Biomedical subjects

H M Davey

Publications and source records attributed to H M Davey.

8 recordsLinked to original sources

PubMed2003

Cancer patients' preferences for written prognostic information provided outside the clinical context.

Cancer patients' preferences for written prognostic information independent of the clinical context have not previously been investigated. This study aimed to assist a state cancer organisation to provide information to patients by assessing patients' understanding of statistical information; eliciting their preferences for framing, content and presentation; and assessing the acceptability of a card sort for obtaining preferences. With the exception of conditional and relative survival, initial difficulties in understanding statistical concepts were improved with a plain language explanation. Analysis of the interview transcripts revealed that participants generally supported the provision of written information about survival in booklets and on the Internet. They wanted positive, relevant and clear information. Participants said that the use of, and preferences for, this information would be affected by a patient's age, time since diagnosis, ability to cope with having cancer and the perceived credibility of the information source. They found the card sort acceptable, saying it made the assessment of understanding and selection of preferences easy. This study has identified two fundamental, and sometimes conflicting, factors underlying patients' preferences: the communication of hope and the need to understand information it has also identified patient characteristics thought to influence preferences. These factors and characteristics need to be taken into account when developing written prognostic information for patients.

Adaptation, Psychological↗

PubMed2000

Flow cytometric analysis of microorganisms.

The application of flow cytometry to microorganisms is as old as the technique itself, but it has historically been underexploited for microbial applications. This is now being reversed and microbiologists are ideally placed to benefit from recent technological advances. While earlier papers demonstrated the use of flow cytometry for studies of viability and taxonomy, recent developments in bioinformatics and reporter gene technologies are leading to novel applications in microbiology. Variants of green fluorescent protein have been used for the study of conditional microbial gene regulation in medically important host-pathogen interactions and fluorescence-activated cell sorting is being applied to the isolation of novel mutants in directed evolution studies. This paper reviews the reasons for the delay in the application of flow cytometry to microbial problems, the range of applications, and their limitations and considers the progress made in developing new strategies for use in microbiological investigations.

Bacteria↗

PubMed2000

Rapid analysis of high-dimensional bioprocesses using multivariate spectroscopies and advanced chemometrics.

There are an increasing number of instrumental methods for obtaining data from biochemical processes, many of which now provide information on many (indeed many hundreds) of variables simultaneously. The wealth of data that these methods provide, however, is useless without the means to extract the required information. As instruments advance, and the quantity of data produced increases, the fields of bioinformatics and chemometrics have consequently grown greatly in importance. The chemometric methods nowadays available are both powerful and dangerous, and there are many issues to be considered when using statistical analyses on data for which there are numerous measurements (which often exceed the number of samples). It is not difficult to carry out statistical analysis on multivariate data in such a way that the results appear much more impressive than they really are. The authors present some of the methods that we have developed and exploited in Aberystwyth for gathering highly multivariate data from bioprocesses, and some techniques of sound multivariate statistical analyses (and of related methods based on neural and evolutionary computing) which can ensure that the results will stand up to the most rigorous scrutiny.

Algorithms↗

PubMed1999

Variable selection and multivariate methods for the identification of microorganisms by flow cytometry.

BACKGROUND: When exploited fully, flow cytometry can be used to provide multiparametric data for each cell in the sample of interest. While this makes flow cytometry a powerful technique for discriminating between different cell types, the data can be difficult to interpret. Traditionally, dual-parameter plots are used to visualize flow cytometric data, and for a data set consisting of seven parameters, one should examine 21 of these plots. A more efficient method is to reduce the dimensionality of the data (e.g., using unsupervised methods such as principal components analysis) so that fewer graphs need to be examined, or to use supervised multivariate data analysis methods to give a prediction of the identity of the analyzed particles. MATERIALS AND METHODS: We collected multiparametric data sets for microbiological samples stained with six cocktails of fluorescent stains. Multivariate data analysis methods were explored as a means of microbial detection and identification. RESULTS: We show that while all cocktails and all methods gave good accuracy of predictions (>94%), careful selection of both the stains and the analysis method could improve this figure (to > 99% accuracy), even in a data set that was not used in the formation of the supervised multivariate calibration model. CONCLUSIONS: Flow cytometry provides a rapid method of obtaining multiparametric data for distinguishing between microorganisms. Multivariate data analysis methods have an important role to play in extracting the information from the data obtained. Artificial neural networks proved to be the most suitable method of data analysis.

Bacillus subtilis↗

PubMed1997

Fluorescent brighteners: novel stains for the flow cytometric analysis of microorganisms.

Flow cytometry is a rapid method for measuring the optical properties of individual cells. The technique has found great utility in the study of mammalian cells, but microbiological applications have been more limited. We here show that UV-excited fluorescent whitening agents, in particular Tinopal CBS-X, are effective stains for both vegetative microbial cells and for spores of Gram-positive bacteria. Pretreatment of samples with ethanol speeds the staining process. Under favourable conditions, Tinopal CBS-X may be used to discriminate among organisms, a fact that may be useful when screening for a target microorganism against a high biological background.

Bacillus subtilis↗

PubMed1996

Oscillatory, stochastic and chaotic growth rate fluctuations in permittistatically controlled yeast cultures.

We describe a continuous culture system related to the turbidostat, but using a feedback system based on biomass estimation from the dielectric permittivity of the cell suspension rather than its optical density. It is shown that this system provides an excellent method of maintaining a constant biomass level within a fermentor. The computer-controlled system was able to effect the essentially continuous registration of growth rate by monitoring the rate of medium addition via the time-dependent activity of the pump. At some biomass setpoints for aerobically grown cultures of baker's yeast substantial time-dependent fluctuations in the growth rate of the culture were thereby observed. At some biomass setpoints, however, or under anaerobic conditions, or when using a non-Crabtree yeast, the growth rate was constant, indicating that the fluctuations were inherent to the biological system and not simply a property of the fermentor and control system. A variety of time series analyses (Fourier transformations, Hurst and Lyapunov exponents, the determination of embedding dimension, and non-linear time series predictions based on the methodology of Sugihara and May) were used to demonstrate, for the first time, that as well as stochastic and periodic components these fluctuations exhibited deterministic chaos. 'Trivial predictors' were unable to give accurate predictions of the growth rate in these cultures. The growth rate fluctuations were studied further by means of offline measurements of changes in percentage viability, bud count, and in the external ethanol and glucose concentrations; these data and other evidence suggested that the growth rate fluctuations were closely linked to the primary respiro-fermentative metabolism of this organism. The identification of chaotic growth rates in cell cultures suggests that there may be novel methods for controlling the growth of such cultures.

Biomass↗

PubMed1996

Quantitative Analysis of the Physiological Heterogeneity within Starved Cultures of Micrococcus luteus by Flow Cytometry and Cell Sorting.

A high proportion of Micrococcus luteus cells in cultures which had been starved for 3 to 6 months lost the ability to grow and form colonies on agar plates but could be resuscitated from their dormancy by incubation in an appropriate liquid medium (A. S. Kaprelyants and D. B. Kell, Appl. Environ. Microbiol. 59:3187-3196, 1993). We used flow cytometry and cell sorting to study populations of bacteria that had been starved for 5 months. These cells could be stained by the fluorescent lipophilic cation rhodamine 123, but such staining was almost independent of metabolically generated energy in that it was not affected by uncouplers. Two populations could be distinguished, one with a lower degree of rhodamine fluorescence (a degree of fluorescence referred to as region A and containing approximately 80% of the cells) and one with a more elevated degree of fluorescence (region B, approximately 20% of the cells). Subsequent incubation of starved cells in fresh medium in the presence of the antibiotic chloramphenicol (to which M. luteus is sensitive) resulted in the transient appearance of cells actively accumulating rhodamine 123 (and fluorescing in region B) and of larger cells exhibiting a yet-greater degree of fluorescence (region C). These more fluorescent cells accounted for as much as 50% of the total population, under conditions in which the viable and total counts were constant. Thus, metabolic resuscitation of at least one-half of the cells takes place under conditions in which cryptic growth cannot play any role. Sorting experiments revealed that the great majority of the viable cells in the starved population are concentrated in regions B and C and that the extent of rhodamine staining under conditions of starvation therefore reflects the physiological state of the cells. Physical separation of these cells from cells in region A resulted in an increase (of approximately 25-fold) in the viability of cells in regions B and C and of the population as a whole. Resuscitation of dormant cells in a most-probable-number assay in the presence of supernatant taken from growing M. luteus revealed the resuscitation of cells from regions B and C but not from region A. It is suggested that initially dormant (resuscitable) cells are concentrated in regions B and C.

Journal Article↗

PubMed1996

Flow cytometry and cell sorting of heterogeneous microbial populations: the importance of single-cell analyses.

The most fundamental questions such as whether a cell is alive, in the sense of being able to divide or to form a colony, may sometimes be very hard to answer, since even axenic microbial cultures are extremely heterogeneous. Analyses that seek to correlate such things as viability, which is a property of an individual cell, with macroscopic measurements of culture variables such as ATP content, respiratory activity, and so on, must inevitably fail. It is therefore necessary to make physiological measurements on individual cells. Flow cytometry is such a technique, which allows one to analyze cells rapidly and individually and permits the quantitative analysis of microbial heterogeneity. It therefore offers many advantages over conventional measurements for both routine and more exploratory analyses of microbial properties. While the technique has been widely applied to the study of mammalian cells, is use in microbiology has until recently been much more limited, largely because of the smaller size of microbes and the consequently smaller optical signals obtainable from them. Since these technical barriers no longer hold, flow cytometry with appropriate stains has been used for the rapid discrimination and identification of microbial cells, for the rapid assessment of viability and of the heterogeneous distributions of a wealth of other more detailed physiological properties, for the analysis of antimicrobial drug-cell interactions, and for the isolation of high-yielding strains of biotechnological interest. Flow cytometric analyses provide an abundance of multivariate data, and special methods have been devised to exploit these. Ongoing advances mean that modern flow cytometers may now be used by nonspecialists to effect a renaissance in our understanding of microbial heterogeneity.

Bacteria↗