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This study aimed to examine the association between infant sleep quality and temperament in one-month-old infants using a large cohort study data. We used data from the Japan Environment and Children's Study, a cohort study which follows around 100,000 women from pregnancy until their children's development. The mothers were asked about their infants' sleep and temperament using a structured questionnaire. Frequent crying (adjusted odds ratio [AOR]: 1.05, 95% confidence interval [CI]: 1.00-1.10) and intense crying (AOR: 1.19, 95% CI: 1.13-1.25) were positively associated with longer sleep periods during the day than at night. Female infants with longer daytime sleep periods than that at nighttime were more likely to cry frequently (AOR: 1.11, 95% CI: 1.04-1.20). Parous women with infants who had frequent night awakening believed their infants cried more intensely (AOR: 1.17, 95% CI: 1.03-1.31). The study demonstrated a specific association between sleep quality and temperament in one-month-old infants. Based on the results of this study, further sleep intervention studies are required to improve infant temperament., Competing Interests: The authors have declared that no competing interests exist.

Objectives: No previous study has used repeated measures data to examine the associations of dog/cat ownership with wheezing and asthma prevalence among children. This prospective study used repeated measurers analysis to determine whether dog/cat ownership in childhood is an independent risk factor for wheezing and asthma, after adjustment for gestational, socio-economical, and demographical confounders confounders, in Japan., Methods: We conducted a multicenter pilot study of the Japan Environment and Children's Study (JECS) during 2009-2010. Among 440 newborn infants enrolled, 410 (52.8% males) were evaluated for dog/cat ownership in the home and history of wheezing and asthma in five follow-up questionnaire surveys (until age 6 years). Dog/cat ownership during follow-up period was categorized into four groups: 7.6% were long-term dog/cat owners, 5.9% were toddler-age owners, 5.9% were preschool-age owners, and 80.7% were never owners., Results: The prevalence of wheezing during follow-up period increased from 20.8% to 35.4% and the prevalence of asthma increased from 1.3% to 16.3%. A fitted logistic generalized estimating equation models including important confounders showed no significant associations of the interaction between dog and/or cat ownership and follow-up time with the risks of wheezing and asthma. However, the risks of wheezing and asthma were slightly lower for long-term and toddler-age dog/cat owners than for preschool-age and never owners., Conclusions: The present findings suggest that dog and cat ownership from toddler-age does not increase the risks of wheezing and asthma compared with never owners among Japanese children., Competing Interests: The authors have declared that no competing interests exist.

The authors present a method for extracting polygon data of endocranial surfaces from CT images of human crania. Based on the fact that the endocast is the largest empty space in the crania, we automate a procedure for endocast extraction by integrating several image processing techniques. Given CT images of human crania, the proposed method extracts endocranial surfaces by the following three steps. The first step is binarization in order to fill void structures, such as diploic space and cracks in the skull. We use a void detection method based on mathematical morphology. The second step is watershed-based segmentation of the endocranial part from the binary image of the CT image. Here, we introduce an automatic initial seed assignment method for the endocranial region using the distance field of the binary image. The final step is partial polygonization of the CT images using the segmentation results as mask images. The resulting polygons represent only the endocranial part, and the closed manifold surfaces are computed even though the endocast is not isolated in the cranium. Since only the isovalue threshold and the size of void structures are required, the procedure is not dependent on the experience of the user. The present paper also demonstrates that the proposed method can extract polygon data of endocasts from CT images of various crania.

A uniform extracellular stimulus triggers cell-specific patterns of Ca(2+) signals, even in genetically identical cell populations. However, the underlying mechanism that generates the cell-to-cell variability remains unknown. We monitored cytosolic inositol 1,4,5-trisphosphate (IP3) concentration changes using a fluorescent IP3 sensor in single HeLa cells showing different patterns of histamine-induced Ca(2+) oscillations in terms of the time constant of Ca(2+) spike amplitude decay and the Ca(2+) oscillation frequency. HeLa cells stimulated with histamine exhibited a considerable variation in the temporal pattern of Ca(2+) signals and we found that there were cell-specific IP3 dynamics depending on the patterns of Ca(2+) signals. RT-PCR and western blot analyses showed that phospholipase C (PLC)-β1, -β3, -β4, -γ1, -δ3 and -ε were expressed at relatively high levels in HeLa cells. Small interfering RNA-mediated silencing of PLC isozymes revealed that PLC-β1 and PLC-β4 were specifically involved in the histamine-induced IP3 increases in HeLa cells. Modulation of IP3 dynamics by knockdown or overexpression of the isozymes PLC-β1 and PLC-β4 resulted in specific changes in the characteristics of Ca(2+) oscillations, such as the time constant of the temporal changes in the Ca(2+) spike amplitude and the Ca(2+) oscillation frequency, within the range of the cell-to-cell variability found in wild-type cell populations. These findings indicate that the heterogeneity in the process of IP3 production, rather than IP3-induced Ca(2+) release, can cause cell-to-cell variability in the patterns of Ca(2+) signals and that PLC-β1 and PLC-β4 contribute to generate cell-specific Ca(2+) signals evoked by G protein-coupled receptor stimulation.

While hearing aids are recommended for people with age-related hearing loss, many with impaired hearing do not use them. In this study, we investigated how many elderly people in the study area needed hearing aids, and the factors that determined continued wearing of the devices. The study area was Kurabuchi Town, Japan, where 1,437 residents (those aged 65 years or over) were eligible for participation in the study; 1,414 participated, of whom, 103 (7.3%) were already using hearing aids at the start of the study. After the primary screening, hearing aids were lent to 68 participants (4.8%) who did not already have one, 38 of whom (60.3% of the borrowers, representing 2.7% of the total aged population) went on to wear the hearing aid continuously. The Hearing Handicap Inventory for the Elderly (HHIE) score was significantly elevated among these 38 participants. This study indicated that hearing aids are of potential benefit to many local residents. Multivariate logistic regression revealed that HHIE scores were associated with the extent of HA usage. The adjusted odds ratio for a 1-unit increase in HHIE score was 1.08 (95% confidence interval: 1.02-1.14). Programs like this, in which people with impaired hearing are identified at the local level and given appropriate assistance, are useful models for future use in societies with aging populations.

The authors propose a CT image segmentation method using structural analysis that is useful for objects with structural dynamic characteristics. Motivation of our research is from the area of genetic activity. In order to reveal the roles of genes, it is necessary to create mutant mice and measure differences among them by scanning their skeletons with an X-ray CT scanner. The CT image needs to be manually segmented into pieces of the bones. It is a very time consuming to manually segment many mutant mouse models in order to reveal the roles of genes. It is desirable to make this segmentation procedure automatic. Although numerous papers in the past have proposed segmentation techniques, no general segmentation method for skeletons of living creatures has been established. Against this background, the authors propose a segmentation method based on the concept of destruction analogy. To realize this concept, structural analysis is performed using the finite element method (FEM), as structurally weak areas can be expected to break under conditions of stress. The contribution of the method is its novelty, as no studies have so far used structural analysis for image segmentation. The method's implementation involves three steps. First, finite elements are created directly from the pixels of a CT image, and then candidates are also selected in areas where segmentation is thought to be appropriate. The second step involves destruction analogy to find a single candidate with high strain chosen as the segmentation target. The boundary conditions for FEM are also set automatically. Then, destruction analogy is implemented by replacing pixels with high strain as background ones, and this process is iterated until object is decomposed into two parts. Here, CT image segmentation is demonstrated using various types of CT imagery.