Effect of oil exposure stages on the heat resistance of Salmonella enterica serovar Enteritidis phage type 30 in peanut flour.

The oil in low-moisture foods (LMFs) shows protective effects on bacteria during thermal processing. However, the circumstances under which this protective effect strengthens remain unclear. This study aimed to understand which step of the oil exposure to bacterial cells (inoculation, isothermal inactivation, or recovery and enumeration step) in LMFs can enhance their heat resistance. Peanut flour (PF) and defatted PF (DPF) were selected as the oil-rich and oil-free LMF models. Salmonella enterica Enteritidis Phage Type 30 (S. Enteritidis) was inoculated into four designated PF groups representing different oil exposure stages. It was isothermally treated to obtain heat resistance parameters. At a constant moisture content (aw,25°C = 0.32 ± 0.02) and controlled aw,85°C (0.32 ± 0.02), S. Enteritidis exhibited significantly high (p < 0.05) D values in oil-rich sample groups. For instance, the heat resistance values of S. Enteritidis in the PF-DPF and DPF-PF groups were D80°C of 138.22 ± 7.45 min and 101.89 ± 7.82 min; however, the D80°C in the DPF-DPF group was 34.54 ± 2.07 min. The oil addition after the thermal treatment also helped injured bacterial recovery in the enumeration. For instance, the D80°C, D85°C, and D90°C values in the DFF-DPF oil groups were 36.86 ± 2.30, 20.65 ± 1.23, and 7.91 ± 0.52 min, respectively, which were higher than those in the DPF-DPF group at 34.54 ± 2.07, 17.87 ± 0.78, and 7.10 ± 0.52 min. We confirmed that the oil protected S. Enteritidis in PF in all three stages: desiccation process, heat treatment, and recovery of bacterial cells in plates.

Domain Adaptation for In-Line Allergen Classification of Agri-Food Powders Using Near-Infrared Spectroscopy.

The addition of incorrect agri-food powders to a production line due to human error is a large safety concern in food and drink manufacturing, owing to incorporation of allergens in the final product. This work combines near-infrared spectroscopy with machine-learning models for early detection of this problem. Specifically, domain adaptation is used to transfer models from spectra acquired under stationary conditions to moving samples, thereby minimizing the volume of labelled data required to collect on a production line. Two deep-learning domain-adaptation methodologies are used: domain-adversarial neural networks and semisupervised generative adversarial neural networks. Overall, accuracy of up to 96.0% was achieved using no labelled data from the target domain moving spectra, and up to 99.68% was achieved when incorporating a single labelled data instance for each material into model training. Using both domain-adaptation methodologies together achieved the highest prediction accuracies on average, as did combining measurements from two near-infrared spectroscopy sensors with different wavelength ranges. Ensemble methods were used to further increase model accuracy and provide quantification of model uncertainty, and a feature-permutation method was used for global interpretability of the models.

Thermal resistance of Listeria monocytogenes, Escherichia coli O157:H7 and Salmonella in animal fat - Kinetic analysis and mathematical modeling.

The objective of this study was to evaluate the effect of fat on thermal resistance of L. monocytogenes, E. coli O157:H7, and Salmonella spp. A 4-strain cocktail of each microorganism was inoculated to beef tallow and heated isothermally at temperatures between 55 and 80℃. All survival curves did not follow the 1st-order inactivation kinetics but conformed to a two-stage linear pattern. The first stage was markedly less heat-resistant than the second, as manifested by significantly lower D values. The z values of E. coli O157 H7 and Salmonella spp. were 11.8 °C and 12.3 °C in the first stage (z1) but increased to 23.7 °C and 20.8 °C in the second stage (z2), respectively. For L. monocytogenes, while the z values were similar for both stages (z1 = 19.6 °C and z2 = 18.5 °C), the second stage D values are 3.6-5.9 times of those in the first stage. One-step analysis was used to fit the nonlinear curves to the Weibull model, yielding < 1 exponents for the model (0.495, 0.362, and 0.282, respectively, for L. monocytogenes, E. coli O157:H7, and Salmonella spp.), suggesting gradually increased thermal resistance during heating. The experimental results showed that these microorganisms could resist heating for longer time and at higher temperatures in tallow than they do in regular meats containing lower levels of fat. The kinetic models can be used to develop thermal processes to properly inactivate pathogens contaminated in the fat portions of meat products or other high fat products.

Investigation of the best possible methods for wind turbine blade waste management by using GIS and FAHP: Turkey case.

The aim of this study is to present the status and projections of wind turbine blade retirement in Turkey; to investigate the number of retiring WT blades in the regional, manufacturer, and material aspects; and to discuss the management methods for retired WT blades. To determine the best possible wind turbine blade waste management methods for Turkey, a combined application of Geographical Information Systems (GIS) and the Fuzzy Analytical Hierarchy Process (FAHP) is used in this study. It is found that around nine thousand WT blades will become waste between 2020 and 2039 in Turkey, corresponding to around 80,500 tons of waste. On average, 52,325 tons of glass/carbon and 28,175 tons of polymers will be accumulated between 2020 and 2039 from wind turbine blades. More than half of the WT blade waste will come from two WT manufacturers, namely, Enercon and Nordex. Aegean and Marmara regions will provide 74% of the blade waste, where 33% of them will be 2 MW and 2.5 MW sizes of WT blades. Furthermore, a case study is applied to Izmir city to demonstrate the results of FAHP for finding the best available method to dispose of WT blades. The results show that using blade waste as filling material is the best alternative, while waste-to-energy is the last favorable option for blade waste management. Finally, sensitivity analyses are applied to demonstrate the robustness of the results for the inclusion of new alternatives and the bias of experts' judgments.

Increased heat tolerance and transcriptome analysis of Salmonella enterica Enteritidis PT 30 heat-shocked at 42 ℃.

In this study, we compared the heat tolerance parameter (D65℃) values of Salmonella enterica serovar Enteritidis PT 30 (S. Enteritidis ) heat adapted at different degrees (at 42 ℃ for 20-180 min) and cultivated using two methods. The treated group with the highest D65℃ value (LP-42 ℃-60 min) and the untreated groups (Control-TSB and Control-TSA) were subjected to transcriptome analysis. Heat-adaptation increased the D65℃ values of S. Enteritidis by 24.5-60.8%. The D65℃ values of the LP-42 ℃-60 min group (1.85 ± 0.13 min, 7.7% higher) was comparable to that of the Control-TSA. A total of 483 up- and 443 downregulated genes of S. enteritidis were identified in the LP-42 ℃-60 min group (log2fold change > 1, adjusted p-value < 0.05). Among these genes, 5 co-expressed and 15 differentially expressed genes in the LP-42 ℃-60 min and Control-TSA grops possibly contributed to the high D65℃ values of S. Enteritidis . The Rpo regulon was involved in the heat adaptation of S. Enteritidis , as evidenced by the significant upregulation of rpoS, rpoN, and rpoE. KEGG enrichment pathways, such as biosynthesis of secondary metabolites, tricarboxylic acid, and ribosomes were identified and mapped to reveal the molecular mechanisms of S. enteritidis during heat adaptation. This study quantified the enhanced heat tolerance of S. Enteritidis heat adapted at different degrees of heat-adaptation. The results of this study may serve as a basis for elucidating the molecular mechanisms underlying the enhanced heat tolerance at the transcriptome level.

The Effect of Serum Electrolyte Levels and Infusion Treatments on the Development of Femoral Central Venous Catheter-Associated Deep Vein Thrombosis in Pediatric Intensive Care Unit.

In this study, we aimed to determine the frequency of symptomatic central venous catheters-associated deep vein thrombosis (CVC-a DVT) among critically ill children with femoral vein implantation in our pediatric intensive care unit (PICU), and to compare the demographic factors, serum electrolyte levels, and types of the infusion treatments performed. A total of 215 patients aged 1 month to 18 years who had femoral CVC implanted between 2019 and 2021 were included in this study. The cases that were clinically symptomatic and had thrombosis diagnosed ultrasonography were accepted as CVC-a DVT (+), and the other cases were considered as CVC-a DVT (-). Of the total 215 cases, 57.2% (n = 123) were female and 42.8% (n = 92) were male. Catheters-associated deep vein thrombosis diagnosis were made in 9.8% of the cases (n = 21). The mean time to diagnose thrombosis in CVC-a DVT (+) cases was 8.33 ± 5.65 days. With regard to gender, age, blood type, intubation status, length of stay on mechanical ventilator, presence of extra hemodialysis catheter, acute and chronic disease status, number of days of PICU hospitalization, and Pediatric Risk of Mortality-3 scoring, no significant differences between CVC-a DVT (-) and CVC-a DVT (+) cases were observed (P > .05). The incidence of thrombosis in refugee cases was found to be significantly higher than in Turkish cases (P = .047; P < .05). There was no statistically significant difference between the groups in baseline, mean, and peak glucose, sodium, and magnesium values and who received magnesium, blood product, inotrope, and 3% hypertonic saline (HTS) infusion (P > .05). No effect of serum glucose, sodium, and magnesium levels on the development of CVC-a DVT was found. Magnesium, blood product, inotrope, and 3% HTS infusion treatments have not been shown to have an effect on the development of CVC-a DVT.