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Operational Earth observation missions, like the Sentinel-3 (S3) satellites, aim to provide imagery for long-term environmental assessment to monitor and analyze vegetation changes and dynamics. However, the S3 archive is limited in temporal availability to the year 2016. Although S3 provides continuity of previous missions, key vegetation products (VPs) including leaf area index (LAI), fraction of photosynthetically active radiation (FAPAR), fractional vegetation cover (FVC), and leaf chlorophyll content (LCC), can be reliably produced from Ocean and Land Colour Instrument (OLCI) data only since the sensors' launch. To overcome this limitation, our study proposes a reconstruction workflow that extends the data record beyond its data acquisition. By using multi-output Gaussian process regression (MOGPR) fusion, we explored guiding predictor VPs from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for the reconstruction of multi-decadal (spanning two decades, 2002–2022) temporal profiles of four OLCI-derived VPs (S3-MOGPR), moving past S3's launch. We first evaluated three MODIS-derived inputs as predictor variables: LAI, FAPAR, and the Normalised Difference Vegetation Index (NDVI) over nine sites with distinct land covers from the Ground-Based Observations for Validation (GBOV) service. Each predictor produced a distinct time series for the four reconstructed S3 VPs. To determine which predictor variable most accurately reconstructs data streams of the targeted variable, all S3-MOGPR VPs were compared to satellite-based products from the Copernicus Global Land Service (CGLS). MOGPR models were trained for 2019 and compared to reference data. Since MODIS LAI demonstrated the best reconstruction performance of all predictors, S3-MOGPR VPs were fully reconstructed from 2022 back to 2002 using guiding MODIS LAI and evaluated with in-situ data. The most consistent reconstructed product was FVC (R=0.96, NRMSE = 0.17) over mixed forests compared to CGLS estimates. FVC also yielded the highest validation statistics (R=0.93, ρ=0.92, NRMSE = 0.14) over croplands. The highest correlation coefficients were achieved by the predictor variable LAI reconstructing FVC with mean R, ρ and NRMSE = 0.11 among all sites of 0.91 and 0.88, respectively. In the absence of both satellite and ground-based LCC reference measurements, the reconstructed LCC profiles were compared to the OLCI and MERIS Terrestrial Chlorophyll Index (OTCI, MTCI). The correlation metrics provided strong evidence of the reconstructed LCC product's integrity, with the highest correlation over deciduous broadleaf, mixed forests and croplands (R>0.9). The lowest correlations for all reconstructed variables appeared over evergreen broadleaf forests, driven by the absence of seasonal patterns. Altogether, by leveraging the flexibility of the MOGPR algorithm with guiding historical data, contemporary EO data can be extrapolated into the past.

Abstract A simple technique designed to automatically identify and characterize wave structures from total electron content (TEC) data obtained from Global Navigation Satellite System (GNSS) satellites and multiple receiver stations is presented. We used 11 years of GNSS data (one complete solar cycle) to detect and characterize the traveling ionospheric disturbances (TIDs) (or wave structures) over high latitude (65°N ± 5°, 147°W ± 5°—Poker Flat, AK) and middle latitude (40°N ± 5°, 117°W ± 5°—Mt. Moses, NV) regions. The algorithm is capable of automatically detecting basic wave parameters such as wave period, horizontal phase velocity, amplitude, wave propagation direction, and wavelength. The designed algorithm can be applicable in the following areas: (a) global GNSS‐TEC (b) climatology of waves (c) input into innovative machine learning algorithms, such as ABCGAN (e.g., Valentic, 2023, https://doi.org/10.5281/zenodo.7747377 designed to characterize background ionospheric plasma and predict wave‐like high/low‐frequency perturbations) (d) anomaly detection for real‐time scenarios. Furthermore, we apply the developed wave detect and characterization technique to investigate three rockets launched on 26 and 28 January 2015. We examine the distribution of different scales of TIDs, and how they varied from high (Poker Flat) to middle (Mt. Moses) latitudes. Lastly, we show that the wave structures at the high‐latitude regions of Poker Flat are substantially affected by auroral processes and those from the middle‐latitude regions of Mt. Moses are impacted by AGWs coupling from below.

Excisable genomic islands (EGIs) are horizontally acquired genetic elements that harbor an array of genes with diverse functions. ROD21 is an EGI found integrated in the chromosome of Salmonella enterica serovar Enteritidis (Salmonella ser. Enteritidis). While this island is known to be involved in the capacity of Salmonella ser. Enteritidis to cross the epithelial barrier and colonize sterile organs, the role of most ROD21 genes remains unknown, and thus, the identification of their function is fundamental to understanding the impact of this EGI on bacterium pathogenicity. Therefore, in this study, we used a bioinformatical approach to evaluate the function of ROD21-encoded genes and delve into the characterization of SEN1990, a gene encoding a putative DNA-binding protein. We characterized the predicted structure of SEN1990, finding that this protein contains a three-stranded winged helix-turn-helix (wHTH) DNA-binding domain. Additionally, we identified homologs of SEN1990 among other members of the EARL EGIs. Furthermore, we deleted SEN1990 in Salmonella ser. Enteritidis, finding no differences in the replication or maintenance of the excised ROD21, contrary to what the previous Refseq annotation of the protein suggests. High-throughput RNA sequencing was carried out to evaluate the effect of the absence of SEN1990 on the bacterium’s global transcription. We found a downregulated expression of oafB, an SPI-17-encoded acetyltransferase involved in O-antigen modification, which was restored when the deletion mutant was complemented ectopically. Additionally, we found that strains lacking SEN1990 had a reduced capacity to colonize sterile organs in mice. Our findings suggest that SEN1990 encodes a wHTH domain-containing protein that modulates the transcription of oafB from the SPI-17, implying a crosstalk between these pathogenicity islands and a possible new role of ROD21 in the pathogenesis of Salmonella ser. Enteritidis.

We understand only a small fraction of the events happening in our brains; therefore, despite all the progress made thus far, a whole array of questions remains. Nonetheless, neurosurgeons invented new tools to circumvent the challenges that had plagued their predecessors. With the manufacturing boom of the 20th century, technological innovations blossomed enabling the neuroscientific community to study and operate upon the living brain in finer detail and with greater precision while avoiding harm to the nervous system. The purpose of this chronological review is to 1) raise awareness among future neurosurgeons about the latest advances in the field, 2) become familiar with innovations such as augmented reality (AR) that should be included in education given their ready applicability in surgical training, and 3) be comfortable with customizing these technologies to real-life cases like in the case of mixed reality.

Highlights • Different genetic levels in underrepresented FTD patients are not well understood. • We compared cognition, neuropsychiatry, and gene-atrophy overlap in FTD cases. • Mutations (MAPT-TARDBP-TREM2), variants (tau-APOE) & sporadic cases were compared. • FTD genetic level was linked to clinical & neurocognitive changes in case analysis. • Mutations showed more impairments than risk variants and sporadic presentations.

This study aimed to explore alternative substrates for growing forest species using eucalyptus bark. It evaluated the potential of extracted Eucalyptus globulus fiber bark as a substitute for commercial growing media such as coconut fiber, moss, peat, and compost pine. We determined the physicochemical parameters of the growing media, the germination rate, and the mean fresh and dry weights of seedlings. We used the Munoo-Liisa Vitality Index (MLVI) test to evaluate the phytotoxicity of the bark alone and when mixed with commercial substrates. Generally, the best mixture for seed growth was 75% extracted eucalyptus bark fiber and 25% commercial substrates. In particular, the 75E-25P (peat) mixture is a promising substitute for seedling growth of Pinus radiata, achieving up to 3-times higher MLVI than the control peat alone. For Quillaja saponaria, the best growth substrate was the 50E-50C (coconut fiber) mixture, which had the most significant MLVI values (127%). We added chitosan and alginate-encapsulated fulvic acid phytostimulants to improve the performance of the substrate mixtures. The fulvic acid, encapsulated or not, significantly improved MLVI values in Q. saponaria species and P. radiata in concentrations between 0.05 and 0.1% w/v. This study suggests that mixtures with higher levels of extracted fiber are suitable for growing forest species, thus promoting the application of circular economy principles in forestry.

Steam explosion pretreatment is suitable for bioethanol production from Eucalyptus globulus wood. Multifactorial experiment designs were used to find the optimal temperature and residence time required to obtain the best glucose yield from the enzymatic hydrolysis of pretreated materials. The chemical composition, crystallinity index, morphology and polymerization degree of the pretreated materials were correlated with enzymatic accessibility. Simultaneous saccharification and fermentation (SSF) using a fed-batch strategy was applied to three different laboratory-scale fermenters. The optimization of the pretreatment was obtained at 208 °C and 11 min. However, the enzymatic hydrolysis performance did not show significant differences from the material obtained at 196 °C and 9.5 min, which was determined to be the real optimum, owing to its lower energy requirement. The vertical fermenter with type “G” blades and the horizontal fermenter with helical blades were both highly efficient for reaching ethanol yields close to 90% based on dry wood, and ethanol concentrations close to 9.0% v/v.

The Granger Causality (GC) statistical test explores the causal relationships between different time series variables. By employing the GC method, the underlying causal links between environmental drivers and global vegetation properties can be untangled, which opens possibilities to forecast the increasing strain on ecosystems by droughts, global warming, and climate change. This study aimed to quantify the spatial distribution of four distinct satellite vegetation products’ (VPs) sensitivities to four environmental land variables (ELVs) at the global scale given the GC method. The GC analysis assessed the spatially explicit response of the VPs: (i) the fraction of absorbed photosynthetically active radiation (FAPAR), (ii) the leaf area index (LAI), (iii) solar-induced fluorescence (SIF), and, finally, (iv) the normalized difference vegetation index (NDVI) to the ELVs. These ELVs can be categorized as water availability assessing root zone soil moisture (SM) and accumulated precipitation (P), as well as, energy availability considering the effect of air temperature (T) and solar shortwave (R) radiation. The results indicate SM and P are key drivers, particularly causing changes in the LAI. SM alone accounts for 43%, while P accounts for 41%, of the explicitly caused areas over arid biomes. SM further significantly influences the LAI at northern latitudes, covering 44% of cold and 50% of polar biome areas. These areas exhibit a predominant response to R, which is a possible trigger for snowmelt, showing more than 40% caused by both cold and polar biomes for all VPs. Finally, T’s causality is evenly distributed amongst all biomes with fractional covers between ∼10 and 20%. By using the GC method, the analysis presents a novel way to monitor the planet’s ecosystem, based on solely two years as input data, with four VPs acquired by the synergy of Sentinel-3 (S3) and 5P (S5P) satellite data streams. The findings indicated unique, biome-specific responses of vegetation to distinct environmental drivers.

Global mapping of essential vegetation traits (EVTs) through data acquired by Earth-observing satellites provides a spatially explicit way to analyze the current vegetation states and dynamics of our planet. Although significant efforts have been made, there is still a lack of global and consistently derived multi-temporal trait maps that are cloud-free. Here we present the processing chain for the spatiotemporally continuous production of four EVTs at a global scale: (1) fraction of absorbed photosynthetically active radiation (FAPAR), (2) leaf area index (LAI), (3) fractional vegetation cover (FVC), and (4) leaf chlorophyll content (LCC). The proposed workflow presents a scalable processing approach to the global cloud-free mapping of the EVTs. Hybrid retrieval models, named S3-TOA-GPR-1.0-WS, were implemented into Google Earth Engine (GEE) using Sentinel-3 Ocean and Land Color Instrument (OLCI) Level-1B for the mapping of the four EVTs along with associated uncertainty estimates. We used the Whittaker smoother (WS) for the temporal reconstruction of the four EVTs, which led to continuous data streams, here applied to the year 2019. Cloud-free maps were produced at 5 km spatial resolution at 10-day time intervals. The consistency and plausibility of the EVT estimates for the resulting annual profiles were evaluated by per-pixel intra-annually correlating against corresponding vegetation products of both MODIS and Copernicus Global Land Service (CGLS). The most consistent results were obtained for LAI, which showed intra-annual correlations with an average Pearson correlation coefficient (R) of 0.57 against the CGLS LAI product. Globally, the EVT products showed consistent results, specifically obtaining higher correlation than R> 0.5 with reference products between 30 and 60° latitude in the Northern Hemisphere. Additionally, intra-annual goodness-of-fit statistics were also calculated locally against reference products over four distinct vegetated land covers. As a general trend, vegetated land covers with pronounced phenological dynamics led to high correlations between the different products. However, sparsely vegetated fields as well as areas near the equator linked to smaller seasonality led to lower correlations. We conclude that the global gap-free mapping of the four EVTs was overall consistent. Thanks to GEE, the entire OLCI L1B catalogue can be processed efficiently into the EVT products on a global scale and made cloud-free with the WS temporal reconstruction method. Additionally, GEE facilitates the workflow to be operationally applicable and easily accessible to the broader community.

Abstract Electron heat flux is an important value for ionospheric space weather modeling networks. Utilizing the 2D array of Time History of Events and Macroscale Interactions during Substorms all‐sky‐imager (ASI) observations, Gabrielse et al. (2021, https://doi.org/10.3389/fphy.2021.744298) described a new method that estimates the auroral scale sizes of intense precipitating electron energy fluxes and their mean energies during two substorms on 16 February 2010. These parameters in combination with SuperThermal Electron Transport code were used to develop a new methodology to calculate electron thermal fluxes from data inputs in 2D during one of the substorms at 09:40:00 UT across Canada and Alaska. To test the effect of various precipitation lifetimes on electron heat flux values, boxcar averages ranging from 0 to 900 s were applied to the ASI data. These data are then combined with the newly developed kinetic simulation to determine the thermal fluxes associated with the observed diffuse and discrete precipitation.

In the last decades big data has facilitating and improving our daily duties in the medical research and clinical fields; the strategy to get to this point is understanding how to organize and analyze the data in order to accomplish the final goal that is improving healthcare system, in terms of cost and benefits, quality of life and outcome patient. The main objective of this review is to illustrate the state-of-art of big data in healthcare, its features and architecture. We also would like to demonstrate the different application and principal mechanisms of big data in the latest technologies known as blockchain and artificial intelligence, recognizing their benefits and limitations. Perhaps, medical education and digital anatomy are unexplored fields that might be profitable to investigate as we are proposing. The healthcare system can be revolutionized using these different technologies. Thus, we are explaining the basis of these systems focused to the medical arena in order to encourage medical doctors, nurses, biotechnologies and other healthcare professions to be involved and create a more efficient and efficacy system.

Nowadays, Unmanned Aerial Vehicles (UAVs) have become the preferred, and sometimes the only support tool when facing critical scenarios such as earthquakes, search and rescue missions, and border surveillance. In these scenarios, deploying a UAV swarm instead of a single UAV can provide additional benefits when, for example, cargo carrying requirements exceed the lifting power of a single UAV, or when the deployment of several UAVs simultaneously can accelerate the accomplishment of the mission, and broaden the covered area. To this aim, in this paper we present MUSCOP, a protocol that allows multiple UAVs to perfectly coordinate their flight when performing planned missions. Experimental results show that the proposed protocol is able to achieve a high degree of swarm cohesion independently of the swarm formation adopted, and even in the presence of very lossy channels, achieving minimal synchronization delays and very low position offsets with regard to the ideal case.

Dengue transmission is determined by a complex set of interactions between the environment, Aedes aegypti mosquitoes, dengue viruses, and humans. Emergence in new geographic areas can be unpredictable, with some regions having established mosquito populations for decades without locally acquired transmission. Key factors such as mosquito longevity, temperature-driven extrinsic incubation period (EIP), and vector–human contact can strongly influence the potential for disease transmission. To assess how these factors interact at the edge of the geographical range of dengue virus transmission, we conducted mosquito sampling in multiple urban areas located throughout the Arizona–Sonora desert region during the summer rainy seasons from 2013 to 2015. Mosquito population age structure, reflecting mosquito survivorship, was measured using a combination of parity analysis and relative gene expression of an age-related gene, SCP-1. Bloodmeal analysis was conducted on field collected blood-fed mosquitoes. Site-specific temperature was used to estimate the EIP, and this predicted EIP combined with mosquito age were combined to estimate the abundance of “potential” vectors (i.e., mosquitoes old enough to survive the EIP). Comparisons were made across cities by month and year. The dengue endemic cities Hermosillo and Ciudad Obregon, both in the state of Sonora, Mexico, had higher abundance of potential vectors than non-endemic Nogales, Sonora, Mexico. Interestingly, Tucson, Arizona consistently had a higher estimated abundance of potential vectors than dengue endemic regions of Sonora, Mexico. There were no observed city-level differences in species composition of blood meals. Combined, these data offer insights into the critical factors required for dengue transmission at the ecological edge of the mosquito’s range. However, further research is needed to integrate an understanding of how social and additional environmental factors constrain and enhance dengue transmission in emerging regions.

Optical Earth Observation is often limited by weather conditions such as cloudiness. Radar sensors have the potential to overcome these limitations, however, due to the complex radar-surface interaction, the retrieving of crop biophysical variables using this technology remains an open challenge. Aiming to simultaneously benefit from the optical domain background and the all-weather imagery provided by radar systems, we propose a data fusion approach focused on the cross-correlation between radar and optical data streams. To do so, we analyzed several multiple-output Gaussian processes (MOGP) models and their ability to fuse efficiently Sentinel-1 (S1) Radar Vegetation Index (RVI) and Sentinel-2 (S2) vegetation water content (VWC) time series over a dry agri-environment in southern Argentina. MOGP models not only exploit the auto-correlations of S1 and S2 data streams independently but also the inter-channel cross-correlations. The S1 RVI and S2 VWC time series at the selected study sites being the inputs of the MOGP models proved to be closely correlated. Regarding the set of assessed models, the Convolutional Gaussian model (CONV) delivered noteworthy accurate data fusion results over winter wheat croplands belonging to the 2020 and 2021 campaigns (NRMSEwheat2020 = 16.1%; NRMSEwheat2021 = 10.1%). Posteriorly, we removed S2 observations from the S1 & S2 dataset corresponding to the complete phenological cycles of winter wheat from September to the end of December to simulate the presence of clouds in the scenes and applied the CONV model at the pixel level to reconstruct spatiotemporally-latent VWC maps. After applying the fusion strategy, the phenology of winter wheat was successfully recovered in the absence of optical data. Strong correlations were obtained between S2 VWC and S1 & S2 MOGP VWC reconstructed maps for the assessment dates (R2¯wheat−2020 = 0.95, R2¯wheat−2021 = 0.96). Altogether, the fusion of S1 SAR and S2 optical EO data streams with MOGP offers a powerful innovative approach for cropland trait monitoring over cloudy high-latitude regions.

Abstract Introduction Timely diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging because it depends on clinical expertise and potentially ambiguous diagnostic guidelines. Recent recommendations highlight the role of multimodal neuroimaging and machine learning methods as complementary tools to address this problem. Methods We developed an automatic, cross‐center, multimodal computational approach for robust classification of patients with bvFTD and healthy controls. We analyzed structural magnetic resonance imaging and resting‐state functional connectivity from 44 patients with bvFTD and 60 healthy controls (across three imaging centers with different acquisition protocols) using a fully automated processing pipeline, including site normalization, native space feature extraction, and a random forest classifier. Results Our method successfully combined multimodal imaging information with high accuracy (91%), sensitivity (83.7%), and specificity (96.6%). Discussion This multimodal approach enhanced the system's performance and provided a clinically informative method for neuroimaging analysis. This underscores the relevance of combining multimodal imaging and machine learning as a gold standard for dementia diagnosis.

Gait generation for legged robots is a challenging task typically requiring either a hand-tuning design or a kinematic model of the robot morphology to compute the movements, generating a high computational and time efforts. Neuroevolution algorithms with the ability to learn network topologies, such as Neuroevolution of Augmenting Topologies (NEAT), Hypercube-based NEAT (HyperNEAT), and τ-HyperNEAT, have been used in the computational community to learn gaits in legged robots. An extended version of HyperNEAT called ES-HyperNEAT, where the substrate hosting the nodes of the neural network evolves in shape, seems to be a promising algorithm to evaluate gait learning tasks. Using two four-legged robot platforms with different degrees of freedom (Quadratot and ARGOv2), we compared the performance of a variety of neuroevolution algorithms based on HyperNEAT for learning gaits. The comparative analysis of the results reveals that the three evaluated algorithms, HyperNEAT, τ-HyperNEAT and ES-HyperNEAT, successfully generate gaits given a fitness function. In particular, for the Quadratot platform, ES-HyperNEAT learns faster and better than the other two methods, a result that is not observed in the ArgoV2. Additionally, ES-HyperNEAT produces more phase changes between joints movement, resulting in more natural robot movements. Finally, ES-HyperNEAT produces complex substrates from simple Compositional Pattern Producing Networks, CPPN-NEAT, allowing the simplification of the underlying neural network.

Objetivo. Los juicios morales se basan en decisiones que toman en cuenta la representación de las normas y la ley, los valores, la funcionalidad y la situación en sí. La moral se ha estudiado con "dilemas morales hipotéticos" para identificar el tipo de resultado y el proceso detrás del razonamiento moral. No obstante, los juicios en sí mismos no son suficientes para establecer diferencias en el tipo de resolución o la relación con otros procesos cognitivos. Por lo anterior, el presente estudio buscó comparar el desempeño en tareas de maximización de la utilidad, control cognitivo y juicios morales, teniendo en cuenta el sexo y otras variables sociodemográficas. Método. Participaron 73 estudiantes universitarios (50 mujeres, 20 hombres y 3 con sexo no reportado, la edad promedio fue 19.53 años (DE = 1.68 años). El Iowa Gambling Task (IGT) se utilizó para identificar comportamientos de maximización de la utilidad. Además, el estudio empleó la prueba de cambios de tarea y la aplicación web Máquina Moral. Resultados. Se encontró una diferencia entre las variables de IGT, sin observar diferencias en la prueba de cambios de tarea. Conclusión. En cuanto al juicio moral, los hombres dieron más valor al cumplimiento de normas que las mujeres. Algunas variables de la tarea IGT apoyan las diferencias entre los sexos. Los resultados son congruentes con las diferencias mostradas por la literatura.

Abstract Eucalyptus globulus is the second most important economic forest species in Chile. Its main use is in the kraft pulp industry, where large amounts of bark waste are generated. Due to its fibrous characteristics, E. globulus bark is proposed as an alternative source of fibres for papermaking. This study focuses on obtaining fibres for liner paper manufacture. A neutral sulphite semi-chemical (NSSC) process was performed, varying the sodium sulphite (5% to 16%) and the sodium carbonate (2% and 4%) concentrations using two reaction temperatures (160°C and 170°C). The NSSC process at 170°C, 16% of sulphite, and 2% of sodium carbonate proved to be the best condition to obtain higher mechanical performance of papers. As the pulping conditions become more drastic, the yield drops, and the physicomechanical properties of paper increases. Results showed that pulps from E. globulus bark could turn into source of fibres for papermaking and other related products.

From molecular mechanisms to global brain networks, atypical fluctuations are the hallmark of neurodegeneration. Yet, traditional fMRI research on resting-state networks (RSNs) has favored static and average connectivity methods, which by overlooking the fluctuation dynamics triggered by neurodegeneration, have yielded inconsistent results. The present multicenter study introduces a data-driven machine learning pipeline based on dynamic connectivity fluctuation analysis (DCFA) on RS-fMRI data from 300 participants belonging to three groups: behavioral variant frontotemporal dementia (bvFTD) patients, Alzheimer's disease (AD) patients, and healthy controls. We considered non-linear oscillatory patterns across combined and individual resting-state networks (RSNs), namely: the salience network (SN), mostly affected in bvFTD; the default mode network (DMN), mostly affected in AD; the executive network (EN), partially compromised in both conditions; the motor network (MN); and the visual network (VN). These RSNs were entered as features for dementia classification using a recent robust machine learning approach (a Bayesian hyperparameter tuned Gradient Boosting Machines (GBM) algorithm), across four independent datasets with different MR scanners and recording parameters. The machine learning classification accuracy analysis revealed a systematic and unique tailored architecture of RSN disruption. The classification accuracy ranking showed that the most affected networks for bvFTD were the SN + EN network pair (mean accuracy = 86.43%, AUC = 0.91, sensitivity = 86.45%, specificity = 87.54%); for AD, the DMN + EN network pair (mean accuracy = 86.63%, AUC = 0.89, sensitivity = 88.37%, specificity = 84.62%); and for the bvFTD vs. AD classification, the DMN + SN network pair (mean accuracy = 82.67%, AUC = 0.86, sensitivity = 81.27%, specificity = 83.01%). Moreover, the DFCA classification systematically outperformed canonical connectivity approaches (including both static and linear dynamic connectivity). Our findings suggest that non-linear dynamical fluctuations surpass two traditional seed-based functional connectivity approaches and provide a pathophysiological characterization of global brain networks in neurodegenerative conditions (AD and bvFTD) across multicenter data.

Desde la década de 1970, la disponibilidad de neuroimágenes estructurales (tomografia computarizada y resonancia magnética) y funcionales como la tomografía computarizada por emisión de fotón único (SPECT), la tomografia por emisión de positrones (PET) o la resonancia magnética funcional (fMRI)), abrió una nueva via en el estudio de la relación bidireccional que existe entre los fenómenos comportamentales y la actividad neuronal. La introducción de estas técnicas condujo a una mejor comprensión del impacto de una lesión cerebral en la actividad cortical y en el desarrollo de síntomas psiquiátricos. Explicar la presencia de síntomas afectivos como una alteración en la función de una estructura cerebral es insuficiente, y se debe considerar siempre un compromiso de los circuitos cerebrales. Muchos trastornos del afecto se han asociado con lesiones en las conexiones talamolímbicas, incluyendo trastorno depresivo mayor, trastorno obsesivo-compulsivo, adicción a sustancias psicoactivas y trastorno de estrés postraumático, por lo que la identificación de los tractos de conectividad puede proporcionar nuevos medios para una intervención terapéutica eficaz.

Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional measures and increase diagnostic confidence. Yet, widespread application of these tools cannot be recommended unless they are proven to perform consistently and reproducibly across samples from different countries. We implemented machine-learning algorithms to evaluate the prediction power of neurocognitive biomarkers (behavioral and imaging measures) for classifying two neurodegenerative conditions –Alzheimer Disease (AD) and behavioral variant frontotemporal dementia (bvFTD)– across three different countries (>200 participants). We use machine-learning tools integrating multimodal measures such as cognitive scores (executive functions and cognitive screening) and brain atrophy volume (voxel based morphometry from fronto-temporo-insular regions in bvFTD, and temporo-parietal regions in AD) to identify the most relevant features in predicting the incidence of the diseases. In the Country-1 cohort, predictions of AD and bvFTD became maximally improved upon inclusion of cognitive screenings outcomes combined with atrophy levels. Multimodal training data from this cohort allowed predicting both AD and bvFTD in the other two novel datasets from other countries with high accuracy (>90%), demonstrating the robustness of the approach as well as the differential specificity and reliability of behavioral and neural markers for each condition. In sum, this is the first study, across centers and countries, to validate the predictive power of cognitive signatures combined with atrophy levels for contrastive neurodegenerative conditions, validating a benchmark for future assessments of reliability and reproducibility.

Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3 (S3) imagery. The traits included leaf chlorophyll content (LCC), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and fractional vegetation cover (FVC), being fundamental for assessing photosynthetic activity on Earth. The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SCOPE and the atmospheric RTM 6SV. The retrieval models, named to S3-TOA-GPR-1.0, were directly implemented in Google Earth Engine (GEE) to enable the quantification of the traits from TOA data as acquired from the S3 Ocean and Land Colour Instrument (OLCI) sensor. Following good to high theoretical validation results with normalized root mean square error (NRMSE) ranging from 5% (FAPAR) to 19% (LAI), a three fold evaluation approach over diverse sites and land cover types was pursued: (1) temporal comparison against LAI and FAPAR products obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) for the time window 2016–2020, (2) spatial difference mapping with Copernicus Global Land Service (CGLS) estimates, and (3) direct validation using interpolated in situ data from the VALERI network. For all three approaches, promising results were achieved. Selected sites demonstrated coherent seasonal patterns compared to LAI and FAPAR MODIS products, with differences between spatially averaged temporal patterns of only 6.59%. In respect of the spatial mapping comparison, estimates provided by the S3-TOA-GPR-1.0 models indicated highest consistency with FVC and FAPAR CGLS products. Moreover, the direct validation of our S3-TOA-GPR-1.0 models against VALERI estimates indicated good retrieval performance for LAI, FAPAR and FVC. We conclude that our retrieval workflow of spatiotemporal S3 TOA data processing into GEE opens the path towards global monitoring of fundamental vegetation traits, accessible to the whole research community.

Background/AIMS: Osteoarthritis (OA), the commonest joint disorder, is a leading cause of disability. Symptomatic slow-acting drugs for OA (SYSADOA), particularly glucosamine plus chondroitin sulphate (GS/CS), are effective for symptom relief, protect joint cartilage and delay OA progression, with a good safety profile. D-002, a mixture of beeswax alcohols that inhibits both cyclooxygenase and 5-lipoxygenase activities, has been effective in experimental and clinical OA studies, showing also a chondroprotective effect.OBJECTIVES: To compare the effects of D-002 and GS/SC administered for 12 weeks on OA symptoms.METHODS: Participants were randomized to GS/CS (375/300 mg) or 50?mg D-002 once daily for 12 weeks. Symptoms were assessed by the Western Ontario and McMaster Individual Osteoarthritis Index (WOMAC) and the visual analogy scale (VAS) scores. The primary outcome was the reduction of the total WOMAC score. Secondary outcomes included WOMAC pain, stiffness and function scores, VAS score and rescue medication consumption.RESULTS: Of 60 randomized patients, 59 completed the study. D-002 and GS/SC reduced significantly total WOMAC score (72.1% and 78.5%, respectively), and pain, joint stiffness and physical function scores versus baseline. VAS scores decreased significantly with D-002 (76.6%) and GS/SC (76.8%). The reductions, significant from the second week, were enhanced over the trial. Rescue medications were consumed by 3/30 D-002 and 4/30 GS/SC patients. No differences between groups were found. Treatments were well tolerated.CONCLUSIONS: D-002 (50 mg/day) administered for 12 weeks was safe and comparable to GS/SC for alleviating OA symptoms (pain, stiffness, and functional limitation) (RPCEC00000180).

Background: To study the extent to which neuropsychiatric symptoms (NPS) influence the cognitive and functional decline in frontotemporal degeneration (FTD) and Alzheimer’s disease (AD).Methods: We assessed the progression of NPS and their influence on cognitive and functional progression in a group of FTD (n = 36) and AD patients (n = 47) at two different stages of the disease (2.5 years). A standardized scale was used to assess NPS—the Columbia University Scale for Psychopathology in Alzheimer’s Disease (CUSPAD)—which tracks different symptoms including depression, psychotic symptoms, as well as sleep and conduct problems. In addition, in a subsample of patients (AD n = 14 and FTD n = 14), we analyzed another group of NPS by using the Neuropsychiatric Inventory (NPI). Cognitive declines were tracked by using the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), while functionality was tracked by using the Lawton scale and the Barthel Index.Results: The presence of NPS impacts cognitive and functional decline in both groups of patients 2.5 years after disease onset. However, we observed a dissociable profile of the affectation of NPS in each group. In the AD group, results indicate that the progression of depressive symptoms and sleep problems predict cognitive and functional decline. In contrast, the progression of a mixed group of NPS, including conduct problems and delusions, predicts cognitive and functional decline in FTD.Conclusion: The presence of NPS has a critical impact on the prediction of cognitive decline in FTD and AD patients after 2.5 years of disease progression. Our results demonstrate the importance of assessing different types of NPS in neurodegenerative disorders which, in turn, predict disease progression. Future studies should assess the role of NPS in predicting different neurocognitive pathways and in neurodegeneration.

JMJD6 is a member of the Jumonji C domain containing enzymes that demethylate and/or hydroxylate substrate proteins. It is a multi-functional protein that has been implicated in disparate aspects of transcriptional and post-transcriptional control of gene expression, including but not limited to enhancer and promoter binding, release of paused RNA polymerase II, control of splicing, and interaction with the translation machinery. JMJD6 contributes to multiple aspects of animal development, including adipogenesis modeled in culture. We mutated proposed or characterized domains in the JMJD6 protein to better understand the requirement for JMJD6 in adipogenic differentiation. Mutation of JMJD6 amino acids that mediate binding of iron and 2-oxogluterate, which are required cofactors for enzymatic activity, had no impact on JMJD6 function, showing that catalytic activity is not required for JMJD6 contributions to adipogenic differentiation. In addition, we documented the formation of JMJD6 oligomers and showed that catalytic activity is not required for oligomerization, as has been reported previously. We also observed no effect of mutations in the sumoylation site and in the poly-serine stretch. In contrast, mutation of the AT hook-like structure, which mediates interaction with DNA and/or RNA, compromised JMJD6 function by blocking its ability to interact with chromatin at genes that express regulators of adipogenesis. The ability of JMJD6 to interact with nucleic acids may be a critical requirement for its function in adipogenic differentiation. The requirement for the AT hook-like domain and the lack of requirement for catalytic activity giving rise to the idea that co-activation of transcription by JMJD6 may be functioning as a scaffold protein that supports the interactions of other critical regulators.

IntroductionUric acid has gained considerable attention as a potential neuroprotective agent in stroke during the last decades, however, its role in the pathophysiology of ischemic stroke remains poorly understood. A serial evaluation of uric acid levels during the acute phase of stroke and its association with infarct size on magnetic resonance imaging is lacking.MethodsWe present a cohort study of 31 patients with ischemic stroke who were not candidates for thrombolysis according to current criteria at the time. We performed daily measurements of serum uric acid and total antioxidant capacity of plasma during the first week after symptoms onset and 30 days after. Infarct size was determined in the acute phase by a DWI sequence and the final infarct size with a control MRI (FLAIR) at day 30.ResultsUric acid significantly decreases between days 2 to 6 compared to day 1, after adjustment by sex, age and DWI at diagnosis, with a nadir value at 72h. A mixed model analysis showed a negative association between DWI at diagnosis and uric acid evolution during the first week after stroke. Moreover, multivariable linear regression of uric acid values during follow up on DWI volumes demonstrated that DWI volume at diagnosis is negatively associated with uric acid levels at day 3 and 4. There were no significant associations between total antioxidant capacity of plasma and DWI at diagnosis, or FLAIR at any point.DiscussionPatients with larger infarcts exhibited a significant decrease in serum uric acid levels, accounting for a more prominent reactive oxygen species scavenging activity with subsequent consumption and decay of this antioxidant. The different kinetics of total antioxidant capacity of plasma and serum uric acid levels suggests a specific role of uric acid in the antioxidant response in ischemic stroke.

The objective of this study was to investigate structural changes and lignin redistribution in Eucalyptus globulus pre-treated by steam explosion under different degrees of severity (S0), in order to evaluate their effect on cellulose accessibility by enzymatic hydrolysis. Approximately 87.7% to 98.5% of original glucans were retained in the pre-treated material. Glucose yields after the enzymatic hydrolysis of pre-treated material improved from 19.4% to 85.1% when S0 was increased from 8.53 to 10.42. One of the main reasons for the increase in glucose yield was the redistribution of lignin as micro-particles were deposited on the surface and interior of the fibre cell wall. This information was confirmed by laser scanning confocal fluorescence and FT-IR imaging; these microscopic techniques show changes in the physical and chemical characteristics of pre-treated fibres. In addition, the results allowed the construction of an explanatory model for microscale understanding of the enzymatic accessibility mechanism in the pre-treated lignocellulose.

Conditions to increase phenolic hydroxyl groups (OH-Phe) in organosolv lignin using alkaline catalysts (NaOH and KOH) were optimized with the purpose of increasing the reactivity of lignin and to evaluate the effect on the structure of the newly generated compounds as a result of the base-catalyzed depolymerization (BCD). The lignin-derived compounds could be used for the synthesis of bio-based polymers and nanomaterials. The maximal yield of OH-Phe reached values of 5270 and 3970 μmol per gram of lignin when NaOH (8.6%, 173 °C, and 33 min) and KOH (11.7%, 174 °C, and 58 min), defined as optimal conditions for BCD, were used, respectively, while for the control lignin, OH-Phe was 2830 μmol per gram of lignin. The molecular weight (Mw) and glass transition temperature (Tg) for lignin-NaOH were lower than those of lignin-KOH and lignin-control. Both lignin derivatives had greater thermal stability at high temperatures than lignin-control. In conclusion, the results showed higher modifications in the structure of lignin as a result of the oxidation process, primarily by cleavage of the β-O-4 ether bond and variations in thermochemical properties when NaOH is used as alkaline catalyst.

Kraft pulp cellulose was hydrolyzed using sulfuric acid, under different thermophysical conditions of temperature, time, pulp concentration, and sonication time. The experimental design revealed the effect of these conditions and their interaction on the hydrolysis yield obtained. In addition, the top five cellulose nanocrystals (CNCs) yields from this experiment design were analyzed. The results obtained indicated that CNCs possess a morphology that can be described as individualized rod particles, with average diameters less than 50 nm and different size distribution. In the analysis of CNCs features, significant Pearson correlations were established between the crystallinity of the CNC, CNC yield, and interplanar crystallites distance (Δd/d). The thermogravimetric (DTG) profiles exhibited two CNCs degradation stages, where the second stage CNCs degradation showed a significative correlation with CNC sulfur content. In our analysis, the crystallographic parameters exhibited a correlation with the mechanical behavior of the CNC, since the potential variation between the distances of the crystalline planes is related to the stress and deformation present in the crystallites of CNCs. This study provides new knowledge regarding CNCs, further enhancing information for CNC-based industries and the processability of CNCs for the development of new materials.

Myogenesis is the biological process by which skeletal muscle tissue forms. Regulation of myogenesis involves a variety of conventional, epigenetic, and epigenomic mechanisms that control chromatin remodeling, DNA methylation, histone modification, and activation of transcription factors. Chromatin remodeling enzymes utilize ATP hydrolysis to alter nucleosome structure and/or positioning. The mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) family of chromatin remodeling enzymes is essential for myogenesis. Here we review diverse and novel mechanisms of regulation of mSWI/SNF enzymes by kinases and phosphatases. The integration of classic signaling pathways with chromatin remodeling enzyme function impacts myoblast viability and proliferation as well as differentiation. Regulated processes include the assembly of the mSWI/SNF enzyme complex, choice of subunits to be incorporated into the complex, and sub-nuclear localization of enzyme subunits. Together these processes influence the chromatin remodeling and gene expression events that control myoblast function and the induction of tissue-specific genes during differentiation.

In the last decade there has been an increase in the use of medical devices in the home environment. These devices are commonly the same as those used in hospitals by healthcare professionals. The use of these these devices by lay users outside of a clinical environment may become unsafe. This study presents a methodology that allows decision makers to identify potential risk situations that may arise when lay users operate healthcare medical devices at home. Through a usability study based on the Grounded Theory methodology, we create a conceptual model in which we identified problems and errors related to the use of a multi-parameter monitor in a home environment by a group of lay users. The conceptual model is reified as a graphical representation, which allows stakeholders to identify (i) the weaknesses of the device, (ii) unsafe operation modes, and (iii) the most suitable device for a specific user.

The combination of hemicellulose pre-hydrolysis by dilute acid or steam-explosion followed by kraft pulping was one approach evaluated in this work to generate pulps from radiata pine wood chips amenable to saccharification by enzymatic hydrolysis. Dilute acid (combined severity factor, CS = 1.67) and steam explosion (severity factor, log Ro = 4.09) treatments were able to solubilize approximately 53% and 63% of the original hemicelluloses content in wood, respectively. Extracted wood chips were subjected to kraft cooking (170 °C, 16-18% active alkali, 30% sulfidity and 1200 H-factor) to produce pulps that were further saccharified by cellulases. Lignin removal increased with increasing active alkali, affording delignification levels 28% for dilute acid and 68% for steam explosion extraction pretreatment pulps. Enzymatic digestibility of P. radiata pulps were low, and only samples pretreated by steam explosion reached glucan-to-glucose conversion near to 75%; this treatment was 31% and 37% higher than that obtained with wood chips that were pretreated by dilute acid extraction.

Extraction of hemicelluloses prior to pulping and conversion of the extracted hemicelluloses to other bioproducts could provide additional revenue to traditional pulp and paper industries. The effect of hemicelluloses pre-extraction with a hydrothermal (HT) process on Pinus radiata chemimechanical pulp (CMP) properties was investigated in this study. The HT extraction resulted in a release of 7% to 58% of the initial amount of hemicelluloses from the wood. The extraction yield increased with temperature and extraction time. This hemicellulosic fraction was in the form of low molar mass oligomers with molecular weights varying from 1.5 to 100 kDa. Compared with the control (unextracted) CMP pulp, the HT pre-extraction significantly reduced the refining energy to obtain a given fibrillation degree (freeness). The pulp yield with the HT/CMP process was in the range of 56% to 75%. Fiber properties of the pulps from pre-extracted wood, such as fiber length, were reduced, while increases in fiber width, fines content, fiber coarseness, and kink index were observed in comparison with the control pulps. The strength properties of CMP pulps decreased with increasing amounts of hemicellulose removal during the stage prior to pulping.

As galactoglucomananas são as principais frações de hemiceluloses presentes nas madeiras moles e contêm, principalmente, as hexoses galactose, glicose e manose. O isolamento eficiente e seletivo dessas hemiceluloses é um obstáculo crítico a superar para sua utilização. Os objetivos deste trabalho foram extrair e caracterizar soluções aquosas ácidas e neutras de hemiceluloses de cavacos de madeira de Pinus radiata, bem como avaliar sua viabilidade para a produção de bioetanol. As hemiceluloses em P. radiata representam 26 g/100 g de madeira (base seca), e as hexoses são responsáveis por aproximadamente 64% dessa quantidade. De acordo com as diferentes condições de extração, cerca de 50% da fração hemicelulósica foi solubilizada e recuperada depois de uma precipitação com etanol. As frações recuperadas de hemiceluloses estavam na forma de oligômeros com peso molecular médio (Mw) variando entre 4x10³ e 4x10(5) g/mol. Os oligômeros hemicelulósicos foram hidrolisados com ácido sulfúrico diluído e os hidrolisados concentrados até aproximadamente 70 g/L hexosas e fermentados pela levedura Saccharomyces cerevisiae. Os resultados de fermentação indicaram que os açúcares obtidos dos extratos ácidos e neutros foram fermentados com rendimentos máximos de etanol de 63% e 54% (22 g/L e 19 g/L), respectivamente. A conversão de hemiceluloses da madeira em etanol é viável, porém seu baixo rendimento faz que o processo não seja economicamente atrativo, razão por que melhorias no processo ou usos alternativos das hemiceluloses devem ser avaliados.Galactoglucomannans are the major hemicellulosic fraction present in softwoods, and is mainly composed by the hexoses: galactose, glucose and mannose. The efficient and selective isolation of these hemicelluloses is regarded as one of the most critical obstacles to overcome for their utilization. The objective of the current work was to extract and characterize acidic and neutral aqueous solutions of hemicelluloses from Pinus radiata wood chips and investigate their feasibility for bioethanol production. Hemicelluloses in P. radiata represented 26 g/100 g wood (o.d.w.) and hexoses are responsible for approximately 64% of this amount. According to the different extraction conditions, approximately 50% of the hemicellulosic fraction was solubilized and recovered after precipitation with ethanol. The recovered hemicellulosic fractions were in the form of oligomers with weight-average molecular weigth (Mw) varying from 4x10³ to 4x10(5) g/mol. Hemicellulosic oligomers were hydrolyzed with dilute sulfuric acid and the hydrolysates concentrated until approximately 70 g/L of hexoses and fermented by Saccharomyces cerevisiae yeast. Fermentation results showed that sugar obtained from acid and neutral extractions were fermented to ethanol with maximum yields of 63% and 54% (22 g/ L and 19 g/L), respectively. The conversion of wood hemicellulosic substrates to ethanol is feasible but the low ethanol yields obtained make the process not economically attractive and optimization of the process or alternatives uses for hemicelluloses should be evaluated.

Se estudió un ejemplar de Centrolophus niger (Gmelin, 1789) (Perciformes: Centrolophidae), capturado como fauna acompañante en faenas de pesca de ``besugo'' Epigonus crassicaudus de Buen, 1959 el 14 de octubre del año 2003 frente a la provincia de Valdivia (39º04'S; 73º57'W) a una profundidad de 400 m, mediante pesca de arrastre de media agua. Este constituye el primer registro para la especie en aguas del talud continental chileno situadas sobre la Placa Sudamericana.A specimen of Centrolophus niger (Gmelin, 1789) (Perciformes: Centrolophidae), caught as by catch of the ``chilean cardenalfish'' Epigonus crassicaudus de Buen 1959, was studied. The specimen was caught on October 14, 2003, on the continental slope just off shore Valdivia Province (39º04'S;73º57'W), at 400 m deep, through midwater trawler fishing. This one is the southernmost record of this genus and species, being simultaneously the first record in Chilean continental slope waters of South American Plate, and the second record for the Chilean ichthyofauna

The finding of three specimens of Nessorhamphus ingolfianus (Schmidt 1912), obtained in front of Valdivia (39º 44'S; 70º 39'W) is reported. This proves to be the first record of this species for the Southeastern Pacific and for the Chilean ichthyofauna.

Plekhm1 is a large, multi-modular, adapter protein implicated in osteoclast vesicle trafficking and bone resorption. In patients, inactivating mutations cause osteopetrosis, and gain-of-function mutations cause osteopenia. Investigations of potential Plekhm1 interaction partners by mass spectrometry identified TRAFD1 (FLN29), a protein previously shown to suppress toll-like receptor signaling in monocytes/macrophages, thereby dampening inflammatory responses to innate immunity. We mapped the binding domains to the TRAFD1 zinc finger (aa 37-60), and to the region of Plekhm1 between its second pleckstrin homology domain and its C1 domain (aa 784-986). RANKL slightly increased TRAFD1 levels, particularly in primary osteoclasts, and the co-localization of TRAFD1 with Plekhm1 also increased with RANKL treatment. Stable knockdown of TRAFD1 in RAW 264.7 cells inhibited resorption activity proportionally to the degree of knockdown, and inhibited acidification. The lack of acidification occurred despite the presence of osteoclast acidification factors including carbonic anhydrase II, a3-V-ATPase, and the ClC7 chloride channel. Secretion of TRAP and cathepsin K were also markedly inhibited in knockdown cells. Truncated Plekhm1 in ia/ia osteopetrotic rat cells prevented vesicle localization of Plekhm1 and TRAFD1. We conclude that TRAFD1, in association with Plekhm1/Rab7-positive late endosomes-early lysosomes, has a previously unknown role in vesicle trafficking, acidification, and resorption in osteoclasts.

The fusion of monocyte/macrophage lineage cells into fully active, multinucleated, bone resorbing osteoclasts is a complex cell biological phenomenon that utilizes specialized proteins. OC-STAMP, a multi-pass transmembrane protein, has been shown to be required for pre-osteoclast fusion and for optimal bone resorption activity. A previously reported knockout mouse model had only mononuclear osteoclasts with markedly reduced resorption activity in vitro, but with paradoxically normal skeletal micro-CT parameters. To further explore this and related questions, we used mouse ES cells carrying a gene trap allele to generate a second OC-STAMP null mouse strain. Bone histology showed overall normal bone form with large numbers of TRAP-positive, mononuclear osteoclasts. Micro-CT parameters were not significantly different between knockout and wild type mice at 2 or 6 weeks old. At 6 weeks, metaphyseal TRAP-positive areas were lower and mean size of the areas were smaller in knockout femora, but bone turnover markers in serum were normal. Bone marrow mononuclear cells became TRAP-positive when cultured with CSF-1 and RANKL, but they did not fuse. Expression levels of other osteoclast markers, such as cathepsin K, carbonic anhydrase II, and NFATc1, were not significantly different compared to wild type. Actin rings were present, but small, and pit assays showed a 3.5-fold decrease in area resorbed. Restoring OC-STAMP in knockout cells by lentiviral transduction rescued fusion and resorption. N- and C-termini of OC-STAMP were intracellular, and a predicted glycosylation site was shown to be utilized and to lie on an extracellular loop. The site is conserved in all terrestrial vertebrates and appears to be required for protein stability, but not for fusion. Based on this and other results, we present a topological model of OC-STAMP as a 6-transmembrane domain protein. We also contrast the osteoclast-specific roles of OC- and DC-STAMP with more generalized cell fusion mechanisms.

Se presenta un paciente de 62 años, sin antecedentes familiares de demencia, que a los 45 años debuta con crisis súbitas de disnea, visión borrosa, caída al suelo y movimientos repetitivos de brazos. Tratado por epilepsia con fenitoína y ácido valproico, repite esporádicamente crisis semejantes. Hace 4 años sus familiares notan cambios de personalidad, irritabilidad y conductas obsesivas. Hace 2 años aparecen episodios de desorientación de días de duración, algunos con alucinaciones auditivas y también fenómenos convulsivos. Ultimamente presenta crisis polimorfas, algunas con prolongada alteración de conciencia, estados catatoniformes y relajación esfinteriana. Examen físico y neurológico sin anormalidades. Evaluación neuropsicológica evidenció consistentes defectos en funciones frontales. EEG mostraron lentitud generalizada y actividad irritativa esporádica en regiones frontotemporales. Atrofia cortical de predominio anterior en CT scan e hipoperfusión fronto-temporal bilateral en SPECT. Exámenes de laboratorio y LCR normales. CONCLUSIÓN: La asociación de DFT con epilepsia, en forma no familiar, sugiere un síndrome neurodegenerativo cortical diferente.A 62 year-old patient is presented, without family antecedents of dementia who begins with 45 years of age with sudden crisis of dyspnea, blurred vision, fall to the floor and repetitive jerks of arms. Tried by epilepsy with phenytoin and valproate repeats similar crisis sporadically. Four years ago their relatives began to notice changes of personality, irritability and obsessive behaviors. Later on, are added episodes of disorientation of days of duration, some with auditory hallucinations and also convulsive manifestations. Finally appear polymorphic crisis, some with continue alteration of consciousness, catatonic states and sphincteric incontinence. Physical and neurological examination without abnormalities. Neuropsychological evaluation evidenced consistent defects in frontal functions. EEG showed widespread slowness and sporadic irritative activity in frontotemporal regions. Anterior cortical atrophy in CTscan and bilateral frontotemporal hypoperfusion in SPECT. Labs exams and CSF were normal. CONCLUSION: The association of FTD and epilepsy, in non-family form, suggests a different neurodegenerative cortical syndrome.

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Vascular corrosion casting is a method used to visualize the three dimensional (3D) anatomy and branching pattern of blood vessels. A polymer resin is injected in the vascular system and, after curing, the surrounding tissue is removed. The latter often deforms or even fractures the fragile cast. Here, a method is proposed that does not require corrosion, and is based on in situ micro computed tomography (micro‐CT) scans. To overcome the lack of CT contrast between the polymer cast and the animals' surrounding soft tissue, hafnium oxide nanocrystals (HfO2 NCs) are introduced as CT contrast agents into the resin. The NCs dramatically improve the overall CT contrast of the cast and allow for straightforward segmentation in the CT scans. Careful design of the NC surface chemistry ensures the colloidal stability of the NCs in the casting resin. Using only 5 m% of HfO2 NCs, high‐quality cardiovascular casts of both zebrafish and mice can be automatically segmented using CT imaging software. This allows to differentiate even μ$\umu$m‐scale details without having to alter the current resin injection methods. This new method of virtual dissection by visualizing casts in situ using contrast‐enhanced CT imaging greatly expands the application potential of the technique. [ABSTRACT FROM AUTHOR]