Energy compensation following consumption of sugar-reduced products: a randomized controlled trial

PURPOSE: Consumption of sugar-reformulated products (commercially available foods and beverages that have been reduced in sugar content through reformulation) is a potential strategy for lowering sugar intake at a population level. The impact of sugar-reformulated products on body weight, energy balance (EB) dynamics and cardiovascular disease risk indicators has yet to be established. The REFORMulated foods (REFORM) study examined the impact of an 8-week sugar-reformulated product exchange on body weight, EB dynamics, blood pressure, arterial stiffness, glycemia and lipemia. METHODS: A randomized, controlled, double-blind, crossover dietary intervention study was performed with fifty healthy normal to overweight men and women (age 32.0 ± 9.8 year, BMI 23.5 ± 3.0 kg/m2) who were randomly assigned to consume either regular sugar or sugar-reduced foods and beverages for 8 weeks, separated by 4-week washout period. Body weight, energy intake (EI), energy expenditure and vascular markers were assessed at baseline and after both interventions. RESULTS: We found that carbohydrate (P < 0.001), total sugars (P < 0.001) and non-milk extrinsic sugars (P < 0.001) (% EI) were lower, whereas fat (P = 0.001) and protein (P = 0.038) intakes (% EI) were higher on the sugar-reduced than the regular diet. No effects on body weight, blood pressure, arterial stiffness, fasting glycemia or lipemia were observed. CONCLUSIONS: Consumption of sugar-reduced products, as part of a blinded dietary exchange for an 8-week period, resulted in a significant reduction in sugar intake. Body weight did not change significantly, which we propose was due to energy compensation.

Dietary nitrate improves vascular function in patients with hypercholesterolemia: a randomized, double-blind, placebo-controlled study

Background: The beneficial cardiovascular effects of vegetables may be underpinned by their high inorganic nitrate content. Objective: We sought to examine the effects of a 6-wk once-daily intake of dietary nitrate (nitrate-rich beetroot juice) compared with placebo intake (nitrate-depleted beetroot juice) on vascular and platelet function in untreated hypercholesterolemics. Design: A total of 69 subjects were recruited in this randomized, double-blind, placebo-controlled parallel study. The primary endpoint was the change in vascular function determined with the use of ultrasound flow-mediated dilatation (FMD). Results: Baseline characteristics were similar between the groups, with primary outcome data available for 67 patients. Dietary nitrate resulted in an absolute increase in the FMD response of 1.1% (an ∼24% improvement from baseline) with a worsening of 0.3% in the placebo group (P < 0.001). A small improvement in the aortic pulse wave velocity (i.e., a decrease of 0.22 m/s; 95% CI: −0.4, −0.3 m/s) was evident in the nitrate group, showing a trend (P = 0.06) to improvement in comparison with the placebo group. Dietary nitrate also caused a small but significant reduction (7.6%) in platelet-monocyte aggregates compared with an increase of 10.1% in the placebo group (P = 0.004), with statistically significant reductions in stimulated (ex vivo) P-selectin expression compared with the placebo group (P < 0.05) but no significant changes in unstimulated expression. No adverse effects of dietary nitrate were detected. The composition of the salivary microbiome was altered after the nitrate treatment but not after the placebo treatment (P < 0.01). The proportions of 78 bacterial taxa were different after the nitrate treatment; of those taxa present, 2 taxa were responsible for >1% of this change, with the proportions of Rothia mucilaginosa trending to increase and Neisseria flavescens (P < 0.01) increased after nitrate treatment relative to after placebo treatment. Conclusions: Sustained dietary nitrate ingestion improves vascular function in hypercholesterolemic patients. These changes are associated with alterations in the oral microbiome and, in particular, nitrate-reducing genera. Our findings provide additional support for the assessment of the potential of dietary nitrate as a preventative strategy against atherogenesis in larger cohorts. This trial was registered at clinicaltrials.gov as NCT01493752.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.

Selecting algorithms for Earth observation of climate within the European Space Agency Climate Change initiative: introduction to a special issue

This special issue is focused on the assessment of algorithms for the observation of Earth’s climate from environ- mental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth’s climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temper- ature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as re- quiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observa- tional contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust.

Acute benefits of the microbial-derived isoflavone metabolite equol on arterial stiffness in men prospectively recruited according to equol producer phenotype: a double-blind randomized controlled trial

There is much speculation with regard to the potential cardioprotective benefits of equol, a microbial-derived metabolite of the isoflavone daidzein, which is produced in the large intestine after soy intake in 30% of Western populations. Although cross-sectional and retrospective data support favorable associations between the equol producer (EP) phenotype and cardiometabolic health, few studies have prospectively recruited EPs to confirm this association. The aim was to determine whether the acute vascular benefits of isoflavones differ according to EP phenotype and subsequently investigate the effect of providing commercially produced S-(–)equol to non-EPs. We prospectively recruited male EPs and non-EPs (n = 14/ group) at moderate cardiovascular risk into a double-blind, placebocontrolled crossover study to examine the acute effects of soy isoflavones (80-mg aglycone equivalents) on arterial stiffness [carotid-femoral pulse-wave velocity (cfPWV)], blood pressure, endothelial function (measured by using the EndoPAT 2000; Itamar Medical), and nitric oxide at baseline (0 h) and 6 and 24 h after intake. In a separate assessment, non-EPs consumed 40 mg S-(–)equol with identical vascular measurements performed 2 h after intake. After soy intake, cfPWV significantly improved in EPs at 24 h (cfPWV change from 0 h: isoflavone, 20.2 6 0.2 m/s; placebo, 0.6 6 0.2 m/s; P , 0.01), which was significantly associated with plasma equol concentrations (R = 20.36, P = 0.01). No vascular effects were observed in EPs at 6 h or in non-EPs at any time point. Similarly, no benefit of commercially produced S-(–)equol was observed in non-EPs despite mean plasma equol concentrations reaching 3.2 mmol/L. Acute soy intake improved cfPWV in EPs, equating to an 11–12% reduced risk of cardiovascular disease if sustained. However, a single dose of commercially produced equol had no cardiovascular benefits in non-EPs. These data suggest that the EP phenotype is critical in unlocking the vascular benefits of equol in men, and long-term trials should focus on confirming the implications of EP phenotype on cardiovascular health. This trial was registered at clinicaltrials.gov as NCT01530893. Am J Clin Nutr doi: 10.3945/ajcn.115.125690.

Changes in physical activity following a genetic-based internet-delivered personalized intervention: randomized controlled trial (Food4Me)

Background: There is evidence that physical activity (PA) can attenuate the influence of the fat mass- and obesity-associated (FTO) genotype on the risk to develop obesity. However, whether providing personalized information on FTO genotype leads to changes in PA is unknown. Objective: The purpose of this study was to determine if disclosing FTO risk had an impact on change in PA following a 6-month intervention. Methods: The single nucleotide polymorphism (SNP) rs9939609 in the FTO gene was genotyped in 1279 participants of the Food4Me study, a four-arm, Web-based randomized controlled trial (RCT) in 7 European countries on the effects of personalized advice on nutrition and PA. PA was measured objectively using a TracmorD accelerometer and was self-reported using the Baecke questionnaire at baseline and 6 months. Differences in baseline PA variables between risk (AA and AT genotypes) and nonrisk (TT genotype) carriers were tested using multiple linear regression. Impact of FTO risk disclosure on PA change at 6 months was assessed among participants with inadequate PA, by including an interaction term in the model: disclosure (yes/no) × FTO risk (yes/no). Results: At baseline, data on PA were available for 874 and 405 participants with the risk and nonrisk FTO genotypes, respectively. There were no significant differences in objectively measured or self-reported baseline PA between risk and nonrisk carriers. A total of 807 (72.05%) of the participants out of 1120 in the personalized groups were encouraged to increase PA at baseline. Knowledge of FTO risk had no impact on PA in either risk or nonrisk carriers after the 6-month intervention. Attrition was higher in nonrisk participants for whom genotype was disclosed (P=.01) compared with their at-risk counterparts. Conclusions: No association between baseline PA and FTO risk genotype was observed. There was no added benefit of disclosing FTO risk on changes in PA in this personalized intervention. Further RCT studies are warranted to confirm whether disclosure of nonrisk genetic test results has adverse effects on engagement in behavior change.

Randomized control trials in an imperfect world

Randomized control trials (RCTs) have become increasingly important as an evidence-based method to evaluate interventions such as government programs and policy initiatives. Frequently, however, RCTs are characterized by ``imperfect compliance'' in that not all the subjects who are randomly assigned to take a treatment choose to do so. This could result in a failure to identify the treatment effect, or the impact of the treatment on the the population. However, useful information on treatment effectiveness can still be recovered by estimating ``bounds'' or a range of values in which treatment effectiveness can lie.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.

The effects of lipoic acid and alpha-tocopherol supplementation on the lipid profile and insulin sensitivity of patients with type 2 diabetes mellitus: A randomized, double-blind, placebo-controlled trial

Antioxidants probably play an important role in the etiology of type 2 diabetes (DM2). This study evaluated the effects of supplementation with lipoic acid (LA) and alpha-tocopherol on the lipid profile and insulin sensitivity of DM2 patients. A randomized, double-blind, placebo-controlled trial involving 102 DM2 patients divided into four groups to receive daily supplementation for 4 months with: 600 mg LA (n = 26); 800 mg alpha-tocopherol (n = 25); 800 mg alpha-tocopherol + 600 mg LA (n = 25); placebo (n = 26). Plasma alpha-tocopherol, lipid profile, glucose, insulin, and the HOMA index were determined before and after supplementation. Differences within and between groups were compared by ANOVA using Bonferroni correction. Student`s t-test was used to compare means of two independent variables. The vitamin E/total cholesterol ratio improved significantly in patients supplemented with vitamin E + LA and vitamin E alone (p <= 0.001). There were improvements of the lipid fractions in the groups receiving LA and vitamin E alone or in combination, and on the HOMA index in the LA group, but not significant. The results suggest that LA and vitamin E supplementation alone or in combination did not affect the lipid profile or insulin sensitivity of DM2 patients. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Serum oxytocin concentrations in elective caesarean delivery: a randomized comparison of three infusion regimens

Background: The aim of this study was to determine serum oxytocin concentrations following different regimens of prophylactic oxytocin administration in women undergoing elective caesarean delivery. Methods: Thirty healthy pregnant patients were randomized, after clamping of the umbilical cord, to receive intravenous oxytocin in one of the following groups: G1 (n = 9), 10 IU of oxytocin infused over 30 min (0.33 IU/min); G2 (n = 11), 10 IU of oxytocin infused over 3 min and 45 s (2.67 IU/min); and G3 (n = 10), 80 IU of oxytocin infused over 30 min (2.67 IU/min). Both patient and surgeon were blinded to allocation. Uterine tone was assessed by surgical palpation. Serum oxytocin concentration was determined by enzyme immunoassay before anaesthesia (T0) and at 5 (T5), 30 (T30) and 60 (T60) min after the start of oxytocin infusion. Results: Serum oxytocin concentrations (mean standard error, ng/mL) were not significantly different in the groups at T0 (0.06 +/- 0.02, 0.04 +/- 0.02 and 0.07 +/- 0.04, respectively, P = 0.76), and T60 (0.65 +/- 0.26, 0.36 +/- 0.26 and 0.69 +/- 0.26, respectively, P = 0.58). G3 showed higher concentrations than G1 at 15 (3.65 +/- 0.74 versus 0.71 +/- 0.27, P = 0.01) and at T30 (6.19 +/- 1.19 versus 1.17 +/- 0.37, P < 0.01), and were higher than G2 at T30 (6.19 +/- 1.19 versus 0.41 +/- 0.2, P < 0.01). Haemodynamic data and uterine tone were considered satisfactory and similar in all groups. No additional uterotonic agents were needed. Conclusion: Serum oxytocin measurements made using enzyme immunoassay in healthy pregnant women undergoing elective caesarean delivery showed that administration of 80 IU oxytocin over 30 min resulted in higher serum oxytocin levels after 5 and 30 min than the two other regimens. The concentrations did not differ between groups at 60 min. (C) 2011 Elsevier Ltd. All rights reserved.

Efficacy of high intensity diode laser as an adjunct to non-surgical periodontal treatment: a randomized controlled trial

The high intensity diode laser has been studied in periodontics for the reduction of subgingival bacteria in non-surgical treatment. Our study evaluated the bacterial effect as well as changes in periodontal clinical parameters promoted by root scaling and planing associated with this wavelength. Twenty-seven patients randomly assigned in two groups underwent root scaling and planing on the tested sites, and only the experimental group received the diode laser irradiation. Among the clinical parameters studied, the clinical probing depth (CPD) and the clinical attachment level (CAL) resulted in significant enhancement in the control group when compared with the experimental group (P = 0.014 and P = 0.039, respectively). The results were similar for both groups regarding the plaque index (PI) and bleeding on probing (BP). No significant difference in the microbiological parameters was observed between the control and experimental groups. It was possible to conclude that the high power diode laser adjunct to the non-surgical periodontal treatment did not promote additional effects to the conventional periodontal treatment.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.