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Flash floods are considered to be one of the most destructive natural hazards, and they are difficult to accurately model and predict. In this study, three hybrid models were proposed, evaluated, and used for flood susceptibility prediction in the Dadu River Basin. These three hybrid models integrate a bivariate statistical method of the fuzzy membership value (FMV) and three machine learning methods of support vector machine (SVM), classification and regression trees (CART), and convolutional neural network (CNN). Firstly, a geospatial database was prepared comprising nine flood conditioning factors, 485 flood locations, and 485 non-flood locations. Then, the database was used to train and test the three hybrid models. Subsequently, the receiver operating characteristic (ROC) curve, seed cell area index (SCAI), and classification accuracy were used to evaluate the performances of the models. The results reveal the following: (1) The ROC curve highlights the fact that the CNN-FMV hybrid model had the best fitting and prediction performance, and the area under the curve (AUC) values of the success rate and the prediction rate were 0.935 and 0.912, respectively. (2) Based on the results of the three model performance evaluation methods, all three hybrid models had better prediction capabilities than their respective single machine learning models. Compared with their single machine learning models, the AUC values of the SVM-FMV, CART-FMV, and CNN-FMV were 0.032, 0.005, and 0.055 higher; their SCAI values were 0.05, 0.03, and 0.02 lower; and their classification accuracies were 4.48%, 1.38%, and 5.86% higher, respectively. (3) Based on the results of the flood susceptibility indices, between 13.21% and 22.03% of the study area was characterized by high and very high flood susceptibilities. The three hybrid models proposed in this study, especially CNN-FMV, have a high potential for application in flood susceptibility assessment in specific areas in future studies.

Renal fibrosis is the common feature of all progressive kidney diseases and exerts great burden on public health worldwide. The maladaptive repair mechanism of tubular epithelial cells, an important mediator of renal fibrogenesis, manifests with partial epithelial–mesenchymal transition (EMT) and cell cycle arrest. The aim of this study is to investigate the possible correlation between partial EMT and cell cycle arrest, and elucidate the underlying mechanism. We examined human kidney allograft samples with interstitial fibrosis and three mice renal fibrosis models, unilateral ureter obstruction (UUO), ischemia–reperfusion injury, and Adriamycin nephropathy. The partial EMT process and p53–p21 axis were elevated in both human allograft with interstitial fibrosis, as well as three mice renal fibrosis models, and showed a time-dependent increase as fibrosis progressed in the UUO model. Snai1 controlled the partial EMT process, and led to parallel changes in renal fibrosis, G2/M arrest, and inflammation. p53–p21 axis arrested cell cycle at G2/M, and prompted partial EMT and fibrosis together with inflammation. NF-κB inhibitor Bay11-7082 disrupted the reciprocal loop between Snai1-induced partial EMT and p53–p21-mediated G2/M arrest. We demonstrated the reciprocal loop between partial EMT and G2/M arrest of TECs during renal fibrogenesis and revealed NF-κB-mediated inflammatory response as the underlying mechanism. This study suggests that targeting NF-κB might be a plausible therapeutic strategy to disrupt the reciprocal loop between partial EMT and G2/M arrest, therefore alleviating renal fibrosis.

Ferroptosis is a newly identified iron-dependent form of death that is becoming increasingly recognized as a promising avenue for cancer therapy. N6-methyladenosine (m 6 A) is the most abundant reversible methylation modification in mRNA contributing to tumorigenesis. However, the crucial role of m 6 A modification in regulating ferroptosis during colorectal cancer (CRC) tumorigenesis remains elusive. Herein, we find that m 6 A modification is increased during ferroptotic cell death and correlates with the decreased m 6 A demethylase fat mass and obesity-associated protein (FTO) expression. Functionally, we demonstrate that suppressing FTO significantly induces CRC ferroptotic cell death, as well as enhancing CRC cell sensitivity to ferroptosis inducer (Erastin and RSL3) treatment. Mechanistically, high FTO expression increased solute carrier family 7 member 11 (SLC7A11) or glutathione peroxidase 4 (GPX4) expressions in an m 6 A-YTHDF2 dependent manner, thereby counteracting ferroptotic cell death stress. In addition, we identify Mupirocin as a novel inhibitor of FTO, and Mupirocin induces CRC ferroptosis and inhibits tumor growth. Clinically, the levels of FTO, SLC7A11, and GPX4, are highly correlated expression in CRC tissues. Our findings reveal that FTO protects CRC from ferroptotic cell death in promoting CRC tumorigenesis through triggering SLC7A11/GPX4 expression.

The increase in T helper 17 cell (Th17)-mediated pro-inflammatory response and decrease in regulatory T cell (Treg)-mediated anti-inflammatory effect aggravate renal tubular epithelial cell (RTEC) injury. However, increasing evidence indicated that mesenchymal stem cell (MSC) possessed the ability to control the imbalance between Th17 and Treg. Given that Th17 and Treg are derived from a common CD4 + T cell precursor, we summarize the current knowledge of MSC-mediated inhibition of the mammalian target of rapamycin (mTOR), which is a master regulator of CD4 + T cell polarization. During CD4 + T cell differentiation, mTOR signaling mediates Th17 and Treg differentiation via hypoxia-inducible factor-1α (HIF-1α)-dependent metabolic regulation and signaling pathway, as well as mTOR-mediated phosphorylation of signal transducer and activator of transcription (STAT) 3 and 5. Through interfering with mTOR signaling, MSC restrains CD4 + T cell differentiation into Th17, but in turn promotes Treg generation. Thus, this review indicates that MSC-mediated Th17-to-Treg polarization is expected to act as new immunotherapy for kidney injury.

The impact of global climate change on vegetation has become increasingly prominent over the past several decades. Understanding vegetation change and its response to climate can provide fundamental information for environmental resource management. In recent years, the arid climate and fragile ecosystem have led to great changes in vegetation in Yunnan Province, so it is very important to further study the relationship between vegetation and climate. In this study, we explored the temporal changes of normalized difference vegetation index (NDVI) in different seasons based on MOD13Q1 NDVI by the maximum value composite and then analyzed spatial distribution characteristics of vegetation using Sen’s tendency estimation, Mann–Kendall significance test, and coefficient of variation model (CV) combined with terrain factors. Finally, the concurrent and lagged effects of NDVI on climate factors in different seasons and months were discussed using the Pearson correlation coefficient. The results indicate that (1) the temporal variation of the NDVI showed that the NDVI values of different vegetation types increased at different rates, especially in growing season, spring, and autumn; (2) for spatial patterns, the NDVI, CV, and NDVI trends had strong spatial heterogeneity owning to the influence of altitudes, slopes, and aspects; and (3) the concurrent effect of vegetation on climate change indicates that the positive effect of temperature on NDVI was mainly in growing season and autumn, whereas spring NDVI was mainly influenced by precipitation. In addition, the lag effect analysis results revealed that spring precipitation has a definite inhibition effect on summer and autumn vegetation, but spring and summer temperature can promote the growth of vegetation. Meanwhile, the precipitation in the late growing season has a lag effect of 1-2 months on vegetation growth, and air temperature has a lag effect of 1 month in the middle of the growing season. Based on the above results, this study provided valuable information for ecosystem degradation and ecological environment protection in the Yunnan Province.

Phenology shifts over time are known as the canary in the mine when studying the response of terrestrial ecosystems to climate change. Plant phenology is a key factor controlling the productivity of terrestrial vegetation under climate change. Over the past several decades, the vegetation in the three-river headwaters region (TRHR) has been reported to have changed greatly owing to the warming climate and human activities. However, uncertainties related to the potential mechanism and influence of climatic and soil factors on the plant phenology of the TRHR are poorly understood. In this study, we used harmonic analysis of time series and the relative and absolute change rate on Google Earth Engine to calculate the start (SOS), end (EOS), and length (LOS) of the growing season based on MOD09A1 datasets; the results were verified by the observational data from phenological stations. Then, the spatiotemporal patterns of plant phenology for different types of terrain and basins were explored. Finally, the potential mechanism involved in the influence of climatic and soil factors on the phenology of plants in the TRHR were explored based on the structural equation model and Pearson’s correlation coefficients. The results show the remotely sensed monitoring data of SOS (R2 = 0.84, p < 0.01), EOS (R2 = 0.72, p < 0.01), and LOS (R2 = 0.86, p < 0.01) were very similar to the observational data from phenological stations. The SOS and LOS of plants possessed significant trends toward becoming advanced (Slope < 0) and extended (Slope > 0), respectively, from 2001 to 2018. The SOS was the earliest and the LOS was the longest in the Lancang River Basin, while the EOS was the latest in the Yangtze River Basin owing to the impact of climate change and soil factors. Meanwhile, the spatial patterns of SOS, EOS, and LOS have strong spatial heterogeneity at different elevations, slopes, and aspects. In addition, the results show that the drivers of plant phenology have basin-wide and stage differences. Specifically, the influence of soil factors on plant phenology in the Yangtze River Basin was greater than that of climatic factors, but climatic factors were key functional indicators of LOS in the Yellow and Lancang river basins, which directly or indirectly affect plant LOS through soil factors. This study will be helpful for understanding the relationship between the plant phenology of the alpine wetland ecosystem and climate change and improving the level of environmental management.

Endomyocardial biopsy is the gold standard method for the diagnosis of cardiac allograft rejection. However, it causes damage to the heart. In this study, we developed a noninvasive method for quantification of granzyme B (GzB) by targeted ultrasound imaging, which detects and provides quantitative information for specific molecules, for acute rejection assessment in a murine cardiac transplantation model. Microbubbles bearing anti-GzB antibodies (MB ) or isotype antibodies (MBcon) were prepared. Hearts were transplanted from C57BL/6J (allogeneic) or C3H (syngeneic) donors to C3H recipients. Target ultrasound imaging was performed on Days 2 and 5 post-transplantations. A pathologic assessment was performed. The expression of granzyme B and IL-6 in the heart was detected by Western blotting. After MB injection, we observed and collected data at 3 and 6 min before and after the flash pulse. Quantitative analysis revealed that the reduction in peak intensity was significantly higher in the allogeneic MB group than in the allogeneic MB group and the isogeneic MB group at PODs 2 and 5. In the allogeneic groups, granzyme B and IL-6 expression levels were higher than those in the isogeneic group. In addition, more CD8 T cells and neutrophils were observed in the allogeneic groups. Ultrasound molecular imaging of granzyme B can be used as a noninvasive method for acute rejection detection after cardiac transplantation.

Tyrosine is an essential ketogenic and glycogenic amino acid for the human body, which means that tyrosine is not only involved in protein metabolism, but also participates in the metabolism of lipids and carbohydrates. The liver is an important place for metabolism of lipids, carbohydrates, and proteins. The metabolic process of biological macro-molecules is a basis for maintaining the physiological activities of organisms, but the cross-linking mechanism of these processes is still unclear. Here, we found that the tyrosine-metabolizing enzymes, which were specifically and highly expressed in the liver, were significantly down-regulated in hepatocellular carcinoma (HCC), and had a correlation with a poor prognosis of HCC patients. Further analysis found that the reduction of tyrosine metabolism would activate the cell cycle and promote cell proliferation. In addition, we also found that the solute carrier family 27 member 5 (SLC27A5) regulates the expression of tyrosine-metabolizing enzymes through nuclear factor erythroid 2-related factor 2 (NRF2). Therefore, the SLC27A5 and tyrosine-metabolizing enzymes that we have identified coordinate lipid and tyrosine metabolism, regulate the cell cycle, and are potential targets for cancer treatment.

Measuring the impact of livestock grazing on grassland above-ground net primary production (ANPP) is essential for grass yield estimation and pasture management. However, since there is a lack of accurate and repeatable techniques to obtain the details of grazing locations and stocking rates at the regional scale, it is an extremely challenging task to study the influence of regional grazing on the grassland ANPP. Taking Zoige County as a case, this paper proposes an approach to quantify the spatial and temporal variation of grazing intensity and grazing period through time-series remote sensing data, simulated grassland ANPP through the denitrification and decomposition (DNDC) model, and then explores the impact of grazing on grassland ANPP. The result showed that the model-estimated ANPP while considering grazing had a significant relationship with the field-observed ANPP, with the coefficient of determination (R2) of 0.75, root mean square error (RMSE) of 122.86 kgC/ha, and average relative error (RE) of 8.77%. On the contrary, if grazing activity was not considered in simulation, a large uncertainty was found when the model-estimated ANPP was compared with the field observation, showing R2 of 0.4, RMSE of 211.51 kgC/ha, and average RE of 32.5%. For the whole area of Zoige County in 2012, the statistics of the estimation showed that the total regional ANPP was up to 3.815 × 105 tC, while the total regional ANPP, without considering grazing, would be overestimated by 44.4%, up to 5.51 × 105 tC. This indicates that the grazing parameters derived in this study could effectively improve the accuracy of ANPP simulation results. Therefore, it is feasible to combine time-series remote sensing data with the process model to simulate the grazing effects on grassland ANPP. However, some issues, such as selecting proper remote sensing data, improving the quality of model input parameters, collecting more field data, and exploring the data assimilation approaches, still should be considered in the future work.

Background Ischemia–reperfusion injury (IRI) is an inevitable process in renal transplantation that significantly increases the risk of delayed graft function, acute rejection, and even graft loss. Formyl peptide receptor 2 (FPR2) is an important receptor in multiple septic and aseptic injuries, but its functions in kidney IRI are still unclear. This study was designed to reveal the pathological role of FPR2 in kidney IRI and its functional mechanisms. Methods To explore the mechanism of FPR2 in kidney IRI, the model rats were sacrificed after IRI surgery. Immunofluorescence, enzyme-linked immunosorbent assays, and western blotting were used to detect differences in the expression of FPR2 and its ligands between the IRI and control groups. WRW 4 (WRWWWW-NH2), a specific antagonist of FPR2, was administered to kidney IRI rats. Kidney function and pathological damage were detected to assess kidney injury and recovery. Flow cytometry was used to quantitatively compare neutrophil infiltration among the experimental groups. Mitochondrial formyl peptides (mtFPs) were synthesized and administered to primary rat neutrophils together with the specific FPR family antagonist WRW 4 to verify our hypothesis in vitro. Western blotting and cell function assays were used to examine the functions and signaling pathways that FPR2 mediates in neutrophils. Results FPR2 was activated mainly by mtFPs during the acute phase of IRI, mediating neutrophil migration and reactive oxygen species production in the rat kidney through the ERK1/2 pathway. FPR2 blockade in the early phase protected rat kidneys from IRI. Conclusions mtFPs activated FPR2 during the acute phase of IRI and mediated rat kidney injury by activating the migration and reactive oxygen species generation of neutrophils through the ERK1/2 pathway.