A Roadmap for Unified Ocean Modeling and Forecasting system for INCOIS

INCOIS, being the nodal organization to provide operational oceanographic services, is actively involved in the numerical modeling of ocean circulation, waves, tsunami and storm-surge as well as regional coupled ocean-atmosphere models for the prediction of track and intensity of tropical cyclones. In order to optimise the models used in INCOIS for these activities and to make a seamless prediction system from global to regional domains, it was decided to have a revisit on the ocean modeling efforts of INCOIS. Outcome of this review as well as a proposal to develop a seamless prediction system is documented in this report. It is envisaged that this document will be used as a guideline for the future ocean modeling efforts in INCOI

Estimating PM 2.5 concentrations in Xi'an City using a generalized additive model with multi-source monitoring data

© 2015 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5) represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT) product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM) is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582) by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Homology modeling, molecular dynamics, and virtual screening of NorA efflux pump inhibitors of Staphylococcus aureus

Baki Vijaya Bhaskar,1 Tirumalasetty Muni Chandra Babu,1 Netala Vasudeva Reddy,2 Wudayagiri Rajendra1 1Division of Molecular Biology, Department of Zoology, 2Department of Biotechnology, Sri Venkateswara University, Tirupati, Andhra Pradesh, India Abstract: Emerging drug resistance in clinical isolates of Staphylococcus aureus might be implicated to the overexpression of NorA efflux pump which is capable of extruding numerous structurally diverse compounds. However, NorA efflux pump is considered as a potential drug target for the development of efflux pump inhibitors. In the present study, NorA model was constructed based on the crystal structure of glycerol-3-phosphate transporter (PDBID: 1PW4). Molecular dynamics (MD) simulation was performed using NAMD2.7 for NorA which is embedded in the hydrated lipid bilayer. Structural design of NorA unveils amino (N)- and carboxyl (C)-terminal domains which are connected by long cytoplasmic loop. N and C domains are composed of six transmembrane &alpha;-helices (TM) which exhibits pseudo-twofold symmetry and possess voluminous substrate binding cavity between TM helices. Molecular docking of reserpine, totarol, ferruginol, salvin, thioxanthene, phenothiazine, omeprazole, verapamil, nalidixic acid, ciprofloxacin, levofloxacin, and acridine to NorA found that all the molecules were bound at the large hydrophobic cleft and indicated significant interactions with the key residues. In addition, structure-based virtual screening was employed which indicates that 14 potent novel lead molecules such as CID58685302, CID58685367, CID5799283, CID5578487, CID60028372, ZINC12196383, ZINC72140751, ZINC72137843, ZINC39227983, ZINC43742707, ZINC12196375, ZINC66166948, ZINC39228014, and ZINC14616160 have highest binding affinity for NorA. These lead molecules displayed considerable pharmacological properties as evidenced by Lipinski rule of five and prophecy of toxicity risk assessment. Thus, the present study will be helpful in designing and synthesis of a novel class of NorA efflux pump inhibitors that restore the susceptibilities of drug compounds. Keywords: Staphylococcus aureus, NorA efflux pump, molecular dynamics, virtual screening, docking&nbsp

INCOIS Live Access Server: A Platform for Serving the Geospatial Data of Indian Ocean

The INCOIS Live Access Server (I-LAS) was setup at Indian National Centre for Ocean Information Services to effectively deliver diversified geospatial products pertaining to Indian Ocean. The I-LAS provides free access to full suite of satellite-derived data products viz., sea surface temperature (SST), surface chlorophyll, surface wind products and number of products derived from objectively analyzed in-situ data. Further model analysis products from GODAS-MOM are also made available. Additionally climatological data sets from World Ocean Atlas 2009 are also made available for inter-comparison and generation of anomalies. Various functionalities for on the fly visualization and downloading of data are in built in to the LAS along with OpenDAP data sharing. Some examples of data usage from the LAS are also presented. It is observed that INCOIS LAS is being extensively used by various users and statistics of data usage is monitored on a regular basis and 100% uptime is maintained