The Diabetes Manual trial protocol – a cluster randomized controlled trial of a self-management intervention for type 2 diabetes [ISRCTN06315411]

Background The Diabetes Manual is a type 2 diabetes self-management programme based upon the clinically effective 'Heart Manual'. The 12 week programme is a complex intervention theoretically underpinned by self-efficacy theory. It is a one to one intervention meeting United Kingdom requirements for structured diabetes-education and is delivered within routine primary care. Methods/design In a two-group cluster randomized controlled trial, GP practices are allocated by computer minimisation to an intervention group or a six-month deferred intervention group. We aim to recruit 250 participants from 50 practices across central England. Eligibility criteria are adults able to undertake the programme with type 2 diabetes, not taking insulin, with HbA1c over 8% (first 12 months) and following an agreed protocol change over 7% (months 13 to 18). Following randomisation, intervention nurses receive two-day training and delivered the Diabetes Manual programme to participants. Deferred intervention nurses receive the training following six-month follow-up. Primary outcome is HbA1c with total and HDL cholesterol; blood pressure, body mass index; self-efficacy and quality of life as additional outcomes. Primary analysis is between-group HbA1c differences at 6 months powered to give 80% power to detect a difference in HbA1c of 0.6%. A 12 month cohort analysis will assess maintenance of effect and assess relationship between self-efficacy and outcomes, and a qualitative study is running alongside. Discussion This trial incorporates educational and psychological diabetes interventions into a single programme and assesses both clinical and psychosocial outcomes. The trial will increase our understanding of intervention transferability between conditions, those diabetes related health behaviours that are more or less susceptible to change through efficacy enhancing mechanisms and how this impacts on clinical outcomes

Randomised trials comparing different healthcare settings : an exploratory review of the impact of pre-trial preferences on participation, and discussion of other methodological challenges

BACKGROUND: We recently published a systematic review of different healthcare settings (such as outpatient, community or home) for administering intravenous chemotherapy, and concluded that performing conventionally designed randomised trials was difficult. The main problems were achieving adequate trial accrual rates and recruiting a study population which adequately represented the target population of interest. These issues stemmed from the fact that potential participants may have had pre-trial perceptions about the trial settings they may be allocated; such preferences will sometimes be strong enough for patients to decline an invitation to participate in a trial. A patient preference trial design (in which patients can choose, or be randomised to, an intervention) may have obviated these recruitment issues, although none of the trials used such a design. METHODS: In order to gain a better understanding of the broader prevalence and extent of these preference issues (and any other methodological challenges), we undertook an exploratory review of settings trials in any area of healthcare treatment research. We searched The Cochrane Library and Google Scholar and used snowballing methods to identify trials comparing different healthcare settings. RESULTS: Trial accrual was affected by patient preferences for a setting in 15 of the 16 identified studies; birth setting trials were the most markedly affected, with between 68 % and 85 % of eligible women declining to participate specifically because of preference for a particular healthcare setting. Recruitment into substance abuse and chemotherapy setting studies was also notably affected by preferences. Only four trials used a preference design: the proportion of eligible patients choosing to participate via a preference group ranged from between 33 % and 67 %. CONCLUSIONS: In trials of healthcare settings, accrual may be seriously affected by patient preferences. The use of trial designs which incorporate a preference component should therefore strongly be considered. When designing such trials, investigators should consider settings to be complex interventions, which are likely to have linked components which may be difficult to control for. Careful thought is also needed regarding the choice of comparator settings and the most appropriate outcome measures to be used

Discovery of an Auto-Regulation Mechanism for the Maltose ABC Transporter MalFGK2

The maltose transporter MalFGK2, together with the substrate-binding protein MalE, is one of the best-characterized ABC transporters. In the conventional model, MalE captures maltose in the periplasm and delivers the sugar to the transporter. Here, using nanodiscs and proteoliposomes, we instead find that MalE is bound with high-affinity to MalFGK2 to facilitate the acquisition of the sugar. When the maltose concentration exceeds the transport capacity, MalE captures maltose and dissociates from the transporter. This mechanism explains why the transport rate is high when MalE has low affinity for maltose, and low when MalE has high affinity for maltose. Transporter-bound MalE facilitates the acquisition of the sugar at low concentrations, but also captures and dissociates from the transporter past a threshold maltose concentration. In vivo, this maltose-forced dissociation limits the rate of transport. Given the conservation of the substrate-binding proteins, this mode of allosteric regulation may be universal to ABC importers

Managing childhood fever and pain – the comfort loop

Parents can transmit their anxiety to their child, and just as children can pick up on parental anxiety, they can also respond to a parent's ability to stay calm in stressful situations. Therefore, when treating children, it is important to address parental anxiety and to improve their understanding of their child's ailment. Parental understanding and management of both pain and fever – common occurrences in childhood – is of utmost importance, not just in terms of children's health and welfare, but also in terms of reducing the economic burden of unnecessary visits to paediatric emergency departments. Allaying parental anxiety reduces the child's anxiety and creates a positive feedback loop, which ultimately affects both the child and parent

The C:N:P:S stoichiometry of soil organic matter

The formation and turnover of soil organic matter (SOM) includes the biogeochemical processing of the macronutrient elements nitrogen (N), phosphorus (P) and sulphur (S), which alters their stoichiometric relationships to carbon (C) and to each other. We sought patterns among soil organic C, N, P and S in data for c. 2000 globally distributed soil samples, covering all soil horizons. For non-peat soils, strong negative correlations (p < 0.001) were found between N:C, P:C and S:C ratios and % organic carbon (OC), showing that SOM of soils with low OC concentrations (high in mineral matter) is rich in N, P and S. The results can be described approximately with a simple mixing model in which nutrient-poor SOM (NPSOM) has N:C, P:C and S:C ratios of 0.039, 0.0011 and 0.0054, while nutrient-rich SOM (NRSOM) has corresponding ratios of 0.12, 0.016 and 0.016, so that P is especially enriched in NRSOM compared to NPSOM. The trends hold across a range of ecosystems, for topsoils, including O horizons, and subsoils, and across different soil classes. The major exception is that tropical soils tend to have low P:C ratios especially at low N:C. We suggest that NRSOM comprises compounds selected by their strong adsorption to mineral matter. The stoichiometric patterns established here offer a new quantitative framework for SOM classification and characterisation, and provide important constraints to dynamic soil and ecosystem models of carbon turnover and nutrient dynamics

Using enhanced number and brightness to measure protein oligomerization dynamics in live cells

Protein dimerization and oligomerization are essential to most cellular functions, yet measurement of the size of these oligomers in live cells, especially when their size changes over time and space, remains a challenge. A commonly used approach for studying protein aggregates in cells is number and brightness (N&B), a fluorescence microscopy method that is capable of measuring the apparent average number of molecules and their oligomerization (brightness) in each pixel from a series of fluorescence microscopy images. We have recently expanded this approach in order to allow resampling of the raw data to resolve the statistical weighting of coexisting species within each pixel. This feature makes enhanced N&B (eN&B) optimal for capturing the temporal aspects of protein oligomerization when a distribution of oligomers shifts toward a larger central size over time. In this protocol, we demonstrate the application of eN&B by quantifying receptor clustering dynamics using electron-multiplying charge-coupled device (EMCCD)-based total internal reflection microscopy (TIRF) imaging. TIRF provides a superior signal-to-noise ratio, but we also provide guidelines for implementing eN&B in confocal microscopes. For each time point, eN&B requires the acquisition of 200 frames, and it takes a few seconds up to 2 min to complete a single time point. We provide an eN&B (and standard N&B) MATLAB software package amenable to any standard confocal or TIRF microscope. The software requires a high-RAM computer (64 Gb) to run and includes a photobleaching detrending algorithm, which allows extension of the live imaging for more than an hour

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends

Skin cancer is considered as one of the most common types of cancer in several countries, and its incidence rate has increased in recent years. Melanoma cases have caused an increasing number of deaths worldwide, since this type of skin cancer is the most aggressive compared to other types. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification is addressed in this review. In addition, a discussion about the application of such methods, as well as future trends, is also provided. Several methods for feature extraction from both macroscopic and dermoscopic images and models for feature selection are introduced and discussed. Furthermore, classification algorithms and evaluation procedures are described, and performance results for lesion classification and pattern analysis are given