The Effect of Life Stage Experience and Social Cognitive Reasoning on Adult Gender Role Orientation: A Multidimensional Approach.

This study adds to the literature on adult gender role by extending adult gender role orientation beyond increases and/or decreases on gender related personality attributes, in particular increases in self-rated Masculine and Feminine ratings. Gender role orientation was examined along three dimensions: gender-related personality attributes of self, attitudes toward gender role issues, and gender-related attributes of others in social contexts. Life stage experience and social cognitive functioning influences on gender role orientation were examined. The participants were 240 individuals from five life stages: Life stage 1--single, never married; Life stage 2--married individuals with no children; Life stage 3--individuals with children no older than 5 years; Life stage 4--individuals with at least one child between the ages of 6 and 24; and Life stage 5--individuals with at least one child aged 25 or older. All participants completed the Bem Sex Role Inventory, Sex Role Orientation scale, Social Paradigm Belief Inventory, and Attributions of Others in Social Contexts designed specifically for this study. The results indicated that (a) life stage 1 participants attributed more negative or socially undesirable characteristics to targets in instrumental social contexts, relative to later life stage groups; (b) women rated themselves as more interpersonally sensitive than did men; men rated as more instrumental than did women; (c) women had more liberal attitudes toward gender role issues than did men; and (d) social cognitive reasoning did not predict gender role orientation. Theoretical and methodological explanations for these findings, coupled with implications and future directions for research, were discussed

QSCOP-BLAST—fast retrieval of quantified structural information for protein sequences of unknown structure

QSCOP is a quantitative structural classification of proteins which distinguishes itself from other classifications by two essential properties: (i) QSCOP is concurrent with the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank and (ii) QSCOP covers the widely used SCOP classification with layers of quantitative structural information. The QSCOP-BLAST web server presented here combines the BLAST sequence search engine with QSCOP to retrieve, for a given query sequence, all structural information currently available. The resulting search engine is reliable in terms of the quality of results obtained, and it is efficient in that results are displayed instantaneously. The hierarchical organization of QSCOP is used to control the redundancy and diversity of the retrieved hits with the benefit that the often cumbersome and difficult interpretation of search results is an intuitive and straightforward exercise. We demonstrate the use of QSCOP-BLAST by example. The server is accessible at http://qscop-blast.services.came.sbg.ac.at

COPS—a novel workbench for explorations in fold space

The COPS (Classification Of Protein Structures) web server provides access to the complete repertoire of known protein structures and protein structural domains. The COPS classification encodes pairwise structural similarities as quantified metric relationships. The resulting metrical structure is mapped to a hierarchical tree, which is largely equivalent to the structure of a file browser. Exploiting this relationship we implemented the Fold Space Navigator, a tool that makes navigation in fold space as convenient as browsing through a file system. Moreover, pairwise structural similarities among the domains can be visualized and inspected instantaneously. COPS is updated weekly and stays concurrent with the PDB repository. The server also exposes the COPS classification pipeline. Newly determined structures uploaded to the server are chopped into domains, the locations of the new domains in the classification tree are determined, and their neighborhood can be immediately explored through the Fold Space Navigator. The COPS web server is accessible at http://cops.services.came.sbg.ac.at/

The structure of DdrB from Deinococcus: a new fold for single-stranded DNA binding proteins

Deinococcus spp. are renowned for their amazing ability to recover rapidly from severe genomic fragmentation as a result of exposure to extreme levels of ionizing radiation or desiccation. Despite having been originally characterized over 50 years ago, the mechanism underlying this remarkable repair process is still poorly understood. Here, we report the 2.8 Å structure of DdrB, a single-stranded DNA (ssDNA) binding protein unique to Deinococcus spp. that is crucial for recovery following DNA damage. DdrB forms a pentameric ring capable of binding single-stranded but not double-stranded DNA. Unexpectedly, the crystal structure reveals that DdrB comprises a novel fold that is structurally and topologically distinct from all other single-stranded binding (SSB) proteins characterized to date. The need for a unique ssDNA binding function in response to severe damage, suggests a distinct role for DdrB which may encompass not only standard SSB protein function in protection of ssDNA, but also more specialized roles in protein recruitment or DNA architecture maintenance. Possible mechanisms of DdrB action in damage recovery are discussed

Detection and Alignment of 3D Domain Swapping Proteins Using Angle-Distance Image-Based Secondary Structural Matching Techniques

This work presents a novel detection method for three-dimensional domain swapping (DS), a mechanism for forming protein quaternary structures that can be visualized as if monomers had “opened” their “closed” structures and exchanged the opened portion to form intertwined oligomers. Since the first report of DS in the mid 1990s, an increasing number of identified cases has led to the postulation that DS might occur in a protein with an unconstrained terminus under appropriate conditions. DS may play important roles in the molecular evolution and functional regulation of proteins and the formation of depositions in Alzheimer's and prion diseases. Moreover, it is promising for designing auto-assembling biomaterials. Despite the increasing interest in DS, related bioinformatics methods are rarely available. Owing to a dramatic conformational difference between the monomeric/closed and oligomeric/open forms, conventional structural comparison methods are inadequate for detecting DS. Hence, there is also a lack of comprehensive datasets for studying DS. Based on angle-distance (A-D) image transformations of secondary structural elements (SSEs), specific patterns within A-D images can be recognized and classified for structural similarities. In this work, a matching algorithm to extract corresponding SSE pairs from A-D images and a novel DS score have been designed and demonstrated to be applicable to the detection of DS relationships. The Matthews correlation coefficient (MCC) and sensitivity of the proposed DS-detecting method were higher than 0.81 even when the sequence identities of the proteins examined were lower than 10%. On average, the alignment percentage and root-mean-square distance (RMSD) computed by the proposed method were 90% and 1.8Å for a set of 1,211 DS-related pairs of proteins. The performances of structural alignments remain high and stable for DS-related homologs with less than 10% sequence identities. In addition, the quality of its hinge loop determination is comparable to that of manual inspection. This method has been implemented as a web-based tool, which requires two protein structures as the input and then the type and/or existence of DS relationships between the input structures are determined according to the A-D image-based structural alignments and the DS score. The proposed method is expected to trigger large-scale studies of this interesting structural phenomenon and facilitate related applications

Cross-Over between Discrete and Continuous Protein Structure Space: Insights into Automatic Classification and Networks of Protein Structures

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.ph

Photos and Phenotypes: Using Camera Traps to Monitor Seasonal Mismatch Between Snowshoe Hares (Lepus americanus) Coat Color Change and Snow Cover

Snowshoe hares biannually change coat color to match the landscape. They depend on this photoperiod-cued change to hide from predators. With climate change affecting snowfall patterns, hares are at risk of higher predation. This issue is the subject of a long-term study. The project uses traditional methods--field technicians, live trapping, and telemetry--to collect data. These methods are constrained by access, weather, daylight, and other limiting factors. Using camera trap images, I have developed a new data collection protocol that addresses these constraints After analyzing 3,400 photos to date, I have found that photo data can provide relevant, accurate, and detailed information. It would provide an easy and cost-efficient way to supplement traditionally-gathered data. My thesis has grown to include four stages. The initial project was developing a novel and noninvasive way to track the hares’ seasonal coat color changes. Now I am applying my protocol to a 10,000 image database. The photos are donated by-catch from unrelated research projects (a lynx survey, wolf project, and general biodiversity study). Already I have confirmed, developed, and applied my method. I was able to fine-tune my protocol as to maximize efficiency. Now I am continuing the application on a grand scale: 10,000 images from five different locations in the United States and Canada. The remaining analysis will be complete by 31 July. With the resulting dataset, I can statistically plot correlations, looking for trends and differences between locations, at different elevations, and across the latitudinal gradient. This camera-based method can be modified and applied to any species that changes appearance over time. As such, it can be used to monitor a number of species across the planet. Such a development would open many doors in wildlife research