Simultaneous nonvanishing of Dirichlet L-functions and twists of Hecke-Maass L-functions

We prove that given a Hecke-Maass form f for SL(2, Z) and a sufficiently large prime q, there exists a primitive Dirichlet character chi of conductor q such that the L-values L(1/2, f circle times chi) and L(1/2, chi) do not vanish.

Chronic lung infection by Pseudomonas aeruginosa biofilm is cured by L-Methionine in combination with antibiotic therapy

Bacterial biofilms are associated with 80-90% of infections. Within the biofilm, bacteria are refractile to antibiotics, requiring concentrations >1,000 times the minimum inhibitory concentration. Proteins, carbohydrates and DNA are the major components of biofilm matrix. Pseudomonas aeruginosa (PA) biofilms, which are majorly associated with chronic lung infection, contain extracellular DNA (eDNA) as a major component. Herein, we report for the first time that L-Methionine (L-Met) at 0.5 mu M inhibits Pseudomonas aeruginosa (PA) biofilm formation and disassembles established PA biofilm by inducing DNase expression. Four DNase genes (sbcB, endA, eddB and recJ) were highly up-regulated upon L-Met treatment along with increased DNase activity in the culture supernatant. Since eDNA plays a major role in establishing and maintaining the PA biofilm, DNase activity is effective in disrupting the biofilm. Upon treatment with L-Met, the otherwise recalcitrant PA biofilm now shows susceptibility to ciprofloxacin. This was reflected in vivo, in the murine chronic PA lung infection model. Mice treated with L-Met responded better to antibiotic treatment, leading to enhanced survival as compared to mice treated with ciprofloxacin alone. These results clearly demonstrate that L-Met can be used along with antibiotic as an effective therapeutic against chronic PA biofilm infection.

Evidence for N-7 guanine methyl transferase activity encoded within the modular domain of RNA-dependent RNA polymerase L of a Morbillivirus

Post-transcriptional modification of viral mRNA is essential for the translation of viral proteins by cellular translation machinery. Due to the cytoplasmic replication of Paramyxoviruses, the viral-encoded RNA-dependent RNA polymerase (RdRP) is thought to possess all activities required for mRNA capping and methylation. In the present work, using partially purified recombinant RNA polymerase complex of rinderpest virus expressed in insect cells, we demonstrate the in vitro methylation of capped mRNA. Further, we show that a recombinant C-terminal fragment (1717-2183 aa) of L protein is capable of methylating capped mRNA, suggesting that the various post-transcriptional activities of the L protein are located in independently folding domains.

Comparative sequence analyses of genome and transcriptome reveal novel transcripts and variants in the Asian elephant Elephas maximus

The Asian elephant Elephas maximus and the African elephant Loxodonta africana that diverged 5-7 million years ago exhibit differences in their physiology, behaviour and morphology. A comparative genomics approach would be useful and necessary for evolutionary and functional genetic studies of elephants. We performed sequencing of E. maximus and map to L. africana at similar to 15X coverage. Through comparative sequence analyses, we have identified Asian elephant specific homozygous, non-synonymous single nucleotide variants (SNVs) that map to 1514 protein coding genes, many of which are involved in olfaction. We also present the first report of a high-coverage transcriptome sequence in E. maximus from peripheral blood lymphocytes. We have identified 103 novel protein coding transcripts and 66-long non-coding (lnc)RNAs. We also report the presence of 181 protein domains unique to elephants when compared to other Afrotheria species. Each of these findings can be further investigated to gain a better understanding of functional differences unique to elephant species, as well as those unique to elephantids in comparison with other mammals. This work therefore provides a valuable resource to explore the immense research potential of comparative analyses of transcriptome and genome sequences in the Asian elephant.

Fingerprinting environmental conditions and related stress using stable isotopic composition of rice (Oryza sativa L.) grain organic matter

Sea level rise (SLR) is a primary factor responsible for inundation of low-lying coastal regions across the world, which in turn governs the agricultural productivity. In this study, rice (Oryza sativa L.) cultivated seasonally in the Kuttanad Wetland, a SLR prone region on the southwest coast of India, were analysed for oxygen, hydrogen and carbon isotopic ratios (delta O-18, delta H-2 and delta C-13) to distinguish the seasonal environmental conditions prevalent during rice cultivation. The region receives high rainfall during the wet season which promotes large supply of fresh water to the local water bodies via the rivers. In contrast, during the dry season reduced river discharge favours sea water incursion which adversely affects the rice cultivation. The water for rice cultivation is derived from regional water bodies that are characterised by seasonal salinity variation which co-varies with the delta O-18 and delta H-2 values. Rice cultivated during the wet and the dry season bears the isotopic imprints of this water. We explored the utility of a mechanistic model to quantify the contribution of two prominent factors, namely relative humidity and source water composition in governing the seasonal variation in oxygen isotopic composition of rice grain OM. delta C-13 values of rice grain OM were used to deduce the stress level by estimating the intrinsic water use efficiency (WUEi) of the crop during the two seasons. 1.3 times higher WUE, was exhibited by the same genotype during the dry season. The approach can be extended to other low lying coastal agro-ecosystems to infer the growth conditions of cultivated crops and can further be utilised for retrieving paleo-environmental information from well preserved archaeological plant remains. (c) 2015 Elsevier Ltd. All rights reserved.

Folding of Protein L with Implications for Collapse in the Denatured State Ensemble

A fundamental question in protein folding is whether the coil to globule collapse transition occurs during the initial stages of folding (burst phase) or simultaneously with the protein folding transition. Single molecule fluorescence resonance energy transfer (FRET) and small-angle X-ray scattering (SAXS) experiments disagree on whether Protein L collapse transition occurs during the burst phase of folding. We study Protein L folding using a coarse-grained model and molecular dynamics simulations. The collapse transition in Protein L is found to be concomitant with the folding transition. In the burst phase of folding, we find that FRET experiments overestimate radius of gyration, R-g, of the protein due to the application of Gaussian polymer chain end-to-end distribution to extract R-g from the FRET efficiency. FRET experiments estimate approximate to 6 angstrom decrease in R-g when the actual decrease is approximate to 3 angstrom on guanidinium chloride denaturant dilution from 7.5 to 1 M, thereby suggesting pronounced compaction in the protein dimensions in the burst phase. The approximate to 3 angstrom decrease is close to the statistical uncertainties of the R-g data measured from SAXS experiments, which suggest no compaction, leading to a disagreement with the FRET experiments. The transition-state ensemble (TSE) structures in Protein L folding are globular and extensive in agreement with the Psi-analysis experiments. The results support the hypothesis that the TSE of single domain proteins depends on protein topology and is not stabilized by local interactions alone.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

Discovering compressing serial episodes from event sequences

Most pattern mining methods yield a large number of frequent patterns, and isolating a small relevant subset of patterns is a challenging problem of current interest. In this paper, we address this problem in the context of discovering frequent episodes from symbolic time-series data. Motivated by the Minimum Description Length principle, we formulate the problem of selecting relevant subset of patterns as one of searching for a subset of patterns that achieves best data compression. We present algorithms for discovering small sets of relevant non-redundant episodes that achieve good data compression. The algorithms employ a novel encoding scheme and use serial episodes with inter-event constraints as the patterns. We present extensive simulation studies with both synthetic and real data, comparing our method with the existing schemes such as GoKrimp and SQS. We also demonstrate the effectiveness of these algorithms on event sequences from a composable conveyor system; this system represents a new application area where use of frequent patterns for compressing the event sequence is likely to be important for decision support and control.

Molecular phylogeny of Glyphochloa (Poaceae, Panicoideae), an endemic grass genus from the Western Ghats, India

The genus Glyphochloa (Poaceae: Panicoideae: Andropogoneae: Rottboellinae) is endemic to peninsular India and is distributed on lateritic plateaus of low and high altitude in and around Western Ghats and the Malabar Coast. The genus presumably originated and diversified in the Western Ghats. Species relationships in the genus Glyphochloa were deduced here based on molecular phylogenies inferred using nuclear ribosomal ITS sequences and plastid intergenic spacer regions (atpB-rbcL, trnT-trnL, trnL-trnF), and new observations were made of spikelet morphology, caryopsis morphology and meiotic chromosome counts. We observed two distinct clades of Glyphochloa s.l. One of these (group I') includes Ophiuros bombaiensis, and is characterized by a single-awned lower glume and a base chromosome number of 6; it grows in low elevation coastal areas. The other clade (group II') has a double-awned lower glume, a base chromosome number of 7, and is restricted to higher elevation lateritic plateaus; G. ratnagirica may belong to the group II clade, or may be a third distinct lineage in the genus. A sister-group relationship between group I and II taxa (with or without G. ratnagirica) is not well supported, although the genus is recovered as monophyletic in shortest trees inferred using ITS or concatenated plastid data. We present a key to species of Glyphochloa and make a new combination for O. bombaiensis.