Concanavalin A (ConA), the most studied plant lectin, has been known as a potent anti-neoplastic agent for a long time. Since initial reports on its capacity to kill cancer cells, much attention has been devoted to unveiling the lectin's exact molecular mechanism. It has been revealed that ConA can bind to several receptors on cancerous and normal cells and modulate the related signaling cascades. The most studied host receptor for ConA is MT1-MMP, responsible for most of the lectin's modulations, ranging from activating immune cells to killing tumor cells. In this study, in addition to studying the effect of ConA on signaling and immune cell function, we will focus on the most up-to-date advancements that unraveled the molecular mechanisms by which ConA can induce autophagy and apoptosis in various cancer cell types, where it has been found that P73 and JAK/STAT3 are the leading players. Moreover, we further discuss the main signaling molecules causing liver injury as the most significant side effect of the lectin injection. Altogether, these findings may shed light on the complex signaling pathways controlling the diverse responses created via ConA treatment, thereby modulating these complex networks to create more potent lectin-based cancer therapy.

Humans maintain their health by consuming a variety of vegetables and fruits that contain antioxidants, both enzymatic and no enzymatic. Raspberry is one of the most diverse genus of true dicotyledonous plants, which includes 12 subspecies and about 429 species. Raspberry fruit is rich in antioxidant compounds, especially polyphenols. Two species of raspberry were studied to determine the amount of antioxidants and phenolic and flavonoid compounds in their fruits at three different stages of fruit ripening immature, semi-ripe and mature. Natural samples of Rubus idaeus and Rubus strigosus were collected. In this study, the fruit extracts of two species were stored at -23 °C for about six months. Free radical cleansing and Ferric reducing antioxidant power methods were used to determine the antioxidant activities of the extracts. The antioxidant activity of both methods revealed a higher mean value in extracts from fully matured fruits compared with immature and semi-ripe fruits. The results showed that the antioxidant activity of Rubus strigosus is 9%, 10%, and 8% higher than Rubus idaeus in the stages of immature, semi-ripe, and full maturity, respectively.

Aiming at the problem that it is difficult to achieve rapid and accurate detection of pesticide residues, the artificial neural network method is used to separate the mixed fluorescence spectra in the measurement of acetamiprid pesticide residues, and a fluorescence spectrum that can quickly detect the pesticide residues of acetamiprid on solid surfaces is designed. According to the back-propagation algorithm, the three-layer artificial neural network principle is used to detect the acetamiprid residue in the mixed system of acetamiprid and filter paper with severely overlapping fluorescence spectra. In the range of 340nm~400nm, using the fluorescence intensity values at 20 characteristic wavelengths as the characteristic network parameters, after network training and testing, the recovery rates of acetamiprid concentrations of 40mg/kg and 90mg/kg are 102% and 97%, respectively. The relative standard deviations of the determination results were 1.4% and 1.9%, respectively. The experimental results show that the BP neural network-assisted fluorescence spectroscopy method for the determination of acetamiprid pesticide residues on filter paper has the characteristics of fast network training, short detection period, and high measurement accuracy.

No abstract