RESUMEN
The interleukin-1 receptor associated kinase 4 (IRAK-4) is a member of serine-threonine kinase family, which plays an important role in the regulation of interleukin-1 receptors (IL-1R) and Toll-like receptors (TLRs) related signaling pathways. At present, the IRAK-4 mediated inflammation and related signaling pathways contribute to inflammation, which are also responsible for other autoimmune diseases and drug resistance in cancers. Therefore, targeting IRAK-4 to develop single-target, multi-target inhibitors and proteolysis-targeting chimera (PROTAC) degraders is an important direction for the treatment of inflammation and related diseases. Moreover, insight into the mechanism of action and structural optimization of the reported IRAK-4 inhibitors will provide the new direction to enrich the clinical therapies for inflammation and related diseases. In this comprehensive review, we introduced the recent advance of IRAK-4 inhibitors and degraders with regards to structural optimization, mechanism of action and clinical application that would be helpful for the development of more potent chemical entities against IRAK-4.
Asunto(s)
Quinasas Asociadas a Receptores de Interleucina-1 , Transducción de Señal , Receptores Toll-Like , Humanos , Inflamación/tratamiento farmacológico , Inflamación/metabolismo , Quinasas Asociadas a Receptores de Interleucina-1/antagonistas & inhibidores , Proteínas Serina-Treonina Quinasas/metabolismo , Receptores de Interleucina-1/metabolismoRESUMEN
Plant phenology is the best indicator of terrestrial ecosystem response to climate change and it becomes a hot issue in the study of global change. The forest in northeast of China plays an important part in global forest ecosystem. In this paper, yearly integrated Normalized Difference Vegetation Index (NDVI) of forest vegetation in northeast China was calculated based on Spot Vegetation datasets from 2001-2010, which has been filtered using Savtiky-Galoy method. And then, the yearly integrated NDVI profile was fitted using a logistic model. Two key parameters of forest phenology (start of season, SOS; end of season, EOS) were extracted according to the greatest rate of curvature of fitted cumulative NDVI and the length of forest phenology (length of season, LOS) was also analyzed. The main conclusions of this paper are (1) SOS mainly occurs in the 110th-140th day and EOS in 260th and 290th day. SOS displays a marked delayed from south to north while EOS gradually advances. However, the changes of SOS and EOS in ten years are not obvious. (2) Corresponding to the SOS and EOS, LOS of forest in study area mainly occurs in the 120th-160th day; however, it is spatially heterogeneous. LOS of forest in Greater Khingan Mountains is shorter (about 120-140 day) than forests in Xiao Hinggan Ling and Changbai Mountains (about 160 day). The results in this paper are concordant with records of phenology in situ measurements and previous researches in the same area. It indicates that forest phenophases using method in this paper from Spot Vegetation dataset is feasible.
Asunto(s)
Bosques , Tecnología de Sensores Remotos , Árboles , China , Cambio Climático , Estaciones del AñoRESUMEN
Leaf area index (LAI) is an important structural parameter of vegetation canopy, the correct estimation of which has been the focus in the remote sensing community. As a kind of hyperspectral and multi-angle remote sensing data with higher resolution (17 m), PROBA/CHRIS has significant application value in LAI inversion. In the present paper, the analytical two-layer canopy reflectance model (ACRM) was used to simulate a series of reflectances with different LAI values. Based on this, a new vegetation index was built and successfully applied to LAI inversion of PROBA/CHRIS image data. Our results indicated that: compared with the spectral index NDVI and multi-angle index HDS, the new index could make better use of spectrum and multi-angle messages and have a better correlation with LAI of the study area; moreover, the correlation coefficient R2 reached up to 0.734 7. And in order to obtain the figure of LAI distribution of the study area, we used the optimal fit equation between LAI and HDVI to estimate LAI, and the accuracy of the RMSE was 0.619 8.
Asunto(s)
Clorofila/análisis , Fotosíntesis/fisiología , Hojas de la Planta/química , Tecnología de Sensores Remotos , Análisis Espectral/métodos , Monitoreo del Ambiente/métodos , Modelos Teóricos , Comunicaciones por Satélite , Análisis Espectral/instrumentaciónRESUMEN
The title compound, C(14)H(21)Cl(3)O(9)·2H(2)O, is a disaccharide constructed from a galactose and a fructose. In the mol-ecular structure, the tetra-hydro-furan five-membered ring and tetra-hydro-pyran six-membered ring assume envelope and chair conformations, respectively. An extensive O-Hâ¯O hydrogen-bonding network occurs in the crystal structure.