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Death Time (death + time)
Selected AbstractsTHERMAL DEATH TIMES OF ESCHERICHIA COLI IN YOUNG COCONUT ENDOSPERM BEVERAGEJOURNAL OF FOOD PROCESSING AND PRESERVATION, Issue 2009ALONZO A. GABRIEL ABSTRACT The decimal reduction times (D values) of Escherichia coli (American Type Culture Collection 25922) were established in a young coconut endosperm beverage, a famous local drink in the Philippines and in many tropical countries. Artificially inoculated cells were heated to 60, 70 and 80C at various heating times prior to survivor enumeration by surface plating onto pre-solidified Eosine Methylene Blue Agar. Results showed that the surviving populations significantly (P < 0.05) decreased with increasing exposure time and temperature. The calculated D values ranged from 0.26 ± 0.01 to 0.56 ± 0.08 min. Validation of the results by establishing the thermal resistance of other E. coli isolates in the coconut beverage medium was recommended. PRACTICAL APPLICATION The study established the thermal inactivation rates of Escherichia coli (American Type Culture Collection 25922) in a young coconut endosperm beverage medium in various heating temperatures. The results obtained from this study may be used in the calculations of appropriate thermal process schedules for the test beverage against the test organism. [source] EFFECT OF HIGH-PRESSURE TREATMENT OF MILK ON LIPASE AND ,-GLUTAMYL TRANSFERASE ACTIVITYJOURNAL OF FOOD BIOCHEMISTRY, Issue 6 2004P. K. PANDEY ABSTRACT High-pressure (HP) treatment (0,180 min at 300,400 MPa) was applied to milk to evaluate the pressure effects on the activities of lipoprotein lipase and ,-glutamyl transferase. Short time pressure exposure resulted in some enhancement in the activity of both enzymes, and for lipase, there was no inactivation during the entire pressure hold time (up to 100 min). With ,-glutamyl transferase, the extent of enhancement in activity was pressure level dependent, with lower pressure resulting in a greater enhancement. Furthermore, longer pressure treatment times resulted in inactivation of ,-glutamyl transferase, following a first order kinetic model. The pressure sensitivity of the inactivation parameters (k and D -values) for ,-glutamyl transferase was adequately described by the pressure death time and Arrhenius models with a zpof 543 MPa and an associated volume of activation, ,V,, of ,3.28 × 10,8 m3/mole. [source] Growth and Survival of Escherichia coli O157:H7 in Different Types of Milk Stored at 4 °C or 20 °CJOURNAL OF FOOD SCIENCE, Issue 8 2003Y. Mamani ABSTRACT: Samples of ultra heat-treated (UHT) milk (whole, semiskimmed, and skimmed milk, whole milk with cinnamon and lemon flavors, and semiskimmed milk with cocoa) were collected. Growth of E. coli O157:H7 was detected in whole milk at 4 °C (generation time 0.89 d) and in all milks at 20 °C during the first 24 h. Growth of nonpathogenice. coli was detected in milk samples without flavors during the same period of time. The fastest death time of E. coli O157:H7 was detected in whole milk with cinnamon and lemon at 4 °C (,1.35 d) The nonpathogenic strain showed the fastest death time in skimmed milk at 20 °C. [source] Joint Modeling for Cognitive Trajectory and Risk of Dementia in the Presence of DeathBIOMETRICS, Issue 1 2010Binbing Yu Summary Dementia is characterized by accelerated cognitive decline before and after diagnosis as compared to normal aging. It has been known that cognitive impairment occurs long before the diagnosis of dementia. For individuals who develop dementia, it is important to determine the time when the rate of cognitive decline begins to accelerate and the subsequent gap time to dementia diagnosis. For normal aging individuals, it is also useful to understand the trajectory of cognitive function until their death. A Bayesian change-point model is proposed to fit the trajectory of cognitive function for individuals who develop dementia. In real life, people in older ages are subject to two competing risks, e.g., dementia and dementia-free death. Because the majority of people do not develop dementia, a mixture model is used for survival data with competing risks, which consists of dementia onset time after the change point of cognitive function decline for demented individuals and death time for nondemented individuals. The cognitive trajectories and the survival process are modeled jointly and the parameters are estimated using the Markov chain Monte Carlo method. Using data from the Honolulu Asia Aging Study, we show the trajectories of cognitive function and the effect of education, apolipoprotein E 4 genotype, and hypertension on cognitive decline and the risk of dementia. [source] Nonparametric Estimation in a Cure Model with Random Cure TimesBIOMETRICS, Issue 1 2001Rebecca A. Betensky Summary. Acute respiratory distress syndrome (ARDS) is a life-threatening acute condition that sometimes follows pneumonia or surgery. Patients who recover and leave the hospital are considered to have been cured at the time they leave the hospital. These data differ from typical data in which cure is a possibility: death times are not observed for patients who are cured and cure times are observed and vary among patients. Here we apply a competing risks model to these data and show it to be equivalent to a mixture model, the more common approach for cure data. Further, we derive an estimator for the variance of the cumulative incidence function from the competing risks model, and thus for the cure rate, based on elementary calculations. We compare our variance estimator to Gray's (1988, Annals of Statistics16, 1140,1154) estimator, which is based on counting process theory. We find our estimator to be slightly more accurate in small samples. We apply these results to data from an ARDS clinical trial. [source] | ||||||||||