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Understanding the pathways of floating material (e.g. larvae, plastics, oil) at the surface ocean is important to improve our knowledge on the surface circulation and for its ecological and environmental impacts. For example, knowing where floating plastic and oil spills accumulate in the surface ocean can help ocean clean-up strategies. One of the main methods of research is virtual particle simulations, which simulate the dispersion of floating material in the Ocean. Previous studies have tried to understand the surface dispersion and accumulation via these numerical simulations. To define the circulation, the velocity outputs of ocean general circulation models are needed. Oceanic models have improved in the past years, but many still do not fully represent the ocean dynamics at the fine-scales (below 100 km). The spatial resolution of ocean models and whether they include a tidal-forcing are two important model parameterizations that can determine how well the ocean dynamics are represented at the fine-scales. In this study we try to answer: How do these model characteristics affect the dispersion and accumulation of virtual particles at the ocean surface? To answer this, we use the ocean surface velocity outputs of different NEMO simulations to simulate the trajectories of virtual particles, and we evaluate the impact of different NEMO simulations’ spatial resolution and the presence or not of a tidal-forcing. As tidal-forcing has a big impact on the ocean model’s representation of internal tides and waves, we focus on a region where there is a high internal-tide signal: the Azores Islands. We evaluate these impacts by looking at whether there is a difference in particles’ accumulation and dispersion in the different model scenarios.

We introduce a modelling concept for the construction of 3-D data-constrained subsurface structural density models at different spatial scales: from large-scale models (thousands of square km) to regional (hundreds of square km) and small-scale (tens of square km) models used in applied geophysics. These models are important for understanding the drivers of geohazards, for efficient and sustainable extraction of resources from sedimentary basins such as groundwater, hydrocarbons or deep geothermal energy, as well as for investigation of capabilities of long-term underground storage of gas and radioactive materials.The modelling concept involves interactive fitting of potential fields (gravity and magnetics) and their derivatives within IGMAS+ (Interactive Gravity and Magnetic Application System), a well-known software tool with almost 40 years of development behind it. The core of IGMAS+ is the analytical solution of the volume integral for gravity and magnetic effects of homogeneous bodies, bounded by polyhedrons of triangulated model interfaces. The backbone model is constrained by interdisciplinary data, e.g. geological maps, seismic reflection and refraction profiles, structural signatures obtained from seismic receiver functions, local surveys etc. The software supports spherical geometries to resolve the first-order effects related to the curvature of the Earth, which is especially important for large-scale models.Currently being developed and maintained at the Helmholtz Centre Potsdam – GFZ German Research Centre, IGMAS+ has a cross-platform implementation with parallelization of computations and optimized storage. The powerful graphical interface makes the interactive modelling and geometry modification process user-friendly and robust. Historically IGMAS+ is free for research and education purposes and has a long-term plan to remain so.IGMAS+ has been used in various tectonic settings and we demonstrate its flexibility and usability on several lithospheric-scale case studies in South America and Europe.Both science and industry are close to the goal of treating all available geoscientific data and geophysical methods inside a single subsurface model that aims to integrate most of the interdisciplinary measurement-based constraints and essential structural trends coming from geology. This approach presents challenges for both its implementation within the modelling software and the usability and plausibility of generated results, requiring a modelling concept that integrates the data methods in a feasible way together with recent advances in data science methods. As such, we present the future outlook of our modelling concept in regards to these challenges.

We present a method to mitigate the atmospheric effects (residual atmospheric lines) in single-dish radio spectroscopy caused by the elevation difference between the target and reference positions. The method is developed as a script using the Atmospheric Transmission at Microwaves (ATM) library built into the Common Astronomy Software Applications (CASA) package. We apply the method to the data taken with the Total Power Array of the Atacama Large Millimeter/submillimeter Array. The intensities of the residual atmospheric (mostly O3) lines are suppressed by, typically, an order of magnitude for the tested cases. The parameters for the ATM model can be optimized to minimize the residual line and, for a specific O3 line at 231.28 GHz, a seasonal dependence of a best-fitting model parameter is demonstrated. The method will be provided as a task within the CASA package in the near future. The atmospheric removal method we developed can be used by any radio/millimeter/submillimeter observatory to improve the quality of its spectroscopic measurements., 21 pages, 12 figures, accepted for publication in PASP

After eight observing Cycles, the Atacama Large Millimeter-submillimeter Array (ALMA) is capable of observing in eight different bands (covering a frequency range from 84 to 950 GHz), with 66 antennas and two correlators. For the current Cycle (7), ALMA offers up to 4300 hours for the 12-m array, and 3000 hours on both the 7-m of the Atacama Compact Array (ACA) and TP Array plus 750 hours in a supplemental call. From the customer perspective (i.e., the astronomical community), ALMA is an integrated product service provider, i.e. it observes in service mode, processes and delivers the data obtained. The Data Management Group (DMG) is in charge of the processing, reviewing, and delivery of the ALMA data and consists of approximately 60 experts in data reduction, from the ALMA Regional Centers (ARCs) and the Joint ALMA Observatory (JAO), distributed in fourteen countries. Prior to their delivery, the ALMA data products go through a thorough quality assurance (QA) process, so that the astronomers can work on their science without the need of significant additional calibration re-processing. Currently, around 90% of the acquired data is processed with the ALMA pipeline (the so called pipeline-able data), while the remaining 10% is processed completely manually. The Level-1 Key Performance Indicator set by the Observatory to DMG is that 90% of the pipeline-able data sets (i.e. some 80% of the data sets observed during an observing cycle) must be processed, reviewed and delivered within 30 days of data acquisition. This paper describes the methodology followed by the JAO in order to process near 80% of the total data observed during Cycle 7, a giant leap with respect to approximately 30% in Cycle 4 (October 2016 - September 2017)., 18 pages, 11 figures, SPIE conference on Astronomical Telescopes and Instrumentation

Glycoproteins are highly complex molecules. Knowledge of their heterogeneities in glycosylation and in other posttranslational modifications provides relevant information and requires high-resolution separation techniques. This chapter focuses on the capillary electrophoresis (CE) analysis of intact glycoproteins and glycopeptides and their fragments. It covers works published since 2015. The aim is to give a general vision of different strategies, approaches, and CE methods used to analyze these biomolecules. Their advantages and limitations are considered. Due to the high interest on monoclonal antibodies, a separated section is devoted to these immunoglobulins. Different detection systems are considered, and a separate section is dedicated to the coupling of CE with mass spectrometry in consideration to the additional information provided and to the large number of papers devoted to this coupling. As a final section, examples of applications of CE analysis of glycoproteins in the areas of biomarkers and therapeutic drugs are included.

Background Social distancing is a crucial intervention to slow down person-to-person transmission of COVID-19. However, social distancing has negative consequences, including increases in depression and anxiety. Digital interventions, such as text messaging, can provide accessible support on a population-wide scale. We developed text messages in English and Spanish to help individuals manage their depressive mood and anxiety during the COVID-19 pandemic. Objective In a two-arm randomized controlled trial, we aim to examine the effect of our 60-day text messaging intervention. Additionally, we aim to assess whether the use of machine learning to adapt the messaging frequency and content improves the effectiveness of the intervention. Finally, we will examine the differences in daily mood ratings between the message categories and time windows. Methods The messages were designed within two different categories: behavioral activation and coping skills. Participants will be randomized into (1) a random messaging arm, where message category and timing will be chosen with equal probabilities, and (2) a reinforcement learning arm, with a learned decision mechanism for choosing the messages. Participants in both arms will receive one message per day within three different time windows and will be asked to provide their mood rating 3 hours later. We will compare self-reported daily mood ratings; self-reported depression, using the 8-item Patient Health Questionnaire; and self-reported anxiety, using the 7-item Generalized Anxiety Disorder scale at baseline and at intervention completion. Results The Committee for the Protection of Human Subjects at the University of California Berkeley approved this study in April 2020 (No. 2020-04-13162). Data collection began in April 2020 and will run to April 2021. As of August 24, 2020, we have enrolled 229 participants. We plan to submit manuscripts describing the main results of the trial and results from the microrandomized trial for publication in peer-reviewed journals and for presentations at national and international scientific meetings. Conclusions Results will contribute to our knowledge of effective psychological tools to alleviate the negative effects of social distancing and the benefit of using machine learning to personalize digital mental health interventions. Trial Registration ClinicalTrials.gov NCT04473599; https://clinicaltrials.gov/ct2/show/NCT04473599 International Registered Report Identifier (IRRID) DERR1-10.2196/23592

This collection of essays brings together scholars from various disciplinary backgrounds, based on three continents, with different theoretical and methodological interests but all active on the topic of complex systems as applied to international relations. They investigate how complex systems have been and can be applied in practice and what differences it makes for the study of international affairs. Two important threads link all the contributions: (i) To which extent is this approach promising to understand global governance dynamics? (ii) How can this be implemented in practice?

The Upper Rhine Graben (URG), as a part of the wider European Cenozoic Rift System, is a tectonically active area that has been extensively investigated for its geothermal energy potential. In this study, we carry out a first investigation of the present-day thermo-mechanical stability of the area as based on a detailed 3D geological and thermal model. The overall goal is, therefore, to assess how the lithospheric strength varies within the URG in response to the natural tectonic setting as well as the internal thermal configuration, and how those variations can be related to the recorded seismicity. The results from the modeling indicate that there is a spatial correlation between the predictions for the graben-wide rheological configuration with both the deep thermal field and the configuration of the crystalline crust. We find that the regional characteristics of the long-term strength of the lithosphere match the spatial distribution of seismicity, indicating that the mechanical stability of the area is primarily controlled by resolved strength variations. By cross-plotting the modeled strength distribution with available seismicity catalogs, our results suggest that seismicity in the graben area is shallower and of lower intensity due to a hotter and weaker crust compared to its surrounding areas. In contrast, seismic energy release appears to occur at deeper levels and being of larger magnitudes east of the graben and in the adjacent Lower Rhine Graben to the north. These results demonstrate the relevance of a proper quantification of the lithospheric rheological configuration and its spatial variability in response to its tectonic inheritance as an asset to interpret the pattern and distribution of seismicity observed in the area.

Nitrogen oxides (NOx ≡ NO + NO2) in the NOx-limited upper troposphere (UT) are long-lived and so have a large influence on the oxidizing capacity of the troposphere and formation of the greenhouse gas ozone. Models misrepresent NOx in the UT and observations to address deficiencies in models are sparse. Here we obtain a year of near-global seasonal mean mixing ratios of NO2 in the UT (450–180 hPa) at 1 ° x 1° by applying cloud-slicing to partial columns of NO2 from TROPOMI. This follows refinement of the cloud-slicing algorithm with synthetic partial columns from the GEOS-Chem chemical transport model. We find that synthetic cloud-sliced UT NO2 are spatially consistent (R = 0.64) with UT NO2 calculated across the same cloud pressure range and scenes as are cloud-sliced (“true” UT NO2), but the cloud-sliced UT NO2 is 11–22 % more than the "true" all-sky seasonal mean. The largest contributors to differences between synthetic cloud-sliced and “true” UT NO2 are target resolution of the cloud-sliced product and uniformity of overlying stratospheric NO2. TROPOMI, prior to cloud-slicing, is corrected for a 13 % underestimate in stratospheric NO2 variance and a 50 % overestimate in free tropospheric NO2 determined by comparison to Pandora total columns at high-altitude sites in Mauna Loa, Izaña and Altzomoni, and MAX-DOAS and Pandora tropospheric columns at Izaña. Two cloud-sliced seasonal mean UT NO2 products for June 2019 to May 2020 are retrieved from corrected TROPOMI total columns using distinct TROPOMI cloud products that assume clouds are reflective boundaries (FRESCO-S) or water droplet layers (ROCINN-CAL). TROPOMI UT NO2 typically ranges from 20-30 pptv over remote oceans to > 80 pptv over locations with intense seasonal lightning. Spatial coverage is mostly in the tropics and subtropics with FRESCO-S and extends to the midlatitudes and polar regions with ROCINN-CAL, due to its greater abundance of optically thick clouds and wider cloud top altitude range. TROPOMI UT NO2 seasonal means are spatially consistent (R = 0.6–0.8) with an existing coarser spatial resolution (5° latitude x 8° longitude) UT NO2 product from the Ozone Monitoring Instrument (OMI). UT NO2 from TROPOMI is 12–26 pptv more than that from OMI due to increase in NO2 with altitude from the OMI pressure ceiling (280 hPa) to that for TROPOMI (180 hPa), but possibly also systematic altitude differences between the TROPOMI and OMI cloud products. The TROPOMI UT NO2 product offers potential to evaluate and improve representation of UT NOx in models and supplement aircraft observations that are sporadic and susceptible to large biases in the UT.

International audience; Intracellular bacterial pathogens harbour genes, the closest homologues of which are found in eukaryotes. Regulator of chromosome condensation 1 (RCC1) repeat proteins are phylogenetically widespread and implicated in protein-protein interactions, such as the activation of the small GTPase Ran by its cognate guanine nucleotide exchange factor, RCC1. Legionella pneumophila and Coxiella burnetii, the causative agents of Legionnaires' disease and Q fever, respectively, harbour RCC1 repeat coding genes. Legionella pneumophila secretes the RCC1 repeat 'effector' proteins LegG1, PpgA and PieG into eukaryotic host cells, where they promote the activation of the pleiotropic small GTPase Ran, microtubule stabilisation, pathogen vacuole motility and intracellular bacterial growth as well as host cell migration. The RCC1 repeat effectors localise to the pathogen vacuole or the host plasma membrane and target distinct components of the Ran GTPase cycle, including Ran modulators and the small GTPase itself. Coxiella burnetii translocates the RCC1 repeat effector NopA into host cells, where the protein localises to nucleoli. NopA binds to Ran GTPase and promotes the nuclear accumulation of Ran(GTP), thus pertubing the import of the transcription factor NF-κB and innate immune signalling. Hence, divergent evolution of bacterial RCC1 repeat effectors defines the range of Ran GTPase cycle targets and likely allows fine-tuning of Ran GTPase activation by the pathogens at different cellular sites.

Groundwater is a strategic and vital resource for agriculture and oil production in the arid region of Carrizal sub-basin (CSB) in Argentina. Increasing groundwater salinity in some areas has created legal conflicts between water users over the source of the salinity. A multidisciplinary approach using hydrogeological, chemical and isotope tools were used to evaluate the source of groundwater salinity in CSB. The Mendoza River is the main source of recharge to the CSB aquifer. Groundwater and surface water from the recharge area near the Mendoza River to the discharge area of the CSB were analyzed for the study. The groundwater salinity varies between ~1000 μS/cm in the north (recharge area) to ~4000 μS/cm in the central region. There is a clear correlation between high level of nitrate and the high salinity spots in the aquifer. These data and the stable isotopes data suggests the source of groundwater salinity is associated with irrigation return flows from the agriculture areas. This is fully supported by the carbon isotopes data that showed clearly the input of carbon from the irrigated agriculture areas in the aquifer. No evidence was found about the role of the oil industry in the salinization of groundwater in the study area. However, a groundwater of different origin than the recharge from the Mendoza River was found down-gradient of the oil field which needs further investigation. The results of this study have implications for improving water management in agriculture areas in arid environments where water resources are under significant pressure due to more demand by an increase in population and agriculture activities under a scenario of a cycle of droughts and climate change.

All supporting data, code and protocols have been provided within the article or through supplementary data files.; International audience; Metagenomics and marker gene approaches, coupled with high-throughput sequencing technologies, have revolutionized the field of microbial ecology. Metagenomics is a culture-independent method that allows the identification and characterization of organisms from all kinds of samples. Whole-genome shotgun sequencing analyses the total DNA of a chosen sample to determine the presence of micro-organisms from all domains of life and their genomic content. Importantly, the whole-genome shotgun sequencing approach reveals the genomic diversity present, but can also give insights into the functional potential of the micro-organisms identified. The marker gene approach is based on the sequencing of a specific gene region. It allows one to describe the microbial composition based on the taxonomic groups present in the sample. It is frequently used to analyse the biodiversity of microbial ecosystems. Despite its importance, the analysis of metagenomic sequencing and marker gene data is quite a challenge. Here we review the primary workflows and software used for both approaches and discuss the current challenges in the field.

IntroductionDepression and diabetes are highly disabling diseases with a high prevalence and high rate of comorbidity, particularly in low-income ethnic minority patients. Though comorbidity increases the risk of adverse outcomes and mortality, most clinical interventions target these diseases separately. Increasing physical activity might be effective to simultaneously lower depressive symptoms and improve glycemic control. Self-management apps are a cost-effective, scalable and easy access treatment to increase physical activity. However, cutting-edge technological applications often do not reach vulnerable populations and are not tailored to an individual’s behavior and characteristics. Tailoring of interventions using machine learning methods likely increases the effectiveness of the intervention.Methods and analysisIn a three-arm randomized controlled trial we will examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. The adaptive intervention group receives messages chosen from different messaging banks by a reinforcement learning algorithm. The uniform random intervention group receives the same messages, but chosen from the messaging banks with equal probabilities. The control group receives a weekly mood message. We aim to recruit 276 adults from primary care clinics aged 18 to 75 years who have been diagnosed with current diabetes and show elevated depressive symptoms (PHQ-8 >5). We will compare passively collected daily step counts, self-report PHQ-8 and most recent HbA1c from medical records at baseline and at intervention completion at 6-month follow-up.Ethics and disseminationThe Institutional Review Board at the University of California San Francisco approved this study (IRB: 17-22608). We plan to submit manuscripts describing our User Designed Methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at (inter)-national scientific meetings.Registrationclinicaltrials.gov: NCT03490253; pre-resultsArticle SummaryStrengths and LimitationsNovel approach of targeting diabetes and depressive symptoms using a smartphone applicationAbility to compare adaptive messaging for increasing physical activity to messages delivered with equal probabilitiesTesting of a smartphone application integrated within primary care settings in a low-income vulnerable patient populationLongitudinal design with 6-month follow-up enables assessing intervention effects over timeChallenges of this trial include supporting users in key behavior change in an automated manner with minimal in-person support

Legionella pneumophila is a ubiquitous environmental bacterium which, upon inhalation, causes a life-threatening pneumonia termed Legionnaires’ disease. The opportunistic pathogen grows in amoebae and macrophages by employing a “type IV” secretion system, which secretes more than 300 different “effector” proteins into the host cell, where they subvert pivotal processes. The function of many of these effector proteins is unknown, and their evolution has not been studied. L. pneumophila RCC1 repeat effectors target the small GTPase Ran, a molecular switch implicated in different cellular processes such as nucleocytoplasmic transport and microtubule cytoskeleton dynamics. We provide evidence that one or more RCC1 repeat genes are distributed in two main clusters of L. pneumophila strains and have divergently evolved to target different components of the Ran GTPase activation cycle at different subcellular sites. Thus, L. pneumophila employs a sophisticated strategy to subvert host cell Ran GTPase during infection., Legionella pneumophila governs its interactions with host cells by secreting >300 different “effector” proteins. Some of these effectors contain eukaryotic domains such as the RCC1 (regulator of chromosome condensation 1) repeats promoting the activation of the small GTPase Ran. In this report, we reveal a conserved pattern of L. pneumophila RCC1 repeat genes, which are distributed in two main clusters of strains. Accordingly, strain Philadelphia-1 contains two RCC1 genes implicated in bacterial virulence, legG1 (Legionella eukaryotic gene 1), and ppgA, while strain Paris contains only one, pieG. The RCC1 repeat effectors localize to different cellular compartments and bind distinct components of the Ran GTPase cycle, including Ran modulators and the small GTPase itself, and yet they all promote the activation of Ran. The pieG gene spans the corresponding open reading frames of legG1 and a separate adjacent upstream gene, lpg1975. legG1 and lpg1975 are fused upon addition of a single nucleotide to encode a protein that adopts the binding specificity of PieG. Thus, a point mutation in pieG splits the gene, altering the effector target. These results indicate that divergent evolution of RCC1 repeat effectors defines the Ran GTPase cycle targets and that modulation of different components of the cycle might fine-tune Ran activation during Legionella infection.

The NE Atlantic is a tectonically complex region, also interesting in terms of georesources and therefore large areas are well covered by geophysical and geological data. In this work, we present a 3D lithospheric-scale structural and density model of the region including the eastern-most area of Greenland, the western coast of Norway, Iceland and Svalbard. It covers an area of 2000 km in longitude by 2500 km in latitude with a depth of 300 km and a resolution of 10 km. The model was developed by integrating different kinds of data and regional or global previous models, mainly of seismic origin, and constrained by gravity observations.The developed model includes the topography, bathymetry and ice thickness obtained from global compilations models. The thickness distribution of sediments was incorporated based on detailed mapping of most areas covered by the model. The structure of the crystalline crust, differentiating between the oceanic and continental areas, is based on seismic information and previous regional models, cross-checked by additional seismic profiles available in the region. The model also includes high velocity/density lower crustal bodies defined by a previous compilation at the Norwegian and Greenland margins and by the analysis of deep seismic profiles in the case of the Iceland area.We assigned constant densities to each layer following seismic velocities and literature-suggested values for every lithology. Due to the active tectonic setting of the area and its consequent elevated temperature and thus low density, the portion of mantle included in the model is the only layer with variable density. To obtain the mentioned density variation, we evaluated different seismic tomographic data for the area and converted them into temperatures. To mitigate the poor reliability of the tomographic models at shallow depths and also taking into account that the effect of the temperature in the uppermost mantle is especially important near mid oceanic ridges, we evaluated the thermal effect of this area by running a thermal model. Therefore, we calculated 3D distribution of temperatures for the whole portion of the mantle included in the model to obtain the reduction in density that these temperatures would cause considering the thermal expansivity of mantle rocks. The gravity response of the model was calculated and compared to the gravity observations using the 3D interactive software IGMAS+. The developed model includes the latest data and information of the area and, at the same time, reasonably fits the measured gravity anomalies. Comparison of the first-pass 3D gravity model to the observed gravity data detected some residual anomalies that require further differentiation of crustal densities. The new 3D lithosphere-scale model allows us to analyze the structural configuration of the area and interpret its tectonic implications. It also forms the base for thermal and mechanical models to obtain the 3D distribution of physical variables and predict the rheological and dynamic behavior of the wider NE Atlantic region.

The configuration of the lithosphere below sedimentary basins varies in response to the basin-forming mechanism, the lifetime of the causative stress fields and the lithological heterogeneity inherited from pre-basin tectonic events. Accordingly, the deep thermal configuration is a function of the tectonic setting, the time since the thermal disturbance occurred and the internal heat sources within the lithosphere. We compare deep thermal configurations in different settings based on data-constrained 3D lithosphere-scale thermal models that consider both geological and geophysical observations and physical processes of heat transfer. The results presented come from a varied range of tectonic settings including: (1) the extensional settings of the Upper Rhine Graben and the East African Rift System, where we show that rifts can be hot for different reasons; (2) the North and South Atlantic passive margins, demonstrating that magma-rich passive margins can be comparatively hot or cold depending on the thermo-tectonic age; (3) the Alps, where we find that foreland basins are influenced by the conductive properties and heat-producing units of the adjacent orogen; and (4)the Sea of Marmara, along the westernmost sector of the North Anatolian Fault Zone, that suggest strike-slip basins may be thermally segmented.

We introduce a new approach for 3D joint inversion of potential fields and its derivatives under the condition of constraining data and information. The interactive 3D gravity and magnetic application IGMAS (Interactive Gravity and Magnetic Application System) has been around for more than 30 years, initially developed on a mainframe and then transferred to the first DOS PCs, before it was adapted to Linux in the ’90s and finally implemented as a cross-platform Java application with GUI called IGMAS+. The software has proven to be very fast, accurate and easy to use once a model has been established. Since 2019 IGMAS+ has been maintained and developed in the Helmholtz Centre Potsdam – GFZ German Research Centre by the staff of Section 4.5 – Basin Modelling and ID2 – eScience Centre.The analytical solution of the volume integral for the gravity and magnetic effect of a homogeneous body is based on the reduction of the three-folded integral to an integral over the bounding polyhedrons (in IGMAS polyhedrons are built by triangles). Later the algorithm has been extended to cover all elements of the gravity tensor as well. Optimized storage enables very fast inversion of densities and changes to the model geometry and this flexibility makes geometry changes easy. The geometry is updated and the gravity is recalculated immediately after each change. Because of the triangular model structure, IGMAS can handle complex structures (multi Z surfaces) like the overhangs of salt domes very well. Geophysical investigations may cover huge areas of several thousand square kilometers but also models of Applied Geophysics at a meter scale. Due to the curvature of the Earth, the use of spherical geometries and calculations is necessary.The model technique is user-friendly because it is highly interactive, operates ideally in real-time whilst conserving topology and can be used for both flat (regional) and spherical models (global) in 3D. Modeling is constrained by seismic and structural input from independent data sources and is essential toward true integration of 3D thermal modeling or even Full Waveform Inversion. We are close to the demand for treating all geophysical methods in a single model of the subsurface and aim of fulfilling most of the constraints: measurements and geological plausibility.We demonstrate the flexibility of the software by modeling: (1) the southern segment of the Central Andes which is designed to assess the relationship between the characteristics of the overriding plate and the deformation and dynamics of the subduction system; (2) the South Caribbean margin which defines the two flat-slab subductions of the Nazca Plate and the Caribbean Plate, with variable mantle density distribution implemented by voxels; (3) the North Patagonian Massif Plateau in Argentina which provides insight into the main height differences between the plateau and the surroundings; and (4) an Alpine model which interrogates the strength of the lithosphere at different locations through the Alps and their forelands.

The Andean orogeny is a ~7000 km long N-S trending mountain range developed along the South American western margin. The formation of this mountain range is driven by the subduction of the oceanic Nazca plate beneath the continental South American plate, being the only known present-day case of subduction-type orogeny. In this tectonic setting, the intrinsic physical properties of the overriding plate govern the formation of zones of crustal strength and weakness and control the localization and the style of deformation. Furthermore, the dynamics of the subducting oceanic lithosphere is strongly conditioned by the properties of the continental counterpart. The southern segment of the Central Andes (29°S-39°S) is a suitable scenario to investigate the relationship between the two plates for several reasons. It is characterized by a complex deformation pattern with variations in horizontal shortening, crustal thickening and mean topographic elevation. In addition, the subduction angle changes at 33°S-35°S latitude from flat in the North to normal in the South. To gain insight into this geodynamic system, a detailed characterization of the lithosphere is needed. Therefore, we constructed a 3D model of the entire segment of the Southern Central Andes that is consistent with the available geological, seismic and gravity data in order to assess the geometry and density variation within the lithosphere. The derived configuration shows a spatial correlation between density domains and known tectonic features. It is also consistent with other independent observations such as S wave velocity variation and surface deformation. The generated structural model allows us to reach the first conclusions about the relationship between the characteristics of the overriding plate and the crustal deformation and dynamics of the subduction system. It is also useful to constrain thermomechanical experiments and therefore contributes to discussions about the crustal thermal and rheological fields within the region.

Incluye contenido parcial de los autores Abstract.Mammalian carnivores are considered a key group in maintaining ecologicalhealth and can indicate potential ecological integrity in landscapes where they occur. Carni-vores also hold high conservation value and their habitat requirements can guide managementand conservation plans. The order Carnivora has 84 species from 8 families in the Neotropicalregion: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; andUrsidae. Herein, we include published and unpublished data on native terrestrial Neotropicalcarnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTRO-PICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data wereobtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organi-zations, and private consultants. Data were collected using several methods including cameratrapping, museum collections, roadkill, line transect, and opportunistic records. Literature(peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated inthis compilation. Most of the data set consists of detection data entries (n=79,343; 79.7%) butalso includes non-detection data (n=20,262; 20.3%). Of those, 43.3% also include count data(n=43,151). The information available in NEOTROPICAL CARNIVORES will contribute tomacroecological, ecological, and conservation questions in multiple spatio-temporal perspec-tives. As carnivores play key roles in trophic interactions, a better understanding of their distri-bution and habitat requirements are essential to establish conservation management plans andsafeguard the future ecological health of Neotropical ecosystems. Our data paper, combinedwith other large-scale data sets, has great potential to clarify species distribution and relatedecological processes within the Neotropics. There are no copyright restrictions and no restric-tion for using data from this data paper, as long as the data paper is cited as the source of theinformation used. We also request that users inform us of how they intend to use the data.

This article belongs to the Special Issue Calibration and Validation of Satellite Altimetry., In the near future, the Surface Water Ocean Topography (SWOT) mission will provide images of altimetric data at kilometric resolution. This unprecedented 2-dimensional data structure will allow the estimation of geostrophy-related quantities that are essential for studying the ocean surface dynamics and for data assimilation uses. To estimate these quantities, i.e., to compute spatial derivatives of the Sea Surface Height (SSH) measurements, the uncorrelated, small-scale noise and errors expected to affect the SWOT data must be smoothed out while minimizing the loss of relevant, physical SSH information. This paper introduces a new technique for de-noising the future SWOT SSH images. The de-noising model is formulated as a regularized least-square problem with a Tikhonov regularization based on the first-, second-, and third-order derivatives of SSH. The method is implemented and compared to other, convolution-based filtering methods with boxcar and Gaussian kernels. This is performed using a large set of pseudo-SWOT data generated in the western Mediterranean Sea from a 1/60 ∘ simulation and the SWOT simulator. Based on root mean square error and spectral diagnostics, our de-noising method shows a better performance than the convolution-based methods. We find the optimal parametrization to be when only the second-order SSH derivative is penalized. This de-noising reduces the spatial scale resolved by SWOT by a factor of 2, and at 10 km wavelengths, the noise level is reduced by factors of 104 and 103 for summer and winter, respectively. This is encouraging for the processing of the future SWOT data., L.G.-N acknowledges Ph.D. funding from CNES. The contributions of L.G.-N, E.C., J.L.S. and N.P. are also funded by CNES (SWOT Science Team project) and ANR (BOOST-SWOT project, ANR-17-CE01-0009-01). A.P. is supported by the PRE-SWOT project (CTM2016-78607-P).

International audience; Legionella species are environmental gram-negative bacteria able to cause a severe form of pneumonia in humans known as Legionnaires' disease. Since the identification of Legionella pneumophila in 1977, four decades of research on Legionella biology and Legionnaires' disease have brought important insights into the biology of the bacteria and the molecular mechanisms that these intracellular pathogens use to cause disease in humans. Nowadays, Legionella species constitute a remarkable model of bacterial adaptation, with a genus genome shaped by their close coevolution with amoebae and an ability to exploit many hosts and signaling pathways through the secretion of a myriad of effector proteins, many of which have a eukaryotic origin. This review aims to discuss current knowledge of Legionella infection mechanisms and future research directions to be taken that might answer the many remaining open questions. This research will without a doubt be a terrific scientific journey worth taking.

ObjectiveThe prevalence of psoriatic arthritis (PsA) is very heterogeneous. There are no data on its frequency in the general population in Spain. The aim of EPISER2016 study was to estimate the prevalence of PsA in people aged ≥20 years in Spain.MethodsCross-sectional multicenter population-based study. Subjects from all the autonomous communities in Spain were randomly selected using multistage stratified cluster sampling. Participants in each of the municipalities randomly selected for the study were administered a telephone-based questionnaire to screen for the study diseases. If the participant reported being previously diagnosed, rheumatologists from the participant's reference hospital confirmed the diagnosis based on a review of the clinical history. Subjects not previously diagnosed but whose screening result was positive based on symptoms received a second telephone call from the investigating rheumatologist in order to evaluate the suspicion. If the suspicion remained, an appointment was made at the reference hospital to complete the diagnostic confirmation process according to CASPAR criteria. To calculate the prevalence and its 95% confidence interval (CI), the sample design was taken into account and weighing was calculated considering age, sex and geographic origin.ResultsThe sample comprised 4916 subjects. The prevalence of PsA was 0.58% (95%CI: 0.38-0.87). All but 1 of the 27 cases (96.30%) had been diagnosed prior to EPISER2016.ConclusionThe prevalence of PsA in Spain was among the highest reported to date, only below that reported in Norway (0.67%) and slightly higher than that reported in Italy (0.42%).

Background Similarities between the pathologic progression of cancer and the physiologic process of placentation have been recognized for many years proposing that both present similar mechanisms and processes. Cervical cancer (CC) is one of the most frequent neoplasia among Mexican women turning it into an important health problem. Objective The aim of this study was to determine the degree of the involvement of pregnancy related genes and in cancer progression by in-silico analysis and validated in CC samples. Results The data mining analysis resulted in the identification of genes expressed in term placenta, first trimester placenta and normal cervical tissues. Finally, we selected KISS1 for the involvement of pregnancy related gene and also in cancer process. In order to explore KISS1 in CC, we analyzed Copy Number Variation (CNV) and gene expression using microarray experiments. KISS1 showed 20% genomic gain in 1q32.1 on CC samples. Furthermore, microarray analysis showed KISS1 as up-regulated genes. Results were validated showing an overexpression of 85% of KISS1 in CC samples. Conclusions Data suggest KISS1 as a great candidate for CC molecular markers or as a therapeutic target for CC. Also, HPV presence does not seem to alter the KISS1 expression in CC.

PURPOSE To assess early retinal microvascular and functional changes in diabetic patients without clinical evidence of diabetic retinopathy with optical coherence tomography angiography and central visual analyzer. METHODS This was an observational case-control study of diabetic patients without diabetic retinopathy and nondiabetic controls. Patients underwent optical coherence tomography angiography imaging and visual acuity testing using the central visual analyzer. The foveal avascular zone area and the capillary density in the superficial and deep capillary plexuses were measured manually by a masked grader. RESULTS Sixty eyes from 35 diabetic patients were included in the study group, and 45 eyes from 31 nondiabetic patients were included in the control group. The foveal avascular zone area was not significantly different between the diabetic group and controls (both P > 0.05). The mean capillary density in the deep capillary plexus was significantly lower in diabetic eyes compared with control eyes (P = 0.04). The mean visual acuity in all central visual analyzer modules was significantly decreased in diabetic patients compared with controls (all P < 0.05). CONCLUSION Optical coherence tomography angiography was able to detect retinal microvascular changes in the deep capillary plexus, and the central visual analyzer showed signs of decreased visual acuity under conditions simulating suboptimal contrast and glare in diabetic patients without diabetic retinopathy.

Cervical cancer (CC) is associated with alterations in immune system balance, which is primarily due to a shift from Th1 to Th2 and the unbalance of Th17/Treg cells. Using in silico DNA copy number analysis, we have demonstrated that ~20% of CC samples exhibit gain of 8q22.3 and 19q13.31; the regions of the genome that encodes the KLF10 and PSG genes, respectively. Gene expression studies demonstrated that there were no alterations in KLF10 mRNA expression, whilst the PSG2 and −5 genes were up-regulated by 1.76 and 3.97-fold respectively in CC compared to normal tissue controls. siRNA and ChIP experiments in SiHa cells have demonstrated that KLF10 participates in immune response through regulation of IL6, IL25 and PSG2 and PSG5 genes. Using cervical tissues from KLF10−/− mice, we have identified down-regulation of PSG17, −21 and −23 and IL11. These results suggest that KLF10 may regulate immune system response genes in cervical cancer among other functions. KLF10 and PSG copy number variations and alterations in mRNA expression levels could represent novel molecular markers in CC.

Neurogenesis plays a significant role during adulthood, and the observation that neural stem cells reside in the central nervous system and the olfactory epithelium has attracted attention due to their importance in neuronal regeneration. In addition, soluble factors (SFs) release by neural stem cells may modulate the neurogenic process. Thus, in this study, we identified the SFs released by olfactory human neural stem/progenitor cells (hNS/PCs-OE). These cells express Ki67, nestin, and βIII-tubulin, indicating their neural lineage. The hNS/PCs-OE also express PSD95 and tau proteins during proliferation, but increased levels are observed after differentiation. Thus, we evaluated the effects of SFs from hNS/PCs-OE on the viability, proliferation, and differentiation potential of adult murine hippocampal neural precursor cells (AHPCs). SFs from hNS/PCs-OE maintain cells in the precursor and proliferative stages and mainly promote the astrocytic differentiation of AHPCs. These effects involved the activation, as measured by phosphorylation, of several proteins (Erk1/2; Akt/PRAS40/GSK3β and JAK/STAT) involved in key events of the neurogenic process. Moreover, according to the results from the antibody-based microarray approach, among the soluble factors, hNS/PCs-OE produce interleukin-6 (IL-6) and neurotrophin 4 (NT4). However, residual epidermal growth factor (EGF) was also detected. These proteins partially reproduced the effects of SFs from hNS/PCs-OE on AHPCs, and the mechanism underlying these effects is mediated by Src proteins, which have been implicated in EGF-induced transactivation of TrkB receptor. The results of the present study suggest the potential use of SFs from hNS/PCs-OE in controlling the differentiation potential of AHPCs. Thus, the potential clinical relevance of hNS/PCs-OE is worth pursuing.

We present Very Large Array C-, X-, and Q-band continuum observations, as well as 1.3 mm continuum and CO(2-1) observations with the Submillimeter Array toward the high-mass protostellar candidate ISOSS J23053+5953 SMM2. Compact centimeter continuum emission was detected near the center of the SMM2 core with a spectral index of 0.24(± 0.15) between 6 and 3.6 cm, and a radio luminosity of 1.3(±0.4) mJy kpc2. The 1.3 mm thermal dust emission indicates a mass of the SMM2 core of 45.8 (±13.4) M ⊙, and a density of 7.1 (±1.2)× 106 cm−3. The CO(2-1) observations reveal a large, massive molecular outflow centered on the SMM2 core. This fast outflow (>50 km s−1 from the cloud systemic velocity) is highly collimated, with a broader, lower-velocity component. The large values for outflow mass (45.2 ± 12.6 M ⊙) and momentum rate (6 ± 2 × 10−3 M ⊙ km s−1yr−1) derived from the CO emission are consistent with those of flows driven by high-mass YSOs. The dynamical timescale of the flow is between 1.5 and 7.2 × 104 yr. We also found from the C18O to thermal dust emission ratio that CO is depleted by a factor of about 20, possibly due to freeze-out of CO molecules on dust grains. Our data are consistent with previous findings that ISOSS J23053 + 5953 SMM2 is an emerging high-mass protostar in an early phase of evolution, with an ionized jet and a fast, highly collimated, and massive outflow.

Spasticity is one of the most frequent and disabling clinical manifestations of patients with stroke. In clinical practice, stretching is the most widely used physiotherapeutic intervention for this population. However, there is no solid evidence for its effectiveness. The aim of this study was to evaluate the effectiveness of different types of stretching in reducing post-stroke spasticity. Research was carried out until March 2021 in the following scientific databases: PubMed, CINAHL, Scopus, Cochrane Library, Web of Science, and PEDro. The PEDro scale and the Cochrane collaboration tool were used to assess the methodological quality and risk of bias of the studies. Eight articles were selected for qualitative analysis; six of them contributed information to the meta-analysis. No conclusive evidence was obtained on the effectiveness of stretching in terms of treating spasticity and range of motion in patients with stroke. Further research is necessary in order to determine the effectiveness of the use of stretching in this population, considering the different types of stretching (static and dynamic), the time of application, the measurement of the different components of spasticity, and the extrapolation of functional results., FundingThis research and the APC was partial funded by the Erasmus+ Strategic Partnership for Higher Education Program (Key Action 203), grant number 2018-1-PL01-KA203-051055.

El piedemonte mendocino (32º 50´S) se localiza en el frente orogénico activo de los Andes, donde se concentra la mayor deformación cuaternaria del país. En particular, esta región presenta condiciones únicas para los estudios neotectónicos de sismicidad de intraplaca. Esta región se ubica dentro del segmento de Flat Slab pampeano y se asocia a la subducción de la Dorsal de Juan Fernández lo que originan la ausencia de vulcanismo en este segmento. Además, tectónicamente, este sector refleja un cambio en el estilo de deformación donde aflora en particular la unidad morfoestructural de la Precordillera Sur que culmina a esta latitud. En este segmento, el frente orogénico activo se asocia a fallas inversas N-S que afectan niveles aluviales pleistocenos tardíos. En función de sus parámetros morfométricos, se han estimado las magnitudes máximas de los sismos posibles y diferentes índices morfométricos que han permitido establecer los sectores de mayor deformación validados con métodos indirectos complementarios de interferometría mediante imágenes radar (técnica DINSAR). Este trabajo resume todos los estudios realizados hasta el momento para comprender el estilo de deformación activa cuaternaria que presenta el piedemonte mendocino.

We present Very Large Array cm continuum observations, as well as 1.3 mm continuum and CO(2–1) observations taken with the Submillimeter Array toward the high-mass protostellar candidate ISOSS J23053+5953 SMM2. Compact cm continuum emission was detected near the center of the SMM2 dust core, and the 1.3 mm thermal dust emission indicates a core mass of 46 M ⊙. The CO(2–1) observation revealed a large, massive molecular flow centered on the SMM2 core. This fast outflow (>50 km s−1) appears highly collimated, with a broader, lower-velocity component. The large values for outflow mass (45 M ⊙), and energetics derived are consistent with those of flows driven by high-mass YSOs. The dynamical timescale of the flow is between 1.5−7.2 × 104 yr. Our data confirm previous findings that SMM2 is an emerging high-mass protostar in a very early phase of evolution, with an ionized jet, and a fast, highly collimated, and massive outflow.