Oxygen sensors and energy sensors act synergistically to achieve a graded alteration in gene expression: Consequences for assessing the level of neuroprotection in response to stressors

Changes in gene expression are associated with switching to an autoprotected phenotype in response to environmental and physiological stress. Ubiquitous molecular chaperones from the heat shock protein (HSP) superfamily confer neuronal protection that can be blocked by antibodies. Recent research has focused on the interactions between the molecular sensors that affect the increased expression of neuroprotective HSPs above constitutive levels. An examination of the conditions under which the expression of heat shock protein 70 (Hsp70) was up regulated in a hypoxia and anoxia tolerant tropical species, the epaulette shark (Hemiscyllium ocellatum), revealed that up-regulation was dependent on exceeding a stimulus threshold for an oxidative stressor. While hypoxic-preconditioning confers neuroprotective changes, there was no increase in the level of Hsp70 indicating that its increased expression was not associated with achieving a neuroprotected state in response to hypoxia in the epaulette shark. Conversely, there was a significant increase in Hsp70 in response to anoxic-preconditioning, highlighting the presence of a stimulus threshold barrier and raising the possibility that, in this species, Hsp70 contributes to the neuroprotective response to extreme crises, such as oxidative stress. Interestingly, there was a synergistic effect of coincident stressors on Hsp70 expression, which was revealed when metabolic stress was superimposed upon oxidative stress. Brain energy charge was significantly lower when adenosine receptor blockade, provided by treatment with aminophylline, was present prior to the final anoxic episode, under these circumstances, the level of Hsp70 induced was significantly higher than in the pair-matched saline treated controls. An understanding of the molecular and metabolic basis for neuroprotective switches, which result in an up-regulation of neuroprotective Hsp70 expression in the brain, is needed so that intervention strategies can be devised to manage CNS pathologies and minimise damage caused by ischemia and trauma. In addition, the current findings indicate that measurements of HSP expression per se may provide a useful correlate of the level of neuroprotection achieved in the switch to an autoprotected phenotype.

Work domain analysis and sensors II: Pasteurizer II case study

In this paper we use sensor-annotated abstraction hierarchies (Reising & Sanderson, 1996, 2002a,b) to show that unless appropriately instrumented, configural displays designed according to the principles of ecological interface design (EID) might be vulnerable to misinterpretation when sensors become unreliable or are unavailable. Building on foundations established in Reising and Sanderson (2002a) we use a pasteurization process control example to show how sensor-annotated AHs help the analyst determine the impact of different instrumentation engineering policies on a configural display that is part of an ecological interface. Our analyses suggest that configural displays showing higher-order properties of a system are especially vulnerable under some conservative instrumentation configurations. However, sensor-annotated AHs can be used to indicate where corrective instrumentation might be placed. We argue that if EID is to be effectively employed in the design of displays for complex systems, then the information needs of the human operator need to be considered while instrumentation requirements are being formulated. Rasmussen's abstraction hierarchy-and particularly its extension to the analysis of information captured by sensors and derived from sensors-may therefore be a useful adjunct to up-stream instrumentation design. (C) 2002 Elsevier Science Ltd. All rights reserved.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

Cardiovascular disease and PPARdelta: Targeting the risk factors

Metabolism, in part, is regulated by the peroxisome proliferator-activated receptors (PPARs). The PPARs act as nutritional lipid sensors and three mammalian PPAR subtypes designated PPARalpha (NR1C1), PPARgamma (NR1C3) and PPARdelta (NR1C2) have been identified. This subgroup of nuclear hormone receptors binds DNA and controls gene expression at the nexus of pathways that regulate lipid and glucose homeostasis, energy storage and expenditure in an organ-specific manner. Recent evidence has demonstrated activation of PPARdelta in the major mass peripheral tissue (ie, adipose and skeletal muscle). It enhances glucose tolerance, insulin-stimulated glucose disposal, lipid catabolism, energy expenditure, cholesterol efflux and oxygen consumption. These effects positively influence the blood-lipid profile. Furthermore, PPARdelta activation produces a predominant type I/slow twitch/oxidative muscle fiber phenotype that leads to increased endurance, insulin sensitivity and resistance to obesity. PPARdelta has rapidly emerged as a potential target in the battle against dyslipidemia, insulin insensitivity, type II diabetes and obesity, with therapeutic efficacy in the treatment of cardiovascular disease risk factors. GW-501516 is currently undergoing phase II safety and efficacy trials in human volunteers for the treatment of dyslipidemia. The outcome of these clinical trials are eagerly awaited against a background of conflicting reports about cancer risks in genetically predisposed animal models. This review focuses on the potential pharmacological utility of selective PPARdelta agonists in the context of risk factors associated with metabolic and cardiovascular disease.

Modelling context information with ORM

Context-aware applications rely on implicit forms of input, such as sensor-derived data, in order to reduce the need for explicit input from users. They are especially relevant for mobile and pervasive computing environments, in which user attention is at a premium. To support the development of context-aware applications, techniques for modelling context information are required. These must address a unique combination of requirements, including the ability to model information supplied by both sensors and people, to represent imperfect information, and to capture context histories. As the field of context-aware computing is relatively new, mature solutions for context modelling do not exist, and researchers rely on information modelling solutions developed for other purposes. In our research, we have been using a variant of Object-Role Modeling (ORM) to model context. In this paper, we reflect on our experiences and outline some research challenges in this area.

Scalable location management for context-aware systems

Location information is commonly used in context-aware applications and pervasive systems. These applications and systems may require knowledge, of the location of users, devices and services. This paper presents a location management system able to gather, process and manage location information from a variety of physical and virtual location sensors. The system scales to the complexity of context-aware applications, to a variety of types and large number of location sensors and clients, and to geographical size of the system. The proposed location management system provides conflict resolution of location information and mechanisms to ensure privacy.

Work domain analysis and sensors I: principles and simple example

In this paper we establish a foundation for understanding the instrumentation needs of complex dynamic systems if ecological interface design (EID)-based interfaces are to be robust in the face of instrumentation failures. EID-based interfaces often include configural displays which reveal the higher-order properties of complex systems. However, concerns have been expressed that such displays might be misleading when instrumentation is unreliable or unavailable. Rasmussen's abstraction hierarchy (AH) formalism can be extended to include representations of sensors near the functions or properties about which they provide information, resulting in what we call a sensor-annotated abstraction hierarchy. Sensor-annotated AHs help the analyst determine the impact of different instrumentation engineering policies on higher-order system information by showing how the data provided from individual sensors propagates within and across levels of abstraction in the AH. The use of sensor-annotated AHs with a configural display is illustrated with a simple water reservoir example. We argue that if EID is to be effectively employed in the design of interfaces for complex systems, then the information needs of the human operator need to be considered at the earliest stages of system development while instrumentation requirements are being formulated. In this way, Rasmussen's AH promotes a formative approach to instrumentation engineering. (C) 2002 Elsevier Science Ltd. All rights reserved.

Functionalized macrocyclic compounds: potential sensors of small molecules and ions

The potential applications of macrocycles in chemistry and at its interfaces with biology and physics continue to emerge, one of which is as receptors for small molecules and ions. This review illustrates these applications with examples from the last ten years employing complexation as the binding mechanism; some of the systems presented have already found real-world sensor applications. In any case, the challenges remain to design more selective and sensitive receptors for guests.

Non-linear analysis of the thermo-electro-mechanical behaviour of shear deformable FGM plates with piezoelectric actuators

This paper investigates the non-linear bending behaviour of functionally graded plates that are bonded with piezoelectric actuator layers and subjected to transverse loads and a temperature gradient based on Reddy's higher-order shear deformation plate theory. The von Karman-type geometric non-linearity, piezoelectric and thermal effects are included in mathematical formulations. The temperature change is due to a steady-state heat conduction through the plate thickness. The material properties are assumed to be graded in the thickness direction according to a power-law distribution in terms of the volume fractions of the constituents. The plate is clamped at two opposite edges, while the remaining edges can be free, simply supported or clamped. Differential quadrature approximation in the X-axis is employed to convert the partial differential governing equations and the associated boundary conditions into a set of ordinary differential equations. By choosing the appropriate functions as the displacement and stress functions on each nodal line and then applying the Galerkin procedure, a system of non-linear algebraic equations is obtained, from which the non-linear bending response of the plate is determined through a Picard iteration scheme. Numerical results for zirconia/aluminium rectangular plates are given in dimensionless graphical form. The effects of the applied actuator voltage, the volume fraction exponent, the temperature gradient, as well as the characteristics of the boundary conditions are also studied in detail. Copyright (C) 2004 John Wiley Sons, Ltd.

Feasibility of controlling nitrification in predenitrification plants using DO, pH and ORP sensors

Experimental studies were carried out on a bench-scale nitrogen removal system with a predenitrification configuration to gain insights into the spatial and temporal variations of DO, pH and ORP in such systems. It is demonstrated that these signals correlate strongly with the operational states of the system, and could therefore be used as system performance indicators. The DO concentration in the first aerobic zone, when receiving constant aeration, and the net pH change between the last and first aerobic zones display strong correlations with the influent ammonia concentration for the domestic wastewater used in this study. The pH profile along the aerobic zones gives good indication on the extent of nitrification. The experimental results also showed a good correlation between ORP values in the last aerobic zone and effluent ammonia and nitrate concentrations, provided that DO in this zone is controlled at a constant level. These results suggest that the DO, pH and ORP sensors could potentially be used as alternatives to the on-line nutrient sensors for the control of continuous systems. An idea of using a fuzzy inference system to make an integrated use of these signals for on-line aeration control is presented and demonstrated on the bench-scale system with promising results. The use of these sensors has to date only been demonstrated in intermittent systems, such as sequencing batch reactor systems.

A comparison of SAR sensors for quantifying Melaleuca biomass on tropical floodplains in northern Australia and New Guinea

Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference