An Intelligent Decision Support System for the Detection of Meat Spoilage using Multispectral Images

In food industry, quality and safety are considered important issues worldwide that are directly related to health and social progress. The use of vision technology for quality testing of food production has the obvious advantage of being able to continuously monitor a production using non-destructive methods, thus increasing the quality and minimizing cost. The performance of an intelligent decision support system has been evaluated in monitoring the spoilage of minced beef stored either aerobically or under modified atmosphere packaging, at different storage temperatures (0, 5, 10, and 15 °C) utilising multispectral imaging information. This paper utilises a neuro-fuzzy model which incorporates a clustering pre-processing stage for the definition of fuzzy rules, while its final fuzzy rule base is determined by competitive learning. Initially, meat samples are classified according to their storage conditions, while identification models are then utilised for the prediction of the Total Viable Counts of bacteria. The innovation of the proposed approach is further extended to the identification of the temperature used for storage, utilizing only imaging spectral information. Results indicated that spectral information in combination with the proposed modelling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

IL-17A potentiates TNFα-induced secretion from human endothelial cells and alters barrier functions controlling neutrophils rights of passage

Interleukin-17A (IL-17A) is an important pro-inflammatory cytokine that regulates leukocyte mobilization and recruitment. To better understand how IL-17A controls leukocyte trafficking across capillaries in the peripheral blood circulation, we used primary human dermal microvascular endothelial cells (HDMEC) to investigate their secretory potential and barrier function when activated with IL-17A and TNFα. Activation by TNFα and IL-17A causes phosphorylation of p38 as well as IκBα whereby NFκB subsequently becomes phosphorylated, a mechanism that initiates transcription of adhesion molecules such as E-selectin. Members of the neutrophil-specific GRO-family chemokines were significantly up-regulated upon IL-17A stimulation on the mRNA and protein level, whereas all tested non-neutrophil-specific chemokines remained unchanged in comparison. Moreover, a striking synergistic effect in the induction of granulocyte colony-stimulating factors (G-CSF) was elicited when IL-17A was used in combination with TNFα, and IL-17A was able to significantly augment the levels of TNFα-induced E-selectin and ICAM-1. In accordance with this observation, IL-17A was able to markedly increase TNFα-induced neutrophil adherence to HDMEC monolayers in an in vitro adhesion assay. Using a trans-well migration assay with an HDMEC monolayer as a barrier, we here show that pre-stimulating the endothelial cells with TNFα and IL-17A together enhances the rate of neutrophil transmigration compared to TNFα or IL-17A alone. These results show that IL-17A and TNFα act in cooperation to facilitate neutrophil migration across the endothelial cell barrier. In addition, the synergistic actions of IL-17A with TNFα to secrete G-CSF appear to be important for mobilizing neutrophils from the bone marrow to the blood stream