923 resultados para Populations


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Aims: Changing behaviour to reduce stroke risk is a difficult prospect made particularly complex because of psychological factors. This study examined predictors of intentions and behaviours to reduce stroke risk in a sample of at-risk individuals, seeking to find how knowledge and health beliefs influenced both intention and actual behaviour to reduce stroke risk. Methods: A repeated measures design was used to assess behavioural intentions at time 1 (T1) and subsequent behaviour (T2). One hundred and twenty six respondents completed an online survey at T1, and behavioural follow-up data were collected from approximately 70 participants 1 month later. Predictors were stroke knowledge, demographic variables, and beliefs about stroke that were derived from an expanded health belief model. Dependent measures were: exercise and weight loss, and intention to engage in these behaviours to reduce stroke risk. Findings: Multiple hierarchical regression analyses showed that, for exercise and weight loss respectively, different health beliefs predicted intention to control stroke risk. The most important exercise-related health beliefs were benefits, susceptibility, and self-efficacy; for weight loss, the most important beliefs were barriers, and to a lesser degree, susceptibility and subjective norm. Conclusions: Health beliefs may play an important role in stroke prevention, particularly beliefs about susceptibility because these emerged for both behaviours. Stroke education and prevention programmes that selectively target the health beliefs relevant to specific behaviours may prove most efficacious.

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Decline in the frequency of potent mesenchymal stem cells (MSCs) has been implicated in ageing and degenerative diseases. Increasing the circulating stem cell population can lead to renewed recruitment of these potent cells at sites of damage. Therefore, identifying the ideal cells for ex vivo expansion will form a major pursuit of clinical applications. This study is a follow-up of previous work that demonstrated the occurrence of fast-growing multipotential cells from the bone marrow samples. To investigate the molecular processes involved in the existence of such varying populations, gene expression studies were performed between fast- and slow-growing clonal populations to identify potential genetic markers associated with stemness using the quantitative real-time polymerase chain reaction comprising a series of 84 genes related to stem cell pathways. A group of 10 genes were commonly overrepresented in the fast-growing stem cell clones. These included genes that encode proteins involved in the maintenance of embryonic and neural stem cell renewal (sex-determining region Y-box 2, notch homolog 1, and delta-like 3), proteins associated with chondrogenesis (aggrecan and collagen 2 A1), growth factors (bone morphogenetic protein 2 and insulin-like growth factor 1), an endodermal organogenesis protein (forkhead box a2), and proteins associated with cell-fate specification (fibroblast growth factor 2 and cell division cycle 2). Expression of diverse differentiation genes in MSC clones suggests that these commonly expressed genes may confer the maintenance of multipotentiality and self-renewal of MSCs.

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It is easy to assume that because Australia and the United States are both predominantly English speaking countries that are relatively young and share many similarities in terms of their historical beginnings, they elicit the same results when investigating psychological constructs. In recent years this has been questioned across a number of domains (e.g., personality and stereotyping) and research has demonstrated that although many constructs are universal, there are differences between these nations; some subtle and others quite stark (McCrae et al., 2005; Terraciano et al., 2005). In this chapter we discuss research that has investigated Posttraumatic Growth (PTG) in various populations in Australia and highlight the similarities and differences that have been found between Australian samples and those published in other countries, especially the US. Data are drawn from quantitative and qualitative investigations conducted with groups who have experienced diverse traumatic events as either direct survivors (e.g., rape, armed hold-up, bereavement) or vicarious survivors (e.g., paramedics). A description of the Australian context sets the scene for the ensuing discussion about PTG in Australian populations.

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Patterns of connectivity among local populations influence the dynamics of regional systems, but most ecological models have concentrated on explaining the effect of connectivity on local population structure using dynamic processes covering short spatial and temporal scales. In this study, a model was developed in an extended spatial system to examine the hypothesis that long term connectivity levels among local populations are influenced by the spatial distribution of resources and other habitat factors. The habitat heterogeneity model was applied to local wild rabbit populations in the semi-arid Mitchell region of southern central Queensland (the Eastern system). Species' specific population parameters which were appropriate for the rabbit in this region were used. The model predicted a wide range of long term connectivity levels among sites, ranging from the extreme isolation of some sites to relatively high interaction probabilities for others. The validity of model assumptions was assessed by regressing model output against independent population genetic data, and explained over 80% of the variation in the highly structured genetic data set. Furthermore, the model was robust, explaining a significant proportion of the variation in the genetic data over a wide range of parameters. The performance of the habitat heterogeneity model was further assessed by simulating the widely reported recent range expansion of the wild rabbit into the Mitchell region from the adjacent, panmictic Western rabbit population system. The model explained well the independently determined genetic characteristics of the Eastern system at different hierarchic levels, from site specific differences (for example, fixation of a single allele in the population at one site), to differences between population systems (absence of an allele in the Eastern system which is present in all Western system sites). The model therefore explained the past and long term processes which have led to the formation and maintenance of the highly structured Eastern rabbit population system. Most animals exhibit sex biased dispersal which may influence long term connectivity levels among local populations, and thus the dynamics of regional systems. When appropriate sex specific dispersal characteristics were used, the habitat heterogeneity model predicted substantially different interaction patterns between female-only and combined male and female dispersal scenarios. In the latter case, model output was validated using data from a bi-parentally inherited genetic marker. Again, the model explained over 80% of the variation in the genetic data. The fact that such a large proportion of variability is explained in two genetic data sets provides very good evidence that habitat heterogeneity influences long term connectivity levels among local rabbit populations in the Mitchell region for both males and females. The habitat heterogeneity model thus provides a powerful approach for understanding the large scale processes that shape regional population systems in general. Therefore the model has the potential to be useful as a tool to aid in the management of those systems, whether it be for pest management or conservation purposes.

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Experimental observations of cell migration often describe the presence of mesoscale patterns within motile cell populations. These patterns can take the form of cells moving as aggregates or in chain-like formation. Here we present a discrete model capable of producing mesoscale patterns. These patterns are formed by biasing movements to favor a particular configuration of agent–agent attachments using a binding function f(K), where K is the scaled local coordination number. This discrete model is related to a nonlinear diffusion equation, where we relate the nonlinear diffusivity D(C) to the binding function f. The nonlinear diffusion equation supports a range of solutions which can be either smooth or discontinuous. Aggregation patterns can be produced with the discrete model, and we show that there is a transition between the presence and absence of aggregation depending on the sign of D(C). A combination of simulation and analysis shows that both the existence of mesoscale patterns and the validity of the continuum model depend on the form of f. Our results suggest that there may be no formal continuum description of a motile system with strong mesoscale patterns.

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The genetic structure of rice tungro bacilliform virus (RTBV) populations within and between growing sites was analyzed in a collection of natural field isolates from different rice varieties grown in eight tungro-endemic sites of the Philippines. Total DNA extracts from 345 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV, a procedure shown in preliminary experiments capable of revealing high levels of polymorphism in RTBV field isolates. In the total population, 17 distinct EcoRV-based genome profiles (genotypes) were identified and used as indicators for virus diversity. Distinct sets of genotypes occurred in Isabela and North Cotabato provinces suggesting a geographic isolation of virus populations. However, among the sites in each province, there were few significant differences in the genotype compositions of virus populations. The number of genotypes detected at a site varied from two to nine with a few genotypes dominating. In general the isolates at a site persisted from season to season indicating a genetic stability for the local virus population. Over the sampling time, IRRI rice varieties, which have green leafhopper resistance genes, supported similar virus populations to those supported by other varieties, indicating that the variety of the host exerted no apparent selection pressures. Insect transmission experiments on selected RTBV field isolates showed that dramatic shifts in genotype and phenotype distributions can occur in response to host /environmental shifts.

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We have recently demonstrated the geographic isolation of rice tungro bacilliform virus (RTBV) populations in the tungro-endemic provinces of Isabela and North Cotabato, Philippines. In this study, we examined the genetic structure of the virus populations at the tungro-outbreak sites of Lanao del Norte, a province adjacent to North Cotabato. We also analyzed the virus populations at the tungro-endemic sites of Subang, Indonesia, and Dien Khanh, Vietnam. Total DNA extracts from 274 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV. In the total population, 22 EcoRV-restricted genome profiles (genotypes) were identified. Although overlapping genotypes could be observed, the outbreak sites of Lanao del Norte had a genotype combination distinct from that of Subang or Dien Khanh but a genotype combination similar to that identified earlier from North Cotabato, the adjacent endemic province. Sequence analysis of the intergenic region and part of the ORF1 RTBV genome from randomly selected genotypes confirms the geographic clustering of RTBV genotypes and, combined with restriction analysis, the results suggest a fragmented spatial distribution of RTBV local populations in the three countries. Because RTBV depends on rice tungro spherical virus (RTSV) for transmission, the population dynamics of both tungro viruses were then examined at the endemic and outbreak sites within the Philippines. The RTBV genotypes and the coat protein RTSV genotypes were used as indicators for virus diversity. A shift in population structure of both viruses was observed at the outbreak sites with a reduced RTBV but increased RTSV gene diversity

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The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as ≥ 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50–94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000–9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.