Dietary Nutrient Intake and Obesity Prevalence Among Native American Adolescents

The prevalence of obesity among adolescent minority populations has been long recognized, but little research has been done on Native Americans adolescents. Using anthropometric measurements and dietary assessments, the findings within each study have shown to obtain baseline measures to determine the prevalence of obesity within the Sherman Indian High School's Native American adolescent population. Data of each assessment appear to be of use for predicting obesity and creating effective future interventions. Compiling data using the Harvard School of Public Health Youth/Adolescent Questionnaire (HSPH YAQ), a semi-quantitative food frequency questionnaire allowed significant data to be found between normal and obese weight students. Utilizing each finding allows more effective ways of targeting and reversing the inclining rate of obesity among Native American adolescents. Results show that antioxidants being examined on such as vitamin E and lycopene are beneficial in lowering the obesity rate among Native American adolescents. Levels of fiber, thiamin and folate consumption was significantly lower among the obese population in Sherman Indian High School's Native American adolescents. Moreover, dietary mineral intake was shown to be lower among obese Native American adolescents comparing with the normal weight group. The results suggested that dietary consumption of these nutrients might correlate and predict obesity and lead to the development of effective interventions for Native Americans. This study also found the effects of total fiber and vitamin B in diets with lifestyle intervention in prediabetic adults, showing that total fiber intake among the normal weight students is significantly higher than obese students, indicating that fiber and vitamin profile could be important determinants of the effect of dietary intervention

Obesity Prevalence and Dietary Intake of Antioxidants in Native American Adolescents

Antioxidants are well known for possessing anti-inflammatory properties, which can reduce the risk of chronic disease and obesity. However, very little research has been done to examine antioxidant intake among adolescent minority populations such as Native American adolescents. Our study examined the significance of antioxidant intake among Native American adolescents at an urban residential high school in Southern California. Our study population consisted of 183 male and female Native American adolescents, 14-18 years of age, representing 43 tribes from across the United States. Students' primary source of meals was provided by the school food service. Based on the BMI calculations, the rate of obesity within our population was 38% for males and 40% for females, more than two-fold the national rate indicated by NHANESIII data. We used the Harvard School of Public Health Youth/Adolescent Questionnaire (HSPH YAQ), a semi-quantitative food frequency questionnaire, to examine antioxidant nutrient intake and evaluate the differences in the intake between normal and obese weight students. Statistical analysis of the results showed that intakes of vitamins C, E, and lycopene were the antioxidant nutrients found to be significantly different between normal and obese weight students and intakes of these nutrients were found to be higher among normal weight students (p-values = 0.02451, 0.00847, and 0.04928, respectively). These results suggest that dietary intake of antioxidants could be increased among Native American adolescents. Further research is needed to confirm our findings and identify effective ways for school food service to incorporate antioxidant rich foods into school menus

Experimental observation of magnetic bobbers for a new concept of magnetic solid-state memory

The use of chiral skyrmions, which are nanoscale vortex-like spin textures, as movable data bit carriers forms the basis of a recently proposed concept for magnetic solid-state memory. In this concept, skyrmions are considered to be unique localized spin textures, which are used to encode data through the quantization of different distances between identical skyrmions on a guiding nanostripe. However, the conservation of distances between highly mobile and interacting skyrmions is difficult to implement in practice. Here, we report the direct observation of another type of theoretically-predicted localized magnetic state, which is referred to as a chiral bobber (ChB), using quantitative off-axis electron holography. We show that ChBs can coexist together with skyrmions. Our results suggest a novel approach for data encoding, whereby a stream of binary data representing a sequence of ones and zeros can be encoded via a sequence of skyrmions and bobbers. The need to maintain defined distances between data bit carriers is then not required. The proposed concept of data encoding promises to expedite the realization of a new generation of magnetic solid-state memory

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent