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PubMed2002

To 5D and beyond: quantitative fluorescence microscopy in the postgenomic era.

Digital fluorescence microscopy is now a standard technology for assaying molecular localisation in cells and tissues. The choice of laser scanning (LSM) and wide-field microscopes (WFM) largely depends on the type of sample, with LSMs performing best on thick samples and WFMs performing best on thin ones. These systems are increasingly used to collect large multidimensional datasets. We propose a unified image structure that considers space, time, and fluorescence wavelength as integral parts of the image. Moreover, the application of fluorescence imaging to large-scale screening means that large datasets are now routinely acquired. We propose that analysis of these data requires querying tools based on relational databases and describe one such system.

Animals↗

PubMed2006

Satisfaction with mental health services. A user participation approach.

User participation in the delivery and evaluation of mental health services has become an important policy element in the development of these services. An important area where user involvement could be especially useful concerns satisfaction with care, which has become considered an important indicator of service excellence. The overall aim of this study was to investigate user satisfaction with mental health services in a county in southern Sweden. The study design used persons with own experience from being a patient or a close relative to a patient as active participants in the data collection. A group of 20 persons with experience from being users or relatives to users were recruited and trained to be interviewers in the study. Together they performed 227 interviews focusing user satisfaction regarding both inpatient and outpatient care. The interview had one quantitative part and one qualitative part. The interviewers' experiences from participation in the project were evaluated through focus groups. In these groups, the topics were the interviewers' impression of the content of their interviews and their experience from being an interviewer. The analysis showed a high satisfaction with care in the quantitative part. In the qualitative part a significant dissatisfaction with many aspects of the care were expressed. The focus group evaluation largely supported the findings from the analyses of the dataset. Experiences of being user and interviewer were generally positive and perceived as rewarding.

Adult↗

PubMed2006

On the use of multi-objective evolutionary algorithms for survival analysis.

This paper proposes and evaluates a multi-objective evolutionary algorithm for survival analysis. One aim of survival analysis is the extraction of models from data that approximate lifetime/failure time distributions. These models can be used to estimate the time that an event takes to happen to an object. To use of multi-objective evolutionary algorithms for survival analysis has several advantages. They can cope with feature interactions, noisy data, and are capable of optimising several objectives. This is important, as model extraction is a multi-objective problem. It has at least two objectives, which are the extraction of accurate and simple models. Accurate models are required to achieve good predictions. Simple models are important to prevent overfitting, improve the transparency of the models, and to save computational resources. Although there is a plethora of evolutionary approaches to extract models for classification and regression, the presented approach is one of the first applied to survival analysis. The approach is evaluated on several artificial datasets and one medical dataset. It is shown that the approach is capable of producing accurate models, even for problems that violate some of the assumptions made by classical approaches.

Algorithms↗

PubMed2003

A probabilistic approach to interpreting verbal autopsies: methodology and preliminary validation in Vietnam.

AIMS: Verbal autopsy (VA) has become an important tool in the past 20 years for determining cause of death in communities where there is no routine registration. In many cases, expert physicians have been used to interpret the VA findings and so assign individual causes of death. However, this is time consuming and not always repeatable. Other approaches such as algorithms and neural networks have been developed in some settings. This paper aims to develop a method that is simple, reliable and consistent, which could represent an advance in VA interpretation. METHODS: This paper describes the development of a Bayesian probability model for VA interpretation as an attempt to find a better approach. This methodology and a preliminary implementation are described, with an evaluation based on VA material from rural Vietnam. RESULTS: The new model was tested against a series of 189 VA interviews from a rural community in Vietnam. Using this very basic model, over 70% of individual causes of death corresponded with those determined by two physicians increasing to over 80% if those cases ascribed to old age or as being indeterminate by the physicians were excluded. DISCUSSION: Although there is a clear need to improve the preliminary model and to test more extensively with larger and more varied datasets, these preliminary results suggest that there may be good potential in this probabilistic approach.

Autopsy↗

PubMedDate not supplied

Comparing medical costs by analyzing high-cost cases.

Most of the medical care expenses paid by an entire company are generated by a small percentage of employees. The most expensive employee may have costs 100 to 500 times as much as the typical employee. Instead of comparing average costs, it makes sense to investigate whether employees with unhealthy behaviors are more prone to extreme costs. This article describes methods of comparing the costs of health risk groups by examining the proportion of high-cost employees in each group. The article illustrates the methods using a health claims dataset that compares male smokers, ex-smokers, and nonsmokers.

Adolescent↗

PubMed2005

Propagation of population pharmacokinetic information using a Bayesian approach: comparison with meta-analysis.

We investigated the propagation of population pharmacokinetic information across clinical studies by applying Bayesian techniques. The aim was to summarize the population pharmacokinetic estimates of a study in appropriate statistical distributions in order to use them as Bayesian priors in consequent population pharmacokinetic analyses. Various data sets of simulated and real clinical data were fitted with WinBUGS, with and without informative priors. The posterior estimates of fittings with non-informative priors were used to build parametric informative priors and the whole procedure was carried on in a consecutive manner. The posterior distributions of the fittings with informative priors where compared to those of the meta-analysis fittings of the respective combinations of data sets. Good agreement was found, for the simulated and experimental datasets when the populations were exchangeable, with the posterior distribution from the fittings with the prior to be nearly identical to the ones estimated with meta-analysis. However, when populations were not exchangeble an alternative parametric form for the prior, the natural conjugate prior, had to be used in order to have consistent results. In conclusion, the results of a population pharmacokinetic analysis may be summarized in Bayesian prior distributions that can be used consecutively with other analyses. The procedure is an alternative to meta-analysis and gives comparable results. It has the advantage that it is faster than the meta-analysis, due to the large datasets used with the latter and can be performed when the data included in the prior are not actually available.

Administration, Oral↗

PubMed1990

Improvements in protein secondary structure prediction by an enhanced neural network.

Computational neural networks have recently been used to predict the mapping between protein sequence and secondary structure. They have proven adequate for determining the first-order dependence between these two sets, but have, until now, been unable to garner higher-order information that helps determine secondary structure. By adding neural network units that detect periodicities in the input sequence, we have modestly increased the secondary structure prediction accuracy. The use of tertiary structural class causes a marked increase in accuracy. The best case prediction was 79% for the class of all-alpha proteins. A scheme for employing neural networks to validate and refine structural hypotheses is proposed. The operational difficulties of applying a learning algorithm to a dataset where sequence heterogeneity is under-represented and where local and global effects are inadequately partitioned are discussed.

Artificial Intelligence↗

PubMed2003

Molestations by homosexual foster parents: newspaper accounts vs official records.

To assess whether a systematic tally of newspaper accounts reflect official foster-parent molestation a review of 6,444 news stories on Lexis-Nexis Academic Universe from 1989 through 2002 about child molestation yielded 33 stories involving foster parents. Of the 25 foster-parent perpetrators, at least 15 (60%) engaged in homosexuality. In Illinois 1997-2002, 92 (34%) of 270 foster- or adoptive-parent perpetrators who engaged in "substantiated" sexual abuse homosexually abused their charges. These findings suggest that the proportion of homosexual perpetrators in a systematic tally of newspaper stories is similar to the proportion of homosexual perpetrators in datasets from large entities and put in question the current policy of utilizing homosexuals as foster and adoptive parents.

Adolescent↗

PubMed2002

Congenital heart surgery nomenclature and database project. Update and proposed data harvest.

In 1998, the first report of the Society of Thoracic Surgery (STS) National Congenital Heart Surgery Database defined clinical features for 18 congenital heart disease categories, providing a significant amount of important information and pinpointing database strengths and weaknesses. Following this report, the STS Congenital Heart Surgery Committee, working with the European Association of Cardio-Thoracic Surgery and the European Congenital Heart Surgeons Foundation, initiated the International Congenital Heart Surgery and Nomenclature Database Project. To standardize nomenclature and reporting strategies and establish a foundation for an international congenital heart surgery database. The project's first report was published in the Annals of Thoracic Surgery in April 2000. The current report outlines modifications to the minimal dataset and diagnosis and procedure short lists.

Databases, Factual↗

PubMed2006

Improving data reliability using a non-compliance detection method versus using pharmacokinetic criteria.

Data from clinical trials present numerous problems for the data analyst. These include non-compliance with the prescribed dosing regimen and inaccurate recollection of dosing history by patients as well as mistakes in recording data. Several methods have been proposed to address these issues. One such technique by Lu et al. (Selecting reliable pharmacokinetic data for explanatory analyses of clinical trials in the presence of possible noncompliance. J. Pharmacokinet. Pharmacodyn. 28:343-362 (2001)) identifies occasions in pharmacokinetic (PK) data where the preceding dosing history is likely to be unreliable. We used this method, implemented in the software program NONMEM (beta) VI, to clean a dataset containing indinavir (IDV) plasma concentrations from HIV-1 infected patients. The data was also cleaned by inspection in Microsoft Excel using clinical PK criteria. A one-compartment model with first order absorption and elimination was fit to both sets of cleaned data. IDV population PK parameters obtained from these analyses were similar to those reported previously. It is established that IDV nephrotoxicity is related to high IDV exposure. However, no relationships were found between any PK parameters and nephrotoxicity in the "compliance cleaned" dataset. In the "PK cleaned" dataset, the oral clearance and apparent volume were lower by 9.1% and 6.6%, respectively in patients with any type of nephrotoxicity and the maximum IDV concentration (C(max)) was 12.1% higher. In patients suffering from nephrolithiasis in particular, C(max) was 15.5% higher. Accordingly, the use of the non-compliance detection method did not improve the reliability of our dataset over the usual method of applying clinical criteria. In fact, analyses on the compliance-cleaned dataset missed some exposure-toxicity relationships. Thus, automated methods must be tested rigorously with 'real life' datasets, used with caution, and always in conjunction with clinical reasoning to avoid overlooking a signal in noisy data.

Adult↗

PubMed2006

An improved calculation of the exergy of natural resources for exergetic life cycle assessment (ELCA).

The focus in environmental research is shifting from emission abatement to critical process analysis, including assessment of resource consumption. The exergy theory offers a thermodynamic methodology to account for the consumption of natural resources. However, exergy data on mineral resources available in the literature are inadequate to apply to exergetic life cycle analysis, due to incompleteness, inconsistencies, and a dated thermochemical basis. An uncertainty assessment of the data has to be performed as well. In this work, three recent thermochemical databases were applied to evaluate the chemical exergy of 85 elements and 73 minerals, 21 of which had not yet been quantified in the literature. The process required the choice of a new reference species for aluminum. Muscovite was selected, giving rise to a chemical exergy of 809.4 kJ/mol for aluminum. The theory proved to be robust for the exergy of chemical elements, as exergy values differing by 1.2% on average from most recent literature were found. On the contrary, the exergy values for minerals differed by factors up to 14 from literature values, due to the application of recent thermochemical values and consistently selected reference species. The consistent dataset of this work will enable straightforward resource intake evaluation through an exergetic life cycle assessment.

Aluminum↗

PubMed2003

The traps and pitfalls inherent in the correlation of changes in the fibre diffraction pattern of hair with breast cancer.

After a correlation between breast cancer and changes in the fibre x-ray diffraction of hair was first published, a number of groups reported their failure to reproduce this phenomenon. There is evidence that these failures resulted from either diffraction images of insufficient quality or analysis techniques unable to distinguish features resulting from the presence of breast cancer from those resulting from mechanical damage. Using an independent analysis of the same dataset reported by one of these unsuccessful groups, the author demonstrates some of the critical flaws inherent in this type of intensity-based analysis.

Breast Neoplasms↗

PubMed2005

Markov model recognition and classification of DNA/protein sequences within large text databases.

MOTIVATION: Short sequence patterns frequently define regions of biological interest (binding sites, immune epitopes, primers, etc.), yet a large fraction of this information exists only within the scientific literature and is thus difficult to locate via conventional means (e.g. keyword queries or manual searches). We describe herein a system to accurately identify and classify sequence patterns from within large corpora using an n-gram Markov model (MM). RESULTS: As expected, on test sets we found that identification of sequences with limited alphabets and/or regular structures such as nucleic acids (non-ambiguous) and peptide abbreviations (3-letter) was highly accurate, whereas classification of symbolic (1-letter) peptide strings with more complex alphabets was more problematic. The MM was used to analyze two very large, sequence-containing corpora: over 7.75 million Medline abstracts and 9000 full-text articles from Journal of Virology. Performance was benchmarked by comparing the results with Journal of Virology entries in two existing manually curated databases: VirOligo and the HLA Ligand Database. Performance estimates were 98 +/- 2% precision/84% recall for primer identification and classification and 67 +/- 6% precision/85% recall for peptide epitopes. We also find a dramatic difference between the amounts of sequence-related data reported in abstracts versus full text. Our results suggest that automated extraction and classification of sequence elements is a promising, low-cost means of sequence database curation and annotation. AVAILABILITY: MM routine and datasets are available upon request.

Abstracting and Indexing↗

PubMed2005

Introduction to stroke genomics.

Translation of the explosion in knowledge of acute ischemic stroke into satisfactory treatment regimens has yet to happen. At present tPA, intra-arterial prourokinase and low-molecular-weight heparin form the vanguard for therapeutic intervention, yet these treatments have a limited therapeutic window. Part of this expansion in understanding has been driven by the contribution of stroke genetics and genomics. However, despite the enormous preclinical and clinical information of receptors, enzymes, second messenger systems, and so forth, that are implicated in stroke pathophysiology, delivery of novel drug treatment has been slow. This introductory chapter discusses the multiple sources of clinical and preclinical genetic information. It will describe the importance of integrating expression information into multiple preclinical models with temporal and spatial roles in lesion pathology and, furthermore developing an understanding of function in the clinic before claiming a role in ischemic stroke. The goal of such a holistic integration of information is to increase the yield from current datasets of gene expression and ultimately to help expand the choice of treatment available to the physician and patient.

Animals↗

PubMed2005

Overview of scorpion toxins specific for Na+ channels and related peptides: biodiversity, structure-function relationships and evolution.

Scorpion venoms contain a large number of bioactive components. Several of the long-chain peptides were shown to be responsible for neurotoxic effects, due to their ability to recognize Na(+) channels and to cause impairment of channel functions. Here, we revisited the basic paradigms in the study of these peptides in the light of recent data concerning their structure-function relationships, their functional divergence and extant biodiversity. The reviewed topics include: the criteria for classification of long-chain peptides according to their function, and a revision of the state-of-the-art knowledge concerning the surface areas of contact of these peptides with known Na(+) channels. Additionally, we compiled a comprehensive list encompassing 191 different amino acid sequences from long-chain peptides purified from scorpion venoms. With this dataset, a phylogenetic tree was constructed and discussed taking into consideration their documented functional divergence. A critical view on problems associated with the study of these scorpion peptides is presented, drawing special attention to the points that need revision and to the subjects under intensive research at this moment, regarding scorpion toxins specific for Na(+) channels and the other related long-chain peptides recently described.

Amino Acid Sequence↗

PubMed1996

Robust Bayesian approaches for clinical trial monitoring.

The interim monitoring and final analysis of data arising from a clinical trial require an inferential method capable of convincing a broad group of potential consumers: doctors; patients; politicians; members of the media, and so on. While Bayesian methods offer a powerful and flexible analytic framework in this setting, this need to convince a diverse community necessitates a practical approach for studying and communicating the robustness of conclusions to the prior specification. In this paper we attempt to characterize the class of priors leading to a given decision (such as stopping the trial and rejecting the null hypothesis) conditional on the observed data. We evaluate the practicality and effectiveness of this procedure over a range of smoothness conditions on the prior class. First, we consider a non-parametric class of priors restricted only in that its elements must have certain prespecified quantiles. We then obtain more precise results by further restricting the prior class, first to a non-parametric class whose members are quasi-unimodal, then to a semi-parametric normal mixture class, and finally to the fully parametric normal family. We illustrate all of our comparisons with a dataset from an AIDS clinical trial that compared the effectiveness of the drug pyrimethamine and a placebo in preventing toxoplasmic encephalitis.

AIDS-Related Opportunistic Infections↗

PubMed2004

Modelling of discrete spatial variation in epidemiology with SAS using GLIMMIX.

SAS provides a macro GLIMMIX, which can be used for modelling of discrete spatial variation in epidemiological studies, where data are aggregated into small areas such as municipalities or postcode sectors. The purpose of these models is primary to examine to what extent unmeasured spatially correlated variables can explain the outcome of interest. Some necessary additional code is proposed for this macro implementing some of the most used models for analysing and exploring spatial variation, in for example Poisson and logistic regression: Gaussian intrinsic conditional autoregression and spatial multiple memberships models originated from multilevel models. The code is illustrated by analysing the well-known Scottish lip cancer dataset with GLIMMIX and the results are compared with a Markov chain Monte Carlo approach. The code gives epidemiologists and bio-statisticians an immediate tool for analysing discrete spatial models in a familiar statistical software package.

Biometry↗

PubMed2005

Metallic and organic contaminants in sediments of Sydney Harbour, Australia and vicinity-- a chemical dataset for evaluating sediment quality guidelines.

An internally consistent dataset comprising 103 surficial estuarine sediment samples were collected from Sydney Harbour, Australia and locations south of Sydney. This paper describes the chemical characteristics of the dataset and evaluates its suitability for use in evaluating biological effects-based sediment quality guidelines (SQGs). The sediments contained mixtures of chemicals, the most prevalent chemical classes being metals and polycyclic aromatic hydrocarbons, whereas sediments from coastal lakes/estuaries south of Sydney had low concentrations of contaminants. Maximum concentrations of the prevalent contaminants zinc, lead, copper and pyrene were 11,300, 1,420, 1,060 mg kg(-1) and 23,300 microg kg(-1), respectively. For the majority of samples, concentrations of individual chemicals exceeded most effects-based SQGs that have been adopted for use in Australia, implying occasional or frequent adverse biological effects are expected. Comparing mixtures of contaminants to ranges in numbers of SQGs exceeded and mean SQG quotients showed that most samples (57% to 68%) had contamination characteristics associated with moderate probabilities (30% to 52%) of acute toxicity, based on North American data. A smaller proportion of samples (15% to 17%) had contamination characteristics associated with high probabilities (74% to 85%) of toxicity. The wide range of chemicals and concentrations, associated with low, medium and high probabilities of toxicity, indicated that the dataset was suitable for future use in evaluating predictive abilities of SQGs. This is relevant, given the recent introduction of North American-derived SQGs for Australia.

Australia↗