Mimicking breast cancer-induced bone metastasis in vivo: Current transplantation models and advanced humanized strategies

Bone metastasis is a complication that occurs in 80 % of women with advanced breast cancer. Despite the prevalence of bone metastatic disease, the avenues for its clinical management are still restricted to palliative treatment options. In fact, the underlying mechanisms of breast cancer osteotropism have not yet been fully elucidated due to a lack of suitable in vivo models that are able to recapitulate the human disease. In this work, we review the current transplantation-based models to investigate breast cancer-induced bone metastasis and delineate the strengths and limitations of the use of different grafting techniques, tissue sources, and hosts. We further show that humanized xenograft models incorporating human cells or tissue grafts at the primary tumor site or the metastatic site mimic more closely the human disease. Tissue-engineered constructs are emerging as a reproducible alternative to recapitulate functional humanized tissues in these murine models. The development of advanced humanized animal models may provide better platforms to investigate the mutual interactions between human cancer cells and their microenvironment and ultimately improve the translation of preclinical drug trials to the clinic.

Mixture models of nucleotide sequence evolution that account for heterogeneity in the substitution process across sites and across lineages

Molecular phylogenetic studies of homologous sequences of nucleotides often assume that the underlying evolutionary process was globally stationary, reversible, and homogeneous (SRH), and that a model of evolution with one or more site-specific and time-reversible rate matrices (e.g., the GTR rate matrix) is enough to accurately model the evolution of data over the whole tree. However, an increasing body of data suggests that evolution under these conditions is an exception, rather than the norm. To address this issue, several non-SRH models of molecular evolution have been proposed, but they either ignore heterogeneity in the substitution process across sites (HAS) or assume it can be modeled accurately using the distribution. As an alternative to these models of evolution, we introduce a family of mixture models that approximate HAS without the assumption of an underlying predefined statistical distribution. This family of mixture models is combined with non-SRH models of evolution that account for heterogeneity in the substitution process across lineages (HAL). We also present two algorithms for searching model space and identifying an optimal model of evolution that is less likely to over- or underparameterize the data. The performance of the two new algorithms was evaluated using alignments of nucleotides with 10 000 sites simulated under complex non-SRH conditions on a 25-tipped tree. The algorithms were found to be very successful, identifying the correct HAL model with a 75% success rate (the average success rate for assigning rate matrices to the tree's 48 edges was 99.25%) and, for the correct HAL model, identifying the correct HAS model with a 98% success rate. Finally, parameter estimates obtained under the correct HAL-HAS model were found to be accurate and precise. The merits of our new algorithms were illustrated with an analysis of 42 337 second codon sites extracted from a concatenation of 106 alignments of orthologous genes encoded by the nuclear genomes of Saccharomyces cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, S. castellii, S. kluyveri, S. bayanus, and Candida albicans. Our results show that second codon sites in the ancestral genome of these species contained 49.1% invariable sites, 39.6% variable sites belonging to one rate category (V1), and 11.3% variable sites belonging to a second rate category (V2). The ancestral nucleotide content was found to differ markedly across these three sets of sites, and the evolutionary processes operating at the variable sites were found to be non-SRH and best modeled by a combination of eight edge-specific rate matrices (four for V1 and four for V2). The number of substitutions per site at the variable sites also differed markedly, with sites belonging to V1 evolving slower than those belonging to V2 along the lineages separating the seven species of Saccharomyces. Finally, sites belonging to V1 appeared to have ceased evolving along the lineages separating S. cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, and S. bayanus, implying that they might have become so selectively constrained that they could be considered invariable sites in these species.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

Factors associated with health risk behavior among school children in urban Vietnam

Background Health risk behavior among young people is a public health problem in Vietnam. In addition, road traffic injuries are the leading cause of death for those aged 15–29 years. The consequences can be devastating for adolescents and their families, and can create a significant economic burden on society. Objective: The aim of this study was to identify protective and risk factors that may influence three health risk behaviors among school children: suicidal thinking (ST), drinking alcohol (DA), and underage motorbike driving (MD). Methods A cross-sectional survey of 972 adolescents (aged 12–15 years) was conducted in two secondary schools in Hanoi, Vietnam. The schools were purposely selected, one each from the inner city and a suburban area, from which classes (grade 6 to 8) were randomly selected. All students attending classes on survey days took part in the survey. The anonymous, self-completed questionnaire included measures of risk behavior, school connectedness, parental bonding, and other factors. Multivariable regression models were used to examine associations between the independent variables and the three health risk behaviors controlling for confounding factors. Results Young people in the inner city school reported a higher prevalence of all three risk behaviors than those in the suburban area (ST: 16.1% [95% confidence interval, or CI, 12.9–19.3] versus 4.6% [95% CI 2.7–6.5], p<0.001; DA: 20.3% [95% CI 16.8–23.8] versus 8.3% [95% CI 5.8–10.8], p<0.001, and MD: 10.1% [95% CI 7.4–12.8] versus 5.7% [95% CI 3.6–7.8], p<0.01). School connectedness and mother and father care appeared to be significant protective factors. For males, bullying in school was associated with suicidal thoughts, whereas for both males and females, school connectedness may be protective against suicidal ideation. Conclusion This study supports findings from other nations regarding suicidal thoughts and alcohol use, and appears to be one of the first to examine risk and protective factors forMD. Health promotion within schools should be introduced to improve students’ feelings of connectedness in combination with communication and education campaigns focusing on parental care and engaging teachers for the promotion of safer, supportive school environments.

Convergence of regenerative medicine and synthetic biology to develop standardized and validated models of human diseases with clinical relevance

In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

Predictors of mental health in midlife and older Australian women: A multilevel investigation

The purpose of this article is to examine the factors associated with women's mental health. A random sample of 340 Australian women aged 40–55 completed surveys on menopausal and lifestyle factors and mental health at three time points. We used hierarchical models to show that decrements in mental health were associated with a corresponding increase in some midlife symptoms (p < .01), time (p < .01), and poor physical health (p < .01), but the effect was not permanent. In older women, mental health was associated with physical functioning, climacteric symptoms, and time, while individual variations in mental health score were largely explained by lifestyle factors.

Factors influencing sustainability of health service innovation: Emergency nurse practitioner services

Introduction: Emergency department nurse practitioner services are one of the most frequently implemented service delivery models in Australian hospitals. This research examined factors influencing sustainability of this innovative service delivery model and offers some recommendations for future service integration. Background Many health service innovations have been implemented in an attempt to meet the growing demand for efficient, cost effective health care however, sustainability of many of these innovations has not been evaluated and is poorly understood. Aim The aim of the research was to identify factors that influence sustainability of emergency department nurse practitioner services and to operationalise a theoretical framework for evaluating innovation sustainability. Methodology The research used case study methodology. The case was emergency nurse practitioner services, and units of analysis were emergency department staff, emergency nurse practitioners and documents relating to nurse practitioner services. The data collection methods included, survey, one-on-one interviews, document analysis and telephone survey. Results This research shows that emergency nurse practitioner services partially comply with the factors of sustainability as described in the Sustainability of Innovation theoretical framework: Political, Organisational, Workforce, Financial and Innovation specific factors. Where services do not entirely meet the factors the existing benefits of the service may outweigh the barriers and other means of working around shortfalls are also implemented by staff to ensure patient safety. Conclusion The rapidly expanding emergency nurse practitioner service has been examined using case study methodology to find that certain factors may be threatening the sustainability of this health service innovation. Potentially an innovation may be sustained when only some factors are met in the short term, however, long term sustainability may be challenged if factors are not addressed and supported.

Comparison between computational models of abdominal aortic aneurysm

Objective: To compare the differences in the hemodynamic parameters of abdominal aortic aneurysm (AAA) between fluid-structure interaction model (FSIM) and fluid-only model (FM), so as to discuss their application in the research of AAA. Methods: An idealized AAA model was created based on patient-specific AAA data. In FM, the flow, pressure and wall shear stress (WSS) were computed using finite volume method. In FSIM, an Arbitrary Lagrangian-Eulerian algorithm was used to solve the flow in a continuously deforming geometry. The hemodynamic parameters of both models were obtained for discussion. Results: Under the same inlet velocity, there were only two symmetrical vortexes in the AAA dilation area for FSIM. In contrast, four recirculation areas existed in FM; two were main vortexes and the other two were secondary flow, which were located between the main recirculation area and the arterial wall. Six local pressure concentrations occurred in the distal end of AAA and the recirculation area for FM. However, there were only two local pressure concentrations in FSIM. The vortex center of the recirculation area in FSIM was much more close to the distal end of AAA and the area was much larger because of AAA expansion. Four extreme values of WSS existed at the proximal of AAA, the point of boundary layer separation, the point of flow reattachment and the distal end of AAA, respectively, in both FM and FSIM. The maximum wall stress and the largest wall deformation were both located at the proximal and distal end of AAA. Conclusions: The number and center of the recirculation area for both models are different, while the change of vortex is closely associated with the AAA growth. The largest WSS of FSIM is 36% smaller than that of FM. Both the maximum wall stress and largest wall displacement shall increase with the outlet pressure increasing. FSIM needs to be considered for studying the relationship between AAA growth and shear stress.

Solid volume fraction estimation of bone:marrow replica models using ultrasound transit time spectroscopy

The acceptance of broadband ultrasound attenuation (BUA) for the assessment of osteoporosis suffers from a limited understanding of both ultrasound wave propagation through cancellous bone and its exact dependence upon the material and structural properties. It has recently been proposed that ultrasound wave propagation in cancellous bone may be described by a concept of parallel sonic rays; the transit time of each ray defined by the proportion of bone and marrow propagated. A Transit Time Spectrum (TTS) describes the proportion of sonic rays having a particular transit time, effectively describing the lateral inhomogeneity of transit times over the surface aperture of the receive ultrasound transducer. The aim of this study was to test the hypothesis that the solid volume fraction (SVF) of simplified bone:marrow replica models may be reliably estimated from the corresponding ultrasound transit time spectrum. Transit time spectra were derived via digital deconvolution of the experimentally measured input and output ultrasonic signals, and compared to predicted TTS based on the parallel sonic ray concept, demonstrating agreement in both position and amplitude of spectral peaks. Solid volume fraction was calculated from the TTS; agreement between true (geometric calculation) with predicted (computer simulation) and experimentally-derived values were R2=99.9% and R2=97.3% respectively. It is therefore envisaged that ultrasound transit time spectroscopy (UTTS) offers the potential to reliably estimate bone mineral density and hence the established T-score parameter for clinical osteoporosis assessment.

Estimating equations for parameters in stochastic growth models from tag-recapture data

James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.

Disease mapping using Bayesian hierarchical models

description and analysis of geographically indexed health data with respect to demographic, environmental, behavioural, socioeconomic, genetic, and infectious risk factors (Elliott andWartenberg 2004). Disease maps can be useful for estimating relative risk; ecological analyses, incorporating area and/or individual-level covariates; or cluster analyses (Lawson 2009). As aggregated data are often more readily available, one common method of mapping disease is to aggregate the counts of disease at some geographical areal level, and present them as choropleth maps (Devesa et al. 1999; Population Health Division 2006). Therefore, this chapter will focus exclusively on methods appropriate for areal data...

Long-term ambient air pollution exposure and self-reported morbidity in the Australian Longitudinal Study on Women's Health: A cross-sectional study

- Objective We sought to assess the effect of long-term exposure to ambient air pollution on the prevalence of self-reported health outcomes in Australian women. - Design Cross-sectional study - Setting and participants The geocoded residential addresses of 26 991 women across 3 age cohorts in the Australian Longitudinal Study on Women's Health between 2006 and 2011 were linked to nitrogen dioxide (NO2) exposure estimates from a land-use regression model. Annual average NO2 concentrations and residential proximity to roads were used as proxies of exposure to ambient air pollution. - Outcome measures Self-reported disease presence for diabetes mellitus, heart disease, hypertension, stroke, asthma, chronic obstructive pulmonary disease and self-reported symptoms of allergies, breathing difficulties, chest pain and palpitations. - Methods Disease prevalence was modelled by population-averaged Poisson regression models estimated by generalised estimating equations. Associations between symptoms and ambient air pollution were modelled by multilevel mixed logistic regression. Spatial clustering was accounted for at the postcode level. - Results No associations were observed between any of the outcome and exposure variables considered at the 1% significance level after adjusting for known risk factors and confounders. - Conclusions Long-term exposure to ambient air pollution was not associated with self-reported disease prevalence in Australian women. The observed results may have been due to exposure and outcome misclassification, lack of power to detect weak associations or an actual absence of associations with self-reported outcomes at the relatively low annual average air pollution exposure levels across Australia.

Workplace acceptance and experiences of LGBTIQ health professionals: A systematic literature review

Background The purpose of this study was to explore the workplace acceptance and experiences of lesbian, gay, bisexual, transgender, intersex and queer (LGBTIQ) paramedics. Methods A systematic search of academic databases and reference lists from selected papers were the sources of the data. Inclusion criteria were research papers published in English, which focused on workplace acceptance and experiences of LGBTIQ health personnel. Results The initial focus of this systematic review was the workplace acceptance and experiences of LGBTIQ paramedics. However due to no published research specific to the paramedic profession the scope of the review was broadened to include of all LGBTIQ health personnel. Thirty-three papers were included in this review. Evidence indicated that LGBTIQ health professionals experienced discrimination from their patients, heterosexual colleagues and ‘closeted’ LGBTIQ peers. Positive contribution of LGBTIQ health professionals include improved patient care and role models for LGBTIQ peers. Inclusive policy is required for LGBTIQ health professional workforce retention. Conclusions The paramedic workforce is known to be a high risk occupational group for post-traumatic stress disorder and depression. Theoretically, LGBTIQ paramedics working in a heteronormative culture experience increased level of stress. While LGBTIQ health professionals receive legislative protection against discrimination, discrimination still exists in practice through lack of visibility. Effective and efficient integration of LGBTIQ health professionals could improve workplace satisfaction, workforce retention, and equity of access by marginalised groups. An inclusive workplace policy of LGBTIQ embraces and celebrates the value of diversity.

Reconciling transport models across scales: The role of volume exclusion

Diffusive transport is a universal phenomenon, throughout both biological and physical sciences, and models of diffusion are routinely used to interrogate diffusion-driven processes. However, most models neglect to take into account the role of volume exclusion, which can significantly alter diffusive transport, particularly within biological systems where the diffusing particles might occupy a significant fraction of the available space. In this work we use a random walk approach to provide a means to reconcile models that incorporate crowding effects on different spatial scales. Our work demonstrates that coarse-grained models incorporating simplified descriptions of excluded volume can be used in many circumstances, but that care must be taken in pushing the coarse-graining process too far.

Models of care in geriatric oncology nursing

Objectives To review models of care for older adults with cancer, with a focus on the role of the oncology nurse in geriatric oncology care. International exemplars of geriatric oncology nursing care are discussed. Data source Published peer reviewed literature, web-based resources, professional society materials, and the authors' experience. Conclusion Nursing care for older patients with cancer is complex and requires integrating knowledge from multiple disciplines that blends the sciences of geriatrics, oncology, and nursing. and which recognizes the dimensions of quality of life. Implications for Nursing Practice: Oncology nurses can benefit from learning key skills of comprehensive geriatric screening and assessment to improve the care they provide for older adults with cancer.