Ecogenomics reveals viral communities across the Challenger Deep oceanic trench by Ying-Li Zhou, Paraskevi Mara, Dean Vik, Virginia P. Edgcomb, Matthew B. Sullivan, Yong Wang

“…Analysis of 13 sediment cores from the Challenger Deep of Marian Trench (down to 11 kilometers depth) identified distinct operational taxonomic units and relevant auxiliary metabolic genes, providing further insight into deep-sea viral metabolic capabilities and ecology.…”
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Spatial variations of microbial communities in abyssal and hadal sediments across the Challenger Deep by Guojie Cui, Jun Li, Zhaoming Gao, Yong Wang

Subjects: “…Challenger Deep…”
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Composition and origin of lipid biomarkers in the surface sediments from the southern Challenger Deep, Mariana Trench by Hongxiang Guan, Linying Chen, Min Luo, Lihua Liu, Shengyi Mao, Huangmin Ge, Mei Zhang, Jiasong Fang, Duofu Chen

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Influence of Extremely High Pressure and Oxygen on Hydrocarbon-Enriched Microbial Communities in Sediments from the Challenger Deep, Mariana Trench by Ying Liu, Songze Chen, Zhe Xie, Li Zhang, Jiahua Wang, Jiasong Fang

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Biotechnological and Ecological Potential of <i>Micromonospora provocatoris</i> sp. nov., a Gifted Strain Isolated from the Challenger Deep of the Mariana Trench by Wael M. Abdel-Mageed, Lamya H. Al-Wahaibi, Burhan Lehri, Muneera S. M. Al-Saleem, Michael Goodfellow, Ali B. Kusuma, Imen Nouioui, Hariadi Soleh, Wasu Pathom-Aree, Marcel Jaspars, Andrey V. Karlyshev

“…A <i>Micromonospora</i> strain, isolate MT25^T, was recovered from a sediment collected from the Challenger Deep of the Mariana Trench using a selective isolation procedure. …”
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Whole Genome Sequence of <i>Dermacoccus</i> <i>abyssi </i>MT1.1 Isolated from the Challenger Deep of the Mariana Trench Reveals Phenazine Biosynthesis Locus and Environmental Adaptation Factors by Wael M. Abdel-Mageed, Bertalan Juhasz, Burhan Lehri, Ali S. Alqahtani, Imen Nouioui, Dawrin Pech-Puch, Jioji N. Tabudravu, Michael Goodfellow, Jaime Rodríguez, Marcel Jaspars, Andrey V. Karlyshev

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Identification of Free-living and Particle-Associated Microbial Communities Present in Hadal regions of the Mariana Trench by Jonathan eTarn, Logan Maxwell Peoples, Kevin eHardy, James eCameron, Douglas Hoyt Bartlett

“…Sequences matching cultivated piezophiles were notably enriched in the Challenger Deep, especially within the particle-associated fraction, and were found in higher abundances than in other hadal studies, where they were either far less prevalent or missing. …”
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Insights into the Vertical Stratification of Microbial Ecological Roles across the Deepest Seawater Column on Earth by Chun-Xu Xue, Jiwen Liu, David J. Lea-Smith, Gary Rowley, Heyu Lin, Yanfen Zheng, Xiao-Yu Zhu, Jinchang Liang, Waqar Ahmad, Jonathan D. Todd, Xiao-Hua Zhang

“…Here, we used metagenomics to investigate the microbial communities and their potential to drive biogeochemical cycling in seven different water layers down the vertical profile of the Challenger Deep (0–10,500 m) in the Mariana Trench, the deepest natural point in the Earth’s oceans. …”
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Distinctive signatures of pathogenic and antibiotic resistant potentials in the hadal microbiome by Liuqing He, Xinyu Huang, Guoqing Zhang, Ling Yuan, Enhui Shen, Lu Zhang, Xiao-Hua Zhang, Tong Zhang, Liang Tao, Feng Ju

“…Results The results indicate that the 10,898 m Challenger Deep bottom sediment harbored prosperous microbiota with contrasting signatures of virulence factors and antibiotic resistance, compared with the neighboring but shallower 6038 m steep wall site and the more nearshore 5856 m Pacific basin site. …”
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Metagenomic characterization of a novel non-ammonia-oxidizing Thaumarchaeota from hadal sediment by Ru-Yi Zhang, Yan-Ren Wang, Ru-Long Liu, Sung-Keun Rhee, Guo-Ping Zhao, Zhe-Xue Quan

“…Results In this study, we explored the metagenomes of Challenger Deep hadal sediment, focusing on the Thaumarchaeota. …”
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Molecular Responses to High Hydrostatic Pressure in Eukaryotes: Genetic Insights from Studies on <i>Saccharomyces cerevisiae</i> by Fumiyoshi Abe

“…Organisms in the Challenger Deep of the Mariana Trench are habitually exposed to pressures up to 110 MPa. …”
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High‐resolution multibeam sonar bathymetry of the deepest place in each ocean by Cassandra Bongiovanni, Heather A. Stewart, Alan J. Jamieson

“…The deepest place in each ocean were identified as the Brownson Deep, Puerto Rico Trench in the Atlantic Ocean (8,378 ± 5 m), an unnamed deep within the South Sandwich Trench in the Southern Ocean (7,432 ± 13 m), an unnamed deep within the Java Trench in the Indian Ocean (7,187 ± 13 m), Challenger Deep within the Mariana Trench in the Pacific Ocean (10,924 ± 15 m), and the Molloy Hole in the Arctic Ocean (5,551 ± 14 m). …”
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Deterministic process controlling the prokaryotic community assembly across seamounts along in the Yap and Mariana trenches by Yue Zhang, Hongmei Jing

“…In addition, higher levels of prokaryotic abundance, diversity, and niche width in the seamounts than the Challenger Deep were observed as well, further proved seamounts as deep oasis for microbes. …”
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Archaea predominate in the ammonia oxidation process in the sediments of the Yap and Mariana Trenches by Hao Liu, Hongmei Jing, Hongmei Jing, Hongmei Jing, Fangzhou Wang, Fangzhou Wang

“…Sediment samples from seamounts and the Challenger Deep along the arc of the Yap Trench and the Mariana Trench were used for the investigation of the geographical distribution of AOA and AOB at the cDNA level, with associated potential nitrification rates (PNRs) being measured. …”
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Fungal Abundance and Diversity in the Mariana Trench, the Deepest Ecosystem on Earth by Stefano Varrella, Giulio Barone, Cinzia Corinaldesi, Alessio Giorgetti, Hidetaka Nomaki, Takuro Nunoura, Eugenio Rastelli, Michael Tangherlini, Roberto Danovaro, Antonio Dell’Anno

“…We investigated the fungal abundance and diversity in the Challenger Deep (at ca. 11,000 m depth) and the slope of the Mariana Trench in comparison with three sites of the adjacent abyssal plain. …”
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Dynamics Modeling and Analysis of an Underwater Glider with Dual-Eccentric Attitude Regulating Mechanism Using Dual Quaternions by Peng Wang, Xuehao Wang, Yanhui Wang, Wendong Niu, Shaoqiong Yang, Chao Sun, Chenyi Luo

“…Finally, Petrel-X^PLUS achieved a pitch angle regulation range of −90°~90° in a water pool experiment and completed three consecutive profiles in a sea trial in the Challenger Deep, Mariana Trench, with all depths over 10,000 m, of which the maximum depth was 10,619 m. …”
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Biological functions at high pressure: transcriptome response of Shewanella oneidensis MR-1 to hydrostatic pressure relevant to Titan and other icy ocean worlds by Judy Malas, Daniel C. Russo, Olivier Bollengier, Michael J. Malaska, Rosaly M. C. Lopes, Fabien Kenig, D'Arcy R. Meyer-Dombard

“…Piezophiles are organisms that grow optimally at pressures higher than atmospheric (0.1 MPa) pressure and have specialized adaptations to the physical constraints of high-pressure environments – up to ~110 MPa at Challenger Deep, the highest pressure deep-sea habitat explored. …”
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A moderately thermophilic origin of a novel family of marine group II euryarchaeota from deep ocean by Haodong Liu, Wei-Wei Liu, Jose M. Haro-Moreno, Bu Xu, Yanfen Zheng, Jiwen Liu, Jiwei Tian, Xiao-Hua Zhang, Ning-Yi Zhou, Liping Qin, Yuanqing Zhu, Francisco Rodriguez-Valera, Chuanlun Zhang

“…In this study, 13 new MGII metagenome-assembled genomes were recovered from surface to the hadal zone in Challenger Deep of the Mariana Trench; four of them from the deep ocean represent a novel group. …”
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DeepPredict: A Zone Preference Prediction System for Online Lodging Platforms by Yihan Ma, Hua Sun, Yang Chen, Jiayun Zhang, Yang Xu, Xin Wang, Pan Hui

“…To tackle the first challenge, DeepPredict involves users’ historical records in all the cities and uses a deep learning based method to process them. …”
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Optimizing Neuro-Oncology Imaging: A Review of Deep Learning Approaches for Glioma Imaging by Madeleine M. Shaver, Paul A. Kohanteb, Catherine Chiou, Michelle D. Bardis, Chanon Chantaduly, Daniela Bota, Christopher G. Filippi, Brent Weinberg, Jack Grinband, Daniel S. Chow, Peter D. Chang

“…This translates into varying degrees of enhancement, edema, and necrosis, making reliable imaging assessment challenging. Deep learning, a subset of machine learning artificial intelligence, has gained traction as a method, which has seen effective employment in solving image-based problems, including those in medical imaging. …”
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