Mary Lunn

Applying cox regression to competing risks

Two methods are given for the joint estimation of parameters in models for competing risks in survival analysis. In both cases Coxs proportional hazards regression model is fitted using a data duplication method. In principle either method can be used for any number of different failure types, assuming independent risks. Advantages of the augmented data approach are that it limits over-parametrisation and it runs immediately on existing software. The methods are used to reanalyse data from two well-known published studies, providing new insights.

Combined niche and neutral effects in a microbial wastewater treatment community

It has long been assumed that differences in the relative abundance of taxa in microbial communities reflect differences in environmental conditions. Here we show that in the economically and environmentally important microbial communities in a wastewater treatment plant, the population dynamics are consistent with neutral community assembly, where chance and random immigration play an important and predictable role in shaping the communities. Using dynamic observations, we demonstrate a straightforward calibration of a purely neutral model and a parsimonious method to incorporate environmental influence on the reproduction (or birth) rate of individual taxa. The calibrated model parameters are biologically plausible, with the population turnover and diversity in the heterotrophic community being higher than for the ammonia oxidizing bacteria (AOB) and immigration into AOB community being relatively higher. When environmental factors were incorporated more of the variance in the observations could be explained but immigration and random reproduction and deaths remained the dominant driver in determining the relative abundance of the common taxa. Consequently we suggest that neutral community models should be the foundation of any description of an open biological system.

What is the extent of prokaryotic diversity

The extent of microbial diversity is an intrinsically fascinating subject of profound practical importance. The term ‘diversity’ may allude to the number of taxa or species richness as well as their relative abundance. There is uncertainty about both, primarily because sample sizes are too small. Non-parametric diversity estimators make gross underestimates if used with small sample sizes on unevenly distributed communities. One can make richness estimates over many scales using small samples by assuming a species/taxa-abundance distribution. However, no one knows what the underlying taxa-abundance distributions are for bacterial communities. Latterly, diversity has been estimated by fitting data from gene clone libraries and extrapolating from this to taxa-abundance curves to estimate richness. However, since sample sizes are small, we cannot be sure that such samples are representative of the community from which they were drawn. It is however possible to formulate, and calibrate, models that predict the diversity of local communities and of samples drawn from that local community. The calibration of such models suggests that migration rates are small and decrease as the community gets larger. The preliminary predictions of the model are qualitatively consistent with the patterns seen in clone libraries in ‘real life’. The validation of this model is also confounded by small sample sizes. However, if such models were properly validated, they could form invaluable tools for the prediction of microbial diversity and a basis for the systematic exploration of microbial diversity on the planet.

White matter lesions account for all age-related declines in speed but not in intelligence.

MRI scans measured white matter lesion prevalence (WMLP) in 65 people ages 65-84 years who also took 17 cognitive tests: 3 tests of general fluid intelligence, 3 of vocabulary, 2 of episodic and 3 of working memory, 2 of processing speed, and 4 of frontal and executive function. Entry of age with WMLP into regression equations as predictors of test scores showed that inferences about the functional relationships between markers of brain aging and cognitive impairments are seriously misleading if they are based on simple correlations alone. A new finding that WMLP accounts for all of the age-related variance between individuals in tests of speed and executive ability but for none of the age-related variance in intelligence revises current hypotheses that gross brain changes affect general fluid intelligence and other mental abilities solely through their effects on information-processing speed.

Spatial-Temporal Survey and Occupancy-Abundance Modeling To Predict Bacterial Community Dynamics in the Drinking Water Microbiome

ABSTRACT Bacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment. Understanding bacterial dynamics in the distribution system is critical to ensuring that safe drinking water is being supplied to customers. We present a 15-month survey of bacterial community dynamics in the drinking water system of Ann Arbor, MI. By sampling the water leaving the treatment plant and at nine points in the distribution system, we show that the bacterial community spatial dynamics of distance decay and dispersivity conform to the layout of the drinking water distribution system. However, the patterns in spatial dynamics were weaker than those for the temporal trends, which exhibited seasonal cycling correlating with temperature and source water use patterns and also demonstrated reproducibility on an annual time scale. The temporal trends were driven by two seasonal bacterial clusters consisting of multiple taxa with different networks of association within the larger drinking water bacterial community. Finally, we show that the Ann Arbor data set robustly conforms to previously described interspecific occupancy abundance models that link the relative abundance of a taxon to the frequency of its detection. Relying on these insights, we propose a predictive framework for microbial management in drinking water systems. Further, we recommend that long-term microbial observatories that collect high-resolution, spatially distributed, multiyear time series of community composition and environmental variables be established to enable the development and testing of the predictive framework. IMPORTANCE Safe and regulation-compliant drinking water may contain up to millions of microorganisms per liter, representing phylogenetically diverse groups of bacteria, archaea, and eukarya that affect public health, water infrastructure, and the aesthetic quality of water. The ability to predict the dynamics of the drinking water microbiome will ensure that microbial contamination risks can be better managed. Through a spatial-temporal survey of drinking water bacterial communities, we present novel insights into their spatial and temporal community dynamics and recommend steps to link these insights in a predictive framework for microbial management of drinking water systems. Such a predictive framework will not only help to eliminate microbial risks but also help to modify existing water quality monitoring efforts and make them more resource efficient. Further, a predictive framework for microbial management will be critical if we are to fully anticipate the risks and benefits of the beneficial manipulation of the drinking water microbiome. Safe and regulation-compliant drinking water may contain up to millions of microorganisms per liter, representing phylogenetically diverse groups of bacteria, archaea, and eukarya that affect public health, water infrastructure, and the aesthetic quality of water. The ability to predict the dynamics of the drinking water microbiome will ensure that microbial contamination risks can be better managed. Through a spatial-temporal survey of drinking water bacterial communities, we present novel insights into their spatial and temporal community dynamics and recommend steps to link these insights in a predictive framework for microbial management of drinking water systems. Such a predictive framework will not only help to eliminate microbial risks but also help to modify existing water quality monitoring efforts and make them more resource efficient. Further, a predictive framework for microbial management will be critical if we are to fully anticipate the risks and benefits of the beneficial manipulation of the drinking water microbiome.

Modeling taxa-abundance distributions in microbial communities using environmental Sequence data

We show that inferring the taxa-abundance distribution of a microbial community from small environmental samples alone is difficult. The difficulty stems from the disparity in scale between the number of genetic sequences that can be characterized and the number of individuals in communities that microbial ecologists aspire to describe. One solution is to calibrate and validate a mathematical model of microbial community assembly using the small samples and use the model to extrapolate to the taxa-abundance distribution for the population that is deemed to constitute a community. We demonstrate this approach by using a simple neutral community assembly model in which random immigrations, births, and deaths determine the relative abundance of taxa in a community. In doing so, we further develop a neutral theory to produce a taxa-abundance distribution for large communities that are typical of microbial communities. In addition, we highlight that the sampling uncertainties conspire to make the immigration rate calibrated on the basis of small samples very much higher than the true immigration rate. This scale dependence of model parameters is not unique to neutral theories; it is a generic problem in ecology that is particularly acute in microbial ecology. We argue that to overcome this, so that microbial ecologists can characterize large microbial communities from small samples, mathematical models that encapsulate sampling effects are required.

Cytokines and IGF-I in delirious and non-delirious acutely ill older medical inpatients

BACKGROUND therapeutic use of cytokines can induce delirium, and delirium often occurs during infections associated with elevated levels of cytokines. This study examined the association of demographic, clinical and biological factors (IL-1alpha, IL-1beta, IL-1RA, IL-6, TNF-alpha, IFN-gamma, LIF, IGF-I, APOE genotype) with the presence and severity of delirium. METHODS in an observational prospective longitudinal study, patients aged 70+ were recruited from an elderly medical unit and assessed every 3-4 days (maximum assessments 4). At each time, the scales MMSE, DRS, CAM, APACHEII were administered and blood was withdrawn to estimate the above biological factors. Mixed effects (PQL) and GEE were used to analyse the repeated measurements and investigate the associations at the individual and population average levels. RESULTS a total of 205 observations on 67 individuals were analysed. Lower levels of IGF-I, and lower levels of circulating IL-1RA, are significantly (P < 0.05) associated with delirium, while the remaining of cytokines, severity of illness and possession of epsilon 4 allele had a non-significant effect. This has been shown by both statistical methods. Similarly lower levels of IGF-I, and high levels of IFN-gamma, are statistically significantly (P < 0.05) associated with higher DRS scores (more severe delirium). CONCLUSIONS this study finds that (i) low levels of both neuroprotective factors (IGF-I, IL-1RA) are associated with delirium, (ii) high IFN-gamma and low IGF-I have significant effects on delirium severity and (iii) otherwise the pro-inflammatory cytokines studied, APOE genotype and severity of illness do not appear to be associated, in older medically ill patients, with either delirium or severity of it.

An assessment of the Basic Treatment Equivalent (BTE) model as measure of radiotherapy workload

Current methods of linear accelerator workload analysis in radiation oncology use patients per hour or fields per hour as the basic unit of measurement but fail to take account of the variations in complexity of different treatment techniques. The Basic Treatment Equivalent (BTE) model of productivity assessment has been derived as a potentially better measure of workload because it includes a complexity factor. This model has now been tested prospectively in ten radiation oncology departments in New South Wales and compared with the numbers of fields and patients per hour. Over a 4-week period there were 50,115 fields administrated in 18,466 fractions in 441 hours of machine time in ten radiation oncology departments. The average productivity results for all departments were 4.18 patients, 11.25 fields and 5.66 BTE per hour. When compared with patients per hour and fields per hour, there was less variability of BTE per patient per hour in all departments, suggesting that most departments deliver radiation therapy in a consistent way, which is not appropriately reflected in the numbers of fields or patients per hour. Departments that were able to treat a high number of patients or fields per hour were able to do so because they used less complicated techniques or had a less complicated casemix of patients. The BTE model allows for variations in the complexity of treatment techniques, is simple to apply, and is reproducible under different conditions in different departments. Following revision of the model, an Australasian study is now proposed. The confirmation of our findings will have significant implications for resource utilization comparisons, patient time allocations, waiting list estimates and cost-benefit analysis.

Understanding Terminal Decline in Cognition and Risk of Death

There is new empirical evidence that the effects of impending death on cognition have been miscalculated because of neglect of the incidence of dropout and of practice gains during longitudinal studies. When these are taken into consideration, amounts and rates of cognitive declines preceding death and dropout are seen to be almost identical, and participants aged 49 to 93 years who neither dropout nor die show little or no decline during a 20-year longitudinal study. Practice effects are theoretically informative. Positive gains are greater for young and more intelligent participants and at all levels of intelligence and durations of practice; declines in scores of 10% or more between successive quadrennial test sessions are risk factors for mortality. Higher baseline intelligence test scores are also associated with reduced risk of mortality, even when demographics and socioeconomic advantage have been taken into consideration.

Unhappiness, health and cognitive ability in old age

BACKGROUND To test whether scores on depression inventories on entry to a longitudinal study predict mental ability over the next 4-16 years. METHOD Associations between scores on the Beck Depression Inventory and on tests of intelligence, vocabulary and memory were analysed in 5070 volunteers aged 49-93 years after differences in prescribed drug consumption, death and drop-out, sex, socio-economic advantage and recruitment cohort effects had also been considered. RESULTS On all cognitive tasks Beck scores on entry, even in the range 0-7 indicating differences in above average contentment, affected overall levels of cognitive performance but not rates of age-related cognitive decline suggesting effects of differences in life satisfaction rather than in depression. CONCLUSIONS A new finding is that, in old age, increments in life satisfaction are associated with better cognitive performance. Implications for interpreting associations between depression inventory scores and cognitive performance in elderly samples are discussed.