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Cave heritage is often threatened by tourism or even scientific activities, which can lead to irreversible deterioration. We present a preventive conservation monitoring protocol to protect caves with rock art, focusing on La Garma Cave (Spain), a World Heritage Site with valuable archaeological materials and Palaeolithic paintings. This study assessed the suitability of the cave for tourist use through continuous microclimate and airborne particles monitoring, biofilm analysis, aerobiological monitoring and experimental visits. Our findings indicate several factors that make it inadvisable to adapt the cave for tourist use. Human presence and transit within the cave cause cumulative effects on the temperature of environmentally very stable and fragile sectors and significant resuspension of particles from the cave sediments. These environmental perturbations represent severe impacts as they affect the natural aerodynamic control of airborne particles and determine bacterial dispersal throughout the cave. This monitoring protocol provides part of the evidence to design strategies for sustainable cave management.

Inferring insect pollination from compression fossils and amber inclusions is difficult because of a lack of consensus on defining an insect pollinator and the challenge of recognizing this ecological relationship in deep time. We propose a conceptual definition for such insects and an operational classification into pollinator or presumed pollinator. Using this approach, we identified 15 insect families that include fossil pollinators and show that pollination relationships have existed since at least the Upper Jurassic (~163 Ma). Insects prior to this can only be classified as presumed pollinators. This gives a more nuanced insight into the origin and evolution of an ecological relationship that is vital to the establishment, composition and conservation of modern terrestrial ecosystems.

Amber is fossilized resin that preserves biological remains in exceptional detail, study of which has revolutionized understanding of past terrestrial organisms and habitats from the Early Cretaceous to the present day. Cretaceous amber outcrops are more abundant in the Northern Hemisphere and during an interval of about 54 million years, from the Barremian to the Campanian. The extensive resin production that generated this remarkable amber record may be attributed to the biology of coniferous resin producers, the growth of resiniferous forests in proximity to transitional sedimentary environments, and the dynamics of climate during the Cretaceous. Here we discuss the set of interrelated abiotic and biotic factors potentially involved in resin production during that time. We name this period of mass resin production by conifers during the late Mesozoic, fundamental as an archive of terrestrial life, the `Cretaceous Resinous Interval (CREI).

Monitoring the concentration of pigments like chlorophyll (Chl) in water-bodies is a key task to contribute to their conservation. However, with the existing sensor technology, measurement in real-time and with enough frequency to ensure proper risk management is not completely feasible. In this work, with the concept of data-driven soft-sensing, three hydrophysical features are used together with three meteorological ones to estimate the concentration of Chl in two tributaries of the River Thames. Data driven models, specifically neural networks, are used with three learning approaches: individual, centralized and federated. Data reduction scenarios are proposed in order to analyze the performance of each approach when less data is available. The best results in the training are usually obtained with the individual approach. However, the federated learning provides better generalization ability. It was also observed that in most of the cases the results of the federated learning approach improve those of the centralized one.

The polarization of the cosmic microwave background (CMB) can be used to search for parity-violating processes like that predicted by a Chern-Simons coupling to a light pseudoscalar field. Such an interaction rotates E modes into E modes in the observed CMB signal through an effect known as cosmic birefringence. Even though isotropic birefringence can be confused with the rotation produced by a miscalibration of the detectors' polarization angles, the degeneracy between both effects is broken when Galactic foreground emission is used as a calibrator. In this work, we use realistic simulations of the High-Frequency Instrument of the Planck mission to test the impact that Galactic foreground emission and instrumental systematics have on the recent birefringence measurements obtained through this technique. Our results demonstrate the robustness of the methodology against the miscalibration of polarization angles and other systematic effects, like intensity-to-polarization leakage, beam leakage, or cross-polarization effects. However, our estimator is sensitive to the EB correlation of polarized foreground emission. Here we propose to correct the bias induced by dust EB by modeling the foreground signal with templates produced in Bayesian component-separation analyses that fit parametric models to CMB data. Acknowledging the limitations of currently available dust templates like that of the Commander sky model, high-precision CMB data and a characterization of dust beyond the modified blackbody paradigm are needed to obtain a definitive measurement of cosmic birefringence in the future.

The target of rapamycin (TOR) signalling pathway plays a key role in the coordination between cellular growth and the cell cycle machinery in eukaryotes. The underlying molecular mechanisms by which TOR might regulate events after anaphase remain unknown. We show for the first time that one of the 2 TOR complexes in budding yeast, TORC1, blocks the separation of cells following cytokinesis by phosphorylation of a member of the NDR (nuclear Dbf2-related) protein-kinase family, the protein Cbk1. We observe that TORC1 alters the phosphorylation pattern of Cbk1 and we identify a residue within Cbk1 activation loop, T574, for which a phosphomimetic substitution makes Cbk1 catalytically inactive and, indeed, reproduces TORC1 control over cell separation. In addition, we identify the exocyst component Sec3 as a key substrate of Cbk1, since Sec3 activates the SNARE complex to promote membrane fusion. TORC1 activity ultimately compromises the interaction between Sec3 and a t-SNARE component. Our data indicate that TORC1 negatively regulates cell separation in budding yeast by participating in Cbk1 phosphorylation, which in turn controls the fusion of secretory vesicles transporting hydrolase at the site of division.

In this work the applicability of an ensemble of population and machine learning models to predict the evolution of the COVID-19 pandemic in Spain is evaluated, relying solely on public datasets. Firstly, using only incidence data, we trained machine learning models and adjusted classical ODE-based population models, especially suited to capture long term trends. As a novel approach, we then made an ensemble of these two families of models in order to obtain a more robust and accurate prediction. We then proceed to improve machine learning models by adding more input features: vaccination, human mobility and weather conditions. However, these improvements did not translate to the overall ensemble, as the different model families had also different prediction patterns. Additionally, machine learning models degraded when new COVID variants appeared after training. We finally used Shapley Additive Explanation values to discern the relative importance of the different input features for the machine learning models’ predictions. The conclusion of this work is that the ensemble of machine learning models and population models can be a promising alternative to SEIR-like compartmental models, especially given that the former do not need data from recovered patients, which are hard to collect and generally unavailable.

Extant terrestrial vertebrates, including birds, have a panoply of symbiotic relationships with many insects and arachnids, such as parasitism or mutualism. Yet, identifying arthropod¿vertebrate symbioses in the fossil record has been based largely on indirect evidence; findings of direct association between arthropod guests and dinosaur host remains are exceedingly scarce. Here, we present direct and indirect evidence demonstrating that beetle larvae fed on feathers from an undetermined theropod host (avian or nonavian) 105 million y ago. An exceptional amber assemblage is reported of larval molts (exuviae) intimately associated with plumulaceous feather and other remains, as well as three additional amber pieces preserving isolated conspecific exuviae. Samples were found in the roughly coeval Spanish amber deposits of El Soplao, San Just, and Peñacerrada I. Integration of the morphological, systematic, and taphonomic data shows that the beetle larval exuviae, belonging to three developmental stages, are most consistent with skin/hide beetles (family Dermestidae), an ecologically important group with extant keratophagous species that commonly inhabit bird and mammal nests. These findings show that a symbiotic relationship involving keratophagy comparable to that of beetles and birds in current ecosystems existed between their Early Cretaceous relatives.

[EN] Psocids, commonly known as barklice, are insects belonging to the order Psocodea, together with the parasitic lice. They usually inhabit forest litter or the bark of tree trunks and branches, showing grazing herbivorous or detritivorous feeding habits. The Cretaceous psocid record is diverse, containing more than 70 described species. Here, we present new psocids (Troctomorpha and possible Psocomorpha) from two Spanish amber outcrops, both Albian (Lower Cretaceous): El Soplao and Ariño. We describe the two new species Azarpsocus anjana Álvarez-Parra and Nel sp. nov. (Manicapsocidae) and Burmacompsocus ojancano Álvarez-Parra and Nel sp. nov. (Compsocidae), and the morphotype Ariño that might belong to Psocomorpha. We discuss the taxonomic placement of the studied specimens and comment on the palaeobiogeography of the Cretaceous psocids. The Cretaceous barklice fauna from Iberia shows more similarities with that from Lebanese (Barremian) and Burmese (Cenomanian) ambers than with that from the palaeogeographically closer French amber (Cenomanian). This finding has been also reported in other insect groups from Spanish amber, and might be the consequence of several factors, such as the palaeoenvironmental conditions of the ecosystems, the palaeogeographical position of the Iberia Island during the latest Jurassic, closer to Gondwana than to Laurasia, and oceanic currents that facilitated or hindered the displacement of insect fauna between continental masses.

Invasive fungi distributed worldwide through globalization have caused devastating diseases in different forests, causing economic and ecologic disturbances. Two such invasive species are Cryphonectria parasitica and Fusarium circinatum, which were introduced to Europe from North America, separated temporally: C. parasitica was introduced about nine decades ago, whereas F. circinatum was introduced around two decades ago. As C. parasitica had a longer time to undergo genetic changes, we hypothesized that it has higher genetic diversity than the recently introduced F. circinatum in Spain. In addition, we studied the genetic characterization of both fungi present in similar ecological conditions in Northern Spain with the aim of providing data for biocontrol measures.

Deep learning (DL) has emerged as a promising tool to downscale climate projections at regional-to-local scales from large-scale atmospheric fields following the perfect-prognosis approach. Given their complexity, it is crucial to properly evaluate these methods, especially when applied to changing climatic conditions where the ability to extrapolate/generalize is key. In this work, we intercompare several DL models extracted from the literature for the same challenging use-case (downscaling temperature in the CORDEX North America domain) and expand standard evaluation methods building on eXplainable Artificial Intelligence (XAI) techniques. Specifically, we introduce two novel XAI-based diagnostics—Aggregated Saliency Map and Saliency Dispersion Maps—and show how they can be used to unravel the internal behavior of these models, aiding in their design and evaluation. This work advocates for the introduction of XAI techniques into deep downscaling evaluation frameworks, especially when working with large regions and/or under climate change conditions.

Coronary artery tortuosity is usually an undetected condition in patients undergoing coronary angiography. This condition requires a longer examination by the specialist to be detected. Yet, detailed knowledge of the morphology of coronary arteries is essential for planning any interventional treatment, such as stenting. We aimed to analyze coronary artery tortuosity in coronary angiography with artificial intelligence techniques to develop an algorithm capable of automatically detecting this condition in patients. This work uses deep learning techniques, in particular, convolutional neural networks, to classify patients into tortuous or non-tortuous based on their coronary angiography. The developed model was trained both on left (Spider) and right (45°/0°) coronary angiographies following a fivefold cross-validation procedure. A total of 658 coronary angiographies were included. Experimental results demonstrated satisfactory performance of our image-based tortuosity detection system, with a test accuracy of (87 ± 6)%. The deep learning model had a mean area under the curve of 0.96 ± 0.03 over the test sets. The sensitivity, specificity, positive predictive values, and negative predictive values of the model for detecting coronary artery tortuosity were (87 ± 10)%, (88 ± 10)%, (89 ± 8)%, and (88 ± 9)%, respectively. Deep learning convolutional neural networks were found to have comparable sensitivity and specificity with independent experts’ radiological visual examination for detecting coronary artery tortuosity for a conservative threshold of 0.5. These findings have promising applications in the field of cardiology and medical imaging.

Long time series of rainfall at different levels of aggregation (daily or hourly in most cases) constitute the basic input for hydrological, hydraulic and climate studies. However, oftentimes the length, completeness, time resolution or spatial coverage of the available records falls short of the minimum requirements to build robust estimations. Here, we introduce NEOPRENE, a Python library to generate synthetic time series of rainfall. NEOPRENE simulates multi-site synthetic rainfall that reproduces observed statistics at different time aggregations. Three case studies exemplify the use of the library, focusing on extreme rainfall, as well as on disaggregating daily rainfall observations into hourly rainfall records. NEOPRENE is distributed from GitHub with an open license (GPLv3), free for research and commercial purposes alike. We also provide Jupyter notebooks with the example use cases to promote its adoption by researchers and practitioners involved in vulnerability, impact and adaptation studies.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19) pandemic. The severity of COVID-19 increases with each decade of life, a phenomenon that suggest that organismal aging contributes to the fatality of the disease. In this regard, we and others have previously shown that COVID-19 severity correlates with shorter telomeres, a molecular determinant of aging, in patient’s leukocytes. Lung injury is a predominant feature of acute SARS-CoV-2 infection that can further progress to lung fibrosis in post-COVID-19 patients. Short or dysfunctional telomeres in Alveolar type II (ATII) cells are sufficient to induce pulmonary fibrosis in mouse and humans. Here, we analyze telomere length and the histopathology of lung biopsies from a cohort of alive post-COVID-19 patients and a cohort of age-matched controls with lung cancer. We found loss of ATII cellularity and shorter telomeres in ATII cells concomitant with a marked increase in fibrotic lung parenchyma remodeling in post- COVID-19 patients compared to controls. These findings reveal a link between presence of short telomeres in ATII cells and long-term lung fibrosis sequel in Post-COVID-19 patients.

The highly conserved TOR signaling pathway is crucial for coordinating cellular growth with the cell cycle machinery in eukaryotes. One of the two TOR complexes in budding yeast, TORC1, integrates environmental cues and promotes cell growth. While cells grow, they need to copy their chromosomes, segregate them in mitosis, divide all their components during cytokinesis, and finally physically separate mother and daughter cells to start a new cell cycle apart from each other. To maintain cell size homeostasis and chromosome stability, it is crucial that mechanisms that control growth are connected and coordinated with the cell cycle. Successive periods of high and low TORC1 activity would participate in the adequate cell cycle progression. Here, we review the known molecular mechanisms through which TORC1 regulates the cell cycle in the budding yeast Saccharomyces cerevisiae that have been extensively used as a model organism to understand the role of its mammalian ortholog, mTORC1.

[EN] This study arises from the need to propose new methodologies to quantify wine consumption more precisely in order to use subsequently this information in observational food-health studies and dietary intervention studies. It has been developed an algorithm based on a “deep learning” method to determine wine volume from a single-view image, and it has been validated through a consumer study developed via a web application. The new model demonstrated satisfactory performance not only in a “daily lifelike” images dataset but also in “real” images (obtained from the consumer study), with a mean absolute error (MAE) of 10 and 26 mL, respectively. In relation to the data reported by the participants in the consumer study (n=38), average red wine volume in a glass was 114±33 mL, without being affected by factors such as gender, time of consumption, type of wine or type of glass. Therefore, the deep learning system together with the web application developed in this study constitute a diet monitoring tool of substantial value in the accurate assessment of daily wine intake, as well as in the habits of its consumption, with relevant applications in observational studies., [ES] Este estudio surge de la necesidad de nuevas metodologías que permitan cuantificar el consumo de vino con mayor precisión, para posteriormente utilizar esta información en estudios observacionales de alimentación-salud y estudios de intervención de dieta. Se ha desarrollado un algoritmo basado en un método de “aprendizaje profundo”, que permite determinar el volumen de vino en una copa/vaso a partir de una fotografía, y se ha validado en un estudio de consumidores realizado a través de una aplicación web. La aplicación del modelo a imágenes “cuasi-reales” y a imágenes "reales" (obtenidas a partir del estudio de consumidores), ha mostrado una precisión satisfactoria con un error absoluto medio (MAE) de 10 mL y 26 mL, respectivamente. En relación a las pautas de consumo de vino observadas en el estudio de consumidores (n=38), el volumen medio de vino tinto servido en una copa fue de 114±33 mL, sin estar condicionado por factores como el sexo del consumidor, el momento de consumo, el tipo de vino, o el formato de copa/vaso. En síntesis, el sistema de aprendizaje profundo desarrollado junto con la aplicación web, constituyen una herramienta de gran valor para la estimación precisa del volumen de vino consumido diariamente, así como las pautas de su consumo, de gran utilidad para estudios poblacionales

European caves contain some of the world’s greatest Paleolithic paintings, and their conservation is at risk due to the use of artificial lighting. Both lighting and high CO2 promotes the growth of phototrophic organisms on walls, speleothems and ground sediments. In addition, the combined effect of increases in CO2, vapor concentration and temperature variations induced by visitors can directly affect the development of corrosion processes on the cave rock surfaces. An early detection of the occurrence of phototrophic biofilms on Paleolithic paintings is of the utmost importance, as well as knowing the microorganisms involved in the colonization of rocks and walls. Knowledge of the colonizing species and their ecology will allow the adoption of control measures. However, this is not always possible due to the limited amount of biomass available for molecular analyses. Here, we present an alternative approach to study faint green biofilms of Chlorophyta in the initial stage of colonization on the Polychrome Panel in El Castillo Cave, Cantabria, Spain. The study of the biofilms collected on the rock art panel and in the ground sediments revealed that the lighting of the cave promoted the development of the green algae Jenufa and Coccomyxa, as well as of complex prokaryotic and eukaryotic communities, including amoebae, their endoparasites and associated bacteria and fungi. The enrichment method used is proposed as a tool to overcome technical constraints in characterizing biofilms in the early stages, allowing a preliminary characterization before deciding for direct or indirect interventions in the cave.

Reelin is an extracellular matrix glycoprotein reduced in brain regions (the prefrontal cortex and the hippocampus) of patients with schizophrenia. There are diverse rodent models of schizophrenia that mimic patient symptoms based on various causal theories; however, likely shared reelin alterations have not yet been systematically assessed in those models. A systematic review of the literature was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model. Articles focused on psychotic disorders or schizophrenia and their relationship with reelin in rodent models were selected. Data (first author, publication year, results, both open field and prepulse inhibition test results, and type of reelin alteration) were extracted in duplicate by two independent reviewers. The 37 reviewed articles reported about various schizophrenia models and their reelin alterations, brain morphology, and behavioral defects. We conclude that reelin is an altered preclinical biomarker common to all models included, mainly prenatal or genetic models, and a key protein in schizophrenia disease, making the reelin signaling pathway in prenatal stages a target of special interest for future preclinical and clinical studies. All models presented at least one of the four described reelin alteration types. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021210568], identifier [CRD42021210568].

Illegal wildlife poisoning is a global threat for biodiversity, yet the magnitude of its impact on ecosystems is largely underestimated as most of poisoning episodes remain undetected. Here, we conducted a large-scale field experiment to better understand the real dimension of the illegal wildlife poisoning in terms of composition and number of species and abundance of impacted individuals, as well as the ecological factors driving it. We used camera traps to monitor simulated poison baits placed in 25 study areas in SW Europe and applied Good–Turing theory to estimate the richness of species of the entire assemblage (observed plus undetected). We recorded 3095 individuals from 39 vertebrate species that consumed 94 % of the baits (N = 590). Yet, using sample completeness to estimate the entire species assemblage yielded a total of 47 species exposed to illegal poisoning. The observed assemblage included different trophic and functional groups (from lizards and snakes to apex species among birds and mammals), as well as a 38 % of threatened and near threatened species (according to Spanish and Portuguese vertebrate red list and UICN list). The size (weight) of the bait outstands as a reliable predictor of the number of species (0–8 species/bait, mean = 2) and individuals (0–99 individuals/bait, mean = 5) susceptible to poisoning. The habitat where the bait was placed modulated the abundance of individuals affected (greater in open than in closed habitats). Type of bait and habitat drove the compositional variation of species. Our approach enables uncover entire species assemblages prone to illegal poisoning and their ecological drivers associated, advancing the understanding of the impact of wildlife poisoning in ecosystems.

The Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) has adopted the FAIR Guiding Principles. We present the Atlas chapter of Working Group I (WGI) as a test case. We describe the application of the FAIR principles in the Atlas, the challenges faced during its implementation, and those that remain for the future. We introduce the open source repository resulting from this process, including coding (e.g., annotated Jupyter notebooks), data provenance, and some aggregated datasets used in some figures in the Atlas chapter and its interactive companion (the Interactive Atlas), open to scrutiny by the scientific community and the general public. We describe the informal pilot review conducted on this repository to gather recommendations that led to significant improvements. Finally, a working example illustrates the re-use of the repository resources to produce customized regional information, extending the Interactive Atlas products and running the code interactively in a web browser using Jupyter notebooks.

Deep learning (DL) has recently emerged as an innovative tool to downscale climate variables from large-scale atmospheric fields under the perfect-prognosis (PP) approach. Different convolutional neural networks (CNNs) have been applied under present-day conditions with promising results, but little is known about their suitability for extrapolating future climate change conditions. Here, we analyze this problem from a multi-model perspective, developing and evaluating an ensemble of CNN-based downscaled projections (hereafter DeepESD) for temperature and precipitation over the European EUR-44i (0.5°) domain, based on eight global circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). To our knowledge, this is the first time that CNNs have been used to produce downscaled multi-model ensembles based on the perfect-prognosis approach, allowing us to quantify inter-model uncertainty in climate change signals. The results are compared with those corresponding to an EUR-44 ensemble of regional climate models (RCMs) showing that DeepESD reduces distributional biases in the historical period. Moreover, the resulting climate change signals are broadly comparable to those obtained with the RCMs, with similar spatial structures. As for the uncertainty of the climate change signal (measured on the basis of inter-model spread), DeepESD preserves the uncertainty for temperature and results in a reduced uncertainty for precipitation. To facilitate further studies of this downscaling approach, we follow FAIR principles and make publicly available the code (a Jupyter notebook) and the DeepESD dataset. In particular, DeepESD is published at the Earth System Grid Federation (ESGF), as the first continental-wide PP dataset contributing to CORDEX (EUR-44).

The assessment of climate change impacts in regions with complex orography and land-sea interfaces poses a challenge related to shortcomings of global climate models. Furthermore, climate indices based on absolute thresholds are especially sensitive to systematic model biases. Here we assess the effect of bias adjustment (BA) on the projected changes in temperature extremes focusing on the number of annual days with maximum temperature above 35°C. To this aim, we use three BA methods of increasing complexity (from simple scaling to empirical quantile mapping) and present a global analysis of raw and BA CMIP5 projections under different global warming levels. The main conclusions are (1) BA amplifies the magnitude of the climate change signal (in some regions by a factor 2 or more) achieving a more plausible representation of future heat threshold-based indices; (2) simple BA methods provide similar results to more complex ones, thus supporting the use of simple and parsimonious BA methods in these studies.

This database contains biogeochemical data on different biogeochemical variables measured in three soil cores sampled in a saltmarsh community of the Bay of Santander (Gulf of Biscay).

Coronavirus disease 2019 (COVID-19) is the greatest threat to global health at the present time, and considerable public and private effort is being devoted to fighting this recently emerged disease. Despite the undoubted advances in the development of vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, uncertainty remains about their future efficacy and the duration of the immunity induced. It is therefore prudent to continue designing and testing vaccines against this pathogen. In this article we computationally designed two candidate vaccines, one monopeptide and one multipeptide, using a technique involving optimizing lambda-superstrings, which was introduced and developed by our research group. We tested the monopeptide vaccine, thus establishing a proof of concept for the validity of the technique. We synthesized a peptide of 22 amino acids in length, corresponding to one of the candidate vaccines, and prepared a dendritic cell (DC) vaccine vector loaded with the 22 amino acids SARS-CoV-2 peptide (positions 50-71) contained in the NTD domain (DC-CoVPSA) of the Spike protein. Next, we tested the immunogenicity, the type of immune response elicited, and the cytokine profile induced by the vaccine, using a non-related bacterial peptide as negative control. Our results indicated that the CoVPSA peptide of the Spike protein elicits noticeable immunogenicity in vivo using a DC vaccine vector and remarkable cellular and humoral immune responses. This DC vaccine vector loaded with the NTD peptide of the Spike protein elicited a predominant Th1-Th17 cytokine profile, indicative of an effective anti-viral response. Finally, we performed a proof of concept experiment in humans that included the following groups: asymptomatic non-active COVID-19 patients, vaccinated volunteers, and control donors that tested negative for SARS-CoV-2. The positive control was the current receptor binding domain epitope of COVID-19

El patrimonio natural y cultural de las cuevas se ve a menudo amenazado por el turismo y por otras actividades de carácter científico que las expone a riesgos que pueden provocar la alteración irreversible de sus condiciones ambientales de carácter irreversible. Las cuevas con arte rupestre y yacimientos arqueológicos suponen un caso especial y complejo. Cualquier modificación en sus condiciones climáticas conlleva un cambio en el ecosistema subterráneo que, a menudo, favorece el desarrollo y proliferación de poblaciones microbianas que llegan a colonizar los diferentes sustratos presentes en la cueva. La cueva de La Garma constituye un ejemplo destacado de cavidad con una larga frecuentación humana desde el Paleolítico antiguo hasta la Edad Media. Desde su descubrimiento en noviembre de 1995, la cueva sólo es accesible para la investigación arqueológica y la monitorización de sus condiciones ambientales. En este trabajo se presentan los resultados del estudio detallado de sus condiciones microclimáticas, y su influencia en la dispersión de microorganismos en el aire subterráneo y en el desarrollo de biofilms sobre la superficie de las rocas y los sedimentos. La dispersión bacteriana en el aire de la cueva está directamente influenciada por la circulación del aire, con fuertes incrementos durante los pulsos de ventilación vinculados a los vientos de componente sur en el exterior. Las conclusiones del estudio desaconsejan la adecuación de la cueva para su uso turístico y el control exhaustivo de cualquier trabajo arqueológico que implique perforaciones, zanjas o movimientos de tierras- sedimentos, ya que se favorecería la proliferación inmediata de colonias microbianas y con ello el desarrollo de procesos irreversibles de biodeterioro.

[ES] Las garrapatas (Ixodida) fósiles son muy escasas y todas, excepto algunos restos del Cuaternario, se han conservado en ámbar. Las más antiguas conocidas se encontraban en ámbar cretácico de Myanmar (99 millones de años). En febrero de 2016 se detectó una pequeña garrapata en una pieza preparada de ámbar del Albiense medio (105 millones de años) de Rábago-El Soplao (Cantabria). Se encuentra junto a más de 30 ejemplares de artrópodos con numerosos coprolitos de artrópodos y fragmentos vegetales. Pese a su pequeño tamaño, menos de un milímetro, y su cuerpo aplastado, se han podido describir las principales características anatómicas, gracias a la microscopía confocal láser espectral. Al principio se consideró dentro de la familia actual Nuttalliellidae, con una única especie conocida en África. La descripción de la familia fósil Deinocrotonidae, en 2017, a partir de numerosos ejemplares en ámbar de Myanmar, mostró que pertenecía al único género conocido de †Deinocrotonidae, Deinocroton. El ejemplar de Cantabria es un adulto, macho, con un tamaño y unas características que lo distinguen de las dos especies hasta ahora descritas, ambas de Myanmar, Deinocroton draculi y D. copia, por lo que se describirá como una nueva especie. Presenta palpos cortos, hipostoma poco desarrollado, poro genital entre las coxas I y II, surco genital posterior muy curvado, y poro anal algo alargado, entre otros caracteres. Se trata de la garrapata más antigua y la más pequeña en estado adulto que se conoce. Deinocroton draculi, especie a partir de la que se describió la familia. Deinocrotonidae, se considera nidícola (vivía en grupos en nidos o cerca de los mismos a la espera de huéspedes). A partir de evidencia diversa, alguna tafonómica, se considera que al menos los dinosaurios emplumados (Enantiornithes en este caso) fueron huéspedes para esta familia. Probablemente, la nueva especie de Cantabria compartía esta paleobiología.

Eukaryotic cells divide and separate all their components after chromosome segregation by a process called cytokinesis to complete cell division. Cytokinesis is highly regulated by the recruitment of the components to the division site and through post-translational modifications such as phosphorylations. The budding yeast mitotic kinases Cdc28-Clb2, Cdc5, and Dbf2-Mob1 phosphorylate several cytokinetic proteins contributing to the regulation of cytokinesis. The PP2A-Cdc55 phosphatase regulates mitosis counteracting Cdk1- and Cdc5-dependent phosphorylation. This prompted us to propose that PP2A-Cdc55 could also be counteracting the mitotic kinases during cytokinesis. Here we show that in the absence of Cdc55, AMR contraction and the primary septum formation occur asymmetrically to one side of the bud neck supporting a role for PP2A-Cdc55 in cytokinesis regulation. In addition, by in vivo and in vitro assays, we show that PP2A-Cdc55 dephosphorylates the chitin synthase II (Chs2 in budding yeast) a component of the Ingression Progression Complexes (IPCs) involved in cytokinesis. Interestingly, the non-phosphorylable version of Chs2 rescues the asymmetric AMR contraction and the defective septa formation observed in cdc55∆ mutant cells. Therefore, timely dephosphorylation of the Chs2 by PP2A-Cdc55 is crucial for proper actomyosin ring contraction. These findings reveal a new mechanism of cytokinesis regulation by the PP2A-Cdc55 phosphatase and extend our knowledge of the involvement of multiple phosphatases during cytokinesis.

Mycoviruses are known to be difficult to cure in fungi but their spontaneous loss occurs commonly. The unexpected disappearance of mycoviruses can be explained by diverse reasons, from methodological procedures to biological events such as posttranscriptional silencing machinery. The long-term effects of a virus infection on the host organism have been well studied in the case of human viruses; however, the possible residual effect on a fungus after the degradation of a mycovirus is unknown. For that, this study analyses a possible residual effect on the transcriptome of the pathogenic fungus Fusarium circinatum after the loss of the mitovirus FcMV1. The mycovirus that previously infected the fungal isolate was not recovered after a 4-year storage period. Only 14 genes were determined as differentially expressed and were related to cell cycle regulation and amino acid metabolism. The results showed a slight acceleration in the metabolism of the host that had lost the mycovirus by the upregulation of the genes involved in essential functions for fungal development. The analysis also revealed a weak expression in the annotated genes of the RNA silencing machinery. To our knowledge, this is the first time that a potential residual effect on the host transcriptome caused by the past infection of a mycovirus is reported.

Machine Learning classification models have been trained and validated from a dataset (73 features and 13,616 instances) including experimental information of a clean cold forming steel fabricated by electric arc furnace and hot rolling. A classification model was developed to identify inclusion contents above the median. The following algorithms were implemented: Logistic Regression, K-Nearest Neighbors, Decision Tree, Random Forests, AdaBoost, Gradient Boosting, Support Vector Classifier and Artificial Neural Networks. Random Forest displayed the best results overall and was selected for the subsequent analyses. The Permutation Importance method was used to identify the variables that influence the inclusion cleanliness and the impact of these variables was determined by means of Partial Dependence Plots. The influence of the final diameter of the coil has been interpreted considering the changes induced by the process of hot rolling in the distribution of inclusions. Several variables related to the secondary metallurgy and tundish operations have been identified and interpreted in metallurgical terms. In addition, the inspection area during the microscopic examination of the samples also appears to influence the inclusion content. Recommendations have been established for the sampling process and for the manufacturing conditions to optimize the inclusionary cleanliness of the steel.

Deep learning is nowadays at the forefront of artificial intelligence. More precisely, the use of convolutional neural networks has drastically improved the learning capabilities of computer vision applications, being able to directly consider raw data without any prior feature extraction. Advanced methods in the machine learning field, such as adaptive momentum algorithms or dropout regularization, have dramatically improved the convolutional neural networks predicting ability, outperforming that of conventional fully connected neural networks. This work summarizes, in an intended didactic way, the main aspects of these cutting-edge techniques from a medical imaging perspective.

Pharmaceuticals are considered emerging contaminants in terms of impacts on wildlife. One chemical group of concern is euthanasia agents used in veterinary medicine. Here we present data on the occurrence of barbiturate intoxication using samples collected from 2004 to 2020 of suspected wildlife and domestic animal poisoning cases in Spain (n = 3210). Barbiturate intoxication was seen in 3.4% (45/1334) of the total number of confirmed intoxicated animals. Barbiturates were detected in 0.2% (1/448) of baits containing detectable poisons. The most frequently detected barbiturate was pentobarbital (42/45, 93.3%), but we also detected phenobarbital, barbital, and thiopental (2.2% prevalence for each). Avian scavengers were most frequently affected by barbiturate intoxication (n = 36), especially Eurasian griffon vultures (Gyps fulvus) (n = 28). Median pentobarbital concentrations detected in intoxicated griffon vultures was 27.3 mg kg−1 in gastric content and 38.1 mg kg−1 in liver, which highlights the acute effect of the chemical soon after ingestion. At least two large intoxication events affecting griffon vultures were related to the consumption of carcasses from euthanized livestock. We also found phenobarbital in a prepared bait linked to the intoxication of one Eurasian buzzard (Buteo buteo). This study highlights the need for stronger regulation of barbiturates to avoid secondary intoxications due to improper disposal of euthanized livestock.

Objectives: To determine if patients with the predominant extracranial large-vessel-vasculitis (LVV) pattern of giant cell arteritis (GCA) have a distinctive HLA-B association, different from that reported in biopsy-proven cranial GCA patients. In a further step we assessed if the combination of HLA-B and HLA-DRB1 alleles confers an increased risk for GCA susceptibility, either for the cranial and extracranial LVV phenotypes. Methods: A total of 184 patients with biopsy-proven cranial GCA, 105 with LVV-GCA and 486 healthy controls were included in our study. We compared HLA-B phenotype frequencies between the three groups. Results: HLA-B*15 phenotype was significantly increased in patients with classic cranial GCA compared to controls (14.7% versus 5.8%, respectively; p<0.01; OR [95% CI] =2.81 [1.54-5.11]). It was mainly due to the HLA-B*15:01 allele (12.5% versus 4.0%, respectively; p<0.01; OR [95% CI] =3.51 [1.77-6.99]) and remained statistically significant after Bonferroni correction. Similar HLA-B*15 association was observed in patients with the LVV-GCA (11.4% versus 5.8%, p=0.04, OR [95% CI] =2.11 [1.04-4.30]). This association was also mainly due to the HLA-B*15:01 allele (10.5% versus 4.0%, respectively; p=0.0054; OR [95% CI] =2.88 [1.19-6.59]). Noteworthy, the presence of HLA-B*15:01 together with HLA-DRB1*04:01 led to an increased risk of developing both cranial and extracranial LVV-GCA. Conclusions: Susceptibility to GCA is strongly related to the HLA region, regardless of the clinical phenotype of expression of the disease.

BAFF, APRIL and BAFF-R are key proteins involved in the development of B-lymphocytes and autoimmunity. Additionally, BAFF, APRIL and BAFFR polymorphisms were associated with immune-mediated conditions, being BAFF GCTGT>A a shared insertion-deletion genetic variant for several autoimmune diseases. Accordingly, we assessed whether BAFF, APRIL and BAFFR represent novel genetic risk factors for Immunoglobulin-A vasculitis (IgAV), a predominantly B-lymphocyte inflammatory condition. BAFF rs374039502, which colocalizes with BAFF GCTGT>A, and two tag variants within APRIL (rs11552708 and rs6608) and BAFFR (rs7290134 and rs77874543) were genotyped in 386 Caucasian IgAV patients and 806 matched healthy controls. No genotypes or alleles differences were observed between IgAV patients and controls when BAFF, APRIL and BAFFR variants were analysed independently. Likewise, no statistically significant differences were found in the genotype and allele frequencies of BAFF, APRIL or BAFFR when IgAV patients were stratified according to the age at disease onset or to the presence/absence of gastrointestinal (GI) or renal manifestations. Similar results were disclosed when APRIL and BAFFR haplotypes were compared between IgAV patients and controls and between IgAV patients stratified according to the clinical characteristics mentioned above. Our results suggest that BAFF, APRIL and BAFFR do not contribute to the genetic network underlying IgAV.

The rapid development of mRNA-based vaccines against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) led to the design of accelerated vaccination schedules that have been extremely effective in naive individuals.While a two-dose immunization regimen with the BNT162b2 vaccine has been demonstrated to provide a 95% efficacy in naive individuals, the effects of the second vaccine dose in individuals who have previously recovered from natural SARS-CoV-2 infection has not been investigated in detail. In this study, we characterize SARS-CoV-2 spike-specific humoral and cellular immunity in naive and previously infected individuals during and after two doses of BNT162b2 vaccination. Our results demonstrate that, while the second dose increases both the humoral and cellular immunity in naive individuals, COVID-19 recovered individuals reach their peak of immunity after the first dose. These results suggests that a second dose, according to the current standard regimen of vaccination, may be not necessary in individuals previously infected with SARS-CoV-2.

Airborne microorganisms can cause important conservation problems in caves with Paleolithic art and therefore the knowledge of cave aerodynamic is essential. La Garma Cave (Cantabria, Spain), an exceptional archaeological site with several levels of galleries interconnected and two entrances, presents a complex atmospheric dynamics. An approach including aerobiological sampling together with microclimate monitoring was applied to assess the factors controlling the origin of airborne fungi. Here we show that winter ventilation is critical for the increasing of Basidiomycota spores in the cave air and the highest concentrations were found in the most ventilated areas. On the contrary, Ascomycota spores prevailed in absence of ventilation. Besides, most Ascomycota were linked to insects and bats that visit or inhabit the cave. The combination of aerobiological and microclimate data constitutes a good approach to evaluate the influence of external climatic conditions and design the most suitable strategies for the conservation of cultural heritage in the cave environment.

Primer premi, Award-winning, Postprint (published version)

The glycolytic enzyme and bacterial virulence factor of Listeria monocytogenes, the glyceraldehyde-3-phosphate dehydrogenase (GAPDH, Lmo2459), ADP-ribosylated the small GTPase, Rab5a, and blocked phagosome maturation. This inhibitory activity localized within the NAD binding domain of GAPDH at the N-terminal 1–22 peptides, also conferred listeriosis protection when used in dendritic cell-based vaccines. In this study, we explore GAPDH of Listeria, Mycobacterium, and Streptococcus spp. taxonomic groups to search for epitopes that confer broad protection against pathogenic strains of these bacteria. GAPDH multivalent epitopes are selected if they induce inhibitory actions and wide-ranging immune responses. Proteomic isolation of GAPDH from dendritic cells infected with Listeria, Mycobacterium, or Streptococcus confirmed similar enzymatic, Rab5a inhibitory and immune stimulation abilities. We identified by bioinformatics and functional analyses GAPDH N-terminal 1–22 peptides from Listeria, Mycobacterium, and Streptococcus that shared 95% sequence homology, enzymatic activity, and B and T cell immune domains. Sera obtained from patients or mice infected with hypervirulent pathogenic Listeria, Mycobacterium, or Streptococcus presented high levels of anti-GAPDH 1–22 antibodies and Th2 cytokines. Monocyte derived dendritic cells from healthy donors loaded with GAPDH 1–22 peptides from Listeria, Mycobacterium, or Streptococcus showed activation patterns that correspond to cross-immunity abilities. In summary, GAPDH 1–22 peptides appeared as putative candidates to include in multivalent dendritic based vaccine platforms for Listeria, Mycobacterium, or Streptococcus.

The prospects and potential of Reverse Electrodialysis (RED) for energy harvesting from natural streams with salinity gradient demand more in-depth studies to understand and overcome the limitations posed by divalent ions. Power performance is greatly influenced by the ionic resistance displayed by the alternating cation and anion exchange membranes (CEMs and AEMs, respectively) housed in RED stacks, which in turn is determined by the type and concentration of ions and counter-ions in the water streams. The effects of divalent ions on power output have been experimentally approached in several works by using real or synthetic water. However, the development of comprehensive models including the effect of divalent ions on membrane resistance and power performance under different scenarios is still very scarce. Thus, this work investigates experimentally the effect of ion species on membrane resistance, providing for the first time mathematical correlations useful to predict power performance in RED stacks under a wide range of compositions of salinity gradient solutions. To this end, electrochemical impedance spectroscopy (EIS) measurements have been performed for CEM and AEM commercial membranes in contact with different concentration of NaCl solutions and including different mixtures of divalent ions (Ca2+, Mg2+, SO42−). These correlations have been implemented in a previously developed model to determine power outputs as function of ion mixture compositions. Scenarios of general interest for RED practical implementation have been addressed; specifically, solutions with a composition representative of seawater or high salinity brines have been studied as high concentration solutions (HCS) and, on the other hand, typical concentrations of wastewater treatment plant effluents, river water or brackish water from desalination plants were used as low concentration solutions (LCS).

Phase reduction is a powerful technique that makes possible to describe the dynamics of a weakly perturbed limit-cycle oscillator in terms of its phase. For ensembles of oscillators, a classical example of phase reduction is the derivation of the Kuramoto model from the mean-field complex Ginzburg-Landau equation (MF-CGLE). Still, the Kuramoto model is a first-order phase approximation that displays either full synchronization or incoherence, but none of the nontrivial dynamics of the MF-CGLE. This fact calls for an expansion beyond the first order in the coupling constant. We develop an isochron-based scheme to obtain the second-order phase approximation, which reproduces the weak-coupling dynamics of the MF-CGLE. The practicality of our method is evidenced by extending the calculation up to third order. Each new term of the power-series expansion contributes with additional higher-order multibody (i.e., nonpairwise) interactions. This points to intricate multibody phase interactions as the source of pure collective chaos in the MF-CGLE at moderate coupling.

Despite the potential applicability of seasonal forecasting for decision making in construction, maintenance and operations of coastal and offshore infrastructures, tailored climate services have yet to be developed in the marine sector. In this work, we explore the potential of a state-of-the-art seasonal forecast system to predict wave conditions, particularly significant wave height. Since this information is not directly provided by models, a statistical downscaling method is applied to infer significant wave height based on model outputs such as sea level pressure, which drive waves over large wave generation areas beyond the target location over time. This method may be beneficial for seasonal forecasting since skill from wide generation areas can be propagated to wave conditions in (distant and smaller) target regions. We consider seasonal predictions with a one-month lead time of the CFSv2 hindcast in two regions: the Western Pacific around Indonesia during the June–July–August (JJA) season and the North Atlantic Ocean during the January–February–March (JFM) season. In the former case, skillful predictions are found, which are higher during decay years after ENSO warm phases when a negative anomaly of the significant wave height is expected. In contrast, statistical downscaling in the North Atlantic Ocean cannot add value to the signal given by the predictor, which is also very weak.

Eukaryotic cells must coordinate contraction of the actomyosin ring at the division site together with ingression of the plasma membrane and remodelling of the extracellular matrix (ECM) to support cytokinesis, but the underlying mechanisms are still poorly understood. In eukaryotes, glycosyltransferases that synthesise ECM polysaccharides are emerging as key factors during cytokinesis. The budding yeast chitin synthase Chs2 makes the primary septum, a special layer of the ECM, which is an essential process during cell division. Here we isolated a group of actomyosin ring components that form complexes together with Chs2 at the cleavage site at the end of the cell cycle, which we named ‘ingression progression complexes’ (IPCs). In addition to type II myosin, the IQGAP protein Iqg1 and Chs2, IPCs contain the F-BAR protein Hof1, and the cytokinesis regulators Inn1 and Cyk3. We describe the molecular mechanism by which chitin synthase is activated by direct association of the C2 domain of Inn1, and the transglutaminase-like domain of Cyk3, with the catalytic domain of Chs2. We used an experimental system to find a previously unanticipated role for the C-terminus of Inn1 in preventing the untimely activation of Chs2 at the cleavage site until Cyk3 releases the block on Chs2 activity during late mitosis. These findings support a model for the co-ordinated regulation of cell division in budding yeast, in which IPCs play a central role.

[ES]: La zona arqueológica de la Garma (Cantabria) forma parte de un gran complejo kárstico activo con varios niveles de galerías de desarrollo horizontal interconectados por conductos verticales. La Garma alberga un conjunto arqueológico excepcional que incluye un magnífico conjunto de arte parietal y suelos paleolíticos en un asombroso estado de conservación, así como valiosísimas evidencias del comportamiento simbólico de los cazadores-recolectores del Pleistoceno. Sus valores patrimoniales le han hecho merecedora de ser incluida en la Lista del Patrimonio Mundial de la UNESCO en el año 2008. La conservación de este enclave es en todo momento prioritaria y recientemente se ha puesto en marcha un programa de conservación preventiva que tiene como objetivo fundamental el conocimiento del ecosistema subterráneo y del impacto de la presencia humana en el medio subterráneo, a los efectos tanto de la propia gestión e investigación de la cavidad como ante una eventual apertura al público en condiciones de máxima seguridad. El funcionamiento de un sistema kárstico subterráneo como el de La Garma, con varios niveles de desarrollo y conectado directamente con el nivel freático activo, implica un complejo movimiento de materia (agua, masas de aire y aerosoles) y energía. Para alcanzar un adecuado conocimiento de su dinámica ambiental, desde febrero de 2015 se está llevando a cabo un estudio multidisciplinar mediante el empleo de metodologías específicas para cada interfase involucrada: microclima (cavidad en tres niveles internos del karst y atmósfera externa), hidroquímica (agua de infiltración y condensación), geoquímica isotópica (aire, suelo) y contaminación microbiológica (aire, suelo, roca). Los primeros datos muestran cambios estacionales muy marcados en el patrón de ventilación general de la cavidad, con mayor tasa de renovación de aire en la época invernal, y una estabilidad ambiental muy diferenciada entre zonas, con algunos sectores aislados del régimen general d, [EN]: The archaeological site of the Garma (Cantabria) is part of an active karst system with several levels of galleries interconnected by vertical shafts. La Garma houses an exceptional archaeological heritage that includes magnificent examples of Palaeolithic cave art and settlement floors in an amazing state of preservation, as well as valuable evidence of symbolic behavior of Pleistocene hunter-gatherers. Its heritage values have made it worthy of their inclusion on the World Heritage List of UNESCO in 2008. The conservation of this site is a priority and it has been recently launched a program of preventive conservation. The main objective of this project is to achieve a better knowledge of the underground ecosystem and the impact of human presence in the underground microenvironment, both for purposes of sound management and research of the cavity as well as for a hypothetical opening to the public in the future. The underground karst system of La Garma, with various levels of galleries and directly connected with active water table, involves a complex movement of matter (water, air masses and aerosols) and energy. To achieve an adequate knowledge of environmental dynamics, our research group is conducting a multidisciplinary study since February 2015 by employing specific methodologies for each interface involved: microclimate (cavity in three internal levels of karst and external atmosphere), hydrochemical (water infiltration and condensation), isotope geochemistry (air, soil) and microbiological contamination (air, soil, rock). Early data show very marked seasonal changes in the general ventilation pattern of the cavity (air renewal in winter) and areas with different microenvironmental stability, including sectors with a greater degree of isolation from the regime of general circulation of air in the cavity.

This paper presents a preliminary study to evaluate the performance of users with cerebral palsy (CP) using an inertial human-computer interface (HCI) based on head movements and a novel algorithm that makes the click easier to users with disability named MouseField. The algorithm is based on expandable buttons and gravity fields, used in the design of alternative HCIs for users with mild to severe motor disorders. Eleven users with CP participated in a series of tests that analyzed the performance in a reach and click task using an inertial interface with and without the MouseField algorithm. In average, the improvement of the performance was 28% with MouseFiled. This proves that the algorithm could be applied to more complex interfaces, e.g. those for augmentative and alternative communication (AAC) to be used in rehabilitation therapies.[EN], Este artículo presenta un estudio preliminar que analiza el rendimiento de usuarios con parálisis cerebral (CP) en el manejo del ordenador a través de una interfaz inercial basada en movimientos de la cabeza y un novedoso algoritmo de facilitación del clic, MouseField. El algoritmo está basado en técnicas de botones expansibles y campos gravitatorios, de gran utilidad en interfaces de acceso alternativo al computador para personas con trastornos motores moderados y severos. Once usuarios con CP participaron en una serie de tests para la comparación del rendimiento alcanzado con una interfaz inercial de acceso al computador frente al rendimiento de esa misma complementada con MouseField. En promedio, la mejora en el rendimiento fue del 28% para tareas de apuntamiento y selección, lo cual demuestra el potencial del algoritmo para el manejo de interfaces más complejas, p.e. de comunicación alternativa aumentativa en terapias de rehabilitación.[ES]