Abstract Bochothrix thermosphacta is an optional aerobic psychrotrophic related to the meat deterioration and consequently loss of a refrigerated cargo contaminated. Predictive microbiology can be used as a quality assurance tool, since it allows the prediction of microbial response based in pass observations. This work aimed model the growth of B. thermosphacta under variation of pH and temperature. For this purpose, the experimental growth data were fitted to the primary models of Baranyi and Roberts and the modified Gompertz model and the data for the maximum rate of growth (μmax) were adjusted to Ratkowsky extended secondary model. The results showed us that the influence of temperature on growth parameters was more evident than pH. Since, by fixing the temperature the change of pH little altered the μmax. However, as the temperature rises the elevation at the μmax is considerable, for example the comparison of predicted values for μmax, when the temperature exceeds 4 °C to 12 °C, it is clear that these rates are more than double. Finally, it is emphasized that all tested models feature good fit to the experimental data, which makes them validated for prediction growth of B. thermosphacta in the same conditions tested experimentally.

Abstract Meat is one of the most perishable foods owing to its nutrient availability, high water activity, and pH around 5.6. These properties are highly conducive for microbial growth. Fresh meat, when exposed to oxygen, is subjected to the action of aerobic psychrotrophic, proteolytic, and lipolytic spoilage microorganisms, such as Pseudomonas spp. The spoilage results in the appearance of slime and off-flavor in food. In order to predict the growth of Pseudomonas fluorescens in fresh meat at different pH values, stored under refrigeration, and temperature abuse, microbial mathematical modeling was applied. The primary Baranyi and Roberts and the modified Gompertz models were fitted to the experimental data to obtain the growth parameters. The Ratkowsky extended model was used to determine the effect of pH and temperature on the growth parameter µmax. The program DMFit 3.0 was used for model adjustment and fitting. The experimental data showed good fit for both the models tested, and the primary and secondary models based on the Baranyi and Roberts models showed better validation. Thus, these models can be applied to predict the growth of P. fluorescens under the conditions tested.

OBJECTIVES: To study pre and postoperative WMA in MTLE patients. METHODS: We performed Voxel-Based Morphometry (VBM) with volume of interest (VOI) in 69 controls (mean age, 34.3±11.1 years) and 67 operated patients (mean age, 34.1±10.4 years) with unilateral MTLE. 34 became seizure-free (SzFree-Group), 23 improved (Engel IB-IIA [Partial recovery-group]) and 10 did not improve (Engel III-IV [Failure-Group]). All had pre and postoperative MRIs (one year minimum). We flipped MRIs of right MTLE patients in order to avoid right-to-left analysis cancelation. VBM was performed on SPM2/MATLAB7.0 with individual masks for surgical lacunae and 1% false-discovery-rate to control for multiple comparisons. We used MARSbar <www.marsbar.sourceforge.net> routine to select ROIs and t-test for statistical analyses. RESULTS: Mean postoperative follow-up was 60.2 (±SD 30.7) months. On baseline MRI, SzFree-Group showed White Matter Atrophy (WMA) involving temporal lobes [TL], ipsilateral occipital, parietal and frontal regions, with areas of significant recovery of WMA on postoperative MRI. Partial recovery-Group presented a more restricted pattern of WMA, involving ipsilateral temporal lobe, contralateral superior temporal gyrus and few areas in bilateral cingulated and orbitofrontal areas. In this group we also identified areas with relative increase of WM after surgery. By contrast, Failure-Group showed more widespread bi-hemispheric areas of WMA on baseline MRI without postoperative improvement. CONCLUSIONS: Although we have identified some differences in baseline WMA, we were unable to correlate a more widespread pattern with a worse prognosis, as SzFree-Group, also presented a bilateral distribution of WMA. The recovery of WMA in SzFree-Group and Partial recovery-group is in agreement with previous MRS and PET studies and suggests that a network of neuronal dysfunction in MTLE can be, at least in part, reversible after successful postoperative seizure control.