Cell-free DNA (cfDNA) released from damaged or dead cells combines with LL37 and is converted into an immune response activator to exacerbate psoriasis. Here, we show that cationic nanoparticles (cNPs) efficiently compete for DNA from the DNA-LL37 immunocomplex and inhibit DNA-LL37-induced cell activation. Using phenotypical images, psoriasis area and severity index scoring, histology, and immunohistochemical analysis, we demonstrate that topical application of cNPs on psoriasiform skin of a mouse model relieves psoriatic symptoms. It is noteworthy that the results were confirmed in a cynomolgus monkey model. Moreover, topically administrated cNPs showed low in vivo toxicity because of their retention in skin. Mechanistic analyses of cytokine expression in the psoriatic site, cfDNA levels in circulation and inflamed skin, skin permeation, and biodistribution of cNPs also matched the therapeutic outcomes. Therefore, we present a previously unidentified strategy of nanomedicine to treat skin inflammatory diseases, which demonstrates great potential for clinical application.
Drainage networks are the basis for segmentation of watersheds, an essential component in hydrological modelling, biogeochemical applications, and resource management plans. With the rapidly increasing availability of topographic information as digital elevation models (DEMs), there have been many studies on DEM‐based drainage network extraction algorithms. Most of traditional drainage network extraction methods require preprocessing of the DEM in order to remove “spurious” sink, which can cause unrealistic results due to removal of real sinks as well. The least cost path (LCP) algorithm can deal with flow routing over sinks without altering data. However, the existing LCP implementations can only simulate either single flow direction or multiple flow direction over terrain surfaces. Nevertheless, terrain surfaces in the real world are usually very complicated including both convergent and divergent flow patterns. The triangular form‐based multiple flow (TFM) algorithm, one of the traditional drainage network extraction methods, can estimate both single flow and multiple flow patterns. Thus, in this paper, it is proposed to combine the advantages of the LCP algorithm and the TFM algorithm in order to improve the accuracy of drainage network extraction from the DEM. The proposed algorithm is evaluated by implementing a data‐independent assessment method based on four mathematical surfaces and validated against “true” stream networks from aerial photograph, respectively. The results show that when compared with other commonly used algorithms, the new algorithm provides better flow estimation and is able to estimate both convergent and divergent flow patterns well regarding the mathematical surfaces and the real‐world DEM.
River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (F DOC ) and DOC concentrations (C DOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine C DOC and F DOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average C DOC was 2.25 ± 0.45 mg/L and average F DOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in F DOC (+0.044 Tg/year 2 , p = .01), but little change in C DOC (−0.001 mg/L/year, p > .10). Although the trend in C DOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (−0.043 and −0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of F DOC and C DOC across China. However, and in contrast with other basins, the significant increase in C DOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving F DOC , the increase in F DOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.
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