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Harry M Marks

Publications and source records attributed to Harry M Marks.

8 recordsLinked to original sources
PubMed2006

Growth kinetics of Salmonella spp. pre- and post-thermal treatment.

This paper reports estimated growth kinetic parameters for a cocktail of stationary phase Salmonella serotypes, pre- and post-thermal inactivation treatment. Cells were grown in brain-heart infusion broth at 25 or 37 degrees Celsius and then destruction of the cells was quantified at 55 degrees Celsius using a submerged coil heating apparatus. The surviving cells (about 1-2 log(10) cfu/ml) were subsequently grown at 25 or 37 degrees Celsius. The results indicated that lag phase duration times for the post- heat treated cells increased at 25 and 37 degrees Celsius by about 6.2 h and at least 3 to 4 h, respectively, and thus the increases appear to be truly different. However, when considering the ratios of the lag phase duration times for post-treated to pre-treated cells, a significant difference was not found, where estimated ratios could exceed 4. Estimated exponential growth rates, EGR, were not affected by the treatment, where for 37 degrees Celsius, EGR was estimated to be 0.9 log(10) (cfu/ml)/h, and at 25 degrees Celsius, the EGR was estimated at 0.45 log(10) (cfu/ml)/h.

Colony Count, Microbial↗
PubMed2006

Overview and summary of the Food Safety and Inspection Service risk assessment for Salmonella enteritidis in shell eggs, October 2005.

In 1998, the United States Department of Agriculture's Food Safety and Inspection Service (FSIS) and the Food and Drug Administration completed a risk assessment that indicated multiple interventions along the farm-to-table chain were needed to reduce the risk of human illness from Salmonella Enteritidis in shell eggs. Based on newly available data and improved modeling techniques, FSIS completed an updated risk assessment to examine the effect of pasteurization and refrigeration on reducing human illnesses from S. Enteritidis in shell eggs. The risk assessment model was written in Visual Basic for Applications (Microsoft, Redmond, WA) and run using Monte Carlo methods. The model estimated that if all shell eggs produced in the United States were pasteurized for a 3-log10 reduction of S. Enteritidis, the annual number of illnesses from S. Enteritidis in eggs would decrease from approximately 130,000 to 40,000. Pasteurization for a 5-log10 reduction of S. Enteritidis was estimated to reduce the annual number of illnesses to 19,000. The model also estimated that if all eggs produced in the United States were stored and held at 7.2 degrees C within 12 hours of lay, the annual number of illnesses from S. Enteritidis in eggs would decrease from 130,000 to 28,000. As a result, rapid cooling and pasteurization of shell eggs were predicted to be highly effective mitigations for reducing illnesses from consumption of S. Enteritidis in shell eggs.

Animals↗
PubMed2003

Epidemiologists explain pellagra: gender, race, and political economy in the work of Edgar Sydenstricker.

Between 1900 and 1940, at least 100,000 individuals in the southern United States died of pellagra, a dietary deficiency disease. Although half of these pellagra victims were African-American and more than two-thirds were women, contemporary observers paid little attention to these gender and racial differences in their analyses of disease. This article reviews the classic epidemiological studies of Joseph Goldberger and Edgar Sydenstricker, who argued that pellagra was deeply rooted in the political economy of cotton monoculture in the South. The methods that Sydenstricker brought to epidemiology from early work on political economy obscured the role of gender inequalities in pellagra, and his focus on economic underdevelopment led him to ignore the prominent role of African-Americans as pellagra's principal victims. Research methods and traditions, no less than more overt ideologies, played a role in maintaining the subordinate social position of women and African-Americans in the southern United States.

Black People↗
PubMed2003

Growth and heat resistance kinetic variation among various isolates of Salmonella and its application to risk assessment.

The abilities of cells of a particular type of bacteria to leave lag phase and begin the process of dividing or surviving heat treatment can depend on the serotypes or strains of the bacteria. This article reports an investigation of serotype-specific differences in growth and heat resistance kinetics of clinical and food isolates of Salmonella. Growth kinetics at 19 degrees C and 37 degrees C were examined in brain heart infusion broth and heat resistance kinetics for 60 degrees C were examined in beef gravy using a submerged coil heating apparatus. Estimates of the parameters of the growth curves suggests a small between-serotype variance of the growth kinetics. However, for inactivation, the results suggest a significant between-serotype effect on the asymptotic D-values, with an estimated between-serotype CV of about 20%. In microbial risk assessment, predictive microbiology is used to estimate growth and inactivation of pathogens. Often the data used for estimating the growth or inactivation kinetics are based on measurements on a cocktail--a mixture of approximately equal proportions of several serotypes or strains of the pathogen being studied. The expected growth or inactivation rates derived from data using cocktails are biased, reflecting the characteristics of the fastest growing or most heat resistant serotype of the cocktail. In this article, an adjustment to decrease this possible bias in a risk assessment is offered. The article also presents discussion of the effect on estimating growth when stochastic assumptions are incorporated in the model. In particular, equations describing the variation of relative growth are derived, accounting for the stochastic variations of the division of cells. For small numbers of cells, the expected value of the relative growth is not an appropriate "representative" value for actual relative growths that might occur.

Animals↗
PubMed2003

Predictive thermal inactivation model for effects of temperature, sodium lactate, NaCl, and sodium pyrophosphate on Salmonella serotypes in ground beef.

Analyses of survival data of a mixture of Salmonella spp. at fixed temperatures between 55 degrees C (131 degrees F) and 71.1 degrees C (160 degrees F) in ground beef matrices containing concentrations of salt between 0 and 4.5%, concentrations of sodium pyrophosphate (SPP) between 0 and 0.5%, and concentrations of sodium lactate (NaL) between 0 and 4.5% indicated that heat resistance of Salmonella increases with increasing levels of SPP and salt, except that, for salt, for larger lethalities close to 6.5, the effect of salt was evident only at low temperatures (<64 degrees C). NaL did not seem to affect the heat resistance of Salmonella as much as the effects induced by the other variables studied. An omnibus model for predicting the lethality for given times and temperatures for ground beef matrices within the range studied was developed that reflects the convex survival curves that were observed. However, the standard errors of the predicted lethalities from this models are large, so consequently, a model, specific for predicting the times needed to obtained a lethality of 6.5 log(10), was developed, using estimated results of times derived from the individual survival curves. For the latter model, the coefficient of variation (CV) of predicted times range from about 6 to 25%. For example, at 60 degrees C, when increasing the concentration of salt from 0 to 4.5%, and assuming that the concentration of SPP is 0%, the time to reach a 6.5-log(10) relative reduction is predicted to increase from 20 min (CV = 11%) to 48 min (CV = 15%), a 2.4 factor (CV = 19%). At 71.1 degrees C (160 degrees F) the model predicts that more than 0.5 min is needed to achieve a 6.5-log(10) relative reduction.

Animals↗
PubMedDate not supplied

Discerning strain effects in microbial dose-response data.

In order to estimate the risk or probability of adverse events in risk assessment, it is necessary to identify the important variables that contribute to the risk and provide descriptions of distributions of these variables for well-defined populations. One component of modeling dose response that can create uncertainty is the inherent genetic variability among pathogenic bacteria. For many microbial risk assessments, the "default" assumption used for dose response does not account for strain or serotype variability in pathogenicity and virulence, other than perhaps, recognizing the existence of avirulent strains. However, an examination of data sets from human clinical trials in which Salmonella spp. and Campylobacter jejuni strains were administered reveals significant strain differences. This article discusses the evidence for strain variability and concludes that more biologically based alternatives are necessary to replace the default assumptions commonly used in microbial risk assessment, specifically regarding strain variability.

Campylobacter Infections↗