Biomedical subjects

J Baranyi

Publications and source records attributed to J Baranyi.

At least 19 recordsLinked to original sources

PubMed2006

Use of optical density detection times to assess the effect of acetic acid on single-cell kinetics.

The growth of Listeria innocua at different acetic acid concentrations (0 to 2,000 ppm) was monitored by optical density measurements in a Bioscreen (Labsystems, Vantaa, Finland). The generated populations came from low inocula that were obtained by serial dilution. A new method to estimate both the growth rate and the lag time of single cells from the detection times (time to reach an optical density of 0.11) was developed. It assumes that the single-cell lag times follow a gamma distribution and takes into account the randomness of the inoculation level. (The initial cell number per well was assumed to follow a Poisson distribution.) In this way, relatively small numbers of replicates are sufficient to obtain a robust estimation of the distribution of single-cell lag times. The results were validated with plate count experiments. It was found that logarithms of both the growth rates and of population lag times increased linearly with the acetic acid concentration. The logarithm of the scale parameter of the gamma distribution of the single-cell lag times also increased linearly with the acetic acid concentration irrespective of the phase of the inoculum.

Acetic Acid↗

PubMed2006

Information systems in food safety management.

Information systems are concerned with data capture, storage, analysis and retrieval. In the context of food safety management they are vital to assist decision making in a short time frame, potentially allowing decisions to be made and practices to be actioned in real time. Databases with information on microorganisms pertinent to the identification of foodborne pathogens, response of microbial populations to the environment and characteristics of foods and processing conditions are the cornerstone of food safety management systems. Such databases find application in: Identifying pathogens in food at the genus or species level using applied systematics in automated ways. Identifying pathogens below the species level by molecular subtyping, an approach successfully applied in epidemiological investigations of foodborne disease and the basis for national surveillance programs. Predictive modelling software, such as the Pathogen Modeling Program and Growth Predictor (that took over the main functions of Food Micromodel) the raw data of which were combined as the genesis of an international web based searchable database (ComBase). Expert systems combining databases on microbial characteristics, food composition and processing information with the resulting "pattern match" indicating problems that may arise from changes in product formulation or processing conditions. Computer software packages to aid the practical application of HACCP and risk assessment and decision trees to bring logical sequences to establishing and modifying food safety management practices. In addition there are many other uses of information systems that benefit food safety more globally, including: Rapid dissemination of information on foodborne disease outbreaks via websites or list servers carrying commentary from many sources, including the press and interest groups, on the reasons for and consequences of foodborne disease incidents. Active surveillance networks allowing rapid dissemination of molecular subtyping information between public health agencies to detect foodborne outbreaks and limit the spread of human disease. Traceability of individual animals or crops from (or before) conception or germination to the consumer as an integral part of food supply chain management. Provision of high quality, online educational packages to food industry personnel otherwise precluded from access to such courses.

Consumer Product Safety↗

PubMed2005

Modelling the variability of lag times and the first generation times of single cells of E. coli.

A mathematical model combining deterministic and stochastic elements describes the growth and division of single cells. Its deterministic part is based on the model of Baranyi and Roberts [International Journal of Food Microbiology 23 (1994) 277] modelling the gradual adjustment of the cells to a new environment. The stochastic part assumes a random threshold size for the division of a single cell, which accounts for the variability of the individual generation times. Experimental results of the first division times of thousands of single cells using a microscopic flow system could be reproduced with this model, and it has the potential to be used to study the effects of different stress and environmental factors on the distribution of the lag and generation times of individual cells.

Cell Division↗

PubMed2005

Social instability in female rats: the relationship between stress-related and anxiety-like consequences.

It is generally believed that anxiety and depression develop in response to stressful events that chronically increase glucocorticoid production (which in turn affects various neurotransmitter systems). In contrast to depression, however, the relationship between chronic stress and anxiety is less clear, as anxiety patients often show normal glucocorticoid levels and respond normally to dexamethasone challenge. Here we report on the interaction between symptoms of chronic stress and anxiety in female rats by making use of the social instability model of anxiety. Subjects were exposed to alternating 24 h periods of isolation and moderate crowding for 14 days. Symptoms of chronic stress and anxiety-like behaviour in the social interaction test were evaluated on the 15th day, i.e. 1 day after the last crowding phase. Social instability resulted in decreased weight gain, and chronically elevated plasma glucocorticoid levels only in rats that showed high aggressiveness during the crowding phases. In contrast, anxiety-like behaviour was increased irrespective to crowding-related aggressiveness. Thus, the development of chronic stress symptoms and anxiety-like behaviour dissociated: the former was bound to crowding-induced aggressiveness (i.e. to a higher stress load), whereas the latter occurred also when such aggressiveness was low, and symptoms of chronic stress did not develop. This finding is consistent with human data, and suggests that stressful events lead to anxiety in both cases: when stressors do or do not lead to chronic stress responses. Studying the distinctive features of anxieties associated or not with chronic endocrine stress responses would enhance our understanding of this disorder.

Adaptation, Physiological↗

PubMed2004

Observing growth and division of large numbers of individual bacteria by image analysis.

We describe a method that enabled us to observe large numbers of individual bacterial cells during a long period of cell growth and proliferation. We designed a flow chamber in which the cells attached to a transparent solid surface. The flow chamber was mounted on a microscope equipped with a digital camera. The shear force of the flow removed the daughter cells, making it possible to monitor the consecutive divisions of a single cell. In this way, kinetic parameters and their distributions, as well as some physiological characteristics of the bacteria, could be analyzed based on more than 1,000 single-cell observations. The method which we developed enabled us to study the history effect on the distribution of the lag times of single cells.

Bacteriological Techniques↗

PubMed2003

Stress, social avoidance and anxiolytics: a potential model of stress-induced anxiety.

We investigated the social behavioural effects of a single exposure to either social defeat or electric shocks, using the recently developed social avoidance test in rats. The testing apparatus consisted of two connected chambers, one of which contained an unfamiliar male confined in a sub-chamber by a perforated Plexiglas wall. The subjects were placed in the empty chamber and, after 3 min of habituation, were allowed to explore the apparatus for 5 min. The latency, frequency and duration of visits made to the opponent-containing chamber were recorded. Both stressors reduced the exploration of the opponent-containing chamber for more than 5 days. The effects of electric shocks were not affected by housing conditions, whereas group housing protected rats from the long-term effects of defeat. In addition, the effects of social defeat in isolated rats lasted longer than the effects of electric shocks. These differences suggest that the two stressors have qualitatively different effects and may model different behavioural states in humans. In a second experiment, social avoidance induced by electric shocks was readily abolished by both chlordiazepoxide and buspirone. We suggest that the shock-induced social avoidance paradigm may become a useful model of stress-induced anxiety.

Animals↗

PubMed2001

The effect of inoculum size on the lag phase of Listeria monocytogenes.

The effect of inoculum size on population lag times of Listeria monocytogenes was investigated using the Bioscreen automated microtitre plate incubator and reader. Under optimum conditions, lag times were little affected by inoculum size and there was little variation between replicate inocula even at very low cell numbers. However, in media containing inhibitory concentrations of NaCl, both the mean lag time and variation between replicate inocula increased as the inoculum size became smaller. The variation in lag time of cells within a population was investigated in more detail by measuring the distribution of detection times from 64 replicate inocula containing only one or two cells capable of initiating growth. The variance of the lag time distribution increased with increasing salt concentration and was greater in exponential than in stationary phase inocula. The number of cells required to initiate growth increased from one cell under optimum conditions to 10(5) cells in medium with 1.8 M NaCl. The addition of spent medium from a stationary phase culture reduced the variance and decreased lag times. The ability to initiate growth under severe salt stress appears to depend on the presence of a resistant sub-fraction of the population, although high cell densities assist adaptation of those resistant cells to the unfavourable growth conditions by some unspecified medium conditioning effect. These results are relevant to the prediction of lag times and probability of growth from low numbers of stressed cells in food.

Adaptation, Physiological↗

PubMed2001

Measurements and predictions of growth for Listeria monocytogenes and Salmonella during fluctuating temperature II. Rapidly changing temperatures.

Growth of Listeria monocytogenes and Salmonella was examined during various rates of increase and decrease in temperature from and to the minimum for growth. Growth was little affected by even the most rapid changes and injury or lag was not observed. Subsequent investigations of growth during periods of rapid variation in temperature from and to temperatures below the growth minimum again had little effect and growth was satisfactorily predicted using the dynamic model of Baranyi and Roberts [Int. J. Food Microbiol. 23 (1994) 277] in conjunction with the data of Food Micromodel.

Colony Count, Microbial↗

PubMed2001

A parallel study on bacterial growth and inactivation.

Pure stochastic birth process models are used to establish the connection between the traditional food microbiology concept of bacterial lag period, before the exponential growth, and the distribution of the lag times of individual cells. In a parallel way, similar study is carried out on the connection between the "shoulder" period, before the exponential decay, and the distribution of the survival times of individual cells. Formulae are derived to calculate the parameters of the growth/survival curves from the distributions of the respective parameters of individual cells. It is shown that, in some aspects, analogy, in some aspects fundamental difference exists between growth and survival modelling.

Bacteria↗

PubMed2001

The effect of glucocorticoids on the anxiolytic efficacy of buspirone.

RATIONALE: The serotonergic system and the hypothalamus-hypophysis-adrenocortical axis reciprocally influence each other. Therefore, the interaction between stress and serotonergic anxiolytics should be of major concern for both laboratory investigations and clinical treatment. OBJECTIVES: We have studied the effects of the serotonergic anxiolytic buspirone in rats in which basal levels of glucocorticoids were low and stable, while acute stress reactions were inhibited or exogenously induced. METHODS: Rats were adrenalectomised. Subcutaneous corticosterone pellets maintained basal glucocorticoid concentrations while acute changes were mimicked by corticosterone injections. Anxiety was assessed by the social interaction test. Temporal changes were evaluated by submitting rats to the same manipulations three times at two-day intervals. RESULTS: Buspirone applied to animals with stable and low plasma glucocorticoid concentrations induced a dramatic increase in social interactions. A slight locomotor suppressive effect was also noticed. The effects of buspirone proved to be stable over time in these animals. Acute treatment with corticosterone doubled the locomotor suppressive effects of buspirone and reversed its anxiolytic effects: the buspirone-corticosterone combination was anxiogenic after the first application. During the second and third treatment, the impact of corticosterone on buspirone efficacy gradually decreased, but the combined treatment remained about half as effective in reducing anxiety as buspirone alone.

Adrenalectomy↗

PubMed2000

Predictions of growth for Listeria monocytogenes and Salmonella during fluctuating temperature.

We studied the predictive performance of a dynamic modelling approach, combined with predictions from the Food MicroModel software, applied to the growth of Listeria monocytogenes and Salmonella in pasteurised milk, chicken liver pâté and minced chicken, under constant as well as fluctuating temperatures. We found that, in general, the accuracy of a prediction under fluctuation temperature was similar to that under constant temperature. Generally, there was a good agreement between predictions and observations. However, the growth of Listeria monocytogenes in pasteurised milk was inhibited largely by the natural flora present.

Animals↗

PubMed2000

Predictive model for the growth of Yersinia enterocolitica under modified atmospheres.

A quadratic response surface model is presented to describe the maximum specific growth rate of Yersinia enterocolitica, at refrigeration temperatures, under modified atmospheres. The presence of CO2 affected mainly the lag phase of the organism. The length of the lag phase increased with higher levels of CO2 in the atmosphere, and this effect was more noticeable at low temperatures. The effect of oxygen was similar but less pronounced. The observed growth was slower with higher CO2. Oxygen also decreased the growth rate, but its effect was significant only when its proportion in the atmosphere was greater than about 40%. Model predictions were compared with growth rates obtained in sea food inoculated with Y. enterocolitica and packaged under modified atmospheres. Predictions were also checked to determine whether they were inside the strict interpolation region of the model.

Animals↗

PubMed1999

Validating and comparing predictive models.

The bias and accuracy factors introduced by Ross [Ross, T., 1996. Indices for performance evaluation of predictive models in food microbiology. J. Appl Bacteriol. 81, 501-508] for the evaluation of the performance of models in 'predictive food microbiology' are refined by basing the calculation of those measures on the mean square differences between predictions and observations. The use of the indices is extended by presenting formulae and methods which enable evaluation of the difference between alternative models for growth of an organism of interest over a domain of environmental factors. This is done by calculating the integral mean of the square differences between the models under investigation over the domain of the environmental variables common to those models, or a sub-region of it. The use of the techniques is exemplified by evaluating the difference between four published models for the growth rate of psychrotrophic pseudomonads.

Bias↗

PubMed1999

Predicting fungal growth: the effect of water activity on Penicillium roqueforti.

The effect of water activity on the colony growth of Penicillium roqueforti is studied by predictive modelling techniques. Measured colony diameter growth curves are fitted to estimate the growth rate and lag phase of the curves. The colony growth rate was modelled by a quadratic function of transformed water activity (a(w)) values, as suggested by Baranyi et al. (Food Microbiol. 10 (1993) 43-59). The lag time was modelled as a function of water activity, by means of the sum of a constant term and a hyperboloid function of a(w) raised to the second power. The lag-phase of Penicillium roqueforti was found insensitive to the water activity in the range of its higher (a(w) > 0.92) values.

Cheese↗

PubMed1999

Validating predictive models of food spoilage organisms.

The accuracy and bias of a predictive model for the maximum specific growth rate of Pseudomonas spp. were studied by means of percentage discrepancy and bias indicators. These were calculated for observations obtained both in laboratory media and in food. When independent pseudomonad data generated in broth were compared with model predictions, the error was smaller than in the case of food. The extent to which the food structure and composition of the microflora contribute to the overall error of the model was quantified.

Animals↗

PubMed1999

Estimating bacterial growth parameters by means of detection times.

We developed a new numerical method to estimate bacterial growth parameters by means of detection times generated by different initial counts. The observed detection times are subjected to a transformation involving the (unknown) maximum specific growth rate and the (known) ratios between the different inoculum sizes and the constant detectable level of counts. We present an analysis of variance (ANOVA) protocol based on a theoretical result according to which, if the specific rate used for the transformation is correct, the transformed values are scattered around the same mean irrespective of the original inoculum sizes. That mean, termed the physiological state of the inoculum, âlpha, and the maximum specific growth rate, mu, can be estimated by minimizing the variance ratio of the ANOVA procedure. The lag time of the population can be calculated as lambda = -ln âlpha/mu; i.e. the lag is inversely proportional to the maximum specific growth rate and depends on the initial physiological state of the population. The more accurately the cell number at the detection level is known, the better the estimate for the variance of the lag times of the individual cells.

Analysis of Variance↗

PubMed1998

Comparison of Stochastic and Deterministic Concepts of Bacterial Lag.

The shortcomings of the traditional deterministic approach to bacterial lag are exposed in this paper. A more precise, stochastic, formulation is put forward which takes account of the variation of the individual cell's lag time. Formulae are given to describe how the lag-distribution of the cells relates to the deterministic population lag commonly used as a practical measure of bacterial lag time.Copyright 1998 Academic Press Limited

Journal Article↗

PubMed1998

Predictive models as means to quantify the interactions of spoilage organisms.

The purpose of this paper is to quantify the interactions of some groups of spoilage organisms that can be usually found in refrigerated meat stored in air, such as: Enterobacteriaceae, Pseudomonas, Acinetobacter, Psychrobacter, Shewanella, Carnobacterium, Lactobacillus, Leuconostoc, Brochothrix and Kurthia spp. The growth of these organisms was studied in the range of temperature 2-11 degrees C and pH 5.2-6.4, which is characteristic of refrigerated meat. The main growth parameters (maximum specific growth rate and lag time) were modelled by multivariate quadratic polynomials of temperature and pH. The interactions of the organisms were analyzed by comparing their growth models obtained in isolation with those obtained in mixture. The difference between the models was quantified by statistical F-values which were used to measure how much the growth of an organism or group of organisms was affected by others and which of them dominated their joint growth.

Bacteria↗