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Therapeutics, based on small interfering RNA (siRNA), have demonstrated tremendous potential for treating cancer. However, issues such as non-specific targeting, premature degradation, and the intrinsic toxicity of the siRNA, have to be solved before they are ready for use in translational medicines. To address these challenges, nanotechnology-based tools might help to shield siRNA and ensure its specific delivery to the target site. Besides playing a crucial role in prostaglandin synthesis, the cyclo-oxygenase-2 (COX-2) enzyme has been reported to mediate carcinogenesis in various types of cancer, including hepatocellular carcinoma (HCC). We encapsulated COX-2-specific siRNA in Bacillus subtilis membrane lipid-based liposomes (subtilosomes) and evaluated their potential in the treatment of diethylnitrosamine (DEN)-induced hepatocellular carcinoma. Our findings suggested that the subtilosome-based formulation was stable, releasing COX-2 siRNA in a sustained manner, and has the potential to abruptly release encapsulated material at acidic pH. The fusogenic property of subtilosomes was revealed by FRET, fluorescence dequenching, content-mixing assay, etc. The subtilosome-based siRNA formulation was successful in inhibiting TNF-α expression in the experimental animals. The apoptosis study indicated that the subtilosomized siRNA inhibits DEN-induced carcinogenesis more effectively than free siRNA. The as-developed formulation also suppressed COX-2 expression, which in turn up-regulated the expression of wild-type p53 and Bax on one hand and down-regulated Bcl-2 expression on the other. The survival data established the increased efficacy of subtilosome-encapsulated COX-2 siRNA against hepatocellular carcinoma.

Function as a Service (FaaS) is highly beneficial to smart city infrastructure due to its flexibility, efficiency, and adaptability, specifically for integration in the digital landscape. FaaS has serverless setup, which means that an organization no longer has to worry about specific infrastructure management tasks; the developers can focus on how to deploy and create code efficiently. Since FaaS aligns well with the IoT, it easily integrates with IoT devices, thereby making it possible to perform event-based actions and real-time computations. In our research, we offer an exclusive likelihood-based model of adaptive machine learning for identifying the right place of function. We employ the XGBoost regressor to estimate the execution time for each function and utilize the decision tree regressor to predict network latency. By encompassing factors like network delay, arrival computation, and emphasis on resources, the machine learning model eases the selection process of a placement. In replication, we use Docker containers, focusing on serverless node type, serverless node variety, function location, deadlines, and edge-cloud topology. Thus, the primary objectives are to address deadlines and enhance the use of any resource, and from this, we can see that effective utilization of resources leads to enhanced deadline compliance. [ABSTRACT FROM AUTHOR]

Copyright of Al-Mustansiriyah Journal for Pharmaceutical Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)