In eukaryotes, holo-Mediator consists of four modules: head, middle, tail, and CDK/Cyclin. The head module performs an essential function involved in regulation of RNA polymerase II (Pol II). We studied the human head module subunit MED17 (hMED17). Recent structural studies showed that yeast MED17 may function as a hinge connecting the neck and movable jaw regions of the head module to the fixed jaw region. Luciferase assays in hMED17-knockdown cells showed that hMED17 supports transcriptional activation, and pulldown assays showed that hMED17 interacted with Pol II and the general transcription factors TFIIB, TBP, TFIIE, and TFIIH. In addition, hMED17 bound to a DNA helicase subunit of TFIIH, XPB, which is essential for both transcription and nucleotide excision repair (NER). Because hMED17 associates with p53 upon UV-C irradiation, we treated human MCF-7 cells with either UV-C or the MDM2 inhibitor Nutlin-3. Both treatments resulted in accumulation of p53 in the nucleus, but hMED17 remained concentrated in the nucleus in response to UV-C. hMED17 colocalized with the NER factors XPB and XPG following UV-C irradiation, and XPG and XPB bound to hMED17 in vitro. These findings suggest that hMED17 may play essential roles in switching between transcription and NER.
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PLoS Pathog
January 2025
Strategic Area: Protecting Crops and the Environment, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom.
Filamentous plant pathogenic fungi pose significant threats to global food security, particularly through diseases like Fusarium Head Blight (FHB) and Septoria Tritici Blotch (STB) which affects cereals. With mounting challenges in fungal control and increasing restrictions on fungicide use due to environmental concerns, there is an urgent need for innovative control strategies. Here, we present a comprehensive analysis of the stage-specific infection process of Fusarium graminearum in wheat spikes by generating a dual weighted gene co-expression network (WGCN).
View Article and Find Full Text PDFComput Med Imaging Graph
December 2024
School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, Beijing, PR China; Zhengzhou Research Institute, Beijing Institute of Technology, Zhengzhou, 450000, Henan, PR China. Electronic address:
In skull base surgery, the method of using a probe to draw or 3D scanners to acquire intraoperative facial point clouds for spatial registration presents several issues. Manual manipulation results in inefficiency and poor consistency. Traditional registration algorithms based on point clouds are highly dependent on the initial pose.
View Article and Find Full Text PDFNeural Netw
January 2025
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi'an, 710054, China; Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, 710054, China.
The presence of substantial similarities and redundant information within video data limits the performance of video object recognition models. To address this issue, a Global-Local Storage Enhanced video object recognition model (GSE) is proposed in this paper. Firstly, the model incorporates a two-stage dynamic multi-frame aggregation module to aggregate shallow frame features.
View Article and Find Full Text PDFSci Rep
January 2025
Shenzhen City Polytechnic, Shenzhen, 518055, China.
In the rapidly evolving field of personalized news recommendation, capturing and effectively utilizing user interests remains a significant challenge due to the vast diversity and dynamic nature of user interactions with news content. Existing recommendation models often fail to fully integrate candidate news items into user interest modeling, which can result in suboptimal recommendation accuracy and relevance. This limitation stems from their insufficient ability to jointly consider user history and the characteristics of candidate news items in the modeling process.
View Article and Find Full Text PDFSci Rep
January 2025
School of Electronic Information Technology, Northeast Forestry University, Harbin, 150040, People's Republic of China.
To address the significantly elevated safety risks associated with construction workers' improper use of helmets and reflective clothing, we propose an enhanced YOLOv8 model tailored for safety wear detection. Firstly, this study introduces the P2 detection layer within the YOLOv8 architecture, which substantially enriches semantic feature representation. Additionally, a lightweight Ghost module is integrated to replace the original backbone of YOLOv8, thereby reducing the parameter count and computational burden.
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