A dynamically coherent pattern of rhythms that matches between distant species across the evolutionary scale.

We address the temporal organization of circadian and ultradian rhythms, crucial for understanding biological timekeeping in behavior, physiology, metabolism, and alignment with geophysical time. Using a newly developed five-steps wavelet-based approach to analyze high-resolution time series of metabolism in yeast cultures and spontaneous movement, metabolism, and feeding behavior in mice, rats, and quails, we describe a dynamically coherent pattern of rhythms spanning over a broad range of temporal scales (hours to minutes). The dynamic pattern found shares key features among the four, evolutionary distant, species analyzed. Specifically, a branching appearance given by splitting periods from 24 h into 12 h, 8 h and below in mammalian and avian species, or from 14 h down to 0.07 h in yeast. Scale-free fluctuations with long-range correlations prevail below ~ 4 h. Synthetic time series modeling support a scenario of coexisting behavioral rhythms, with circadian and ultradian rhythms at the center of the emergent pattern observed.

Contribution of a method of assessing minimum audible angle in headphones.

OBJECTIVES: The main objective of this study was to test the feasibility of measuring minimum audible angle in headphones with different reference positions in the horizontal plane, and comparing different types of pre-recorded head-related transfer functions. The secondary objective was to assess spatial discrimination performance in simulated unilateral hearing loss by measuring the minimum audible angle under monaural conditions using headphones. MATERIALS AND METHODS: Minimum audible angle was assessed in 27 normal-hearing subjects, to test their spatial discrimination abilities, using 4 datasets of pre-recorded head-related transfer functions: 2 recorded on mannequins (KU100, KEMAR), and 2 individualized head-related transfer function datasets (TBM, PBM). Performance was evaluated at 3 reference positions (0°, 50° and 180°) in 1 binaural and 2 monaural conditions. RESULTS: KU100 generated minimum audible angle values smaller than KEMAR in frontal and lateral position P<0.005), with a suggestive difference (P<0.05) compared to TBM and PBM in the frontal and lateral planes. Comparison between binaural and monaural conditions showed significant differences in frontal position for MON-c (contralateral) and MON-i (ipsilateral) (P<0.001), in lateral position for MON-c only (P<0.001) and in posterior position for MON-c and MON-i (P<0.001). CONCLUSION: This study suggests that evaluation of spatial discrimination capacity using minimum audible angle with the KU100 head-related transfer dataset was reliable and robust.

PM10 concentration forecasting in the metropolitan area of Oviedo (Northern Spain) using models based on SVM, MLP, VARMA and ARIMA: A case study.

Atmospheric particulate matter (PM) is one of the pollutants that may have a significant impact on human health. Data collected over seven years in a city of the north of Spain is analyzed using four different mathematical models: vector autoregressive moving-average (VARMA), autoregressive integrated moving-average (ARIMA), multilayer perceptron (MLP) neural networks and support vector machines (SVMs) with regression. Measured monthly average pollutants and PM10 (particles with a diameter less than 10µm) concentration are used as input to forecast the monthly averaged concentration of PM10 from one to seven months ahead. Simulations showed that the SVM model performs better than the other models when forecasting one month ahead and also for the following seven months.

Predictive modelling of eutrophication in the Pozón de la Dolores lake (Northern Spain) by using an evolutionary support vector machines approach.

Eutrophication is a water enrichment in nutrients (mainly phosphorus) that generally leads to symptomatic changes and deterioration of water quality and all its uses in general, when the production of algae and other aquatic vegetations are increased. In this sense, eutrophication has caused a variety of impacts, such as high levels of Chlorophyll a (Chl-a). Consequently, anticipate its presence is a matter of importance to prevent future risks. The aim of this study was to obtain a predictive model able to perform an early detection of the eutrophication in water bodies such as lakes. This study presents a novel hybrid algorithm, based on support vector machines (SVM) approach in combination with the particle swarm optimization (PSO) technique, for predicting the eutrophication from biological and physical-chemical input parameters determined experimentally through sampling and subsequent analysis in a certificate laboratory. This optimization technique involves hyperparameter setting in the SVM training procedure, which significantly influences the regression accuracy. The results of the present study are twofold. In the first place, the significance of each biological and physical-chemical variables on the eutrophication is presented through the model. Secondly, a model for forecasting eutrophication is obtained with success. Indeed, regression with optimal hyperparameters was performed and coefficients of determination equal to 0.90 for the Total phosphorus estimation and 0.92 for the Chlorophyll concentration were obtained when this hybrid PSO-SVM-based model was applied to the experimental dataset, respectively. The agreement between experimental data and the model confirmed the good performance of the latter.

Improvement on binding of chondroitin sulfate derivatives to midkine by increasing hydrophobicity.

The interactions between chondroitin sulfate (CS) and a wide number of proteins modulate important biological processes. Here, the binding properties to midkine and pleiotrophin of sulfated, fully protected intermediates, typically obtained in the chemical synthesis of CS oligosaccharides, were tested for the first time. Using a fluorescence polarization competition experiment, we discovered that these synthetic precursors strongly bound these two closely related cytokines involved in cancer and inflammation. The relative binding affinities of these intermediates were significantly higher than those displayed by the corresponding fully deprotected oligosaccharides, indicating that the presence of hydrophobic protecting groups strongly enhanced the binding of CS-like derivatives to midkine. These compounds offer novel opportunities for the development of potent inhibitors/activators of CS-protein interactions with potential therapeutic applications.

Detection and quantitative analysis of two independent binding modes of a small ligand responsible for DC-SIGN clustering.

DC-SIGN (dendritic cell-specific ICAM-3 grabbing non-integrin) is a C-type lectin receptor (CLR) present, mainly in dendritic cells (DCs), as one of the major pattern recognition receptors (PRRs). This receptor has a relevant role in viral infection processes. Recent approaches aiming to block DC-SIGN have been presented as attractive anti-HIV strategies. DC-SIGN binds mannose or fucose-containing carbohydrates from viral proteins such as the HIV envelope glycoprotein gp120. We have previously demonstrated that multivalent dendrons bearing multiple copies of glycomimetic ligands were able to inhibit DC-SIGN-dependent HIV infection in cervical explant models. Optimization of glycomimetic ligands requires detailed characterization and analysis of their binding modes because they notably influence binding affinities. In a previous study we characterized the binding mode of DC-SIGN with ligand 1, which shows a single binding mode as demonstrated by NMR and X-ray crystallography. In this work we report the binding studies of DC-SIGN with pseudotrisaccharide 2, which has a larger affinity. Their binding was analysed by TR-NOESY and STD NMR experiments, combined with the CORCEMA-ST protocol and molecular modelling. These studies demonstrate that in solution the complex cannot be explained by a single binding mode. We describe the ensemble of ligand bound modes that best fit the experimental data and explain the higher inhibition values found for ligand 2.

Air quality modeling in the Oviedo urban area (NW Spain) by using multivariate adaptive regression splines.

The aim of this research work is to build a regression model of air quality by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (northern Spain) at a local scale. To accomplish the objective of this study, the experimental data set made up of nitrogen oxides (NO x ), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3), and dust (PM10) was collected over 3 years (2006-2008). The US National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of these numerical calculations, using the MARS technique, conclusions of this research work are exposed.

Analysis and detection of functional outliers in water quality parameters from different automated monitoring stations in the Nalón river basin (Northern Spain).

The purposes and intent of the authorities in establishing water quality standards are to provide enhancement of water quality and prevention of pollution to protect the public health or welfare in accordance with the public interest for drinking water supplies, conservation of fish, wildlife and other beneficial aquatic life, and agricultural, industrial, recreational, and other reasonable and necessary uses as well as to maintain and improve the biological integrity of the waters. In this way, water quality controls involve a large number of variables and observations, often subject to some outliers. An outlier is an observation that is numerically distant from the rest of the data or that appears to deviate markedly from other members of the sample in which it occurs. An interesting analysis is to find those observations that produce measurements that are different from the pattern established in the sample. Therefore, identification of atypical observations is an important concern in water quality monitoring and a difficult task because of the multivariate nature of water quality data. Our study provides a new method for detecting outliers in water quality monitoring parameters, using turbidity, conductivity and ammonium ion as indicator variables. Until now, methods were based on considering the different parameters as a vector whose components were their concentration values. This innovative approach lies in considering water quality monitoring over time as continuous curves instead of discrete points, that is to say, the dataset of the problem are considered as a time-dependent function and not as a set of discrete values in different time instants. This new methodology, which is based on the concept of functional depth, was applied to the detection of outliers in water quality monitoring samples in the Nalón river basin with success. Results of this study were discussed here in terms of origin, causes, etc. Finally, the conclusions as well as advantages of the functional method are exposed.

Secretion of IL-16 through TNFR1 and calpain-caspase signaling contributes to MRSA pneumonia.

Staphylococcus aureus is a major cause of severe pneumonia. Multiple mechanisms of proinflammatory signaling are activated to recruit immune cells into the airway in response to S. aureus. We found that interleukin-16 (IL-16), a T cell cytokine that binds CD4, is potently activated by S. aureus, specifically by protein A (SpA), and to a much greater extent than by Gram-negative pathogens or lipopolysaccharide. IL-16 production involved multiple signals including ligation of tumor necrosis factor receptor (TNFR) family members or epidermal growth factor receptor, both receptors for SpA and generation of Ca(2+) fluxes to activate calpains and caspase-3. Although human airway epithelial cells, vascular endothelial cells, THP-1 and Jurkat T cells released IL-16 in response to S. aureus in vitro, in a murine model of pneumonia, CD4(+) cells were the major source of IL-16 suggesting the involvement of an autocrine signaling pathway. The production of IL-16 contributed to lung damage as neutralization of IL-16 enhanced S. aureus clearance and resulted in diminished lung pathology in S. aureus pneumonia. Our results suggest that the ability of S. aureus to activate TNFR1 and Ca(2+)/calpain signaling contribute to T cell activation and excessive inflammation in the setting of acute pneumonia.

[Serum microRNA-21 usefulness in inflammatory pathology of the colon]. / Utilidad de la determinación sérica de microRNA-21 en la enfermedad inflamatoria del colon.

BACKGROUND: MicroRNAs are 20-22 nucleotide molecular structures with post-transcriptional activity that are involved in the immune response, as well as in the inflammatory pathways of different cells and tissues. AIMS: We present herein a prospective study in which serum microRNA-21 expression was determined in patients diagnosed with acute appendicitis as a model of bowel inflammation. MATERIAL AND METHODS: A prospective cohort study of patients diagnosed with acute appendicitis was conducted. Serum microRNA-21 was analyzed through the PCR of blood samples taken from the patients prior to surgery. MicroRNA-21 values were compared with the analytic variables (leukocytes, hemoglobin, hematocrit, platelets, prothrombin activity, glucose, urea, and creatinine) and the anatomopathologic variables (normal appendix, phlegmonous, gangrenous, and perforated acute appendicitis). RESULTS: A total of 60 patients with acute appendicitis diagnosis were consecutively included in the study from June to October 2009. Sixty-six percent of the patients were men (40 men and 20 women), with a mean age of 26.2±14.8 years. The mean absolute level of microRNA-21 was 24.8±0.93, whereas the mean microRNA-21 gene expression was 1.04±0.28. No correlation between the analytic and anatomopathologic parameters evaluated was observed (P=.47). CONCLUSIONS: It is necessary to continue to search for the most appropriate microRNAs, so that their determination in serum can lead to greater precision in establishing the diagnosis and outcome of inflammatory disorders of the bowel.

Hybrid modelling based on support vector regression with genetic algorithms in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain).

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational waters. As a result, anticipate its presence is a matter of importance to prevent risks. The aim of this study is to use a hybrid approach based on support vector regression (SVR) in combination with genetic algorithms (GAs), known as a genetic algorithm support vector regression (GA-SVR) model, in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain). The GA-SVR approach is aimed at highly nonlinear biological problems with sharp peaks and the tests carried out proved its high performance. Some physical-chemical parameters have been considered along with the biological ones. The results obtained are two-fold. In the first place, the significance of each biological and physical-chemical variable on the cyanotoxins presence in the reservoir is determined with success. Finally, a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained.

Detection of outliers in water quality monitoring samples using functional data analysis in San Esteban estuary (Northern Spain).

Water quality controls involve large number of variables and observations, often subject to some outliers. An outlier is an observation that is numerically distant from the rest of the data or that appears to deviate markedly from other members of the sample in which it occurs. An interesting analysis is to find those observations that produce measurements that are different from the pattern established in the sample. Therefore, identification of atypical observations is an important concern in water quality monitoring and a difficult task because of the multivariate nature of water quality data. Our study provides a new method for detecting outliers in water quality monitoring parameters, using oxygen and turbidity as indicator variables. Until now, methods were based on considering the different parameters as a vector whose components were their concentration values. Our approach lies in considering water quality monitoring through time as curves instead of vectors, that is to say, the data set of the problem is considered as a time-dependent function and not as a set of discrete values in different time instants. The methodology, which is based on the concept of functional depth, was applied to the detection of outliers in water quality monitoring samples in San Esteban estuary. Results were discussed in terms of origin, causes, etc., and compared with those obtained using the conventional method based on vector comparison. Finally, the advantages of the functional method are exposed.

Association of topical amphotericin B lipid complex treatment to standard therapy for rhinomaxillary mucormycosis after liver transplantation: a case report.

Solid organ transplantation is becoming increasingly more common in the treatment of end-stage organ failure. The advent of newer immunosuppressive protocols and refined surgical techniques has allowed therapy to become standard care. Infection is a major and frequently life-threatening complication after transplantation and the incidence of opportunistic fungal infections in organ transplant recipients ranges from 2%-50% depending on the type of organ transplanted. We present a case of rhinomaxillary form of mucormycosis infection after liver transplantation. The succession of multiple risk factors in a torpid postoperative period was a key factor in the development of this disease. Multidisciplinary management with an early diagnosis, aggressive surgery, and intravenous and topical antifungal therapy care were definitive for the eradication of infection. The goal of the present report was to show efficacious management including the association of topical treatment with amphotericin B complex lipid to standard therapy and the absence of side effects.

Evaluation of pre-treatment processes for increasing biodegradability of agro-food wastes.

Anaerobic digestion (AD) technology can be employed for treating sewage sludge, livestock waste or food waste. Generally, the hydrolysis stage is the rate-limiting step of the AD processes for solid waste degradation. Therefore, physical, chemical and biological pre-treatment methods or their combination are required, in order to reduce the rate of such a limiting step. In this study, four methods (mechanical shredding, acid hydrolysis, alkaline hydrolysis and sonication) were tested to improve methane production and anaerobic biodegradability of different agro-food wastes and their mixtures. The kinetics of anaerobic degradation and methane production ofpre-treated individual wastes and selected mixtures were investigated with batch tests. Sonication at lower frequencies (37 kHz) proved to give the best results with methane productivity enhancements of over 100% in the case of pig manure and in the range of 10-47% for the other wastes assayed. Furthermore, the ultimate methane production was proportional, in all the cases, to the specific energy input applied (Es). Sonication can, thus, enhance waste digestion and the rate and quantity of biogas generated. The behaviour of the other pre-treatments under the conditions assayed is not significant. Only a slight enhancement of biogas production (around 10%) was detected for whey and waste activated sludge (WAS) after mechanical shredding. The lack of effectiveness of chemical pre-treatments (acid and alkaline hydrolysis) can be justified by the inhibition of the methanogenic process due to the presence of high concentrations of sodium (up to 8 g l(-1) in some tests). Only in the case of WAS did the acid hydrolysis considerably increase the biodegradability of the sample (79%), because in this case no inhibition by sodium took place. Some hints of a synergistic effect have been observed when co-digestion of the mixtures was performed.

Biochemical methane potential (BMP) of agro-food wastes from the Cider Region (Spain).

An inventory of agro-food industry organic waste streams with a high potential for biogas transformation was studied in a logistically viable area (Cider Region, Asturias, Spain). Three industries were selected as the most viable ones: livestock, dairy and beverage. The potential for methane production from six wastes (beverage waste, BW; milled apple waste, MA; milk waste, MK; yogurt waste, YG; fats and oils from dairy wastewater treatment, F&O and cattle manure, CM) at five different substrate:inoculum ratios (0.25, 0.50, 0.75, 1.00 and 1.50) was evaluated in laboratory batch assays. Obtained methane yields ranged from 202-549 mL STP CH(4)·g VS waste(-1), and the methane content in biogas ranged from 58-76%. The ultimate practical biochemical methane potentials were slightly affected by the substrate:inoculum ratio. The estimation of the regional fluxes of waste and methane potentials suggests anaerobic digestion as a sustainable solution for the valorization of the organic wastes generated in this Region.

A new improved study of cyanotoxins presence from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain) using the MARS technique.

Cyanotoxins, a kind of poisonous substances produced by cyanobacteria, are responsible for health risks in drinking and recreational water uses. The aim of this study is to improve our previous and successful work about cyanotoxins prediction from some experimental cyanobacteria concentrations in the Trasona reservoir (Asturias, Northern Spain) using the multivariate adaptive regression splines (MARS) technique at a local scale. In fact, this new improvement consists of using not only biological variables, but also the physical-chemical ones. As a result, the coefficient of determination has improved from 0.84 to 0.94, that is to say, more accurate predictive calculations and a better approximation to the real problem were obtained. Finally the agreement of the MARS model with experimental data confirmed the good performance.

Study of cyanotoxins presence from experimental cyanobacteria concentrations using a new data mining methodology based on multivariate adaptive regression splines in Trasona reservoir (Northern Spain).

There is an increasing need to describe cyanobacteria blooms since some cyanobacteria produce toxins, termed cyanotoxins. These latter can be toxic and dangerous to humans as well as other animals and life in general. It must be remarked that the cyanobacteria are reproduced explosively under certain conditions. This results in algae blooms, which can become harmful to other species if the cyanobacteria involved produce cyanotoxins. In this research work, the evolution of cyanotoxins in Trasona reservoir (Principality of Asturias, Northern Spain) was studied with success using the data mining methodology based on multivariate adaptive regression splines (MARS) technique. The results of the present study are two-fold. On one hand, the importance of the different kind of cyanobacteria over the presence of cyanotoxins in the reservoir is presented through the MARS model and on the other hand a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained. The agreement of the MARS model with experimental data confirmed the good performance of the same one. Finally, conclusions of this innovative research are exposed.

Diffractive and reactive scattering of H2 from Ru(0001): experimental and theoretical study.

We present a combined experimental and theoretical study of the diffraction of H(2) from Ru(0001) in the incident energy range 78-150 meV, and a theoretical study of dissociative chemisorption of H(2) in the same system. Pronounced out-of-plane diffraction was observed in the whole energy range studied. The energy dependence of the elastic diffraction intensities was measured along the two main symmetry directions for a fixed parallel translational energy. The data were compared with quantum dynamics calculations performed by using DFT-based, six-dimensional potential energy surfaces calculated with both the PW91 and RPBE functionals, as well as with a functional obtained from a weighted average of both (the MIX functional, which was earlier shown to perform quite well for H(2) + Cu(111)). Our results show that the PW91 functional describes the H(2) diffraction intensities more accurately than the RPBE and the MIX functionals, although the absolute values of these intensities are overestimated in the calculations. For the reaction probabilities a preference for one or the other functional cannot be given over the entire energy range probed by the sticking experiments. The PW91 functional yields too high reaction probabilities over the entire investigated energy range, but is better than RPBE at low collision energies (<0.1 eV). The RPBE functional gives too low reaction probabilities at low energy and somewhat too high reaction probabilities at high energy, but agrees better with experiment than PW91 for energies >0.1 eV. The results suggest that, in order to get a better description of both H(2) diffraction and dissociative chemisorption for this system, a specific reaction parameter functional for H(2) + Ru(0001) is needed that is a weighted average of functionals other than PW91 and RPBE. We speculate that differences between the H(2) + Ru(0001) system (early and low reaction barrier) and H(2) + Cu(111) (late and high reaction barrier) may well lead to fundamentally different specific reaction parameter functionals, and that including a reasonable accurate description of the van der Waals interaction might be important for H(2) + Ru(0001) which has barriers localised far away from the surface. Based on our results we advocate new, systematic combined theoretical and experimental studies of H(2) interacting with transition metals in early and late barrier systems, with the aim of determining whether specific reaction parameter functionals for these systems might differ in a systematic way.

Detection of outliers in gas emissions from urban areas using functional data analysis.

In this work a solution for the problem of the detection of outliers in gas emissions in urban areas that uses functional data analysis is described. Different methodologies for outlier identification have been applied in air pollution studies, with gas emissions considered as vectors whose components are gas concentration values for each observation made. In our methodology we consider gas emissions over time as curves, with outliers obtained by a comparison of curves instead of vectors. The methodology, which is based on the concept of functional depth, was applied to the detection of outliers in gas omissions in the city of Oviedo and results were compared with those obtained using a conventional method based on a comparison of vectors. Finally, the advantages of the functional method are reported.

NMR structural studies of oligosaccharides related to cancer processes.

A summary of spectroscopic methods for structural and conformational elucidation of bioactive carbohydrates based on nuclear magnetic resonance (NMR) is described. The formation of carbohydrate-protein complexes is often the initial step of biological responses. Therefore, knowledge about the structural factors that stabilize the complex may be relevant and contribute to predict the structural/conformational requirements of new drugs acting as agonists. Two examples of medical significance in the cancer research field are discussed (1) conformational studies of glycoconjugates related to antitumour vaccines (2) conformational analysis of glycosaminoglycans and the interaction heparin-fibroblast growth factor (FGF).