Trace Metal Sensors for Coastal Monitoring, Seaside, California, April 11-13, 2005: workshop proceedings

The Alliance for Coastal Technologies (ACT) Workshop on Trace Metal Sensors for Coastal Monitoring was convened April 11-13, 2005 at the Embassy Suites in Seaside, California with partnership from Moss Landing Marine Laboratories (MLML) and the Monterey Bay Aquarium Research Institute (MBARI). Trace metals play many important roles in marine ecosystems. Due to their extreme toxicity, the effects of copper, cadmium and certain organo-metallinc compounds (such as tributyltin and methylmercury) have received much attention. Lately, the sublethal effects of metals on phytoplankton biochemistry, and in some cases the expression of neurotoxins (Domoic acid), have been shown to be important environmental forcing functions determining the composition and gene expression in some groups. More recently the role of iron in controlling phytoplankton growth has led to an understanding of trace metal limitation in coastal systems. Although metals play an important role at many different levels, few technologies exist to provide rapid assessment of metal concentrations or metal speciation in the coastal zone where metal-induced toxicity or potential stimulation of harmful algal blooms, can have major economic impacts. This workshop focused on the state of on-site and in situ trace element detection technologies, in terms of what is currently working well and what is needed to effectively inform coastal zone managers, as well as guide adaptive scientific sampling of the coastal zone. Specifically the goals of this workshop were to: 1) summarize current regional requirements and future targets for metal monitoring in freshwater, estuarine and coastal environments; 2) evaluate the current status of metal sensors and possibilities for leveraging emerging technologies for expanding detection limits and target elements; and 3) help identify critical steps needed for and limits to operational deployment of metal sensors as part of routine water quality monitoring efforts. Following a series of breakout group discussions and overview talks on metal monitoring regulatory issues, analytical techniques and market requirements, workshop participants made several recommendations for steps needed to foster development of in situ metal monitoring capacities: 1. Increase scientific and public awareness of metals of environmental and biological concern and their impacts in aquatic environments. Inform scientific and public communities regarding actual levels of trace metals in natural and perturbed systems. 2. Identify multiple use applications (e.g., industrial waste steam and drinking water quality monitoring) to support investments in metal sensor development. (pdf contains 27 pages)

Transfer of Medical Sensor Technologies to Environmental Monitoring, Solomons, Maryland, April 6-8, 2005: workshop proceedings

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Parametric Analysis for Monitoring 2D Kinetics of Receptor-Ligand binding

Thermal fluctuation approach is widely used to monitor association kinetics of surface-bound receptor-ligand interactions. Various protocols such as sliding standard deviation (SD) analysis (SSA) and Page's test analysis (PTA) have been used to estimate two-dimensional (2D) kinetic rates from the time course of displacement of molecular carrier. In the current work, we compared the estimations from both SSA and modified PTA using measured data from an optical trap assay and simulated data from a random number generator. Our results indicated that both SSA and PTA were reliable in estimating 2D kinetic rates. Parametric analysis also demonstrated that such the estimations were sensitive to parameters such as sampling rate, sliding window size, and threshold. These results furthered the understandings in quantifying the biophysics of receptor-ligand interactions.

Single cell proteomics microchip to profile immune function, with applications in stem cell biology, translational disease mechanism study and clinical therapeutics monitoring

In response to infection or tissue dysfunction, immune cells develop into highly heterogeneous repertoires with diverse functions. Capturing the full spectrum of these functions requires analysis of large numbers of effector molecules from single cells. However, currently only 3-5 functional proteins can be measured from single cells. We developed a single cell functional proteomics approach that integrates a microchip platform with multiplex cell purification. This approach can quantitate 20 proteins from >5,000 phenotypically pure single cells simultaneously. With a 1-million fold miniaturization, the system can detect down to ~100 molecules and requires only ~104 cells. Single cell functional proteomic analysis finds broad applications in basic, translational and clinical studies. In the three studies conducted, it yielded critical insights for understanding clinical cancer immunotherapy, inflammatory bowel disease (IBD) mechanism and hematopoietic stem cell (HSC) biology.

To study phenotypically defined cell populations, single cell barcode microchips were coupled with upstream multiplex cell purification based on up to 11 parameters. Statistical algorithms were developed to process and model the high dimensional readouts. This analysis evaluates rare cells and is versatile for various cells and proteins. (1) We conducted an immune monitoring study of a phase 2 cancer cellular immunotherapy clinical trial that used T-cell receptor (TCR) transgenic T cells as major therapeutics to treat metastatic melanoma. We evaluated the functional proteome of 4 antigen-specific, phenotypically defined T cell populations from peripheral blood of 3 patients across 8 time points. (2) Natural killer (NK) cells can play a protective role in chronic inflammation and their surface receptor – killer immunoglobulin-like receptor (KIR) – has been identified as a risk factor of IBD. We compared the functional behavior of NK cells that had differential KIR expressions. These NK cells were retrieved from the blood of 12 patients with different genetic backgrounds. (3) HSCs are the progenitors of immune cells and are thought to have no immediate functional capacity against pathogen. However, recent studies identified expression of Toll-like receptors (TLRs) on HSCs. We studied the functional capacity of HSCs upon TLR activation. The comparison of HSCs from wild-type mice against those from genetics knock-out mouse models elucidates the responding signaling pathway.

In all three cases, we observed profound functional heterogeneity within phenotypically defined cells. Polyfunctional cells that conduct multiple functions also produce those proteins in large amounts. They dominate the immune response. In the cancer immunotherapy, the strong cytotoxic and antitumor functions from transgenic TCR T cells contributed to a ~30% tumor reduction immediately after the therapy. However, this infused immune response disappeared within 2-3 weeks. Later on, some patients gained a second antitumor response, consisted of the emergence of endogenous antitumor cytotoxic T cells and their production of multiple antitumor functions. These patients showed more effective long-term tumor control. In the IBD mechanism study, we noticed that, compared with others, NK cells expressing KIR2DL3 receptor secreted a large array of effector proteins, such as TNF-α, CCLs and CXCLs. The functions from these cells regulated disease-contributing cells and protected host tissues. Their existence correlated with IBD disease susceptibility. In the HSC study, the HSCs exhibited functional capacity by producing TNF-α, IL-6 and GM-CSF. TLR stimulation activated the NF-κB signaling in HSCs. Single cell functional proteome contains rich information that is independent from the genome and transcriptome. In all three cases, functional proteomic evaluation uncovered critical biological insights that would not be resolved otherwise. The integrated single cell functional proteomic analysis constructed a detail kinetic picture of the immune response that took place during the clinical cancer immunotherapy. It revealed concrete functional evidence that connected genetics to IBD disease susceptibility. Further, it provided predictors that correlated with clinical responses and pathogenic outcomes.

Watershed monitoring and the TMDL modeling to assess bacterial loading in estuarine environments to improve management

Shellfish bed closures along the North Carolina coast have increased over the years seemingly concurrent with increases in population (Mallin 2000). More and faster flowing storm water has come to mean more bacteria, and fecal indicator bacterial (FIB) standards for shellfish harvesting are often exceeded when no source of contamination is readily apparent (Kator and Rhodes, 1994). Could management reduce bacterial loads if the source of the bacteria where known? Several potentially useful methods for differentiating human versus animal pollution sources have emerged including Ribotyping and Multiple Antibiotic Resistance (MAR) (US EPA, 2005). Total Maximum Daily Load (TMDL) studies on bacterial sources have been conducted for streams in NC mountain and Piedmont areas (U.S. EPA, 1991 and 2005) and are likely to be mandated for coastal waters. TMDL analysis estimates allowable pollutant loads and allocates them to known sources so management actions may be taken to restore water to its intended uses (U.S. EPA, 1991 and 2005). This project sought first to quantify and compare fecal contamination levels for three different types of land use on the coast, and second, to apply MAR and ribotyping techniques and assess their effectiveness for indentifying bacterial sources. Third, results from these studies would be applied to one watershed to develop a case study coastal TMDL. All three watershed study areas are within Carteret County, North Carolina. Jumping Run Creek and Pettiford Creek are within the White Oak River Basin management unit whereas the South River falls within the Neuse River Basin. Jumping Run Creek watershed encompasses approximately 320 ha. Its watershed was a dense, coastal pocosin on sandy, relic dune ridges, but current land uses are primarily medium density residential. Pettiford Creek is in the Croatan National Forest, is 1133 ha. and is basically undeveloped. The third study area is on Open Grounds Farm in the South River watershed. Half of the 630 ha. watershed is under cultivation with most under active water control (flashboard risers). The remaining portion is forested silviculture.(PDF contains 4 pages)

A bayesian probabilistic approach to structural health monitoring

A Bayesian probabilistic methodology for on-line structural health monitoring which addresses the issue of parameter uncertainty inherent in problem is presented. The method uses modal parameters for a limited number of modes identified from measurements taken at a restricted number of degrees of freedom of a structure as the measured structural data. The application presented uses a linear structural model whose stiffness matrix is parameterized to develop a class of possible models. Within the Bayesian framework, a joint probability density function (PDF) for the model stiffness parameters given the measured modal data is determined. Using this PDF, the marginal PDF of the stiffness parameter for each substructure given the data can be calculated.

Monitoring the health of a structure using these marginal PDFs involves two steps. First, the marginal PDF for each model parameter given modal data from the undamaged structure is found. The structure is then periodically monitored and updated marginal PDFs are determined. A measure of the difference between the calibrated and current marginal PDFs is used as a means to characterize the health of the structure. A procedure for interpreting the measure for use by an expert system in on-line monitoring is also introduced.

The probabilistic framework is developed in order to address the model parameter uncertainty issue inherent in the health monitoring problem. To illustrate this issue, consider a very simplified deterministic structural health monitoring method. In such an approach, the model parameters which minimize an error measure between the measured and model modal values would be used as the "best" model of the structure. Changes between the model parameters identified using modal data from the undamaged structure and subsequent modal data would be used to find the existence, location and degree of damage. Due to measurement noise, limited modal information, and model error, the "best" model parameters might vary from one modal dataset to the next without any damage present in the structure. Thus, difficulties would arise in separating normal variations in the identified model parameters based on limitations of the identification method and variations due to true change in the structure. The Bayesian framework described in this work provides a means to handle this parametric uncertainty.

The probabilistic health monitoring method is applied to simulated data and laboratory data. The results of these tests are presented.

Wind-driven desertification: process modeling, remote monitoring, and forecasting

Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.

The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.

In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.

Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.

Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.

The distribution of Corixidae in relation to the water quality of British lakes: A monitoring model

This article is an attempt to devise a method of using certain species of Corixidae as a basis for the assessment of general water quality in lakes. An empirical graphical representation of the distribution of populations or communities of Corixidae in relation to conductivity, based mainly on English and Welsh lakes, is used as a predictive monitoring model to establish the "expected" normal community at a given conductivity, representing the total ionic concentration of the water body. A test sample from another lake of known conductivity is then compared with "expected" community. The "goodness of fit" is examined visually or by calculation of indices of similarity based on the relative proportions of the constituent species of each community. A computer programme has been devised for this purpose.