Search

Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score.

We examined the association of joint trajectories of ethnic identity and criminal offending to psychosocial maturity, gang membership, and Mexican American affiliation among 300 Mexican American male juvenile offenders from ages 14 to 22. There were two low-offending groups: one was the highest in ethnic identity and changing slightly with age and the other was the lowest in ethnic identity and stable with age. A third group displayed moderately declining offending and moderately stable ethnic identity. A fourth group displayed high-offending individuals with moderate, but increasing, levels of ethnic identity, who were initially lower in psychosocial maturity and more likely to be gang members. The findings highlight the need to contextualize theories of ethnic identity development.

To survey protein expression patterns in the reduced culm number (RCN) rice, a comparative shotgun proteomic analysis was conducted. For large-scale protein identification, multidimensional protein identification technology (MudPIT) coupled with pre-fractionation of plant shoot proteins led to the identification of 3004 non-redundant rice proteins. By statistically comparing relative amounts of 1353 reproducibly identified proteins between the RCN rice and the wild-type rice, 44 differentially expressed proteins were detected, where 42 proteins were increased and 2 proteins were decreased in the RCN rice. These proteins appear to have roles in glycolysis, trichloroacetic acid cycle, secondary metabolism, nutrient recycling, and nucleotide metabolism and repair. Consequently, we hypothesized that the RCN rice might fail to maintain sugar nutrient homeostasis. This was confirmed with the observation that the sucrose concentration was increased significantly in the RCN rice compared with the wild-type rice. Also, the RCN rice showed a hypersensitive response to exogenous sucrose treatment.

Mungbean (Vigna radiata (L.) Wilczek) is a unique species in its ability to fix atmospheric nitrogen, with early maturity, and relatively good drought resistance. We used 454 sequencing technology for transcriptome sequencing. A total of 150 159 and 142 993 reads produced 5 254 and 6 374 large contigs (≥ 500 bp) with an average length of 833 and 853 for Sunhwa and Jangan, respectively. Functional annotation to known sequences yielded 41.34% and 41.74% unigenes for Jangan and Sunhwa. A higher number of simple sequence repeat (SSR) motifs was identified in Jangan (1 630) compared with that of Sunhwa (1 334). A similar SSR distribution pattern was observed in both varieties. A total of 8 249 single nucleotide polymorphisms (SNPs) and indels with 2 098 high-confidence candidates were identified in the two mungbean varieties. The average distance between individual SNPs was approximately 860 bp. Our report demonstrates the utility of transcriptomic data for implementing a functional annotation and development of genetic markers. We also provide large resource sequence data for mungbean improvement programs.