Identification of miRNAs from French bean (Phaseolus vulgaris) under low nitrate stress

Objective: In this study, we report the role of miRNAs involved under nitrogen starvation from widely grown vegetable crop, French bean. In recent years, a great deal of attention has been paid to the elucidation of miRNAs involved in low nitrate stress. Methods: To identify miRNAs expressed under stress, cDNA libraries were analyzed. Results: We reported the nine potential miRNAs with 67 targets involved in nutrient transporters and other stress specific genes. Among the miRNA sequences obtained 6 sequences belong to miR172 family, one with miR169. RT-PCR analysis of expression of miR172 family was induced upon low nitrate stress while miR169 family was repressed. In addition, Pvu-SN7b and Pvu-miR16 may be new members of miRNA172 and miR169 families, respectively. Conclusion: The targets of Pvu-SN7b were major protein kinases, one among which is the Protein Kinase CK2. CK2 Kinase is found to involve in transcription-directed signaling, gene control and cell-cycle regulation. Other targets of Pvu-SN7b were involved in DNA-dependent transcription regulation, photo-periodism, calcium-mediated signaling. Pvu-miR16 targets Thymidine kinase, the key enzyme of deoxy-nucleotide synthesis. The cleavage of these targets affects cell proliferation there by affecting nodule formation. Pvu-miR8 inhibits translation of its target protein Pre-protein translocase, a membrane-bound protein transporter involved in trans-membrane protein transportation. Together these results denote the response and role of miRNAs to nitrate-limiting conditions in French bean.

Role of Monoubiquitylation on the Control of IκBα Degradation and NF-κB Activity

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High-Throughput Sequencing of microRNAs in Peripheral Blood Mononuclear Cells: Identification of Potential Weight Loss Biomarkers

INTRODUCTION: MicroRNAs (miRNAs) are being increasingly studied in relation to energy metabolism and body composition homeostasis. Indeed, the quantitative analysis of miRNAs expression in different adiposity conditions may contribute to understand the intimate mechanisms participating in body weight control and to find new biomarkers with diagnostic or prognostic value in obesity management. OBJECTIVE: The aim of this study was the search for miRNAs in blood cells whose expression could be used as prognostic biomarkers of weight loss. METHODS: Ten Caucasian obese women were selected among the participants in a weight-loss trial that consisted in following an energy-restricted treatment. Weight loss was considered unsuccessful when <5% of initial body weight (non-responders) and successful when >5% (responders). At baseline, total miRNA isolated from peripheral blood mononuclear cells (PBMC) was sequenced with SOLiD v4. The miRNA sequencing data were validated by RT-PCR. RESULTS: Differential baseline expression of several miRNAs was found between responders and non-responders. Two miRNAs were up-regulated in the non-responder group (mir-935 and mir-4772) and three others were down-regulated (mir-223, mir-224 and mir-376b). Both mir-935 and mir-4772 showed relevant associations with the magnitude of weight loss, although the expression of other transcripts (mir-874, mir-199b, mir-766, mir-589 and mir-148b) also correlated with weight loss. CONCLUSIONS: This research addresses the use of high-throughput sequencing technologies in the search for miRNA expression biomarkers in obesity, by determining the miRNA transcriptome of PBMC. Basal expression of different miRNAs, particularly mir-935 and mir-4772, could be prognostic biomarkers and may forecast the response to a hypocaloric diet.

Probabilistic robust control : theory and applications

In this work, the development of a probabilistic approach to robust control is motivated by structural control applications in civil engineering. Often in civil structural applications, a system's performance is specified in terms of its reliability. In addition, the model and input uncertainty for the system may be described most appropriately using probabilistic or "soft" bounds on the model and input sets. The probabilistic robust control methodology contrasts with existing H∞/μ robust control methodologies that do not use probability information for the model and input uncertainty sets, yielding only the guaranteed (i.e., "worst-case") system performance, and no information about the system's probable performance which would be of interest to civil engineers.

The design objective for the probabilistic robust controller is to maximize the reliability of the uncertain structure/controller system for a probabilistically-described uncertain excitation. The robust performance is computed for a set of possible models by weighting the conditional performance probability for a particular model by the probability of that model, then integrating over the set of possible models. This integration is accomplished efficiently using an asymptotic approximation. The probable performance can be optimized numerically over the class of allowable controllers to find the optimal controller. Also, if structural response data becomes available from a controlled structure, its probable performance can easily be updated using Bayes's Theorem to update the probability distribution over the set of possible models. An updated optimal controller can then be produced, if desired, by following the original procedure. Thus, the probabilistic framework integrates system identification and robust control in a natural manner.

The probabilistic robust control methodology is applied to two systems in this thesis. The first is a high-fidelity computer model of a benchmark structural control laboratory experiment. For this application, uncertainty in the input model only is considered. The probabilistic control design minimizes the failure probability of the benchmark system while remaining robust with respect to the input model uncertainty. The performance of an optimal low-order controller compares favorably with higher-order controllers for the same benchmark system which are based on other approaches. The second application is to the Caltech Flexible Structure, which is a light-weight aluminum truss structure actuated by three voice coil actuators. A controller is designed to minimize the failure probability for a nominal model of this system. Furthermore, the method for updating the model-based performance calculation given new response data from the system is illustrated.

Diseño del procedimiento para la validación de los equipos de un sistema de control de acceso de RFID pasivo

[ES]En este documento se realiza el diseño de un procedimiento para la validación de los equipos necesarios a la hora de implantar un sistema de control de acceso mediante RFID pasivo. Para ello, se analizarán los distintos tipos de sistemas RFID y se elige uno para la posterior adquisición de los dispositivos necesarios. Se comprobará la normativa vigente ETSI, que regula las emisiones de potencia de los equipos de identificación por radiofrecuencia, y se verificará que se cumplen los requisitos necesarios para implantar el sistema de control de acceso realizando un análisis funcional en situaciones reales.

Recent progress in the identification and determination of freshwater phytoplankton in the natural environment

The biomass of the phytoplankton and its composition is one of the most important factors in water quality control. Determination of the phytoplankton assemblage is usually done by microscopic analysis (Utermöhl's method). Quantitative estimations of the biovolume, by cell counting and cell size measurements, are time-consuming and normally are not done in routine water quality control. Several alternatives have been tried: computer-based image analysis, spectral fluorescence signatures, flow cytometry and pigment fingerprinting aided by high performance liquid chromatography (HPLC). The latter method is based on the fact that each major algal group of taxa contains a specific carotenoid which can be used for identification and relative quantification of the taxa in the total assemblage. This article gives a brief comparative introduction to the different techniques available and presents some recent results obtained by HPLC-based pigment fingerprinting, applied to three lakes of different trophic status. The results show that this technique yields reliable results from different lake types and is a powerful tool for studying the distribution pattern of the phytoplankton community in relation to water depth. However, some restrictions should be taken into account for the interpretation of routine data.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.