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Human colon microbiota produce a metabolite called urolithin A (URO A) from ellagic acid and linked compounds, and this metabolite has been demonstrated to have antioxidant, anti-inflammatory, and antiapoptotic activities. The current work examines the various mechanisms through which URO A protects against doxorubicin (DOX)-induced liver injury in Wistar rats. In this experiment, Wistar rats were administered DOX intraperitoneally (20 mg kg−1) on day 7 while given URO A intraperitoneally (2.5 or 5 mg kg−1 d−1) for 14 days. The serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma glutamyl transferase (GGT) were measured. Hematoxylin and eosin (HE) staining was used to evaluate histopathological characteristics, and then antioxidant and anti-inflammatory properties were evaluated in tissue and serum, respectively. We also looked at how active caspase 3 and cytochrome c oxidase were in the liver. The findings demonstrated that supplementary URO A therapy clearly mitigated DOX-induced liver damage. The antioxidant enzymes SOD and CAT were elevated in the liver, and the levels of inflammatory cytokines, such as TNF-α, NF-kB, and IL-6, in the tissue were significantly attenuated, all of which complemented the beneficial effects of URO A in DOX-induced liver injury. In addition, URO A was able to alter the expression of caspase 3 and cytochrome c oxidase in the livers of rats that were subjected to DOX stress. These results showed that URO A reduced DOX-induced liver injury by reducing oxidative stress, inflammation, and apoptosis.

Biological and financial models are examples of dynamical systems where both stochastic and historical behavior are important to be considered. The fractional Brownian motion (fBM) is commonly used, sometimes with fractional-order derivatives, to model the combined stochastic and fractional effects. Recently, spectral techniques are used to analyze models with fBM using, e.g., iterated Itô fractional integrals such as the fractional Wiener-Hermite (FWHE). In the current work, FWHE is generalized and adapted to be consistent with the Malliavin calculus approach. The conditions for existence and uniqueness are outlined in addition to the proof of convergence. The solution algorithm is described in detail. Using FWHE, the stochastic fractional model is replaced by a deterministic fractional-order system that can be handled using well-known mathematical tools to evaluate the solution statistics. Analytical solutions can be obtained for many important models such as the fractional stochastic Black–Scholes model. The convergence is studied and compared with the exact solution and high convergence is noticed compared with other techniques. A general numerical algorithm is described to analyze the resultant deterministic system in the case of no feasible analytical solutions. The algorithm is applied to study and simulate the population model with nonlinear losses for different values of the Hurst parameter. The results show the efficiency of FWHE in analyzing practical linear and nonlinear models.

Seeking an alternative approach for detecting adverse drug reactions (ADRs) in coronavirus patients (COVID-19) and enhancing drug safety, a retrospective study of six months was conducted utilizing an electronic medical record (EMR) database to detect ADRs in hospitalized patients for COVID-19, using “ADR prompt indicators” (APIs). Consequently, confirmed ADRs were subjected to multifaceted analyses, such as demographic attribution, relationship with specific drugs and implication for organs and systems of the body, incidence rate, type, severity, and preventability of ADR. The incidence rate of ADRs is 37%, the predisposition of organs and systems to ADR is observed remarkably in the hepatobiliary and gastrointestinal systems at 41.8% vs. 36.2%, p < 0.0001, and the classes of drugs implicated in the ADRs are lopinavir-ritonavir 16.3%, antibiotics 24.1%, and hydroxychloroquine12.8%. Furthermore, the duration of hospitalization and polypharmacy are significantly higher in patients with ADRs at 14.13 ± 7.87 versus 9.55 ± 7.90, p < 0.001, and 9.74 ± 5.51 versus 6.98 ± 4.36, p < 0.0001, respectively. Comorbidities are detected in 42.5% of patients and 75.2%, of patients with DM, and HTN, displaying significant ADRs, p-value < 0.05. This is a symbolic study providing a comprehensive acquaintance of the importance of APIs in detecting hospitalized ADRs, revealing increased detection rates and robust assertive values with insignificant costs, incorporating the hospital EMR database, and enhancing transparency and time effectiveness.