The future for genetic studies in reproduction

Genetic factors contribute to risk of many common diseases affecting reproduction and fertility. In recent years, methods for genome-wide association studies(GWAS) have revolutionized gene discovery forcommontraits and diseases. Results of GWAS are documented in the Catalog of Published Genome-Wide Association Studies at the National Human Genome Research Institute and report over 70 publications for 32 traits and diseases associated with reproduction. These include endometriosis, uterine fibroids, age at menarche and age at menopause. Results that pass appropriate stringent levels of significance are generally well replicated in independent studies. Examples of genetic variation affecting twinning rate, infertility, endometriosis and age at menarche demonstrate that the spectrum of disease-related variants for reproductive traits is similar to most other common diseases.GWAS 'hits' provide novel insights into biological pathways and the translational value of these studies lies in discovery of novel gene targets for biomarkers, drug development and greater understanding of environmental factors contributing to disease risk. Results also show that genetic data can help define sub-types of disease and co-morbidity with other traits and diseases. To date, many studies on reproductive traits have used relatively small samples. Future genetic marker studies in large samples with detailed phenotypic and clinical information will yield new insights into disease risk, disease classification and co-morbidity for many diseases associated with reproduction and infertility.

3D cultures of prostate cancer cells cultured in a novel high-throughput culture platform are more resistant to chemotherapeutics compared to cells cultured in monolayer

Despite monolayer cultures being widely used for cancer drug development and testing, 2D cultures tend to be hypersensitive to chemotherapy and are relatively poor predictors of whether a drug will provide clinical benefit. Whilst generally more complicated, three dimensional (3D) culture systems often better recapitulate true cancer architecture and provide a more accurate drug response. As a step towards making 3D cancer cultures more accessible, we have developed a microwell platform and surface modification protocol to enable high throughput manufacture of 3D cancer aggregates. Herein we use this novel system to characterize prostate cancer cell microaggregates, including growth kinetics and drug sensitivity. Our results indicate that prostate cancer cells are viable in this system, however some non-cancerous prostate cell lines are not. This system allows us to consistently control for the presence or absence of an apoptotic core in the 3D cancer microaggregates. Similar to tumor tissues, the 3D microaggregates display poor polarity. Critically the response of 3D microaggregates to the chemotherapeutic drug, docetaxel, is more consistent with in vivo results than the equivalent 2D controls. Cumulatively, our results demonstrate that these prostate cancer microaggregates better recapitulate the morphology of prostate tumors compared to 2D and can be used for high-throughput drug testing.

Pituitary volume and early treatment response in drug-naïve first-episode psychosis patients

BACKGROUND: An early response to antipsychotic treatment in patients with psychosis has been associated with a better course and outcome. However, factors that predict treatment response are not well understood. The onset of schizophrenia and related disorders has been associated with increased levels of stress and hyper-activation of the hypothalamic-pituitary-adrenal (HPA) axis. This study examined whether pituitary volume at the onset of psychosis may be a potential predictor of early treatment response in first-episode psychosis (FEP) patients. METHODS: We investigated the relationship between baseline pituitary volume and symptomatic treatment response over 12 weeks using mixed model analysis in a sample of 42 drug-naïve or early treated FEP patients who participated in a controlled dose-finding study of quetiapine fumarate. Logistic regression was used to examine predictors of treatment response. Pituitary volume was measured from magnetic resonance imaging scans that were obtained upon entry into the trial. RESULTS: Larger pituitary volume was associated with less improvement in overall psychotic symptoms (Brief Psychiatric Rating Scale (BPRS) P=0.031) and positive symptoms (BPRS positive symptom subscale P=0.010). Regardless of gender, patients with a pituitary volume at the 25th percentile (413 mm(3)) were approximately three times more likely to respond to treatment by week 12 than those at the 75th percentile (635 mm(3)) (odds ratio=3.07, CI: 0.90-10.48). CONCLUSION: The association of baseline pituitary volumes with early treatment response highlights the importance of the HPA axis in emerging psychosis. Potential implications for treatment strategies in early psychosis are discussed.

Size-resolved particle distribution and gaseous concentrations by real-world road tunnel measurement

Measurements of aerosol particle number size distributions (15-700 nm), CO and NOx were performed in a bus tunnel, Australia. Daily mean particle size distributions of mixed diesel/CNG (Compressed Natural Gas) buses traffic flow were determined in 4 consecutive measurement days. EFs (Emission Factors) of Particle size distribution of diesel buses and CNG buses were obtained by MLR (Multiple Linear Regression) methods, particle distributions of diesel buses and CNG buses were observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow were decomposed by two log-normal fitting curves for each 30 minutes interval mean scans, all the mix fleet PSD emission can be well fitted by the summation of two log-normal distribution curves, and these were composed of nuclei mode curve and accumulation curve, which were affirmed as the CNG buses and diesel buses PN emission curves respectively. Finally, particle size distributions of diesel buses and CNG buses were quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters were 74.5～87.5nm, geometric standard deviations were 1.89～1.98. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters were 21～24 nm, geometric standard deviations were 1.27～1.31.

Lactose surface modification by decantation: Are drug-fine lactose ratios the key to better dispersion of salmeterol xinafoate from lactose-interactive mixtures?

Purpose The role of fine lactose in the dispersion of salmeterol xinafoate (SX) from lactose mixtures was studied by modifying the fine lactose concentration on the surface of the lactose carriers using wet decantation. Methods Fine lactose was removed from lactose carriers by wet decantation using ethanol saturated with lactose. Particle sizing was achieved by laser diffraction. Fine particle fractions (FPFs) were determined by Twin Stage Impinger using a 2.5% SX mixture, and SX was analyzed by a validated high-performance liquid chromatography method. Adhesion forces between probes of SX and silica and the lactose surfaces were determined by atomic force microscopy. Results FPFs of SX were related to fine lactose concentration in the mixture for inhalation grade lactose samples. Reductions in FPF (2-4-fold) of Aeroflo 95 and 65 were observed after removing fine lactose by wet decantation; FPFs reverted to original values after addition of micronized lactose to decanted mixtures. FPFs of SX of sieved and decanted fractions of Aeroflo carriers were significantly different (p < 0.001). The relationship between FPF and fine lactose concentration was linear. Decanted lactose demonstrated surface modification through increased SX-lactose adhesion forces; however, any surface modification other than removal of fine lactose only slightly influenced FPF. Conclusions Fine lactose played a key and dominating role in controlling FPF. SX to fine lactose ratios influenced dispersion of SX with maximum dispersion occurring as the ratio approached unity.

Volatile organic compounds: Characteristics, distribution and sources in urban schools

Long term exposure to organic pollutants, both inside and outside school buildings may affect children’s health and influence their learning performance. Since children spend significant amount of time in school, air quality, especially in classrooms plays a key role in determining the health risks associated with exposure at schools. Within this context, the present study investigated the ambient concentrations of Volatile Organic Compounds (VOCs) in 25 primary schools in Brisbane with the aim to quantify the indoor and outdoor VOCs concentrations, identify VOCs sources and their contribution, and based on these; propose mitigation measures to reduce VOCs exposure in schools. One of the most important findings is the occurrence of indoor sources, indicated by the I/O ratio >1 in 19 schools. Principal Component Analysis with Varimax rotation was used to identify common sources of VOCs and source contribution was calculated using an Absolute Principal Component Scores technique. The result showed that outdoor 47% of VOCs were contributed by petrol vehicle exhaust but the overall cleaning products had the highest contribution of 41% indoors followed by air fresheners and art and craft activities. These findings point to the need for a range of basic precautions during the selection, use and storage of cleaning products and materials to reduce the risk from these sources.

A normal-distribution based rating aggregation method for generating product reputations

With the extensive use of rating systems in the web, and their significance in decision making process by users, the need for more accurate aggregation methods has emerged. The Naïve aggregation method, using the simple mean, is not adequate anymore in providing accurate reputation scores for items [6 ], hence, several researches where conducted in order to provide more accurate alternative aggregation methods. Most of the current reputation models do not consider the distribution of ratings across the different possible ratings values. In this paper, we propose a novel reputation model, which generates more accurate reputation scores for items by deploying the normal distribution over ratings. Experiments show promising results for our proposed model over state-of-the-art ones on sparse and dense datasets.

Hepatitis C and initiates into injecting drug use among young people: Part I: The first shot

Explores how young people in Australia first come to inject drugs and how they learn about hepatitis C and sterile injecting drug use. Background on hepatitis C; Reasons for injecting drugs; Selection criteria for young people's participation in the i2i Project.

Reproducible and label-free biosensor for the selective extraction and rapid detection of proteins in biological fluids

Erythropoietin (EPO), a glycoprotein hormone of ∼34 kDa, is an important hematopoietic growth factor, mainly produced in the kidney and controls the number of red blood cells circulating in the blood stream. Sensitive and rapid recombinant human EPO (rHuEPO) detection tools that improve on the current laborious EPO detection techniques are in high demand for both clinical and sports industry. A sensitive aptamer-functionalized biosensor (aptasensor) has been developed by controlled growth of gold nanostructures (AuNS) over a gold substrate (pAu/AuNS). The aptasensor selectively binds to rHuEPO and, therefore, was used to extract and detect the drug from horse plasma by surface enhanced Raman spectroscopy (SERS). Due to the nanogap separation between the nanostructures, the high population and distribution of hot spots on the pAu/AuNS substrate surface, strong signal enhancement was acquired. By using wide area illumination (WAI) setting for the Raman detection, a low RSD of 4.92% over 150 SERS measurements was achieved. The significant reproducibility of the new biosensor addresses the serious problem of SERS signal inconsistency that hampers the use of the technique in the field. The WAI setting is compatible with handheld Raman devices. Therefore, the new aptasensor can be used for the selective extraction of rHuEPO from biological fluids and subsequently screened with handheld Raman spectrometer for SERS based in-field protein detection.

The time taken for the regional distribution of ventilation to stabilise: An investigation using electrical impedance tomography

Electrical impedance tomography is a novel technology capable of quantifying ventilation distribution in the lung in real time during various therapeutic manoeuvres. The technique requires changes to the patient’s position to place the electrical impedance tomography electrodes circumferentially around the thorax. The impact of these position changes on the time taken to stabilise the regional distribution of ventilation determined by electrical impedance tomography is unknown. This study aimed to determine the time taken for the regional distribution of ventilation determined by electrical impedance tomography to stabilise after changing position. Eight healthy, male volunteers were connected to electrical impedance tomography and a pneumotachometer. After 30 minutes stabilisation supine, participants were moved into 60 degrees Fowler’s position and then returned to supine. Thirty minutes was spent in each position. Concurrent readings of ventilation distribution and tidal volumes were taken every five minutes. A mixed regression model with a random intercept was used to compare the positions and changes over time. The anterior-posterior distribution stabilised after ten minutes in Fowler’s position and ten minutes after returning to supine. Left-right stabilisation was achieved after 15 minutes in Fowler’s position and supine. A minimum of 15 minutes of stabilisation should be allowed for spontaneously breathing individuals when assessing ventilation distribution. This time allows stabilisation to occur in the anterior-posterior direction as well as the left-right direction.

Gamma tocotrienol targets tyrosine phosphatase SHP2 in mammospheres resulting in cell death through RAS/ERK pathway

Background There is increasing evidence supporting the concept of cancer stem cells (CSCs), which are responsible for the initiation, growth and metastasis of tumors. CSCs are thus considered the target for future cancer therapies. To achieve this goal, identifying potential therapeutic targets for CSCs is essential. Methods We used a natural product of vitamin E, gamma tocotrienol (gamma-T3), to treat mammospheres and spheres from colon and cervical cancers. Western blotting and real-time RT-PCR were employed to identify the gene and protein targets of gamma-T3 in mammospheres. Results We found that mammosphere growth was inhibited in a dose dependent manner, with total inhibition at high doses. Gamma-T3 also inhibited sphere growth in two other human epithelial cancers, colon and cervix. Our results suggested that both Src homology 2 domain-containing phosphatase 1 (SHP1) and 2 (SHP2) were affected by gamma-T3 which was accompanied by a decrease in K- and H-Ras gene expression and phosphorylated ERK protein levels in a dose dependent way. In contrast, expression of self-renewal genes TGF-beta and LIF, as well as ESR signal pathways were not affected by the treatment. These results suggest that gamma-T3 specifically targets SHP2 and the RAS/ERK signaling pathway. Conclusions SHP1 and SHP2 are potential therapeutic targets for breast CSCs and gamma-T3 is a promising natural drug for future breast cancer therapy.

The high price of drug patents: Australia, patent law, pharmaceutical drugs and the Trans-Pacific Partnership

This week, the secrecy surrounding an independent Australian report on patent law and pharmaceutical drugs has been lifted, and the work has been published to great acclaim...

Uncertain species distribution: From interpolation to extrapolation

Species distribution models (SDMs) are considered to exemplify Pattern rather than Process based models of a species' response to its environment. Hence when used to map species distribution, the purpose of SDMs can be viewed as interpolation, since species response is measured at a few sites in the study region, and the aim is to interpolate species response at intermediate sites. Increasingly, however, SDMs are also being used to also extrapolate species-environment relationships beyond the limits of the study region as represented by the training data. Regardless of whether SDMs are to be used for interpolation or extrapolation, the debate over how to implement SDMs focusses on evaluating the quality of the SDM, both ecologically and mathematically. This paper proposes a framework that includes useful tools previously employed to address uncertainty in habitat modelling. Together with existing frameworks for addressing uncertainty more generally when modelling, we then outline how these existing tools help inform development of a broader framework for addressing uncertainty, specifically when building habitat models. As discussed earlier we focus on extrapolation rather than interpolation, where the emphasis on predictive performance is diluted by the concerns for robustness and ecological relevance. We are cognisant of the dangers of excessively propagating uncertainty. Thus, although the framework provides a smorgasbord of approaches, it is intended that the exact menu selected for a particular application, is small in size and targets the most important sources of uncertainty. We conclude with some guidance on a strategic approach to identifying these important sources of uncertainty. Whilst various aspects of uncertainty in SDMs have previously been addressed, either as the main aim of a study or as a necessary element of constructing SDMs, this is the first paper to provide a more holistic view.

Information-theoretic analysis of brain white matter fiber orientation distribution functions

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.