ABSTRACT
Despite the wide medical knowledge about the direct role of many viruses in the pathogenesis of certain cancers, there is still ambiguity and hazy vision about the direct role of bacteria in cancer incidence. Understanding the role of bacteria in carcinogenesis is no longer a scientific luxury, but it has become an urgent and extremely important necessity to realize the pathogenesis of cancer caused by oncogenic bacteria as an attempt to overcome the oncogenic mechanisms exhibited by these oncogenic bacteria. This review shed the light on the indirect role of the host's inflammatory and immunological responses in the pathogenesis of bacteria-induced cancer. Also, this review discussed the indirect role of the bacterial toxins and virulence factors in the induction of common gastrointestinal cancers, such as gallbladder cancer (GBC), colorectal cancer (CRC), and gastric cancer (GC). Finally, this review dealt with the debate about the possibility of bacterial DNA integration into the human genome and cancer incidence.
ABSTRACT
One of the greatest challenges facing the humankind nowadays is to confront that emerging virus, which is the Coronavirus (COVID-19), and therefore all organizations have to unite in order to tackle that the transmission risk of this virus. From this standpoint, the scientific researchers have to find good mathematical models that do describe the transmission of such virus and contribute to reducing it in one way or another, where the study of COVID-19 transmission dynamics by mathematical models is very important for analyzing and controlling this disease propagation. Thus, in the current work, we present a new fractional-order mathematical model that describes the dynamics of COVID-19. In the proposed model, the total population is divided into eight classes, in addition to three compartments used to estimate the parameters and initial values. The effective reproduction number ( R 0 ) is derived by next generation matrix (NGM) method and all possible equilibrium points and their stability are investigated in details. We used the reported data (from January 23, 2020, to November 21, 2020) from the National Health Commission (NHC) of China to estimate the parameters and initial conditions (ICs) which suggested for our model. Simulation outcomes demonstrate that the fractional order model (FOM) represents behaviors that follow the real data more accurately than the integer-order model. The current work enhances the recent reported results of Zu et al. published in THE LANCET (doi:10.2139/ssrn.3539669).
