The coactivator p300/CREB-binding protein (CBP) regulates genes by facilitating the assembly of transcriptional machinery and by acetylating histones and other factors. However, it remains mostly ...unclear how both functions of p300 are dynamically coordinated during gene control. Here, we showed that p300 can orchestrate two functions through the formation of dynamic clusters with certain transcription factors (TFs), which is mediated by the interactions between a TF’s transactivation domain (TAD) and the intrinsically disordered regions of p300. Co-condensation can enable spatially defined, all-or-none activation of p300’s catalytic activity, priming the recruitment of coactivators, including Brd4. We showed that co-condensation can modulate transcriptional initiation rate and burst duration of target genes, underlying nonlinear gene regulatory functions. Such modulation is consistent with how p300 might shape gene bursting kinetics globally. Altogether, these results suggest an intriguing gene regulation mechanism, in which TF and p300 co-condensation contributes to transcriptional bursting regulation and cooperative gene control.
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•Some transcription factors can recruit p300 by co-condensation•Interactions between disordered regions of TF and p300 can drive co-condensation•Co-condensation can promote p300 transactivation and stabilize TF-p300 assembly•Transcriptional bursting and dose-response curve are modulated by co-condensation
Ma et al. demonstrate that transcription factor and coactivator p300 can cocondense. They systematically dissect the mechanism and function of co-condensation. The findings offer quantitative insights into how p300 catalytic activity, gene transcriptional bursting, and gene dose-response curve can be regulated by co-condensation.
The observations from satellite microwave-sounding instruments have been widely used in weather and climate studies. Since the data resolution varies with frequency and satellite viewing angle, it is ...normally required that the measurements at each frequency be resampled to obtain a uniform resolution prior to various applications. In this study, the ATOVS and AVHRR pre-processing package (AAPP) Fourier transform algorithm is modified for ATMS data and the results are compared with those derived from Backus–Gilbert inversion (BGI) and the original AAPP. From the simulated and observed ATMS data, we demonstrated the new algorithm has better results in terms of imaging quality and noise suppression, compared with BGI and AAPP. In general, our modified AAPP algorithm reduces the error by at least about 0.5 K in ATMS channels 2 and 6 and at all the viewing angles.
Rural tourism development has been an essential driving force behind China’s promotion of integrated urban–rural development, sustainable rural development and rural revitalization in the new era. ...This study included 1470 villages on the national list of beautiful leisure villages in China (BLVCs) from 2010 to 2021. We explored the distribution characteristics and influencing factors based on mathematical statistics and spatial analysis in ArcGIS to provide a theoretical reference for promoting the development of leisure village agriculture and rural tourism. The results show that the distribution of BLVC presents a clustered state, showing a distribution pattern of a dual core, seven centers and multiple scattered points. BLVCs are mainly distributed in areas with flat terrain and sufficient water resources, which are conducive to agricultural production and life. Having convenient transportation and rich tourism resources aids the promotion of rural tourism development. The resulting gap in regional development is balanced to some extent by government support. The research results provide a reference value for future rural spatial optimization and sustainable development. This paper summarizes the law of rural development and clarifies the factors influencing the development of rural tourism, and it provides the Chinese experience as a model for a rural renaissance empowered by rural tourism.
Diffuse lower-grade gliomas (LGG) represent the highly heterogeneous and infiltrative neoplasms in the central nervous system (CNS). Replication factor C 2 (RFC2) is a subunit of the RFC complex that ...modulates DNA replication and repair. However, the prognosis value of RFC2 and its association with the immune signature of tumor microenvironment (TME) in LGG remains unknown. Based on Oncomine, TCGA, GTEx, TIMER, GEPIA, and HPA databases, we evaluated RFC2 expression levels and its clinical prognostic value in LGG and other cancers. Then we analyzed the correlations between RFC2 expression and tumor mutation burden (TMB), tumor microsatellite instability (MSI), and mismatch repair (MMR) genes across cancers. And CIBERSORT and ESTIMATE algorithms were conducted to estimate the association of RFC2 with immune cell infiltration of LGG. Additionally, we performed the functional enrichment analyses of RFC2 in LGG. Then functional experiments were employed to further validate the oncogenic role of RFC2 in LGG. Our results showed that RFC2 was widely highly expressed in most types of cancer. And its expression was closely related to the clinicopathological features and prognosis in LGG and other cancer types. RFC2 levels were also correlated with TMB and MSI across various cancers. Furthermore, RFC2 was positively associated with the infiltration levels of immune cells and immune checkpoint genes in LGG. Additionally, in vitro experiments revealed that RFC2 played an oncogenic role in LGG progression. In conclusion, our findings revealed that RFC2 could serve as a reliable biomarker to predict the prognosis and immune signature for LGG.
Radiotherapy is the standard adjuvant treatment for glioma patients; however, the efficacy is limited by radioresistance. The function of Interleukin-1 receptor associated kinase 1 (IRAK1) in ...tumorigenesis and radioresistance remains to be elucidated. IRAK1 expression and its correlation with prognosis were analyzed in glioma tissues. We found that glioma patients with overexpressed IRAK1 show a poor prognosis. Notably, ionizing radiation (IR) remarkably induces IRAK1 expression, which was decreased by STING antagonist H-151 treatment. JASPAR prediction, ChIP assays, and dual luciferase reporter assays indicated that transcription factor FOXA2, suppressed by STING inhibition, directly binds to the IRAK1 promoter region and activates its transcription. IRAK1 knockdown inhibits malignancy and enhances the radiosensitivity of glioma in vitro and in vivo. To explore the potential IRAK1 interacting targets mediating the radioresistance of glioma cells, IP/Co-IP, LC-MS/MS, GST pull-down, and ubiquitination analyses were conducted. Mechanistically, IRAK1 bound to PRDX1, a major member of antioxidant enzymes, and further prevents ubiquitination and degradation of PRDX1 mediated by E3 ubiquitin ligase HECTD3; Both the DOC and HECT domains of HECTD3 directly interacted with PRDX1 protein. Overexpression of PRDX1 reverses the radiotherapy sensitization effect of IRAK1 depletion by diminishing autophagic cell death. These results suggest the IRAK1-PRDX1 axis provides a potential therapeutic target for glioma patients.
The signals of Global Navigation Satellite System (GNSS) are so vulnerable that can be easily jammed by intentional or unintentional interferences. One of the effective ways to protect GNSS signals ...from jamming is to use the Space‐Time Array Processing (STAP) technology. However, undesired carrier phase bias would be induced to the signals because of the STAP, which significantly influences the precision of positioning. Many algorithms have been proposed to deal with this carrier phase bias, but most of them need the directional information of signals or the pre‐test of antennas. In this paper, a carrier phase correction algorithm without the need of prior information is proposed. Alarmed by the jerk of carrier frequency, the algorithm can detect the change of jamming and calculate the induced carrier phase bias. Then it can correct this bias from the signal and alleviate its influence. The simulation results show that the algorithm can limit the bias from more than 60° to less than 10°, which verifies that the proposed algorithm is effective in the low dynamic receiver.
Radiotherapy benefits patients with advanced esophageal squamous cell carcinoma (ESCC) in terms of symptom relief and long-term survival. In contrast, a substantial proportion of ESCC patients have ...not benefited from radiotherapy. This study aimed to establish and validate an artificial neural network-based radiomics model for the pretreatment prediction of the radiotherapy response of advanced ESCC by using integrated data combined with feasible baseline characteristics of computed tomography. A total of 248 patients with advanced ESCC who underwent baseline CT and received radiotherapy were enrolled in this study and were analyzed by two types of radiomics models, machine learning and deep learning. As a result, the Att. Resnet50 pretrained network model indicated superior performance, with AUCs of 0.876, 0.802 and 0.732 in the training, internal validation, and external validation cohorts, respectively. Similarly, our Att. Resnet50 pretrained network model showed excellent calibration and significant clinical benefit according to the C index and decision curve analysis. Herein, a novel pretreatment radiomics model was established based on deep learning methods and could be used for radiotherapy response prediction in advanced ESCC patients, thus providing reliable evidence for therapeutic decision-making.
Communications between actin filaments and integrin-mediated focal adhesion (FA) are crucial for cell adhesion and migration. As a core platform to organize FA proteins, the tripartite ...ILK/PINCH/Parvin (IPP) complex interacts with actin filaments to regulate the cytoskeleton-FA crosstalk. Rsu1, a Ras suppressor, is enriched in FA through PINCH1 and plays important roles in regulating F-actin structures. Here, we solved crystal structures of the Rsu1/PINCH1 complex, in which the leucine-rich-repeats of Rsu1 form a solenoid structure to tightly associate with the C-terminal region of PINCH1. Further structural analysis uncovered that the interaction between Rsu1 and PINCH1 blocks the IPP-mediated F-actin bundling by disrupting the binding of PINCH1 to actin. Consistently, overexpressing Rsu1 in HeLa cells impairs stress fiber formation and cell spreading. Together, our findings demonstrated that Rsu1 is critical for tuning the communication between F-actin and FA by interacting with the IPP complex and negatively modulating the F-actin bundling.
PBRM1 is the second most commonly mutated gene after VHL in clear cell renal cell carcinoma (ccRCC). However, the biological consequences of PBRM1 mutations for kidney tumorigenesis are unknown. ...Here, we find that kidney-specific deletion of Vhl and Pbrm1, but not either gene alone, results in bilateral, multifocal, transplantable clear cell kidney cancers. PBRM1 loss amplified the transcriptional outputs of HIF1 and STAT3 incurred by Vhl deficiency. Analysis of mouse and human ccRCC revealed convergence on mTOR activation, representing the third driver event after genetic inactivation of VHL and PBRM1. Our study reports a physiological preclinical ccRCC mouse model that recapitulates somatic mutations in human ccRCC and provides mechanistic and therapeutic insights into PBRM1 mutated subtypes of human ccRCC.
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•PBRM1 is a bona fide tumor suppressor in the pathogenesis of ccRCC•PBRM1 prevents self-perpetuating amplification of HIF1/STAT3 signaling in Vhl−/− cell•Loss of Vhl and Pbrm1 in mouse kidney results in multifocal, transplantable ccRCC•In ccRCC, mTORC1 activation is the third driver event after loss of VHL and PBRM1
Nargund et al. present a three-step process in the pathogenesis of mouse and human clear cell kidney cancer. After the loss of VHL, the loss of SWI/SNF tumor suppressor protein PBRM1/BAF180 further activates HIF1/STAT3 signaling in mouse kidney and positions mTORC1 activation as the preferred third driver event.
Pansharpening, which fuses the panchromatic (PAN) band with multispectral (MS) bands to obtain an MS image with spatial resolution of the PAN images, has been a popular topic in remote sensing ...applications in recent years. Although the deep-learning-based pansharpening algorithm has achieved better performance than traditional methods, the fusion extracts insufficient spatial information from a PAN image, producing low-quality pansharpened images. To address this problem, this paper proposes a novel progressive PAN-injected fusion method based on superresolution (SR). The network extracts the detail features of a PAN image by using two-stream PAN input; uses a feature fusion unit (FFU) to gradually inject low-frequency PAN features, with high-frequency PAN features added after subpixel convolution; uses a plain autoencoder to inject the extracted PAN features; and applies a structural similarity index measure (SSIM) loss to focus on the structural quality. Experiments performed on different datasets indicate that the proposed method outperforms several state-of-the-art pansharpening methods in both visual appearance and objective indexes, and the SSIM loss can help improve the pansharpened quality on the original dataset.
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