Biosorption of Pb(II) Using Natural and Treated Ardisia compressa K. Leaves: Simulation Framework Extended through the Application of Artificial Neural Network and Genetic Algorithm.

This study explored the effects of solution pH, biosorbent dose, contact time, and temperature on the Pb(II) biosorption process of natural and chemically treated leaves of A. compressa K. (Raw-AC and AC-OH, respectively). The results show that the surface characteristics of Raw-AC changed following alkali treatment. FT-IR analysis showed the presence of various functional groups on the surface of the biosorbent, which were binding sites for the Pb(II) biosorption. The nonlinear pseudo-second-order kinetic model was found to be the best fitted to the experimental kinetic data. Adsorption equilibrium data at pH = 2-6, biosorbents dose from 5 to 20 mg/L, and temperature from 300.15 to 333.15 K were adjusted to the Langmuir, Freundlich, and Dubinin-Radushkevich (D-R) isotherm models. The results show that the adsorption capacity was enhanced with the increase in the solution pH and diminished with the increase in the temperature and biosorbent dose. It was also found that AC-OH is more effective than Raw-AC in removing Pb(II) from aqueous solutions. This was also confirmed using artificial neural networks and genetic algorithms, where it was demonstrated that the improvement was around 57.7%. The nonlinear Langmuir isotherm model was the best fitted, and the maximum adsorption capacities of Raw-AC and AC-OH were 96 mg/g and 170 mg/g, respectively. The removal efficiency of Pb(II) was maintained approximately after three adsorption and desorption cycles using 0.5 M HCl as an eluent. This research delved into the impact of solution pH, biosorbent characteristics, and operational parameters on Pb(II) biosorption, offering valuable insights for engineering education by illustrating the practical application of fundamental chemical and kinetic principles to enhance the design and optimization of sustainable water treatment systems.

Antiproliferative and proapoptotic effects of astemizole on cervical cancer cells.

OBJECTIVE: Cervical cancer is a major cause of mortality among women in developing countries. Thus, it is necessary to offer novel therapies to treat this malignancy. Astemizole has been suggested as a novel and interesting anticancer agent because it targets several proteins involved in cancer including Eag1 (ether à-go-go-1) potassium channels. Eag1 has been proposed as a tumor marker for different types of cancer. Actually, we previously suggested Eag1 channels as cervical cancer and dysplasia markers. Besides, Eag1 has been proposed as a therapeutic target for different malignancies. However, the effect of astemizole in cervical cancer cells is unknown. Therefore, we investigated the effect of astemizole on the proliferation and apoptosis of cervical cancer cells. METHODS: Five cervical cancer cell lines (HeLa, SiHa, CaSki, INBL, and C-33A) were cultured according to manufacturer's instructions. Eag1 protein expression was studied by immunocytochemistry. Cell proliferation was assayed with the MTT method, and apoptosis was investigated by flow cytometry. RESULTS: Eag1 protein expression was observed in different cell lines. Astemizole decreased cell proliferation in up to 40% and increased apoptosis severalfold in all the cell lines studied. CONCLUSIONS: Our results suggest astemizole as a potential therapy for cervical cancer.