The OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS): Spectral Maps of the Asteroid Bennu

The OSIRIS-REx Visible and Infrared Spectrometer (OVIRS) is a point spectrometer covering the spectral range of 0.4 to 4.3 microns (25,000-2300 cm-1). Its primary purpose is to map the surface composition of the asteroid Bennu, the target asteroid of the OSIRIS-REx asteroid sample return mission. The information it returns will help guide the selection of the sample site. It will also provide global context for the sample and high spatial resolution spectra that can be related to spatially unresolved terrestrial observations of asteroids. It is a compact, low-mass (17.8 kg), power efficient (8.8 W average), and robust instrument with the sensitivity needed to detect a 5% spectral absorption feature on a very dark surface (3% reflectance) in the inner solar system (0.89-1.35 AU). It, in combination with the other instruments on the OSIRIS-REx Mission, will provide an unprecedented view of an asteroid's surface.Comment: 14 figures, 3 tables, Space Science Reviews, submitte

Detectors for the James Webb Space Telescope Near-Infrared Spectrograph I: Readout Mode, Noise Model, and Calibration Considerations

We describe how the James Webb Space Telescope (JWST) Near-Infrared Spectrograph's (NIRSpec's) detectors will be read out, and present a model of how noise scales with the number of multiple non-destructive reads sampling-up-the-ramp. We believe that this noise model, which is validated using real and simulated test data, is applicable to most astronomical near-infrared instruments. We describe some non-ideal behaviors that have been observed in engineering grade NIRSpec detectors, and demonstrate that they are unlikely to affect NIRSpec sensitivity, operations, or calibration. These include a HAWAII-2RG reset anomaly and random telegraph noise (RTN). Using real test data, we show that the reset anomaly is: (1) very nearly noiseless and (2) can be easily calibrated out. Likewise, we show that large-amplitude RTN affects only a small and fixed population of pixels. It can therefore be tracked using standard pixel operability maps.Comment: 55 pages, 10 figure

Histopathological and molecular heterogeneity among individuals with dementia associated with Presenilin mutations

BACKGROUND: Mutations in the presenilin (PSEN) genes are associated with early-onset familial Alzheimer's disease (FAD). Biochemical characterizations and comparisons have revealed that many PSEN mutations alter gamma-secretase activity to promote accumulation of toxic Abeta42 peptides. In this study, we compared the histopathologic and biochemical profiles of ten FAD cases expressing independent PSEN mutations and determined the degradation patterns of amyloid-beta precursor protein (AbetaPP), Notch, N-cadherin and Erb-B4 by gamma-secretase. In addition, the levels of Abeta40/42 peptides were quantified by ELISA. RESULTS: We observed a wide variation in type, number and distribution of amyloid deposits and neurofibrillary tangles. Four of the ten cases examined exhibited a substantial enrichment in the relative proportions of Abeta40 over Abeta42. The AbetaPP N-terminal and C-terminal fragments and Tau species, assessed by Western blots and scanning densitometry, also demonstrated a wide variation. The Notch-1 intracellular domain was negligible by Western blotting in seven PSEN cases. There was significant N-cadherin and Erb-B4 peptide heterogeneity among the different PSEN mutations. CONCLUSION: These observations imply that missense mutations in PSEN genes can alter a range of key gamma-secretase activities to produce an array of subtly different biochemical, neuropathological and clinical manifestations. Beyond the broad common features of dementia, plaques and tangles, the various PSEN mutations resulted in a wide heterogeneity and complexity and differed from sporadic AD.Fil: Maarouf, Chera L.. Sun Health Research Institute; Estados UnidosFil: Daugs, Ian D.. Sun Health Research Institute; Estados UnidosFil: Spina, Salvatore. Universita Degli Studi Di Siena; Italia. Indiana University; Estados UnidosFil: Vidal, Ruben. Indiana University; Estados UnidosFil: Kokjohn, Tyler A.. Sun Health Research Institute; Estados Unidos. Midwestern University; Estados UnidosFil: Patton, R. Lyle. Sun Health Research Institute; Estados UnidosFil: Kalback, Walter M.. Sun Health Research Institute; Estados UnidosFil: Luehrs, Dean C.. Sun Health Research Institute; Estados UnidosFil: Walker, Douglas G.. Sun Health Research Institute; Estados UnidosFil: Castaño, Eduardo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Beach, Thomas G.. Sun Health Research Institute; Estados UnidosFil: Ghetti, Bernardino. Indiana University; Estados UnidosFil: Roher, Alex E.. Sun Health Research Institute; Estados Unido

JWST Near-Infrared Detectors: Latest Test Results

The James Webb Space Telescope, an infrared-optimized space telescope being developed by NASA for launch in 2013, will utilize cutting-edge detector technology in its investigation of fundamental questions in astrophysics. JWST's near infrared spectrograph, NIRSpec utilizes two 2048 x 2048 HdCdTe arrays with Sidecar ASIC readout electronics developed by Teledyne to provide spectral coverage from 0.6 microns to 5 microns. We present recent test and calibration results for the NIRSpec flight arrays as well as data processing routines for noise reduction and cosmic ray rejection

Detector Arrays for the James Webb Space Telescope Near-Infrared Spectrograph

The James Webb Space Telescope's (JWST) Near Infrared Spectrograph (NIRSpec) incorporates two 5 micron cutoff (lambda(sub co) = 5 microns) 2048x2048 pixel Teledyne HgCdTe HAWAII-2RG sensor chip assemblies. These detector arrays, and the two Teledyne SIDECAR application specific integrated circuits that control them, are operated in space at T approx. 37 K. In this article, we provide a brief introduction to NIRSpec, its detector subsystem (DS), detector readout in the space radiation environment, and present a snapshot of the developmental status of the NIRSpec DS as integration and testing of the engineering test unit begins

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

James Webb Space Telescope Near-Infrared Spectrograph: Dark Performance of the First Flight Candidate Detector Arrays

The James Webb Space Telescope (JWST) Near Infrared Spectrograph (NIRSpec) incorporates two 5 micron cutoff (lambda(sub co) = 5 micron) 2048x2048 pixel Teledyne HgCdTe HAWAII-2RG sensor chip assemblies. These detector arrays, and the two Teledyne SIDECAR application specific integrated circuits that control them, are operated in space at T approx. 37 K. This article focuses on the measured performance of the first flight-candidate, and near-flight candidate, detector arrays. These are the first flight-packaged detector arrays that meet NIRSpec's challenging 6 e(-) rms total noise requirement

Abundance of the Quorum-Sensing Factor Ax21 in Four Strains of Stenotrophomonas maltophilia Correlates with Mortality Rate in a New Zebrafish Model of Infection

Stenotrophomonas maltophilia is a Gram-negative pathogen with emerging nosocomial incidence. Little is known about its pathogenesis and the genomic diversity exhibited by clinical isolates complicates the study of pathogenicity and virulence factors. Here, we present a strategy to identify such factors in new clinical isolates of S. maltophilia, incorporating an adult-zebrafish model of S. maltophilia infection to evaluate relative virulence coupled to 2D difference gel electrophoresis to explore underlying differences in protein expression. In this study we report upon three recent clinical isolates and use the collection strain ATCC13637 as a reference. The adult-zebrafish model shows discrimination capacity, i.e. from very low to very high mortality rates, with clinical symptoms very similar to those observed in natural S. maltophilia infections in fish. Strain virulence correlates with resistance to human serum, in agreement with previous studies in mouse and rat and therefore supporting zebrafish as a replacement model. Despite its clinical origin, the collection strain ATCC13637 showed obvious signs of attenuation in zebrafish, with null mortality. Multilocus-sequence-typing analysis revealed that the most virulent strains, UV74 and M30, exhibit the strongest genetic similitude. Differential proteomic analysis led to the identification of 38 proteins with significantly different abundance in the three clinical strains relative to the reference strain. Orthologs of several of these proteins have been already reported to have a role in pathogenesis, virulence or resistance mechanisms thus supporting our strategy. Proof of concept is further provided by protein Ax21, whose abundance is shown here to be directly proportional to mortality in the zebrafish infection model. Indeed, recent studies have demonstrated that this protein is a quorum-sensing-related virulence factor

Detectors for the James Webb Space Telescope Near-Infrared Spectrograph I: Readout Mode, Noise Model, and Calibration Considerations

We describe how the James Webb Space Telescope (JWST) Near-Infrared Spectrograph's (NIRSpec's) detectors will be read out, and present a model of how noise scales with the number of multiple non-destructive reads sampling-up-the-ramp. We believe that this noise model, which is validated using real and simulated test data, is applicable to most astronomical near-infrared instruments. We describe some non-ideal behaviors that have been observed in engineering grade NIRSpec detectors, and demonstrate that they are unlikely to affect NIRSpec sensitivity, operations, or calibration. These include a HAWAII-2RG reset anomaly and random telegraph noise (RTN). Using real test data, we show that the reset anomaly is: (1) very nearly noiseless and (2) can be easily calibrated out. Likewise, we show that RTN affects only a small and fixed population of pixels. It can therefore be tracked using standard pixel operability maps

Amyloid Plaques Beyond Aβ: A Survey of the Diverse Modulators of Amyloid Aggregation

Aggregation of the amyloid-β (Aβ) peptide is strongly correlated with Alzheimer’s disease (AD). Recent research has improved our understanding of the kinetics of amyloid fibril assembly and revealed new details regarding different stages in plaque formation. Presently, interest is turning toward studying this process in a holistic context, focusing on cellular components which interact with the Aβ peptide at various junctures during aggregation, from monomer to cross-β amyloid fibrils. However, even in isolation, a multitude of factors including protein purity, pH, salt content, and agitation affect Aβ fibril formation and deposition, often producing complicated and conflicting results. The failure of numerous inhibitors in clinical trials for AD suggests that a detailed examination of the complex interactions that occur during plaque formation, including binding of carbohydrates, lipids, nucleic acids, and metal ions, is important for understanding the diversity of manifestations of the disease. Unraveling how a variety of key macromolecular modulators interact with the Aβ peptide and change its aggregation properties may provide opportunities for developing therapies. Since no protein acts in isolation, the interplay of these diverse molecules may differentiate disease onset, progression, and severity, and thus are worth careful consideration