Adakitic Dacites Formed by Intracrustal Crystal Fractionation of Water-rich Parent Magmas at Nevado de Longaví Volcano (36·2°S; Andean Southern Volcanic Zone, Central Chile)

The mid-Holocene eruptive products of Nevado de Longaví volcano (36·2°S, Chile) are the only reported occurrence of adakitic volcanic rocks in the Quaternary Andean Southern Volcanic Zone (33-46°S). Dacites of this volcano are chemically distinct from other evolved magmas of the region in that they have high La/Yb (15-20) and Sr/Y (60-90) ratios and systematically lower incompatible element contents. An origin by partial melting of high-pressure crustal sources seems unlikely from isotopic and trace element considerations. Mafic enclaves quenched into one of the dacites, on the other hand, constitute plausible parental magmas. Dacites and mafic enclaves share several characteristics such as mineral chemistry, whole-rock isotope and trace element ratios, highly oxidizing conditions (NNO + 1·5 to >NNO + 2, where NNO is the nickel-nickel oxide buffer), and elevated boron contents. A two-stage mass-balance crystal fractionation model that matches both major and trace elements is proposed to explain magmatic evolution from the least evolved mafic enclave to the dacites. Amphibole is the main ferromagnesian phase in both stages of this model, in agreement with the mineralogy of the magmas. We also describe cumulate-textured xenoliths that correspond very closely to the solid assemblages predicted by the model. We conclude that Nevado de Longaví adakitic dacites are the products of polybaric fractional crystallization from exceptionally water-rich parent magmas. These basaltic magmas are inferred to be related to an exceptionally high, but transient input of slab-derived fluids released from serpentinite bodies hosted in the oceanic Mocha Fracture Zone, which projects beneath Nevado de Longaví. Fractional crystallization that is modally dominated by amphibole, with very minor garnet extraction, is a mechanism for generating adakitic magmas in cold subduction zones where a high flux of slab-derived fluids is presen

Neural Networks for Aircraft Trajectory Prediction: Answering Open Questions About Their Performance

The increase in air traffic in the recent years has motivated the development of technologies to monitor air space and warn about possible collisions by predicting the trajectories that will be followed by aircraft. In this field, neural networks have become prominent thanks to their potential to learn to predict maneuvers without providing aspects that are difficult to model such as atmospheric conditions, or detailed aircraft parameters. A variety of models have been proposed; however, these are often tested in very limited setups, leaving many unanswered questions about how they perform in certain conditions, or whether or not their accuracy can be improved by training models for specific trajectories, using additional features, predicting more distant points directly, etc. This may be problematic for researchers or developers of these systems, who have no way of knowing what strategies will yield the best results. We have identified ten open research questions that have not been answered through in-depth testing. This motivated us to carry out a novel experimental study that performs aircraft trajectory prediction with several dozens configuration variants to answer the aforementioned questions by means of a much more complete evaluation. Some of the conclusions of our study stand in contrast with some popular practices in the state of the art, which casts some doubts on the simplicity of their application; for example, differential features are crucial for proper performance but are not mentioned by most studies, while complex, more elaborate models may lead to worse results than simple ones. Other important insights include the benefit from specialized models in more challenging scenarios, the influence of the known trajectory length in said scenarios, the step degradation of predictions when predicting further into the future, or the detrimental effect of adding additional features. These insights should help guide future research about the application of neural networks when it comes to aircraft trajectory prediction and their eventual inclusion in final systems.journal articl

Regulation of TSHR expression in the thyroid and thymus may contribute to TSHR tolerance failure in graves’ disease patients via two distinct mechanisms

Graves’ disease; TSHR; ToleranceMalaltia de Graves; TSHR; TolerànciaEnfermedad de Graves; TSHR; ToleranciaGraves' disease (GD) involves the presence of agonistic auto-antibodies against the thyrotropin receptor (TSHR), which are responsible for the clinical symptoms. While failure of TSHR tolerance is central to GD pathogenesis, the process leading to this failure remains poorly understood. Two mechanisms intimately linked to tolerance have been proposed to explain the association of SNPs located in TSHR intron 1 to GD: (1) differential alternative splicing in the thyroid; and (2) modulation of expression in the thymus. To elucidate the relative contribution to these two mechanisms to GD pathogenesis, we analyzed the level of full-length and ST4 and ST5 isoform expression in the thyroid (n = 49) and thymus (n = 39) glands, and the influence of intron 1-associated SNPs on such expression. The results show that: (1) the level of flTSHR and ST4 expression in the thymus was unexpectedly high (20% that of the thyroid); (2) while flTSHR is the predominant isoform, the levels are similar to ST4 (ratio flTSHR/ST4 = 1.34 in the thyroid and ratio flTSHR/ST4 in the thymus = 1.93); (3) next-generation sequencing confirmed the effect of the TSHR intron 1 polymorphism on TSHR expression in the thymus with a bias of 1.5 ± 0.2 overexpression of the protective allele in the thymus compared to the thyroid; (4) GD-associated intron 1 SNPs did not influence TSHR alternative splicing of ST4 and ST5 in the thyroid and thymus; and (5) three-color confocal imaging showed that TSHR is associated with both thymocytes, macrophages, and dendritic cells in the thymus. Our findings confirm the effect of intron 1 polymorphisms on thymic TSHR expression and we present evidence against an effect on the relative expression of isoforms. The high level of ST4 expression in the thymus and its distribution within the tissue suggest that this would most likely be the isoform that induces central tolerance to TSHR thus omitting most of the hinge and transmembrane portion. The lack of central tolerance to a large portion of TSHR may explain the relatively high frequency of autoimmunity related to TSHR and its clinical consequence, GD.This study was funded by Instituto de Salud Carlos III, grants PI14/00848, and PI17/00324, co-financed by the European Regional Development Fund (ERDF). DÁ-S is in recipient of a predoctoral fellowship from the Vall d’Hebron Research Institute (VHIR)

Vaccination with designed neopeptides induces intratumoral, cross-reactive CD4+ T cell responses in glioblastoma

Purpose: The low mutational load of some cancers is considered one reason for the difficulties to develop effective tumor vaccines. To overcome this problem, we developed a strategy to design neopeptides through single amino acid mutation to enhance their immunogenicity. Experimental Design: Exome- and RNA sequencing as well as in silico HLA-binding predictions to autologous HLA molecules were used to identify candidate neopeptides. Subsequently, in silico HLA-anchor placements were used to deduce putative T cell receptor contacts of peptides. Single amino acids of TCR contacting residues were then mutated by amino acid replacements. Overall, 175 peptides were synthesized and sets of 25 each containing both peptides designed to bind to HLA class I and II molecules applied in the vaccination. Upon development of a tumor recurrence, the tumor-infiltrating lymphocytes (TILs) were characterized in detail both at the bulk and clonal level. Results: The immune response of peripheral blood T cells to vaccine peptides, including natural peptides and designed neopeptides, gradually increased with repetitive vaccination, but remained low. In contrast, at the time of tumor recurrence, CD8+ TILs and CD4+ TILs responded to 45% and 100% respectively of the vaccine peptides. Further, TIL-derived CD4+ T cell clones showed strong responses and tumor cell lysis not only against the designed neopeptide but also against the unmutated natural peptides of the tumor. Conclusions: Turning tumor self-peptides into foreign antigens by introduction of designed mutations is a promising strategy to induce strong intratumoral CD4+ T cell responses in a cold tumor like glioblastoma

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Disseny d'un extensor de pistó per a motor òptic d'encesa per compressió per a aplicacions pesades

[ES] El objetivo de este proyecto es el diseño de una pieza conocida como “Extensor del pistón” para la futura fabricación de un nuevo motor transparente por parte del Departamento de Máquinas y Motores Térmicos. Dicha máquina es un tipo de motor de combustión interna alternativo que permite visualizar los fenómenos que ocurren en el interior de la cámara de combustión del cilindro. Esta pieza es un elemento esencial para garantizar al mismo tiempo el funcionamiento del motor y la posibilidad de observar lo que pasa en su interior. Además, el motor está destinado para aplicaciones de “Alta carga” (camiones, grandes grupos electrógenos, maquinaria pesada, etc.), cuatro veces más grande que cualquier otro que se haya fabricado antes en el Departamento. El TFG aborda tareas como la definición de las condiciones de operación y los esfuerzos a los que se va a someter la pieza, así como la selección de materiales adecuados para la aplicación. Estudiar alternativas de diseño de la pieza en función de los materiales seleccionados, asistido con análisis de esfuerzos mediante herramientas de diseño CAD y simulación por elementos finitos. Selección del proceso de fabricación y finalmente realización de presupuesto de fabricación de cada una de las alternativas de las piezas diseñadas. En cuanto a las competencias específicas de grado se refiere, se van a aplicar conocimientos de termodinámica aplicada, ingeniería gráfica, ingeniería de materiales, así como elasticidad y resistencia de materiales al comportamiento de sólidos reales y principios de la resistencia de materiales. Por otra parte, en cuanto a la aplicación de competencias generales podemos destacar, sobre todo, capacidad de resolución de problemas con iniciativa, toma de decisiones, análisis y resolución de problemas, diseño y proyecto.[EN] The aim of this project is the design of a part known as the "Piston Extender" for the future manufacture of a new transparent engine by the Department of Machines and Thermal Engines. This machine is a type of alternative internal combustion engine that makes it possible to visualise the phenomena occurring inside the combustion chamber of the cylinder. This part is an essential element to ensure both the operation of the engine and the possibility of observing what is going on inside it. In addition, the engine is intended for "High Load" applications (trucks, large generators, heavy machinery, etc.), four times larger than any other engine ever produced in the Department. The TFG addresses tasks such as the definition of the operating conditions and stresses to which the part will be subjected, as well as the selection of suitable materials for the application. Studying design alternatives for the part depending on the materials selected, assisted by stress analysis using CAD design tools and finite element simulation. Selection of the manufacturing process and, finally, preparation of the manufacturing budget for each of the alternatives for the parts designed. As far as the specific competences of the degree are concerned, knowledge of applied thermodynamics, graphic engineering, materials engineering, as well as elasticity and resistance of materials will be applied to the behaviour of real solids and the principles of the resistance of materials. On the other hand, as far as the application of general competences is concerned, we can highlight, above all, the ability to solve problems with initiative, decision-making, analysis and problem-solving, design and project.Sellés Simón, D. (2022). Diseño de un extensor de pistón para motor óptico de encendido por compresión para aplicaciones pesadas. Universitat Politècnica de València. http://hdl.handle.net/10251/18800

Stratigraphy, petrology, and geochemistry of Nevado de Longaví volcano : Chilean Andes (36.2°S)

Le volcan Nevado de Longaví (36.2°S, Andes du Chili) a émis des laves dont la composition chimique est, de plusieurs points de vue, unique dans le contexte des Andes du Sud. Les produits les plus récents du volcan sont caractérisés par les concentrations des éléments incompatibles les plus faibles de la région et par des rapports Sr/Y et La/Yb élevés. Ces caractéristiques sont expliquées par le fractionnement de phases minérales qui sont stabilisées dans des magmas riches en eau (amphibole, plagioclase calcique, ±grenat). Ces minéraux forment des xénolites plutoniques retrouvés dans certaines laves. La subduction d'une zone de fracture dans la croûte océanique est probablement responsable des teneurs en eau anormalement élevées. Cette zone de fracture n'est pas stationnaire mais migre vers le sud ; la stratigraphie interne du volcan enregistre des changements de chimie et minéralogie cohérents avec une augmentation progressive de l'influence de la zone de fracture

openSkies - Integration of Aviation Data into the R Ecosystem

Aviation data has become increasingly more accessible to the public thanks to the adoption of technologies such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Mode S, which provide aircraft information over publicly accessible radio channels. Furthermore, the OpenSky Network provides multiple public resources to access such air traffic data from a large network of ADS-B receivers. Here, we present openSkies, the first R package for processing public air traffic data. The package provides an interface to the OpenSky Network resources, standardized data structures to represent the different entities involved in air traffic data, and functionalities to analyze and visualize such data. Furthermore, the portability of the implemented data structures makes openSkies easily reusable by other packages, therefore laying the foundation of aviation data engineering in R.Ministerio de Ciencia e Innovación PID2019-105471RB-I00Junta de Andalucía P18-RT-106

Neural Networks for Aircraft Trajectory Prediction: Answering Open Questions About Their Performance

The increase in air traffic in the recent years has motivated the development of technologies to monitor air space and warn about possible collisions by predicting the trajectories that will be followed by aircraft. In this field, neural networks have become prominent thanks to their potential to learn to predict maneuvers without providing aspects that are difficult to model such as atmospheric conditions, or detailed aircraft parameters. A variety of models have been proposed; however, these are often tested in very limited setups, leaving many unanswered questions about how they perform in certain conditions, or whether or not their accuracy can be improved by training models for specific trajectories, using additional features, predicting more distant points directly, etc. This may be problematic for researchers or developers of these systems, who have no way of knowing what strategies will yield the best results. We have identified ten open research questions that have not been answered through in-depth testing. This motivated us to carry out a novel experimental study that performs aircraft trajectory prediction with several dozens configuration variants to answer the aforementioned questions by means of a much more complete evaluation. Some of the conclusions of our study stand in contrast with some popular practices in the state of the art, which casts some doubts on the simplicity of their application; for example, differential features are crucial for proper performance but are not mentioned by most studies, while complex, more elaborate models may lead to worse results than simple ones. Other important insights include the benefit from specialized models in more challenging scenarios, the influence of the known trajectory length in said scenarios, the step degradation of predictions when predicting further into the future, or the detrimental effect of adding additional features. These insights should help guide future research about the application of neural networks when it comes to aircraft trajectory prediction and their eventual inclusion in final systems.Ministerio de Ciencia, Innovación y Universidades PID2019-105471RB-I00Junta de Andalucía P18-RT-1060Junta de Andalucía US-138056