Effectiveness of 7-valent pneumococcal conjugate vaccine against radiologically diagnosed pneumonia in indigenous infants in Australia

Objective To evaluate the effectiveness of the 7-valent pneumococcal conjugate vaccine (PCV7) in preventing pneumonia, diagnosed radiologically according to World Health Organization (WHO) criteria, among indigenous infants in the Northern Territory of Australia. Methods We conducted a historical cohort study of consecutive indigenous birth cohorts between 1 April 1998 and 28 February 2005. Children were followed up to 18 months of age. The PCV7 programme commenced on 1 June 2001. All chest X-rays taken within 3 days of any hospitalization were assessed. The primary endpoint was a first episode of WHO-defined pneumonia requiring hospitalization. Cox proportional hazards models were used to compare disease incidence. Findings There were 526 pneumonia events among 10 600 children - an incidence of 3.3 per 1000 child-months; 183 episodes (34.8%) occurred before 5 months of age and 247 (47.0%) by 7 months. Of the children studied, 27% had received 3 doses of vaccine by 7 months of age. Hazard ratios for endpoint pneumonia were 1.01 for 1 versus 0 doses; 1.03 for 2 versus 0 doses; and 0.84 for 3 versus 0 doses. Conclusion There was limited evidence that PCV7 reduced the incidence of radiologically confirmed pneumonia among Northern Territory indigenous infants, although there was a non-significant trend towards an effect after receipt of the third dose. These findings might be explained by lack of timely vaccination and/or occurrence of disease at an early age. Additionally, the relative contribution of vaccine-type pneumococcus to severe pneumonia in a setting where multiple other pathogens are prevalent may differ with respect to other settings where vaccine efficacy has been clearly established.

Mobile silencing in plants: what is the signal and what defines the target

RNA-mediated silencing in plants can spread from cell to cell and over a long distance, and such mobile silencing has been extensively studied in the past decade. However, major questions remain as to what is the exact nature of the mobile silencing signals, how the components of the RNA-directed DNA methylation pathway are involved, and why systemic spread of silencing has only been observed for transgenes but not endogenous genes. In this review, we provide an overview of the current knowledge on mobile gene silencing in plants and present a model where systemic silencing involves long nuclear RNA transcripts that serve as a template to amplify primary siRNA signals.

Application of gene silencing in plants

Recent studies of gene silencing in plants have revealed two RNA-mediated epigenetic processes, RNA-directed RNA degradation and RNA-directed DNA methylation. These natural processes have provided new avenues for developing high-efficiency, high-throughput technology for gene suppression in plants.

Application of gene silencing in plants

Recent studies of gene silencing in plants have revealed two RNA-mediated epigenetic processes, RNA-directed RNA degradation and RNA-directed DNA methylation. These natural processes have provided new avenues for developing high-efficiency, high-throughput technology for gene suppression in plants.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Development and validation of anthropometric prediction equations for estimation of body fat in Indonesian men

Body composition of 292 males aged between 18 and 65 years was measured using the deuterium oxide dilution technique. Participants were divided into development (n=146) and cross-validation (n=146) groups. Stature, body weight, skinfold thickness at eight sites, girth at five sites, and bone breadth at four sites were measured and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-stature ratio (WSR) calculated. Equations were developed using multiple regression analyses with skinfolds, breadth and girth measures, BMI, and other indices as independent variables and percentage body fat (%BF) determined from deuterium dilution technique as the reference. All equations were then tested in the cross-validation group. Results from the reference method were also compared with existing prediction equations by Durnin and Womersley (1974), Davidson et al (2011), and Gurrici et al (1998). The proposed prediction equations were valid in our cross-validation samples with r=0.77- 0.86, bias 0.2-0.5%, and pure error 2.8-3.6%. The strongest was generated from skinfolds with r=0.83, SEE 3.7%, and AIC 377.2. The Durnin and Womersley (1974) and Davidson et al (2011) equations significantly (p<0.001) underestimated %BF by 1.0 and 6.9% respectively, whereas the Gurrici et al (1998) equation significantly (p<0.001) overestimated %BF by 3.3% in our cross-validation samples compared to the reference. Results suggest that the proposed prediction equations are useful in the estimation of %BF in Indonesian men.

Climate Change and the Resilience of Commodity Food Production in Australia

The current view of Australian state and national governments about the effects of climate change on agriculture is that farmers – through the adoption of mitigation and adaptation strategies – will remain resilient, and agricultural production will continue to expand. The assumption is that neoliberalism will provide the best ‘free market’ options for climate change mitigation and adaptation in farming. In contrast, we argue that neoliberalism will increase the move towards productivis (‘high-tech’) agriculture – the very system that has caused major environmental damage to the Australian continent. High-tech farming is highly dependent upon access to water and fossil fuels, both of which would appear to be the main limits to production in future decades. Productivist agriculture is a system highly reliant upon fertilizers and fuels that are derived from the petrochemical industry, and are currently increasing in cost as the price of oil increases.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Managing and analysing big audio data for environmental monitoring

Environmental monitoring is becoming critical as human activity and climate change place greater pressures on biodiversity, leading to an increasing need for data to make informed decisions. Acoustic sensors can help collect data across large areas for extended periods making them attractive in environmental monitoring. However, managing and analysing large volumes of environmental acoustic data is a great challenge and is consequently hindering the effective utilization of the big dataset collected. This paper presents an overview of our current techniques for collecting, storing and analysing large volumes of acoustic data efficiently, accurately, and cost-effectively.

Productive and inclusive? How documentation concealed racialising practices in a diversity project

This article examines how documentation concealed racialising practices in a diversity project that was seen to be productive and inclusive. Documentation examples are taken from a doctoral study about embedding Indigenous perspectives in early childhood education curricula in two Australian urban childcare centres. In place of reporting examples of ‘good’ early childhood education practice, the study labelled racialising practices in educators’ work. The primary aim was to understand how racialising practices are mobilised in professional practices, including documentation, even when educators’ work is seen to be high quality. Extracts from two communal journals that captured an action research process around embedding practices are examined to show how racism and whiteness were concealed within the documentation. This enables understanding about how documentation can provide evidence to stakeholders that diversity work in mainstream childcare centres is productive and inclusive, despite disparity between what is recorded and what occurs in practice.

International entrepreneurship and firm performance over economic crisis

Small and medium firms (SMEs) that operate in global markets are vulnerable to external shocks in uncertain, hostile and volatile business environments given their limited resources and inexperience. In such environments entrepreneurial firms respond by making strategic choices to mitigate such vulnerabilities. This research examines one such important strategic choice – entrepreneurial posturing and its link to financial performance in Finnish SMEs during the global financial crisis. Findings suggest that the dimensions of entrepreneurial posturing have a differential effect on firm performance depending upon the severity of the business environment as well as the firm’s degree of internationalization. Implications for theory and practice are discussed and directions for future research provided.

H2-O2 porous fuel injection in a radical farming scramjet

This paper reports on the experimental testing of oxygen compatible ceramic matrix composite porous injectors in a nominally two-dimensional hydrogen fuelled and oxygen enriched radical farming scramjet in the T4 shock tunnel facility. All experiments were performed at a dynamic pressure of 146 kPa, an equivalent flight Mach number of 9.7, a stagnation pressure and enthalpy of 40MPa and 4.3 MJ/kg respectively and at a fuelling condition that resulted in an average equivalence ratio of 0.472. Oxygen was pre-mixed with the fuel prior to injection to achieve enrichment percentages of approximately 13%, 15% and 17%. These levels ensured that the hydrogen-oxidiser mix injected into the engine always remained too fuel rich to sustain a flame without any additional mixing with the captured air. Addition of pre-mixed oxygen with the fuel was found to significantly alter the performance of the engine; enhancing both combustion and ignition and converting a previously observed limited combustion condition into one with sustained and noticeable combustion induced pressure rise. Increases in the enrichment percentage lead to further increases in combustion levels and acted to reduce ignition lengths within the engine. Suppressed combustion runs, where a nitrogen test gas was used, confirmed that the pressure rise observed in these experiments as attributed to the oxygen enrichment and not associated with the increased mass injected.

Dietary flavonoids from modified apple reduce inflammation markers and modulate gut microbiota in mice

Apples are rich in polyphenols, which provide antioxidant properties, mediation of cellular processes such as inflammation, and modulation of gut microbiota. In this study we compared genetically engineered apples with increased flavonoids [myeloblastis transcription factor 10 (MYB10)] with nontransformed apples from the same genotype, "Royal Gala" (RG), and a control diet with no apple. Compared with the RG diet, the MYB10 diet contained elevated concentrations of the flavonoid subclasses anthocyanins, flavanol monomers (epicatechin) and oligomers (procyanidin B2), and flavonols (quercetin glycosides), but other plant secondary metabolites were largely unaltered. We used these apples to investigate the effects of dietary flavonoids on inflammation and gut microbiota in 2 mouse feeding trials. In trial 1, male mice were fed a control diet or diets supplemented with 20% MYB10 apple flesh and peel (MYB-FP) or RG apple flesh and peel (RG-FP) for 7 d. In trial 2, male mice were fed MYB-FP or RG-FP diets or diets supplemented with 20% MYB10 apple flesh or RG apple flesh for 7 or 21 d. In trial 1, the transcription levels of inflammation-linked genes in mice showed decreases of >2-fold for interleukin-2 receptor (Il2rb), chemokine receptor 2 (Ccr2), chemokine ligand 10 (Cxcl10), and chemokine receptor 10 (Ccr10) at 7 d for the MYB-FP diet compared with the RG-FP diet (P <0.05). In trial 2, the inflammation marker prostaglandin E2 (PGE2) in the plasma of mice fed the MYB-FP diet at 21 d was reduced by 10-fold (P < 0.01) compared with the RG-FP diet. In colonic microbiota, the number of total bacteria for mice fed the MYB-FP diet was 6% higher than for mice fed the control diet at 21 d (P = 0.01). In summary, high-flavonoid apple was associated with decreases in some inflammation markers and changes in gut microbiota when fed to healthy mice.