Arabidopsis LFR, a SWI/SNF complex component, interacts with ICE1 and activates ICE1 and CBF3 expression in cold acclimation

Low temperatures restrict the growth and geographic distribution of plants, as well as crop yields. Appropriate transcriptional regulation is critical for cold acclimation in plants. In this study, we found that the mutation of Leaf and flower related (LFR), a component of SWI/SNF chromatin remodeling complex (CRC) important for transcriptional regulation in Arabidopsis (Arabidopsis thaliana), resulted in hypersensitivity to freezing stress in plants with or without cold acclimation, and this defect was successfully complemented by LFR. The expression levels of CBFs and COR genes in cold-treated lfr-1 mutant plants were lower than those in wild-type plants. Furthermore, LFR was found to interact directly with ICE1 in yeast and plants. Consistent with this, LFR was able to directly bind to the promoter region of CBF3, a direct target of ICE1. LFR was also able to bind to ICE1 chromatin and was required for ICE1 transcription. Together, these results demonstrate that LFR interacts directly with ICE1 and activates ICE1 and CBF3 gene expression in response to cold stress. Our work enhances our understanding of the epigenetic regulation of cold responses in plants

A Physically Based Spatial Expansion Algorithm for Surface Air Temperature and Humidity

An algorithm was developed to expand the surface air temperature and air humidity to a larger spatial domain, based on the fact that the variation of surface air temperature and air humidity is controlled jointly by the local turbulence and the horizontal advection. This study proposed an algorithm which considers the advective driving force outside the thermal balance system and the turbulent driving force and radiant driving force inside the thermal balance system. The surface air temperature is determined by a combination of the surface observations and the regional land surface temperature observed from a satellite. The average absolute difference of the algorithm is 0.65 degree and 0.31 mb, respectively, for surface air temperature and humidity expansion, which provides a promising approach to downscale the two surface meteorological variables

Using Simplified Thermal Inertia to Determine the Theoretical Dry Line in Feature Space for Evapotranspiration Retrieval

With the development of quantitative remote sensing, regional evapotranspiration (ET) modeling based on the feature space has made substantial progress. Among those feature space based evapotranspiration models, accurate determination of the dry/wet lines remains a challenging task. This paper reports the development of a new model, named DDTI (Determination of Dry line by Thermal Inertia), which determines the theoretical dry line based on the relationship between the thermal inertia and the soil moisture. The Simplified Thermal Inertia value estimated in the North China Plain is consistent with the value measured in the laboratory. Three evaluation methods, which are based on the comparison of the locations of the theoretical dry line determined by two models (DDTI model and the heat energy balance model), the comparison of ET results, and the comparison of the evaporative fraction between the estimates from the two models and the in situ measurements, were used to assess the performance of the new model DDTI. The location of the theoretical dry line determined by DDTI is more reasonable than that determined by the heat energy balance model. ET estimated from DDTI has an RMSE (Root Mean Square Error) of 56.77 W/m2 and a bias of 27.17 W/m2; while the heat energy balance model estimated ET with an RMSE of 83.36 W/m2 and a bias of −38.42 W/m2. When comparing the coeffcient of determination for the two models with the observations from Yucheng, DDTI demonstrated ET with an R2 of 0.9065; while the heat energy balance model has an R2 of 0.7729. When compared with the in situ measurements of evaporative fraction (EF) at Yucheng Experimental Station, the ET model based on DDTI reproduces the pixel scale EF with an RMSE of 0.149, much lower than that based on the heat energy balance model which has an RMSE of 0.220. Also, the EF bias between the DDTI model and the in situ measurements is 0.064, lower than the EF bias of the heat energy balance model, which is 0.084

SMG9 is a novel prognostic-related biomarker in glioma correlating with ferroptosis and immune infiltrates

Background: Glioma is the most frequent type of malignancy that may damage the brain with high morbidity and mortality rates and patients' prognoses are still dismal. Ferroptosis, a newly uncovered mode of programmed cell death, may be triggered to destroy glioma cells. Nevertheless, the significance of ferroptosis-related genes (FRGs) in predicting prognosis in glioma individuals is still a mystery. Methods: The CGGA (The Chinese Glioma Atlas), GEO (Gene Expression Omnibus), and TCGA (The Cancer Genome Atlas) databases were all searched to obtain the glioma expression dataset. First, TCGA was searched to identify differentially expressed genes (DEGs). This was followed by a machine learning algorithm-based screening of the glioma's most relevant genes. Additionally, these genes were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) functional enrichment analyses. The chosen biological markers were then submitted to single-cell, immune function, and gene set enrichment analysis (GSEA). In addition, we performed functional enrichment and Mfuzz expression profile clustering on the most promising biological markers to delve deeper into their regulatory mechanisms and assess their clinical diagnostic capacities. Results: We identified 4444 DEGs via differential analysis and 564 FRGs from the FerrDb database. The two were subjected to intersection analysis, which led to the discovery of 143 overlapping genes. After that, glioma biological markers were identified in fourteen genes by the use of machine learning methods. In terms of its use for clinical diagnosis, SMG9 stands out as the most significant among these biomarkers. Conclusion: In light of these findings, the identification of SMG9 as a new biological marker has the potential to provide information on the mechanism of action and the effect of the immune milieu in glioma. The promise of SMG9 in glioma prognosis prediction warrants more study

DataSheet_1_Arabidopsis LFR, a SWI/SNF complex component, interacts with ICE1 and activates ICE1 and CBF3 expression in cold acclimation.pdf

Low temperatures restrict the growth and geographic distribution of plants, as well as crop yields. Appropriate transcriptional regulation is critical for cold acclimation in plants. In this study, we found that the mutation of Leaf and flower related (LFR), a component of SWI/SNF chromatin remodeling complex (CRC) important for transcriptional regulation in Arabidopsis (Arabidopsis thaliana), resulted in hypersensitivity to freezing stress in plants with or without cold acclimation, and this defect was successfully complemented by LFR. The expression levels of CBFs and COR genes in cold-treated lfr-1 mutant plants were lower than those in wild-type plants. Furthermore, LFR was found to interact directly with ICE1 in yeast and plants. Consistent with this, LFR was able to directly bind to the promoter region of CBF3, a direct target of ICE1. LFR was also able to bind to ICE1 chromatin and was required for ICE1 transcription. Together, these results demonstrate that LFR interacts directly with ICE1 and activates ICE1 and CBF3 gene expression in response to cold stress. Our work enhances our understanding of the epigenetic regulation of cold responses in plants.</p

XRD investigation of binary alloys solidification

The solidification of two binary alloys, In-10Sn and Sn-13Pb, has been investigated by X-ray diffractometry (XRD) at high temperature. The high temperature X-ray camera used in the experiments is mounted on a diffractometer, allocates a sample holder apt to contain molten metals and can operate up to 1600°C in vacuum or in a controlled atmosphere of inert gas. Melts have been slowly cooled down to the liquidus temperature and XRD spectra recorded step by step. The temperature was kept constant while XRD data were collected. From the spectra the radial distribution functions (RDF) have been then determined for each temperature. Experiments showed that atomic clustering forms in the melt immediately before the appearing of the first solid and that the structures in the liquid are correlated to those of the solid. Experimental problems connected to real-time monitoring of phase transformations involving liquid metals have been examined. To avoid convective motions in the liquid and to achieve the best experimental conditions, it is discussed the possibility to perform the same experiments under conditions of reduced gravity aboard the International Space Station (ISS)