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Leafy greens are frequently implicated in foodborne disease outbreaks and cut-leafy greens are a food that requires time and temperature control for safety. Predictive microbiology uses mathematical models to predict the growth of bacteria based on environmental conditions. The objective of our study was to compare published square root growth models for Salmonella (n = 6), pathogenic E. coli (n = 6) and Listeria monocytogenes (n = 4) using real world transport temperature data. Data from trucks transporting fresh-cut leafy greens during cross-country shipments were used as temperature inputs to the models. Bacterial growth was computed using the temperatures from each probe in every truck over the duration of transit, which resulted in 12–18 growth predictions per truck for each model. Each model generally gave significantly different predictions than other models for the same organism. The exception was for the two Salmonella models predicting the least growth and the two Salmonella models predicting the most growth which gave predictions that were not significantly different. Although different models tended to give different predictions, their ability to rank risk by truck was generally consistent across models. While absolute risk might be dependent upon choice of model, relative risk is independent of model choice. • Two Salmonella models predicting the least growth gave similar predictions • Two Salmonella models predicting the most growth gave similar predictions • Six E. coli models gave significantly different predictions from one another • Four L. monocytogenes models also gave significantly different predictions • Models tended to rank different trucks similarly despite different predictions [ABSTRACT FROM AUTHOR]

Hemostasis encompasses an ensemble of interactions among platelets, coagulation factors, blood cells, endothelium, and hemodynamic forces, but current assays assess only isolated aspects of this complex process. Accordingly, here we develop a comprehensive in vitro mechanical injury bleeding model comprising an “endothelialized” microfluidic system coupled with a microengineered pneumatic valve that induces a vascular “injury”. With perfusion of whole blood, hemostatic plug formation is visualized and “in vitro bleeding time” is measured. We investigate the interaction of different components of hemostasis, gaining insight into several unresolved hematologic issues. Specifically, we visualize and quantitatively demonstrate: the effect of anti-platelet agent on clot contraction and hemostatic plug formation, that von Willebrand factor is essential for hemostasis at high shear, that hemophilia A blood confers unstable hemostatic plug formation and altered fibrin architecture, and the importance of endothelial phosphatidylserine in hemostasis. These results establish the versatility and clinical utility of our microfluidic bleeding model. [ABSTRACT FROM AUTHOR]