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Abstract Cobalt is an efficient catalyst for Fischer−Tropsch synthesis (FTS) of hydrocarbons from syngas (CO + H2) with enhanced selectivity for long-chain hydrocarbons when promoted by Manganese. However, the molecular scale origin of the enhancement remains unclear. Here we present an experimental and theoretical study using model catalysts consisting of crystalline CoMnOx nanoparticles and thin films, where Co and Mn are mixed at the sub-nm scale. Employing TEM and in-situ X-ray spectroscopies (XRD, APXPS, and XAS), we determine the catalyst’s atomic structure, chemical state, reactive species, and their evolution under FTS conditions. We show the concentration of CHx, the key intermediates, increases rapidly on CoMnOx, while no increase occurs without Mn. DFT simulations reveal that basic O sites in CoMnOx bind hydrogen atoms resulting from H2 dissociation on Co0 sites, making them less available to react with CHx intermediates, thus hindering chain termination reactions, which promotes the formation of long-chain hydrocarbons.

Despite the high efficiency of current SARS-CoV-2 mRNA vaccines in reducing COVID-19 morbidity and mortality, waning immunity and the emergence of resistant variants underscore the need for novel vaccination strategies. This study explores a heterologous mRNA/Modified Vaccinia virus Ankara (MVA) prime/boost regimen employing a trimeric form of the receptor binding domain (RBD) of the SARS-CoV-2 spike (S) protein compared to a homologous MVA/MVA regimen. In C57BL/6 mice, the RBD was delivered during priming via an mRNA vector encapsulated in nanoemulsions (NE) or lipid nanoparticles (LNP), followed by a booster with a replication-deficient MVA-based recombinant virus (MVA-RBD). This heterologous mRNA/MVA regimen elicited strong anti-RBD binding and neutralizing antibodies (BAbs and NAbs) against both the ancestral SARS-CoV-2 strain and different variants of concern (VoCs). Additionally, this protocol induced robust and polyfunctional RBD-specific CD4 and CD8 T cell responses, particularly in animals primed with mLNP-RBD. In K18-hACE2 transgenic mice, the LNP-RBD/MVA combination provided complete protection from morbidity and mortality following a live SARS-CoV-2 challenge compared with the partial protection observed with mNE-RBD/MVA or MVA/MVA regimens. Although the mNE-RBD/MVA regimen only protects half of the animals, it was able to induce antibodies with Fc-mediated effector functions besides NAbs. Moreover, viral replication and viral load in the respiratory tract were markedly reduced and decreased pro-inflammatory cytokine levels were observed. These results support the efficacy of heterologous mRNA/MVA vaccine combinations over homologous MVA/MVA regimen, using alternative nanocarriers that circumvent intellectual property restrictions of current mRNA vaccine formulations.

El sistema de justicia juvenil está mostrando cambios en sus enfoques y principios. El objetivo de esta investigación es identificar qué efectos surgen cuando se trabaja de manera interdisciplinaria, situando a los menores no como infractores, sino como adolescentes, reconociendo sus necesidades, capacidades y derechos. A partir de un enfoque cualitativo, se diseña un estudio de caso. Se eligen tres individuos entre el alumnado de un instituto de enseñanza secundaria donde se llevan a cabo medidas de internamiento. Mediante entrevistas, análisis documental y observación participante, se analizan las historias de vida, el acompañamiento de las familias y el trabajo realizado por los miembros del equipo docente en la identificación y eliminación de las barreras. Los resultados ponen de manifiesto la necesidad de partir de las vivencias de cada adolescente para identificar las barreras que encuentra. Se concluye que cuando se detectan las barreras y se trabaja en ellas se promueve el trabajo en red, la compartición de responsabilidades, la cohesión de criterios y el compromiso institucional.

Abstract Electrochemical CO2 reduction reaction in aqueous electrolytes is a promising route to produce added-value chemicals and decrease carbon emissions. However, even in Gas-Diffusion Electrode devices, low aqueous CO2 solubility limits catalysis rate and selectivity. Here, we demonstrate that when assembled over a heterogeneous electrocatalyst, a film of nitrile-modified Metal-Organic Framework (MOF) acts as a remarkable CO2-solvation layer that increases its local concentration by ~27-fold compared to bulk electrolyte, reaching 0.82 M. When mounted on a Bi catalyst in a Gas Diffusion Electrode, the MOF drastically improves CO2-to-HCOOH conversion, reaching above 90% selectivity and partial HCOOH currents of 166 mA/cm2 (at −0.9 V vs RHE). The MOF also facilitates catalysis through stabilization of reaction intermediates, as identified by operando infrared spectroscopy and Density Functional Theory. Hence, the presented strategy provides new molecular means to enhance heterogeneous electrochemical CO2 reduction reaction, leading it closer to the requirements for practical implementation.

Abstract Metal promotion could unlock high performance in zinc-zirconium catalysts, ZnZrO x , for CO2 hydrogenation to methanol. Still, with most efforts devoted to costly palladium, the optimal metal choice and necessary atomic-level architecture remain unclear. Herein, we investigate the promotion of ZnZrO x catalysts with small amounts (0.5 mol%) of diverse hydrogenation metals (Re, Co, Au, Ni, Rh, Ag, Ir, Ru, Pt, Pd, and Cu) prepared via a standardized flame spray pyrolysis approach. Cu emerges as the most effective promoter, doubling methanol productivity. Operando X-ray absorption, infrared, and electron paramagnetic resonance spectroscopic analyses and density functional theory simulations reveal that Cu0 species form Zn-rich low-nuclearity CuZn clusters on the ZrO2 surface during reaction, which correlates with the generation of oxygen vacancies in their vicinity. Mechanistic studies demonstrate that this catalytic ensemble promotes the rapid hydrogenation of intermediate formate into methanol while effectively suppressing CO production, showcasing the potential of low-nuclearity metal ensembles in CO2-based methanol synthesis.

Abstract Vaccines based on mRNA technology have revolutionized the field. In fact, lipid nanoparticles (LNP) formulated with mRNA are the preferential vaccine platform used in the fight against SARS-CoV-2 infection, with wider application against other diseases. The high demand and property right protection of the most potent cationic/ionizable lipids used for LNP formulation of COVID-19 mRNA vaccines have promoted the design of alternative nanocarriers for nucleic acid delivery. In this study we have evaluated the immunogenicity and efficacy of different rationally designed lipid and polymeric-based nanoparticle prototypes against SARS-CoV-2 infection. An mRNA coding for a trimeric soluble form of the receptor binding domain (RBD) of the spike (S) protein from SARS-CoV-2 was encapsulated using different components to form nanoemulsions (NE), nanocapsules (NC) and lipid nanoparticles (LNP). The toxicity and biological activity of these prototypes were evaluated in cultured cells after transfection and in mice following homologous prime/boost immunization. Our findings reveal good levels of RBD protein expression with most of the formulations. In C57BL/6 mice immunized intramuscularly with two doses of formulated RBD-mRNA, the modified lipid nanoparticle (mLNP) and the classical lipid nanoparticle (LNP-1) were the most effective delivery nanocarriers at inducing binding and neutralizing antibodies against SARS-CoV-2. Both prototypes fully protected susceptible K18-hACE2 transgenic mice from morbidity and mortality following a SARS-CoV-2 challenge. These results highlight that modulation of mRNAs immunogenicity can be achieved by using alternative nanocarriers and support further assessment of mLNP and LNP-1 prototypes as delivery vehicles for mRNA vaccines.

We present the first comprehensive investigation of transition metal-substituted Hydroxyapatite (TM-HAP) materials for photocatalytic CO2 reduction (CO2RR). Density functional theory (DFT) was used to study in a systematic manner the stability of 3d, 4d, 5d transition metal dopants on the HAP (000̅1) surface, analyzing their stability, activity, and selectivity for photocatalytic CO2RR. DFT results allowed to narrow down the selection to three transition metal elements (Co, Ni, Mo) based on their structural stability, band structure and performance. A selective analysis of product formation for carbon monoxide and formate was made, showing that TM dopants facilitate the initial protonation step in the CO2 reduction by adsorbing H2 molecule on TM atoms and then dissociating it into two hydrogen atoms. The performance of Ni- and Co-HAP towards the reaction activity is consistent with experimental results. Mo-HAP stands as a new and attractive photocatalyst for further investigation, given its excellent predicted performance.

BackgroundCommon Variable Immunodeficiency (CVID) represents a heterogenic group of primary immunodeficiencies (PID) characterized by impaired antibody production and susceptibility to infections. Non-infectious complications, such as autoimmune diseases, lymphoproliferative disorders, and malignancies, now significantly impact prognosis. Moreover, both hematologic and solid organ malignancies are more frequently observed in CVID patients compared to other PIDs. The risk factors for carcinogenesis in CVID remain largely unknown.ObjectiveThis multicenter study aims to characterize the clinical profile of cancer in CVID patients in Spain and to identify independent risk factors associated with malignancy development, focusing on the role of immune dysregulation.MethodsA nationwide, cross-sectional study was conducted from November 2019 to May 2022, involving 17 hospitals treating PID patients in Spain. Data were collected systematically on demographics, infectious and non-infectious comorbidities, immunological parameters, and treatment. Statistical analysis, including multivariate logistic regression, was performed to identify risk factors associated to malignancy.ResultsOf 250 CVID patients, 38 (15.26%) were diagnosed with cancer, predominantly non-Hodgkin lymphoma, gastric cancer, and lung adenocarcinoma. Cancer patients were significantly older (mean age 60.70 vs. 49.36 years, p

Background: The development of obesity-associated comorbidities such as type 2 diabetes (T2D) and hepatic steatosis has been linked to selected microRNAs in individual studies; however, an unbiased genome-wide approach to map T2D induced changes in the miRNAs landscape in human liver samples, and a subsequent robust identification and validation of target genes are still missing. Methods: Liver biopsies from age- and gender-matched obese individuals with (n=20) or without (n=20) T2D were used for microRNA microarray analysis. The candidate microRNA and target genes were validated in 85 human liver samples, and subsequently mechanistically characterized in hepatic cells as well as by dietary interventions and hepatic overexpression in mice. Results: Here, we present the human hepatic microRNA transcriptome of type 2 diabetes in liver biopsies and use a novel seed prediction tool to robustly identify microRNA target genes, which were then validated in a unique cohort of 85 human livers. Subsequent mouse studies identified a distinct signature of T2D-associated miRNAs, partly conserved in both species. Of those, human-murine miR-182–5 p was the most associated with whole-body glucose homeostasis and hepatic lipid metabolism. Its target gene LRP6 was consistently lower expressed in livers of obese T2D humans and mice as well as under conditions of miR-182–5 p overexpression. Weight loss in obese mice decreased hepatic miR-182–5 p and restored Lrp6 expression and other miR-182–5 p target genes. Hepatic overexpression of miR-182–5 p in mice rapidly decreased LRP6 protein levels and increased liver triglycerides and fasting insulin under obesogenic conditions after only seven days. Conclusions: By mapping the hepatic miRNA-transcriptome of type 2 diabetic obese subjects, validating conserved miRNAs in diet-induced mice, and establishing a novel miRNA prediction tool, we provide a robust and unique resource that will pave the way for future studies in the field. As proof of concept, we revealed that the repression of LRP6 by miR-182–5 p, which promotes lipogenesis and impairs glucose homeostasis, provides a novel mechanistic link between T2D and non-alcoholic fatty liver disease, and demonstrate in vivo that miR-182–5 p can serve as a future drug target for the treatment of obesity-driven hepatic steatosis. Funding: This work was supported by research funding from the Deutsche Forschungsgemeinschaft (KI 1887/2-1, KI 1887/2-2, KI 1887/3-1 and CRC-TR296), the European Research Council (ERC, CoG Yoyo LepReSens no. 101002247; PTP), the Helmholtz Association (Initiative and Networking Fund International Helmholtz Research School for Diabetes; MB) and the German Center for Diabetes Research (DZD Next Grant 82DZD09D1G).

The aim of this current work is to identify three different gears of cross-country skiing utilizing embedded inertial measurement units and a suitable deep learning model. The cross-country style studied was the skating style during the uphill, which involved three different gears: symmetric gear pushing with poles on both sides (G3) and two asymmetric gears pushing with poles on the right side (G2R) or to the left side (G2L). To monitor the technique, inertial measurement units (IMUs) were affixed to the skis, recording acceleration and Euler angle data during the uphill tests performed by two experienced skiers using the gears under study. The initiation and termination points of the tests were controlled via Bluetooth by a smartphone using a custom application developed with Android Studio. Data were collected on the smartphone and stored on the SD memory cards included in each IMU. Convolutional neural networks combined with long short-term memory were utilized to classify and extract spatio-temporal features. The performance of the model in cross-user evaluations demonstrated an overall accuracy of 90%, and it achieved an accuracy of 98% in the cross-scene evaluations for individual users. These results indicate a promising performance of the developed system in distinguishing between different ski gears within skating styles, providing a valuable tool to enhance ski training and analysis.

The high genetic diversity of the tomato and its high micronutrient content make this fruit very interesting from an economic and nutritional point of view. The genetic erosion suffered by this crop, due to breeding objectives based on yield and marketing, makes it necessary to return to the origins in search of the nutritional and organoleptic quality lost in traditional varieties. In this study, the agronomic, physical, organoleptic, and nutritional characteristics of eighteen F1 hybrids, obtained by crossing fourteen traditional varieties, previously selected for their quality, were studied in order to select genotypes of superior quality that could be candidates for new varieties. All the parameters studied were strongly influenced by genotype, with a wide range between varieties. Most of the experimental hybrids showed higher quality scores than the commercial hybrids used as controls, due to the extensive selection process carried out on the parents in previous work. Principal component analysis revealed the characteristics of each hybrid that distinguished it from the others. Some hybrids (H1, H2, and H4) stood out for their high concentration of active compounds, others (H14, H13, H8, H15, H7, and H9) for their agronomic performance and high β-carotene content, and H3 was the only one to contain chlorophyll in its ripe fruits. Finally, the evaluation index allowed the selection of five hybrids with interesting characteristics, combining good yield performance and high quality. The results of this work have allowed for the selection of a group of hybrids with high organoleptic and nutritional quality which will be used as parents in a breeding programme, in which their characteristics will be fixed and their resilience will be increased through the introduction of virus resistance.

This paper addresses the issue of LED short-circuit fault detection in signaling and lighting systems in the automotive industry. The conventional diagnostic method commonly implemented in newer vehicles relies on measuring the voltage drop across different LED branches and comparing it with threshold values indicating faults caused by open circuits or LED short circuits. With this algorithm, detecting cases of a few LEDs short-circuited within a branch, particularly a single malfunctioning LED, is particularly challenging. In this work, two easily implementable algorithms are proposed to address this issue within the vehicle’s control unit. One is based on a mathematical prediction model, while the other utilizes a neural network. The results obtained offer a 100% LED short-circuit fault detection rate in the majority of analyzed cases, representing a significant improvement over the conventional method, even in scenarios involving a single malfunctioning LED within a branch. Additionally, the neural network-based model can accurately predict the number of failed LEDs.