A diagnostic study of temperature controls on global terrestrial carbon exchange

The observed interannual variability of atmospheric CO2 reflects short-term variability in sources and sinks of CO2 . Analyses using 13CO2 and O2 suggest that much of the observed interannual variability is due to changes in terrestrial CO2 exchange. First principles, empirical correlations and process models suggest a link between climate variation and net ecosystem exchange, but the scaling of ecological process studies to the globe is notoriously difficult. We sought to identify a component of global CO2 exchange that varied coherently with land temperature anomalies using an inverse modeling approach. We developed a family of simplified spatially aggregated ecosystem models (designated K-model versions) consisting of five compartments: atmospheric CO2 , live vegetation, litter, and two soil pools that differ in turnover times. The pools represent cumulative differences from mean C storage due to temperature variability and can thus have positive or negative values. Uptake and respiration of CO2 are assumed to be linearly dependent on temperature. One model version includes a simple representation of the nitrogen cycle in which changes in the litter and soil carbon pools result in stoichiometric release of plant-available nitrogen, the other omits the nitrogen feedback. The model parameters were estimated by inversion of the model against global temperature and CO2 anomaly data using the variational method. We found that the temperature sensitivity of carbon uptake (NPP) was less than that of respiration in all model versions. Analyses of model and data also showed that temperature anomalies trigger ecosystem changes on multiple, lagged time-scales. Other recent studies have suggested a more active land biosphere at Northern latitudes in response to warming and longer growing seasons. Our results indicate that warming should increase NPP, consistent with this theory, but that respiration should increase more than NPP, leading to decreased or negative NEP. A warming trend could, therefore increase NEP if the indirect feedbacks through nutrients were larger than the direct effects of temperature on NPP and respiration, a conjecture which can be tested experimentally. The fraction of the growth rate not predicted by the K-model represents model and data errors, and variability in anthropogenic release, ocean uptake, and other processes not explicitly represented in the model. These large positive and negative residuals from the K-model may be associated with the Southern Oscillation Index

On the edge degrees of trees

Let mij(G) be the number of edges of graph G, connecting vertices of degrees i and j. Necessary and sufficient conditions are established on a symmetric matrix M of type Δ × Δ such that there is a tree T for which Mij = mij(T) holds for all i, j

Characterizing the Information Content of Cloud Thermodynamic Phase Retrievals from the Notional PACE OCI Shortwave Reflectance Measurements

We rigorously quantify the probability of liquid or ice thermodynamic phase using only shortwave spectral channels specific to the NASA MODIS, VIIRS, and the notional future PACE imager. The results show that two shortwave-infrared channels (2135 nm and 2250 nm) provide more information on cloud thermodynamic phase than either channel alone. The analysis is performed with a nonlinear statistical estimation approach, the GEneralized Nonlinear Retrieval Analysis (GENRA). The GENRA technique has previously been used to quantify the retrieval of cloud optical properties from passive shortwave observations, for an assumed thermodynamic phase. Here we present the methodology needed to extend the utility of GENRA to a binary thermodynamic phase space (i.e. liquid or ice). We apply formal information content metrics to quantify our results; two of these (mutual and conditional information) have not previously been used in the field of cloud studies

Transformation of enals and enones into the glycoside-type derivatives by electrochemical generation of phenyl seleny cation

1126-112

Radiomics-Based Assessment of Primary Sjögren's Syndrome From Salivary Gland Ultrasonography Images

Salivary gland ultrasonography (SGUS) has shown good potential in the diagnosis of primary Sjögren's syndrome (pSS). However, a series of international studies have reported needs for improvements of the existing pSS scoring procedures in terms of inter/intra observer reliability before being established as standardized diagnostic tools. The present study aims to solve this problem by employing radiomics features and artificial intelligence (AI) algorithms to make the pSS scoring more objective and faster compared to human expert scoring. The assessment of AI algorithms was performed on a two-centric cohort, which included 600 SGUS images (150 patients) annotated using the original SGUS scoring system proposed in 1992 for pSS. For each image, we extracted 907 histogram-based and descriptive statistics features from segmented salivary glands. Optimal feature subsets were found using the genetic algorithm based wrapper approach. Among the considered algorithms (seven classifiers and five regressors), the best preforming was the multilayer perceptron (MLP) classifier (κ = 0.7). The MLP over-performed average score achieved by the clinicians (κ = 0.67) by the considerable margin, whereas its reliability was on the level of human intra-observer variability (κ = 0.71). The presented findings indicate that the continuously increasing HarmonicSS cohort will enable further advancements in AI-based pSS scoring methods by SGUS. In turn, this may establish SGUS as an effective noninvasive pSS diagnostic tool, with the final goal to supplement current diagnostic tests

Three-dimensional reconstruction and NURBS-based structured meshing of coronary arteries from the conventional X-ray angiography projection images

Despite its two-dimensional nature, X-ray angiography (XRA) has served as the gold standard imaging technique in the interventional cardiology for over five decades. Accordingly, demands for tools that could increase efficiency of the XRA procedure for the quantitative analysis of coronary arteries (CA) are constantly increasing. The aim of this study was to propose a novel procedure for three-dimensional modeling of CA from uncalibrated XRA projections. A comprehensive mathematical model of the image formation was developed and used with a robust genetic algorithm optimizer to determine the calibration parameters across XRA views. The frames correspondences between XRA acquisitions were found using a partial-matching approach. Using the same matching method, an efficient procedure for vessel centerline reconstruction was developed. Finally, the problem of meshing complex CA trees was simplified to independent reconstruction and meshing of connected branches using the proposed nonuniform rational B-spline (NURBS)-based method. Because it enables structured quadrilateral and hexahedral meshing, our method is suitable for the subsequent computational modelling of CA physiology (i.e. coronary blood flow, fractional flow reverse, virtual stenting and plaque progression). Extensive validations using digital, physical, and clinical datasets showed competitive performances and potential for further application on a wider scale

Regulation of TMPRSS6 by BMP6 and iron in human cells and mice.

Mutations in transmembrane protease, serine 6 (TMPRSS6), encoding matriptase-2, are responsible for the familial anemia disorder iron-refractory iron deficiency anemia (IRIDA). Patients with IRIDA have inappropriately elevated levels of the iron regulatory hormone hepcidin, suggesting that TMPRSS6 is involved in negatively regulating hepcidin expression. Hepcidin is positively regulated by iron via the bone morphogenetic protein (BMP)-SMAD signaling pathway. In this study, we investigated whether BMP6 and iron also regulate TMPRSS6 expression. Here we demonstrate that, in vitro, treatment with BMP6 stimulates TMPRSS6 expression at the mRNA and protein levels and leads to an increase in matriptase-2 activity. Moreover, we identify that inhibitor of DNA binding 1 is the key element of the BMP-SMAD pathway to regulate TMPRSS6 expression in response to BMP6 treatment. Finally, we show that, in mice, Tmprss6 mRNA expression is stimulated by chronic iron treatment or BMP6 injection and is blocked by injection of neutralizing antibody against BMP6. Our results indicate that BMP6 and iron not only induce hepcidin expression but also induce TMPRSS6, a negative regulator of hepcidin expression. Modulation of TMPRSS6 expression could serve as a negative feedback inhibitor to avoid excessive hepcidin increases by iron to help maintain tight homeostatic balance of systemic iron levels

In Vivo Delivery of Gremlin siRNA Plasmid Reveals Therapeutic Potential against Diabetic Nephropathy by Recovering Bone Morphogenetic Protein-7

Diabetic nephropathy is a complex and poorly understood disease process, and our current treatment options are limited. It remains critical, then, to identify novel therapeutic targets. Recently, a developmental protein and one of the bone morphogenetic protein antagonists, Gremlin, has emerged as a novel modulator of diabetic nephropathy. The high expression and strong co-localization with transforming growth factor- β1 in diabetic kidneys suggests a role for Gremlin in the pathogenesis of diabetic nephropathy. We have constructed a gremlin siRNA plasmid and have examined the effect of Gremlin inhibition on the progression of diabetic nephropathy in a mouse model. CD-1 mice underwent uninephrectomy and STZ treatment prior to receiving weekly injections of the plasmid. Inhibition of Gremlin alleviated proteinuria and renal collagen IV accumulation 12 weeks after the STZ injection and inhibited renal cell proliferation and apoptosis. In vitro experiments, using mouse mesangial cells, revealed that the transfect ion of gremlin siRNA plasmid reversed high glucose induced abnormalities, such as increased cell proliferation and apoptosis and increased collagen IV production. The decreased matrix metalloprotease level was partially normalized by transfection with gremlin siRNA plasmid. Additionally, we observed recovery of bone morphogenetic protein-7 signaling activity, evidenced by increases in phosphorylated Smad 5 protein levels. We conclude that inhibition of Gremlin exerts beneficial effects on the diabetic kidney mainly through maintenance of BMP-7 activity and that Gremlin may serve as a novel therapeutic target in the management of diabetic nephropathy

The effects of CO2, climate and land-use on terrestrial carbon balance, 1920-1992: An analysis with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system