Dataset Information

Geographical Differences in the Population-Based Cross-Sectional Growth Curve and Age at Peak Height Velocity with respect to the Prevalence Rate of Overweight in Japanese Children.

ABSTRACT: The School Health Examination Survey is a nationwide examination carried out annually in Japan, and the results are entered into a prefectural-level physical measurement database. We used this database to determine the geographical differences in a population-based cross-sectional growth curve and investigated the association between age at peak height velocity (PHV) and the prevalence rate of overweight in children among Japanese prefectures. Mean prefectural-level age at PHV was estimated by the cubic spline-fitting procedure using cross-sectional whole-year prefectural mean height data (5-17 years, 2006-2013), and 8-year (2006-2013) means of the standardized prevalence rates of overweight children and other anatomical data (8-year standardized weight and height) were recalculated. Mean prefectural age at PHV was more strongly correlated with the mean prefectural prevalence rate of overweight (age 5-8 years) than with other weights or heights in both sexes. On the basis of these findings and their confirmation by multiple regression analysis, the prevalence rate of overweight was selected as a primary factor to explain the geographical difference in age at PHV. These findings suggest that childhood overweight is a dominant factor responsible for the observed geographical differences in onset of puberty in Japan.

SUBMITTER: Yokoya M

PROVIDER: S-EPMC4260373 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Geographical Differences in the Population-Based Cross-Sectional Growth Curve and Age at Peak Height Velocity with respect to the Prevalence Rate of Overweight in Japanese Children.

Yokoya Masana M Higuchi Yukito Y

International journal of pediatrics 20141124

The School Health Examination Survey is a nationwide examination carried out annually in Japan, and the results are entered into a prefectural-level physical measurement database. We used this database to determine the geographical differences in a population-based cross-sectional growth curve and investigated the association between age at peak height velocity (PHV) and the prevalence rate of overweight in children among Japanese prefectures. Mean prefectural-level age at PHV was estimated by t ...[more]

PMID: 25506368

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Project description:BackgroundThe identification of protein families is of outstanding practical importance for in silico protein annotation and is at the basis of several bioinformatic resources. Pfam is possibly the most well known protein family database, built in many years of work by domain experts with extensive use of manual curation. This approach is generally very accurate, but it is quite time consuming and it may suffer from a bias generated from the hand-curation itself, which is often guided by the available experimental evidence.ResultsWe introduce a procedure that aims to identify automatically putative protein families. The procedure is based on Density Peak Clustering and uses as input only local pairwise alignments between protein sequences. In the experiment we present here, we ran the algorithm on about 4000 full-length proteins with at least one domain classified by Pfam as belonging to the Pseudouridine synthase and Archaeosine transglycosylase (PUA) clan. We obtained 71 automatically-generated sequence clusters with at least 100 members. While our clusters were largely consistent with the Pfam classification, showing good overlap with either single or multi-domain Pfam family architectures, we also observed some inconsistencies. The latter were inspected using structural and sequence based evidence, which suggested that the automatic classification captured evolutionary signals reflecting non-trivial features of protein family architectures. Based on this analysis we identified a putative novel pre-PUA domain as well as alternative boundaries for a few PUA or PUA-associated families. As a first indication that our approach was unlikely to be clan-specific, we performed the same analysis on the P53 clan, obtaining comparable results.ConclusionsThe clustering procedure described in this work takes advantage of the information contained in a large set of pairwise alignments and successfully identifies a set of putative families and family architectures in an unsupervised manner. Comparison with the Pfam classification highlights significant overlap and points to interesting differences, suggesting that our new algorithm could have potential in applications related to automatic protein classification. Testing this hypothesis, however, will require further experiments on large and diverse sequence datasets.

Dataset Information

Geographical Differences in the Population-Based Cross-Sectional Growth Curve and Age at Peak Height Velocity with respect to the Prevalence Rate of Overweight in Japanese Children.

Publications

Geographical Differences in the Population-Based Cross-Sectional Growth Curve and Age at Peak Height Velocity with respect to the Prevalence Rate of Overweight in Japanese Children.

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