Data-driven spatio-temporal modelling of glioblastoma.

Mathematical oncology provides unique and invaluable insights into tumour growth on both the microscopic and macroscopic levels. This review presents state-of-the-art modelling techniques and focuses on their role in understanding glioblastoma, a malignant form of brain cancer. For each approach, we summarize the scope, drawbacks and assets. We highlight the potential clinical applications of each modelling technique and discuss the connections between the mathematical models and the molecular and imaging data used to inform them. By doing so, we aim to prime cancer researchers with current and emerging computational tools for understanding tumour progression. By providing an in-depth picture of the different modelling techniques, we also aim to assist researchers who seek to build and develop their own models and the associated inference frameworks. Our article thus strikes a unique balance. On the one hand, we provide a comprehensive overview of the available modelling techniques and their applications, including key mathematical expressions. On the other hand, the content is accessible to mathematicians and biomedical scientists alike to accommodate the interdisciplinary nature of cancer research.

Bisphosphosphonate-calcium phosphate cement composite and its properties.

Calcium phosphate cement (CPC) has been studied extensively due to its bioactivity and biodegradability. CPC is typically made by a combination of multiple calcium phosphates that form a paste that sets and hardens in the body after being combined with either water or an aqueous solution. It is highly moldable and easily manipulated, and CPCs possess osteoconductive properties. Due to these characteristics, CPCs offer great promise in bone grafting applications. CPC combined with drugs has a great potential as drug delivery system and has been studied extensively. In this review we have focused on Bisphosphonate-CPC drug delivery system. In addition, we introduce and discuss the potential of studying other bisphosphonates.

Site-specific chelation therapy with EDTA-loaded albumin nanoparticles reverses arterial calcification in a rat model of chronic kidney disease.

Medial arterial calcification (MAC) is a common outcome in diabetes and chronic kidney disease (CKD). It occurs as linear mineral deposits along the degraded elastin lamellae and is responsible for increased aortic stiffness and subsequent cardiovascular events. Current treatments for calcification, particularly in CKD, are predominantly focused on regulating the mineral disturbance and other risk factors. Ethylene diamine tetraacetic acid (EDTA), a chelating agent, can resorb mineral deposits, but the systemic delivery of EDTA may cause side effects such as hypocalcemia and bone resorption. We have developed elastin antibody conjugated albumin nanoparticles that target only degraded elastin in vasculature while sparing healthy tissues. In this study, we tested a targeted nanoparticle-based EDTA chelation therapy to reverse CKD-associated MAC. Renal failure was induced in Sprague-Dawley rats by a high adenine diet supplemented by high P and Ca for 28 days that led to MAC. Intravenous delivery of DiR dye-loaded nanoparticles confirmed targeting to vascular degraded elastin and calcification sites within 24 hours. Next, EDTA-loaded albumin nanoparticles conjugated with an anti-elastin antibody were intravenously injected twice a week for two weeks. The targeted nanoparticles delivered EDTA at the site of vascular calcification and reversed mineral deposits without any untoward effects. Systemic EDTA injections or blank nanoparticles were ineffective in reversing MAC. Reversal of calcification seems to be stable as it did not return after the treatment was stopped for an additional four weeks. Targeted EDTA chelation therapy successfully reversed calcification in this adenine rat model of CKD. We consider that targeted NP therapy will provide an attractive option to reverse calcification and has a high potential for clinical translation.