Search

There are many pathologies and capacity losses that progress with a similar evolution profile in certain groups of people. Health professionals are becoming increasingly knowledgeable in anticipating the development of these pathologies through preventive medicine. However, the increasing amount of data, coming from the collection of information from a larger number of patients, makes it difficult to analyse it manually. In the case of gerontology, it is difficult to classify in groups the evolution of the elderly for common pathologies in that age group. To be able to do this would make it possible to know in advance how a pathology or capacity loss will progress in an ageing person and to apply the corresponding preventive procedures. There are already works that try to improve the results of preventive medicine, but these are focused on analysing the current state of the patient and not their foreseeable future. In this article, time series forecasting by means of recurrent neural networks is used to analyse the evolution of the functional profile of ageing people as a time series. Based on the patterns contained in the patient’s time series and in the training of a model with data from previous patients, it is possible to determine the future evolution in patients with a similar history. To do this, functional profile data collected on an assessment platform developed by the authors of this article is used.

DC-SIGN, a lectin discovered two decades ago, plays a relevant role in innate immunity. Since its discovery, it has turned out to be a target for developing antiviral drugs based on carbohydrates due to its participation in the infection process of several pathogens. A plethora of carbohydrate multivalent systems using different scaffolds have been described to achieve this goal. Our group has made significant contributions to this field, which are revised herein

The rate of world population aging is increasing. This situation directly affects all countries socially and economically, increasing their compromise and effort to improve the living conditions of this sector of society. In environments with large influxes of elderly people, such as nursing homes, the use of technology has shown promise in improving their quality of life. The use of smart devices allows people to automate everyday tasks and learn from them to predict future actions. Additionally, smartphones capture a wealth of information that allows to adapt to nearby actuators according to people’s preferences and even detects anomalies in their behaviour. Current works are proposing new frameworks to detect these behaviours and act accordingly. However, these works are not focused on managing multidevice environments where sensor and smartphone data are considered to automate environments with elderly people or to learn from them. Also, most of these works require a permanent Internet connection, so the full benefit of smart devices is not completely achieved. In this work, we present an architecture that takes the data from sensors and smartphones in order to adapt the behaviour of the actuators of the environment. In addition, it uses this data to learn from the environment to predict actions or to extrapolate the actions that should be executed according to similar behaviours. The architecture is implemented through a use case based on a nursing home located in a rural area. Thanks to this work, the quality of life of the elderly is improved in a simple, affordable, and transparent way for them.

Using stock return data for the Japanese equity market, for the period from July 1983 to June 2018, we analyze the effect of major nuclear disasters worldwide on Japanese discount rates. For that purpose, we compare the performance of the capital asset pricing model (CAPM) conditional on the event of nuclear disasters with that of the classic CAPM and the Fama&ndash, French three- and five-factor models. In order to control for nuclear disasters, we use an instrument that allows us to parameterize the linear stochastic discount factor of the conditional CAPM and transform the classic CAPM into a three-factor model. In this regard, the use of nuclear disasters as an explanatory variable for the cross-sectional behavior of stock returns is a novel contribution of this research. Our results suggest that nuclear disasters account for a large fraction of the variation of stock returns, allowing the CAPM to perform similarly to the Fama&ndash, French three- and five-factor models. Furthermore, our results show that, in general, nuclear disasters are positively related to the expected returns of a large number of assets under study. Our results have important implications for the task of estimating the cost of equity and constitute a step forward in understanding the relationship between equity risk premiums and nuclear disasters.

The relatively recent green bond market is increasingly attracting interest at the technical, regulatory, and academic research levels. Although a considerable body of research on green bonds focuses on the investor&rsquo, s perspective, this study takes the perspective of a project finance sponsor to analyze whether there is a direct financial incentive for issuing green bonds in contrast to other types of financing. In order to measure the impact of green bond financing on the profitability and solvency of environmentally friendly investments, we study the sensitivity of the financial performance of a well-established project finance investment&mdash, the Sagunto regasification plant&mdash, to shifts in its financial structure. In particular, we develop a base case that allows us to study the impact of green financing compared to other financial structures typically used in project finance, under different scenarios. Our results show that in all cases, the internal rate of return (IRR) for shareholders is higher when green bonds instead of bank loans are issued to finance investments. Additionally, in the vast majority of the scenarios, green bond financing results in higher average debt service coverage ratios. Consequently, our results suggest that green bond financing constitutes a strong financial incentive for sponsors, which can help align their objectives with those of public authorities.

High-mannose (Man

Nanotechnology is science, engineering, and technology conducted at the nanoscale, which is about 1 to 100 nanometers. It has led to the development of nanomaterials, which behave very differently compared with materials with larger scales and can be applied in a wide range of applications in biomedicine. The physical and chemical properties of materials of such small compounds depend mainly on the size, shape, composition, and functionalisation of the system. Nanoparticles, carbon nanotubes, liposomes, polymers, dendrimers, nanogels, among others, can be nanoengineeried for controlling all parameters, including their functionalisation with ligands, which provide the desired interaction with the immunological system. However, undesired issues related to their toxicity and hypersensitivity responses have impeded more rapid health applications. Through interactions with the immune system, some of these nanostructures show promising applications as vaccines and diagnostics tools. Dendrimeric Antigens, Nanoallergens, and nanoparticles are potential tools for the in vitro diagnosis of allergic reactions. Glycodendrimers, liposomes, polymers, and nanoparticles have shown interesting applications in immunotherapy. There are wide panels of structures accessible, and controlling their physico-chemical properties would allow the obtainment of safer and more efficient compounds for clinical applications goals, either in diagnosis or treatment.

Recent literature shows that many testing procedures used to evaluate asset pricing models result in spurious rejection probabilities. Model misspecification, the strong factor structure of test assets, or skewed test statistics largely explain this. In this paper we use the relative entropy of pricing kernels to provide an alternative framework for testing asset pricing models. Building on the fact that the law of one price guarantees the existence of a valid pricing kernel, we study the relationship between the mean-variance efficiency of a model&rsquo, s factor-mimicking portfolio, as measured by the cross-sectional generalized least squares (GLS) R2 statistic, and the relative entropy of the pricing kernel, as determined by the Kullback&ndash, Leibler divergence. In this regard, we suggest an entropy-based decomposition that accurately captures the divergence between the factor-mimicking portfolio and the minimum-variance pricing kernel resulting from the Hansen-Jagannathan bound. Our results show that, although GLS R2 statistics and relative entropy are strongly correlated, the relative entropy approach allows us to explicitly decompose the explanatory power of the model into two components, namely, the relative entropy of the pricing kernel and that corresponding to its correlation with asset returns. This makes the relative entropy a versatile tool for designing robust tests in asset pricing.

This work presents a new family of bio-hybrid light-emitting diodes (Bio-HLEDs) using all-bio color down-converting coatings that combine silk fibroin (SF) as a packaging matrix and fluorescent proteins (FPs) as emitters. The thermal, mechanical, optical, and luminescent features of the FP–SF bio-phosphors were optimized with respect to the blend composition and the FP stability under thermal and irradiation stress. Bio-HLEDs with FP–SF filters feature stabilities of 1.2 h and 500 h (200 mA) at efficiencies of ∼40 lm W−1for on-chip and remote configurations, respectively. This is significantly superior to devices with FP–polymer bio-phosphors –i.e., 1.8 min (on-chip) and 300 h (remote) at −1. The excellence of the biogenic phosphors is attributed to (i) the ideal optical features of the SF films, (ii) the highly efficient emission of the FPs, and (iii) the high thermal- and photo-stabilities of FPs in the SF matrix. Finally, we revealed that the emission deactivation process of FP–SF phosphors is related to a very slow protonation of the ionic form of the FP chromophore along with large morphological changes due to thermal- and photo-induced FP motions. Overall, this work shows the promising prospects of fully biogenic phosphors en route to designing highly stable bio-based lighting devices

An effective specific immunotherapy should contain elements to generate specific recognition (T-cell peptides) and to modulate the immunological response towards a Th1/Treg pattern by enhancing dendritic cells (DCs). We propose a novel sublingual immunotherapy for peach allergy, using systems, that combine Prup3-T-cell peptides with mannose dendrons (D

Recent literature shows that market anomalies have significantly diminished, while research on market factors has largely improved the performance of asset pricing models. In this paper we study the extent to which data envelopment analysis (DEA) techniques can help improve the performance of multifactor models. Specifically, we test the explanatory power of the Fama and French three-factor model, combined with an additional factor based on DEA, on a sample of 2101 European equity funds, for the period from 2001 to 2016. Accordingly, we first form the fund portfolios that constitute our test assets and create the efficiency factor. Secondly, we estimate the prices of risk tied to the four factors using ordinary least squares (OLS) on a two-stage cross-sectional regression. Finally, we use the R-squared statistic estimated by generalized least squares (GLS), as well as the Gibbons Ross and Shanken test and the J-test for overidentifying restrictions in order to study the performance of the model, including and omitting the efficiency factor. The results show that the efficiency factor improves the performance of the model and reduces the pricing errors of the assets under consideration, which allows us to conclude that the efficiency index may be used as a factor in asset pricing models.

The number of Internet of Things (IoT) devices is growing at an unstoppable pace. In most cases, the proper functioning of these devices requires human intervention. Due to this growth, people will have to configure more and more devices leading to the investment of a considerable effort and time. Nowadays, some works try to automate the user actions with IoT devices by using machine learning algorithms based on the relationships among devices or the previous human behaviour. However, these proposals do not make use of contextual information obtained from the devices themselves or they employ complex sets of prediction models. This paper proposes a neural network-based solution to predict the devices behaviour by using previous interactions and contextual information as input variables. Thanks to this, device interactions can be predicted and automated, even without having previous records, by knowing behaviours of devices of the same type in similar environment.

With each new year, the world’s population is more aged and the birth rate decreases. That is why, in a not distant future, we will encounter the challenge that there will be many elderly people in our population and few young people to care for them. To help facilitate this task, the use of new technologies is increasing. Therefore, this paper proposes the use of a not intrusive system that, using a microservice architecture and long-distance, non-intrusive facial recognition, allows to control elderly assistance to their daily tasks in residences, facilitating the work of nurses. For example, to check that all the elderly regularly go to the dining room at meal times or to the gym if they should do some type of rehabilitation exercises. For this, the system uses security cameras that are installed in the access of the different zones to be controlled.

International audience; Chondroitin sulfate type-E (CS-E) is a sulfated polysaccharide that shows several interesting biological activities, such as modulation of the neuronal growth factor signaling and its interaction with langerin, a C-type lectin with a crucial role in the immunological system. However, applications of CS-E are hampered by the typical heterogeneous structure of the natural polysaccharide. Well-defined, homogeneous CS-E analogues are highly demanded. Here, we report the synthesis of monodispersed, structurally well-defined second-generation glycodendrimers displaying up to 18 CS-E disaccharide units. These complex multivalent systems have a molecular weight and a number of disaccharide repeating units comparable with those of the natural polysaccharides. In addition, surface plasmon resonance experiments revealed a calcium-independent interaction between these glycodendrimers and langerin, in the micromolar range, highlighting the utility of these compounds as CS-E mimetics.

N-Heterocyclic Thiones (NHT) proved to be efficient ligands for the stabilization of small platinum nanoparticles (1.3–1.7 nm), synthesized by decomposition of [Pt(dba)2], under a H2 atmosphere, in the presence of variable sub-stoichiometric amounts of the NHT. Full characterization by means of TEM, HR-TEM, NMR, ICP, TGA and XPS have been carried out, providing information about the nature of the metal nanoparticles and the interaction of the NHT ligands to the metal surface. Importantly, DFT calculations indicate that some NHT ligands interact with the metal through the CvC double bond of the imidazole fragment in addition to the sulfur atom, thus providing additional stabilization to the nanoparticles. According to XPS, TGA and ICP techniques, the surface coverage by the ligand increases by decreasing the size of the substituents on the nitrogen atom. The platinum nanoparticles have been used as catalyst in the hydroboration of alkynes. The most active system is that with a less covered surface area lacking an interaction of the ligand by means of the CvC double bond. This catalyst hydroborates alkynes with excellent selectivities towards the monoborylated anti-Markovnikov product (vinyl-boronate) when one equiv. of borane is used. Very interestingly, aliphatic alkynes undergo a second hydroborylation process leading to the corresponding 1,1- and 1,2-diboroylated species with good selectivities towards the former

Carbohydrate multivalent interactions play a key role in nature as efficient recognition tools for controlling a plethora of physiological and pathological events. These interactions are weak but the presence of multiple copies of ligands and receptors on biological surfaces leads to a multivalent recognition with enhanced selectivity and exponentially increased affinity. Here we report a simple and straightforward methodology for multivalent presentation of both simple monosaccharide ligands and complex dendritic glycostructures using polymeric nanogels (NGs). The interaction between the glycoNGs and a model lectin has been analysed by DLS and UV–Vis agglutination assays, showing that the introduction of glycodendrons with 3 and 9 mannose residues into the NGs results in a strong enhancement of the multivalency.

High-mannose (Man9GlcNAc2) is the main carbohydrate unit present in viral envelope glycoproteins such as gp120 of HIV and the GP1 of Ebola virus. This oligosaccharide comprises the Man9 epitope conjugated to two terminal N-acetylglucosamines by otherwise rarely-encountered β-mannose glycosidic bond. Formation of this challenging linkage is the bottleneck of the few synthetic approaches described to prepare high mannose. Herein, we report the synthesis of the Man9 epitope with both alpha and beta configurations at the reducing end, and subsequent evaluation of the impact of this configuration on binding to natural receptor of high-mannose, DC-SIGN. Using fluorescence polarization assays, we demonstrate that both anomers bind to DC-SIGN with comparable affinity. These relevant results therefore indicate that the more synthetically-accesible Man9 alpha epitope may be deployed as ligand for DC-SIGN in both in vitro and in vivo biological assays

Each person interacts with multiple health institution’s systems along their life. These systems are usually developed to fulfill the specific needs of sanitary organizations or Web of Medical Things manufacturers. However, most of the times these information systems aren’t interconnected, making it very difficult to put in common the information of a patient scattered in various systems. Thus, it’s necessary to develop solutions that allow health information systems developers to consult all the information of an user across the multiple health’s information systems it is scattered and to offer this information organized as the Personal Health Trajectory of the user (a succession of Personal Health Records ordered by time). This paper proposes a solution for the integration of heterogeneous health information systems, the processing of their data and its provisioning in a health trajectory perspective through an API. Thus, software developers of healthcare solutions can leverage this API to develop a new generation of person-oriented solutions.

Significant methodological progress has taken place to quantify the reliability of networked systems over the past decades. Both numerical and analytical methods have enjoyed improvements via a host of advanced Monte Carlo simulation strategies, state space partition methods, statistical learning, and Boolean functions among others. The latter approach exploits logic to approximate network reliability assessments efficiently while offering theoretical error guarantees. In parallel, physicists have made progress modeling complex systems via tensor networks (TNs), particularly quantum many-body systems. Inspired by the representation power of quantum TNs, this paper offers a new approach to efficiently bound all-terminal network reliability (ATR). It does so by exactly solving a related network Boolean satisfiability counting problem (or # SAT NET ), represented as a TN, by counting configurations in which all network nodes are connected to at least a neighbor. Our # SAT NET counting outperforms state-of-the-art approximate and exact counters for the same problem as shown for challenging two-dimensional lattice networks of increasing size. While the over-counting from # SAT NET increases exponentially relative to the number of configurations that satisfy ATR problems (or # REL AT ), the bias is predictable for ideal networks, such as lattices, and our upper bound is guaranteed with 100 % confidence. This bound also cuts through the upper bound from other analytical methods for the ATR problem, such as recursive decomposition algorithms (RDA)—a desirable feature when exact or approximate methods with error guarantees fail to scale. Clearly, our goal is not to solve the general stochastic network reliability problem, which remains a # P problem in the computational complexity hierarchy (i.e., a counting version of non-deterministic polynomial time [NP] problems for which there is no known polynomial time algorithms to find their solutions). Instead, we present a novel bounding technique for network reliability, which relies on exactly counting configurations for our network satisfiability problem by using quantum computing principles. We offer a proof for the counting bound to hold in a connectivity ATR sense, and illustrate trends with cubic and lattice networks. Overall, the proposed method provides an alternative to available system reliability assessment approaches, and opens directions for future research, especially as discoveries in logic, algebraic projections, and quantum computation continue to accrue.

Central scaffold topology and carbohydrate density are important features in determining the binding mechanism and potency of synthetic multivalent of poly‐ versus monodisperse carbohydrate systems against a model plant toxin (Ricinus communis agglutinin (RCA120)). Lower densities of protein receptors favour the use of heterogeneous, polydisperse glycoconjugate presentations, as determined by surface plasmon resonance and dynamic light scattering., We thank the European Commission (Marie Curie CIG, O.B.), MINECO (CTQ2014‐58664‐R, CTQ2014‐52328‐P, and RYC‐2015‐17705), the European Regional Development Fund, Generalitat de Catalunya (M.S.) and CSIC (JAEdoc contract, J.J.R.) for financial support. O.B. is a Ramón y Cajal Fellow.

Chondroitin sulfate (CS) is a member of the glycosaminoglycan (GAG) family, a class of polysaccharides implicated in relevant biological functions. The structural complexity of these carbohydrates demands the development of simple glycomimetics as useful tools to study the biological processes where GAGs are involved. In this work we described the synthesis of the disaccharide unit of the CS-E (GlcA-GalNAc(4,6-di-OSO3)), in a multivalent presentation. Using a fluorescence polarization competition assay we have demonstrated that a hexavalent dendrimer of this disaccharide interact with midkine, in the low micromolar range. This result highlights the potency of these disaccharide-displaying multivalent systems as interesting mimetics of longer and synthetically more complex GAG oligosaccharides.

Reliance on classical valuation methods such as the net present value (NPV) has often resulted in controversial asset valuations in the mining sector. An alternative method, termed decoupled net present value (DNPV), is used to evaluate mining investment opportunities. The proposed valuation method decouples the time value of money from the risk associated with the project providing a consistent valuation method free from the problems typically associated with the application of NPV. Market risks (e.g., commodity prices, foreign exchange) can be systematically combined with non-market risks (e.g., effect on operations of climate change and/or large earthquakes). More importantly, DNPV allows seamless integration of project risk assessment performed by technical experts and risk management implemented by business executives into the financial evaluation of the project. A simplified mining investment project is analyzed using traditional techniques and compared with the proposed DNPV. The example includes a discussion about how valuation is affected by climate change and earthquake risks, and how investment in resilience and adaption can be incorporated in the proposed analysis.

The infection of humans by lethal pathogens such as Ebola and other related viruses has not been properly addressed so far. In this context, a relevant question arises: What can chemistry do in the search for new strategies and approaches to solve this emergent problem? Although initially a variety of known chemical compounds-for other purposes-proved disappointing in tests against Ebola virus (EBOV) infection, more recently, specific molecules have been prepared. In this Perspective, we present new approaches directed at the design of efficient entry inhibitors to minimize the development of resistance by viral mutations. In particular, we focus on dendrimers as well as fullerene C-with a unique symmetrical and 3D globular structure-as biocompatible carbon platforms for the multivalent presentation of carbohydrates. The antiviral activity of these compounds in an Ebola pseudotyped infection model was in the low micromolar range for fullerenes with 12 and 36 mannoses. However, new tridecafullerenes-in which the central alkyne scaffold of [60]fullerene is connected to 12 sugar-containing [60]fullerene units (total 120 mannoses)-exhibit an outstanding antiviral activity with IC in the sub-nanomolar range! The multivalent presentation of specific carbohydrates by using 3D fullerenes as controlled biocompatible carbon scaffolds represents a real advance, being currently the most efficient molecules in vitro against EBOV infection. However, additional studies are needed to determine the optimized fullerene-based leads for practical applications.

Gold nanoparticles (Au-NPs) have been prepared using N-heterocyclic thiones (NHTs) as ligand stabilisers. These Au-NPs have been shown to be very stable, even in air, and have been characterized by a combination of several techniques (TEM, HR-TEM, STEM-HAADF, EDX, DLS, elemental analysis and 1H NMR). These nanoparticles are active in the catalytic reduction of nitroarenes to anilines., Financial support (FEDER contribution) from the MINECO (Projects CTQ2016-76267-P, CTQ2016-80814-R and CTQ2014-51912-REDC) and the Junta de Andalucía (Project FQM-2126) is gratefully acknowledged. P. L thanks the Spanish MINECO for a Juan de la Cierva contract. R. C. F thanks Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq-CsF) and Fundación Carolina for financial support. L. C. M. thanks the CAPES Foundation, Ministry of Education of Brazil (CAPES-CsF 13465-13-9) for a doctoral grant.

An effective specific immunotherapy should contain elements to generate specific recognition (T-cell peptides) and to modulate the immunological response towards a Th1/Treg pattern by enhancing dendritic cells (DCs). We propose a novel sublingual immunotherapy for peach allergy, using systems, that combine Prup3-T-cell peptides with mannose dendrons (D1ManPrup3 and D4ManPrup3). Peach anaphylactic mice were treated 1, 2 and 5 nM concentrations. Tolerance was assessed one/five weeks after finishing treatment by determining in vivo/in vitro parameters after challenge with Prup3. Only mice receiving D1ManPrup3 at 2 nM were protected from anaphylaxis (no temperature changes, decrease in Prup3-sIgE and -sIgG1 antibody levels, and secreting cells) compared to PBS-treated mice. Moreover, an increase of Treg-cells and regulatory cytokines (IL-10+/IFN-γ+) in CD4+-T-cells and DCs were found. These changes were maintained at least five weeks after stopping treatment. D1ManPrup3 is an effective new approach of immunotherapy inducing protection from anaphylaxis which persists after finishing treatment.

Recent studies showed that Parkinson’s disease (PD) patients improved their gait parameters while walking with rhythmic auditory stimulation (RAS). They achieved a longer stride length, a reduced stride time variability and a higher walking speed. Combining RAS with mobile gait analysis would allow continuous monitoring of RAS effects and gait in natural environments. This paper proposes a mobile solution for home-based assessment of RAS by combining RAS gait training and a mobile system for data acquisition. Existing datasets were used to investigate the cadence of PD patients and to propose suitable frequencies for RAS gait training. The cadence calculation was implemented using a peak detection algorithm, which uses the time difference between two mid-swing events as stride time values. We validated our system as a whole using a cohort of 13 PD patients who performed RAS gait training. The algorithms were also validated against the eGaIT system, a state-of-the-art system, and achieved a mean F 1 score for detected strides of 97.57 % ± 0.86 % and a mean absolute error for the cadence of 0.16 spm ± 0.09 spm. This study lays the ground work for further clinical studies investigating the effectiveness of mobile RAS within a home environment.

SCOPE Glycodendropeptides (GDPs) functionalized with mannose can enhance allergen interaction with dendritic cells (DCs) via C-type lectin receptors (CLRs), modulating the immune response. They can present multiple peptides and have potential applications for diagnosis and treatment of food allergy (FA). The immune response induced by GDPs with mannose and Pru p 3 peptides (mono/tetravalent) with ester (D1 ManPrup3/D4 ManPrup3) or ether linkers (D1 Man-O- Prup3/D4 Man-O- Prup3) in lipid-transfer-protein-allergic patients and tolerant controls is analyzed. METHODS AND RESULTS The immunological response induced by GDPs is studied by assessing monocyte-derived-DC maturation, lymphocyte proliferation, cytokine production, and basophil response by flow cytometry. Dn ManPrup3 was recognized by DCs via CLRs inducing DC maturation in all subjects. However, CCR7 expression is significantly upregulated in allergic patients compared to tolerant controls. These changes correlate with lymphocyte proliferation and specific production of Th2/Th1 cytokines in allergic patients. Moreover, D1 ManPrup3 does not induce basophil activation. CONCLUSION Dn ManPrup3 induces changes in DC maturation and lymphocyte proliferation, indicating specific recognition via CLRs. Prup3-GDPs are recognized by immune cells, inducing a specific immune response and modulating the immunological response in FA patients. The specific geometry of D1 ManPrup3 in particular makes it a potential candidate for specific immunotherapy development.

Cell recognition, adhesion, and internalization are involved in infectious, reproductive, and inflammatory processes and are generally mediated by interactions between molecules located in the cell membrane and the extracellular matrix. These processes can decrease proliferation rates and they are well known for bacteria, fungi, and animals, but there is a lack of knowledge regarding autotrophic cells. Carbohydrates and proteins (e.g., lectins) are important molecules for cell interactions and information about these molecules is essential to better understand many biological phenomena in uni- or multicellular organisms. Most studies focus on the identification of the carbohydrates present on the cell surface by using labeled lectins. Alternatively, here we present a pioneer research performed by using three different labeled carbohydrates in a multivalent presentation (glycodendrons) to detect the presence of carbohydrate receptors (e.g., lectins) on cell surfaces of 12 algal species. The goal of this study was to detect some specificity in these molecular interactions, but in a reverse way in comparison to that commonly described in the literature. We tested trivalent molecules containing residuals of D-mannose, L-fucose, or N-acetyl-galactosamine to identify their bindings with the corresponding lectins expressed on cell surfaces. We envisage that our new approach could be an alternative tool for taxonomic and physiological studies on microalgae or even on other groups of organisms. Based on our results, the receptors found in the cell surface of the algal species tend to differ in composition, quantity, and distribution. The differences were mainly species-specific, since no patterns were identified at higher taxonomic level. Moreover, like lectins, labeled carbohydrates were proved to be a reliable tool for the study of cell surface composition.

Carbon nanotubes (CNTs) were surface-modified by a glycodendrimer with four glucose units (4-Gl). Electrodes for supercapacitors based on CNT/4-Gl hybrids were used for the first time in this work. The preparation was conducted by casting eight alternating bilayers of two types of modified multiwalled carbon nanotubes (MWCNTs), MWCNT-COOH/4-Gl and MWCNT-NH/4-Gl, from aqueous dispersions (pH = 6). The electrodes showed good cohesion, dimensional stability, and a homogeneous nanoscale structure because the carbon nanotube/dendrimer layers interact electrostatically. The supercapacitor was stacked with a separator embedded with a 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ionic liquid electrolyte. The device with 20Â wt% of dendrimer with respect to CNT content in the electrodes achieved a remarkable increase of 600Â % in capacitance compared with the capacitance without the dendrimer., The authors are grateful to Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)—Brazil for the scholarship of João Paulo Campos Trigueiro and to the Centro de Microscopia/UFMG for the images provided. Pró-Reitoria de Pesquisa from UFMG (PRPq/UFMG) is acknowledged for financial support of the English revision. Rute C. Figueiredo extends gratitude to the Carolina Foundation for its scholarship program for the mobility of Brazilian teachers.

Scope: Much of the knowledge about gene expression during anaphylaxis comes from candidate gene studies. Despite their potential role, expression changes in dendritic cells (DCs) have not been studied in this context using high throughput methods. The molecular mechanisms underlying food-antigen-induced anaphylaxis are investigated using DCs from an animal model. Methods and results: RNA sequencing is used to study gene expression in lymph-node-derived DCs from anaphylactic mice sensitized intranasally with the major peach allergen Pru p 3 during the acute reaction phase, induced intraperitoneally. In total, 237 genes changed significantly, 181 showing at least twofold changes. Almost three-quarters of these increase during anaphylaxis. A subset is confirmed using RT-PCR in a second set of samples obtained from a new batch of mice. Enrichment analysis shows an overrepresentation of genes involved in key immune system and inflammatory processes, including TGF-β signaling. Comparison with a study using anaphylactic human subjects show significant overlap. Conclusions: The findings provide a comprehensive overview of the transcriptional changes occurring in DCs during anaphylaxis and help elucidate the mechanisms involved. They add further weight to the putative role of these cells in anaphylaxis and highlight genes that may represent potential therapeutic targets.

The synthesis of multivalent systems based on hexakis-adducts of [60]fullerene employing a biocompatible copper-free click chemistry strategy has been accomplished. A symmetric hexakis-adduct of fullerene bearing 12 maleimide units (3) is reported, and it has been employed to carry out the thiol-maleimide Michael addition. To achieve orthogonal click addition, an asymmetric derivative bearing one maleimide and 10 cyclooctynes has been synthesized. The sequential and one-pot transformations of the two clickable groups have been explored, finding the best results in the case of the one-pot experiment. This route has been used to obtain a biocompatible hexakis-adduct appended with two different biomolecules, carbohydrates, and amino acids.

URL del artículo en la web de la Revista: https://www.upo.es/revistas/index.php/RevMetCuant/article/view/2703 Performance measurement is an area of crucial interest in asset valuation and investment management. High volatility as well as time aggregation of returns, amongst other characteristics, may distort the results of conventional measures of performance. In this work, we study the performance of 115 Spanish Absolute Return Funds in the period 2010-2015, using the Sharpe, Treynor, Jensen and Modified Sharpe ratios. We then apply Data Envelopment Analysis to classify the funds in order to avoid the problems arising from the non-normality of their returns, since non-gaussian returns do not pose a problem in Data Envelopment Analysis implementation. In addition, we apply the Malkiel, Brown and Goetzman test and the Rude and Khan test in annual periods to determine the existence of persistence. Finally, we study the relationship between efficiency and persistence in order to determine the relationship between both measures and to support decision-making processes. The results show a significant relationship between cross efficiency and Modified Sharpe ratios as well as the existence of persistence for annual periods. Nevertheless, the results do not allow concluding any relationship amongst efficiency and persistence. La medida de la performance es un área de crucial interés en la valoración de activos y selección de inversiones. Elevadas volatilidades, así como la agregación temporal de rendimientos, entre otras características, pueden distorsionar los resultados de las medidas convencionales de performance. En este trabajo, estudiamos la performance de 115 fondos de retorno absoluto españoles en el periodo 2010¿2015 usando los ratios de Sharpe, Treynor y Jensen y el ratio de Sharpe modificado. Posteriormente, para clasificar los fondos se aplica el Análisis Envolvente de Datos (Data Envelopment Analysis, DEA) en aras de evitar los problemas derivados de la no normalidad de los rendimientos, dado que rendimientos no gaussianos no suponen un problema a la hora de implementar el Análisis Envolvente de Datos. Adicionalmente, se aplica el test de Malkiel, Brown y Goetzman y el test de Rude y Khan en periodos anuales para determinar la existencia de persistencia. Finalmente. se estudia la relación entre eficiencia y persistencia con objeto de determinar la relación entre ambas medidas y apoyar el proceso de toma de decisiones. Los resultados muestran una significativa relación entre eficiencia cruzada y el ratio de Sharpe modificado así como la existencia de persistencia en periodos anuales. No obstante, los resultados no permiten concluir en ninguna relación directa entre eficiencia y persistencia. Universidad Pablo de Olavide

SWCNTs, MWCNTs, and SWCNHs have been employed as virus-mimicking nanocarbon platforms for the multivalent presentation of carbohydrates in an artificial Ebola virus infection model assay. These carbon nanoforms have been chemically modified by the covalent attachment of glycodendrons and glycofullerenes using the CuAAC >click chemistry> approach. This modification dramatically increases the water solubility of these structurally different nanocarbons. Their efficiency in blocking DC-SIGN-mediated viral infection by an artificial Ebola virus has been tested in a cellular experimental assay, finding that glycoconjugates based on MWCNTs functionalized with glycofullerenes are potent inhibitors of viral infection., Financial support by the European Research Council (ERC-320441-Chirallcarbon), Ministerio de Economı́a y Competitividad (MINECO) of Spain (projects CTQ2017-83531-R, CTQ2017-84327-P, CTQ2017-86265-P, and CTQ2014-52328-P), the Comunidad Autónoma de Madrid (PHOTOCARBON project S2013/MIT-2841), and Instituto de Salud Carlos III (ISCIII) (FIS1400708 and Red de Investigación en SIDA, RIS, RD12/0017) is acknowledged. MICIU/ICTI2017-2020/CTQ2017-84327-P MICIU/ICTI2017-2020/CTQ2017-86265-P MINECO/ICTI2013-2016/CTQ2014-52328-P S2013/MIT-2841/PHOTOCARBON

Public information services and documents should be accessible to the widest possible readership. In particular, information from these sources often takes the form of numerical expressions, which pose comprehension problems for many people, including people with disabilities, who are often also exposed to poverty, illiteracy, or lack of access to advanced technology. This paper presents an approach to treat numerical information in the text simplification process to make it more accessible. A generic model for automatic text simplification systems is presented, aimed at making documents more accessible to readers with cognitive disabilities. The proposed approach is validated with a real system to simplify numerical expressions in Spanish. This system is then evaluated and the results show that it is appropriate for the task at hand.

In this paper, a practical application of a valuation method that decouples the time value of money from the risk associated with the project is used to value an investment on a solar project. The proposed method is termed decoupled net present value (DNPV). A simple investment renewable energy project is presented using both the traditional NPV techniques and the proposed DNPV. The proposed methodology provides a consistent valuation method free from the problems typically associated with the application of traditional NPV and, more importantly, it allows a seamless integration of project risk assessment performed by technical experts and risk management implemented by business executives into the financial evaluation of the project.

The high-mannose oligosaccharide (or its corresponding Man