Acute ingestion of beetroot bread increases endothelium-independent vasodilation and lowers diastolic blood pressure in healthy men: a randomized controlled trial

Dietary nitrate, from beetroot, has been reported to lower blood pressure (BP) by the sequential reduction of nitrate to nitrite and further to NO in the circulation. However, the impact of beetroot on microvascular vasodilation and arterial stiffness is unknown. In addition, beetroot is consumed by only 4.5% of the UK population, whereas bread is a staple component of the diet. Thus, we investigated the acute effects of beetroot bread (BB) on microvascular vasodilation, arterial stiffness, and BP in healthy participants. Twenty-three healthy men received 200 g bread containing 100 g beetroot (1.1 mmol nitrate) or 200 g control white bread (CB; 0 g beetroot, 0.01 mmol nitrate) in an acute, randomized, open-label, controlled crossover trial. The primary outcome was postprandial microvascular vasodilation measured by laser Doppler iontophoresis and the secondary outcomes were arterial stiffness measured by Pulse Wave Analysis and Velocity and ambulatory BP measured at regular intervals for a total period of 6 h. Plasma nitrate and nitrite were measured at regular intervals for a total period of 7 h. The incremental area under the curve (0-6 h after ingestion of bread) for endothelium-independent vasodilation was greater (P = 0.017) and lower for diastolic BP (DBP; P = 0.032) but not systolic (P = 0.99) BP after BB compared with CB. These effects occurred in conjunction with increases in plasma and urinary nitrate (P < 0.0001) and nitrite (P < 0.001). BB acutely increased endothelium-independent vasodilation and decreased DBP. Therefore, enriching bread with beetroot may be a suitable vehicle to increase intakes of cardioprotective beetroot in the diet and may provide new therapeutic perspectives in the management of hypertension.

Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

Randomized controlled trial of parent-enhanced CBT compared with individual CBT for obsessive-compulsive disorder in young people

Objective: Obsessive-compulsive disorder (OCD) in young people can be effectively treated with Cognitive Behavior Therapy (CBT). Practice guidelines in the United Kingdom recommend that CBT be delivered with parental or family involvement; however, there is no evidence from randomized trials that this enhances effectiveness. The aim of this trial was to assess if CBT with high parental involvement was more effective than CBT with low parental involvement (individual CBT) in reducing symptoms of OCD. Method: Fifty young people ages 12–17 years with OCD were randomly allocated to individual CBT or parent-enhanced CBT. In parent-enhanced CBT parents attended all treatment sessions; in individual CBT, parents attended only Sessions 1, 7, and the final session. Participants received up to 14 sessions of CBT. Data were analyzed using intent-to-treat and per-protocol methods. The primary outcome measure was the Children’s Yale-Brown Obsessive Compulsion Scale (Scahill et al., 1997). Results: Both forms of CBT significantly reduced symptoms of OCD and anxiety. Change in OCD symptoms was maintained at 6 months. Per-protocol analysis suggested that parent-enhanced CBT may be associated with significantly larger reductions in anxiety symptoms. Conclusions: High and low parental involvement in CBT for OCD in young people were both effective, and there was no evidence that 1 method of delivery was superior on the primary outcome measure. However, this study was small. Future trials should be adequately powered and examine interactions with the age of the young person and comorbid anxiety disorders.

Magnetic resonance imaging of a randomized controlled trial investigating predictors of recovery following psychological treatment in adolescents with moderate to severe unipolar depression: study protocol for Magnetic Resonance - Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT)

Background Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. Methods/Design Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). Discussion MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.

Sea surface temperature climate change initiative: alternative image classification algorithms for sea-ice affected oceans

We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.

Flavonoid-rich fruits and vegetables improve microvascular reactivity and inflammatory status in men at risk of cardiovascular disease – FLAVURS: a randomized controlled trial

BACKGROUND: Observed associations between increased fruit and vegetable (F&V) consumption, particularly those F&Vs that are rich in flavonoids, and vascular health improvements require confirmation in adequately powered randomized controlled trials. OBJECTIVE: This study was designed to measure the dose-response relation between high-flavonoid (HF), low-flavonoid (LF), and habitual F&V intakes and vascular function and other cardiovascular disease (CVD) risk indicators. DESIGN: A single-blind, dose-dependent, parallel randomized controlled dietary intervention study was conducted. Male and female low-F&V consumers who had a ≥1.5-fold increased risk of CVD (n = 174) were randomly assigned to receive an HF F&V, an LF F&V, or a habitual diet, with HF and LF F&V amounts sequentially increasing by 2, 4, and 6 (+2, +4, and +6) portions/d every 6 wk over habitual intakes. Microvascular reactivity (laser Doppler imaging with iontophoresis), arterial stiffness [pulse wave velocity, pulse wave analysis (PWA)], 24-h ambulatory blood pressure, and biomarkers of nitric oxide (NO), vascular function, and inflammation were determined at baseline and at 6, 12, and 18 wk. RESULTS: In men, the HF F&V diet increased endothelium-dependent microvascular reactivity (P = 0.017) with +2 portions/d (at 6 wk) and reduced C-reactive protein (P = 0.001), E-selectin (P = 0.0005), and vascular cell adhesion molecule (P = 0.0468) with +4 portions/d (at 12 wk). HF F&Vs increased plasma NO (P = 0.0243) with +4 portions/d (at 12 wk) in the group as a whole. An increase in F&Vs, regardless of flavonoid content in the groups as a whole, mitigated increases in vascular stiffness measured by PWA (P = 0.0065) and reductions in NO (P = 0.0299) in the control group. CONCLUSION: These data support recommendations to increase F&V intake to ≥6 portions daily, with additional benefit from F&Vs that are rich in flavonoids, particularly in men with an increased risk of CVD. This trial was registered at www.controlled-trials.com as ISRCTN47748735.

Fast identification algorithms for Gaussian process model

A class identification algorithms is introduced for Gaussian process(GP)models.The fundamental approach is to propose a new kernel function which leads to a covariance matrix with low rank,a property that is consequently exploited for computational efficiency for both model parameter estimation and model predictions.The objective of either maximizing the marginal likelihood or the Kullback–Leibler (K–L) divergence between the estimated output probability density function(pdf)and the true pdf has been used as respective cost functions.For each cost function,an efficient coordinate descent algorithm is proposed to estimate the kernel parameters using a one dimensional derivative free search, and noise variance using a fast gradient descent algorithm. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis

Satellite data are increasingly used to provide observation-based estimates of the effects of aerosols on climate. The Aerosol-cci project, part of the European Space Agency's Climate Change Initiative (CCI), was designed to provide essential climate variables for aerosols from satellite data. Eight algorithms, developed for the retrieval of aerosol properties using data from AATSR (4), MERIS (3) and POLDER, were evaluated to determine their suitability for climate studies. The primary result from each of these algorithms is the aerosol optical depth (AOD) at several wavelengths, together with the Ångström exponent (AE) which describes the spectral variation of the AOD for a given wavelength pair. Other aerosol parameters which are possibly retrieved from satellite observations are not considered in this paper. The AOD and AE (AE only for Level 2) were evaluated against independent collocated observations from the ground-based AERONET sun photometer network and against “reference” satellite data provided by MODIS and MISR. Tools used for the evaluation were developed for daily products as produced by the retrieval with a spatial resolution of 10 × 10 km2 (Level 2) and daily or monthly aggregates (Level 3). These tools include statistics for L2 and L3 products compared with AERONET, as well as scoring based on spatial and temporal correlations. In this paper we describe their use in a round robin (RR) evaluation of four months of data, one month for each season in 2008. The amount of data was restricted to only four months because of the large effort made to improve the algorithms, and to evaluate the improvement and current status, before larger data sets will be processed. Evaluation criteria are discussed. Results presented show the current status of the European aerosol algorithms in comparison to both AERONET and MODIS and MISR data. The comparison leads to a preliminary conclusion that the scores are similar, including those for the references, but the coverage of AATSR needs to be enhanced and further improvements are possible for most algorithms. None of the algorithms, including the references, outperforms all others everywhere. AATSR data can be used for the retrieval of AOD and AE over land and ocean. PARASOL and one of the MERIS algorithms have been evaluated over ocean only and both algorithms provide good results.

Automated algorithms for multilayer thin film filter design using metamaterials

Currently, infrared filters for astronomical telescopes and satellite radiometers are based on multilayer thin film stacks of alternating high and low refractive index materials. However, the choice of suitable layer materials is limited and this places limitations on the filter performance that can be achieved. The ability to design materials with arbitrary refractive index allows for filter performance to be greatly increased but also increases the complexity of design. Here a differential algorithm was used as a method for optimised design of filters with arbitrary refractive indices, and then materials are designed to these specifications as mono-materials with sub wavelength structures using Bruggeman’s effective material approximation (EMA).

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

Apolipoprotein e genotype has a modest impact on the postprandial plasma response to meals of varying fat composition in healthy men in a randomized controlled trial

BACKGROUND:Apolioprotein E (APOE) genotype is reported to influence a person's fasting lipid profile and potentially the response to dietary fat manipulation. The impact of APOE genotype on the responsiveness to meals of varying fat composition is unknown. OBJECTIVE:We examined the effect of meals containing 50 g of fat rich in saturated fatty acids (SFAs), unsaturated fatty acids (UNSATs), or SFAs with fish oil (SFA-FO) on postprandial lipemia. METHOD:A randomized, controlled, test meal study was performed in men recruited according to the APOE genotype (n = 10 APOE3/3, n = 11 APOE3/E4). RESULTS:For the serum apoE response (meal × genotype interaction P = 0.038), concentrations were on average 8% lower after the UNSAT than the SFA-FO meal in APOE4 carriers (P = 0.015) only. In the genotype groups combined, there was a delay in the time to reach maximum triacylglycerol (TG) concentration (mean ± SEM: 313 ± 25 vs. 266 ± 27 min) and higher maximum nonesterified fatty acid (0.73 ± 0.05 vs. 0.60 ± 0.03 mmol/L) and glucose (7.92 ± 0.22 vs. 7.25 ± 0.22 mmol/L) concentrations after the SFA than the UNSAT meal, respectively (P ≤ 0.05). In the Svedberg flotation rate 60-400 TG-rich lipoprotein fraction, meal × genotype interactions were observed for incremental area under the curve (IAUC) for the TG (P = 0.038) and apoE (P = 0.016) responses with a 58% lower apoE IAUC after the UNSAT than the SFA meal (P = 0.017) in the E4 carriers. CONCLUSIONS:Our data indicate that APOE genotype had a modest impact on the postprandial response to meals of varying fat composition in normolipidemic men. The physiologic importance of greater apoE concentrations after the SFA-rich meals in APOE4 carriers may reflect an impact on TG-rich lipoprotein clearance from the circulation. This trial was registered at clinicaltrials.gov as NCT01522482.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Orange juice–derived flavanone and phenolic metabolites do not acutely affect cardiovascular risk biomarkers: a randomized, placebo-controlled, crossover trial in men at moderate risk of cardiovascular disease

Background: Epidemiological data suggest inverse associations between citrus flavanone intake and cardiovascular disease (CVD) risk. However, insufficient randomized controlled trial (RCT) data limit our understanding of mechanisms by which flavanones and their metabolites potentially reduce cardiovascular (CV) risk factors. Objective: We examined the effects of orange juice or a dose-matched hesperidin supplement on plasma concentrations of established and novel flavanone metabolites and their effects on CV risk biomarkers in men at moderate CVD risk. Methods: In an acute, randomized, placebo-controlled crossover trial, 16 fasted participants (aged 51-69 y) received orange juice or a hesperidin supplement (both providing 320 mg hesperidin) or control (all matched for sugar and vitamin C content). At baseline and 5 h post-intake, endothelial function (primary outcome), further CV risk biomarkers (i.e. blood pressure, arterial stiffness, cardiac autonomic function, platelet activation and NADPH oxidase gene expression) and plasma flavanone metabolites were assessed. Prior to each intervention, a diet low in flavonoids, nitrate/nitrite, alcohol and caffeine was followed and a standardized low-flavonoid evening meal was consumed. Results: Orange juice intake significantly elevated mean (± SEM) plasma concentrations of 8 flavanone (1.75 ± 0.35 µmol/L, P < 0.0001) and 15 phenolic metabolites (13.27 ± 2.22 µmol/L, P < 0.0001) compared with control at 5 h post-consumption. Despite increased plasma flavanone and phenolic metabolite concentrations, CV risk biomarkers were unaltered. Following hesperidin supplement intake, flavanone metabolites were not different to control, suggesting altered absorption/metabolism compared with the orange juice matrix. Conclusions: Following single-dose flavanone intake within orange juice, we detected circulating flavanone and phenolic metabolites collectively reaching a concentration of 15.20 ± 2.15 µmol/L but observed no effect on CV risk biomarkers. Longer-duration RCTs are required to further examine the previous associations between higher flavanone intakes and improved cardiovascular health and to ascertain the relative importance of food matrix and flavanone-derived phenolic metabolites.

Rapid preconditioning of data for accelerating convex hull algorithms

Given a dataset of two-dimensional points in the plane with integer coordinates, the method proposed reduces a set of n points down to a set of s points s ≤ n, such that the convex hull on the set of s points is the same as the convex hull of the original set of n points. The method is O(n). It helps any convex hull algorithm run faster. The empirical analysis of a practical case shows a percentage reduction in points of over 98%, that is reflected as a faster computation with a speedup factor of at least 4.