This current study review provides a brief review of a natural bee product known as propolis and its relevance toward combating SARS-CoV viruses. Propolis has been utilized in medicinal products for centuries due to its excellent biological properties. These include anti-oxidant, immunomodulatory, anti-inflammatory, anti-viral, anti-fungal, and bactericidal activities. Furthermore, studies on molecular simulations show that flavonoids in propolis may reduce viral replication. While further research is needed to validate this theory, it has been observed that COVID-19 patients receiving propolis show earlier viral clearance, enhanced symptom recovery, quicker discharge from hospitals, and a reduced mortality rate relative to other patients. As a result, it appears that propolis could probably be useful in the treatment of SARS-CoV-2-infected patients. Therefore, this review sought to explore the natural properties of propolis and further evaluated past studies that investigated propolis as an alternative product for the treatment of COVID-19 symptoms. In addition, the review also highlights the possible mode of propolis action as well as molecular simulations of propolis compounds that may interact with the SARS-CoV-2 virus. The activity of propolis compounds in decreasing the impact of COVID-19-related comorbidities, the possible roles of such compounds as COVID-19 vaccine adjuvants, and the use of nutraceuticals in COVID-19 treatment, instead of pharmaceuticals, has also been discussed.
This study investigates the thermal decomposition, thermodynamic and kinetic behavior of rice-husk (R), sewage sludge (S) and their blends during co-pyrolysis using thermogravimetric analysis at a constant heating rate of 20 °C/min. Coats-Redfern integral method is applied to mass loss data by employing seventeen models of five major reaction mechanisms to calculate the kinetics and thermodynamic parameters. Two temperature regions: I (200-400 °C) and II (400-600 °C) are identified and best fitted with different models. Among all models, diffusion models show high activation energy with higher R2(0.99) of rice husk (66.27-82.77 kJ/mol), sewage sludge (52.01-68.01 kJ/mol) and subsequent blends (45.10-65.81 kJ/mol) for region I and for rice husk (7.31-25.84 kJ/mol), sewage sludge (1.85-16.23 kJ/mol) and blends (4.95-16.32 kJ/mol) for region II, respectively. Thermodynamic parameters are calculated using kinetics data to assess the co-pyrolysis process enthalpy, Gibbs-free energy, and change in entropy. Artificial neural network (ANN) models are developed and employed on co-pyrolysis thermal decomposition data to study the reaction mechanism by calculating Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and coefficient of determination (R2). The co-pyrolysis results from a thermal behavior and kinetics perspective are promising and the process is viable to recover organic materials more efficiently.