Effectiveness of an mHealth intervention combining a smartphone app and smart band on body composition in an overweight and obese population: Randomized controlled trial (EVIDENT 3 study)

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect

From genomes to systems: the path with yeast

Metabolic Control Analysis (MCA) is a conceptual and mathematical formalism that models the relative contributions of individual effectors in a pathway to both the flux through the pathway and the concentrations of individual intermediates within it. To exploit MCA in an initial Systems Biology analysis of the eukaryotic cell, two categories of experiments are required. In category 1 experiments, flux is changed and the impact on the levels of the direct and indirect products of gene action is measured. We have measured the impact of changing the flux on the transcriptome, proteome and metabolome of Saccharomyces cerevisiae. In this whole-cell analysis, flux equates to growth rate. In category 2 experiments, the levels of individual gene products are altered, and the impact on the flux is measured. We have used competition analyses between the complete set of heterozygous yeast deletion mutants to reveal genes encoding proteins with high flux control coefficients. These genes may be exploited, in a top-down analysis, to build a coarse-grained model of the eukaryotic cell, as exemplified by yeast. More detailed modelling requires that ‘natural’ biological systems be identified. The combination of flux balance analysis with both genetics and metabolomics in the definition of metabolic systems is discussed

Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models

Biological functions require a coherent cross talk among multiple layers of regulation within the cell. Computational efforts that aim to understand how these layers are integrated across spatial, temporal, and functional scales represent a challenge in Systems Biology. We have developed a computational, multi-scale framework that couples cell cycle and metabolism networks in the budding yeast cell. Here we describe the methodology at the basis of this framework, which integrates on off-the-shelf logical (Boolean) models of a minimal yeast cell cycle with a constraint-based model of metabolism (i.e., the Yeast 7 metabolic network reconstruction). Models are implemented in Python code using the BooleanNet and COBRApy packages, respectively, and are connected through the Boolean logic. The methodology allows for incorporation of interaction data, and validation through –omics data. Furthermore, evolutionary strategies may be incorporated to explore regulatory structures underlying coherent cross talks among regulatory layers

Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models

Biological functions require a coherent cross talk among multiple layers of regulation within the cell. Computational efforts that aim to understand how these layers are integrated across spatial, temporal, and functional scales represent a challenge in Systems Biology. We have developed a computational, multi-scale framework that couples cell cycle and metabolism networks in the budding yeast cell. Here we describe the methodology at the basis of this framework, which integrates on off-the-shelf logical (Boolean) models of a minimal yeast cell cycle with a constraint-based model of metabolism (i.e., the Yeast 7 metabolic network reconstruction). Models are implemented in Python code using the BooleanNet and COBRApy packages, respectively, and are connected through the Boolean logic. The methodology allows for incorporation of interaction data, and validation through –omics data. Furthermore, evolutionary strategies may be incorporated to explore regulatory structures underlying coherent cross talks among regulatory layers

Coordination of sucrose uptake and respiration in the yeast Debaryomyces yamadae

Screening in batch cultures identified Debaryomyces yamadae as a yeast that exhibits the Kluyver effect for sucrose: this disaccharide can be respired but, even under oxygen-limited conditions, alcoholic fermentation of sucrose does not occur. Ethanol, glycerol and arabitol were the main fermentation products during oxygen-limited growth on glucose in chemostat cultures. None of these fermentation products were produced in oxygen-limited chemostat cultures grown on sucrose and the fraction of the sucrose that could not be respired remained unused in the culture medium. This absence of alcoholic fermentation was not due to repression of the key fermentative enzymes pyruvate decarboxylase and alcohol dehydrogenase. In contrast to some other yeasts that exhibit a Kluyver effect, D. yamadae did not exhibit a preference for ethanol in batch cultures grown on mixtures of ethanol and sucrose. Sucrose metabolism in D. yamadae involves intracellular hydrolysis by an α-glucosidase. Incubation of weakly buffered cell suspensions with sucrose led to a rapid transient alkalinization, indicating the presence of a sucrose-proton symport system. The apparent substrate saturation constant of the sucrose-uptake system was 0.2 mmol l-1. Sucrose-dependent alkalinization rates were much lower in samples from oxygen-limited cultures than in samples from aerobic cultures. Transient responses of D. yamadae to oxygen limitation were investigated by applying a sudden decrease in the oxygen feed to aerobic sugar-limited chemostat cultures. In glucose grown cultures, this led to alcoholic fermentation and no significant accumulation of sugar occurred after the switch. In sucrose-limited cultures, sugar accumulation occurred instantaneously after the switch, and ethanol formation was virtually absent. The results indicate that the Kluyver effect for sucrose in D. yamadae, i.e. the adjustment of the glycolytic flux to the cells' respiratory capacity, is effected by rapid down-regulation of the capacity of the sucrose carrier under oxygen-limited conditions

EFEITO DE ÉPOCAS DE DEFICIÊNCIA HÍDRICA NA EFICIÊNCIA DO USO DO NITROGÊNIO DA CULTURA DO FEIJÃO cv. IMBABELLO

Visando identificar estádios da cultura de feijão que apresentam a menor sensibilidade ao estresse de água no solo, nos quais a irrigação pode ser omitida sem um significativo decréscimo na eficiência de uso de nitrogênio e na produtividade final, foi realizado experimento em um solo franco arenoso (Typic Haplustoll) na Estação Experimental da Universidade Central do Equador, "La Tola", em Tumbaco-Pichincha, Equador, entre julho e novembro de 1994. Os tratamentos consistiram da combinação de sete regimes de irrigação, incluindo irrigação ótima durante todo o ciclo, irrigação deficiente durante todo o ciclo, irrigação tradicional da região, deficiência hídrica no período vegetativo, na floração e formação de vagens, no enchimento de vagens e na maturidade; e de dois níveis de adubação nitrogenada (20 kg N/ha e 80 kg N/ha). Os quatorze tratamentos resultantes foram arranjados e analisados num esquema de parcelas sub-divididas com quatro repetições. O tamanho da parcela experimental foi de 33,6 m2 (8 linhas de 7 metros de comprimento, distantes entre si 0,6 m) com uma população de 120.000 plantas/ha. O nitrogênio fixado do ar pelo feijoeiro foi calculado pelo método de diluição isotópica do 15N, no tratamento com adubação de 20 kg N/ha. A solução marcada foi de sulfato de amônio, com abundância de 5% de átomos de 15N. Como planta-controle, foi utilizado o trigo, semeado no sulco central. Da análise dos resultados obtidos, concluiu-se que: A deficiência de água no solo, durante a fase vegetativa, não afetou a eficiência de uso de nitrogênio, a fixação biológica do nitrogênio, nem a produção de sementes, permitindo uma economia de água de 30%. A deficiência de água durante a floração e enchimento de vagens, afetou drasticamente a fixação biológica do nitrogênio, que comparativamente ao controle, foi reduzida 2,2 vezes.<br>To identify specific growth stages of the common bean crop at which the plant is less sensitive to water stress, in which irrigation could be omitted without significant decrease in biological nitrogen fixation and final yield, a field experiment was conducted at "La Tola" University Experiment Station, Tumbaco, Pichincha, Ecuador, on a sandy loam soil (Typic Haplustoll). The treatments consisted of the combinations of seven irrigation regimes, including normal watering, full stress, traditional practice, single stress at vegetation, at flowering, at yield formation and at ripening, and two levels of applied N (20 and 80 kg/ha). These fourteen treatment combinations were arranged and analysed in a split-plot design with four replications. The plot size was 33.6 m2 (8 rows, 7 m long) with a population of 120,000 plants/ha. Irrigation treatments were started after uniform germination and crop establishment. Soil moisture was monitored with neutron probe down to the 0.50 m depth, 24 hours before and after each irrigation. Nitrogen Fixation was calculated using the 15N methodology for the 20 kg N/ha treatment. Yield data show that treatments which had irrigation deficit had lower yield than those with supplementary irrigation. Nitrogen fertilization significantly increased the number of pods and grain yield. Biological Nitrogen Fixation was significantly affected by water stress at the flowering and yield formation stages