U-Pb geochronology and paleogeography of the Valanginian–Hauterivian Neuquén Basin: Implications for Gondwana-scale source areas

Sedimentary basins located at the margins of continents act as the final base level for continental-scale catchments that are sometimes located thousands of kilometers away from the basin, and this condition of exceptionally long sediment transfer zones is probably reinforced in supercontinents, such as Gondwana. One of the most prominent marine basins in southwestern Gondwana during the Jurassic and Early Cretaceous was the Neuquén Basin (west-central Argentina), but its role as a sediment repository of far-flung source areas has not been extensively considered. This contribution provides the first detailed detrital-zircon U-Pb geochronology of the Valanginian–Hauterivian Pilmatué Member of the Agrio Formation, which is combined with sedimentology and paleogeographic reconstructions of the unit within the Neuquén Basin for a better understanding of the fluvial delivery systems. Our detrital-zircon signatures suggest that Triassic–Permian zircon populations were probably sourced from the adjacent western sector of the North Patagonian Massif, whereas Early Jurassic, Cambrian, Ordovician, and Proterozoic grains were most likely derived from farther east, in the eastern sector of the North Patagonian Massif, as well as presently remote terranes such as the Saldania Belt in southern Africa. We thus propose a Valanginian–Hauterivian longitudinal delivery system that, starting in the mid-continent region of southwestern Gondwana and by effective sorting, was bringing fine-grained or finer caliber sand to the Neuquén Basin shoreline. This delivery system was probably active (though not necessarily continuously) from Early Jurassic to Early Cretaceous until finally coming to an end during the opening of the South Atlantic Ocean in the latest Early Cretaceous.Fil: Schwarz, Ernesto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Geológicas. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Investigaciones Geológicas; ArgentinaFil: Finzel, E.S.. University of Iowa; Estados UnidosFil: Veiga, Gonzalo Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Geológicas. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Investigaciones Geológicas; ArgentinaFil: Rapela, Carlos Washington. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Geológicas. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Investigaciones Geológicas; ArgentinaFil: Echevarria, C.. No especifíca;Fil: Spalletti, Luis Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Geológicas. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Investigaciones Geológicas; Argentin

Multiwavelength observations of V479 Andromedae: a close compact binary with an identity crisis

We conducted a multi-wavelength study to unveil the properties of the extremely long-period cataclysmic variable V479 And. We performed series of observations, including moderate to high spectral resolution optical spectrophotometry, X-ray observations with Swift, linear polarimetry and near-IR photometry. This binary system is a low-inclination ~ 17^o system with a 0.594093(4) day orbital period. The absorption line complex in the spectra indicate a G8--K0 spectral type for the donor star, which has departed from the zero-age main sequence. This implies a distance to the object of about 4 kpc. The primary is probably a massive 1.1-1.4 Msun magnetic white dwarf, accreting matter at a rate M(dot) > 10^-10 Msun/ yr. This rate can be achieved if the donor star fills its corresponding Roche lobe, but there is little observational evidence for a mass-transfer stream in this system. An alternative explanation is a stellar wind from the donor star, although such a high rate mass loss is not anticipated from a subgiant. If the strongly magnetic white dwarf in V479 And. is confirmed by future observations, the system the polar with the longest observed orbital period. We also discuss the evolutionary state of V479 And.Comment: 12 pages, 12 figures, accepted for publication in Astronomy and Astrophysic

Fgf8-Related Secondary Organizers Exert Different Polarizing Planar Instructions along the Mouse Anterior Neural Tube

Peer reviewe

BSSRDF estimation from single images

We present a novel method to estimate an approximation of the reflectance characteristics of optically thick, homogeneous translucent materials using only a single photograph as input. First, we approximate the diffusion profile as a linear combination of piecewise constant functions, an approach that enables a linear system minimization and maximizes robustness in the presence of suboptimal input data inferred from the image. We then fit to a smoother monotonically decreasing model, ensuring continuity on its first derivative. We show the feasibility of our approach and validate it in controlled environments, comparing well against physical measurements from previous works. Next, we explore the performance of our method in uncontrolled scenarios, where neither lighting nor geometry are known. We show that these can be roughly approximated from the corresponding image by making two simple assumptions: that the object is lit by a distant light source and that it is globally convex, allowing us to capture the visual appearance of the photographed material. Compared with previous works, our technique offers an attractive balance between visual accuracy and ease of use, allowing its use in a wide range of scenarios including off-the-shelf, single images, thus extending the current repertoire of real-world data acquisition techniques

Clinical evaluation of the role of ceftaroline in the management of community acquired bacterial pneumonia

Ceftaroline fosamil (ceftaroline) was recently approved for the treatment of community- acquired pneumonia (CAP) and complicated skin infections. This newly developed cephalosporin possesses a broad spectrum of activity against gram-positive and gram-negative bacteria. Most importantly, ceftaroline demonstrates potent in vitro antimicrobial activity against multi-drug resistant Streptococcus pneumoniae and methicillin-resistant strains of Staphylococcus aureus. In two Phase III, double-blinded, randomized, prospective trials (FOCUS 1 and FOCUS 2), ceftaroline was shown to be non-inferior to ceftriaxone for the treatment of CAP in hospitalized patients. Ceftaroline exhibits low resistance rates and a safety profile similar to that of other cephalosporins. In this review, we will evaluate the pharmacological characteristics, safety, antimicrobial properties, and efficacy of ceftaroline and its applications in the treatment of CAP

Characterization of the functional properties of the neuroectoderm in mouse Cripto -/-

During development of the mammalian embryo, there is a complex relation between formation of the mesoderm and the neuroectoderm. In mouse, for example, the role of the node and its mesendoderm derivatives in anterior neural specification is still debated. Mouse Cripto(-/-) embryos could potentially help settle this debate because they lack almost all embryonic endoderm and mesoderm, including the node and its derivatives. In the present paper, we show that Cripto(-/-) embryos can still form functional neural stem cells that are able to differentiate and maintain a neural phenotype both in vivo and in vitro. These data suggest that signals emanating from the mesoderm and endoderm might not be essential for the formation and differentiation of neural stem cells. However, we use grafting experiments to show that the Cripto(-/-) isthmus (the secondary organizer located at the midbrain-hindbrain boundary) loses its inductive ability. We further show that the Cripto(-/-)isthmus expresses lower amounts of the isthmic signalling molecule, Fgf8. Since nearby tissues remain competent to respond to exogenously added Fgf8, this reduction in Fgf8 levels in the Cripto(-/-) isthmus is the potential cause of the loss of patterning ability in graft experiments. Overall, we interpret our data to suggest that the mammalian node and primitive streak are essential for the development of the regional identities that control the specification and formation of the secondary organizers within the developing brain.2.161 JCR (2009) Q4, 27/36 Developmental biolog

Rare Recombinant GI.5[P4] Norovirus That Caused a Large Foodborne Outbreak of Gastroenteritis in a Hotel in Spain in 2021

Noroviruses are among the most important causes of acute gastroenteritis (AGE). In summer 2021, a large outbreak of norovirus infections affecting 163 patients, including 15 norovirus-confirmed food handlers, occurred in a hotel in Murcia in southeast Spain. A rare GI.5[P4] norovirus strain was identified as the cause of the outbreak. The epidemiological investigation determined that norovirus transmission might have been initiated through an infected food handler. The food safety inspection found that some symptomatic food handlers continued working during illness. Molecular investigation with whole-genome and ORF1 sequencing provided enhanced genetic discrimination over ORF2 sequencing alone and enabled differentiation of the GI.5[P4] strains into separate subclusters, suggesting different chains of transmission. These recombinant viruses have been identified circulating globally over the last 5 years, warranting further global surveillance. IMPORTANCE Due to the large genetic diversity of noroviruses, it is important to enhance the discriminatory power of typing techniques to differentiate strains when investigating outbreaks and elucidating transmission chains. This study highlights the importance of (i) using whole-genome sequencing to ensure genetic differentiation of GI noroviruses to track chains of transmission during outbreak investigations and (ii) the adherence of symptomatic food handlers to work exclusion rules and strict hand hygiene practices. To our knowledge, this study provides the first full-length genome sequences of GI.5[P4] strains apart from the prototype strain.We thank the Genomics and Bioinformatic Departments at the ISCIII for technical assistance. This study was partially funded through project PI20CIII/00005.S

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project

Introduction Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visual disorders. However, current screening programmes face several limitations: training required to perform them efficiently, lack of accurate screening tools and poor collaboration from young children. Some of these limitations can be overcome by new digital tools. Implementing a system based on artificial intelligence systems avoid the challenge of interpreting visual outcomes. The objective of the TrackAI Project is to develop a system to identify children with visual disorders. The system will have two main components: a novel visual test implemented in a digital device, DIVE (Device for an Integral Visual Examination); and artificial intelligence algorithms that will run on a smartphone to analyse automatically the visual data gathered by DIVE. Methods and analysis This is a multicentre study, with at least five centres located in five geographically diverse study sites participating in the recruitment, covering Europe, USA and Asia. The study will include children aged between 6 months and 14 years, both with normal or abnormal visual development. The project will be divided in two consecutive phases: design and training of an artificial intelligence (AI) algorithm to identify visual problems, and system development and validation. The study protocol will consist of a comprehensive ophthalmological examination, performed by an experienced paediatric ophthalmologist, and an exam of the visual function using a DIVE. For the first part of the study, diagnostic labels will be given to each DIVE exam to train the neural network. For the validation, diagnosis provided by ophthalmologists will be compared with AI system outcomes. Ethics and dissemination The study will be conducted in accordance with the principles of Good Clinical Practice. This protocol was approved by the Clinical Research Ethics Committee of Aragón, CEICA, on January 2019 (Code PI18/346). Results will be published in peer-reviewed journals and disseminated in scientific meetings

Secretagogin expression in the vertebrate brainstem with focus on the noradrenergic system and implications for Alzheimer's disease

Calcium-binding proteins are widely used to distinguish neuronal subsets in the brain. This study focuses on secretagogin, an EF-hand calcium sensor, to identify distinct neuronal populations in the brainstem of several vertebrate species. By using neural tube whole mounts of mouse embryos, we show that secretagogin is already expressed during the early ontogeny of brainstem noradrenaline cells. In adults, secretagogin-expressing neurons typically populate relay centres of special senses and vegetative regulatory centres of the medulla oblongata, pons and midbrain. Notably, secretagogin expression overlapped with the brainstem column of noradrenergic cell bodies, including the locus coeruleus (A6) and the A1, A5 and A7 fields. Secretagogin expression in avian, mouse, rat and human samples showed quasi-equivalent patterns, suggesting conservation throughout vertebrate phylogeny. We found reduced secretagogin expression in locus coeruleus from subjects with Alzheimer's disease, and this reduction paralleled the loss of tyrosine hydroxylase, the enzyme rate limiting noradrenaline synthesis. Residual secretagogin immunoreactivity was confined to small submembrane domains associated with initial aberrant tau phosphorylation. In conclusion, we provide evidence that secretagogin is a useful marker to distinguish neuronal subsets in the brainstem, conserved throughout several species, and its altered expression may reflect cellular dysfunction of locus coeruleus neurons in Alzheimer's disease

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

Background The nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter‑annual climate variability. Methods We used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud‑based computing platform for subsequent modelling. To determine the biodiversity threats from high inter‑annual climate variability, we employed the spatial–temporal satellite‑derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery. Results SOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions. Conclusions In the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.EEA Santa CruzFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gaitan, Juan José. Universidad Nacional de Luján. Buenos Aires; Argentina.Fil: Gaitan, Juan José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Mastrangelo, Matias Enrique. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Mastrangelo, Matias Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Nosetto, Marcelo Daniel. Universidad Nacional de San Luis. Instituto de Matemática Aplicada San Luis. Grupo de Estudios Ambientales; Argentina.Fil: Nosetto, Marcelo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Villagra, Pablo Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Villagra, Pablo Eugenio. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Balducci, Ezequiel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Yuto; Argentina.Fil: Pinazo, Martín Alcides. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Eclesia, Roxana Paola. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina.Fil: Von Wallis, Alejandra. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Villarino, Sebastián. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Villarino, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Alaggia, Francisco Guillermo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Alaggia, Francisco Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gonzalez-Polo, Marina. Universidad Nacional del Comahue; Argentina.Fil: Gonzalez-Polo, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. INIBIOMA; Argentina.Fil: Manrique, Silvana M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Energía No Convencional. CCT Salta‑Jujuy; Argentina.Fil: Meglioli, Pablo A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Meglioli, Pablo A. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Mónaco, Martín H. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Chaves, Jimena Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Medina, Ariel. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Gasparri, Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional; Argentina.Fil: Gasparri, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Alvarez Arnesi, Eugenio. Universidad Nacional de Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Alvarez Arnesi, Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Barral, María Paula. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Barral, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Von Müller, Axel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel Argentina.Fil: Pahr, Norberto Manuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Uribe Echevarría, Josefina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Quimilí; Argentina.Fil: Fernandez, Pedro Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Famaillá; Argentina.Fil: Fernandez, Pedro Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Morsucci, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Morsucci, Marina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Lopez, Dardo Ruben. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Lopez, Dardo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata (UNLP). Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.Fil: Alvarez, Leandro M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Alvarez, Leandro M. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Barberis, Ignacio Martín. Universidad Nacional de Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Barberis, Ignacio Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Colomb, Hernán Pablo. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Colomb, Hernán. Administración de Parques Nacionales (APN). Parque Nacional Los Alerces; Argentina.Fil: La Manna, Ludmila. Universidad Nacional de la Patagonia San Juan Bosco. Centro de Estudios Ambientales Integrados (CEAI); Argentina.Fil: La Manna, Ludmila. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Barbaro, Sebastian Ernesto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; Argentina.Fil: Blundo, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Blundo, Cecilia. Universidad Nacional de Tucumán. Tucumán; Argentina.Fil: Sirimarco, Marina Ximena. Universidad Nacional de Mar del Plata. Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP); Argentina.Fil: Sirimarco, Marina Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Cavallero, Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Zalazar, Gualberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Zalazar, Gualberto. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina