Search

Multidrug resistance (MDR) promotes tumor recurrence and metastasis and heavily reduces anticancer efficiency, which has become a primary reason for the failure of clinical chemotherapy. The mechanisms of MDR are so complex that conventional chemotherapy usually fails to achieve an ideal therapeutic effect and even accelerates the occurrence of MDR. In contrast, the combination of chemotherapy with dual-drug has significant advantages in tumor therapy. A novel dual-drug codelivery nanosystem, which combines dual-drug administration with nanotechnology, can overcome the application limitation of free drugs. Both the characteristics of nanoparticles and the synergistic effect of dual drugs contribute to circumventing various drug-resistant mechanisms in tumor cells. Therefore, developing dual-drug codelivery nanosystems with different multidrug-resistant mechanisms has an important reference value for reversing MDR and enhancing the clinical antitumor effect. In this review, the advantages, principles, and common codelivery nanocarriers in the application of dual-drug codelivery systems are summarized. The molecular mechanisms of MDR and the dual-drug codelivery nanosystems designed based on different mechanisms are mainly introduced. Meanwhile, the development prospects and challenges of codelivery nanosystems are also discussed, which provide guidelines to exploit optimized combined chemotherapy strategies in the future.

Source tracing of heavy metals in agricultural soils is of critical importance for effective pollution control and targeting policies. It is a great challenge to identify and apportion the complex sources of soil heavy metal pollution. In this study, a traditional analysis method, positive matrix fraction (PMF), and three machine learning methodologies, including self-organizing map (SOM), conditional inference tree (CIT) and random forest (RF), were used to identify and apportion the sources of heavy metals in agricultural soils from Lianzhou, Guangdong Province, China. Based on PMF, the contribution of the total loadings of heavy metals in soil were 19.3% for atmospheric deposition, 65.5% for anthropogenic and geogenic sources, and 15.2% for soil parent materials. Based on SOM model, As, Cd, Hg, Pb and Zn were attributed to mining and geogenic sources; Cr, Cu and Ni were derived from geogenic sources. Based on CIT results, the influence of altitude on soil Cr, Cu, Hg, Ni and Zn, as well as soil pH on Cd indicated their primary origin from natural processes. Whereas As and Pb were related to agricultural practices and traffic emissions, respectively. RF model further quantified the importance of variables and identified potential control factors (altitude, soil pH, soil organic carbon) in heavy metal accumulation in soil. This study provides an integrated approach for heavy metals source apportionment with a clear potential for future application in other similar regions, as well as to provide the theoretical basis for undertaking management and assessment of soil heavy metal pollution.

In the original article [...]