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BackgroundIdentifying risk factors for poor outcomes can help with risk stratification and targeting of treatment. Risk factors for mortality and exacerbations have been identified in bronchiectasis but have been almost exclusively studied in European and North American populations. This study investigated the risk factors for poor outcome in a large population of bronchiectasis patients enrolled in India.MethodsThe European Multicentre Bronchiectasis Audit and Research Collaboration (EMBARC) and Respiratory Research Network of India (EMBARC-India) registry is a prospective observational study of adults with computed tomography-confirmed bronchiectasis enrolled at 31 sites across India. Baseline characteristics of patients were used to investigate associations with key clinical outcomes: mortality, severe exacerbations requiring hospital admission, overall exacerbation frequency and decline in forced expiratory volume in 1 s.Results1018 patients with at least 12-month follow-up data were enrolled in the follow-up study. Frequent exacerbations (≥3 per year) at baseline were associated with an increased risk of mortality (hazard ratio (HR) 3.23, 95% CI 1.39–7.50), severe exacerbations (HR 2.71, 95% CI 1.92–3.83), future exacerbations (incidence rate ratio (IRR) 3.08, 95% CI 2.36–4.01) and lung function decline. Coexisting COPD, dyspnoea and current cigarette smoking were similarly associated with a worse outcome across all end-points studied. Additional predictors of mortality and severe exacerbations were increasing age and cardiovascular comorbidity. Infection with Gram-negative pathogens (predominantlyKlebsiella pneumoniae) was independently associated with increased mortality (HR 3.13, 95% CI 1.62–6.06), whilePseudomonas aeruginosainfection was associated with severe exacerbations (HR 1.41, 95% CI 1.01–1.97) and overall exacerbation rate (IRR 1.47, 95% CI 1.13–1.91).ConclusionsThis study identifies risk factors for morbidity and mortality among bronchiectasis patients in India. Identification of these risk factors may support treatment approaches optimised to an Asian setting.

siRNA has become an indispensible tool for silencing gene expression. It can act as an antiviral agent in RNAi pathway against plant diseases caused by plant viruses. However, identification of appropriate features for effective siRNA design has become a pressing issue for researchers which need to be resolved. Feature selection is a vital pre-processing technique involved in bioinformatics data set to find the most discriminative information not only for dimensionality reduction and detection of relevance features but also for minimizing the cost associated with features to design an accurate learning system. In this paper, we propose an ANN based feature selection approach using hybrid GA-PSO for selecting feature subset by discarding the irrelevant features and evaluating the cost of the model training. The results showed that the performance of proposed hybrid GA-PSO model outperformed the results of general PSO.&nbsp

Tea Gardens generally produce two kinds of waste materials such as Tea Factory waste (TFW) and Pruning Litter (PL). Minimum 2 % of TFW is produced as by - product during processing of tea contributing a huge quantity as waste material.Similarly during pruning operations considerable amount of biomass are produced. Both the bio-waste materials can be managed by biological process to produce value added organic supplement to enrich the soil of tea plantation. During the present study different physico-chemical properties, viz. pH, P2O2 , K2O and nitrogen’s of TFW were analyzed. In TFW the value of Total soluble solids ranged (27.2-31.1%) and Crude fiber ranged (25.83-31.12%) and Caffenine amount ranged (23.14- 27.94%) and Total ash ranged (3.15-6.54%) The aflavin ranged (0.45-0.76%) and the arubignins ranged (18.45-21.32%). In TFW and PL some beneficial and active microbial populations are found which can be used in tea plants after making value added compost to increase their natural productivity. In this study focus was given to explore the beneficial and active microorganisms found in TFW and PL and found some beneficial microbes such as Actinomycetes, Azotobacter, Azospirillum and Phosphate solubilizing bacteria respectively

RNAi represents an extraordinarily powerful method to silence the gene expression using synthetic plasmid or viral encoded small interfering RNAs (siRNAs) . So, finding an effective siRNA against a specific mRNA from the branch of predicted sequences is found to be an intriguing challenge among the researchers till date. Although various siRNA datasets with their gene silencing efficacy are available in the mammalian cell, but the same is scanty in plant genomes. The present study involves the development of a hybrid neuro-genetic approach, i.e., optimization of Back Propagation Neural Network (BPNN) model combining with Genetic Algorithm (GA) to predict siRNA silencing efficacy targeting against various plant viruses . BPNN model has been developed based on three different features, namely nucleotide position preferred, nucleotide position avoided, and thermodynamic characteristics. Identical methodology have been employed with a published dataset of 240 HIV siRNA sequences with silencing efficacy to compare the efficiency of the proposed model. BPNN performance is further optimized by employing GA for weight initialization. GA-BPNN has shown more promising results compared to BPNN in terms of accuracy and potential approaches.

In Northeast Indian tea plantations infection of Fusaruim solani , resulting dieback of tea plant is increasing which causes considerable crop loss during the recent times. In this investigation, native plant extracts, i.e. Acorus calamus L., Azadirachta indica A. Juss., Clerodendrum viscosum Vent., and Xanthium strumarium L. and microbials i.e. Bacillus subtilis and Trichoderma viride Pers. were utilized to evaluate the efficacy in controlling dieback disease of tea. These extracts inhibited the growth of Fusarium solani by 60-90%. In field application of C. viscosum and X. strumarium extracts reduced the disease up to 89.3% and 81% respectively. More than 70% disease reduction was observed when aqueous extracts of A. calamus and A. indica were used separately. Maximum disease reduction was achieved up to 86.9% due to application of T. viride . The results, thus, suggested the potential use of herbal extracts and microbial strains as an effective component of integrated disease management (IDM) schedule in the organic tea farming. The methods and rate of application are also discussed.

Actin-1 is a ubiquitous protein belonging to the reproductive class of Actin family in Arabidopsis thaliana. Thisprotein is involved in the formation of filaments that are major components of the cytoskeleton. Despite the im-portance of this protein, very little information is availa ble regarding its structure and function in plants. In thisstudy, analysis of the protein sequence was done an d comparative model of Actin-1 was constructed (UNIPROTID: P0CJ46) from Arabidopsis thaliana using the crystal structure of Dictyostelium discoideum actin (PDB ID:1NLV-A) as template employing Modelle r version 9.9. The stable structure was generated by 5 nanosecond mole-cular dynamics simulation steps usin g GROMOS43A1 96 force field that characterized its structural and dynamicfeature. The biochemical function of the final simulated structure was also investigated using PROFUNC. Themolecular simulation study suggested that the modeled Acti n-1 protein retain its stable conformation in aqueoussolution. The predicted binding sites in the modeled Actin- 1 protein are very informative for further protein-ligandinteraction study.

Superoxide dismutases (SODs), members of the metalloenzymes family are most effective intracellular enzymatic antioxidant in aerobic organisms. These enzymes provide the first line of defense in plants against the toxic effects of elevated levels of reactive oxygen species (ROS) generated during various environmental stresses. The availability of high-throughput computational tools has provided better opportunities to characterize the protein features and determine their function. In the present study an attempt was made to gain an insight into the structure and evolution of subunits of SODs (Cu-Zn, Mn and Fe SODs) of rice. The 3-Dimensional structures of SODs were modeled based on available X-ray crystal structures and further validated. The primary sequence, secondary and tertiary structure analysis revealed Mn and Fe SOD to be structurally homologous while Cu-Zn SOD is un-related to either of them. Comparative structural study also revealed former two were dominated by α-helices followed by β-strands in contrast; Cu-Zn SOD dominated by β-strands. Molecular phylogeny indicated a common evolutionary origin of Mn and Fe SOD while Cu-Zn SOD may have evolved separately.

Simple Sequence Repeats (SSRs) developed from Expressed Sequence Tags (ESTs), known as EST-SSRs are most widely used and potentially valuable source of gene based markers for their high levels of crosstaxon portability, rapid and less expensive development. The EST sequence information in the publicly available databases is increasing in a faster rate. The emerging computational approach provides a better alternative process of development of SSR markers from the ESTs than the conventional methods. In the present study, 12,851 EST sequences of Camellia sinensis, downloaded from National Center for Biotechnology Information (NCBI) were mined for the development of Microsatellites. 6148 (4779 singletons and 1369 contigs) non redundant EST sequences were found after preprocessing and assembly of these sequences using various computational tools. Out of total 3822.68 kb sequence examined, 1636 (26.61%) EST sequences containing 2371 SSRs were detected with a density of 1 SSR/1.61 kb leading to development of 245 primer pairs. These mined EST-SSR markers will help further in the study of variability, mapping, evolutionary relationship in Camellia sinensis. In addition, these developed SSRs can also be applied for various studies across species.

Social network analysis (SNA) has been effectively used in counter-terrorism analysis by generating homogeneous network. In this paper, we consider a large dataset reporting various terrorist attacks over the globe and represent the dataset as a heterogeneous network. The objective of this paper is to the explore the effect of various link prediction frameworks such as topic modeling, network topology and graph kernels. We propose bipartite based link prediction over topic feature relationship, heterogeneous version of node proximity based link prediction and graph kernel methods. From various experimental observation, it is evident that bipartite method based on topic modeling also return comparable results (sometimes better) as that of node proximity and graph kernel.

Glycoside hydrolase family 19 chitinases (EC 3.2.1.14) widely distributed in plants, bacteria and viruses catalyse the hydrolysis of chitin and play a major role in plant defense mechanisms and development. Rice possesses several classes of chitinase, out of which a single structure of class I has been reported in PDB to date. In the present study an attempt was made to gain more insight into the structure, function and evolution of class I, II and IV chitinases of GH family 19 from rice. The three-dimensional structures of chitinases were modelled and validated based on available X-ray crystal structures. The structural study revealed that they are highly α-helical and bilobed in nature. These enzymes are single or multi domain and multi-functional in which chitin-binding domain (CBD) and catalytic domain (CatD) are present in class I and IV whereas class II lacks CBD. The CatD possesses a catalytic triad which is thought to be involved in catalytic process. Loop III, which is common in all three classes of chitinases, reflects that it may play a significant role in their function. Our study also confirms that the absence and presence of different loops in GH family 19 of rice may be responsible for various sized products. Molecular phylogeny revealed chitinases in monocotyledons and dicotyledons differed from each other forming two different clusters and may have evolved differentially. More structural study of this enzyme from different plants is required to enhance the knowledge of catalytic mechanism and substrate binding.

UNLABELLED With the advent of high-throughput sequencing technology, sequences from many genomes are being deposited to public databases at a brisk rate. Open access to large amount of expressed sequence tag (EST) data in the public databases has provided a powerful platform for simple sequence repeat (SSR) development in species where sequence information is not available. SSRs are markers of choice for their high reproducibility, abundant polymorphism and high inter-specific transferability. The mining of SSRs from ESTs requires different high-throughput computational tools that need to be executed individually which are computationally intensive and time consuming. To reduce the time lag and to streamline the cumbersome process of SSR mining from ESTs, we have developed a user-friendly, web-based EST-SSR pipeline "EST-SSR-MARKER PIPELINE (ESMP)". This pipeline integrates EST pre-processing, clustering, assembly and subsequently mining of SSRs from assembled EST sequences. The mining of SSRs from ESTs provides valuable information on the abundance of SSRs in ESTs and will facilitate the development of markers for genetic analysis and related applications such as marker-assisted breeding. AVAILABILITY The database is available for free at http://bioinfo.aau.ac.in/ESMP.

Asthma is a chronic disorder affecting millions of people worldwide. The prevalence of asthma is around 300 million and is expected to increase another 100 million by 2025. Obesity, on the other hand, also affects a large number of individuals. Overweight in adults is defined when body mass index (BMI) is between 25 to 30 kg/m 2 and obesity when the BMI >30 kg/m 2 . It has been a matter of interest for researchers to find a relation between these two conditions. This knowledge will provide a new insight into the management of both conditions. At present, obese asthma patients may be considered a special category and it is important to assess the impact of management of obesity on asthma symptoms.