Insulin resistance in adolescents with Down syndrome: a cross-sectional study

BACKGROUND: The prevalence of diabetes mellitus is higher in individuals with Down syndrome (DS) than in the general population; it may be due to the high prevalence of obesity presented by many of them. The aim of this study was to evaluate the insulin resistance (IR) using the HOMA (Homeostasis Model Assessment) method, in DS adolescents, describing it according to the sex, body mass index (BMI) and pubertal development. METHODS: 15 adolescents with DS (8 males and 7 females) were studied, aged 10 to 18 years, without history of disease or use of medication that could change the suggested laboratory evaluation. On physical examination, the pubertal signs, acanthosis nigricans (AN), weight and height were evaluated. Fasting plasma glucose and insulin were analysed by the colorimetric method and RIA-kit LINCO, respectively. IR was calculated using the HOMA method. The patients were grouped into obese, overweight and normal, according to their BMI percentiles. The EPIINFO 2004 software was used to calculate the BMI, its percentile and Z score. RESULTS: Five patients were adults (Tanner V or presence of menarche), 9 pubertal (Tanner II – IV) and 1 prepubertal (Tanner I). No one had AN. Two were obese, 4 overweight and 9 normal. Considering the total number of patients, HOMA was 1.7 ± 1.0, insulin 9.3 ± 4.8 μU/ml and glucose 74.4 ± 14.8 mg/dl. The HOMA values were 2.0 ± 1.0 in females and 1.5 ± 1.0 in males. Considering the nutritional classification, the values of HOMA and insulin were: HOMA: 3.3 ± 0.6, 2.0 ± 1.1 and 1.3 ± 0.6, and insulin: 18.15 ± 1.6 μU/ml, 10.3 ± 3.5 μU/ml and 6.8 ± 2.8 μU/ml, in the obese, overweight and normal groups respectively. Considering puberty, the values of HOMA and insulin were: HOMA: 2.5 ± 1.3, 1.4 ± 0.6 and 0.8 ± 0.0, and insulin: 13.0 ± 5.8 μU/ml, 7.8 ± 2.9 μU/ml and 4.0 ± 0.0 μU/ml, in the adult, pubertal and prepubertal groups respectively. CONCLUSION: The obese and overweight, female and adult patients showed the highest values of HOMA and insulin

Comprehensive transcriptome analysis of the highly complex Pisum sativum genome using next generation sequencing

<p>Abstract</p> <p>Background</p> <p>The garden pea, <it>Pisum sativum</it>, is among the best-investigated legume plants and of significant agro-commercial relevance. <it>Pisum sativum </it>has a large and complex genome and accordingly few comprehensive genomic resources exist.</p> <p>Results</p> <p>We analyzed the pea transcriptome at the highest possible amount of accuracy by current technology. We used next generation sequencing with the Roche/454 platform and evaluated and compared a variety of approaches, including diverse tissue libraries, normalization, alternative sequencing technologies, saturation estimation and diverse assembly strategies. We generated libraries from flowers, leaves, cotyledons, epi- and hypocotyl, and etiolated and light treated etiolated seedlings, comprising a total of 450 megabases. Libraries were assembled into 324,428 unigenes in a first pass assembly.</p> <p>A second pass assembly reduced the amount to 81,449 unigenes but caused a significant number of chimeras. Analyses of the assemblies identified the assembly step as a major possibility for improvement. By recording frequencies of Arabidopsis orthologs hit by randomly drawn reads and fitting parameters of the saturation curve we concluded that sequencing was exhaustive. For leaf libraries we found normalization allows partial recovery of expression strength aside the desired effect of increased coverage. Based on theoretical and biological considerations we concluded that the sequence reads in the database tagged the vast majority of transcripts in the aerial tissues. A pathway representation analysis showed the merits of sampling multiple aerial tissues to increase the number of tagged genes. All results have been made available as a fully annotated database in fasta format.</p> <p>Conclusions</p> <p>We conclude that the approach taken resulted in a high quality - dataset which serves well as a first comprehensive reference set for the model legume pea. We suggest future deep sequencing transcriptome projects of species lacking a genomics backbone will need to concentrate mainly on resolving the issues of redundancy and paralogy during transcriptome assembly.</p

Changes in Drug Utilization during a Gap in Insurance Coverage: An Examination of the Medicare Part D Coverage Gap

Jennifer Polinski and colleagues estimated the effect of the "coverage gap" during which US Medicare beneficiaries are fully responsible for drug costs and found that the gap was associated with a doubling in discontinuing essential medications

Life history, climate and biogeography interactively affect worldwide genetic diversity of plant and animal populations.

Understanding how biological and environmental factors interactively shape the global distribution of plant and animal genetic diversity is fundamental to biodiversity conservation. Genetic diversity measured in local populations (GDP) is correspondingly assumed representative for population fitness and eco-evolutionary dynamics. For 8356 populations across the globe, we report that plants systematically display much lower GDP than animals, and that life history traits shape GDP patterns both directly (animal longevity and size), and indirectly by mediating core-periphery patterns (animal fecundity and plant dispersal). Particularly in some plant groups, peripheral populations can sustain similar GDP as core populations, emphasizing their potential conservation value. We further find surprisingly weak support for general latitudinal GDP trends. Finally, contemporary rather than past climate contributes to the spatial distribution of GDP, suggesting that contemporary environmental changes affect global patterns of GDP. Our findings generate new perspectives for the conservation of genetic resources at worldwide and taxonomic-wide scales