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Ricin is a family member of the lethal ribosome-inactivating proteins (RIP) found in plants. Ricin toxin A-chain (RTA) from castor beans catalyzes the hydrolytic depurination of a single base from a GAGA tetraloop of eukaryotic rRNA to release a single adenine from the sarcin-ricin loop (SRL). Protein synthesis is inhibited by loss of the elongation factor binding site resulting in cell death. We report a sensitive coupled assay for the measurement of adenine released from ribosomes or small stem-loop RNAs by RTA catalysis. Adenine phosphoribosyl transferase (APRTase) and pyruvate orthophosphate dikinase (PPDK) convert adenine to ATP for quantitation by firefly luciferase. The resulting AMP is cycled to ATP to give sustained luminescence proportional to adenine concentration. Subpicomole adenine quantitation permits the action of RTA on eukaryotic ribosomes to be followed in continuous, high-throughput assays. Facile analysis of RIP catalytic activity will have applications in plant toxin detection, inhibitor screens, mechanistic analysis of depurinating agents on oligonucleotides and intact ribosomes, and in cancer immunochemotherapy. Kinetic analysis of the catalytic action of RTA on rabbit reticulocyte 80S ribosomes establishes a catalytic efficiency of 2.6 x [10.sup.8] [M.sup.-1] [s.sup.-1], a diffusion limited reaction indicating catalytic perfection even with large reactants.

A study was conducted to investigate circular DNA and DNA/RNA hybrid GAGA sequence oligonucleotides as minimal substrates and inhibitor scaffolds for Ricin Toxin A-chain (RTA) catalysis. The results revealed that RNA/DNA hybrid oligonucleotide cyclic GdAGA provides a new scaffold for RTA inhibitor design.

Part of the Earth Observing Sysytem Aqua Advanced Microwave Scanning Radiometer (AMSR-E) Arctic sea ice validation campaign in March 2003 was dedicated to the validation of snow depth on sea ice and ice temperature products. The difficulty with validating these two variables is that neither can currently be measured other than in situ. For this reason, two aircraft flights on March 13 and 19, 2003, were dedicated to these products, and flight lines were coordinated with in situ measurements of snow and sea ice physical properties. One flight was in the vicinity of Barrow, AK, covering Elson Lagoon and the adjacent Chukchi and Beaufort Seas. The other flight was farther north in the Beaufort Sea (about 73[degrees]N, 147.5[degrees]W) and was coordinated with a Navy ice camp. The results confirm the AMSR-E snow depth algorithm and its coefficients for first-year ice when it is relatively smooth. For rough first-year ice and for multiyear ice, there is still a relationship between the spectral gradient ratio of 19 and 37 GHz, but a different set of algorithm coefficients is necessary. Comparisons using other AMSR-E channels did not provide a clear signature of sea ice characteristics and, hence, could not provide guidance for the choice of algorithm coefficients. The limited comparison of in situ snow-ice interface and surface temperatures with 6-GHz brightness temperatures, which are used for the retrieval of ice temperature, shows that the 6-GHz temperature is correlated with the snow-ice interface temperature to only a limited extent. For strong temperature gradients within the snow layer, it is clear that the 6-GHz temperature is a weighted average of the entire snow layer. Index Terms--Advanced Microwave Scanning Radiometer (AMSR), passive microwave, sea ice, snow on sea ice, validation.

This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: 1) the National Aeronautics and Space Administration Team (NT) algorithm and 2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over-or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper were assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7, 18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an 'effective' viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors. Index Terms--Passive microwave, remote sensing, sea ice.

The objective of this paper is to characterize spatial properties of snow-depth structures and their role as indicators of sea-ice properties and sea-ice-morphogenetic processes, and to provide quantitative measures of sea-ice properties that may be utilized in analyses of passive-microwave data. Snow-depth data collected near Point Barrow, Alaska, as part of the AMSR-Ice03 Field Validation Campaign for Advanced Microwave Scanning Radiometer (AMSR)-E-Sea-Ice Products from the NASA Earth Observing System Aqua satellite, are analyzed and compared to P-3 Polarimetric Scanning Radiometer (PSR) data, a proxy for AMSR-E brightness temperatures. The approach taken in the analysis is geostatistical characterization. Vario functions of first and second order are calculated for the snow-depth profiles, then geostatistical classification parameters are extracted and combined into feature vectors, on which the characterization is based. The complexity of sea ice requires a generalization of the method by introduction of the hyperparameter concept. Results include a quantitative characterization of sea-ice provinces from field transects in the Beaufort Sea, Chukchi Sea, and Elson Lagoon, which represent a good subset of Arctic sea-ice types, an internal segmentation of the longer profiles, and a derivation of surface-roughness length and of sea-ice-type complexity. PSR data reflect complexity of spatial snow-depth structures as captured in multidimensional feature vectors and, less directly, snow-depth and surface-roughness length. These results indicate that passive-microwave data in general may be affected by spatial snow depth and surface roughness, with a dependence on scale and quantified by geostatistical classification. Index Terms--Classification, morphogenesis, remote sensing, roughness, sea ice, spatial data analysis.

Aircraft-acquired passive microwave data, laser radar height observations, RADARSAT synthetic aperture radar imagery, and in situ measurements obtained during the AMSR-Ice03 experiment are used to investigate relationships between microwave emission and ice characteristics over several space scales. The data fusion allows delineation of the shore-fast ice and pack ice in the Barrow area, AK, into several ice classes. Results show good agreement between observed and Polarimetric Scanning Radiometer (PSR)-derived snow depths over relatively smooth ice, with larger differences over ridged and rubbled ice. The PSR results are consistent with the effects on snow depth of the spatial distribution and nature of ice roughness, ridging, and other factors such as ice age. Apparent relationships exist between ice roughness and the degree of depolarization of emission at 10, 19, and 37 GHz. This depolarization would yield overestimates of total ice concentration using polarization-based algorithms, with indications of this seen when the NT-2 algorithm is applied to the PSR data. Other characteristics of the microwave data, such as effects of grounding of sea ice and large contrast between sea ice and adjacent land, are also apparent in the PSR data. Overall, the results further demonstrate the importance of macroscale ice roughness conditions such as ridging and rubbling on snow depth and microwave emissivity. Index Terms--Passive microwave, roughness, sea ice, shore-fast ice, snow depth.

An overview of the March 2003 coordinated sea ice field campaign in the Alaskan Arctic is presented with reference to the papers in this special section. This campaign is part of the program to validate the Aqua Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) sea ice products. Standard AMSR-E sea ice products include sea ice concentration, sea ice temperature, and snow depth on sea ice. The validation program consists of three elements, namely: 1) satellite data comparisons; 2) coordinated satellite/aircraft/surface measurements; and 3) modeling and sensitivity analyses. Landsat-7 and RADARSAT observations were used in comparative studies with the retrieved AMSR-E sea ice concentrations. The aircraft sensors provided high-resolution microwave imagery of the surface, atmospheric profiles of temperature and humidity, and digital records of sea ice conditions. When combined with in situ measurements, aircraft data were used to validate the AMSR-E sea ice temperature and snow-depth products. The modeling studies helped interpret the field-data comparisons, provided insight on the limitations of the AMSR-E sea ice algorithms, and suggested potential improvements to the AMSR-E retrieval algorithms. Index Terms--Advanced Microwave Scanning Radiometer for the Earth Observing Mission (AMSR-E), Arctic, sea ice, validation.

In March 2003, a field validation campaign was conducted on the sea ice near Barrow, AK. The goal of this campaign was to produce an extensive dataset of sea ice thickness and snow properties (depth and stratigraphy) against which remote sensing products collected by aircraft and satellite could be compared. Chief among these were products from the Polarimetric Scanning Radiometer (PSR) flown aboard a NASA P-3B aircraft and the Aqua Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The data were collected in four field areas: three on the coastal sea ice near Barrow, AK, and the fourth out on the open ice pack 175 km northeast of Barrow. The snow depth ranged from 9.4-20.8 cm in coastal areas (n = 9881 for three areas) with the thinnest snow on ice that had formed late in the winter. Out in the main pack ice, the snow was 20.6 cm deep (n = 1906). The ice in all four areas ranged from 138-219 cm thick (n = 1952), with the lower value again where the ice had formed late in the winter. Snow layer and grain characteristics observed in 118 snow pits indicated that 44% of observed snow layers were depth hoar; 46% were wind slab. Snow and ice measurements were keyed to photomosaics produced from low-altitude vertical aerial photographs. Using these, and a distinctive three-way relationship between ice roughness, snow surface characteristics, and snow depth, strip maps of snow depth, each about 2 km wide, were produced bracketing the traverse lines. These maps contain an unprecedented level of snow depth detail against which to compare remote sensing products. The maps are used in other papers in this special issue to examine the retrieval of snow properties from the PSR and AMSR-E sensors. Index Terms--Cryosphere, field validation, sea ice, snow.

FIFTY MORE YEARS BELOW ZERO: TRIBUTES AND MEDITATIONS FOR THE NAVAL ARCTIC RESEARCH LABORATORY'S FIRST HALF CENTURY. Edited by DAVID W. NORTON. Calgary, Alberta, and Fairbanks, Alaska: The Arctic Institute [...]