Expression of the alpha subunit of PABA peptide hydrolase (EC 3.4.24.18) in MDCK cells Synthesis and secretion of an enzymatically inactive homodimer

AbstractIn this paper, we report the expression of PPHα in the polarized cell line MDCK (Madin Darby canine kidney). In these cells, the enzyme was synthesized m an inactive profonn, which upon treatment with trypsin was activated. The enzyme isolated from cell extracts was core-glycosylated and appeared to be retained in the ER as a homodimer. No PPHα was detectable on the surface of intact cells by immunofluoreseence. However, a complex glycosylated soluble but inactive form was present in the culture medium, suggesting that proteolytic removal of the C-terminal membrane anchoring peptide leads to the secretion of PPHα

Alpha, Betti and the Megaparsec Universe: on the Topology of the Cosmic Web

We study the topology of the Megaparsec Cosmic Web in terms of the scale-dependent Betti numbers, which formalize the topological information content of the cosmic mass distribution. While the Betti numbers do not fully quantify topology, they extend the information beyond conventional cosmological studies of topology in terms of genus and Euler characteristic. The richer information content of Betti numbers goes along the availability of fast algorithms to compute them. For continuous density fields, we determine the scale-dependence of Betti numbers by invoking the cosmologically familiar filtration of sublevel or superlevel sets defined by density thresholds. For the discrete galaxy distribution, however, the analysis is based on the alpha shapes of the particles. These simplicial complexes constitute an ordered sequence of nested subsets of the Delaunay tessellation, a filtration defined by the scale parameter, $\alpha$. As they are homotopy equivalent to the sublevel sets of the distance field, they are an excellent tool for assessing the topological structure of a discrete point distribution. In order to develop an intuitive understanding for the behavior of Betti numbers as a function of $\alpha$, and their relation to the morphological patterns in the Cosmic Web, we first study them within the context of simple heuristic Voronoi clustering models. Subsequently, we address the topology of structures emerging in the standard LCDM scenario and in cosmological scenarios with alternative dark energy content. The evolution and scale-dependence of the Betti numbers is shown to reflect the hierarchical evolution of the Cosmic Web and yields a promising measure of cosmological parameters. We also discuss the expected Betti numbers as a function of the density threshold for superlevel sets of a Gaussian random field.Comment: 42 pages, 14 figure

Cognitive Functioning in Patients with Bipolar Disorder: Association with Depressive Symptoms and Alcohol Use

BACKGROUND: Cognitive dysfunction is clearly recognized in bipolar patients, but the degree of impairment varies due to methodological factors as well as heterogeneity in patient populations. The goal of this study was to evaluate cognitive functioning in bipolar patients and to assess its association with depressive symptoms. Post hoc the relationship with lifetime alcohol use disorder was explored. METHODOLOGY/PRINCIPAL FINDINGS: The study included 110 bipolar patients and 75 healthy controls. Patients with severe depressive symptoms, (hypo)manic symptoms and current severe alcohol use disorder were excluded. Diagnoses were evaluated via the Mini-International Neuropsychiatric Interview. Cognitive functioning was measured in domains of psychomotor speed, speed of information processing, attentional switching, verbal memory, visual memory, executive functioning and an overall mean score. Severity of depression was assessed by the Inventory of Depressive Symptomatology-self rating. Patients were euthymic (n = 46) or with current mild (n = 38) or moderate (n = 26) depressive symptoms. Cognitive impairment was found in 26% (z-score 2 or more above reference control group for at least one domain) of patients, most prominent in executive functioning (effect size; ES 0.49) and speed of information processing (ES 0.47). Depressive symptoms were associated with dysfunction in psychomotor speed (adjusted beta 0.43; R(2) 7%), speed of information processing (adjusted beta 0.36; R(2) 20%), attentional switching (adjusted beta 0.24; R(2) 16%) and the mean score (adjusted beta 0.23; R(2) 24%), but not with verbal and visual memory and executive functioning. Depressive symptoms explained 24% of the variance in the mean z-score of all 6 cognitive domains. Comorbid lifetime alcohol use (n = 21) was not associated with cognitive dysfunction. CONCLUSIONS/SIGNIFICANCE: Cognitive dysfunction in bipolar disorder is more severe in patients with depressive symptoms, especially regarding speed and attention. Therefore, interpretation of cognitive functioning in patients with depressive symptoms should be cautious. No association was found between cognitive functioning and lifetime comorbid alcohol use disorder

Can Variation in Hypothalamic-Pituitary-Adrenal (HPA)-Axis Activity Explain the Relationship between Depression and Cognition in Bipolar Patients?

Background: Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is thought to be associated with more mood symptoms and worse cognitive functioning. This study examined whether variation in HPA axis activity underlies the association between mood symptoms and cognitive functioning. Methodology/Principal Findings: In 65 bipolar patients cognitive functioning was measured in domains of psychomotor speed, speed of information processing, attentional switching, verbal memory, visual memory, executive functioning and an overall mean score. Severity of depression was assessed by the Inventory of Depressive Symptomatology-self rating version. Saliva cortisol measurements were performed to calculate HPA axis indicators: cortisol awakening response, diurnal slope, the evening cortisol level and the cortisol suppression on the dexamethasone suppression test. Regression analyses of depressive symptoms and cognitive functioning on each HPA axis indicator were performed. In addition we calculated percentages explanation of the association between depressive symptoms and cognition by HPA axis indicators. Depressive symptoms were associated with dysfunction in psychomotor speed, attentional switching and the mean score, as well as with attenuation in diurnal slope value. No association was found between HPA axis activity and cognitive functioning and HPA axis activity did not explain the associations between depressive symptoms and cognition. Conclusions/Significance: As our study is the first one in this field specific for bipolar patients and changes in HPA-axis activity did not seem to explain the association between severity of depressive symptoms and cognitive functioning in bipolar patients, future studies are needed to evaluate other factors that might explain this relationship

Capturing Complete Spatial Context in Satellite Observations of Greenhouse Gases

Scientific consensus from a 2015 pre-Decadal Survey workshop highlighted the essential need for a wide-swath (mapping) low earth orbit (LEO) instrument delivering carbon dioxide (CO_2), methane (CH_4), and carbon monoxide (CO) measurements with global coverage. OCO-2 pioneered space-based CO_2 remote sensing, but lacks the CH_4, CO and mapping capabilities required for an improved understanding of the global carbon cycle. The Carbon Balance Observatory (CARBO) advances key technologies to enable high-performance, cost-effective solutions for a space-based carbon-climate observing system. CARBO is a compact, modular, 15-30° field of view spectrometer that delivers high-precision CO_2, CH_4, CO and solar induced chlorophyll fluorescence (SIF) data with weekly global coverage from LEO. CARBO employs innovative immersion grating technologies to achieve diffraction-limited performance with OCO-like spatial (2x2 km^2) and spectral (λ/Δλ ≈ 20,000) resolution in a package that is >50% smaller, lighter and more cost-effective. CARBO delivers a 25- to 50-fold increase in spatial coverage compared to OCO-2 with no loss of detection sensitivity. Individual CARBO modules weigh < 20 kg, opening diverse new space-based platform opportunities

Cloud type comparisons of AIRS, CloudSat, and CALIPSO cloud height and amount

The precision of the two-layer cloud height fields derived from the Atmospheric Infrared Sounder (AIRS) is explored and quantified for a five-day set of observations. Coincident profiles of vertical cloud structure by CloudSat, a 94 GHz profiling radar, and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), are compared to AIRS for a wide range of cloud types. Bias and variability in cloud height differences are shown to have dependence on cloud type, height, and amount, as well as whether CloudSat or CALIPSO is used as the comparison standard. The CloudSat-AIRS biases and variability range from &amp;minus;4.3 to 0.5&amp;plusmn;1.2&amp;ndash;3.6 km for all cloud types. Likewise, the CALIPSO-AIRS biases range from 0.6&amp;ndash;3.0&amp;plusmn;1.2&amp;ndash;3.6 km (&amp;minus;5.8 to &amp;minus;0.2&amp;plusmn;0.5&amp;ndash;2.7 km) for clouds &amp;ge;7 km (&amp;lt;7 km). The upper layer of AIRS has the greatest sensitivity to Altocumulus, Altostratus, Cirrus, Cumulonimbus, and Nimbostratus, whereas the lower layer has the greatest sensitivity to Cumulus and Stratocumulus. Although the bias and variability generally decrease with increasing cloud amount, the ability of AIRS to constrain cloud occurrence, height, and amount is demonstrated across all cloud types for many geophysical conditions. In particular, skill is demonstrated for thin Cirrus, as well as some Cumulus and Stratocumulus, cloud types infrared sounders typically struggle to quantify. Furthermore, some improvements in the AIRS Version 5 operational retrieval algorithm are demonstrated. However, limitations in AIRS cloud retrievals are also revealed, including the existence of spurious Cirrus near the tropopause and low cloud layers within Cumulonimbus and Nimbostratus clouds. Likely causes of spurious clouds are identified and the potential for further improvement is discussed

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO₂) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) X_(CO₂) retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O₂ A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO₂ and H₂O column abundances using observations taken at 1.61 µm (weak CO₂ band) and 2.06 µm (strong CO₂ band), while neglecting atmospheric scattering. The CO₂ and H₂O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of  ≃ 20–25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be  ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April–May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1

The ACOS CO_2 retrieval algorithm – Part 1: Description and validation against synthetic observations

This work describes the NASA Atmospheric CO_2 Observations from Space (ACOS) X_(CO_2) retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of ~0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small

The on-orbit performance of the Orbiting Carbon Observatory-2 (OCO-2) instrument and its radiometrically calibrated products

The Orbiting Carbon Observatory-2 (OCO-2) carries and points a three-channel imaging grating spectrometer designed to collect high-resolution, co-boresighted spectra of reflected sunlight within the molecular oxygen (O_2) A-band at 0.765 microns and the carbon dioxide (CO_2) bands at 1.61 and 2.06 microns. These measurements are calibrated and then combined into soundings that are analyzed to retrieve spatially resolved estimates of the column-averaged CO_2 dry-air mole fraction, XCO_2. Variations of XCO_2 in space and time are then analyzed in the context of the atmospheric transport to quantify surface sources and sinks of CO_2. This is a particularly challenging remote-sensing observation because all but the largest emission sources and natural absorbers produce only small (< 0.25 %) changes in the background XCO_2 field. High measurement precision is therefore essential to resolve these small variations, and high accuracy is needed because small biases in the retrieved XCO_2 distribution could be misinterpreted as evidence for CO_2 fluxes. To meet its demanding measurement requirements, each OCO-2 spectrometer channel collects 24 spectra s^(−1) across a narrow ( 17 000), dynamic range (∼ 10^4), and sensitivity (continuum signal-to-noise ratio > 400). The OCO-2 instrument performance was extensively characterized and calibrated prior to launch. In general, the instrument has performed as expected during its first 18 months in orbit. However, ongoing calibration and science analysis activities have revealed a number of subtle radiometric and spectroscopic challenges that affect the yield and quality of the OCO-2 data products. These issues include increased numbers of bad pixels, transient artifacts introduced by cosmic rays, radiance discontinuities for spatially non-uniform scenes, a misunderstanding of the instrument polarization orientation, and time-dependent changes in the throughput of the oxygen A-band channel. Here, we describe the OCO-2 instrument, its data products, and its on-orbit performance. We then summarize calibration challenges encountered during its first 18 months in orbit and the methods used to mitigate their impact on the calibrated radiance spectra distributed to the science community