Incomplete pregnancy and risk of ovarian cancer : results from two Australian case-control studies and systematic review

Although full-term pregnancies reduce the risk of ovarian cancer, it has not been conclusively established whether incomplete pregnancies also influence risk. We investigated the relationship between a history of incomplete pregnancy and incident epithelial ovarian cancer among over 4,500 women who participated in two large Australian population-based case-control studies in 1990-1993 and 2002-2005. They provided responses to detailed questions about their reproductive histories and other personal factors. Summary odds ratios (OR) and confidence intervals (CI) derived from each study using the same covariates were aggregated. We found no significant associations between the number of incomplete pregnancies and ovarian cancer, for parous (OR = 0.98, 95% CI: 0.89, 1.08) or nulliparous (OR = 1.06, 95% CI: 0.75, 1.48) women, nor for the number of spontaneous or induced abortions and ovarian cancer for parous women (OR = 0.95, 95% CI 0.82, 1.09; OR = 1.08, 95% CI: 0.86, 1.36) or nulliparous women (OR = 1.2, 95% CI: 0.6, 2.4; OR = 0.8, 95% CI: 0.47, 1.38), respectively. A systematic review of 37 previous studies of the topic confirmed our findings that a history of incomplete pregnancy does not influence a woman’s risk of epithelial ovarian cancer.

Clarification of cane juice for fermentation

Fermentation feedstocks in the sugar industry are based on cane juice, B molasses or final molasses. Brazil has been producing ethanol by directing sugarcane juice to fermentation directly or using lower quality juice as a diluent with B molasses to prepare the fermentation broth. One issue that has received only limited interest particularly from outside Brazil is the most appropriate conditions for clarification of the juice going to fermentation. Irrespective of whether the juice supply is the total flow from the milling tandem or a diffuser station or a part of the total flow, removal of the insoluble solids is essential. However, the standard defecation process used by sugar factories around the world to clarify juice can introduce unwanted calcium ions and remove other nutrients such as phosphorus and nitrogen that are considered essential for the fermentation process. An investigation was undertaken by SRI to assess the effects on the constituents of cane juice when subjected to the typical clarification process in an Australian factory and what conditions would be needed to provide a clarified juice suitable for fermentation. Typical juices from one factory were clarified in laboratory trials under a range of pH conditions and the resulting clarified juices analysed. The results indicated that pH had a major effect on the residual concentrations of key constituents in the clarified juice and that the selected clarification conditions are determined by the nominated quality criteria of clarified juice feedstock for fermentation. Further trials were conducted in overseas factories to confirm the results obtained in Australia. It became apparent that the preferred specifications for clarified juice going to fermentation varied from country to country. Each supplier of fermentation technology had criteria applying to clarified juice feedstock that would have a major impact on the standard of clarification required to achieve compliance with the criteria.

Civics and citizenship education in the national history curriculum : conducting the same music or rehearsing an incomplete tune?

This paper raises some questions about teaching and teacher education in the social sciences in response to the decision to implement a national curriculum in Australia. In particular, it contends that the decision to focus on discipline-specific knowledge in the social sciences will not necessarily meet the hopes of the Melbourne Declaration and deliver a 21st century curriculum that prepares students for the future. In doing so, it suggests that social educators need to engage with the broader discourse and political context shaping the push for curriculum reform in Australia and makes reference to the marginalisation of civics and citizenship education in the latest draft of the Australian curriculum: History.

Using incomplete online metric maps for topological exploration with the Gap Navigation Tree

This paper presents a general, global approach to the problem of robot exploration, utilizing a topological data structure to guide an underlying Simultaneous Localization and Mapping (SLAM) process. A Gap Navigation Tree (GNT) is used to motivate global target selection and occluded regions of the environment (called “gaps”) are tracked probabilistically. The process of map construction and the motion of the vehicle alters both the shape and location of these regions. The use of online mapping is shown to reduce the difficulties in implementing the GNT.

Handling incomplete data in survival analysis with multiple covariates

This paper studies the missing covariate problem which is often encountered in survival analysis. Three covariate imputation methods are employed in the study, and the effectiveness of each method is evaluated within the hazard prediction framework. Data from a typical engineering asset is used in the case study. Covariate values in some time steps are deliberately discarded to generate an incomplete covariate set. It is found that although the mean imputation method is simpler than others for solving missing covariate problems, the results calculated by it can differ largely from the real values of the missing covariates. This study also shows that in general, results obtained from the regression method are more accurate than those of the mean imputation method but at the cost of a higher computational expensive. Gaussian Mixture Model (GMM) method is found to be the most effective method within these three in terms of both computation efficiency and predication accuracy.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Microalgal biomass as a fermentation feedstock for bioethanol production

BACKGROUND The increasing cost of fossil fuels as well as the escalating social and industrial awareness of the environmental impacts associated with the use of fossil fuels has created the need for more sustainable fuel options. Bioethanol, produced from renewable biomass such as sugar and starch materials, is believed to be one of these options, and it is currently being harnessed extensively. However, the utilization of sugar and starch materials as feedstocks for bioethanol production creates a major competition with the food market in terms of land for cultivation, and this makes bioethanol from these sources economically less attractive. RESULT This study explores the suitability of microalgae (Chlorococum sp.) as a substrate for bioethanol production via yeast (Saccharomycesbayanus)under different fermentation conditions. Results show a maximum ethanol concentration of 3.83 g L -1 obtained from 10 g L-1 of lipid-extracted microalgae debris. CONCLUSION This productivity level (∼38% w/w), which is in keeping with that of current production systems endorses microalgae as a promising substrate for bioethanol production.

Development of a pilot-scale bacterial fermentation for plasmid-based biopharmaceutical production using a stoichiometric medium

The recognition of the potential efficacy of plasmid DNA (pDNA) molecules as vectors in the treatment and prevention of emerging diseases has birthed the confidence to combat global pandemics. This is due to the close-to-zero safety concern associated with pDNA vectors compared to viral vectors in cell transfection and targeting. Considerable attention has been paid to the potential of pDNA vectors but comparatively less thought has been given to the practical challenges in producing large quantities to meet current rising demands. A pilot-scale fermentation scheme was developed by employing a stoichiometrically-designed growth medium whose exceptional plasmid yield performance was attested in a shake flask environment for pUC19 and pEGFP-N1 transformed into E. coliDH5α and E. coliJM109, respectively. Batch fermentation of E. coliDH5α-pUC19 employing the stoichiometric medium displayed a maximum plasmid volumetric and specific yield of 62.6 mg/L and 17.1 mg/g (mg plasmid/g dry cell weight), respectively. Fed-batch fermentation of E. coliDH5α-pUC19 on a glycerol substrate demonstrated one of the highest ever reported pilot-scale plasmid specific yield of 48.98 mg/g and a volumetric yield of 0.53 g/L. The attainment of high plasmid specific yields constitutes a decrease in plasmid manufacturing cost and enhances the effectiveness of downstream processes by reducing the proportion of intracellular impurities. The effect of step-rise temperature induction was also considered to maximize ColE1-origin plasmid replication.

Bio-hydrogen production from food waste through anaerobic fermentation

In order to protect our planet and ourselves from the adverse effects of excessive CO2 emissions and to prevent an imminent non-renewable fossil fuel shortage and energy crisis, there is a need to transform our current ‘fossil fuel dependent’ energy systems to new, clean, renewable energy sources. The world has recognized hydrogen as an energy carrier that complies with all the environmental quality and energy security, demands. This research aimed at producing hydrogen through anaerobic fermentation, using food waste as the substrate. Four food waste substrates were used: Rice, fish, vegetable and their mixture. Bio-hydrogen production was performed in lab scale reactors, using 250 mL serum bottles. The food waste was first mixed with the anaerobic sewage sludge and incubated at 37°C for 31 days (acclimatization). The anaerobic sewage sludge was then heat treated at 80°C for 15 min. The experiment was conducted at an initial pH of 5.5 and temperatures of 27, 35 and 55°C. The maximum cumulative hydrogen produced by rice, fish, vegetable and mixed food waste substrates were highest at 37°C (Rice =26.97±0.76 mL, fish = 89.70±1.25 mL, vegetable = 42.00±1.76 mL, mixed = 108.90±1.42 mL). A comparative study of acclimatized (the different food waste substrates were mixed with anaerobic sewage sludge and incubated at 37°C for 31days) and non-acclimatized food waste substrate (food waste that was not incubated with anaerobic sewage sludge) showed that acclimatized food waste substrate enhanced bio-hydrogen production by 90 - 100%.

Significant deterioration in nanomechanical quality occurs through incomplete extrafibrillar mineralization in rachitic bone: Evidence from in-situ synchrotron X-ray scattering and backscattered electron imaging

Bone diseases such as rickets and osteoporosis cause significant reduction in bone quantity and quality, which leads to mechanical abnormalities. However, the precise ultrastructural mechanism by which altered bone quality affects mechanical properties is not clearly understood. Here we demonstrate the functional link between altered bone quality (reduced mineralization) and abnormal fibrillar-level mechanics using a novel, real-time synchrotron X-ray nanomechanical imaging method to study a mouse model with rickets due to reduced extrafibrillar mineralization. A previously unreported N-ethyl-N-nitrosourea (ENU) mouse model for hypophosphatemic rickets (Hpr), as a result of missense Trp314Arg mutation of the phosphate regulating gene with homologies to endopeptidase on the X chromosome (Phex) and with features consistent with X-linked hypophosphatemic rickets (XLHR) in man, was investigated using in situ synchrotron small angle X-ray scattering to measure real-time changes in axial periodicity of the nanoscale mineralized fibrils in bone during tensile loading. These determine nanomechanical parameters including fibril elastic modulus and maximum fibril strain. Mineral content was estimated using backscattered electron imaging. A significant reduction of effective fibril modulus and enhancement of maximum fibril strain was found in Hpr mice. Effective fibril modulus and maximum fibril strain in the elastic region increased consistently with age in Hpr and wild-type mice. However, the mean mineral content was ∼21% lower in Hpr mice and was more heterogeneous in its distribution. Our results are consistent with a nanostructural mechanism in which incompletely mineralized fibrils show greater extensibility and lower stiffness, leading to macroscopic outcomes such as greater bone flexibility. Our study demonstrates the value of in situ X-ray nanomechanical imaging in linking the alterations in bone nanostructure to nanoscale mechanical deterioration in a metabolic bone disease. Copyright