Buthus occitanus (B.occitanus) is one of the most dangerous scorpions in the world. Despite the involvement of B.occitanus scorpion in severe cases of envenomation in Morocco, no study has focused yet on the proteomic composition of the Moroccan B.occitanus scorpion venom. Mass spectrometry-based proteomic techniques are commonly used in the study of scorpion venoms. The implementation of top-down and bottom-up approaches for proteomic analyses facilitates screening by allowing a global view of the structural aspects of such complex matrices. Here, we provide a partial overview of the venom of B.occitanus, in order to explore the diversity of its toxins and hereafter understand their effects. To this end, a combination of top-down and bottomup approaches was applied using nano-high liquid chromatography coupled to nano-electrospray tandem mass spectrometry (nano-LC-ESI-MS/MS). TheLC-MS results showed that B.occitanus venom contains around 200 molecular masses ranging from 1868 to 16,720 Da, the most representative of which are those between 5000 and 8000 Da. Interestingly, combined top-down and bottom-up LC-MS/MS results allowed the identification of several toxins, which were mainly those acting on ion channels, including those targeting sodium (NaScTxs), potassium (KScTxs), chloride (ClScTxs) and calcium channels (CaScTx), as well as antimicrobial peptides (AMPs), amphipathic peptides, myotropic neuropeptides and hypothetical secreted proteins. This study reveals the molecular diversity of B.occitanus scorpion venom and identifies components that may have useful pharmacological activities.
Hepatocellular carcinoma (HCC) is the most common primary liver cancer in adults, the fifth most common malignancy worldwide and the third leading cause of cancer related death. An alternative to the surgical treatments and drugs, such as sorafenib, commonly used in medicine is necessary to overcome this public health problem. In this study, we determine the anticancer effect on HCC of Moroccan cobra Naja haje venom and its fraction obtained by gel filtration chromatography against Huh7.5 cancer cell line. Cells were grown together with WI38 human fibroblast cells, LX2 human hepatic stellate cell line, and human endothelial cells (HUVEC) in MCTS (multi-cellular tumor spheroids) models. The hepatotoxicity of venom and its fractions were also evaluated using the normal hepatocytes cell line (Fa2N-4 cells). Our results showed that an anti HCC activity of Moroccan cobra Naja haje venom and, more specifically, the F7 fraction of gel filtration chromatography exhibited the greatest anti-hepatocellular carcinoma effect by decreasing the size of MCTS. This effect is associated with a low toxicity against normal hepatocytes. These results strongly suggest that the F7 fraction of Moroccan cobra Naja haje venom obtained by gel filtration chromatography possesses the ability to inhibit cancer cells proliferation. More research is needed to identify the specific molecule(s) responsible for the anticancer effect and investigate their mechanism of action.
Particle swarm optimization (PSO) is one of the most well-regard metaheuristics with remarkable performance when solving diverse optimization problems. However, PSO faces two main problems that degrade its performance: slow convergence and local optima entrapment. In addition, the performance of this algorithm substantially degrades on high-dimensional problems. In the classical PSO, particles can move in each iteration with either slower or faster speed. This work proposes a novel idea called velocity pausing where particles in the proposed velocity pausing PSO (VPPSO) variant are supported by a third movement option that allows them to move with the same velocity as they did in the previous iteration. As a result, VPPSO has a higher potential to balance exploration and exploitation. To avoid the PSO premature convergence, VPPSO modifies the first term of the PSO velocity equation. In addition, the population of VPPSO is divided into two swarms to maintain diversity. The performance of VPPSO is validated on forty three benchmark functions and four real-world engineering problems. According to the Wilcoxon rank-sum and Friedman tests, VPPSO can significantly outperform seven prominent algorithms on most of the tested functions on both low- and high-dimensional cases. Due to its superior performance in solving complex high-dimensional problems, VPPSO can be applied to solve diverse real-world optimization problems. Moreover, the velocity pausing concept can be easily integrated with new or existing metaheuristic algorithms to enhance their performances. The Matlab code of VPPSO is available at: https://uk.mathworks.com/matlabcentral/fileexchange/119633-vppso.
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