Community metabolism, P/R ratio and photosynthetic efficiency of a brackishwater farm

The productivity level of a brackishwater fish culture farm consisting of 25 ponds, with a water spread area of 2.5 ha, was studied. Gross community photosynthesis of the farm was found to be 46.32 Kcal/m2/day, which is equivalent to the release of 13.23 of O2/m2/day, or the fixing of 4.10 gC/m2/day. Respiratory demand of the farm was estimated to be 44.66 kcal/m2/day, which is equivalent to the uptake of 12.76 g O2/m2/day or the utilization of 3.95 gC/m2/day. Photosynthetic efficiency of the farm was high at 2.26%. The P/R ratio was 1.04, showing eutrophic nature

A REVIEW ON PHARMACO KINETIC DRUG INTERACTIONS OF STATINS

The 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins) are generally well tolerated as monotherapy. Statins are associated with two important adverse effects, asymptomatic elevation in liver enzymes and myopathy. Myopathy is most likely to occur when statins are administered with other drugs. Statins are substrates of multiple drug transporters (including OAT- -P1B1, BCRP and MDR1) and several cytochrome P450 (CYP) enzymes (including CYP3A4, CYP2C8, CYP2C19, and CYP2C9). Possible adverse effects of statins can occur due to interactions in concomitant use of drugs that substantially inhibit or induce their methabolic pathway. This review aim is to summarize the most important interactions of statins

Stability Indicating RP-HPLC Method for Determination of Valsartan in Pure and Pharmaceutical Formulation

Abstract: A simple, rapid and accurate and stability indicating RP-HPLC method was developed for the determination of valsartan in pure and tablet forms. The method showed a linear response for concentrations in the range of 50-175 µg/mL using 0.01 M NH 4 H 2 PO 4 (pH 3.5) buffer: methanol [50:50] as the mobile phase with detection at 210 nm and a flow rate of 1 mL/min and retention time 11.041 min. The method was statistically validated for accuracy, precision, linearity, ruggedness, robustness, forced degradation, solution stability and selectivity. Quantitative and recovery studies of the dosage form were also carried out and analyzed; the % RSD from recovery studies was found to be less than 1. Due to simplicity, rapidity and accuracy of the method, we believe that the method will be useful for routine quality control analysis

An Oscillating MinD Protein Determines the Cellular Positioning of the Motility Machinery in Archaea.

MinD proteins are well studied in rod-shaped bacteria such as E. coli, where they display self-organized pole-to-pole oscillations that are important for correct positioning of the Z-ring at mid-cell for cell division. Archaea also encode proteins belonging to the MinD family, but their functions are unknown. MinD homologous proteins were found to be widespread in Euryarchaeota and form a sister group to the bacterial MinD family, distinct from the ParA and other related ATPase families. We aimed to identify the function of four archaeal MinD proteins in the model archaeon Haloferax volcanii. Deletion of the minD genes did not cause cell division or size defects, and the Z-ring was still correctly positioned. Instead, one of the deletions (ΔminD4) reduced swimming motility and hampered the correct formation of motility machinery at the cell poles. In ΔminD4 cells, there is reduced formation of the motility structure and chemosensory arrays, which are essential for signal transduction. In bacteria, several members of the ParA family can position the motility structure and chemosensory arrays via binding to a landmark protein, and consequently these proteins do not oscillate along the cell axis. However, GFP-MinD4 displayed pole-to-pole oscillation and formed polar patches or foci in H. volcanii. The MinD4 membrane-targeting sequence (MTS), homologous to the bacterial MinD MTS, was essential for the oscillation. Surprisingly, mutant MinD4 proteins failed to form polar patches. Thus, MinD4 from H. volcanii combines traits of different bacterial ParA/MinD proteins

Probabilistic Random Walk Models for Comparative Network Analysis

Graph-based systems and data analysis methods have become critical tools in many fields as they can provide an intuitive way of representing and analyzing interactions between variables. Due to the advances in measurement techniques, a massive amount of labeled data that can be represented as nodes on a graph (or network) have been archived in databases. Additionally, novel data without label information have been gradually generated and archived. Labeling and identifying characteristics of novel data is an important first step in utilizing the valuable data in an effective and meaningful way. Comparative network analysis is an effective computational means to identify and predict the properties of the unlabeled data by comparing the similarities and differences between well-studied and less-studied networks. Comparative network analysis aims to identify the matching nodes and conserved subnetworks across multiple networks to enable a prediction of the properties of the nodes in the less-studied networks based on the properties of the matching nodes in the well-studied networks (i.e., transferring knowledge between networks). One of the fundamental and important questions in comparative network analysis is how to accurately estimate node-to-node correspondence as it can be a critical clue in analyzing the similarities and differences between networks. Node correspondence is a comprehensive similarity that integrates various types of similarity measurements in a balanced manner. However, there are several challenges in accurately estimating the node correspondence for large-scale networks. First, the scale of the networks is a critical issue. As networks generally include a large number of nodes, we have to examine an extremely large space and it can pose a computational challenge due to the combinatorial nature of the problem. Furthermore, although there are matching nodes and conserved subnetworks in different networks, structural variations such as node insertions and deletions make it difficult to integrate a topological similarity. In this dissertation, novel probabilistic random walk models are proposed to accurately estimate node-to-node correspondence between networks. First, we propose a context-sensitive random walk (CSRW) model. In the CSRW model, the random walker analyzes the context of the current position of the random walker and it can switch the random movement to either a simultaneous walk on both networks or an individual walk on one of the networks. The context-sensitive nature of the random walker enables the method to effectively integrate different types of similarities by dealing with structural variations. Second, we propose the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) model. In the CUFID model, we construct an integrated network by inserting pseudo edges between potential matching nodes in different networks. Then, we design the random walk protocol to transit more frequently between potential matching nodes as their node similarity increases and they have more matching neighboring nodes. We apply the proposed random walk models to comparative network analysis problems: global network alignment and network querying. Through extensive performance evaluations, we demonstrate that the proposed random walk models can accurately estimate node correspondence and these can lead to improved and reliable network comparison results

A practical method for optimum seismic design of friction wall dampers

Friction control systems have been widely used as one of the efficient and cost effective solutions to control structural damage during strong earthquakes. However, the height-wise distribution of slip loads can significantly affect the seismic performance of the strengthened frames. In this study, a practical design methodology is developed for more efficient design of friction wall dampers by performing extensive nonlinear dynamic analyses on 3, 5, 10, 15, and 20-story RC frames subjected to seven spectrum-compatible design earthquakes and five different slip load distribution patterns. The results show that a uniform cumulative distribution can provide considerably higher energy dissipation capacity than the commonly used uniform slip load pattern. It is also proved that for a set of design earthquakes, there is an optimum range for slip loads that is a function of number of stories. Based on the results of this study, an empirical equation is proposed to calculate a more efficient slip load distribution of friction wall dampers for practical applications. The efficiency of the proposed method is demonstrated through several design examples

Simultaneous Optimization of Both Node and Edge Conservation in Network Alignment via WAVE

Network alignment can be used to transfer functional knowledge between conserved regions of different networks. Typically, existing methods use a node cost function (NCF) to compute similarity between nodes in different networks and an alignment strategy (AS) to find high-scoring alignments with respect to the total NCF over all aligned nodes (or node conservation). But, they then evaluate quality of their alignments via some other measure that is different than the node conservation measure used to guide the alignment construction process. Typically, one measures the amount of conserved edges, but only after alignments are produced. Hence, a recent attempt aimed to directly maximize the amount of conserved edges while constructing alignments, which improved alignment accuracy. Here, we aim to directly maximize both node and edge conservation during alignment construction to further improve alignment accuracy. For this, we design a novel measure of edge conservation that (unlike existing measures that treat each conserved edge the same) weighs each conserved edge so that edges with highly NCF-similar end nodes are favored. As a result, we introduce a novel AS, Weighted Alignment VotEr (WAVE), which can optimize any measures of node and edge conservation, and which can be used with any NCF or combination of multiple NCFs. Using WAVE on top of established state-of-the-art NCFs leads to superior alignments compared to the existing methods that optimize only node conservation or only edge conservation or that treat each conserved edge the same. And while we evaluate WAVE in the computational biology domain, it is easily applicable in any domain.Comment: 12 pages, 4 figure