Loading of the rat ulna is an ideal model to examine stress fracture healing. The aim of this study was to undertake a detailed examination of the histology, histomorphometry and gene expression of the healing and remodelling process initiated by fatigue loading of the rat ulna. Ulnae were harvested 1, 2, 4, 6, 8, and 10 weeks following creation of a stress fracture. Stress fracture healing involved direct remodelling that progressed along the fracture line as well as woven bone proliferation at the site of the fracture. Histomorphometry demonstrated rapid progression of basic multicellular units from 1 to 4 weeks with significant slowing down of healing by 10 weeks after loading. Quantitative PCR was performed at 4 hours, 24 hours, 4 days, 7 days, and 14 days after loading. Gene expression was compared to an unloaded control group. At 4 hours after fracture, there was a marked 220-fold increase (P<0.0001) in expression of IL-6. There were also prominent peak increases in mRNA expression for OPG, COX-2, and VEGF (all P<0.0001). At 24 hours, there was a peak increase in mRNA expression for IL-11 (73-fold increase, P<0.0001). At 4 days, there was a significant increase in mRNA expression for Bcl-2, COX-1, IGF-1, OPN, and SDF-1. At 7 days, there was significantly increased mRNA expression of RANKL and OPN. Prominent, upregulation of COX-2, VEGF, OPG, SDF-1, BMP-2, and SOST prior to peak expression of RANKL indicates the importance of these factors in mediating directed remodelling of the fracture line. Dramatic, early upregulation of IL-6 and IL-11 demonstrate their central role in initiating signalling events for remodelling and stress fracture healing.

BackgroundReal-time quantitative RT-PCR (qPCR) is a powerful technique capable of accurately quantitating mRNA expression levels over a large dynamic range. This makes qPCR the most widely used method for studying quantitative gene expression. An important aspect of qPCR is selecting appropriate controls or normalization factors to account for any differences in starting cDNA quantities between samples during expression studies. Here, we report on the selection of a concise set of housekeeper genes for the accurate normalization of quantitative gene expression data in differentiating osteoblasts, osteoclasts and macrophages. We implemented the use of geNorm, an algorithm that determines the suitability of genes to function as housekeepers by assessing expression stabilities. We evaluated the expression stabilities of 18S, ACTB, B2M, GAPDH, HMBS and HPRT1 genes.FindingsOur analyses revealed that 18S and GAPDH were regulated during osteoblast differentiation and are not suitable for use as reference genes. The most stably expressed genes in osteoblasts were ACTB, HMBS and HPRT1 and their geometric average constitutes a suitable normalization factor upon which gene expression data can be normalized. In macrophages, 18S and GAPDH were the most variable genes while HMBS and B2M were the most stably expressed genes. The geometric average of HMBS and B2M expression levels forms a suitable normalization factor to account for potential differences in starting cDNA quantities during gene expression analysis in macrophages. The expression stabilities of the six candidate reference genes in osteoclasts were, on average, more variable than that observed in macrophages but slightly less variable than those seen in osteoblasts. The two most stably expressed genes in osteoclasts were HMBS and B2M and the genes displaying the greatest levels of variability were 18S and GAPDH. Notably, 18S and GAPDH were the two most variably expressed control genes in all three cell types. The geometric average of HMBS, B2M and ACTB creates an appropriate normalization factor for gene expression studies in osteoclasts.ConclusionWe have identified concise sets of genes suitable to use as normalization factors for quantitative real-time RT-PCR gene expression studies in osteoblasts, osteoclasts and macrophages.

Research capacity building in healthcare works to generate and apply new knowledge to improve health outcomes; it creates new career pathways, improves staff satisfaction, retention and organisational performance. While there are examples of investment and research activity in rural Australia, overall, rural research remains under-reported, undervalued and under-represented in the evidence base. This is particularly so in primary care settings. This lack of contextual knowledge generation and translation perpetuates rural–metropolitan health outcome disparities. Through greater attention to and investment in building research capacity and capability in our regional, rural and remote health services, these issues may be partially addressed. It is proposed that it is time for Australia to systematically invest in rurally focussed, sustainable, embedded research capacity building.

RUNX2 gene SNPs were genotyped in subjects from the upper and lower deciles of age-and weight-adjusted femoral neck BMD. Of 16 SNPs in RUNX2 and its two promoters (P1 and P2), only SNPs in the P2 promoter were significantly associated with BMD. These P2 promoter SNPs were functionally different in gel-shift and promoter activity assays.Introduction: Specific osteoblast genes are induced by Runx2, a cell-specific transcription factor that is a candidate gene for controlling BMD. We tested the hypothesis that RUNX2 genetic variation is associated with BMD. Materials and Methods: From a population repository of normal subjects, the age-and weight-adjusted femoral neck BMD was ranked, and the upper and lower deciles (n ‫ס‬ 132 each) were taken to represent the adjusted extremes of the population distribution. In these 264 subjects, we identified 16 allelic variations within the RUNX2 gene and promoters (P1 and P2) through DNA sequencing and denaturing high-performance liquid chromatography. Characterization of these alleles was performed through allele-specific cloning, transfection into ROS 17/2.8 cells, luciferase reporter analysis, and electrophoretic mobility shift assays. Results: Within the P2 promoter were three polymorphic nucleotides for which the minor alleles were over-represented in the upper decile of BMD (0.117 and 0.064 in the upper and lower deciles, respectively). These alleles are in near complete linkage disequilibrium with each other and represent a haplotype block that is significantly associated with increased BMD. The common and rare P2 promoter alleles were cloned upstream of luciferase, and when transfected into osteoblast-like cells, the construct representing the rare haplotype showed significantly greater P2 promoter activity than the common haplotype. Conclusions: Because the high BMD allele had higher P2 promoter activity, the data suggest that greater RUNX2 P2 promoter activity is associated with higher BMD.

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The percentage of LAPs varied substantially by definition, and further work is required to validate the methods, particularly around the appropriateness of length of consultation time with ACEM, between different hospitals and remoteness areas. Age was strongly associated with low acuity, with substantial effects also observed for GP density, and attendances during out of hours and weekends.

ObjectivesDespite being one of the healthiest countries in the world, Australia displays substantial mortality differentials by socioeconomic disadvantage, remoteness and sex. In this study, we examined how these mortality differentials translated to differences in life expectancy between 2001 and 2012.Design and settingPopulation-based study using mortality and estimated residential population data from Australia's largest state, New South Wales (NSW), between 2001 and 2012. Age-group-specific death rates by socioeconomic disadvantage quintile, remoteness (major cities vs regional and remote areas), sex and year were estimated via Poisson regression, and inputted into life table calculations to estimate life expectancy.ResultsLife expectancy decreased with increasing socioeconomic disadvantage in males and females. The disparity between the most and least socioeconomically deprived quintiles was 3.77 years in males and 2.39 years in females in 2012. Differences in life expectancy by socioeconomic disadvantage were mostly stable over time. Gender gaps in life expectancy ranged from 3.50 to 4.93 years (in 2012), increased with increasing socioeconomic disadvantage and decreased by ∼1 year for all quintiles between 2001 and 2012. Overall, life expectancy varied little by remoteness, but was 1.8 years higher in major cities compared to regional/remote areas in the most socioeconomically deprived regions in 2012.ConclusionsSocioeconomic disadvantage and sex were strongly associated with life expectancy. The disparity in life expectancy across the socioeconomic spectrum was larger in males and was stable over time. In contrast, gender gaps reduced for all quintiles between 2001 and 2012, and a remoteness effect was evident in 2012, but only for those living in the most deprived areas.

Globally, the impact of COVID‐19 on healthcare workers' mental health has been a major focus of recent research. However, Australian research involving nurses, particularly across the acute care sector, is limited. This cross‐sectional research aimed to explore the impact of pandemic‐related stress on psychological adjustment outcomes and potential protective factors for nurses ( n = 767) working in the Australian acute care sector during the COVID‐19 pandemic. Nurses completed an online questionnaire with psychometrically validated measures of pandemic‐related stress, psychological adjustment outcomes (depression, anxiety, and subjective well‐being), and protective factors (posttraumatic growth and self‐compassion). Descriptive analyses revealed that pandemic‐related stress was reported by 17.7% of the participants. Psychological adjustment outcome scores above normal for depression (27.5%) and anxiety (22.0%) were found, and 36.4% of the participants reported poor subjective well‐being. Regression analyses suggest that pandemic‐related stress predicted greater depression ( B = 0.32, SE = 0.02, 95% confidence interval [0.28, 0.35]) and anxiety ( B = 0.26, SE = 0.01, 95% confidence interval [0.24, 0.29]) and less subjective well‐being ( B = −0.14, SE = 0.01, 95% confidence interval [−0.16, −0.12]). Self‐compassion weakened the relationship between pandemic‐related stress and greater depression, however, exacerbated the relationship between pandemic‐related stress and less subjective well‐being. Posttraumatic growth reduced the negative relationship between pandemic‐related stress and psychological adjustment outcomes. These findings will inform strategies to facilitate psychological resources that support nurses' psychological adjustment, enabling better pandemic preparedness at both an individual and organizational level.