Most members of the oomycete genus Phytophthora are primary plant pathogens. Both soil- and airborne Phytophthora species are able to survive adverse environmental conditions with enduring resting ...structures, mainly sexual oospores, vegetative chlamydospores and hyphal
aggregations. Soilborne Phytophthora species infect fine roots and the bark of suberized roots and the collar region with motile biflagellate zoospores released from sporangia during wet soil conditions. Airborne Phytophthora species infect leaves, shoots, fruits and bark of
branches and stems with caducous sporangia produced during humid conditions on infected plant tissues and dispersed by rain and wind splash. During the past six decades, the number of previously unknown Phytophthora declines and diebacks of natural and semi-natural forests and woodlands
has increased exponentially, and the vast majority of them are driven by introduced invasive Phytophthora species. Nurseries in Europe, North America and Australia show high infestation rates with a wide range of mostly exotic Phytophthora species. Planting of infested nursery
stock has proven to be the main pathway of Phytophthora species between and within continents. This review provides insights into the history, distribution, aetiology, symptomatology, dynamics and impact of the most important canker, decline and dieback diseases caused by soil- and
airborne Phytophthora species in forests and natural ecosystems of Europe, Australia and the Americas.
The hypothesis of cancer stem cells has been proposed to explain the therapeutic failure in a variety of cancers including lung cancers. Previously, we demonstrated acquisition of ...epithelial-mesenchymal transition, a feature highly reminiscent of cancer stem-like cells, in gefitinib-resistant A549 cells (A549/GR). Here, we show that A549/GR cells contain a high proportion of CXCR4+ cells that are responsible for having high potential of self-renewal activity in vitro and tumorigenicity in vivo. A549/GR cells exhibited strong sphere-forming activity and high CXCR4 expression and SDF-1α secretion compared with parent cells. Pharmacological inhibition (AMD3100) and/or siRNA transfection targeting CXCR4 significantly suppressed sphere-forming activity in A549 and A549/GR cells, and in various non-small cell lung cancer (NSCLC) cell lines. A549/GR cells showed enhanced Akt, mTOR and STAT3 (Y705) phosphorylation. Pharmacological inhibition of phosphatidyl inositol 3-kinase or transfection with wild-type PTEN suppressed phosphorylation of Akt, mTOR and STAT3 (Y705), sphere formation, and CXCR4 expression in A549/GR cells, whereas mutant PTEN enhanced these events. Inhibition of STAT3 by WP1066 or siSTAT3 significantly suppressed the sphere formation, but not CXCR4 expression, indicating that STAT3 is a downstream effector of CXCR4-mediated signaling. FACS-sorted CXCR4+ A549/GR cells formed many large spheres, had self-renewal capacity, demonstrated radiation resistance in vitro and exhibited stronger tumorigenic potential in vivo than CXCR4- cells. Lentiviral-transduction of CXCR4 enhanced sphere formation and tumorigenicity in H460 and A549 cells, whereas introduction of siCXCR4 suppressed these activities in A549/GR cells. Our data indicate that CXCR4+ NSCLC cells are strong candidates for tumorigenic stem-like cancer cells that maintain stemness through a CXCR4-medated STAT3 pathway and provide a potential therapeutic target for eliminating these malignant cells in NSCLC.
Aims
In the preliminary study, kimchi, a traditional food fermented with Chinese cabbage, protected scopolamine‐induced mouse memory deficit in passive avoidance test. Therefore, we screened ...protective ingredients, particularly lactic acid bacteria, from Chinese cabbage kimchi against scopolamine‐induced memory deficit in mice.
Methods and Results
Lactic acid bacteria, isolated from Chinese cabbage kimchi, were identified by 16S rDNA sequence analysis, G+C content and cellular fatty acid composition and sugar fermentation test. Memory deficit was induced in mice by intraperitoneally injecting with scopolamine.
Kimchi, particularly its supernatant, protected scopolamine‐induced memory deficit in mice in passive avoidance test. Of kimchi ingredients, a lactic acid bacterium, strain C29, potently protected scopolamine‐induced memory deficit in mice. C29 was a gram‐positive, catalase‐negative, anaerobic and non‐motile rod. Its pylogenetic property was near to Lactobacillus pentosus (99%) and Lact. plantarum (99%). However, C29 fermented inulin and L‐rhamnose and grew in pH 3 and at 45°C in contrast with Lact. pentosus and Lact. plantarum. Therefore, it named to be Lact pentosus var. plantarum C29. The strain C29 protected scopolamine‐induced memory deficit in Y‐maze and Morris water maze tests. Furthermore, C29 increased hippocampal BDNF and p‐CREB expressions, which were reduced by scopolamine.
Conclusion
Lactobacillus pentosus var. plantarum C29 may protect memory deficit by inducing BDNF and p‐CREB expressions.
Significance and Impact of the Study
Lactic acid bacteria, such as Lact pentosus var. plantarum C29, may prevent memory deficit and its contained fermented foods may be beneficial for dementia.
Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream ...to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.
Objectives
Hepatocellular carcinoma (HCC) can be diagnosed non-invasively with contrast-enhanced ultrasound (CEUS) in cirrhosis if the characteristic pattern of arterial phase hyperenhancement ...followed by hypoenhancement is present. Recent studies suggest that diagnosis based on this “hyper-hypo” pattern needs further refinement. This study compares the diagnostic accuracies of standardized CEUS for HCC according to the current guideline definition and following the newly developed CEUS algorithms (CEUS LI-RADS®, ESCULAP) in a prospective multicenter real-life setting.
Methods
Cirrhotic patients with liver lesions on B-mode ultrasound were recruited prospectively from 04/2018 to 04/2019, and clinical and imaging data were collected. The CEUS standard included an additional examination point after 4–6 min in case of no washout after 3 min. The diagnostic accuracies of CEUS following the guidelines (“hyper-hypo” pattern), based on the examiner’s subjective interpretation (“CEUS subjective”), and based on the CEUS algorithms ESCULAP and CEUS LI-RADS® were compared.
Results
In total, 470 cirrhotic patients were recruited in 43 centers. The final diagnosis was HCC in 378 cases (80.4%) according to the reference standard (histology 77.4%, MRI 16.4%, CT 6.2%). The “hyper-hypo” pattern yielded 74.3% sensitivity and 63% specificity. “CEUS subjective” showed a higher diagnostic accuracy (sensitivity, 91.5%; specificity, 67.4%; positive predictive value, 92%; negative predictive value, 66%). Sensitivity was higher for ESCULAP (95%) and “CEUS subjective” (91.5%) versus CEUS LI-RADS® (65.2%;
p
< 0.001). Specificity was highest for CEUS LI-RADS® (78.6%;
p
< 0.001).
Conclusions
CEUS has an excellent diagnostic accuracy for the non-invasive diagnosis of HCC in cirrhosis. CEUS algorithms may be a helpful refinement of the “hyper-hypo” pattern defined by current HCC guidelines.
Key Points
• Contrast-enhanced ultrasound (CEUS) has a high diagnostic accuracy for the non-invasive diagnosis of hepatocellular carcinoma (HCC) in cirrhosis.
• The CEUS algorithm ESCULAP (Erlanger Synopsis for Contrast-enhanced Ultrasound for Liver lesion Assessment in Patients at risk) showed the highest sensitivity, whereas the CEUS LI-RADS® (Contrast-Enhanced UltraSound Liver Imaging Reporting and Data System) algorithm yielded the highest specificity.
• A standardized CEUS examination procedure with an additional examination point in the late phase, after 4–6 min in lesions with no washout after 3 min, is vital.
A
bstract
We study the phenomenology of electric dipole moments (EDMs) induced in various scalar leptoquark models. We consider generic leptoquark couplings to quarks and leptons and match to ...Standard Model effective field theory. After evolving the resulting operators to low energies, we connect to EDM experiments by using up-to-date hadronic, nuclear, and atomic matrix elements. We show that current experimental limits set strong constraints on the possible CP-violating phases in leptoquark models. Depending on the quarks and leptons involved in the interaction, the existing searches for EDMs of leptons, nucleons, atoms, and molecules all play a role in constraining the CP-violating couplings. We discuss the impact of hadronic and nuclear uncertainties as well as the sensitivities that can be achieved with future EDM experiments. Finally, we study the impact of EDM constraints on a specific leptoquark model that can explain the recent
B
-physics anomalies.
Participatory budgeting (PB) is a novel way to understand the ways in which local projects are funded. Citizens engage in direct participation at every level of the project from designing, ...evaluating, modifying, and eventually disbursing funds. In short, PB is a fair and practical way for citizens to participate in direct democracy, rather than passive engagement through voting and waiting for elected officials to render a decision. In addition, due to its commitment to community-based philosophy, PB represents a radical move toward social justice.
Quantifying gross primary production (GPP) remains a major challenge in global carbon cycle research. Spaceborne monitoring of solar-induced chlorophyll fluorescence (SIF), an integrative ...photosynthetic signal of molecular origin, can assist in terrestrial GPP monitoring. However, the extent to which SIF tracks spatiotemporal variations in GPP remains unresolved. Orbiting Carbon Observatory-2 (OCO-2)'s SIF data acquisition and fine spatial resolution permit direct validation against ground and airborne observations. Empirical orthogonal function analysis shows consistent spatiotemporal correspondence between OCO-2 SIF and GPP globally. A linear SIF-GPP relationship is also obtained at eddy-flux sites covering diverse biomes, setting the stage for future investigations of the robustness of such a relationship across more biomes. Our findings support the central importance of high-quality satellite SIF for studying terrestrial carbon cycle dynamics.
The authors assess the ability of 18 Earth system models to simulate the land and ocean carbon cycle for the present climate. These models will be used in the next Intergovernmental Panel on Climate ...Change (IPCC) Fifth Assessment Report (AR5) for climate projections, and such evaluation allows identification of the strengths and weaknesses of individual coupled carbon–climate models as well as identification of systematic biases of the models. Results show that models correctly reproduce the main climatic variables controlling the spatial and temporal characteristics of the carbon cycle. The seasonal evolution of the variables under examination is well captured. However, weaknesses appear when reproducing specific fields: in particular, considering the land carbon cycle, a general overestimation of photosynthesis and leaf area index is found for most of the models, while the ocean evaluation shows that quite a few models underestimate the primary production. The authors also propose climate and carbon cycle performance metrics in order to assess whether there is a set of consistently better models for reproducing the carbon cycle. Averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles and PDFs from different observed datasets. Although the metrics used in this study allow identification of somemodels as better or worse than the average, the ranking of this study is partially subjective because of the choice of the variables under examination and also can be sensitive to the choice of reference data. In addition, it was found that the model performances show significant regional variations.
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