Risk factor control is key in diabetic nephropathy

Prolonged duration of diabetes, poor glycaemic control and hypertension are major risk factors for both diabetic nephropathy and cardiovascular disease. Optimising blood sugar control together with excellent control of blood pressure can reduce the risk of developing diabetic nephropathy. Diabetic nephropathy should be considered in any patient with diabetes when persistent albuminuria develops. Microalbuminuria is the earliest clinically detectable indicator of diabetic nephropathy risk. The majority of patients with diabetic nephropathy are appropriately diagnosed based on elevated urinary albumin excretion and/or reduced 0032-6518 renal function. Patients with type 2 diabetes should have annual urinary ACR measurements from the time of diabetes diagnosis while those with type 1 diabetes should commence five years after diagnosis. Blood pressure lowering to 130/80mmHg and reduction of proteinuria to <1 g/day retards progression of diabetic nephropathy and reduces the number of cardiovascular events. Drugs that block the renin-angiotensin-aldosterone system (RAAS) are effective in reducing proteinuria, managing hypertension and reducing cardiovascular risk. Unless there are clear contraindications or intolerance all patients with diabetic nephropathy should be prescribed an ACEI or ARB. Stopping an ACEI or ARB during intercurrent illness or times of volume depletion is critically important. Patients with diabetic nephropathy should have at least yearly measurements of blood pressure, renal function and urinary ACR.

A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for energy-con\-strained environments, provided that applications have the mechanisms to produce outputs of the highest possible quality within the given energy budget.
We introduce a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows users to express the relative importance of computations for the quality of the end result, as well as minimum quality requirements. The significance-aware runtime system uses an application-specific analytical energy model to identify the degree of concurrency and approximation that maximizes quality while meeting user-specified energy constraints. Evaluation on a dual-socket 8-core server shows that the proposed
framework predicts the optimal configuration with high accuracy, enabling energy-constrained executions that result in significantly higher quality compared to loop perforation, a compiler approximation technique.

Lung consequences in adults born prematurely

Although survival has improved significantly in recent years, prematurity remains a major cause of infant and childhood mortality and morbidity. Preterm births (<37 weeks of gestation) account for 8% of live births representing >50 000 live births each year in the UK. Preterm birth, irrespective of whether babies require neonatal intensive care, is associated with increased respiratory symptoms, partially reversible airflow obstruction and abnormal thoracic imaging in childhood and in young adulthood compared with those born at term. Having failed to reach their optimal peak lung function in early adulthood, there are as yet unsubstantiated concerns of accelerated lung function decline especially if exposed to noxious substances leading to chronic respiratory illness; even if the rate of decline in lung function is normal, the threshold for respiratory symptoms will be crossed early. Few adult respiratory physicians enquire about the neonatal period in their clinical practice. The management of these subjects in adulthood is largely evidence free. They are often labelled as asthmatic although the underlying mechanisms are likely to be very different. Smoking cessation, maintaining physical fitness, annual influenza immunisation and a general healthy lifestyle should be endorsed irrespective of any symptoms. There are a number of clinical and research priorities to maximise the quality of life and lung health in the longer term not least understanding the underlying mechanisms and optimising treatment, rather than extrapolating from other airway diseases.

PAlliative Care in chronic Kidney diSease: the PACKS study—quality of life, decision making, costs and impact on carers in people managed without dialysis

BACKGROUND: The number of patients with advanced chronic kidney disease opting for conservative management rather than dialysis is unknown but likely to be growing as increasingly frail patients with advanced renal disease present to renal services. Conservative kidney management includes ongoing medical input and support from a multidisciplinary team. There is limited evidence concerning patient and carer experience of this choice. This study will explore quality of life, symptoms, cognition, frailty, performance decision making, costs and impact on carers in people with advanced chronic kidney disease managed without dialysis and is funded by the National Institute of Health Research in the UK.

METHODS: In this prospective, multicentre, longitudinal study, patients will be recruited in the UK, by renal research nurses, once they have made the decision not to embark on dialysis. Carers will be asked to 'opt-in' with consent from patients. The approach includes longitudinal quantitative surveys of quality of life, symptoms, decision making and costs for patients and quality of life and costs for carers, with questionnaires administered quarterly over 12 months. Additionally, the decision making process will be explored via qualitative interviews with renal physicians/clinical nurse specialists.

DISCUSSION: The study is designed to capture patient and carer profiles when conservative kidney management is implemented, and understand trajectories of care-receiving and care-giving with the aim of optimising palliative care for this population. It will explore the interactions that lead to clinical care decisions and the impact of these decisions on informal carers with the intention of improving clinical outcomes for patients and the experiences of care givers.

Application-Level Energy Awareness for OpenMP

Power, and consequently energy, has recently attained first-class system resource status, on par with conventional metrics such as CPU time. To reduce energy consumption, many hardware- and OS-level solutions have been investigated. However, application-level information - which can provide the system with valuable insights unattainable otherwise - was only considered in a handful of cases. We introduce OpenMPE, an extension to OpenMP designed for power management. OpenMP is the de-facto standard for programming parallel shared memory systems, but does not yet provide any support for power control. Our extension exposes (i) per-region multi-objective optimization hints and (ii) application-level adaptation parameters, in order to create energy-saving opportunities for the whole system stack. We have implemented OpenMPE support in a compiler and runtime system, and empirically evaluated its performance on two architectures, mobile and desktop. Our results demonstrate the effectiveness of OpenMPE with geometric mean energy savings across 9 use cases of 15 % while maintaining full quality of service.

The determination of optimal processing conditions for PLA and PLA/CaCO3 in twin screw extrusion using DoE and multivariate analysis

Biodegradable polymers, such as PLA (Polylactide), come from renewable resources like corn starch and if disposed of correctly, degrade and become harmless to the ecosystem making them attractive alternatives to petroleum based polymers. PLA in particular is used in a variety of applications including medical devices, food packaging and waste disposal packaging. However, the industry faces challenges in melt processing of PLA due to its poor thermal stability which is influenced by processing temperatures and shearing.
Identification and control of suitable processing conditions is extremely challenging, usually relying on trial and error, and often sensitive to batch to batch variations. Off-line assessment in a lab environment can result in high scrap rates, long lead times and lengthy and expensive process development. Scrap rates are typically in the region of 25-30% for medical grade PLA costing between €2000-€5000/kg.
Additives are used to enhance material properties such as mechanical properties and may also have a therapeutic role in the case of bioresorbable medical devices, for example the release of calcium from orthopaedic implants such as fixation screws promotes healing. Additives can also reduce the costs involved as less of the polymer resin is required.
This study investigates the scope for monitoring, modelling and optimising processing conditions for twin screw extrusion of PLA and PLA w/calcium carbonate to achieve desired material properties. A DAQ system has been constructed to gather data from a bespoke measurement die comprising melt temperature; pressure drop along the length of the die; and UV-Vis spectral data which is shown to correlate to filler dispersion. Trials were carried out under a range of processing conditions using a Design of Experiments approach and samples were tested for mechanical properties, degradation rate and the release rate of calcium. Relationships between recorded process data and material characterisation results are explored.

Any versus long-term prescribing of high risk medications in older people using 2012 Beers Criteria: results from three cross-sectional samples of primary care records for 2003/4, 2007/8 and 2011/12

Background: High risk medications are commonly prescribed to older US patients. Currently, less is known about high risk medication prescribing in other Western Countries, including the UK. We measured trends and correlates of high risk medication prescribing in a subset of the older UK population (community/institutionalized) to inform harm minimization efforts. Methods: Three cross-sectional samples from primary care electronic clinical records (UK Clinical Practice Research Datalink, CPRD) in fiscal years 2003/04, 2007/08 and 2011/12 were taken. This yielded a sample of 13,900 people aged 65 years or over from 504 UK general practices. High risk medications were defined by 2012 Beers Criteria adapted for the UK. Using descriptive statistical methods and regression modelling, prevalence of ‘any’ (drugs prescribed at least once per year) and ‘long-term’ (drugs prescribed all quarters of year) high risk medication prescribing and correlates were determined. Results: While polypharmacy rates have risen sharply, high risk medication prevalence has remained stable across a decade. A third of older (65+) people are exposed to high risk medications, but only half of the total prevalence was long-term (any = 38.4 % [95 % CI: 36.3, 40.5]; long-term = 17.4 % [15.9, 19.9] in 2011/12). Long-term but not any high risk medication exposure was associated with older ages (85 years or over). Women and people with higher polypharmacy burden were at greater risk of exposure; lower socio-economic status was not associated. Ten drugs/drug classes accounted for most of high risk medication prescribing in 2011/12. Conclusions: High risk medication prescribing has not increased over time against a background of increasing polypharmacy in the UK. Half of patients receiving high risk medications do so for less than a year. Reducing or optimising the use of a limited number of drugs could dramatically reduce high risk medications in older people. Further research is needed to investigate why the oldest old and women are at greater risk. Interventions to reduce high risk medications may need to target shorter and long-term use separately.

Methods for Optimal Work Instruction Delivery: Pictograms v Images

This paper focuses on quantifying the benefits of pictogram based instructions relative to static images for work instruction delivery. The assembly of a stiffened aircraft panel has been used as an exemplar for the work which seeks to address the challenge of identifying an instructional mode that can be location or language neutral while at the same time optimising assembly build times and maintaining build quality. Key performance parameters measured using a series of panel build experiments conducted by two separate groups were: overall build time, the number of subject references to instructional media, the number of build errors and the time taken to correct any mistakes. Overall build time for five builds for a group using pictogram instructions was about 20% lower than for the group using image based instructions. Also, the pictogram group made fewer errors. Although previous work identified that animated instructions result in optimal build times, the language neutrality of pictograms as well as the fact that they can be used without visualisation hardware mean that, on balance, they have broader applicability in terms of transferring assembly knowledge to the manufacturing environment.

Injurious tail biting in pigs: How can it be controlled in existing systems without tail docking?

Tail biting is a serious animal welfare and economic problem in pig production. Tail docking, which reduces but does not eliminate tail biting, remains widespread. However, in the EU tail docking may not be used routinely, and some 'alternative' forms of pig production and certain countries do not allow tail docking at all. Against this background, using a novel approach focusing on research where tail injuries were quantified, we review the measures that can be used to control tail biting in pigs without tail docking. Using this strict criterion, there was good evidence that manipulable substrates and feeder space affect damaging tail biting. Only epidemiological evidence was available for effects of temperature and season, and the effect of stocking density was unclear. Studies suggest that group size has little effect, and the effects of nutrition, disease and breed require further investigation. The review identifies a number of knowledge gaps and promising avenues for future research into prevention and mitigation. We illustrate the diversity of hypotheses concerning how different proposed risk factors might increase tail biting through their effect on each other or on the proposed underlying processes of tail biting. A quantitative comparison of the efficacy of different methods of provision of manipulable materials, and a review of current practices in countries and assurance schemes where tail docking is banned, both suggest that daily provision of small quantities of destructible, manipulable natural materials can be of considerable benefit. Further comparative research is needed into materials, such as ropes, which are compatible with slatted floors. Also, materials which double as fuel for anaerobic digesters could be utilised. As well as optimising housing and management to reduce risk, it is important to detect and treat tail biting as soon as it occurs. Early warning signs before the first bloody tails appear, such as pigs holding their tails tucked under, could in future be automatically detected using precision livestock farming methods enabling earlier reaction and prevention of tail damage. However, there is a lack of scientific studies on how best to respond to outbreaks: the effectiveness of, for example, removing biters and/or bitten pigs, increasing enrichment, or applying substances to tails should be investigated. Finally, some breeding companies are exploring options for reducing the genetic propensity to tail bite. If these various approaches to reduce tail biting are implemented we propose that the need for tail docking will be reduced. © 2014 The Animal Consortium.

Physical model parameter optimisation for calibrated emulation of the Dallas Rangemaster Treble Booster guitar pedal

In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.