Tumor microenvironment-responsive spherical nucleic acid nanoparticles for enhanced chemo-immunotherapy.

Certain chemotherapeutics can induce tumor cells' immunogenic cell death (ICD), release tumor antigens, and thereby trigger personalized antitumor immune responses. Co-delivery of adjuvants using nanocarriers could amplify the ICD-induced tumor-specific immunity achieving a synergistic chemo-immunotherapeutic effect. However, complicated preparation, low drug loading efficiency, and potential carrier-associated toxicity are the major challenges that limited its clinical applications. Herein, a carrier-free core-shell nanoparticle (MPLA-CpG-sMMP9-DOX, MCMD NPs) was constructed by facile self-assembly of spherical nucleic acids (SNA) with two adjuvants of CpG ODN and monophosphoryl lipid A (MPLA) as a core and doxorubicin (DOX) radially around the dual-adjuvants SNA as a shell. The results demonstrated that MCMD NPs could enhance drugs accumulation in tumors, and release DOX upon enzymatic degradation of matrix metalloproteinase-9 (MMP-9) peptide in the tumor microenvironment (TME), which enhanced the direct-killing effect of DOX on tumor cells. The core of MPLA-CpG SNA efficiently boosted the ICD-induced antitumor immune response to further attack tumor cells. Thus, MCMD NPs achieved a synergistic therapeutic effect of chemo-immunotherapy with reduced off-target toxicity. This study provided an efficient strategy for the development of a carrier-free nano-delivery system for enhanced cancer chemo-immunotherapy.

Identification of the heavy metal pollution sources in the rhizosphere soil of farmland irrigated by the Yellow River using PMF analysis combined with multiple analysis methods-using Zhongwei city, Ningxia, as an example.

In recent years, with the frequent occurrences of heavy metal (HM) pollution in agriculture, the problem of HM pollution in farmland soil, especially in the areas irrigation by the Yellow River, has been attracted increasing attention because of the complex sources of pollution. Qualitative identification of pollution sources and quantification of their contributions to HMs in soil are the key links in the prevention and control of HM pollution. The contents of 11 heavy metals (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sn, V, and Zn) in the rhizosphere soil of the Ningxia irrigation area were determined by inductively coupled plasma mass spectrometry (ICP-MS). Multiple methods were used for source identification, including positive matrix factorization (PMF) analysis combined with multiple other analyses (single factor index method (Pi), coefficient of variation(CV), correlation analysis(CA), enrichment factor(EF), and principal component analysis(PCA)). The results showed that (1) the over-standard rates of As, Cd, Cr, Mn, Pb, Sn, and Zn in the study area were 100%, of which Cd was seriously polluted, while As, Zn, and Sn were moderately polluted. (2) The HM contributions from irrigation and silt soil formed by the Yellow River sediment were the highest (42.45%), followed by the smelting industry and traffic pollution (16.06%). (3) The contribution of agricultural pollution to HMs in the region was 15.54%, in which As was mainly from pesticides and Cd was mainly from fertilizers.

Quantitative source identification and apportionment of heavy metals under two different land use types: comparison of two receptor models APCS-MLR and PMF.

At present, many researchers are increasingly aware of the importance of using models to identify heavy metal (HM) pollution sources. However, on the performance and application of different source identification models to HMs under different land use types had been studied little. In this study, comparison of absolute principal component scores-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models and their application characteristics in identifying pollution sources were carried out by using 11 HMs in Zhongwei City farmland and Shizuishan industrial park, Ningxia. The results indicated that HM pollution in farmland mainly came from pesticides, fertilizers, and deposition of the Yellow River, while the pollution in industrial park mainly originated from atmospheric deposition and various industrial productions. The APCS-MLR model had the problem of less identification sources and the difficulty to explain the complex pollution, while the PMF model not only identified more pollution sources, but also distinguished heavy metal-related sources for two different land use types and different industrial production conditions. It is of great significance the formulation of agricultural-related pesticides' and chemical fertilizers' rational use and various industrial production-related raw materials put in and emission control strategies.