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The use of bee honey and royal jelly as natural compounds is effective in reducing cisplatin nephrotoxicity and may offer a promising chance for clinically meaningful prevention. This study has potentially important implications for the treatment of cisplatin kidney side effects and is considered to be the first to investigate this effect of honey and royal jelly in human subjects. However, due to its small sample size, we recommend further investigation using a larger sample size.

Coronavirus disease 2019 (COVID‐19) has had different waves within the same country. The spread rate and severity showed different properties within the COVID‐19 different waves. The present work aims to compare the spread and the severity of the different waves using the available data of confirmed COVID‐19 cases and death cases. Real‐data sets collected from the Johns Hopkins University Center for Systems Science were used to perform a comparative study between COVID‐19 different waves in 12 countries with the highest total performed tests for severe acute respiratory syndrome coronavirus 2 detection in the world (Italy, Brazil, Japan, Germany, Spain, India, USA, UAE, Poland, Colombia, Turkey, and Switzerland). The total number of confirmed cases and death cases in different waves of COVID‐19 were compared to that of the previous one for equivalent periods. The total number of death cases in each wave was presented as a percentage of the total number of confirmed cases for the same periods. In all the selected 12 countries, Wave 2 had a much higher number of confirmed cases than that in Wave 1. However, the death cases increase was not comparable with that of the confirmed cases to the extent that some countries had lower death cases than in Wave 1, UAE, and Spain. The death cases as a percentage of the total number of confirmed cases in Wave 1 were much higher than that in Wave 2. Some countries have had Waves 3 and 4. Waves 3 and 4 have had lower confirmed cases than Wave 2, however, the death cases were variable in different countries. The death cases in Waves 3 and 4 were similar to or higher than Wave 2 in most countries. Wave 2 of COVID‐19 had a much higher spread rate but much lower severity resulting in a lower death rate in Wave 2 compared with that of the first wave. Waves 3 and 4 have had lower confirmed cases than Wave 2; that could be due to the presence of appropriate treatment and vaccination. However, that was not reflected in the death cases, which were similar to or higher than Wave 2 in most countries. Further studies are needed to explain these findings.

Background The new coronavirus (SARS‐COV‐2) that emerged at the end of 2019 was stated in China and infected millions of people around the world, with the highest spread rate amongst humans compared with other coronaviruses. This paper aimed to review and analyse the published studies about COVID‐19 diagnosis, prevention, and treatment. Method The reviewed studies were clinical trials, in‐vivo, in‐vitro, guidelines, reports from the world health organization (WHO), and the centre for disease control and prevention (CDC) in addition to systemic reviews. All data extracted and analysed to stand on the latest updates and recommendations for fighting this severe attack of COVID‐19. Results Most important antiviral therapy of COVID‐19 clinical trials is still running without clear results, but a few trials have indicated the role of numerous drugs in the treatment of COVID‐19. Specific recommendations for aerosol therapy should be followed for the management of COVID‐19. Conclusion Nature of COVID‐19 is still not very clear, however, management of the condition is similar to the previous attacks of coronaviruses.

Backgrounds SARS‐CoV‐2 is affecting different countries all over the world, with significant variation in infection‐rate and death‐ratio. We have previously shown a presence of a possible relationship between different variables including the Bacillus Calmette–Guérin (BCG) vaccine, average age, gender, and malaria treatment, and the rate of spread, severity and mortality of COVID‐19 disease. This paper focuses on developing machine learning models for this relationship. Methods We have used real‐datasets collected from the Johns Hopkins University Center for Systems Science and Engineering and the European Centre for Disease Prevention and Control to develop a model from China data as the baseline country. From this model, we predicted and forecasted different countries' daily confirmed‐cases and daily death‐cases and examined if there was any possible effect of the variables mentioned above. Results The model was trained based on China data as a baseline model for daily confirmed‐cases and daily death‐cases. This machine learning application succeeded in modelling and forecasting daily confirmed‐cases and daily death‐cases. The modelling and forecasting of viral spread resulted in four different regions; these regions were dependent on the malarial treatments, BCG vaccination, weather conditions, and average age. However, the lack of social distancing resulted in variation in the effect of these factors, for example, double‐humped spread and mortality cases curves and sudden increases in the spread and mortality cases in different countries. The process of machine learning for time‐series prediction and forecasting, especially in the pandemic COVID‐19 domain, proved usefulness in modelling and forecasting the end status of the virus spreading based on specific regional and health support variables. Conclusion From the experimental results, we confirm that COVID‐19 has a very low spread in the African countries with all the four variables (average young age, hot weather, BCG vaccine and malaria treatment); a very high spread in European countries and the USA with no variable (old people, cold weather, no BCG vaccine and no malaria). The effect of the variables could be on the spread or the severity to the extent that the infected subject might not have symptoms or the case is mild and can be missed as a confirmed‐case. Social distancing decreases the effect of these factors.