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Transcription Factors HNF1A, HNF4A, and FOXA2 Regulate Hepatic Cell Protein N-Glycosylation Article
Vedrana Vičić Bočkor,Nika Foglar,Goran Josipović,Marija Klasić,Ana Vujić,Branimir Plavša,Toma Keser,Samira Smajlović,Aleksandar Vojta,Vlatka Zoldoš
Engineering 2024, Volume 32, Issue 1, Pages 58-69 doi: 10.1016/j.eng.2023.09.019
Hepatocyte nuclear factor 1 alpha (HNF1A), hepatocyte nuclear factor 4 alpha (HNF4A), and forkhead box protein A2 (FOXA2) are key transcription factors that regulate a complex gene network in the liver, creating a regulatory transcriptional loop. The Encode and ChIP-Atlas databases identify the recognition sites of these transcription factors in many glycosyltransferase genes. Our in silico analysis of HNF1A, HNF4A, and FOXA2 binding to the 10 candidate glyco-genes studied in this work confirms a significant enrichment of these transcription factors specifically in the liver. Our previous studies identified HNF1A as a master regulator of fucosylation, glycan branching, and galactosylation of plasma glycoproteins. Here, we aimed to functionally validate the role of the three transcription factors on downstream glyco-gene transcriptional expression and the possible effect on glycan phenotype. We used the state-of-the-art clustered regularly interspaced short palindromic repeats/dead Cas9 (CRISPR/dCas9) molecular tool for the downregulation of the HNF1A, HNF4A, and FOXA2 genes in HepG2 cells—a human liver cancer cell line. The results show that the downregulation of all three genes individually and in pairs affects the transcriptional activity of many glyco-genes, although downregulation of glyco-genes was not always followed by an unambiguous change in the corresponding glycan structures. The effect is better seen as an overall change in the total HepG2 N-glycome, primarily due to the extension of biantennary glycans. We propose an alternative way to evaluate the N-glycome composition via estimating the overall complexity of the glycome by quantifying the number of monomers in each glycan structure. We also propose a model showing feedback loops with the mutual activation of HNF1A–FOXA2 and HNF4A–FOXA2 affecting glyco-genes and protein glycosylation in HepG2 cells.
Keywords: Clustered regularly interspaced short palindromic repeats/dead Cas9 (CRISPR/dCas9) Epigenetics Hepatocyte nuclear factor 1 alpha (HNF1A) Hepatocyte nuclear factor 4 alpha (HNF4A) Forkhead box protein A2 (FOXA2) N-glycosylation HepG2 cells
The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery Review
Wei Chen,Chi Song,Liang Leng,Sanyin Zhang,Shilin Chen
Engineering 2024, Volume 32, Issue 1, Pages 19-29 doi: 10.1016/j.eng.2023.09.011
G protein-coupled receptors (GPCRs) are crucial players in various physiological processes, making them attractive candidates for drug discovery. However, traditional approaches to GPCR ligand discovery are time-consuming and resource-intensive. The emergence of artificial intelligence (AI) methods has revolutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identification and optimization of GPCR ligands. In this study, we provide guidelines for effectively utilizing AI methods for GPCR ligand discovery, including data collation and representation, model selection, and specific applications. First, the online resources that are instrumental in GPCR ligand discovery were summarized, including databases and repositories that contain valuable GPCR-related information and ligand data. Next, GPCR and ligand representation schemes that can convert data into computer-readable formats were introduced. Subsequently, the key applications of AI methods in the different stages of GPCR drug discovery were discussed, ranging from GPCR function prediction to ligand design and agonist identification. Furthermore, an AI-driven multi-omics integration strategy for GPCR ligand discovery that combines information from various omics disciplines was proposed. Finally, the challenges and future directions of the application of AI in GPCR research were deliberated. In conclusion, continued advancements in AI techniques coupled with interdisciplinary collaborations will offer great potential for improving the efficiency of GPCR ligand discovery.
Keywords: G protein-coupled receptor Ligand Artificial intelligence Multi-omics Drug discovery
Xin Yu Wu,Fengshuo Wan,Hongyuan Feng,Shichao Jin,Chong Guo,Yu Wei,Dunge Liu,Yuqian Yang,Longzhu Cai,Zhi Hao Jiang,Wei Hong
Engineering 2024, Volume 32, Issue 1, Pages 70-82 doi: 10.1016/j.eng.2023.08.013
This paper presents a systematic investigation and demonstration of a K-band circularly polarized liquid-crystal-based phased array (LCPA), including the design, over-the-air (OTA) in-array calibration, and experimental validation. The LCPA contains 16 phase-shifting radiating channels, each consisting of a circularly polarized stacked patch antenna and a liquid-crystal-based phase shifter (LCPS) based on a loaded differential line structure. Thanks to its slow-wave properties, the LCPS exhibits a maximum phase-shifting range of more than 360° with a figure of merit of 78.3°·dB−1 based on a liquid crystal layer with a thickness of only 5 μm. Furthermore, an automatic OTA calibration based on a state ergodic method is proposed, which enables the extraction of the phase–voltage curve of every individual LCPA channel. The proposed LCPA is manufactured and characterized with a total profile of only 1.76 mm, experimentally demonstrating a scanned circularly polarized beam from −40° to +40° with a measured peak gain of 12.5 dBic and a scanning loss of less than 2.5 dB. The bandwidth of the LCPA, which satisfies the requirements of port reflection (|S11|) < −15 dB, an axial ratio (AR) < 3 dB, beam squinting < 3°, and a gain variation < 2.2 dB, spans from 25.5 to 26.0 GHz. The total efficiency is about 34%, which represents a new state of the art. The use of the demonstrated low-profile LCPA to support circularly polarized scanning beams, along with the systematic design and calibration methodology, holds potential promise for a variety of millimeter-wave applications.
Keywords: Circularly polarized Liquid crystal Liquid-crystal-based phased array (LCPA) Phase shifter Over-the-air (OTA) calibration
Feng Jin, Duruo Huang, Michel Lino, Hu Zhou
Engineering 2024, Volume 32, Issue 1, Pages 100-106 doi: 10.1016/j.eng.2023.09.020
Over the past few decades, one of the most significant advances in dam construction has been the invention of the rock-filled concrete (RFC) dam, which is constructed by pouring high-performance selfcompacting concrete (HSCC) to fill the voids in preplaced large rocks. The innovative use of large rocks in dam construction provides engineers with a material that requires less cement consumption and hydration heat while enhancing construction efficiency and environmental friendliness. However, two fundamental scientific issues related to RFC need to be addressed: namely, the pouring compactness and the effect of large rocks on the mechanical and physical properties of RFC. This article provides a timely review of fundamental research and innovations in the design, construction, and quality control of RFC dams. Prospects for next-generation concrete dams are discussed from the perspectives of environmental
friendliness, intrinsic safety, and labor savings.
Keywords: Rock-filled concrete dam Pouring compactness Effect of large rocks Intelligent quality control Unmanned dam construction
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Transcription Factors HNF1A, HNF4A, and FOXA2 Regulate Hepatic Cell Protein N-Glycosylation
Vedrana Vičić Bočkor,Nika Foglar,Goran Josipović,Marija Klasić,Ana Vujić,Branimir Plavša,Toma Keser,Samira Smajlović,Aleksandar Vojta,Vlatka Zoldoš
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The Application of Artificial Intelligence Accelerates G Protein-Coupled Receptor Ligand Discovery
Wei Chen,Chi Song,Liang Leng,Sanyin Zhang,Shilin Chen
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High-Efficiency Circularly Polarized Phased Array Based on 5 μm-Thick Nematic Liquid Crystals: Design, Over-The-Air Calibration, and Experimental Validation
Xin Yu Wu,Fengshuo Wan,Hongyuan Feng,Shichao Jin,Chong Guo,Yu Wei,Dunge Liu,Yuqian Yang,Longzhu Cai,Zhi Hao Jiang,Wei Hong
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