Improving the description of interactions between Ca2+ and protein carboxylate groups, including γ-carboxyglutamic acid: revised CHARMM22∗ parameters

A reliable description of ion pair interactions for biological systems, particularly those involving polyatomic ions such as carboxylate and divalent ions such as Ca²⁺, using biomolecular force-fields is essential for making useful predictions for a range of protein functions. In particular, the interaction of divalent ions with the double carboxylate group present in γ-carboxyglutamic acid (Gla), relevant to the function of many proteins, is relatively understudied using biomolecular force-fields. Using force-field based metadynamics simulations to predict the free energy of binding between Ca²⁺ and the carboxylate group in liquid water, we show that a widely-used biomolecular force-field, CHARMM22∗, substantially over-estimates the binding strength between Ca²⁺ and the side-chains of both glutamic acid (Glu) and Gla, compared with experimental data obtained for the analogous systems of aqueous calcium-acetate and calcium-malonate. To correct for this, we propose and test a range of modifications to the σ value of the heteroatomic Lennard-Jones interaction between Ca²⁺ and the oxygen of the carboxylate group. Our revised parameter set can recover the same three association modes of this aqueous ion pair as the standard parameter set, and yields free energies of binding for the carboxylate-Ca²⁺ interaction in good agreement with experimental data. The revised parameter set recovers other structural properties of the ion pair in agreement with the standard CHARMM22∗ parameter set.

A revised Australian dietary guideline index and its association with key sociodemographic factors, health behaviors and body mass index in peri-retirement aged adults

The Dietary Guideline Index, a measure of diet quality, was updated to reflect the 2013 Australian Dietary Guidelines. This paper describes the revision of the index (DGI-2013) and examines its use in older adults. The DGI-2013 consists of 13 components reflecting food-based daily intake recommendations of the Australian Dietary Guidelines. In this cross-sectional study, the DGI-2013 score was calculated using dietary data collected via an 111-item food frequency questionnaire and additional food-related behaviour questions. The DGI-2013 score was examined in Australian adults (aged 55-65 years; n = 1667 men; 1801 women) according to sociodemographics, health-related behaviours and BMI. Women scored higher than men on the total DGI-2013 and all components except for dairy. Those who were from a rural area (men only), working full-time (men only), with lower education, smoked, did not meet physical activity guidelines, and who had a higher BMI, scored lower on the DGI-2013, highlighting a group of older adults at risk of poor health. The DGI-2013 is a tool for assessing compliance with the Australian Dietary Guidelines. We demonstrated associations between diet quality and a range of participant characteristics, consistent with previous literature. This suggests that the DGI-2013 continues to demonstrate convergent validity, consistent with the original Dietary Guideline Index.

Advanced web and network technologies, and applications. APWeb 2008 international workshops: BIDM, IWHDM, and DeWeb Shenyang, China, April 26-28, 2008, Shenyang, China revised papers

Constitutes the thoroughly refereed joint post-workshop proceedings of three international workshops held in conjunction with the 10th Asia-Pacific Web Conference, APWeb 2008, in Shenyang, China, in April 2008.

Measuring chronic condition self-management in an Australian community: factor structure of the revised Partners in Health (PIH) scale

Purpose To evaluate the factor structure of the revised Partners in Health (PIH) scale for measuring chronic condition self-management in a representative sample from the Australian community.

Methods A series of consultations between clinical groups underpinned the revision of the PIH. The factors in the revised instrument were proposed to be: knowledge of illness and treatment, patient–health professional partnership, recognition and management of symptoms and coping with chronic illness. Participants (N = 904) reporting having a chronic illness completed the revised 12-item scale. Two a priori models, the 4-factor and bi-factor models were then evaluated using Bayesian confirmatory factor analysis (BCFA). Final model selection was established on model complexity, posterior predictive p values and deviance information criterion.

Results Both 4-factor and bi-factor BCFA models with small informative priors for cross-loadings provided an acceptable fit with the data. The 4-factor model was shown to provide a better and more parsimonious fit with the observed data in terms of substantive theory. McDonald’s omega coefficients indicated that the reliability of subscale raw scores was mostly in the acceptable range.

Conclusion The findings showed that the PIH scale is a relevant and structurally valid instrument for measuring chronic condition self-management in an Australian community. The PIH scale may help health professionals to introduce the concept of self-management to their patients and provide assessment of areas of self-management. A limitation is the narrow range of validated PIH measurement properties to date. Further research is needed to evaluate other important properties such as test–retest reliability, responsiveness over time and content validity.