Targeted degradation of oncogenic BCR-ABL by silencing the gene of NEDD8 E3 ligase RAPSYN.

Tyrosine kinase inhibitors have been the standard treatment for patients with Philadelphia chromosome-positive (Ph+) leukemia. However, a series of issues, including drug resistance, relapse and intolerance, are still an unmet medical need. Here, we report the targeted siRNA-based lipid nanoparticles in Ph+ leukemic cell lines for gene therapy of Ph+ leukemia, which specifically targets a recently identified NEDD8 E3 ligase RAPSYN in Ph+ leukemic cells to disrupt the neddylation of oncogenic BCR-ABL. To achieve the specificity for Ph+ leukemia therapy, a single-chain fragment variable region (scFv) of anti-CD79B monoclonal antibody was covalently conjugated on the surface of OA2-siRAPSYN lipid nanoparticles to generate the targeted lipid nanoparticles (scFv-OA2-siRAPSYN). Through effectively silencing RAPSYN gene in leukemic cell lines by the nanoparticles, BCR-ABL was remarkably degraded accompanied by the inhibition of proliferation and the promotion of apoptosis. The specific targeting, therapeutic effects and systemic safety were further evaluated and demonstrated in cell line-derived mouse models. The present study has not only addressed the clinical need of Ph+ leukemia, but also enabled gene therapy against a less druggable target.

Reconstruction of all-weather land surface temperature based on a combined physical and data-driven model.

At present, the remote sensing (RS) thermal infrared (TIR) images that are commonly used to obtain land surface temperature (LST) are contaminated by clouds and thus cannot obtain spatiotemporal integrity of LST. To solve this problem, this study combined a physical model with strong interpretability with a data-driven model with high data adaptability. First, the physical model (Weather Research and Forecast (WRF) model) was used to generate LST source data. Then, combined with multisource RS data, a data-driven method (random forest (RF)) was used to improve the accuracy of the LST, and a model framework for a data-driven auxiliary physical model was formed. Finally, all-weather MODIS-like data with a spatial resolution of 1 km were generated. Beijing, China, was used as the study area. The results showed that in cases of more clouds and fewer clouds, the reconstructed all-weather LST had a high spatial continuity and could restore the spatial distribution details of the LST well. The mean absolute error (MAE), root mean square error (RMSE), and correlation coefficient (ρ) in the case of more (fewer) clouds were ranked as follows: MAE < 1 K (< 2 K), RMSE < 2 K (< 2 K), and ρ > 0.9. The errors obeyed an approximately normal distribution. The total MAE, RMSE, and ρ were 0.80 K, 1.09 K, and 0.94 K, respectively. Generally, the LST reconstructed in this paper had a high accuracy, and the model could provide all-weather MODIS-like LST to compensate for the disadvantages of satellite TIR images (i.e., contamination by clouds and inability to obtain complete LST values).

Spatiotemporal distribution characteristics of ecosystem health and the synergetic impact of its driving factors in the Yangtze River Delta, China.

In recent years, . the rapid development of the Yangtze River Delta in China has led to increasingly serious regional eco-environmental problems. Therefore, it is of great significance for the construction of ecological civilization to study the ecosystem health in the Yangtze River Delta. In this paper, the assessment framework of "Vigor-Organization-Resilience" was used to assess the ecosystem health index (EHI) of the Yangtze River Delta from 2000 to 2020, and then the spatial autocorrelation method was used to analyze the agglomeration of EHI in 314 counties in this region. Finally, the eXtreme Gradient Boosting (XGBoost) model and the SHapley Additive exPlanation (SHAP) model were combined to explore the synergistic impact of EHI driving factors. The results show that (1) from 2000 to 2020, the EHI in the Yangtze River Delta is at the level of ordinary health, and gradually decreased; (2) the EHI has significant spatial positive correlation and aggregation; (3) the driving factors in descending order of importance are urbanization level (UL), precipitation (PRE), PM2.5 (PM), normalized difference vegetation index (NDVI), and temperature (TEMP); and (4) the relationship between UL and EHI is logarithmic; PRE and EHI are quartic polynomial; PM, NDVI, TEMP, and EHI are quadratic polynomial. The results of this paper are of great significance to the management and restoration of the ecosystem in this region.

Reprogrammed siTNFα/neutrophil cytopharmaceuticals targeting inflamed joints for rheumatoid arthritis therapy.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by severe synovial inflammation and cartilage damage. Despite great progress in RA therapy, there still lacks the drugs to completely cure RA patients. Herein, we propose a reprogrammed neutrophil cytopharmaceuticals loading with TNFα-targeting-siRNA (siTNFα) as an alternative anti-inflammatory approach for RA treatment. The loaded siTNFα act as not only the gene therapeutics to inhibit TNFα production by macrophages in inflamed synovium, but also the editors to reprogram neutrophils to anti-inflammatory phenotypes. Leveraging the active tendency of neutrophils to inflammation, the reprogrammed siTNFα/neutrophil cytopharmaceuticals (siTNFα/TP/NEs) can rapidly migrate to the inflamed synovium, transfer the loaded siTNFα to macrophages followed by the significant reduction of TNFα expression, and circumvent the pro-inflammatory activity of neutrophils, thus leading to the alleviated synovial inflammation and improved cartilage protection. Our work provides a promising cytopharmaceutical for RA treatment, and puts forward a living neutrophil-based gene delivery platform.

Single-component lipid nanoparticles for engineering SOCS1 gene-silenced dendritic cells to boost tumor immunotherapy.

Dendritic cells (DCs) that can prime antitumor responses show great potential in tumor immunotherapy, whereas the unsatisfactory effect which can be ascribed in part to the high expression of inhibitory cytokines, such as the suppressor of cytokine signaling 1 (SOCS1), restricts their application. Thus, silencing these genes in DCs is essential for DC-based therapy. However, safe and effective delivery of siRNA to DCs still faces challenges. Herein, we designed single-component lipid nanoparticles comprising a solely cationic lipid (OA2) for introducing siRNA into mouse DCs in order to inhibit the immunosuppressive gene and boost the effector responses of DC-based therapy. Compared to other multi-component lipid nanoparticles, single-component lipid nanoparticles are theoretically easy-to-control and detective, which is beneficial for future translation. We showed that the application of OA2 lipid nanoparticles significantly downregulated the expression of SOCS1 in DCs over 50%, compared with the commercial lipofectine2000. Besides, the treatment of OA2 lipid nanoparticles had no influence on the antigen capture of DCs. Thus, we fabricated a SOCS1-downregulated DC vaccine pulsed with Ova antigen and demonstrated that the antigen presentation and pro-inflammatory factor secretion ability of DCs were improved due to the SOCS1 downregulation, leading to an ameliorated immunosuppressive tumor microenvironment and finally exhibiting potent tumor prevention and suppression in B16-Ova tumor-bearing mice. Single-component lipid nanoparticles, which provide an available vector platform for siRNA delivery to primary DCs, appear to be a potent tool to engineer DCs and in turn boost DC-based tumor immunotherapy.

Modular synthesis of amphiphilic chitosan derivatives based on copper-free click reaction for drug delivery.

Amphiphilic chitosan derivatives have attracted wide attention as drug carriers due to their physicochemical properties. However, obtaining a desired amphiphilic chitosan derivative by tuning the various functional groups was complex and time-consuming. Therefore, a facile and common synthesis strategy would be promising. In this study, a modular strategy based on strain-promoted azide-alkyne cycloaddition (SPAAC) click reaction was designed and applied in synthesizing deoxycholic acid- or octanoic acid-modified N-azido propionyl-N,O-sulfate chitosan through tuning the hydrophobic groups. Additionally, chitosan derivatives with the same substitute groups were prepared via amide coupling as controls. We demonstrated that these derivates via the two strategies showed no obvious difference in physicochemical properties, drug loading ability and biosafety, indicating the feasibility of modular strategy. Notably, the modular strategy exhibited advantages including high reactivity, flexibility and reproducibility. We believe that this modular strategy could provide varied chitosan derivatives in an easy and high-efficiency way for improving multifunctional drug carriers.

Spatial and temporal changes in ecosystem service values in karst areas in southwestern China based on land use changes.

Ecological restoration projects have great impacts on ecosystem service values (ESVs) in China. However, it is still unclear how the temporal and spatial characteristics of ESVs in karst areas in southwestern China changed before and after the implementation of some ecological restoration projects. Land use data from five phases between 1980 and 2018 were used in combination with socioeconomic data of karst areas in southwestern China. The equivalent factor method and spatial, autocorrelation analysis method were used to study the temporal and spatial distributions of ESVs. The results show that (1) the conversion of land use types mainly consisted of the conversion of cultivated lands to woodlands, grasslands, and water areas, and from grasslands to woodlands, construction lands, and wetlands; (2) from 1980 to 2018, the overall trend of ESVs in the study area first decreased and then increased; the ESVs increased by 19.62 billion yuan, with a growth rate of 0.35%, and changes in water areas were the main reason for the ESVs increase, while changes in the areas of woodlands and wetlands were the second reason for the ESVs increase; (3) in terms of its spatial distribution, the ESVs was higher in the southwest direction, while in other areas, from west to east, the ESVs generally showed a spatial distribution pattern of "high-low-high-low"; and (4) the ESVs in the study area had significant, positive autocorrelations in its spatial distribution from 1980 to 2018. The spatial aggregation of ESVs among cities mainly included aggregations of spatially similar values. The results of this study provide reference data for ecological infrastructure construction and ecological-economic development in karst areas in southwestern China.

In vitro anti-tumor effect of mGM-CSF-GnRH3 and mGM-CSF-GRP6 recombinant fusion protein and theirbioinformatics prediction / 中国肿瘤生物治疗杂志

@#Objective: To prepare the fusion protein mGM-CSF-GnRH3 (mGGn) of mouse granulocyte-macrophage colony stimulating factor (mGM-CSF) combining with gonadotropin releasing hormone (GnRH) and the fusion protein mGM-CSF-GRP6 (mG6) of mGM-CSF combining with gastrin-releasing peptide (GRP), and to investigate the inhibitory effect of the above two fusion proteins on B16F10 melanoma in vitro as well as to preliminarily predict their isoelectric point, relative molecular weight, hydrophobicity, stability, subcellular localization, signal peptide, spatial structure and potential epitopes. Methods:After the successful preparation of mGGn and mG6, the effects of different concentrations of fusion proteins on tumor cell morphology, migration, proliferation and cell cycle were detected by microscopic observation, scratch test, CCK-8 method and flow cytometry, respectively. The protein online analysis systems EXPASY, GOR4, SWISS MODEL were used to predict the basic properties and secondary/tertiary structure of recombinant fusion proteins. The B cell epitopes were predicted by IEDB and ABCpred software, the CTL epitopes were comprehensively predicted by SYFPEITHI, BlMAS and NetCTL software, and the Th epitopes were predicted by NetMHCIIpan 3.1 Server and IEDB software. Results:Both mGGn and mG6 inhibited the migration and proliferation of tumor cells. mGGn could block B16F10 cell cycle at G1 phase while mG6 could block B16F10 cell cycle at S phase, all of which prevented cells entering into G2 phase to inhibit tumor cell growth. The mGGn and mG6 fusion proteins got diverse structures and had multiple potential B epitopes, CTL epitopes and Th epitopes. Conclusion: mGGn and mG6 have inhibitory effect on B16F10 melanoma in vitro, and bioinformatics predictions have laid a foundation for further study of the biological functions and immunological activities of these fusion proteins.