Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.

No-reference image quality assessment using modified extreme learning machine classifier

In this paper, we present a machine learning approach to measure the visual quality of JPEG-coded images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity (HVS) factors such as edge amplitude, edge length, background activity and background luminance. Image quality assessment involves estimating the functional relationship between HVS features and subjective test scores. The quality of the compressed images are obtained without referring to their original images ('No Reference' metric). Here, the problem of quality estimation is transformed to a classification problem and solved using extreme learning machine (ELM) algorithm. In ELM, the input weights and the bias values are randomly chosen and the output weights are analytically calculated. The generalization performance of the ELM algorithm for classification problems with imbalance in the number of samples per quality class depends critically on the input weights and the bias values. Hence, we propose two schemes, namely the k-fold selection scheme (KS-ELM) and the real-coded genetic algorithm (RCGA-ELM) to select the input weights and the bias values such that the generalization performance of the classifier is a maximum. Results indicate that the proposed schemes significantly improve the performance of ELM classifier under imbalance condition for image quality assessment. The experimental results prove that the estimated visual quality of the proposed RCGA-ELM emulates the mean opinion score very well. The experimental results are compared with the existing JPEG no-reference image quality metric and full-reference structural similarity image quality metric.

Bauer Method of MVDR Spectral Factorization for Pitch Modification in the Source Domain

In our earlier work [1], we employed MVDR (minimum variance distortionless response) based spectral estimation instead of modified-linear prediction method [2] in pitch modification. Here, we use the Bauer method of MVDR spectral factorization, leading to a causal inverse filter rather than a noncausal filter setup with MVDR spectral estimation [1]. Further, this is employed to obtain source (or residual) signal from pitch synchronous speech frames. The residual signal is resampled using DCT/IDCT depending on the target pitch scale factor. Finally, forward filters realized from the above factorization are used to get pitch modified speech. The modified speech is evaluated subjectively by 10 listeners and mean opinion scores (MOS) are tabulated. Further, modified bark spectral distortion measure is also computed for objective evaluation of performance. We find that the proposed algorithm performs better compared to time domain pitch synchronous overlap [3] and modified-LP method [2]. A good MOS score is achieved with the proposed algorithm compared to [1] with a causal inverse and forward filter setup.

A new glucose: Towards conformationally locked flexoses through annulation

A new family of surf ace-modified carbohydrates with locked, axial-rich conformations and bipolarofacial architectures has been developed with the aid of carbocyclic ring annulation. These novel trans-decalin-based carbohydrates have been synthesized, from simple aromatic precursors such as tetralin, through the ozonolysis of an appropriately protected allylic alcohol, followed by a cascade of intramolecular acetalizations to generate the sugar pyran moiety. The stereoselective synthesis of (racemic) cyclohexane-annulated 0-glucopyranoside and a-glucofuranoside from a common annulated trans-cyclohexadiene diol (trans-CHD) precursor under-scores the versatility of our approach. The efficacy of the annulation stratagem in generating carbohydrate diversity has been demonstrated through the synthesis of two regioisomeric annulated gulose derivatives, which differ only in the site of ring annulation on the sugar moiety. The mapping of the MLP surface and solid-state architecture of the new sugar shows that cycloalkane annulation results in surface modification and fine-tuning of sugar hydrophilicity. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005).

A new glucose: Towards conformationally locked flexoses through annulation

A new family of surf ace-modified carbohydrates with locked, axial-rich conformations and bipolarofacial architectures has been developed with the aid of carbocyclic ring annulation. These novel trans-decalin-based carbohydrates have been synthesized, from simple aromatic precursors such as tetralin, through the ozonolysis of an appropriately protected allylic alcohol, followed by a cascade of intramolecular acetalizations to generate the sugar pyran moiety. The stereoselective synthesis of (racemic) cyclohexane-annulated 0-glucopyranoside and a-glucofuranoside from a common annulated trans-cyclohexadiene diol (trans-CHD) precursor under-scores the versatility of our approach. The efficacy of the annulation stratagem in generating carbohydrate diversity has been demonstrated through the synthesis of two regioisomeric annulated gulose derivatives, which differ only in the site of ring annulation on the sugar moiety. The mapping of the MLP surface and solid-state architecture of the new sugar shows that cycloalkane annulation results in surface modification and fine-tuning of sugar hydrophilicity. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005).

GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

HARMONY: a server for the assessment of protein structures

Protein structure validation is an important step in computational modeling and structure determination. Stereochemical assessment of protein structures examine internal parameters such as bond lengths and Ramachandran (phi, psi) angles. Gross structure prediction methods such as inverse folding procedure and structure determination especially at low resolution can sometimes give rise to models that are incorrect due to assignment of misfolds or mistracing of electron density maps. Such errors are not reflected as strain in internal parameters. HARMONY is a procedure that examines the compatibility between the sequence and the structure of a protein by assigning scores to individual residues and their amino acid exchange patterns after considering their local environments. Local environments are described by the backbone conformation, solvent accessibility and hydrogen bonding patterns. We are now providing HARMONY through a web server such that users can submit their protein structure files and, if required, the alignment of homologous sequences. Scores are mapped on the structure for subsequent examination that is useful to also recognize regions of possible local errors in protein structures. HARMONY server is located at http://caps.ncbs.res.in/harmony/

sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes

Background:Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. Methodology/Principal Findings: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. Conclusions/Significance: We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that similar to 40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.

Classification of Protein Kinases on the Basis of Both Kinase and Non-Kinase Regions

Background: Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multidomain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies. Methodology: Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. Conclusions: The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multidomain architecture.

An algorithm to find distant repeats in a pair of protein sequences

Distant repeats between a pair of protein sequences can be exploited to study the various aspects of proteins such as structure-function relationship, disorders due to protein malfunction, evolutionary analysis, etc. An in-depth analysis of the distant repeats would facilitate to establish a stable evolutionary relation of the repeats with respect to their three-dimensional structure. To this effect, an algorithm has been devised to identify the distant repeats in a pair of protein sequences by essentially using the scores of PAM (Percent Accepted Mutation) matrices. The proposed algorithm will be of much use to researchers involved in the comparative study of various organisms based on the amino-acid repeats in protein sequences. (C) 2010 Elsevier B.V. All rights reserved.

Allergenic Cross-Reactivity between Parthenium and Ragweed Pollen Allergens

Cross-reactivity of allergens from the pollen of the Compositae weeds, Parthenium hysterophorus (American feverfew) and Ambrosia (ragweed), in 2 groups of patients with different geographic distributions was studied. Parthenium-sensitive Indian patients, who were never exposed to ragweed, elicited positive skin reactions with ragweed pollen extracts. A significant correlation in the RAST scores of Parthenium and ragweed-specific IgE was observed with the sera of Parthenium and ragweed-sensitive Indian and US patients, respectively. RAST inhibition experiments demonstrated that the binding of IgE antibodies in the sera of ragweed-sensitive patients to short (Wl) and giant (W3) ragweed allergen discs could be inhibited by up to 94% by Parthenium pollen extracts. Similar inhibition (up to 82%) was obtained when the sera of Parthenium rhinitis patients were incubated with ragweed allergen extracts. A dose-dependent proliferation of lymphocytes from a Parthenium-sensitive rhinitis patient with elevated levels of both Parthenium and ragweed-specific IgE was observed when incubated with Parthenium and ragweed pollen extracts. A 1.6-fold higher proliferation, however, was observed with Parthenium pollen extract at a concentration of 100 µg/ml. These results suggest that shared epitopes present on Parthenium and ragweed pollen allergens are recognized by both Indian and US patients sensitized by exposure to Parthenium and ragweed pollen, respectively. The high degree of cross-reactivity between Parthenium and ragweed pollen allergens suggests that individuals sensitized to Parthenium may develop type-I hypersensitivity reactions to ragweed and vice versa when they travel to regions infested with the weed to which they had not been previously exposed.

Effect of altering endogenous gonadotrophin concentrations on the kinetics of testicular germ cell turnover in the bonnet monkey (Macaca radiata)

The role of FSH and diurnal testosterone rhythms in specific germ cell transformations during spermatogenesis were investigated using DNA flow cytometry and morphometry of the seminiferous epithelium of the adult male bonnet monkey (Macaca radiata), the endogenous hormone levels of which were altered by two different protocols. (1) Active immunization of five monkeys for 290 days using ovine FSH adsorbed on Alhydrogel resulted in the neutralization of endogenous FSH, leaving the LH and diurnal testosterone rhythms normal. (2) Desensitization of the pituitary gonadotrophs of ten monkeys by chronically infusing gonadotrophin-releasing hormone analogue, buserelin (50 micrograms/day release rate), via an Alzet pump implant (s.c.) led to a 60-80% reduction in LH and FSH as well as total abolition of testosterone rhythms. The basal testosterone level (3.3 +/- 2.0 micrograms/l), however, was maintained in this group by way of an s.c. testosterone silicone elastomer implant. Both of the treatments caused significant (P < 0.01) nearly identical reduction in testicular biopsy scores, mitotic indices and daily sperm production rates compared with respective controls. The germ cell DNA flow cytometric profiles of the two treatment groups, however, were fundamentally different from each other. The pituitary-desensitized group exhibited a significant (P < 0.001) increase in 2C (spermatogonial) and decrease in 1C (round spermatid) populations while S-phase (preleptotene spermatocytes) and 4C (primary spermatocytes) populations were normal, indicating an arrest in meiosis caused presumably by the lack of increment in nocturnal serum testosterone. In contrast, in the FSH-immunized group, at day 80 when the FSH deprivation was total, the primary block appeared to be at the conversion of spermatogonia (2C) to cells in S-phase and primary spermatocytes (4C reduced by > 90%). In addition, at this time, although the round spermatid (1C) population was reduced by 65% (P < 0.01) the elongate spermatid (HC) population showed an increase of 52% (P < 0.05). This, taken together with the fact that sperm output in the ejaculate is reduced by 80%, suggests a blockade in spermiogenesis and spermiation. Administration of booster injections of oFSH at time-points at which the antibody titre was markedly low (at days 84 and 180) resulted in a transient resurgence in spermatogenesis (at day 180 and 228), and this again was blocked by day 290 when the FSH antibody titre increased.

Molecular systematics and conservation of the langurs and leaf monkeys of South Asia

Numerous morphology-based classification schemes have been proposed for langurs and leaf monkeys of South Asia but there is very little agreement between them. An incorrect classification scheme when used as a basis for biogeographic studies can support erroneous hypotheses. Further, lack of taxonomic resolution will also confound conservation efforts, given that conservation biologists use traditional morphology-based-classification schemes to prioritize species for conservation. Here, I have revisited recent molecular phylogenetic studies done on langurs and leaf monkeys of South Asia. Results from these studies are in turn used to derive a rational and scientific basis for prioritizing species for conservation. Molecular data support the classification of langurs of the Indian subcontinent-Hanuman, Nilgiri and purple-faced langurs-in the genus Semnopithecus, whereas Phayre's leaf monkey along with other Southeast Asian leaf monkeys form another distinct clade (Trachypithecus). The phylogenetic position of capped and golden langurs remains unresolved. Molecular data suggest that they are closely related to each other but this group might have evolved through past hybridization between Semnopithecus and Trachypithecus. Additionally, genetic data also support the splitting of the so-called Hanuman langurs into at least three species. The scores for taxonomic uniqueness of langurs and leaf monkeys of South Asia were revised using this molecular phylogeny-based classification. According to the revised scores, Phayres leaf monkey and golden langur are priority species for conservation followed by capped and Nilgiri langurs.

A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

Recovery of tropical rainforest avifauna in relation to vegetation succession following shifting cultivation in Mizoram, north-east India

1. Recovery of rainforest bird community structure and composition, in relation to forest succession after slash-and-burn shifting cultivation or jhum was studied in Mizoram, north-east India. Replicate fallow sites abandoned after shifting cultivation 1, 5, 10, 25 and approximate to 100 years ago, were compared with primary evergreen and semi-evergreen forest using transect and quadrat sampling. 2. Vegetation variables such as woody plant species richness, tree density and vertical stratification increased with fallow age in a rapid. nun-linear, asymptotic manner. Principal components analysis of vegetation variables summarized 92.8% of the variation into two axes: PC1 reflecting forest development and woody plant succession (variables such as tree density, woody plant species richness), and PC2 depicting bamboo density, which increased from 1 to 25 years and declined thereafter. 3. Bird species richness, abundance and diversity, increased rapidly and asymptotically during succession paralleling vegetation recovery as shown by positive correlations with fallow age and PC1 scores of sites. Bamboo density reflected by PC2 had a negative effect on bird species richness and abundance. 4. The bird community similarity (Morisita index) of sites with primary forest also increased asymptotically with fallow age indicating sequential species turnover during succession. Bird community similarity of sites with primary forest (or between sites) was positively correlated with both physiognomic and floristic similarities with primary forest (or between sites). 5. The number of bird species in guilds associated with forest development and woody plants (canopy insectivores, frugivores: bark feeders) was correlated with PCI scores of the sites. Species in other guilds (e. g. granivores, understorey insectivores) appeared to dominate during early and mid-succession. 6. The non-linear relationships imply that fallow periods less than a threshold of 25 years for birds, and about 50-75 years for woody plants, are likely to cause substantial community alteration. 7. As 5-10-year rotation periods or jhum cycles prevail in many parts of north-east India. there is a need to protect and conserve tracts of late-successional and primary forest.