Use of stable-isotope probing, full-cycle rRNA analysis, and fluorescence in situ hybridization-microautoradiography to study a methanol-fed denitrifying microbial community

A denitrifying microbial consortium was enriched in an anoxically operated, methanol-fed sequencing batch reactor (SBR) fed with a mineral salts medium containing methanol as the sole carbon source and nitrate as the electron acceptor. The SBR was inoculated with sludge from a biological nutrient removal activated sludge plant exhibiting good denitrification. The SBR denitrification rate improved from less than 0.02 mg of NO3-.N mg of mixed-liquor volatile suspended solids (MLVSS)(-1) h(-1) to a steady-state value of 0.06 mg of NO3-.N mg of MLVSS-1 h(-1) over a 7-month operational period. At this time, the enriched microbial community was subjected to stable-isotope probing (SIP) with [C-13] methanol to biomark the DNA of the denitrifiers. The extracted [C-13]DNA and [C-12]DNA from the SIP experiment were separately subjected to full-cycle rRNA analysis. The dominant 16S rRNA gene phylotype (group A clones) in the [C-13]DNA clone library was closely related to those of the obligate methylotrophs Methylobacillus and Methylophilus in the order Methylophilales of the Betaproteobacteria (96 to 97% sequence identities), while the most abundant clone groups in the [C-12]DNA clone library mostly belonged to the family Saprospiraceae in the Bacteroidetes phylum. Oligonucleotide probes for use in fluorescence in situ hybridization (FISH) were designed to specifically target the group A clones and Methylophilales (probes DEN67 and MET1216, respectively) and the Saprospiraceae clones (probe SAP553). Application of these probes to the SBR biomass over the enrichment period demonstrated a strong correlation between the level of SBR denitrification and relative abundance of DEN67-targeted bacteria in the SBR community. By contrast, there was no correlation between the denitrification rate and the relative abundances of the well-known denitrifying genera Hyphomicrobium and Paracoccus or the Saprospiraceae clones visualized by FISH in the SBR biomass. FISH combined with microautoradiography independently confirmed that the DEN67-targeted cells were the dominant bacterial group capable of anoxic [C-14] methanol uptake in the enriched biomass. The well-known denitrification lag period in the methanol-fed SBR was shown to coincide with a lag phase in growth of the DEN67-targeted denitrifying population. We conclude that Methylophilales bacteria are the dominant denitrifiers in our SBR system and likely are important denitrifiers in full-scale methanol-fed denitrifying sludges.

Effects of reduction in heroin supply on injecting drug use: analysis of data from needle and syringe programmes

n early 2001 there was a dramatic decline in the availability of heroin in New South Wales (NSW), Australia, where previously heroin had been readily available at a low price and high purity.1 The decline was confirmed by Australia's strategic early warning system, which revealed a reduction in heroin supply across Australia and a considerable increase in price,2 particularly from January to April 2001. This "heroin shortage" provided a natural experiment in which to examine the effect of substantial changes in price and availability on injecting drug use and its associated harms in Australia's largest heroin market,2 a setting in which harm reduction strategies were widely used. Publicly funded needle and syringe programmes were introduced to Australia in 1987, and methadone maintenance programmes, which were established in the 1970s, were significantly expanded in 1985 and again in 1999.

The use of cusum analysis in the early detection and management of hospital bed occupancy crises

Objective: To assess the value of cusum analysis in hospital bed management. Design: Comparative analysis of medical patient flows, bed occupancy, and emergency department admission rates and access block over 2 years. Setting: Internal Medicine Services and Emergency Department in a teaching hospital. Interventions: Improvements in bed use and changes in the level of available beds. Main outcome measures: Average length of stay; percentage occupancy of available beds; number of patients waiting more than 8 hours for admission (access block); number of medical patients occupying beds in non-medical wards; and number of elective surgical admissions. Results: Cusum analysis provided a simple means of revealing important trends in patient flows that were not obvious in conventional time-series data. This prompted improvements in bed use that resulted in a decrease of 9500 occupied bed-days over a year. Unfortunately and unexpectedly, after some initial improvement, the levels of access block, medical ward congestion and elective surgical admissions all then deteriorated significantly. This was probably caused by excessive bed closures in response to the initial improvement in bed use. Conclusion: Cusum analysis is a useful technique for the early detection of significant changes in patient flows and bed use, and in determining the appropriate number of beds required for a given rate of patient flow.

Tooth wear: diet analysis and advice

Diet analysis and advice for patients with tooth wear is potentially the most logical intervention to arrest attrition, erosion and abrasion. It is saliva that protects the teeth against corrosion by the acids which soften enamel and make it susceptible to wear. Thus the lifestyles and diet of patients at risk need to be analysed for sources of acid and reasons for lost salivary protection. Medical conditions which put patients at risk of tooth wear are principally: asthma, bulimia nervosa, caffeine addiction, diabetes mellitus, exercise dehydration, functional depression, gastroesophageal reflux in alcoholism, hypertension and syndromes with salivary hypofunction. The sources of acid are various, but loss of salivary protection is the common theme. In healthy young Australians, soft drinks are the main source of acid, and exercise dehydration the main reason for loss of salivary protection. In the medically compromised, diet acids and gastroesophageal reflux are the sources, but medications are the main reasons for lost salivary protection. Diet advice for patients with tooth wear must: promote a healthy lifestyle and diet strategy that conserves the teeth by natural means of salivary stimulation; and address the specific needs of the patients' oral and medical conditions. Individualised, patient-empowering erosion WATCH strategies; on Water, Acid, Taste, Calcium and Health, are urgently required to combat the emerging epidemic of tooth wear currently being experienced in westernised societies.

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulae for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.

Demonstration of a simple entangling optical gate and its use in bell-state analysis

We demonstrate a new architecture for an optical entangling gate that is significantly simpler than previous realizations, using partially polarizing beam splitters so that only a single optical mode-matching condition is required. We demonstrate operation of a controlled-z gate in both continuous-wave and pulsed regimes of operation, fully characterizing it in each case using quantum process tomography. We also demonstrate a fully resolving, nondeterministic optical Bell-state analyzer based on this controlled-z gate. This new architecture is ideally suited to guided optics implementations of optical gates.

Analysis of stirred mill performance using DEM simulation: Part 2 - Coherent flow structures, liner stress and wear, mixing and transport

Stirred Mills are becoming increasingly used for fine and ultra-fine grinding. This technology is still poorly understood when used in the mineral processing context. This makes process optimisation of such devices problematic. 3D DEM simulations of the flow of grinding media in pilot scale tower mills and pin mills are carried out in order to investigate the relative performance of these stirred mills. In the first part of this paper, media flow patterns and energy absorption rates and distributions were analysed to provide a good understanding of the media flow and the collisional environment in these mills. In this second part we analyse steady state coherent flow structures, liner stress and wear by impact and abrasion. We also examine mixing and transport efficiency. Together these provide a comprehensive understanding of all the key processes operating in these mills and a clear understanding of the relative performance issues. (C) 2006 Elsevier Ltd. All rights reserved.

A need for caution in the use of frontal analysis continuous capillary electrophoresis for the determination of ligand binding data

Attention is drawn to a need for caution in the determination of binding data for protein-polyelectrolyte interactions by frontal analysis continuous capillary electrophoresis (FACCE). Because the method is valid only for systems involving comigration of complex(es) and slower-migrating reactant, establishing conformity with that condition is clearly a prerequisite for its application. However, that requirement has not been tested in any published studies thus far. On the basis of calculated FACCE patterns, presented to illustrate features by which such comigration of complex(es) and slower-migrating reactant can be identified, the form of the published pattern for a P-lactoglobulin-poly(styrenesulfonate) mixture does not seem to signify the migration behavior required to justify its consideration in such terms. Additional experimental studies are therefore needed to ascertain the validity of FACCE as a means of determining binding data for the characterization of protein-polyelectrolyte interactions. (c) 2005 Elsevier Inc. All rights reserved.

Use of latent profile analysis to identify eating disorder phenotypes in an adult Australian twin cohort

Context: The relationships among the different eating disorders that exist in the community are poorly understood, especially for residual disorders in which bingeing or purging occurs in the absence of other behaviors. Objective: To examine a community sample for the number of mutually exclusive weight and eating profiles. Design: Data regarding lifetime eating disorder symptoms and weight range were submitted to a latent profile analysis. Profiles were compared regarding personality, current eating and weight, retrospectively reported life events, and lifetime depressive psychopathology. Setting: Longitudinal study among female twins from the Australian Twin Registry in whom eating was assessed by a telephone interview. Participants: A community sample of 1002 twins (individuals) who had participated in earlier waves of data collection. Main Outcome Measures: Number and clinical character of latent profiles. Results: The best fit was a 5-profile solution with women who were (1) of normal weight with few lifetime eating disorders (4.3%), (2) overweight (10.6% had a lifetime eating disorder), (3) underweight and generally had no eating disorders except for 5.3% who had restricting anorexia nervosa, (4) of low to normal weight (89.0% had a lifetime eating disorder), and (5) obese (37.0% had a lifetime eating disorder). Each profile contained more than 1 type of lifetime eating disorder except for the third profile. Women in the first and third profiles had the best functioning, with women in the fourth and fifth profiles having similarly poorer functioning. The women in the fourth group had a symptom profile distinctive from the other 4 groups in terms of severity; they were also more likely to have had lifetime major depression and suicidality. Conclusion: Lifetime weight ranges and the severity of eating disorder symptoms affected clustering more than the type of eating disorder symptom.

On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples

This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).