Biomedical subjects

Maria G Corradini

Publications and source records attributed to Maria G Corradini.

7 recordsLinked to original sources

PubMed2006

An expanded Fermi solution for microbial risk assessment.

'Fermi solution' refers to an estimate of a quantity of interest derived from a sequence of guesses about factors of which detailed knowledge is unavailable. When one makes such guesses, it is unlikely that the large majority of them will be either too high or too low. Most probably, some of the overestimates will be offset by some of the underestimates, and the final result will be often close to the correct value. The method has been popularized as recreational physics but it has also been applied in risk assessment, where the factors involved, but not their exact magnitudes, are known. The concept has potential application in certain types of food poisoning risk assessments, and in estimating the number victims of a bioterrorist attack on the food or water supply, where some guessing is inevitable because of the absence of accurate relevant data. We consider a version of the method in which ranges instead of single values are entered as the factors' estimates. For simplicity, the risk to be assessed is taken to be the product of the factors, and their true values are regarded as being uniformly distributed over their respective ranges. The risk itself is therefore construed as a random variable with a probability distribution whose parameters are explicitly determined by the individual factors' ranges and which can often be approximated by a lognormal distribution. The mode of this lognormal distribution is taken to be the "best guess" of the risk, and a credible interval is constructed with a specified level of "confidence". The best guess and credible interval are shown to be robust against small perturbations of the ranges. Thus, even if the ranges are misspecified to some degree, assessments based on the best guess or credible interval will not be substantially altered. This can help to achieve consensus among assessors in situations where very little hard knowledge exists. The calculation procedure has been automated in software that has been made freely available over the Internet. The concept is demonstrated with two hypothetical problems: predicting the number of persons who would come down with acute food poisoning after consuming a contaminated dish, and estimating the number of daily salmonellosis cases in a large metropolitan area.

Confidence Intervals↗

PubMed2006

Properties of low moisture composite materials consisting of oil droplets dispersed in a protein-carbohydrate-glycerol matrix: effect of continuous phase composition.

The influence of continuous phase composition on the properties of low moisture (<3% water) composite materials consisting of oil droplets dispersed in a protein-carbohydrate-glycerol matrix was investigated. These composites were produced by blending canola oil (62.3%), whey protein concentrate (1.7%, WPC), and corn syrup and glycerol together (36.0% combined) using a high speed mixer equipped with a whisk. The polyol composition was varied by changing the ratio of corn syrup to glycerol in the system while keeping the total concentration of these two polyol components constant. Some composites were analyzed directly after preparation ("unbaked"), while others were analyzed after heating at 176 degrees C for 10 min to simulate baking of a food product ("baked"). The "lightness" of the composites was greater before baking (higher L value), but the color intensity of the composites was greater after baking (higher b value), which was attributed to Maillard browning reactions. The brownness of the baked composites increased with increasing corn syrup concentration, which was attributed to Maillard browning reactions. Squeezing flow viscometry indicated that the consistency and yield stress of the composites increased with baking, which was attributed to whey protein unfolding and aggregation. These rheological parameters also increased with increasing corn syrup concentration, which was attributed to its influence on the continuous phase rheology and on the interactions between the whey proteins. This study shows that the continuous phase composition and thermal history of low moisture composite materials have a large impact on their final physicochemical properties.

Carbohydrates↗

PubMed2006

On modeling and simulating transitions between microbial growth and inactivation or vice versa.

Resumed growth of the survivors of a heat or chemical treatment after cooling or a disinfectant dissipation is not an uncommon phenomenon. Similarly, the inverse, the onset of mortality in a growing microbial population as a result of exposure to increasing temperature or concentration of an antimicrobial agent, is also a familiar scenario. Provided that in either regime, the organism has no time to adapt biologically, the continuous transition from growth to inactivation or vice versa can be simulated with conventional growth and inactivation models, whose rate constant is allowed to change sign. Where both the growth and inactivation follow first-order kinetics, the sign change has no effect on the model equation's solutions. The same applies when the growth and inactivation patterns are described by a rate model, like the differential logistic equation or its various variants. However, determination of such models' coefficients from experimental isothermal growth and inactivation data can be difficult for technical reasons, unless the model can be integrated analytically. If not, or when the model itself is unknown a priori, then the rate equation would have to be derived from the fit of empirical models like the Weibull, modified versions of the logistic function and the like. But this may create a new kind of problem as a result of that the log and certain power operations cannot be used for negative numbers. For certain models at least, the problem can be solved through modification of the procedure by which the rate equation is solved numerically. This is demonstrated in simulated transitions between growth and inactivation and between inactivation and growth based on the log linear and Weibullian-power law models and three logistic patterns based on a shifted logistic function, the Baranyi-Roberts model and a shifted arctan model.

Bacteria↗

PubMed2006

Linear and non-linear kinetics in the synthesis and degradation of acrylamide in foods and model systems.

Isothermal acrylamide formation in foods and asparagine-glucose model systems has ubiquitous features. On a time scale of about 60 min, at temperatures in the approximate range of 120-160 degrees C, the acrylamide concentration-time curve has a characteristic sigmoid shape whose asymptotic level and steepness increases with temperature while the time that corresponds to the inflection point decreases. In the approximate range of 160-200 degrees C, the curve has a clear peak, whose onset, height, width and degree of asymmetry depend on the system's composition and temperature. The synthesis-degradation of acrylamide in model systems has been recently described by traditional kinetic models. They account for the intermediate stages of the process and the fate of reactants involved at different levels of scrutiny. The resulting models have 2-6 rate constants, accounting for both the generation and elimination of the acrylamide. Their temperature dependence has been assumed to obey the Arrhenius equation, i.e., each step in the reaction was considered as having a fixed energy of activation. A proposed alternative is constructing the concentration curve by superimposing a Fermian decay term on a logistic growth function. The resulting model, which is not unique, has five parameters: a hypothetical uninterrupted generation-level, two steepness parameters; of the concentration climbs and fall and two time characteristics; of the acrylamide synthesis and elimination. According to this model, peak concentration is observed only when the two time constants are comparable. The peak's shape and height are determined by the gap between the two time constants and the relative magnitudes of the two "rate" parameters. The concept can be extended to create models of non-isothermal acrylamide formation. The basic assumption, which is yet to be verified experimentally, is that the momentary rate of the acrylamide synthesis or degradation is the isothermal rate at the momentary temperature, at a time that corresponds to its momentary concentration. The theoretical capabilities of a model of this kind are demonstrated with computer simulations. If the described model is correct, then by controlling temperature history, it is possible to reduce the acrylamide while still accomplishing much of the desirable effects of a heat process.

Acrylamide↗

PubMed2005

Modeling and predicting non-isothermal microbial growth using general purpose software.

Published experimental isothermal growth curves of Clostridium perfringens cells in ground ham were fitted with a modified three-parameter version of the logistic equation as a primary model and the temperature dependence of the three parameters by ad hoc empirical secondary models. These were used to predict the organism's non-isothermal growth curves under three different cooling regimes. The assumption has been that the organism's instantaneous (or momentary) non-isothermal growth rate is the isothermal rate at the given temperature at a time that corresponds to its instantaneous population size. This could be translated into a differential rate model equation, whose coefficients are constructed from terms that reflect the changing growth parameters with temperature and hence with time. The continuous rate equation, however, can be solved incrementally by a numerical procedure that can be implemented in similar purpose software like Microsoft Excel(R). In all three cases, there was good agreement between the growth curves predicted by the model and those found experimentally. This demonstrated that the procedure can be used to generate growth curves under complicated thermal histories that may include regular and irregular temperature oscillations.

Animals↗

PubMed2004

Statistical analysis of the fluctuating counts of fecal bacteria in the water of Lake Kinneret.

Counts of E. coli, Enteroccoci and fecal coliforms in four sites around Lake Kinneret (The Sea of Galilee), collected every 2-4 weeks for about 5 years during 1995-2002 showed irregular fluctuations punctuated by aperiodic outbursts of variable magnitude. Because of the haphazard nature of fecal contamination and large intervals between successive counts, these patterns were described by probabilistic models, based on the truncated Laplace or Extreme Value distribution. Their applicability was tested by comparing the predicted frequencies of counts exceeding different levels calculated from the first half of each record with those actually observed in its second half. Despite the records imperfections and minor violations of the underlying models' assumptions, there was a reasonable agreement between the estimated and actual frequencies. This demonstrated that it is possible to translate the irregular fluctuation pattern into a set of probabilities of future high counts. In principle, such probabilities can be used to quantify the water's fecal contamination pattern and as a tool to assess the efficacy of preventive measures to reduce it.

Enterobacteriaceae↗

PubMed2004

Demonstration of the applicability of the Weibull-log-logistic survival model to the isothermal and nonisothermal inactivation of Escherichia coli K-12 MG1655.

Published isothermal semilogarithmic survival curves of Escherichia coli K-12 MG1655, in the range of 49.8 to 60.6 degrees C, all had noticeable downward concavity. They could be described by the model log S(t) = -b(T)t n, where S(t) = N(t)/N0, N(t) and N0 being the momentary and initial number of organisms, respectively; b(T) is a temperature-dependent rate parameter; and n is a constant found to be about 1.5. The temperature dependence of b(T) could be described by the log-logistic model, b(T) = ln[1 + exp[k(T - Tc)]], which had an almost perfect fit, with k = 0.88 degrees C(-1) and Tc = 60.5 degrees C. The constants, n, k, and Tc were considered the organism's survival parameters in the particular medium. They were incorporated into a rate equation on the assumption that in nonisothermal heating, the momentary inactivation rate is the isothermal rate at the momentary temperature at a time that corresponds to the momentary survival ratio. This model's estimates matched the actual survival curves obtained in the same work under two different nonisothermal heating profiles, lending support to the notion that the Weibull-log-logistic model combination can be used not only to describe isothermal inactivation mathematically, but also to predict survival patterns under nonisothermal conditions.

Colony Count, Microbial↗