Search

Assuming that the targeted microorganism’s isothermal survival curves follow the Weibullian pattern, which describes a large number of microbial isothermal survival curves, a simple numerical algorithm was developed to calculate the momentary survival ratio during non-isothermal thermal processes. The algorithm is based on a mathematical expression derived from a non-isothermal survival rate model proposed in the literature. Simulations indicated that the proposed algorithm generated the same results as those obtained from other non-isothermal models found in the literature. However, compared to the published models, the proposed algorithm has two advantages. One is that the calculation speed is very fast because only simple algebraic operations are involved, and the other is that it can be programmed very easily in different computer languages and spreadsheets. In addition, the algorithm provides an effective way to estimate changes of microbial survival ratio with time from product temperatures that are either directly measured during thermal processing or predicted by proper heat transfer models. Thus, the algorithm can also be easily incorporated into control systems of commercial thermal process equipment.

Differential equations used to describe the original and modified Geeraerd models were, respectively, simplified into an explicit equation in which the integration of the specific inactivation rate with respect to time was numerically approximated using the Simpson's rule. The explicit numerical solutions were then used to simulate microbial survival curves and fit nonisothermal survival data for identifying model parameters in Microsoft Excel. The results showed that the explicit numerical solutions provided an easy way to accurately simulate microbial survival and estimate model parameters from nonisothermal survival data using the Geeraerd models.

The apparent position numerical solution (APNS) method, which is based on the solution of the heat transfer equation for a spherical geometry, is commonly used in thermal treatment calculations to accurately predict the temperature history of products in containers of arbitrary shapes. This is accomplished by finding the ‘apparent position’ within a sphere that represents the actual temperature profile at the slowest heating and cooling points of a canned food container of arbitrary geometry. The APNS method provides a good temperature prediction during the late heating sterilization stage of processes that have approximately constant heating temperatures or those that have heating temperatures experiencing small deviations. However, the agreement between the temperature predicted by the APNS method and the actual temperature of the product at a given location is not good in the initial stage of the process cooling phase. An equation able to calculate differences between the temperature at any location of a cylindrical container and that predicted by the APNS method was derived from the heat transfer equations governing the thermal process. By incorporating the calculated temperature differences into the APNS method, during the cooling phase, a better agreement between the actual and predicted temperatures was obtained for several process conditions.

Gluconobacter oxydans that produces the cellulose was isolated. In order to confirm the chemical features of cellulose, various spectrophtometeric analysis were carried out using electron microscopy, X-ray diffractogram, and CP/MAS13C NMR. The purified cellulose was found to be identical to that ofAcetobacter xylinum. For effective production of cellulose, the various carbon and nitrogen sources, mixture of calcium and magnesium ions, and biotin concentration were investigated in flask cultures. Among the various carbon sources, glucose and sucrose were found to be best for the production of cellulose, with maximum concentration of 2.41 g/L obtained when a mixture of 10 g/L of each glucose and sucrose were used. With regard to the nitrogen sources, when 20 g/L of yeast extract was used, the maximum concentration of bacterial cellulose was reached. The concentration of cellulose was increased with mixture of 2 mM of each Ca2+ and Mg2+. The optimum biotin concentration for the production of cellulose was in the range of 15 to 20 mg/L. At higher biotin concentration (25–35 mg/L), the bacterial cellulose production was lower.

OBJECTIVE: This study aimed to observe the effect of local mild hypothermia on regional cerebral blood flow (rCBF) after acute intracerebral hemorrhage (ICH) and to evaluate its relation to clinical outcome in patients with ICH. METHODS: 36 CT proven ICH patients with Glasgow coma scale (GCS) score of 5 or more were randomly assigned to 2 group: local mild hypothermia with conventional mannitol (Group A) or conventional mannitol (Group B). SPECT study was performed at day 7 after therapy. The SPECT images were semi-quantitatively analyzed, and the radioactivity ratios of lesion to normal tissue (L/NT) were calculated. National Institutes of Health Stroke Scale (NIHSS) were used in evaluation at days 14 and 21 after therapy. RESULTS: There were significant differences in NIHSS score at days 14 and 21, and the L/NT ratios between the groups A and B ( P< 0.05). Based on GCS, more patients in the group A showed favorable outcomes than patients in the group B ( P< 0.05). Furthermore, the L/NT ratios significantly increased in patients with favorable outcomes compared to poor outcomes. Changes in NIHSS score at days 14 and 21 were closely negatively correlated with the L/NT ratios in the groups A and B (r = −0.58, −0.61, and −0.52, −0.75, respectively, P< 0.05). CONCLUSION: Local mild hypothermia could significantly increase rCBF and improve clinical outcome in ICH patients as evaluated by 99m Tc-ECD SPECT study.

The Baranyi and Roberts model is one of the most frequently used microbial growth models. It has been successfully applied to numerous studies of various microorganisms in different food products. Under dynamic conditions, the model is implicitly formulated as a set of two coupled differential equations which could be numerically solved using the Runge–Kutta method. In this study, a simplified numerical solution of the coupled differential equations was derived and used to simulate microbial growth under dynamic conditions in Microsoft Excel. As expected, the results obtained were the same as those from solving the coupled differential equations using a MATLAB Solver. In addition, model parameters were accurately identified by fitting the numerical solution to simulated growth curves under dynamic (time-varying) temperature conditions using the Microsoft Excel Solver.

Background We sought to investigate the clinical features of and risk factors for recurrent major depression (MD) with history of postpartum episodes (PPD) in Han Chinese women and the differences between first-onset postpartum MD (MD that has its first lifetime depressive episode in the postpartum period) and first-onset non-postpartum MD (MD with history of PPD and has its first lifetime depressive episode in a period other than postpartum). Methods Data were derived from the China, Oxford and Virginia Commonwealth University Experimental Research on Genetic Epidemiology (CONVERGE) study (N=6017 cases) and analyzed in two steps. We first examined the clinical features of and risk factors for MD patients with (N=981) or without (N=4410) a history of PPD. We then compared the differences between first-onset postpartum MD (N=583) and first-onset non-postpartum MD (N=398) in those with a history of PPD. Linear, logistic and multinomial logistic models were employed to measure the associations. Results A history of PPD was associated with more guilt feelings, greater psychiatric comorbidity, higher neuroticism, earlier onset and more chronicity (OR 0.2–2.8). Severe premenstrual symptoms (PMS) and more childbirths increased the risk of PPD, as did a family history of MD, childhood sexual abuse, stressful life events and lack of social support (OR 1.1–1.3). In the MD with history of PPD subsample, first-onset postpartum MD was associated with fewer recurrent major depressive episodes, less psychiatric comorbidity, lower neuroticism, less severe PMS and fewer disagreements with their husbands (OR 0.5–0.8), but more childbirths (OR 1.2). Limitations Data were obtained retrospectively through interview and recall bias may have affected the results. Conclusions MD with history of PPD in Han Chinese women is typically chronic and severe, with particular risk factors including severe PMS and more childbirths. First-onset postpartum MD and first-onset non-postpartum MD can be partly differentiated by their clinical features and risk factors, but are not clearly distinctive.

To investigate the predictors of local recurrence and survival in primary retroperitoneal leiomyosarcoma (PRLS).A retrospective analysis was conducted on 46 cases of PRLS between August 2006 and April 2012. There were 9 male and 37 female patients, and they were 30-79 year old (median 49 year old). Kaplan-Meier estimations and Cox regression analyses were performed.The tumor size were 5-36 cm, and 29 cases (63.1%) of this group was more than 10 cm. Local 3- and 5-year control rates after complete resection were 47% and 30%. FNCLCC (Fédération Nationale des Centres de Lutte Contre le Cancer) grading (RR = 3.10, 95%CI: 1.59-6.04), gender (RR = 5.30, 95%CI: 1.64-17.13) and blood loss (RR = 3.12, 95%CI: 1.28-7.60) were independent prognostic factor of local recurrence in multivariable analysis (P0.05). The 5-year disease-free survival rates after complete resection of PRLS was 26%; and the 5-year disease-specific survival (DSS) rates after complete resection was 48%. The median DSS was 60 months in negative margin of resection and 50 months in positive margin. However, by multivariate analysis, only FNCLCC grading was significant independent predictors of DSS (RR = 2.01, 95%CI: 1.16-3.49, P = 0.013).Gender, FNCLCC grading and blood loss were independent prognostic factor of local recurrence. The disease-specific survival in PRLS varied significantly according to FNCLCC grading.

The microfluidisation process was used to reduce the particle size and loosen the tight microstructure of corn bran. This process significantly increased corn bran's antioxidant activity exhibited through a surface reaction phenomenon and the extractability of phenolic compounds after alkaline and acid hydrolysis. For corn bran microfluidised through an 87 μm interaction chamber for 5 passes, the two most largely increased phenolic acids released after alkaline hydrolysis were p-coumaric acid (51.1%) and ferulic acid (45.1%). On the other hand, high shear stress during microfluidisation caused partial dispersion or dissolution of free phenolic compounds in water which was lost after the process. It was also found that bran residues after alkaline and acid hydrolysis still exhibited strong antioxidant activity via a surface reaction phenomenon, probably indicating the conventional method based on solvent extraction and relatively mild alkaline and/or acid hydrolysis underestimates the total phenolic content and antioxidant activity of corn bran.

Isothermal microbial survival curves are usually described by either linear or nonlinear time-dependent models, from which non-isothermal survival curves can be generated if the parameters describing the survival kinetics of the microbial population are known. In order to estimate these parameters, an algorithm based on the steepest decent optimization method was developed. The algorithm searches the values of the survival parameters which minimize the sum of the squared differences between the experimental data and the calculated values provided by the model. The difference of the proposed algorithm with a typical optimization technique is that each data point used is not necessarily coming from the same thermal treatment; instead, data from different non-isothermal processes can be used. The developed algorithm was tested by using published non-isothermal survival data of Salmonella. The data showed that the survival curves can be described by the Weibull model, an already accepted and frequently used nonlinear model. Salmonella's survival parameters were estimated from the end points and all data points, respectively, of three non-isothermal survival curves. The results obtained showed that the number of survival data points must be sufficiently large to obtain true or statistically sound values of the survival parameters. A suitable way to achieve this is to implement the algorithm using all data points of multiple non-isothermal survival curves or a large number of end points of non-isothermal treatments. Mathematically, the developed algorithm should be applicable to any microbial survival kinetics accurately describing the inactivation of the microorganisms because no specific survival kinetics has to be pre-assumed to run the algorithm.

If methods of differentiating stem cells into thyrocytes can be perfected, they may provide a ready source of normal thyrocytes for basic research and clinical application. We developed a novel culture method capable of differentiating mouse embryonic stem (ES) cells into thyroid follicular cells.E14 mouse ES cells were allowed to differentiate into embryoid bodies and then stimulated with thyroid-stimulating hormone, insulin, and potassium iodide. The resulting differentiated cells were observed for expression of thyrocyte-specific mRNA transcripts with reverse transcriptase (RT)-polymerase chain reaction. To definitively identify thyrocytes, we simultaneously observed the thyrocyte-specific proteins, thyroid transcription factor-1 and PAX-8, with dual-color immunofluorescent labeling. The cells were further characterized by electron microscopy.The ES cells were successfully differentiated into thyrocytes. Differentiated cells expressed PAX-8, thyroid-stimulating hormone receptor, sodium/iodide symporter, thyroperoxidase, and thyroglobulin mRNAs, and coexpressed thyroid transcription factor-1 and PAX-8 proteins. The extent of differentiation was further explored by electron microscopy, which showed that differentiated cells had ultrastructural features similar to adult human thyrocytes, whereas the cells from unstimulated cultures were mostly disintegrated and lacked developed organelle structures.These data show that E14 mouse ES cells can be differentiated into thyrocytes by culturing with thyroid-stimulating hormone, insulin, and potassium iodide. The development of reliable methods to produce thyroid cells from ES cells is important to future research in thyroid biology and medical applications.

Publisher Summary This chapter addresses the on-line correction of in-pack processing of foods, presenting a short review of the work done on batch retorts and a description of new developments on continuous retorts. The primary purpose of on-line correction of process temperature deviations is to automatically vary the process time to ensure that all containers receive the heat treatment necessary to achieve the required sterilization at the cold spot (the slowest heating point) of the food product. The critical part of the control system, specifically for batch retort operations, is to implement a fast method for accurately determining the new process time necessary to compensate for the process temperature deviations. In an on-line correction algorithm, the target process lethality is the most important constraint utilized to calculate the required new processing time. The traditional approach to evaluate the efficacy of a thermal process is based on the assumption that the inactivation of microbial cells and spores follows a first-order kinetic model. However, there is a growing concern about its validity because curvilinear isothermal survival curves are frequently observed. The Weibull model has been shown to be able to provide a more accurate estimation of microbial inactivation by heat and also by other inactivation sources: pressure and chemical agents. This model is of special interest to thermal processes of low-acid canned foods. Given the importance of non-linear kinetics in the evaluation of thermal processes, the chapter discusses on-line correction strategies for continuous retorts by using both first-order kinetics and the Weibull model.