Dexamethasone is a glucocorticoid steroid with anti-inflammatory properties used to treat many diseases, including cancer, in which it helps manage various side effects of chemo-, radio-, and immunotherapies. Here, we investigate the tumor microenvironment (TME)-normalizing effects of dexamethasone in metastatic murine breast cancer (BC). Dexamethasone normalizes vessels and the extracellular matrix, thereby reducing interstitial fluid pressure, tissue stiffness, and solid stress. In turn, the penetration of 13 and 32 nm dextrans, which represent nanocarriers (NCs), is increased. A mechanistic model of fluid and macromolecule transport in tumors predicts that dexamethasone increases NC penetration by increasing interstitial hydraulic conductivity without significantly reducing the effective pore diameter of the vessel wall. Also, dexamethasone increases the tumor accumulation and efficacy of ∼30 nm polymeric micelles containing cisplatin (CDDP/m) against murine models of primary BC and spontaneous BC lung metastasis, which also feature a TME with abnormal mechanical properties. These results suggest that pretreatment with dexamethasone before NC administration could increase efficacy against primary tumors and metastases.

Convex relaxations, Global optimization, Optimal control, 49M20, 90C26,

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A method is presented for guaranteeing robust steady-state operation of chemical processes using a model-based approach, taking into account uncertainty in the model parameters and disturbances in the process inputs. Intractable constrained max-min optimisation formulations have been proposed for this problem in the past. A new approach is presented in which the equality constraints (process model equations) are solved numerically for the process variables as implicit functions of the uncertain parameters and controls. The problem is then formulated as a semi-infinite program (SIP) constrained only by the performance specifications as semi-infinite inequality constraints. A rigorous, finite ε-optimal convergent algorithm for solving such SIPs is proposed, making no assumptions on convexity, which makes use of the novel developments of parametric interval-Newton methods for bounding implicit functions, and novel developments in McCormick relaxations of algorithms.

No abstract