Key Intervention Characteristics in e-Health: Steps Towards Standardized Communication

PURPOSE: This paper reports expert opinion on e-health intervention characteristics that enable effective communication of characteristics across the diverse field of e-health interventions. The paper presents a visualization tool to support communication of the defining characteristics. METHODS: An initial list of e-health intervention characteristics was developed through an iterative process of item generation and discussion among the 12 authors. The list was distributed to 123 experts in the field, who were emailed an invitation to assess and rank the items. Participants were asked to evaluate these characteristics in three separate ways. RESULTS: A total of 50 responses were received for a response rate of 40.7%. Six respondents who reported having little or no expertise in e-health research were removed from the dataset. Our results suggest that 10 specific intervention characteristics were consistently supported as of central importance by the panel of 44 e-intervention experts. The weight and perceived relevance of individual items differed between experts; oftentimes, this difference is a result of the individual theoretical perspective and/or behavioral target of interest. CONCLUSIONS: The first iteration of the visualization of salient characteristics represents an ambitious effort to develop a tool that will support communication of the defining characteristics for e-health interventions aimed to assist e-health developers and researchers to communicate the key characteristics of their interventions in a standardized manner that facilitates dialog

Promotion of Prescription Drugs to Consumers and Providers, 2001–2010

Background: Pharmaceutical firms heavily promote their products and may have changed marketing strategies in response to reductions in new product approvals, restrictions on some forms of promotion, and the expanding role of biologic therapies. Methods: We used descriptive analyses of annual cross-sectional data from 2001 through 2010 to examine direct-to-consumer advertising (DTCA) (Kantar Media) and provider-targeted promotion (IMS Health and SDI), including: (1) inflation-adjusted total promotion spending ($and percent of sales); (2) distribution by channel (consumer v. provider); and (3) provider specialty both for the industry as a whole and for top-selling biologic and small molecule therapies. Results: Total promotion peaked in 2004 at US$36.1 billion (13.4% of sales). By 2010 it had declined to $27.7B (9.0$370 million (8.8% of sales) spent on promotion, top biologics were promoted less, with only $33 million (1.4% of sales) spent per product. Little change occurred in the composition of promotion between primary care physicians and specialists from 2001–2010. Conclusions: These findings suggest that pharmaceutical companies have reduced promotion following changes in the pharmaceutical pipeline and patent expiry for several blockbuster drugs. Promotional strategies for biologic drugs differ substantially from small molecule therapies

MSH3 polymorphisms and protein levels affect CAG repeat instability in huntington's disease mice

Expansions of trinucleotide CAG/CTG repeats in somatic tissues are thought to contribute to ongoing disease progression through an affected individual's life with Huntington's disease or myotonic dystrophy. Broad ranges of repeat instability arise between individuals with expanded repeats, suggesting the existence of modifiers of repeat instability. Mice with expanded CAG/CTG repeats show variable levels of instability depending upon mouse strain. However, to date the genetic modifiers underlying these differences have not been identified. We show that in liver and striatum the R6/1 Huntington's disease (HD) (CAG)~100 transgene, when present in a congenic C57BL/6J (B6) background, incurred expansion-biased repeat mutations, whereas the repeat was stable in a congenic BALB/cByJ (CBy) background. Reciprocal congenic mice revealed the Msh3 gene as the determinant for the differences in repeat instability. Expansion bias was observed in congenic mice homozygous for the B6 Msh3 gene on a CBy background, while the CAG tract was stabilized in congenics homozygous for the CBy Msh3 gene on a B6 background. The CAG stabilization was as dramatic as genetic deficiency of Msh2. The B6 and CBy Msh3 genes had identical promoters but differed in coding regions and showed strikingly different protein levels. B6 MSH3 variant protein is highly expressed and associated with CAG expansions, while the CBy MSH3 variant protein is expressed at barely detectable levels, associating with CAG stability. The DHFR protein, which is divergently transcribed from a promoter shared by the Msh3 gene, did not show varied levels between mouse strains. Thus, naturally occurring MSH3 protein polymorphisms are modifiers of CAG repeat instability, likely through variable MSH3 protein stability. Since evidence supports that somatic CAG instability is a modifier and predictor of disease, our data are consistent with the hypothesis that variable levels of CAG instability associated with polymorphisms of DNA repair genes may have prognostic implications for various repeat-associated diseases

Computational Structural Analysis: Multiple Proteins Bound to DNA

BACKGROUND: With increasing numbers of crystal structures of proteinratioDNA and proteinratioproteinratioDNA complexes publically available, it is now possible to extract sufficient structural, physical-chemical and thermodynamic parameters to make general observations and predictions about their interactions. In particular, the properties of macromolecular assemblies of multiple proteins bound to DNA have not previously been investigated in detail. METHODOLOGY/PRINCIPAL FINDINGS: We have performed computational structural analyses on macromolecular assemblies of multiple proteins bound to DNA using a variety of different computational tools: PISA; PROMOTIF; X3DNA; ReadOut; DDNA and DCOMPLEX. Additionally, we have developed and employed an algorithm for approximate collision detection and overlapping volume estimation of two macromolecules. An implementation of this algorithm is available at http://promoterplot.fmi.ch/Collision1/. The results obtained are compared with structural, physical-chemical and thermodynamic parameters from proteinratioprotein and single proteinratioDNA complexes. Many of interface properties of multiple proteinratioDNA complexes were found to be very similar to those observed in binary proteinratioDNA and proteinratioprotein complexes. However, the conformational change of the DNA upon protein binding is significantly higher when multiple proteins bind to it than is observed when single proteins bind. The water mediated contacts are less important (found in less quantity) between the interfaces of components in ternary (proteinratioproteinratioDNA) complexes than in those of binary complexes (proteinratioprotein and proteinratioDNA).The thermodynamic stability of ternary complexes is also higher than in the binary interactions. Greater specificity and affinity of multiple proteins binding to DNA in comparison with binary protein-DNA interactions were observed. However, protein-protein binding affinities are stronger in complexes without the presence of DNA. CONCLUSIONS/SIGNIFICANCE: Our results indicate that the interface properties: interface area; number of interface residues/atoms and hydrogen bonds; and the distribution of interface residues, hydrogen bonds, van der Walls contacts and secondary structure motifs are independent of whether or not a protein is in a binary or ternary complex with DNA. However, changes in the shape of the DNA reduce the off-rate of the proteins which greatly enhances the stability and specificity of ternary complexes compared to binary ones

Characterization of long and stable de novo single alpha-helix domains provides novel insight into their stability

Naturally-occurring single α-helices (SAHs), are rich in Arg (R), Glu (E) and Lys (K) residues, and stabilized by multiple salt bridges. Understanding how salt bridges promote their stability is challenging as SAHs are long and their sequences highly variable. Thus, we designed and tested simple de novo 98-residue polypeptides containing 7-residue repeats (AEEEXXX, where X is K or R) expected to promote salt-bridge formation between Glu and Lys/Arg. Lys-rich sequences (EK3 (AEEEKKK) and EK2R1 (AEEEKRK)) both form SAHs, of which EK2R1 is more helical and thermo-stable suggesting Arg increases stability. Substituting Lys with Arg (or vice versa) in the naturally-occurring myosin-6 SAH similarly increased (or decreased) its stability. However, Arg-rich de novo sequences (ER3 (AEEERRR) and EK1R2 (AEEEKRR)) aggregated. Combining a PDB analysis with molecular modelling provides a rational explanation, demonstrating that Glu and Arg form salt bridges more commonly, utilize a wider range of rotamer conformations, and are more dynamic than Glu–Lys. This promiscuous nature of Arg helps explain the increased propensity of de novo Arg-rich SAHs to aggregate. Importantly, the specific K:R ratio is likely to be important in determining helical stability in de-novo and naturally-occurring polypeptides, giving new insight into how single α-helices are stabilized

NetTurnP – Neural Network Prediction of Beta-turns by Use of Evolutionary Information and Predicted Protein Sequence Features

UNLABELLED: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences

Prognostic value of myocardial perfusion scintigraphy in type 2 diabetic patients with mild, stable angina pectoris

Aim: To determine the prognostic value of reversible myocardial perfusion defects on myocardial perfusion scintigraphy (MPS) in patients with type 2 diabetes mellitus and mild anginal complaints. Methods and results: In the MERIDIAN trial, patients with diabetes mellitus type 2, stable, mild anginal symptoms (Canadian Cardiovascular Society classification (CCS) I-II/IV) and reversible perfusion defects were randomized to either continued pharmacological treatment or early invasive treatment. In this sub analysis, the severity of the myocardial perfusion defect was related to the occurrence of cardiac death and non-fatal myocardial infarction, in 319 patients (63% male, 65 ± 9 years). During follow-up (2.2 ± 0.6 years), 14 patients had a cardiac event: 3 in 171 patients without myocardial ischemia and 11 in 148 patients with myocardial ischemia. Annual event rates rose from 0.8% to 5.8% with increasing severity of myocardial ischemia. Multivariable analysis identified the presence of severe myocardial ischemia (hazard ratio (HR) 5.45, 95%CI 1.89-15.71) and insulin use (HR 4.00, 95%CI 1.25-12.75) as independent predictors of cardiac events. Conclusions: Type 2 diabetics with mild anginal symptoms with no or moderate myocardial ischemia have a low annual cardiac event rate. In patients with severe myocardial ischemia event rate increased 3-6 fold