As a new carbon-based nanomaterial, graphene has exhibited unique advantages in significantly improving the combination properties of traditional polymer hydrogels. The specific properties of graphene, such as high electrical conductivity, high thermal conductivity and excellent mechanical properties, have made graphene not only a gelator to self-assemble into the graphene-based hydrogels (GBH) with extraordinary electromechanical performance, but also a filler to blend with small molecules and macromolecules for the preparation of multifunctional GBH. It fully exploits the practical applications of traditional hydrogels. This review summarizes the preparation methods, properties, and the applications of GBH. Further developments and challenges of GBH are also prospected.

Probability forecasts in complex environments can benefit from combining the estimates of large groups of forecasters (“judges”). But aggregating multiple opinions raises several challenges. First, human judges are notoriously incoherent when their forecasts involve logically complex events. Second, individual judges may have specialized knowledge, so different judges may produce forecasts for different events. Third, the credibility of individual judges might vary, and one would like to pay greater attention to more trustworthy forecasts. These considerations limit the value of simple aggregation methods like unweighted linear averaging. In this paper, a new algorithm is proposed for combining probabilistic assessments from a large pool of judges, with the goal of efficiently implementing the coherent approximation principle (CAP) while weighing judges by their credibility. Two measures of a judge's likely credibility are introduced and used in the algorithm to determine the judge's weight in aggregation. As a test of efficiency, the algorithm was applied to a data set of nearly half a million probability estimates of events related to the 2008 U.S. presidential election (∼16,000 judges). Compared with unweighted scalable CAP algorithms, the proposed weighting schemes significantly improved the stochastic accuracy with a comparable run time, demonstrating the efficiency and effectiveness of the weighting methods for aggregating large numbers and varieties of forecasts.

Severe multidrug resistance (MDR) often develops in the process of chemotherapy for most small molecule anticancer drugs, which results in clinical chemotherapy failures.Methods: Here, a nanodrug is constructed through the self-assembly of amphiphilic drug-inhibitor conjugates (ADIC) containing a redox-responsive linkage for reversing the multidrug resistance (MDR) in cancer treatment. Specifically, hydrophilic anticancer irinotecan (Ir) and hydrophobic P-gp protein inhibitor quinine (Qu) are linked by a redox responsive bridge for overcoming MDR of tumors.Results: Ir-ss-Qu is able to self-assemble into nanoparticles (NPs) in water and shows the longer blood retention half-life compared with that of free Ir or Qu, which facilitates drug accumulation in tumor site. After endocytosis of Ir-ss-Qu NPs by drug-resistant tumor cells, the disulfide bond in the linkage between Ir and Qu is cleaved rapidly induced by glutathione (GSH) to release anticancer drug Ir and inhibitor Qu synchronously. The released Qu can markedly reduce the expression of P-gp in drug-resistant tumor cells and inhibits P-gp to pump Ir out of the cells. The increased concentration of intracellular Ir can effectively improve the therapeutic efficacy.Conclusions: Such redox-responsive Ir-ss-Qu NPs, as a drug delivery system, exhibit very high cytotoxicity and the most effective inhibitory to the growth of drug-resistant breast cancer compared with that of free therapeutic agents in vitro and in vivo.

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