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Introduction Propranolol is a nonspecific beta-blocker that was presented as the first beta blocker in i960.1 It is used in various cases, and mainly to treat high blood pressure,2 cardiac arrhythmias,3,4 thyrotoxicosis,5 migraine headaches,6 and psychiatric diseases.7 In recent studies, the beneficial effects of the drug to inhibit angiogenesis,8 treatment of different types of cancer,9-12 and hemangioma in children13 has been established. Previous studies have shown that oral clearance of propranolol is higher in black people due to the higher activity of hepatic metabolic pathways.21,22 However in the study about the effects of 2D6 genotypes on the side effects and effectiveness of Metoprolol in the treatment of hypertension,9 despite the influence of these factors on pharmacokinetic of the drug, it was not associated with side effects of beta blocker or its effectiveness.23 In another study on the racial differences in pharmacokinetic propranolol, it was found that CYP1A2 metabolism pathway plays a role in 4-hydroxylation of propranolol, as well as CYP2D6, and the formation of metabolites resulting from these metabolic pathways, is considerably higher in African- American race than in Asian race. In the study of Xie and Chen in china, Cpmax in women and their AUC were respectively %99 and %74 more than men, the results were statistically significant. [...]half-life of the drug in women was longer than in men.25 In another study on the difference of propranolol metabolic clearance in both genders it has been observed that after administration of 80 mg of the oral drug, there has been no significant difference in volume of distribution and half-life of the drug. In poor metabolizer people, following the administration of certain doses of the drug, there was more increase in the concentration of the drug, longer elimination half-life and an increase in the inhibition of beta. [...]administration of standard doses of beta blocker might cause the outbreak of dose-dependent side effects.37 One of propranolol metabolites is 4-Hydroxypropranolol resulted from drug oxidation in the route of P450 cytochrome.

The changes in total phenolic content (TPC), total flavonoid content (TFC), proline, malondialdehyde (MDA), H₂O₂, and antioxidant activity were assessed based on three model systems in three Achillea species (Achillea millefolium, A. nobilis, and A. filipendulina) growing under four irrigation regimes, including 100 % FC (field capacity as normal irrigation) 75 % FC (low stress), 50 % FC (moderate stress), and 25 % FC (severe stress) conditions. The highest TPC (47.13 mg tannic acid/g DW) and TFC (20.86 mg quercetin/g W) were obtained in A. filipendulina under moderate and severe stress conditions. In 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay, the highest and the lowest antioxidant activity was obtained for A. millefolium (70.28 %) and A. filipendulina (53.21 %), respectively, while in the FTC model system A. nobilis revealed the highest antioxidant activity (1.934) in severe drought condition. In the linoleic model system, the highest antioxidant activity was observed under low drought stress condition in A. nobilis. MDA and H₂O₂ content were increased due to both low (75 % FC) and moderate (50 % FC) drought stress, but they were decreased under severe stress condition (25 % FC). Furthermore, A. millefolium revealed the lowest H₂O₂ (4.96 nm/g FW) and MDA content (176.32 μmol/g). Investigation of the relationship among different metabolites showed a strong positive correlation with TPC and TFC. Finally, the moderate drought stress treatment (50 % FC) was introduced as the optimum condition to obtain appreciable TPC and TFC,, while the highest antioxidant activity was obtained in severe stress condition (25%FC).

Modeling techniques can be powerful predictors of soil salinity across various scales, ranging from local landscapes to global territories. This study was aimed to examine the accuracy of soil salinity prediction model integrating ANNs (artificial neural networks) and topographic factors with different cell sizes. For this purpose, soil salinity was determined at 103 points in the east of Mashhad, Razavi Khorasan, Iran. The region was categorized into two distinct parts: study area (1) (with a steep topography) and study area (2) (with a flat topography). To explore the impact of terrain on salinity prediction accuracy, ANNs were trained using topographical factors as inputs across a range of cell sizes (30, 50, 90, 200, and 500 m). The model’s effectiveness was evaluated based on their Root Mean Square Error (RMSE) and coefficient of determination (R 2 ). Results indicated variability in model performance, with RMSE ranging from 0.324 to 0.461 and R 2 from 0.159 to 0.281 across the spectrum of cell sizes. Deeper analysis on different topographical influences showed that for the study area (1), a cell size of 30 m yielded the most accurate predictions (RMSE = 0.234 dS/m and R 2 = 0.515), whereas for the study area (2), a cell size of 50 m was optimal (RMSE = 0.658 dS/m and R 2 = 0.597). In general, the findings concluded that smaller cell sizes can enhance prediction accuracy in areas with complex and varied topography, while larger cell sizes can be more effective in flat areas. This study demonstrates the significance of incorporating terrain attributes and their optimal resolutions for accurate soil salinity prediction. Our findings underscore the importance of tailoring the resolution of input data to match the specific topographic features of the area, challenging the conventional notion that higher input resolution invariably yields better results in soil properties prediction. These insights provide valuable guidance for effective soil management and agricultural practices, as well as contribute to more informed decision-making in land management and environmental conservation.

Molecular signaling pathways play a significant role in the regulation of biological mechanisms, and their abnormal expression can provide the conditions for cancer development. The signal transducer and activator of transcription 3 (STAT3) is a key member of the STAT proteins and its oncogene role in cancer has been shown. STAT3 is able to promote the proliferation and invasion of cancer cells and induces chemoresistance. Different downstream targets of STAT3 have been identified in cancer and it has also been shown that microRNA (miR), long non-coding RNA (lncRNA) and other molecular pathways are able to function as upstream mediators of STAT3 in cancer. In the present review, we focus on the role and regulation of STAT3 in gastric cancer (GC). miRs and lncRNAs are considered as potential upstream mediators of STAT3 and they are able to affect STAT3 expression in exerting their oncogene or onco-suppressor role in GC cells. Anti-tumor compounds suppress the STAT3 signaling pathway to restrict the proliferation and malignant behavior of GC cells. Other molecular pathways, such as sirtuin, stathmin and so on, can act as upstream mediators of STAT3 in GC. Notably, the components of the tumor microenvironment that are capable of targeting STAT3 in GC, such as fibroblasts and macrophages, are discussed in this review. Finally, we demonstrate that STAT3 can target oncogene factors to enhance the proliferation and metastasis of GC cells.

Parkinson's disease (PD) is a prevalent and burdensome neurodegenerative disorder that has been extensively researched to understand its complex etiology, diagnosis, and treatment. The interplay between genetic and environmental factors in PD makes its pathophysiology difficult to comprehend, emphasizing the need for further investigation into genetic and epigenetic markers involved in the disease. Early diagnosis is crucial for optimal management of the disease, and the development of novel diagnostic biomarkers is ongoing. Although many efforts have been made in the field of recognition and interpretation of the mechanisms involved in the pathophysiology of the disease, the current knowledge about PD is just the tip of the iceberg. By scrutinizing genetic and epigenetic patterns underlying PD, new avenues can be opened for dissecting the pathology of the disorder, leading to more precise and efficient diagnostic and therapeutic approaches. This review emphasizes the importance of studying dysregulated cell signaling pathways and molecular processes associated with genes and epigenetic alterations in understanding PD, paving the way for the development of novel therapeutic strategies to combat this devastating disease. Graphical Abstract Epigenetic signaling cascade in PD. Figure was extracted from the Pathway Studio, Elsevier.

Prostate cancer (PCa) accounts for a high number of deaths in males with no available curative treatments. Patients with PCa are commonly diagnosed in advanced stages due to the lack of symptoms in the early stages. Recently, the research focus was directed toward gene editing in cancer therapy. Small interfering RNA (siRNA) intervention is considered as a powerful tool for gene silencing (knockdown), enabling the suppression of oncogene factors in cancer. This strategy is applied to the treatment of various cancers including PCa. The siRNA can inhibit proliferation and invasion of PCa cells and is able to promote the anti-tumor activity of chemotherapeutic agents. However, the off-target effects of siRNA therapy remarkably reduce its efficacy in PCa therapy. To date, various carriers were designed to improve the delivery of siRNA and, among them, nanoparticles are of importance. Nanoparticles enable the targeted delivery of siRNAs and enhance their potential in the downregulation of target genes of interest. Additionally, nanoparticles can provide a platform for the co-delivery of siRNAs and anti-tumor drugs, resulting in decreased growth and migration of PCa cells. The efficacy, specificity, and delivery of siRNAs are comprehensively discussed in this review to direct further studies toward using siRNAs and their nanoscale-delivery systems in PCa therapy and perhaps other cancer types.

Purpose While the rate of survival has increased in the past decade, the diagnosis of breast cancer is an extremely stressful experience for patients and it is associated with the manifestation of several psychological problems. To examine the effect of a group cognitive behavioral therapy (CBT) on the quality of life and emotional disturbance of women with breast cancer. Methods The study was a randomized controlled clinical trial. Samples were 48 women who had been diagnosed with breast cancer and had undergone mastectomy and chemotherapy. Study variables were measured before and after the intervention and 1 month after the end of the intervention as a follow-up. Controls received nothing and were just followed-up. Repeated measure ANOVAs were used to compare the effectiveness of the intervention on the study variables. Results The results of 32 women were analyzed. The increase in quality of life scores was significantly higher in the intervention group compared to the control group ( P  < 0.05). There were also significantly lower changes in the depression, anxiety, and stress scores of the intervention group ( P  < 0.05). However, the changes in the score of death anxiety were not significantly lower in the intervention group in comparison to controls ( P  > 0.05). Conclusion Group cognitive behavioral therapy was effective in the improvement of quality of life and decreases some aspects of emotional disturbance. Findings of this study suggest that women with breast cancer can benefit from group CBT. Yet, some aspects of the mental health of these women may need more attention and individualized methods. Trial registration ClinicalTrials.gov Identifier: IRCT20100911004728N4

Molecular signaling pathways involved in cancer have been intensively studied due to their crucial role in cancer cell growth and dissemination. Among them, zinc finger E-box binding homeobox-1 (ZEB1) and -2 (ZEB2) are molecules that play vital roles in signaling pathways to ensure the survival of tumor cells, particularly through enhancing cell proliferation, promoting cell migration and invasion, and triggering drug resistance. Importantly, ZEB proteins are regulated by microRNAs (miRs). In this review, we demonstrate the impact that miRs have on cancer therapy, through their targeting of ZEB proteins. MiRs are able to act as onco-suppressor factors and inhibit the malignancy of tumor cells through ZEB1/2 down-regulation. This can lead to an inhibition of epithelial-mesenchymal transition (EMT) mechanism, therefore reducing metastasis. Additionally, miRs are able to inhibit ZEB1/2-mediated drug resistance and immunosuppression. Additionally, we explore the upstream modulators of miRs such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), as these regulators can influence the inhibitory effect of miRs on ZEB proteins and cancer progression.

Background Although obesity increases the risk of hypertension, the effect of obesity based on metabolic status on the incidence of hypertension is not known. This study aimed to determine the association between obesity phenotypes including metabolically unhealthy obesity (MUO) and metabolically healthy obesity (MHO) and the risk of hypertension incidence. Methods We conducted a prospective cohort study on 6747 adults aged 35–65 from Ravansar non-communicable diseases (RaNCD) study. Obesity was defined as body mass index above 30 kg/m 2 and metabolically unhealthy was considered at least two metabolic disorders based on the International Diabetes Federation criteria. Obesity phenotypes were categorized into four groups including MUO, MHO, metabolically unhealthy non obesity (MUNO), and metabolically healthy non obesity (MHNO). Cox proportional hazards regression models were applied to analyze associations with hypertension incidence. Results The MHO (HR: 1.37; 95% CI: 1.03–1.86) and MUO phenotypes (HR: 2.44; 95% CI: 1.81–3.29) were associated with higher hypertension risk compared to MHNO. In addition, MUNO phenotype was significantly associated with risk of hypertension incidence (HR: 1.65; 95% CI: 1.29–2.14). Conclusions Both metabolically healthy and unhealthy obesity increased the risk of hypertension incidence. However, the increase in metabolically unhealthy phenotype was higher.