Mutant prevention concentrations of ciprofloxacin and enrofloxacin for Salmonella enterica

Objectives: To determine the mutant prevention concentrations (MPCs) of ciprofloxacin and enrofloxacin against four strains of Salmonella enterica serovar Enteritidis and four strains of S. Typhimurium including one fully susceptible, one multiply resistant (MAR), one GyrA mutant and one GyrA/MAR mutant. Further, to examine mutants arising after exposure to sub-MPC concentrations of the antibiotics for susceptibility to ciprofloxacin and enrofloxacin, and cyclohexane tolerance. Methods: MICs were determined using the agar dilution method of the BSAC. The MPC was recorded as the lowest concentration of antibiotic to inhibit growth from an inoculum of 10(10) cfu. Results: The MPCs and resulting MPC/MIC ratios of enrofloxacin were generally two- to four-fold higher than for ciprofloxacin. At 24 h for both antibiotics, MPCs were lowest for the fully susceptible strains (0.25-0.5 mg/L), similar for the MAR (1-4 mg/L) and GyrA (2-4 mg/L) mutants and highest for the GyrA/MAR mutants (1-8 mg/L). MPC/MIC ratios at 24 h were 2-16 for all strains except those for the MAR strains without mutation in gyrA where the ratios were 8-64. Conclusions: The ability to eradicate Salmonella in vivo depends on many factors such as antibiotic susceptibility of the strain, dose and route of administration. It is suggested that these MPC values will be useful when considering dosing strategies. In view of the high MPC/MIC ratio, MAR strains with wild-type gyrA, although susceptible to ciprofloxacin (MICs 0.06-0.13 mg/L), may give rise to treatment failures.

Statistical inference of OH concentrations and air mass dilution rates from successive observations of non-methane hydrocarbons in single air masses

Bayesian inference has been used to determine rigorous estimates of hydroxyl radical concentrations () and air mass dilution rates (K) averaged following air masses between linked observations of nonmethane hydrocarbons (NMHCs) spanning the North Atlantic during the Intercontinental Transport and Chemical Transformation (ITCT)-Lagrangian-2K4 experiment. The Bayesian technique obtains a refined (posterior) distribution of a parameter given data related to the parameter through a model and prior beliefs about the parameter distribution. Here, the model describes hydrocarbon loss through OH reaction and mixing with a background concentration at rate K. The Lagrangian experiment provides direct observations of hydrocarbons at two time points, removing assumptions regarding composition or sources upstream of a single observation. The estimates are sharpened by using many hydrocarbons with different reactivities and accounting for their variability and measurement uncertainty. A novel technique is used to construct prior background distributions of many species, described by variation of a single parameter . This exploits the high correlation of species, related by the first principal component of many NMHC samples. The Bayesian method obtains posterior estimates of , K and following each air mass. Median values are typically between 0.5 and 2.0 × 106 molecules cm−3, but are elevated to between 2.5 and 3.5 × 106 molecules cm−3, in low-level pollution. A comparison of estimates from absolute NMHC concentrations and NMHC ratios assuming zero background (the “photochemical clock” method) shows similar distributions but reveals systematic high bias in the estimates from ratios. Estimates of K are ∼0.1 day−1 but show more sensitivity to the prior distribution assumed.

Estimating numbers of infectious units from serial dilution assays

The paper concerns the design and analysis of serial dilution assays to estimate the infectivity of a sample of tissue when it is assumed that the sample contains a finite number of indivisible infectious units such that a subsample will be infectious if it contains one or more of these units. The aim of the study is to estimate the number of infectious units in the original sample. The standard approach to the analysis of data from such a study is based on the assumption of independence of aliquots both at the same dilution level and at different dilution levels, so that the numbers of infectious units in the aliquots follow independent Poisson distributions. An alternative approach is based on calculation of the expected value of the total number of samples tested that are not infectious. We derive the likelihood for the data on the basis of the discrete number of infectious units, enabling calculation of the maximum likelihood estimate and likelihood-based confidence intervals. We use the exact probabilities that are obtained to compare the maximum likelihood estimate with those given by the other methods in terms of bias and standard error and to compare the coverage of the confidence intervals. We show that the methods have very similar properties and conclude that for practical use the method that is based on the Poisson assumption is to be recommended, since it can be implemented by using standard statistical software. Finally we consider the design of serial dilution assays, concluding that it is important that neither the dilution factor nor the number of samples that remain untested should be too large.

Evaluation of an improved tracer method to monitor cheese curd syneresis at varying milk fat levels in a cheese vat

Previous studies have reported that cheese curd syneresis kinetics can be monitored by dilution of chemical tracers, such as Blue Dextran, in whey. The objective of this study was to evaluate an improved tracer method to monitor whey volumes expelled over time during syneresis. Two experiments with different ranges of milk fat (0-5% and 2.3-3.5%) were carried out in an 11 L double-O laboratory scale cheese vat. Tracer was added to the curd-whey mixture during the cutting phase of cheese making and samples were taken at 10 min intervals up to 75 min after cutting. The volume of whey expelled was measured gravimetrically and the dilution of tracer in the whey was measured by absorbance at 620 nm. The volumes of whey expelled were significantly reduced at higher milk fat levels. Whey yield was predicted with a SEP ranging from 3.2 to 6.3 g whey/100 mL of milk and a CV ranging from 2.03 to 2.7% at different milk fat levels.