The basic objective of this work was to study the effect of model cationic drug metformin HCl on swelling and erosion and, in turn, the release of KCl and drug itself, from the kappa-carrageenan matrices. Water uptake by the matrix up to 2 hours was found to increase with KCl concentration from the plain matrix. Erosion was not affected by concentration of KCl. Incorporation of drug favors water uptake, but in presence of KCl it was found to be reduced. Drug-containing matrices have shown higher release of KCl as compared with plain batches. Drug release was retarded as KCl concentration increased up to 5%, above which the reduced cohesivity of the matrix caused increase in drug release.

Brain tumors are a widespread and serious neurological phenomenon that can be life- threatening. The computing field has allowed for the development of artificial intelligence (AI), which can mimic the neural network of the human brain. One use of this technology has been to help researchers capture hidden, high-dimensional images of brain tumors. These images can provide new insights into the nature of brain tumors and help to improve treatment options. AI and precision medicine (PM) are converging to revolutionize healthcare. AI has the potential to improve cancer imaging interpretation in several ways, including more accurate tumor genotyping, more precise delineation of tumor volume, and better prediction of clinical outcomes. AI-assisted brain surgery can be an effective and safe option for treating brain tumors. This review discusses various AI and PM techniques that can be used in brain tumor treatment. These new techniques for the treatment of brain tumors, i.e., genomic profiling, microRNA panels, quantitative imaging, and radiomics, hold great promise for the future. However, there are challenges that must be overcome for these technologies to reach their full potential and improve healthcare.

No abstract

No abstract

No abstract