Conventional anti-angiogenic cancer therapy is frequently undermined by adaptive tumor hypoxia and the consequent establishment of an immunosuppressive microenvironment, which together drive therapeutic resistance. To overcome this limitation, we engineered a tumor-targeted nano-platform (Reg@CeO2@HA) that co-delivers low-dose regorafenib with enzymatically versatile cerium oxide nanoparticles. This system concurrently normalizes tumor vasculature, scavenges pathological reactive oxygen species, and alleviates hypoxia—collectively reprogramming the immunosuppressive tumor landscape. Mechanistically, the platform could downregulate PD-L1 expression, reduce infiltration of M2-polarized tumor-associated macrophages, and attenuate myeloid-derived suppressor cell-mediated T-cell exhaustion. Furthermore, it could induce immunogenic cell death, thereby priming a systemic anti-tumor immune response. In combination with PD-L1 blockade, Reg@CeO2@HA could elicit potent synergistic efficacy, marked by robust CD8+ T-cell infiltration and profound tumor suppression. Taken together, the present study established a novel therapeutic paradigm that concurrently addresses vascular abnormality and immune dysfunction within the TME. This integrated nano-strategy could not only overcome the key limitations of conventional anti-angiogenic therapy but also provide a versatile and potent approach to sensitize osteosarcoma and other immunologically cold solid tumors to immunotherapy.
Zili Lin, Qing Liu, Xiangyao Li et al.· Materials Today Bio· 0 citations
In Industrial Internet of Things (IIoT) deployments, mobile edge computing (MEC) offloads computation-intensive tasks, a constrained biobjective problem trading time delay against energy consumption (MTOP). We show that this benchmark is exactly separable across micro base-station (MiBS) regions: its delay and energy objectives are additive over regions, and the only coupling, intra-cell interference, stays within a region. Exploiting this, we propose CR-MTMEMTO-D, a structure-aware decomposition multitasking method that treats each region as an independent subtask, solves it with a feasibility-repaired NSGA-II, and reconstructs the global feasible Pareto front as the non-dominated subset of the Minkowski sum of the regional fronts, an exact composition that adds no global evaluations. Across 12 instances (45–432 variables, 20 seeds), it attains the best hypervolume and IGD on every instance (mean HV 0.9340 vs. 0.8021 for a plain NSGA-II baseline; average rank 1.00), with the margin widening as the problem scales, and it is unchanged under total-evaluation matching because every evaluation is a regional main task. A feasibility-priority acceptance gate keeps the population fully feasible. Under matched budgets, a prior cheap-task pool with bandit-controlled transfer adds no significant gain, which motivates the structural approach.