells. These formaldehyde-induced alterations in metabolic pathways of brain cells may contribute to the known impairments in memory and learning that have been reported for neurodegenerative conditions and for formaldehyde-exposed animals

Integrated Robust Optimal Design (IROD) via sensitivity minimization

A novel Integrated Robust Optimal Design (IROD) methodology is presented in this work which combines a traditional sensitivity theory with relatively new dvancements in Bilinear Matrix Inequality (BMI) constrained optimization problems. IROD provides the least conservative approach for robust control synthesis. The proposed methodology is demonstrated using numerical examples of integrated control-structure design problem for combine harvester header and excavator linkages. The IROD methodology is compared with the state of the art sequential design method using the two application examples, and the results show that the proposed methodology provides a viable alternative for robust controller synthesis and often times offers even a better performance than competing methods. Although this method requires linearization of nonlinear system at each system parameter optimization step, a technique to linearized Differential Algebraic Equations (DAE) is presented which allows use of symbolic approach for linearization. This technique avoids repetitive linearizations. For the nonlinear systems with parametric uncertainties which can not be linearized at operating points, a new methodology is proposed for robust feedback linearization using sensitivity dynamics-based formulation. The feedback linearization approach is used for systems with augmented sensitivity dynamics and used to refine control input to improve robustness. The method is demonstrated using an example of a position tracking control of a hydraulic actuator. The robustness of controller design is demonstrated by considering variations in fluid density parameter. The results show that the proposed methodology improves robustness of the feedback linearization to parametric variations

Comparative Study of Constant Voltage and Constant Current Electroanesthesia

In the field of anesthesia, drugs are used extensively, however; electro anesthesia or the use of electric current to achieve anesthesia is also being studied because of its excellent recovery characteristics. This thesis is a comparative study of different techniques of achieving electro anesthesia. Pharmacologically, general anesthesia is a completely irreversible converging depression of certain central nervous system functions wherein respiration, circulation and the vital life support mechanisms are not seriously impaired. Clinically, general anesthesia is a production of unconsciousness, some degree of areflexia, muscular relaxation and varying degrees of respiratory depression in an orderly progression. Electro anesthesia can be defined as anesthesia achieved using electricity as an anesthetic agent instead of commonly used drugs like Barbiturates, Halothane, etc. Sometimes electro anesthesia is used along with some chemical drugs, the reasons for which will be discussed later. In chemical anesthesia, the changes in the physiological parameters such as body temperature, heart rate, respiratory rate, etc. are correlated to the deepness of anesthesia

Framework for a space shuttle main engine health monitoring system

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making

A System Dynamics Model for Simulating Ambulatory Health Care Demands

Introduction: This article demonstrates the utility of the system dynamics approach to model and simulate US demand for ambulatory health care service both for the general population and for specific cohort subpopulations over the 5-year period, from 2003 to 2008. A system dynamics approach that is shown to meaningfully project demand for services has implications for health resource planning and for generating knowledge that is critical to assessing interventions. Methods: The study uses a cohort-component method in combination with structural modeling to simulate ambulatory health care utilization. Data are drawn from the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey. Results: The simulation of the total population requiring ambulatory services between 2003 and 2008 is performed to test the functionality and validate the model. Results show a close agreement between the simulated and actual data; the percent error between the two is relatively low, 1.5% on average. In addition, simulations of purposively selected population subsets are executed (men, 18–24 years of age, white, African American, Hispanic, and insurance coverage), resulting in error between simulated and actual data, which is 7.05% on average. Conclusions: The proposed model demonstrates that it is possible to represent and mimic, with reasonable accuracy, the demand for health care services by the total ambulatory population and the demand by selected population subsets. This model and its simulation demonstrate how these techniques can be used to identify disparities among population subsets and a vehicle to test the impact of health care interventions on ambulatory utilization. A system dynamics approach may be a useful tool for policy and strategic planners

Forecasting Empty Container Volumes

The accumulation and repositioning of empty containers have become acute problems for container ports and are expected to intensify in the future given the expected growth in trade imbalances among trading nations. These problems are major costs and operational challenges for container ports. More accurate forecasting of volumes of port empty containers will enable container ports to develop more cost efficient plans for the repositioning of empty containers. This paper compares the Tioga Group, United Nations and Winters method (utilizing empty container volumes of three U.S. container ports) in forecasting volumes of port empty containers. The Winters method is found to provide more accurate forecasts of volumes of port empty containers than the Tioga Group and United Nations methods