Oxidised mannan as a novel adjuvant inducing mucosal IgA production.

Mannan, oxidatively coupled to recombinant protein antigens, has here been tested as a possible adjuvant for the production of antibody on the mucosa. Given intranasally, but not intraperitoneally, mannan markedly enhanced the production of IgA, IgG1 and IgG2a in the serum, and IgA locally in the lung and at remote mucosal sites, including tears, vaginal and salivary secretions. Oxidative coupling was critical to its action, since neither mannan simply mixed with protein nor mannan–protein conjugates which had been reduced by treatment with sodium borohydride, acted as adjuvants. Oxidatively coupled mannan was compared with the widely studied mucosal adjuvant, cholera toxin (CT). The use of oxidised mannan as an adjuvant induced better responses than CT judged by the induction of IgA in serum, vaginal washings and saliva. Thus, oxidised mannan, which is non-toxic and can be administered without injection, is a suitable adjuvant coupled with protective antigens for vaccinating against a number of infections that occur via the mucous membranes.

Oxidised mannan-listeriolysin O conjugates induce Th1/Th2 cytokine responses after intranasal immunisation

Clearance of infectious organisms does not always require polarised Th1 or Th2 responses and it may be advantageous for both Th1 and Th2 responses to be elicited for effective protection against an invading pathogen. It was the aim of this study to investigate oxidised mannan as a possible Th1/Th2 adjuvant. Oxidised mannan was conjugated to two candidate antigens and delivered intranasally to mice. Immunisation with the oxidised conjugate resulted in significant antigen specific proliferative responses, IL-2, IFN-γ and IL-4 production when compared to unconjugated controls.

Bovine muc1 inhibits binding of enteric bacteria to caco-2 cells

Inhibition of bacterial adhesion to intestinal epithelial receptors by the consumption of natural food components is an attractive strategy for the prevention of microbial related gastrointestinal illness. We hypothesised that Muc1, a highly glycosylated mucin present in cows’ milk, may be one such food component. Purified bovine Muc1 was tested for its ability to inhibit binding of common enteric bacterial pathogens to Caco-2 cells grown in vitro. Muc1 caused dose-dependent binding inhibition of Escherichia coli, Salmonella enterica serovar Typhimurium (S. Typhimurium), Staphylococcus aureus and Bacillus subtilis. This inhibition was more pronounced for the Gram negative compared with Gram positive bacteria. It was also demonstrated that Muc1, immobilised on a membrane, bound all these bacterial species in a dose-dependent manner, although there was greater interaction with the Gram negative bacteria. A range of monosaccharides, representative of the Muc1 oligosaccharide composition, were tested for their ability to prevent binding of E. coli and S. Typhimurium to Caco-2 cells. Inhibition was structure dependent with sialic acid, L(-) fucose and D(+) mannose significantly inhibiting binding of both Gram negative species. N-acetylglucosamine and N-acetylgalactosamine significantly inhibited binding of E. coli whilst galactose, one of the most abundant Muc1 monosaccharides, showed the strongest inhibition against S. Typhimurium. Treatment with sialidase significantly decreased the inhibitory properties of Muc1, demonstrating the importance of sialic acid in adhesion inhibition. It is concluded that bovine Muc1 prevents binding of bacteria to human intestinal cells and may have a role in preventing the binding of common enteropathogenic bacteria to human intestinal epithelial surfaces.

Physiology and biochemistry of budburst in Vitis vinifera

Both the physiological and biochemical control of budburst in the grapevine, Vitis Vinifera L. were investigated. It was found that the accuracy of a predictive model for grapevine budburst based on ambient temperature was limited under the experimental conditions. There was a significant correlation of 4.7 ± 0.3 days between the days of maximal xylem exudation and budburst over the 3 years of investigation. The co-relationships between daily xylem exudate volume and a range of environmental parameters were considered. It was found that soil temperature was highly correlated against daily xylem exudation. Ambient temperature and soil moisture were significantly correlated with xylem exudation, however the coefficients of correlation were much lower than that of soil temperature. Rainfall showed only a very limited correlation with daily xylem exudate flow. Seasonal variations in the pH and the carbohydrate and inorganic nutrient concentrations of xylem exudate were investigated. Exudate carbohydrate concentrations fell from 660 µM before the day of maximal xylem exudation to zero levels within 4 weeks. Xylem exudate pH was found to consistently fall to a minimum at the time of maximal exudate flow. Exudate concentrations of the metallic cofactors Ca, K, Mg, Mn and Zn varied directly with daily exudate flow, suggesting some sort of flow-dependent mobilisation of these nutrients. A growth promontory oligosaccharide fraction was prepared by partial acid hydrolysis of grapevine primary cell wall material. This fraction significantly increased control growth of the Lemna minor L. bioassay over a limited ‘window’ of bioactivity. A growth inhibitory oligosaccharide fraction, similar in activity to abscisic acid was isolated from grapevine xylem exudate prior to budburst. The exudate concentration or efficacy of this substance declined after budburst such that there was no apparent growth inhibition. A model is proposed for grapevine budburst whereby an oligosaccharide growth inhibitor is gradually removed from the xylematic stream under the effects of soil temperature, allowing the surge of metabolic activity and vegetative growth that constitute budburst.

Long lived multi-isotype anti-HIV antibody responses following a prime-double boost immunization strategy

Despite decades of work, an effective HIV vaccine remains elusive. In an effort to elicit protective immunity, investigators have sought to define vaccines able to elicit durable HIV-specific B-cell and T-cell activities. Additionally, vaccines are sought which can induce antibodies of a variety of isotypes, as each isotype possesses unique attributes in terms of opsonization, Fc receptor binding capacity, complement fixation and location. One prominent new vaccine strategy, applied to numerous distinct antigenic systems is the prime boost-regimen, with DNA, vaccinia virus (VV), and/or purified recombinant protein. To examine the durability, location and isotype distribution of responses induced by prime-boost regimens, we tested successive immunizations with DNA, VV and protein (D-V-P), comparing three forms of protein inoculations: (i) purified protein administered intramuscularly with complete Freunds adjuvant, (ii) purified protein administered intranasally, and (iii) purified protein conjugated to oxidized mannan, administered intranasally. We found that all three protocols elicited serum antibodies of multiple isotypes, with serum IgA being most prominent among mice immunized with mannan-conjugated protein. All D-V-P protocols, regardless of protein form or route, also elicited antibody responses at mucosal surfaces. In bronchoalveolar lavage, a tendency toward IgA production was again most prominent in mice boosted with the protein–mannan conjugate. Both B-cell and T-cell responses were sustained for more than 1 year post-immunization following each form of vaccination. Contemporaneous with long-lasting serum and mucosal antibodies were antibody forming cells in the bone marrow of primed animals. Results highlight the D-V-P vaccination strategy as a promising approach for attaining durable, multi-isotype B-cell and T-cell activities toward HIV.

Projected socioeconomic disparities in the prevalence of obesity among Australian adults

Objective: To project prevalence of normal weight, overweight and obesity by educational attainment, assuming a continuation of the observed individual weight change in the 5-year follow-up of the national population survey, the Australian Diabetes, Obesity and Lifestyle study (AusDiab; 2000–2005).

Methods: Age-specific transition probabilities between BMI categories, estimated using logistic regression, were entered into education-level-specific, incidence-based, multi-state life tables. Assuming a continuation of the weight change observed in AusDiab, these life tables estimate the prevalence of normal weight, overweight and obesity for Australian adults with low (secondary), medium (diploma) and high (degree) levels of education between 2005 and 2025.

Results: The prevalence of obesity among individuals with secondary level educational attainment is estimated to increase from 23% in 2000 to 44% in 2025. Among individuals with a degree qualification or higher, it will increase from 14% to 30%. If all current educational inequalities in weight change could be eliminated, the projected difference in the prevalence of obesity by 2025 between the highest and lowest educated categories would only be reduced by half (to a 6 percentage point difference from 14 percentage points).

Conclusion: We predict that almost half of Australian adults with low educational status will be obese by 2025. Current trends in obesity have the potential to drive an increase in the absolute difference in obesity prevalence between educational categories in future years.

Implications: Unless obesity prevention and management strategies focus specifically on narrowing social inequalities in obesity, inequalities in health are likely to widen.

Mortality disparities between geographic regions : results from a risk percentiles model for coronary heart disease

Background: Planning of disease prevention strategies requires information regarding the distribution of absolute risk in the population to allow targeting of people at high disease risk. It is well known that death rates from coronary heart disease (CHD) are higher in remote areas of Australia compared with major cities. Less well understood is the distribution of the absolute risk of CHD death within the different geographic regions. We present a mathematical model of CHD which projects the lifetime risk of death among individuals in different percentiles of CHD risk. We apply this to model the distribution of CHD risk within different geographic regions.

Methods: Using information from the Framingham1, MRFIT2 and AusDiab3 studies, the Australian population was divided into percentiles of CHD risk within age and gender groups by geographic location. Absolute mortality risk was determined at each percentile using current Australian mortality data. Survival curves were generated for each percentile using these risk estimates. Approximate confidence intervals were derived using bootstrap methods.

Conclusions: The difference in life expectancy at age 25 between those in the lowest decile of CHD risk compared to the highest was 5.8 years (95%CI:4.7,6.7) in major cities compared to 8.5 years (95%CI:7.6,9.7) in remote areas. The difference in risk of premature death (before age 75) was 12% (95%CI:10%,14%) in major cities compared to 33% (95%CI:28%,38%) in remote areas.

Methodological problem with comparing increases in different measures of body weight

Background A number of studies have compared proportional increases over time in waist circumference (WC) and body mass index (BMI). However this method is flawed. Here, we explain why comparisons of WC and BMI must take into account the relationship between them. We used data from two cross-sectional US surveys (NHANES 1988-94 and 2005-06), and calculated the percentage change in the average BMI and the average WC between the two surveys, comparing the results with a regression analysis of changes in WC relative to BMI.

Findings The crude percentage change in BMI (5.8%) was marginally greater than for WC (5.1%). But these percentages cannot be directly compared, as the relationship between the measures is described by a regression equation with an intercept term that does not equal zero. The coefficient of time from the regression equation will determine whether or not WC is on average larger for a given BMI at the second compared with the first time point.

Conclusion Differences in the percentage change in WC and the percentage change in BMI cannot be usefully directly compared. Comparisons of increases in the two measures must account for the relationship between them as described by the regression equation.

Age at quitting smoking as a predictor of risk of cardiovascular disease incidence independent of smoking status, time since quitting and pack-years

Background: Risk prediction for CVD events has been shown to vary according to current smoking status, pack-years smoked over a lifetime, time since quitting and age at quitting. The latter two are closely and inversely related. It is not known whether the age at which one quits smoking is an additional important predictor of CVD events. The aim of this study was to determine whether the risk of CVD events varied according to age at quitting after taking into account current smoking status, lifetime pack-years smoked and time since quitting.
Findings. We used the Cox proportional hazards model to evaluate the risk of developing a first CVD event for a cohort of participants in the Framingham Offspring Heart Study who attended the fourth examination between ages 30 and 74 years and were free of CVD. Those who quit before the median age of 37 years had a risk of CVD incidence similar to those who were never smokers. The incorporation of age at quitting in the smoking variable resulted in better prediction than the model which had a simple current smoker/non-smoker measure and the one that incorporated both time since quitting and pack-years. These models demonstrated good discrimination, calibration and global fit. The risk among those quitting more than 5 years prior to the baseline exam and those whose age at quitting was prior to 44 years was similar to the risk among never smokers. However, the risk among those quitting less than 5 years prior to the baseline exam and those who continued to smoke until 44 years of age (or beyond) was two and a half times higher than that of never smokers.
Conclusions: Age at quitting improves the prediction of risk of CVD incidence even after other smoking measures are taken into account. The clinical benefit of adding age at quitting to the model with other smoking measures may be greater than the associated costs. Thus, age at quitting should be considered in addition to smoking status, time since quitting and pack-years when counselling individuals about their cardiovascular risk.

Framingham risk prediction equations for incidence of cardiovascular disease using detailed measures for smoking

Current prediction models for risk of cardiovascular disease (CVD) incidence incorporate smoking as a dichotomous yes/no measure. However, the risk of CVD associated with smoking also varies with the intensity and duration of smoking and there is a strong association between time since quitting and the risk of disease onset. This study aims to develop improved risk prediction equations for CVD incidence incorporating intensity and duration of smoking and time since quitting. The risk of developing a first CVD event was evaluated using a Cox’s model for participants in the Framingham offspring cohort who attended the fourth examination (1988–92) between the ages of 30 and 74 years and were free of CVD (n=3751). The full models based on the smoking variables and other risk factors, and reduced models based on the smoking variables and non-laboratory risk factors demonstrated good discrimination, calibration and global fit. The incorporation of both time since quitting among past smokers and pack-years among current smokers resulted in better predictive performance as compared to a dichotomous current/non-smoker measure and a current/quitter/never smoker measure. Compared to never smokers, the risk of CVD incidence increased with pack-years. Risk among those quitting more than five years prior to the baseline exam and within five years prior to the baseline exam were similar and twice as high as that of never smokers. A CVD risk equation incorporating the effects of pack-years and time since quitting provides an improved tool to quantify risk and guide preventive care.

Epidemiologic merit of obese-years, the combination of degree and duration of obesity

This study aims to test the effect of combining the degree and the duration of obesity into a single variable-obese-years-and to examine whether obese-years is a better predictor of the risk of diabetes than simply body mass index (BMI) or duration of obesity. Of the original cohort of the Framingham Heart Study, 5,036 participants were followed up every 2 years for up to 48 years (from 1948). The variable, obese-years, was defined by multiplying for each participant the number of BMI units above 30 kg/m(2) by the number of years lived at that BMI. Associations with diabetes were analyzed by using time-dependent Cox proportional hazards regression models adjusted for potential confounders. The incidence of type-2 diabetes increased as the number of obese-years increased, with adjusted hazard ratios of 1.07 (95% confidence interval: 1.06, 1.09) per additional 10 obese-years. The dose-response relation between diabetes incidence and obese-years varied by sex and smoking status. The Akaike Information Criterion was lowest in the model containing obese-years compared with models containing either the degree or duration of obesity alone. A construct of obese-years is strongly associated with risk of diabetes and could be a better indicator of the health risks associated with increasing body weight than BMI or duration of obesity alone.

Comparing trends in BMI and waist circumference

The nature of excess body weight may be changing over time to one of greater central adiposity. The aim of this study is to determine whether BMI and waist circumference (WC) are increasing proportionately among population subgroups and the range of bodyweight, and to examine the public health implications of the findings. Our data are from two cross-sectional surveys (the US National Health and Nutrition Examination Studies (NHANES) in 1988–1994 (NHANES III) and 2005–2006), from which we have used samples of 15,349 and 4,176 participants aged ≥20 years. Between 1988–1994 and 2005–2006 BMI increased by an average of 1.8 kg/m2 and WC by 4.7 cm (adjusted for sex, age, race-ethnicity, and education). The increase in WC was more than could be attributed simply to increases in BMI. This independent increase in WC (of on average, 0.9 cm) was consistent across the different BMI categories, sexes, education levels, and race-ethnicity groups. It occurred in younger but not older age groups. Overall in each BMI category, the prevalence of low-risk WC decreased and the prevalence of increased-risk or substantially increased-risk WC increased. These results suggest that the adverse health consequences associated with obesity may be increasingly underestimated by trends in BMI alone. Since WC is closely linked to adverse cardiovascular outcomes, it is important to know the prevailing trends in both of these parameters.

The effect of modifiable risk factors on geographic mortality differentials : a modelling study

Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown.

Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy.

Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%.

Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas. Background: Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods. We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results: Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas - accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men - accounting for 8.8% and 6.3% respectively - and only smoking contributing to the difference in women - accounting for 12.3%. Conclusions: These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.