Indices of reproductive skew depend on average reproductive success

Several indices of reproductive skew, which quantify the degree of unequal partitioning of reproductive output among members in an animal society, have been proposed. Here we point out the drawbacks of these indices. The most serious problem is the dependence of the indices on mean reproductive success: skew values tend to be larger, as average numbers of offspring decrease, due to random sampling error in numbers of offspring. Thus it is difficult to compare societies with different average lifetime reproductive success using these indices, even though we have presented methods to calculate the expected reproductive skew caused by random sampling error, especially when average numbers of offspring are small, as is often the case with cooperatively breeding vertebrates. As an alternative, we propose using the spatial dispersion indices of population ecology (Morisita's index or its standardized version) for the measurement of reproductive skew. These indices are almost independent of average fecundity and have their own method of testing for random variation in offspring numbers. This revised version was published online in July 2006 with corrections to the Cover Date.     

Atypical surface behavior of ceramides with nonhydroxy and 2-hydroxy very long-chain (C28–C32) PUFAs

Unique species of ceramide (Cer) with very-long-chain polyunsaturated fatty acid (VLCPUFA), mainly 28–32 carbon atoms, 4–5 double bonds, in nonhydroxy and 2-hydroxy forms (n-V Cer and h-V Cer, respectively), are generated in rat spermatozoa from the corresponding sphingomyelins during the acrosomal reaction. The aim of this study was to determine the properties of these sperm-distinctive ceramides in Langmuir monolayers. Individual Cer species were isolated by HPLC and subjected to analysis of surface pressure, surface potential, and Brewster angle microscopy (BAM) as a function of molecular packing. In comparison with known species of Cer, n-V Cer and h-V Cer species showed much larger mean molecular areas and increased molecular dipole moments in liquid expanded phases, which suggest bending and partial hydration of the double bonded portion of the VLCPUFA. The presence of the 2-hydoxyl group induced a closer molecular packing in h-V Cer than in their chain-matched n-V Cer. In addition, all these Cer species showed liquid-expanded to liquid-condensed transitions at room temperature. Existence of domain segregation was confirmed by BAM. Additionally, thermodynamic analysis suggests a phase transition close to the physiological temperature for VLCPUFA-Cers if organized as bulk dispersions.     

Characterization of germin-like protein with polyphenol oxidase activity from Satsuma mandarine

Polyphenol oxidases (PPOs) catalyzing the oxygen dependent oxidation of phenols to quinones are ubiquitously distributed in plants and are assumed to be involved in plant defense against pests and pathogens. A protein with high PPO activity was identified in Satsuma mandarine, extracted with Tris–HCl buffer, purified by salt precipitation and column chromatography, and characterized by mass spectrometry as germin-like protein (GLP), which belongs to pathogenesis related protein (PR) family. In the present study, the structure and enzymatic properties of GLP were characterized using spectroscopy methods. Based on native PAGE analysis, the molecular weight of GLP was estimated to be 108 kDa and GLP was identified as a pentamer containing five subunits of 22 kDa. The optimum pH and temperature for PPO catalyzing activity of GLP was 6.5 and 65 °C, respectively. Kinetic constants were 0.0365 M and 0.0196 M with the substrates catechol and pyrogallol, respectively. The structural characterization of GLP provided better insights into the regions responsible for its PPO activity.     

Towards a biogeographic regionalization of the European biota

Aim To determine if it is possible to generate analytically derived regionalizations for multiple groups of European plants and animals and to explore potential influences on the regions for each taxonomic group. Location Europe. Methods We subjected range maps of trees, butterflies, reptiles, amphibians, birds and mammals to k‐means clustering followed by v‐fold cross‐validation to determine the pattern and number of regions (clusters). We then used the mean range sizes of species in each group as a correlate of the number of regions obtained for each taxon, and climate and species richness gradients as correlates of the spatial arrangement of the group‐specific regions. We also included the pattern of tree clusters as a predictor of animal clusters in order to test the ‘habitat templet’ concept as an explanation of animal distribution patterns. Results Spatially coherent clusters were found for all groups. The number of regions ranged from three to eight and was strongly associated with the mean range sizes of the species in each taxon. The cluster patterns of all groups were associated with various combinations of climate, underlying species richness gradients and, in the case of animals, the arrangement of tree clusters, although the rankings of the correlates differed among groups. In four of five groups the tree pattern was the strongest single predictor of the animal cluster patterns. Main conclusions Despite a long history of human disturbance and habitat modification, the European biota retains a discernable biogeographic structure. The primary driver appears to be aspects of climate related to water–energy balance, which also influence richness gradients. For many animals, the underlying habitat structure, as measured by tree distributions, appears to have a strong influence on their biogeographic structure, highlighting the need to preserve natural forest formations if we want to preserve the historical signal found in geographic distributions.     

The management of vegetation classifications with fuzzy clustering

Questions: Does fuzzy clustering provide an appropriate numerical framework to manage vegetation classifications? What is the best fuzzy clustering method to achieve this? Material: We used 531 relevés from Catalonia (Spain), belonging to two syntaxonomic alliances of mesophytic and xerophytic montane pastures, and originally classified by experts into nine and 13 associations, respectively. Methods: We compared the performance of fuzzy C‐means (FCM), noise clustering (NC) and possibilistic C‐means (PCM) on four different management tasks: (1) assigning new relevé data to existing types; (2) updating types incorporating new data; (3) defining new types with unclassified relevés; and (4) reviewing traditional vegetation classifications. Results: As fuzzy classifiers, FCM fails to indicate when a given relevé does not belong to any of the existing types; NC might leave too many relevés unclassified; and PCM membership values cannot be compared. As unsupervised clustering methods, FCM is more sensitive than NC to transitional relevés and therefore produces fuzzier classifications. PCM looks for dense regions in the space of species composition, but these are scarce when vegetation data contain many transitional relevés. Conclusions: All three models have advantages and disadvantages, although the NC model may be a good compromise between the restricted FCM model and the robust but impractical PCM model. In our opinion, fuzzy clustering might provide a suitable framework to manage vegetation classifications using a consistent operational definition of vegetation type. Regardless of the framework chosen, national/regional vegetation classification panels should promote methodological standards for classification practices with numerical tools.     

How different from random are docking predictions when ranked by scoring functions?

Docking algorithms predict the structure of protein–protein interactions. They sample the orientation of two unbound proteins to produce various predictions about their interactions, followed by a scoring step to rank the predictions. We present a statistical assessment of scoring functions used to rank near‐native orientations, applying our statistical analysis to a benchmark dataset of decoys of protein–protein complexes and assessing the statistical significance of the outcome in the Critical Assessment of PRedicted Interactions (CAPRI) scoring experiment. A P value was assigned that depended on the number of near‐native structures in the sampling. We studied the effect of filtering out redundant structures and tested the use of pair‐potentials derived using ZDock and ZRank. Our results show that for many targets, it is not possible to determine when a successful reranking performed by scoring functions results merely from random choice. This analysis reveals that changes should be made in the design of the CAPRI scoring experiment. We propose including the statistical assessment in this experiment either at the preprocessing or the evaluation step. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

The Intrasectional Chemotaxonomic Placement of Hypericum elegans Stephan ex Willd. Inferred from the Essential‐Oil Chemical Composition

Here we report, for the first time, the results of detailed GC and GC/MS analyses of the essential oil of a rare taxon in Serbia, Hypericum elegans Stephan ex Willd . One hundred and sixty two constituents identified accounted for 98.6% of the oil. The major components of the oil were undecane (31.9%), α‐pinene (16.7%), nonane (6.1%), bicyclogermacrene (5.8%), 2‐methyloctane (3.7%), and germacrene D (3.6%). Non‐terpenoids as chemotaxonomic markers constituted the main fraction of H. elegans oil, whereby n‐alkanes were the most abundant contributors of this fraction. Based on these results and previously published ones, we performed an intrasectional multivariate statistical comparison of corresponding essential‐oil chemical compositions. Principal component analysis (PCA) and agglomerative hierarchical clustering (AHC) of the data on the volatile profiles of section Hypericum taxa revealed that H. elegans either represents an oil chemotype of its own (AHC) or could be considered related to H. perforatum (PCA).     

双绕蛋白质的分类与识别

蛋白质折叠识别是蛋白质结构研究的重要内容。双绕是α/β蛋白质中结构典型的常见折叠类型。选取22个家族中序列一致性小于25%的79个典型双绕蛋白质作为训练集,以RMSD为指标进行系统聚类,并对各类建立基于结构比对的概形隐马尔科夫模型(profile-HMM)。将Astral1.65中序列一致性小于95%的9 505个样本作为检验集,整体识别敏感性为93.9%,特异性为82.1%,MCC值为0.876。结果表明:对于成员较多,无法建立统一模型的折叠类型,分类建模可以实现较高准确率的识别。     

Interaction of the N-terminal segment of HCV protein NS5A with model membranes

We have identified a membrane-active region in the HCV NS5A protein by performing an exhaustive study of membrane rupture induced by a NS5A-derived peptide library on model membranes having different phospholipid compositions. We report the identification in NS5A of a highly membranotropic region located at the suggested membrane association domain of the protein. We report the binding and interaction with model membranes of two peptides patterned after this segment, peptides 1A and 1B, derived from the strains 1a_H77 and 1b_HC-4J respectively. We show that they insert into phospholipid membranes, interact with them, and are located in a shallow position in the membrane. The NS5A region where this segment resides might have an essential role in the membrane replication and/or assembly of the viral particle through the modulation of the replication complex, and consequently, directly implicated in the HCV life cycle.