ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r², intercept and slope. Second, the two models’ assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS‐ and RIVPACS‐type models, if not to replace them.     

An additional ionic bond suggested by molecular modelling of TEM-2 might induce a slight discrepancy between catalytic properties of TEM-1 and TEM-2 β-lactamases

Abstract The plasmid-mediated TEM-1 and TEM-2 β-lactamases are the most commonly encountered among Gram-negative bacteria. They belong to molecular class A, and differ by one amino acid at position 39: TEM-1 have a glutamine and TEM-2 a lysine. Kinetic parameters ( k _cat and K _m) and catalytic efficiency ( k _cat/ K _m) of TEM-1 and TEM-2 β-lactamases are slightly, but significantly different. For all antibiotics except methicillin and cefazolin, the catalytic efficiency values of TEM-2 are clearly greater than that of TEM-1. Molecular modelling of TEM-2, when compared to that of TEM-1, showed an additional ionic bond between Lys-39 and Glu-281.     

Modelling family 2 cystatins and their interaction with papain

Cystatins are extensively studied cysteine protease inhibitors, found in wide range of organisms with highly conserved structural folds. S-type of cystatins is well known for their abundance in saliva, high selectivity and poorer activity towards host cysteine proteases in comparison to their immediate ancestor cystatin C. Despite more than 90% sequence similarity, the members of this group show highly dissimilar binding affinity towards papain. Cystatin M/E is a potent inhibitor of legumain and papain like cysteine proteases and recognized for its involvement in skin barrier formation and potential role as a tumor suppressor gene. However, the structures of these proteins and their complexes with papain or legumain are still unknown. In the present study, we have employed computational methods to get insight into the interactions between papain and cystatins. Three-dimensional structures of the cystatins are generated by homology modelling, refined with molecular dynamics simulation, validated through numerous web servers and finally complexed with papain using ZDOCK algorithm in Discovery Studio. A high degree of shape complementarity is observed within the complexes, stabilized by numerous hydrogen bonds (HB) and hydrophobic interactions. Using interaction energy, HB and solvent accessible surface area analyses, we have identified a series of key residues that may be involved in papain–cystatin interaction. Differential approaches of cystatins towards papain are also noticed which are possibly responsible for diverse inhibitory activity within the group. These findings will improve our understanding of fundamental inhibitory mechanisms of cystatin and provide clues for further research.     

In vitro and in silico evaluation of fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor

The fucosterol has been reported numerous biological activities. In this study, the activity in vitro of the fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor was evaluated. The structural identification was obtained by nuclear magnetic resonance (NMR) spectroscopy and based on experimental data, we combined docking and molecular dynamics simulations coupled to the molecular-mechanics-generalized-born-surface-area approach to evaluating the structural and energetic basis for the molecular recognition of fucosterol and neostigmine at the binding site of acetylcholinesterase (AChE). In addition, the Lineweaver–Burk plot showed the nature of a non-competitive inhibition. The maximum velocity (V_max) and the constant of Michaelis–Menten (K_m) estimated for fucosterol (0.006 µM) were 0.015 1/V_o (ΔA/h and 6.399 1/[ACh] mM^?1, respectively. While, for neostigmine (0.14 µM), the V_max was 0.022 1/V_o (ΔA/h) and K_m of 6.726 1/[ACh] mM^?1, these results showed a more effective inhibition by fucosterol respect to neostigmine. Structural analysis revealed that neostigmine reaches the AChE binding site reported elsewhere, whereas fucosterol can act as a no-competitive and competitive acetylcholinesterase inhibitor, in agree with kinetic enzymatic experiments. Binding free energy calculations revealed that fucosterol reaches the acetylcholinesterase binding site with higher affinity than neostigmine, which is according to experimental results. Whereas the per-residue decomposition free energy analysis let us identify crucial residues involved in the molecular recognition of ligands by AChE. Results corroborate the ability of theoretical methods to provide crucial information at the atomic level about energetic and structural differences in the binding interaction and affinity from fucosterol with AChE.

Communicated by Ramaswamy H. Sarma     

Modelling the Brain for Rotational Loading: Shear Effects and Other Complications

Abstract

This study considers modelling the brain due to rotation of the skull where, at lower frequencies, the shear property of the material is important. Investigations reported here cover the effect of elastic and viscoelastic (lossy) cerebral material, the effect of the Falx protruding into the brain, the gap around the Falx and the brain filled with non viscous fluid in addition to different models of the Falx with bending or membrane stiffness. Analytical benchmark formulations are also described for the simple 2D plane strain in a cylinder produced by a half-sine rotation on the outer periphery which allows numerical (Finite Element) models to be validated. The results show the importance of the material properties, duration of loading and amplitude of loading as well as the influence of the partition. The results are shown for predicted maximum Principal strains in the models, as this may well be indicative of whether damage of the brain tissue occurs.     

Detectability and criterion measures in temporal generalization

Computer simulation of performance on “normal” and “episodic” temporal generalization tasks was used to examine the relations between the theoretical parameters of models which fit temporal generalization data (“timing sensitivity” and “threshold”), and the d′ (detectability) and beta (decision criterion) measures of signal-detection theory. In general, changes in timing sensitivity altered d′, whereas threshold changes affected beta, supporting the assertion that the two sorts of variables (“sensitivity/detectability” and “threshold/criterion”) were psychologically equivalent. Cases where temporal generalization gradients were apparently contaminated by “random responding” could be treated by changes in beta, but cases in which temporal generalization gradients were not peaked at the standard posed severe problems for a simple signal-detection account, although existing models of temporal generalization performance could deal with them.     

Landscape diversity patterns and endemism of Araceae in Ecuador

Araceae is one of the largest herb families in tropical America, but its patterns of diversity and endemism are poorly known. We used predictive distribution modelling in GIS to study Araceae richness on a landscape scale in Ecuador. Modelling was based on georeferenced herbarium collections with humidity and mean annual temperature as climatic variables. Variation partitioning using multiple regression showed that humidity and altitude were main factors in explaining Araceae diversity patterns. Endemism was less well explained by present climatic factors. Unlike common diversity patterns of herbs or epiphytes, Araceae richness was highest in the eastern (Amazon) lowland rain forest with a secondary centre on the Andean foothills of northwestern Ecuador. The peak in endemism was on the western slopes of the Andes, corresponding to areas that have been severely affected by human activities and deforestation. Eastern lowland (Amazonian) forests were poor in endemic Araceae.