Daily life stress and the cortisol awakening response : testing the anticipation hypothesis

Acknowledgments We thank Paul Stewart for his contribution to data collection and Dr Matthew Jones for programming the handheld computers. Author Contributions Conceived and designed the experiments: WS DJP. Performed the experiments: DJP. Analyzed the data: WS. Wrote the paper: WS DJP.Peer reviewedPublisher PD

Insulin resistance in type 1 diabetes: what is ‘double diabetes’ and what are the risks?

In this review, we explore the concept of ‘double diabetes’, a combination of type 1 diabetes with features of insulin resistance and type 2 diabetes. After considering whether double diabetes is a useful concept, we discuss potential mechanisms of increased insulin resistance in type 1 diabetes before examining the extent to which double diabetes might increase the risk of cardiovascular disease (CVD). We then go on to consider the proposal that weight gain from intensive insulin regimens may be associated with increased CV risk factors in some patients with type 1 diabetes, and explore the complex relationships between weight gain, insulin resistance, glycaemic control and CV outcome. Important comparisons and contrasts between type 1 diabetes and type 2 diabetes are highlighted in terms of hepatic fat, fat partitioning and lipid profile, and how these may differ between type 1 diabetic patients with and without double diabetes. In so doing, we hope this work will stimulate much-needed research in this area and an improvement in clinical practice

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

Background: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual aminoacids are systematically mutated to alanine and changes in free energy of binding (Delta Delta G) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition.Results: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which Delta Delta G >= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%.Conclusion: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration

Accumulation of Polychlorinated Biphenyls in Adipocytes: Selective Targeting to Lipid Droplets and Role of Caveolin-1

Background : Polychlorinated biphenyls (PCBs) are persistent environmental pollutants that preferentially accumulate in lipid-rich tissues of contaminated organisms. Although the adipose tissue constitutes a major intern reservoir of PCBs and recent epidemiological studies associate PCBs to the development of obesity and its related disorders, little is known about the mechanisms involved in their uptake by the adipose tissue and their intracellular localization in fat cells

The Overlap of Small Molecule and Protein Binding Sites within Families of Protein Structures

Protein–protein interactions are challenging targets for modulation by small molecules. Here, we propose an approach that harnesses the increasing structural coverage of protein complexes to identify small molecules that may target protein interactions. Specifically, we identify ligand and protein binding sites that overlap upon alignment of homologous proteins. Of the 2,619 protein structure families observed to bind proteins, 1,028 also bind small molecules (250–1000 Da), and 197 exhibit a statistically significant (p<0.01) overlap between ligand and protein binding positions. These “bi-functional positions”, which bind both ligands and proteins, are particularly enriched in tyrosine and tryptophan residues, similar to “energetic hotspots” described previously, and are significantly less conserved than mono-functional and solvent exposed positions. Homology transfer identifies ligands whose binding sites overlap at least 20% of the protein interface for 35% of domain–domain and 45% of domain–peptide mediated interactions. The analysis recovered known small-molecule modulators of protein interactions as well as predicted new interaction targets based on the sequence similarity of ligand binding sites. We illustrate the predictive utility of the method by suggesting structural mechanisms for the effects of sanglifehrin A on HIV virion production, bepridil on the cellular entry of anthrax edema factor, and fusicoccin on vertebrate developmental pathways. The results, available at http://pibase.janelia.org, represent a comprehensive collection of structurally characterized modulators of protein interactions, and suggest that homologous structures are a useful resource for the rational design of interaction modulators

Usefulness and limitations of transthoracic echocardiography in heart transplantation recipients

Transthoracic echocardiography is a primary non-invasive modality for investigation of heart transplant recipients. It is a versatile tool which provides comprehensive information about cardiac structure and function. Echocardiographic examinations can be easily performed at the bedside and serially repeated without any patient's discomfort. This review highlights the usefulness of Doppler echocardiography in the assessment of left ventricular and right ventricular systolic and diastolic function, of left ventricular mass, valvular heart disease, pulmonary arterial hypertension and pericardial effusion in heart transplant recipients. The main experiences performed by either standard Doppler echocardiography and new high-tech ultrasound technologies are summarised, pointing out advantages and limitations of the described techniques in diagnosing acute allograft rejection and cardiac graft vasculopathy. Despite the sustained efforts of echocardiographic technique in predicting the biopsy state, endocardial myocardial biopsies are still regarded as the gold standard for detection of acute allograft rejection. Conversely, stress echocardiography is able to identify accurately cardiac graft vasculopathy and has a recognised prognostic in this clinical setting. A normal stress-echo justifies postponement of invasive studies. Another use of transthoracic echocardiography is the monitorisation and the visualisation of the catheter during the performance of endomyocardial biopsy. Bedside stress echocardiography is even useful to select appropriately heart donors with brain death. The ultrasound monitoring is simple and effective for monitoring a safe performance of biopsy procedures

Diverse and Active Roles for Adipocytes During Mammary Gland Growth and Function

The mammary gland is unique in its requirement to develop in close association with a depot of adipose tissue that is commonly referred to as the mammary fat pad. As discussed throughout this issue, the mammary fat pad represents a complex stromal microenvironment that includes a variety of cell types. In this article we focus on adipocytes as local regulators of epithelial cell growth and their function during lactation. Several important considerations arise from such a discussion. There is a clear and close interrelationship between different stromal tissue types within the mammary fat pad and its adipocytes. Furthermore, these relationships are both stage- and species-dependent, although many questions remain unanswered regarding their roles in these different states. Several lines of evidence also suggest that adipocytes within the mammary fat pad may function differently from those in other fat depots. Finally, past and future technologies present a variety of opportunities to model these complexities in order to more precisely delineate the many potential functions of adipocytes within the mammary glands. A thorough understanding of the role for this cell type in the mammary glands could present numerous opportunities to modify both breast cancer risk and lactation performance

Characterization of Profilin Polymorphism in Pollen with a Focus on Multifunctionality

Profilin, a multigene family involved in actin dynamics, is a multiple partners-interacting protein, as regard of the presence of at least of three binding domains encompassing actin, phosphoinositide lipids, and poly-L-proline interacting patches. In addition, pollen profilins are important allergens in several species like Olea europaea L. (Ole e 2), Betula pendula (Bet v 2), Phleum pratense (Phl p 12), Zea mays (Zea m 12) and Corylus avellana (Cor a 2). In spite of the biological and clinical importance of these molecules, variability in pollen profilin sequences has been poorly pointed out up until now. In this work, a relatively high number of pollen profilin sequences have been cloned, with the aim of carrying out an extensive characterization of their polymorphism among 24 olive cultivars and the above mentioned plant species. Our results indicate a high level of variability in the sequences analyzed. Quantitative intra-specific/varietal polymorphism was higher in comparison to inter-specific/cultivars comparisons. Multi-optional posttranslational modifications, e.g. phosphorylation sites, physicochemical properties, and partners-interacting functional residues have been shown to be affected by profilin polymorphism. As a result of this variability, profilins yielded a clear taxonomic separation between the five plant species. Profilin family multifunctionality might be inferred by natural variation through profilin isovariants generated among olive germplasm, as a result of polymorphism. The high variability might result in both differential profilin properties and differences in the regulation of the interaction with natural partners, affecting the mechanisms underlying the transmission of signals throughout signaling pathways in response to different stress environments. Moreover, elucidating the effect of profilin polymorphism in adaptive responses like actin dynamics, and cellular behavior, represents an exciting research goal for the future