The Use of a Smartphone App and an Activity Tracker to Promote Physical Activity in the Management of Chronic Obstructive Pulmonary Disease: Randomized Controlled Feasibility Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is highly prevalent and significantly affects the daily functioning of patients. Self-management strategies, including increasing physical activity, can help people with COPD have better health and a better quality of life. Digital mobile health (mHealth) techniques have the potential to aid the delivery of self-management interventions for COPD. We developed an mHealth intervention (Self-Management supported by Assistive, Rehabilitative, and Telehealth technologies-COPD [SMART-COPD]), delivered via a smartphone app and an activity tracker, to help people with COPD maintain (or increase) physical activity after undertaking pulmonary rehabilitation (PR). OBJECTIVE: This study aimed to determine the feasibility and acceptability of using the SMART-COPD intervention for the self-management of physical activity and to explore the feasibility of conducting a future randomized controlled trial (RCT) to investigate its effectiveness. METHODS: We conducted a randomized feasibility study. A total of 30 participants with COPD were randomly allocated to receive the SMART-COPD intervention (n=19) or control (n=11). Participants used SMART-COPD throughout PR and for 8 weeks afterward (ie, maintenance) to set physical activity goals and monitor their progress. Questionnaire-based and physical activity-based outcome measures were taken at baseline, the end of PR, and the end of maintenance. Participants, and health care professionals involved in PR delivery, were interviewed about their experiences with the technology. RESULTS: Overall, 47% (14/30) of participants withdrew from the study. Difficulty in using the technology was a common reason for withdrawal. Participants who completed the study had better baseline health and more prior experience with digital technology, compared with participants who withdrew. Participants who completed the study were generally positive about the technology and found it easy to use. Some participants felt their health had benefitted from using the technology and that it assisted them in achieving physical activity goals. Activity tracking and self-reporting were both found to be problematic as outcome measures of physical activity for this study. There was dissatisfaction among some control group members regarding their allocation. CONCLUSIONS: mHealth shows promise in helping people with COPD self-manage their physical activity levels. mHealth interventions for COPD self-management may be more acceptable to people with prior experience of using digital technology and may be more beneficial if used at an earlier stage of COPD. Simplicity and usability were more important for engagement with the SMART-COPD intervention than personalization; therefore, the intervention should be simplified for future use. Future evaluation will require consideration of individual factors and their effect on mHealth efficacy and use; within-subject comparison of step count values; and an opportunity for control group participants to use the intervention if an RCT were to be carried out. Sample size calculations for a future evaluation would need to consider the high dropout rates.

Footprinting molecular electrostatic potential surfaces for calculation of solvation energies.

A liquid is composed of an ensemble of molecules that populate a large number of different states, so calculation of the solvation energy of a molecule in solution requires a method for summing the interactions with the environment over all of these states. The surface site interaction model for the properties of liquids at equilibrium (SSIMPLE) simplifies the surface of a molecule to a discrete number of specific interaction sites (SSIPs). The thermodynamic properties of these interaction sites can be characterised experimentally, for example, through measurement of association constants for the formation of simple complexes that feature a single H-bonding interaction. Correlation of experimentally determined solution phase H-bond parameters with gas phase ab initio calculations of maxima and minima on molecular electrostatic potential surfaces (MEPS) provides a method for converting gas phase calculations on isolated molecules to parameters that can be used to estimate solution phase interaction free energies. This approach has been generalised using a footprinting technique that converts an MEPS into a discrete set of SSIPs (each described by a polar interaction parameter, εi). These SSIPs represent the molecular recognition properties of the entire surface of the molecule. For example, water is described by four SSIPs, two H-bond donor sites and two H-bond acceptor sites. A liquid mixture is described as an ensemble of SSIPs that represent the components of the mixture at appropriate concentrations. Individual SSIPs are assumed to be independent, so speciation of SSIP contacts can be calculated based on properties of the individual SSIP interactions, which are given by the sum of a polar (εiεj) and a non-polar (E(vdW)) interaction term. Results are presented for calculation the free energies of transfer of a range of organic molecules from the pure liquid into water, from the pure liquid into n-hexadecane, from n-hexadecane into water, from n-octanol into water, and for the transfer of water from pure water into a range of organic liquids. The agreement with experiment is accurate to within 1.6-3.9 kJ mol(-1) root mean square difference, which suggests that the SSIMPLE approach is a promising method for estimation of solvation energies in more complex systems.

PREDICTOR: a web-based tool for the prediction of atomic structure from sequence for double helical DNA with up to 150 base pairs.

We announce the release of a web-based tool for DNA structure prediction (PREDICTOR) which allows the calculation of atomic structures of double-helical DNA with up to 150 Watson-Crick base pairs (http://farwer.staff.shef.ac.uk/ PREDICTOR). The semi-empirical method uses computational chemistry to extrapolate knowledge of sequence-dependent DNA structure contained in the X-ray crystal structure database. The properties of the base stacking interactions are treated theoretically, and an empirical model is used to add the conformational constraints imposed by the backbone. For DNA oligomers in the X-ray crystal structure database that were not used for parameterisation of the model, the method distinguishes A and B form DNA reasonably reliably, and the final structures are accurate to 2 å rmsd. Simulation of a 150mer and a 494mer with experimentally confirmed bending clearly reproduces the bending whereas the predicted structure of a random 150mer does not show any curvature. Calculation times are 90 seconds for an octamer and 7 minutes for a 30mer.

Prediction of atomic structure from sequence for double helical DNA oligomers.

DNA can adopt different conformations depending on the base sequence, solvent, electrolyte composition and concentration, pH, temperature, and interaction with proteins. Here we present a model for calculating the three-dimensional atomic structure of double-stranded DNA oligomers. A theoretical energy function is used for calculating the interactions within the base steps and an empirical backbone function is used to restrict the conformational space accessible to the bases and to account for the conformational coupling of neighboring steps in a sequence. Conformational searching on large structures or a large number of structures is possible, because each base step can be described by just two primary degrees of freedom (slide and shift). A genetic algorithm is used to search for low-energy structures in slide-shift space, and this allows very rapid optimization of DNA oligomers. The other base step parameters have been previously optimized for all possible slide-shift sequence combinations, and a heuristic algorithm is used to add the atomic details of the backbone conformation in the final step of the calculation. The structures obtained by this method are very similar to the corresponding X-ray crystal structures observed experimentally. The average RMSD is 2.24 Angstroms for a set of 20 oligomer structures. For 15 of these sequences, the X-ray crystal structure is the global energy minimum. The other 5 are bistable sequences that have B-form global energy minima but crystallize as A-DNA.

Testing similarity measures with continuous and discrete protein models.

There are many ways to define the distance between two protein structures, thus assessing their similarity. Here, we investigate and compare the properties of five different distance measures, including the standard root-mean-square deviation (cRMSD). The performance of these measures is studied from different perspectives with two different protein models, one continuous and the other discrete. Using the continuous model, we examine the correlation between energy and native distance, and the ability of the different measures to discriminate between the two possible topologies of a three-helix bundle. Using the discrete model, we perform fits to real protein structures by minimizing different distance measures. The properties of the fitted structures are found to depend strongly on the distance measure used and the scale considered. We find that the cRMSD measure very effectively describes long-range features but is less effective with short-range features, and it correlates weakly with energy. A stronger correlation with energy and a better description of short-range properties is obtained when we use measures based on intramolecular distances.