An improved model for the analysis of combined antimicrobials: a replacement for the Chou-Talalay combination index method.

AIMS: To rationalize confusion in the literature concerning the analysis of combined antimicrobials, specifically to see if the combination index (CI) method of analysis was as rigorous as claimed. METHODS AND RESULTS: Data from previous studies of the inhibition of Staphylococcus aureus by mixed antimicrobials were re-analysed using the CI method and a model which takes account of differences in the concentration exponents of individual antimicrobials. CONCLUSIONS: The Chou-Talalay combination index method for the analysis of combined antimicrobials was found to be valid only in the specific cases where concentration exponents were equal. In these cases, the CI method was found to be a function of the residuals of fitting the additive model to the observed data. Where concentration exponents were not equal, the CI method was invalid, whereas the additive model took these differences into account. SIGNIFICANCE AND IMPACT OF STUDY: The CI method can be replaced wholly by the additive model described. The model allows simple regression to be used to analyse whole data sets and provides simple graphical output.

Microbial growth parameters obtained from the analysis of time to detection data using a novel rearrangement of the Baranyi-Roberts model.

AIMS: To explore the predictions of a novel rearrangement of the Baranyi-Roberts model (BRM) with time to detection data obtained from optical density data of microbial growth. METHODS AND RESULTS: Growth of Escherichia coli and Salmonella Typhimurium under mild conditions of temperature (25-37°C), salt (0·086, 0·51 and 1·03 mol l(-1)) and pH (6·85-4·5) was examined using optical density. Time to detection (TTD) data were fitted to a model based on a rearrangement of the BRM. Observations showed compatibility with standard viable count studies and produced highly accurate specific growth rates and lag phase durations. At high salt and low pH, however, there was a substantial dependency on the initial inoculum for the observation of visible growth. At 30 and 37°C, with 1·03 mol l(-1) salt, and at pH <5·75, no visible growth was recorded for E. coli at initial inoculum levels below 10(7) CFU ml(-1). CONCLUSIONS: The rearranged BRM can be used directly with TTD data obtained from optical density measurements. SIGNIFICANCE AND IMPACT OF THE STUDY: A distinct advantage of the rearranged model is that it allows for a very simple interpretation of easily obtainable data using standard nonlinear regression. The rearranged model gives to TTD data the same modelling capability that the BRM gives to plate count data.

A new model for the effect of pH on microbial growth: an extension of the Gamma hypothesis.

AIMS: To investigate the appropriateness of the extended Lambert-Pearson model (ELPM) to model the effect of pH (as hydrogen and hydroxyl ions) over the whole biokinetic pH range in comparison with other available models. METHODS AND RESULTS: Data for the effect of pH on microbial growth were obtained from the literature or in-house. Data were examined using several models for pH. Models were compared using the residual mean of squares. Using the ELPM, pH was modelled as hydrogen ions and hydroxyl ions; hence, the model was monotonic in each. The ELPM was able to model data more successfully than the cardinal pH model (CPM) and other models in the majority of cases. CONCLUSIONS: Examining the effect of pH as hydrogen and hydroxyl ions has the advantage that the basic form of the ELPM can be retained as each is treated as a distinct antimicrobial effect. With the ELPM, each inhibitor is described by two parameters; from these parameters, the pH(min) , pH(opt) and pH(max) can be obtained. Furthermore, the idea of a dose response, absent from other models, becomes important. SIGNIFICANCE AND IMPACT OF THE STUDY: The CPM is an excellent model for certain situations - where there is a high degree of symmetry between the suboptimal pH and superoptimal pH response and where there are few data points available. The ELPM is more amenable to highly asymmetric behaviour, especially where plateaus of effect around the pH optimum are observed and where the number of data points is not restrictive.

Chromosome pairing within genomes in maize-Tripsacum hybrids.

When the ten chromosomes of maize were inserted inlto a polyploid (2n = 72) Tripsacum dactyloides background they formed up to five pairs at meiosis. Two plants that each contained 36 Tripsacum and 14 maize chromosomes were deprived from the F(1) of maize x Tripsacum. Chromo. somes of these plants frequently formed 25 bivalents, 18 between Tripsacum chromosomes and seven between maize chromosomes. Maize chromosomes could be distinguished from Tripsacum chromosomes on the basis of size. The withint-genome pairing is probably induced by the genetic background.

Modelling the effect of combined antimicrobials: A base model for multiple-hurdles.

Combining antimicrobials to reduce microbial growth and to combat the potential impact of antimicrobial resistance is an important subject both in foods and in pharmaceutics. Modelling of combined treatments designed to reduce or eliminate microbial contamination in foods (microbiological predictive modelling) has become commonplace. Two main reference models are used to analyse mixtures: the Bliss Independence and the Loewe reference models (LRM). By using optical density to analyse the growth of Aeromonas hydrophila, Cronobacter sakazakii and Escherichia coli in combined NaCl/NaCl (a mock combination experiment) and combined NaCl/KCl experiments, previous models for combined antimicrobials in foods, based on the Bliss approach, were shown to be inconsistent and that models based on the LRM more applicable. The LRM was shown, however, to be valid only in the specific cases where the concentration exponents of all components in a mixture were identical. This is assured for a mock combination experiment but not for a true mixture. This, essentially, invalidates the LRM as a general reference model. A new model, based on the LRM but allowing for mixed exponents, was used to analyse the combined inhibition data, and concluded that the NaCl/KCl system gave the additive effect expected from literature studies. This study suggests the need to revise current models used to analyse combined effects.

Development of resistance to chlorhexidine diacetate in Pseudomonas aeruginosa and the effect of a "residual" concentration.

Stable resistance in Pseudomonas aeruginosa NCIMB 10421 was obtained by step-wise exposure to gradually increasing concentrations of chlorhexidine diacetate (CHX). Repeated exposure to a proposed "residual" (sub-MIC) concentration of CHX also created stable resistance. Resistance was also developed by a single exposure to the "residual" concentration of CHX, but this was unstable. Similar experiments with Escherichia coli and CHX or cetylpyridinium chloride resulted in no significant increase in resistance. Antibiotic susceptibility profiles of the CHX-resistant P. aeruginosa cultures showed no cross-resistance, although some of the cultures were resistant to benzalkonium chloride.

Therapeutic efficacy of superactive charcoal in rats exposed to oral lethal doses of T-2 toxin.

Superactive charcoal, a compound known to complex with many toxins, was evaluated in this study for its effectiveness in preventing death in rats given an oral lethal dose of 8 mg/kg body weight of T-2 toxin. The median effective dose of oral superactive charcoal in preventing deaths in rats was 0.175 g/kg body weight. Concurrent use of cathartics, such as sorbitol, magnesium sulfate and sodium sulfate, to facilitate removal of the superactive charcoal:T-2 toxin complex formed in vivo did not enhance the survival rates of rats. One gram per kilogram body weight oral superactive charcoal enhanced survival times and survival rates in rats given 8 mg/kg of T-2 toxin as late as 3 hr after the T-2 toxin was administered. Some benefit in survival rate may be derived from giving the superactive charcoal as late as 5 hr after the T-2 toxin.

Viscoelastic adherence to corneal endothelium following phacoemulsification.

PURPOSE: To compare the residual adherence of viscoelastics to the corneal endothelium following phacoemulsification in an in vitro rabbit model. SETTING: Departments of Ophthalmology and Anatomy, Wayne State University, Detroit, Michigan, USA. METHODS: Three groups of 10 rabbit eyes each had a lensectomy via phacoemulsification using sodium hyaluronate (Amvisc Plus, Healon GV) or sodium chondroitin sulfate-sodium hyaluronate (Viscoat) as the viscoelastic agent. After phacoemulsification and cortex removal, a central corneal block was excised, cryofixed, and processed for light and electron microscopy. Viscoelastic thickness was determined by a calibrated reticule on the light microscope or a calibrated measuring program in the electron microscope. The nonparametric statistical test, Kruskal-Wallis, was used to compare viscoelastic groups. RESULTS: Median phacoemulsification time between viscoelastic agents was not significantly different. Median viscoelastic thicknesses were 13.0 microns for Amvisc Plus, 0.4 micron for Healon GV, and 375.0 microns for Viscoat. Each was significantly different from the others (Kruskal-Wallis, P < .001). CONCLUSIONS: Median thickness of Amvisc Plus, Healon GV, and Viscoat remaining adherent to the corneal endothelium after phacoemulsification was markedly different. Viscoat provided the greatest amount of viscoelastic material adjacent to the corneal endothelium.

Experimental neodymium:YAG laser damage to acrylic, poly(methyl methacrylate), and silicone intraocular lens materials.

PURPOSE: To compare neodymium:YAG (Nd:YAG) laser effects on acrylic, silicone, and poly(methyl methacrylate) (PMMA) intraocular lens (IOL) polymers. METHODS: Ten Nd:YAG laser exposures were produced in each of 6 implantation-quality acrylic (Alcon MA60BM), silicone (Staar AQ1016), and PMMA (Alcon MC60BM) IOLs under identical conditions. Each polymer type was irradiated at 6 power settings (0.3, 0.5, 1.0, 1.5, 2.0, and 3.0 mJ) and at 2 focal points (midpoint of lens optic and on the posterior surface to which a cellophane membrane was affixed). The linear extent of the damage was measured using light microscopy. Specimens exposed to 1.0 mJ were processed for scanning electron microscopy. RESULTS: The damage threshold (> or = 5 microns depth) was 0.3 mJ for silicone and 1.0 mJ for acrylic and PMMA IOLs. At the clinically relevant power levels, 1.0 to 2.0 mJ, the depth of damage in the acrylic polymer was 11.9 to 30.5 times less than the depth in the silicone polymer. Similarly, the depth of damage in the PMMA polymer was 5.4 to 52.6 times less than the depth in the silicone polymer. The morphologic pattern of damage in the silicone IOL showed a deep, irregularly configured trough with meandering tendrils. Acrylic IOL damage morphology consisted of an ameboid-shaped entry site without radiating fractures and mild posterior penetration. Poly(methyl methacrylate) IOL damage consisted of a shallow focal trough with radiating fractures. CONCLUSIONS: The silicone IOL polymer had the lowest threshold for laser-induced damage and greater linear extension of damage than the PMMA and acrylic IOL polymers. Poly(methyl methacrylate) and silicone polymers exhibited collateral damage or ejected particulates adjacent to the entry site, whereas the acrylic polymer showed a discrete locus of damage.

Growth curve prediction from optical density data.

A fundamental aspect of predictive microbiology is the shape of the microbial growth curve and many models are used to fit microbial count data, the modified Gompertz and Baranyi equation being two of the most widely used. Rapid, automated methods such as turbidimetry have been widely used to obtain growth parameters, but do not directly give the microbial growth curve. Optical density (OD) data can be used to obtain the specific growth rate and if used in conjunction with the known initial inocula, the maximum population data and knowledge of the microbial number at a predefined OD at a known time then all the information required for the reconstruction of a standard growth curve can be obtained. Using multiple initial inocula the times to detection (TTD) at a given standard OD were obtained from which the specific growth rate was calculated. The modified logistic, modified Gompertz, 3-phase linear, Baranyi and the classical logistic model (with or without lag) were fitted to the TTD data. In all cases the modified logistic and modified Gompertz failed to reproduce the observed linear plots of the log initial inocula against TTD using the known parameters (initial inoculum, MPD and growth rate). The 3 phase linear model (3PLM), Baranyi and classical logistic models fitted the observed data and were able to reproduce elements of the OD incubation-time curves. Using a calibration curve relating OD and microbial numbers, the Baranyi equation was able to reproduce OD data obtained for Listeria monocytogenes at 37 and 30°C as well as data on the effect of pH (range 7.05 to 3.46) at 30°C. The Baranyi model was found to be the most capable primary model of those examined (in the absence of lag it defaults to the classic logistic model). The results suggested that the modified logistic and the modified Gompertz models should not be used as Primary models for TTD data as they cannot reproduce the observed data.

Modelling of bacterial growth with shifts in temperature using automated methods with Listeria monocytogenes and Pseudomonas aeruginosa as examples.

Time to detection (TTD) measurements using turbidometry allow a straightforward method for the measurement of bacterial growth rates under isothermal conditions. Growth rate measurements were carried out for Listeria monocytogenes at 25, 30 and 37°C and for Pseudomonas aeruginosa over the temperature range 25 to 45°C. The classical three-parameter logistic model was rearranged to provide the theoretical foundation for the observed TTD. A model was subsequently developed for the analysis of TTD data from non-isothermal studies based on the Malthusian approximation of the logistic model. The model was able to predict the TTD for cultures of L. monocytogenes or P. aeruginosa undergoing simple temperature shunts (e.g. 25 to 37°C and vice versa), and for a multiple temperature shunt for L. monocytogenes (25-37-25-37°C and 37-25-37-25°C) over a period of 24h. In no case did a temperature shunt induce a lag.

Population distributions of minimum inhibitory concentration--increasing accuracy and utility.

AIMS: To generate continuous minimum inhibitory concentration (MIC) data that describes the discrete nature of experimentally derived population MIC data. METHODS AND RESULTS: A logistic model was fitted to experimentally derived MIC population cumulative distributions from clinical isolates of Haemophilus influenzae, Moraxella catarrhalis, Streptococcus pneumoniae and Staphylococcus aureus (European Committee on Antimicrobial Susceptibility Testing, BSAC and MYSTIC population susceptibility databases). From the model continuous distributions of population susceptibility were generated. The experimentally observed population distributions based on discrete MIC could be reproduced from this underlying continuous distribution. Monte Carlo (MC) simulation was used to confirm findings. Where the discrete experimental data contained few or no isolates with MIC greater or less than the antimicrobial concentration range tested, the true mean MIC was a factor of 0.707 times that normally reported and may be of little clinical significance. Where data contained isolates beyond the range of concentration used, the true MIC was dependent on the SD and the number of isolates and could be clinically significant. Subpopulations of differing susceptibilities could be modelled successfully using a modified logistic equation: this allows a more accurate examination of the data from these databases. CONCLUSIONS: The mean MIC and SD of population data currently reported are incorrect as the method of obtaining such parameters relies on normally distributed data which current MIC population data are not. SIGNIFICANCE AND IMPACT OF THE STUDY: Obtaining the distribution parameters from the underlying continuous distribution of MIC can be carried out using a simple logistic equation. MC simulation using these values allows easy visualization of the discrete data. The analyses of subpopulations within the data should increase the usefulness of horizontal studies.

A newly developed assay to study the minimum inhibitory concentration of Satureja spinosa essential oil.

AIMS: The minimum inhibitory concentration (MIC) of Satureja spinosa essential oil against Staphylococcus aureus, Escherichia coli O157:H7, Listeria monocytogenes, Salmonella enterica, Salmonella serovar Enteritidis PT4 and Bacillus cereus was comparatively assessed with an established optical density method as well as a novel impedimetric method. METHODS AND RESULTS: The impedimetric analysis takes into account information of microbial growth, such as detection time, maximum conductance, and slope of the conductance curve. For each pathogen two levels of inoculation were studied, a high (10(5) CFU ml(-1)) and a low level (10(2) CFU ml(-1)). Non-linear regression analysis was used to fit the data using a modification of a previously published model, from which a more exact value can be obtained for the MIC. Both methods gave similar MICs as shown by t-test statistical analysis. Salm. Enteritidis seems to be the least sensitive to the action of S. spinosa essential oil followed by L. monocytogenes, E. coli, B.cereus and Staph. aureus. The MICs of low inoculum were lower than that of high inoculum. CONCLUSIONS: The new impedimetric assay of MIC of essential oils can be considered a reliable rapid method for screening antimicrobial effectiveness of natural additives. SIGNIFICANCE AND IMPACT OF THE STUDY: Determination of the minimum inhibitory concentration of an essential oil with the simple conductance technique and further study of the mode of action of its components is a good combination for obtaining additional knowledge for industrial application of such natural additives.

Susceptibility testing: inoculum size dependency of inhibition using the Colworth MIC technique.

The minimum inhibitory concentration, MIC, is an accepted and well used criterion for measuring the susceptibility of organisms to inhibitors. Many factors influence the MIC value obtained, including temperature, inoculum size and type of organism. A modification of the method developed in this laboratory to obtain inhibition profiles of antimicrobials was used to examine the effect of inoculum size on the degree of inhibition observed with respect to inhibitor concentration. The data obtained enabled the production of an empirical model of inhibition, based on a Gompertz function, relating the level of growth observed to both the inoculum size and concentration of the inhibitor. The inoculum size dependencies of phenethyl alcohol, phenoxyethanol, p-chloro-m-cresol, trichloro-phenol, thymol and dodecyltrimethylammmonium bromide against Staphylococcus aureus were obtained.

Monitoring local food security and coping strategies: lessons from information collection and analysis in Mopti, Mali.

Save the Children Fund (UK) established a local food security monitoring project in the Mopti region of Mali, which was operational between 1987 and 1993. This article describes some of the lessons learnt from this experience of monitoring food security and coping strategies. It illustrates how coping strategies can be an important element in tracking vulnerability in the Sahel, but that interpretation is complex and there are limitations to their use. Secondly, consideration must be given to the institutional context in which information systems are set up. Information providers must be linked institutionally to response mechanisms, to ensure that data are fed systematically into the design, implementation and monitoring of appropriate response.

Advances in disinfection testing and modelling.

AIMS: To develop a set of kinetic equations which more ably describe the disinfection process. METHODS AND RESULTS: A group of functions, the fat equations, based on the model used for the quantification of microbial inhibition, was produced. These functions introduce a limit to the numbers of micro-organisms capable of being disinfected. These new expressions were shown to be more general forms of currently-used (e.g. log-linear) disinfection models, and accommodate the lags and/or tails of non-linear log-survivor--time plots. An advance in the experimental procedures used to obtain disinfection data, using an optical density technique, was developed concomitantly. CONCLUSION: The methods of analyses (experimental and modelling) allow the researcher to examine, more ably, five-minute disinfection (or specific time disinfection tests) as well as the more important disinfection rate analyses. SIGNIFICANCE AND IMPACT OF THE STUDY: The fat equations are an improvement over commonly-used rate models of disinfection, which are shown to be special cases of these equations. This raises the question as to whether our current understanding of the kinetic basis of disinfection requires revision.

Comparative analysis of antibiotic and antimicrobial biocide susceptibility data in clinical isolates of methicillin-sensitive Staphylococcus aureus, methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa between 1989 and 2000.

AIMS: To analyse population minimum inhibitory concentrations (MICs) data from clinical strains of Staphylococcus aureus and Pseudomonas aeruginosa for changes over a 10-year period and to look for correlations between the antimicrobials tested. METHODS AND RESULTS: Data from the MIC study of 256 clinical isolates of Staph. aureus [169 methicillin-sensitive Staph. aureus (MSSA), 87 methicillin-resistant Staph. aureus (MRSA)] and 111 clinical isolates of Ps. aeruginosa against eight antimicrobial biocides and several clinically relevant antibiotics was analysed using anova, Spearman-Rho correlation and principal component analysis. Comparisons suggest that alterations in the mean susceptibility of Staph. aureus to antimicrobial biocides have occurred between 1989 and 2000, but that these changes were mirrored in MSSA and MRSA suggests that methicillin resistance has little to do with these changes. Between 1989 and 2000 a sub-population of MRSA has acquired a higher resistance to biocides, but this has not altered the antibiotic susceptibility of that group. In both Staph. aureus and Ps. aeruginosa several correlations (both positive and negative) between antibiotics and antimicrobial biocides were found. CONCLUSIONS: From the analyses of these clinical isolates it is very difficult to support a hypothesis that increased biocide resistance is a cause of increased antibiotic resistance either in Staph. aureus or in Ps. aeruginosa. SIGNIFICANCE AND IMPACT OF THE STUDY: The observation of negative correlations between antibiotics and biocides may be a useful reason for the continued use of biocides promoting hygiene in the hospital environment.