Effects of structural variation in xyloglucan polymers on interactions with bacterial cellulose

A cellulose/xyloglucan framework is considered to form the basis for the mechanical properties of primary plant cell walls and hence to have a major influence on the biomechanical properties of growing, fleshy plant tissues. In this study, structural variants of xyloglucan have been investigated as components of composites with bacterial cellulose as a simplified model for the cellulose/xyloglucan framework of primary plant cell walls. Evidence for molecular binding to cellulose with perturbation of cellulose crystallinity was found for all xyloglucan types. High molecular mass samples gave homogeneous centimeter-scale composites with extensive cross-linking of cellulose with xyloglucan. Lower molecular mass xyloglucans gave heterogeneous composites having a range of microscopic structures with little, if any, cross-linking. Xyloglucans with reduced levels of galactose substitution had evidence of self-association, competitive with cellulose binding. At comparable molecular mass, fucose substitution resulted in a modest promotion of microscopic features characteristic of primary cell walls. Taken together, the data are evidence that galactose substitution of the xyloglucan core structure is a major determinant of cellulose composite formation and properties, with additional fucose substitution acting as a secondary modulator. These conclusions are consistent with reported structural and mechanical properties of Arabidopsis mutants lacking specific facose and/or galactose residues.

Extending a model of shift-work tolerance

The present study contributes to theory and practice through the development of a model of shift-work tolerance with the potential to indicate interventions that reduce nurses' intention toward turnover and increase job satisfaction in hospital-based settings. Survey data from 1257 nurses were used to conduct structural equation modeling that examine the direct and indirect effects of supervisor and colleague support, team identity, team climate, and control over working environment on time-based work/life conflict, psychological well-being, physical symptoms, job satisfaction, and turnover intention. The analysis of the proposed model revealed a good fit The chi-square difference test was non-significant (χ2(26)=338.56), the fit indices were high (CFI=.923, NFI=.918, and NNFI=.868), the distribution of residuals was symmetric and approached zero, the average standardized residual was low (AASR=.04), and the standardized RMR was .072. In terms of the predictor variable, the final model explained 48% of the variance in turnover intention. The data revealed considerable evidence of both direct effects on adjustment and complex indirect links between levels of adjustment and work-related social support, team identity, team climate, and control. Nurses with high supervisor and coworker support experienced more positive team climates, identified more strongly with their team, and increased their perceptions of control over their work environment. This in turn lowered their appraisals of their time-based work/life conflict, which consequently increased their psychological well-being and job satisfaction and reduced their physical health symptoms and turnover intention. The type of shift schedule worked by the nurses influenced levels of turnover intention, control over work environment, time-based work/life conflict, and physical symptoms.

Structural ambiguity of the Chinese version of the Hospital Anxiety and Depression Scale in patients with coronary heart disease

Background The Hospital Anxiety and Depression Scale (HADS) is a widely used screening tool designed as a case detector for clinically relevant anxiety and depression. Recent studies of the HADS in coronary heart disease (CHD) patients in European countries suggest it comprises three, rather than two, underlying sub-scale dimensions. The factor structure of the Chinese version of the HADS was evaluated in patients with CHD in mainland China. Methods Confirmatory factor analysis (CFA) was conducted on self-report HADS forms from 154 Chinese CHD patients. Results Little difference was observed in model fit between best performing three-factor and two-factor models. Conclusion The current observations are inconsistent with recent studies highlighting a dominant underlying tri-dimensional structure to the HADS in CHD patients. The Chinese version of the HADS may perform differently to European language versions of the instrument in patients with CHD.

Strain energies due to nonplanar distortion of fullerenes and their dependence on structural motifs

Accurate strain energies due to nonplanar distortion of 114 isolated pentagon rule (IPR) fullerenes with 60-102 carbon atoms have been calculated based on B3LYP/6-31G(d) optimized structures. The calculated values of strain energy due to nonplanar distortion (E-np) are reproduced by three simple schemes based upon counts of 8, 16, and 30 distinct structural motifs composed of hexagons and pentagons. Using C-180 (I-h) and CN (I-h) (N is very large) as test molecules, the intrinsic limitations of the motif model based on six-membered rings (6-MRs) as the central unit have been discussed. On the basis of the relationship between the contributions of motifs to E-np and the number of five-membered rings (5-MRs) in motifs, we found that IPR fullerenes with dispersed 5-MRs present smaller nonplanar distortions.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein’s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision. ©2005 IEEE

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.