The translation initiation factor DAP5 promotes IRES-driven translation of p53 mRNA

Translational regulation of the p53 mRNA can determine the ratio between p53 and its N-terminal truncated isoforms and therefore has a significant role in determining p53-regulated signaling pathways. Although its importance in cell fate decisions has been demonstrated repeatedly, little is known about the regulatory mechanisms that determine this ratio. Two internal ribosome entry sites (IRESs) residing within the 5'UTR and the coding sequence of p53 mRNA drive the translation of full-length p53 and Delta 40p53 isoform, respectively. Here, we report that DAP5, a translation initiation factor shown to positively regulate the translation of various IRES containing mRNAs, promotes IRES-driven translation of p53 mRNA. Upon DAP5 depletion, p53 and Delta 40p53 protein levels were decreased, with a greater effect on the N-terminal truncated isoform. Functional analysis using bicistronic vectors driving the expression of a reporter gene from each of these two IRESs indicated that DAP5 preferentially promotes translation from the second IRES residing in the coding sequence. Furthermore, p53 mRNA expressed from a plasmid carrying this second IRES was selectively shifted to lighter polysomes upon DAP5 knockdown. Consequently, Delta 40p53 protein levels and the subsequent transcriptional activation of the 14-3-3 sigma gene, a known target of Delta 40p53, were strongly reduced. In addition, we show here that DAP5 interacts with p53 IRES elements in in vitro and in vivo binding studies, proving for the first time that DAP5 directly binds a target mRNA. Thus, through its ability to regulate IRES-dependent translation of the p53 mRNA, DAP5 may control the ratio between different p53 isoforms encoded by a single mRNA.

A Committee Machine Approach for Compressed Sensing Signal Reconstruction

Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.

Medium-Voltage Drive for Induction Machine With Multilevel Dodecagonal Voltage Space Vectors With Symmetric Triangles

Multilevel inverters with dodecagonal (12-sided polygon) voltage space vector structure have advantages, such as complete elimination of fifth and seventh harmonics, reduction in electromagnetic interference, reduction in device voltage ratings, reduction of switching frequency, extension of linear modulation range, etc., making it a viable option for high-power medium-voltage drives. This paper proposes two power circuit topologies capable of generating multilevel dodecagonal voltage space vector structure with symmetric triangles (for the first time) with minimum number of dc-link power supplies and floating capacitor H-bridges. The first power topology is composed of two hybrid cascaded five-level inverters connected to either side of an open-end winding induction machine. Each inverter consists of a three-level neutral-point-clamped inverter, which is cascaded with an isolated H-bridge making it a five-level inverter. The second topology is for a normal induction motor. Both of these circuit topologies have inherent capacitor balancing for floating H-bridges for all modulation indexes, including transient operations. The proposed topologies do not require any precharging circuitry for startup. A simple pulsewidth modulation timing calculation method for space vector modulation is also presented in this paper. Due to the symmetric arrangement of congruent triangles within the voltage space vector structure, the timing computation requires only the sampled reference values and does not require any offline computation, lookup tables, or angle computation. Experimental results for steady-state operation and transient operation are also presented to validate the proposed concept.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Accurate Steady-State Representation of a Doubly Fed Induction Machine

This letter presents an accurate steady-state phasor model for a doubly fed induction machine. The drawback of existing steady-state phasor model is discussed. In particular, the inconsistency of existing equivalent model with respect to reactive power flows when operated at supersynchronous speeds is highlighted. Relevant mathematical basis for the proposed model is presented and its validity is illustrated on a 2-MW doubly fed induction machine.

Damage quantification under sliding and seizure condition using first-of-a-kind fretting machine

In a practical situation, it is difficult to model exact contact conditions clue to challenges involved in the estimation of contact forces, and relative displacements between the contacting bodies. Sliding and seizure conditions were simulated on first-of-a-kind displacement controlled system. Self-mated stainless steels have been investigated in detail. Categorization of contact conditions prevailing at the contact interface has been carried out based on the variation of coefficient of friction with number of cycles, and three-dimensional fretting loops. Surface and subsurface micro-cracks have been observed, and their characteristic shows strong dependence on loading conditions. Existence of shear bands in the subsurface region has been observed for high strain and low strain rate loading conditions. Studies also include the influence of initial surface roughness on the damage under two extreme contact conditions. (C) 2013 Elsevier B.V. All rights reserved.

Is the cellular initiation of translation an exclusive property of the initiator tRNAs?

Translation of mRNAs is the primary function of the ribosomal machinery. Although cells allow for a certain level of translational errors/mistranslation (which may well be a strategic need), maintenance of the fidelity of translation is vital for the cellular function and fitness. The P-site bound initiator tRNA selects the start codon in an mRNA and specifies the reading frame. A direct P-site binding of the initiator tRNA is a function of its special structural features, ribosomal elements, and the initiation factors. A highly conserved feature of the 3 consecutive G:C base pairs (3GC pairs) in the anticodon stem of the initiator tRNAs is vital in directing it to the P-site. Mutations in the 3GC pairs diminish/abolish initiation under normal physiological conditions. Using molecular genetics approaches, we have identified conditions that allow initiation with the mutant tRNAs in Escherichia coli. During our studies, we have uncovered a novel phenomenon of in vivo initiation by elongator tRNAs. Here, we recapitulate how the cellular abundance of the initiator tRNA, and nucleoside modifications in rRNA are connected with the tRNA selection in the P-site. We then discuss our recent finding of how a conserved feature in the mRNA, the Shine-Dalgarno sequence, influences tRNA selection in the P-site.

Translation Induction on Indian Language Corpora Using Translingual Themes from Other Languages

Identifying translations from comparable corpora is a well-known problem with several applications, e.g. dictionary creation in resource-scarce languages. Scarcity of high quality corpora, especially in Indian languages, makes this problem hard, e.g. state-of-the-art techniques achieve a mean reciprocal rank (MRR) of 0.66 for English-Italian, and a mere 0.187 for Telugu-Kannada. There exist comparable corpora in many Indian languages with other ``auxiliary'' languages. We observe that translations have many topically related words in common in the auxiliary language. To model this, we define the notion of a translingual theme, a set of topically related words from auxiliary language corpora, and present a probabilistic framework for translation induction. Extensive experiments on 35 comparable corpora using English and French as auxiliary languages show that this approach can yield dramatic improvements in performance (e.g. MRR improves by 124% to 0.419 for Telugu-Kannada). A user study on WikiTSu, a system for cross-lingual Wikipedia title suggestion that uses our approach, shows a 20% improvement in the quality of titles suggested.

Alternate Proof for Steady-State Equivalent Circuit of a Doubly Fed Induction Machine

This letter presents an alternate proof for the steady-state equivalent circuit of a doubly fed induction machine operating at supersynchronous speeds. The spatial orientation of rotating magnetic fields is used to validate the conjugation of rotor side quantities arising in supersynchronous mode. The equivalent circuit is further validated using dynamic simulations of a stand-alone machine.