Cancer is still one of the leading causes of death worldwide, and finding new treatments remains a major challenge. Previous studies showed that modified forms of pectin, a complex polysaccharide present in the primary plant cell wall, possess anticancer properties. Nevertheless, the mechanism of action of modified pectin and the pathways involved are unclear. Here, we show that citrus pectin modified by heat treatment induced cell death in HepG2 and A549 cells. The induced cell death differs from classical apoptosis because no DNA cleavage was observed. In addition, Z-VAD-fmk, a pan-caspase inhibitor, did not influence the observed cell death in HepG2 cells but appeared to be partly protective in A549 cells, indicating that heat-modified citrus pectin might induce caspase-independent cell death. An increase in the abundance of the phosphatidylethanolamine-conjugated Light Chain 3 (LC3) protein and a decrease in p62 protein abundance were observed in both cell types when incubated in the presence of heat-modified citrus pectin. These results indicate the activation of autophagy. To our knowledge, this is the first time that autophagy has been revealed in cells incubated in the presence of a modified form of pectin. This autophagy activation appears to be protective, at least for A549 cells, because its inhibition with 3-methyladenine increased the observed modified pectin-induced cytotoxicity. This study confirms the potential of modified pectin to improve chemotherapeutic cancer treatments.
Hybridoma cells are commonly grown for the production of monoclonal antibodies (MAb). For monitoring and control purposes of the bioreactors, dynamic models of the cultures are required. However these models are difficult to infer from the usually limited amount of available experimental data and do not focus on target protein production optimization. This paper explores an experimental case study where hybridoma cells are grown in a sequential batch reactor. The simplest macroscopic reaction scheme translating the data is first derived using a maximum likelihood principal component analysis. Subsequently, nonlinear least-squares estimation is used to determine the kinetic laws. The resulting dynamic model reproduces quite satisfactorily the experimental data, as evidenced in direct and cross-validation tests. Furthermore, model predictions can also be used to predict optimal medium renewal time and composition.
A novel approach to complex target recognition using wavelet decomposition of the radar cross section is introduced. The analysis technique is presented, and it shown how it can be implemented using MA TLAB software. Applications in the radar field are then investigated, both for simple and complex targets. The results obtained show that this technique is very promising and yields recognition levels difficult to achieve with any other available technique.
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