Chronic hypoxia in high altitude constitutes an associated factor for fetal growth restriction, even when there is genetic adaptation, as observed in studies performed in populations living at high altitudes (Tibet, Andes, Europe and North America). Socioeconomic and nutritional deprivation is frequently observed in those populations, being also associated to fetal growth. Objective: To analyze anthropometric measures at birth in relation with altitude, and to assess the effect of maternal nutrition status, socioeconomic conditions and altitude on those measures. Population and methods: The study was based on the information registered in the Perinatal Information System (SIP -Clap-OPS) by the provincial team from the province of Jujuy and forwarded to national level, between 1996 -1998. Variables included pre-gestational BMI, maternal weight gain, maternal education, birth weight (BW), length at birth (LB), and head circumference (HC). Cases were grouped in three categories according to the altitude of the institution where the childbirth was attended: 84.1% R1, 5.8% R2 and 10.1% R3, being the latter the area at higher altitude (Puna). Confounding variables were controlled by exclusion and analytical tools. Results: From 25,811 registries, 24,651 with complete information were selected. Mean BW was 3259 Ϯ 538 g in R1; 3162 Ϯ 420 in R2, and 3080 Ϯ 483 in R3, with a difference of 179 grams between R1 and R3, (F 110.7; p Ͻ 0.001) and 209 g between R1 and R3 (F 199; p Ͻ 0.001) in term deliveries. In this group, LB difference was 0.3 cm (Fϭ274,9, pϽ0.001), and HC difference was 0.6 cm (F102.7; p Ͻ 0.001) between low and highlands (R1 and R3, respectively). Multivariate analysis, by linear regression, showed a final model to predict BW ϭ -1557.4 183.2 * birth at high altitude ϩ 28.9 * parity ϩ 13.3 * 8.7 BMI ϩ 8.7 * maternal weight gain ϩ 113.3 * gestational age at birth ϩ ⌺. Conclusion: Altitude influences BW significantly. Nevertheless, nutritional and social factors have a direct and sinergic relationship with BW. Background. Reduced iron is one of the most commonly used iron fortificants, because of its low cost and lack of chemical reactivity. The bioavailability of this fortificant has not been reliably measured in humans because of technical difficulties. Objective. To assess iron bioavailability of wheat flour fortified with reduced iron. Methods. Homemade bread fortified with two reduced iron compounds was produced. We used an in vitro digestion and the Caco-2 cells model to measure the bioavailability of two types of reduced Fe (8 and Ͼ20 m particle size), using ferritin formation by Caco-2 cells and intracellular Fe concentration as indicators of Fe incorporated to the enterocyte. Results. In vitro digestion experiments showed higher values of solubility and dialyzability of reduced-8 m Fe compared to reduced Ͼ20 m Fe. Intracellular iron and ferritin concentrations in Caco-2 cells exposed to digest from bread fortified with reduced-8 m Fe were higher than in bread fortified with reduced Ͼ20 m Fe. When brea...
Introduction: Many adaptive systems are difficult to analyze and to control using traditional techniques. Aims: In this work, we introduce a computerized tool to study agents having a life cycle, which evolve through time, and are subject to stochastic events. Methods: We used population's dynamic techniques and the high capability of computer systems to process data to build a simulator, which was developed using techniques based on evolution and adaptation of the best, known as genetic algorithms, introducing stochastic methods to model situations where the occurrence of events has a given probability distribution. To model the system, it is necessary to set up the software with environmental properties, to define the genotype information for each type of agent, and to include the rules to confer the phenotype. Also, it is possible to shape several aspects like the main data of the life cycle of the agents. Results: With all the data, the soft has an initial population with a required amount of agents and simulates the population's development across the time. For each interval of time it is possible to observe the population's density, to analyze the genetic evolution and to extract statistical data about the main characteristics of each agent. Comments: This tool is appropriate to simulate epidemiological events, because it is possible to simulate the development of one or more populations under different environments and conditions, during different intervals of time. It is also useful to identify the main features that may alter the system.
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