Proteogenomics | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, or the integration of proteomics with genomics and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

NCI-CPTAC DREAM Proteogenomics Challenge (Registration Now Open) | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, integration of proteomics, genomics, and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

APOLLO Network | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes.

Leaderboard Now Open: CPTAC’s DREAM Proteogenomics Computational Challenge | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) is pleased to announce the opening of the leaderboard to its Proteogenomics Computational DREAM Challenge. The leadership board remains open for submissions during September 25, 2017 through October 8, 2017, with the Challenge expected to run until November 17, 2017.

Moonshot Objectives: Catalyze New Scientific Breakthroughs-Proteogenomics.

PubMed

Rodland, Karin D; Piehowski, Paul; Smith, Richard D

Breaking down the silos between disciplines to accelerate the pace of cancer research is a key paradigm for the Cancer Moonshot. Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids-DNA, RNA, and their modifications-and a focus on proteins and protein function. Proteogenomics represents a fusion of those two approaches, leveraging the strengths of each to provide a more integrated vision of the flow of information from DNA to RNA to protein and eventually function at the molecular level. Proteogenomic studies have been incorporated into multiple activities associated with the Cancer Moonshot, demonstrating substantial added value. Innovative study designs integrating genomic, transcriptomic, and proteomic data, particularly those using clinically relevant samples and involving clinical trials, are poised to provide new insights regarding cancer risk, progression, and response to therapy.

A note on the false discovery rate of novel peptides in proteogenomics.

PubMed

Zhang, Kun; Fu, Yan; Zeng, Wen-Feng; He, Kun; Chi, Hao; Liu, Chao; Li, Yan-Chang; Gao, Yuan; Xu, Ping; He, Si-Min

2015-10-15

Proteogenomics has been well accepted as a tool to discover novel genes. In most conventional proteogenomic studies, a global false discovery rate is used to filter out false positives for identifying credible novel peptides. However, it has been found that the actual level of false positives in novel peptides is often out of control and behaves differently for different genomes. To quantitatively model this problem, we theoretically analyze the subgroup false discovery rates of annotated and novel peptides. Our analysis shows that the annotation completeness ratio of a genome is the dominant factor influencing the subgroup FDR of novel peptides. Experimental results on two real datasets of Escherichia coli and Mycobacterium tuberculosis support our conjecture. yfu@amss.ac.cn or xupingghy@gmail.com or smhe@ict.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Proteogenomic characterization of human colon and rectal cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Bing; Wang, Jing; Wang, Xiaojing

2014-09-18

We analyzed proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) and performed integrated proteogenomic analyses. Protein sequence variants encoded by somatic genomic variations displayed reduced expression compared to protein variants encoded by germline variations. mRNA transcript abundance did not reliably predict protein expression differences between tumors. Proteomics identified five protein expression subtypes, two of which were associated with the TCGA "MSI/CIMP" transcriptional subtype, but had distinct mutation and methylation patterns and associated with different clinical outcomes. Although CNAs showed strong cis- and trans-effects on mRNA expression, relatively few of these extend to the proteinmore » level. Thus, proteomics data enabled prioritization of candidate driver genes. Our analyses identified HNF4A, a novel candidate driver gene in tumors with chromosome 20q amplifications. Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords novel insights into cancer biology.« less

Best Performers Announced for the NCI-CPTAC DREAM Proteogenomics Computational Challenge | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) is pleased to announce that teams led by Jaewoo Kang (Korea University), and Yuanfang Guan with Hongyang Li (University of Michigan) as the best performers of the NCI-CPTAC DREAM Proteogenomics Computational Challenge. Over 500 participants from 20 countries registered for the Challenge, which offered $25,000 in cash awards contributed by the NVIDIA Foundation through its Compute the Cure initiative.

Announcing the Launch of CPTAC’s Proteogenomics DREAM Challenge | Office of Cancer Clinical Proteomics Research

Cancer.gov

This week, we are excited to announce the launch of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomics Computational DREAM Challenge.  The aim of this Challenge is to encourage the generation of computational methods for extracting information from the cancer proteome and for linking those data to genomic and transcriptomic information.  The specific goals are to predict proteomic and phosphoproteomic data from other multiple data types including transcriptomics and genetics.

NCI Releases Video: Proteogenomics Research - On the Frontier of Precision Medicine | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), part of the National Institutes of Health, announces the release of an educational video titled “Proteogenomics Research: On the Frontier of Precision Medicine."  Launched at the HUPO2017 Global Leadership Gala Dinner, catalyzed in part by the Cancer Moonshot initiative and featuring as keynote speaker the 47th Vice President of the United States of America Joseph R.

Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Network | Office of Cancer Clinical Proteomics Research

Cancer.gov

July 11, 2016 — In the spirit of collaboration inspired by the Vice President’s Cancer Moonshot, the Department of Veterans Affairs (VA), the Department of Defense (DoD), and the National Cancer Institute (NCI) are proud to announce a new tri-agency coalition that will help cancer patients by enabling their oncologists to more rapidly and accurately identify effective drugs to treat cancer based on a patient’s unique proteogenomic profile.

VIDEO: Dr. Henry Rodriguez - Proteogenomics in Cancer Medicine | Office of Cancer Clinical Proteomics Research

Cancer.gov

Dr. Henry Rodriguez, director of the Office of Cancer Clinical Proteomics Research (OCCPR) at NCI, speaks with ecancer television at WIN 2017 about the translation of the proteins expressed in a patient's tumor into a map for druggable targets. By combining genomic and proteomic information (proteogenomics), leading scientists are gaining new insights into ways to detect and treat cancer due to a more complete and unified understanding of complex biological processes.

Proteogenomic characterization of human colon and rectal cancer

PubMed Central

Zhang, Bing; Wang, Jing; Wang, Xiaojing; Zhu, Jing; Liu, Qi; Shi, Zhiao; Chambers, Matthew C.; Zimmerman, Lisa J.; Shaddox, Kent F.; Kim, Sangtae; Davies, Sherri R.; Wang, Sean; Wang, Pei; Kinsinger, Christopher R.; Rivers, Robert C.; Rodriguez, Henry; Townsend, R. Reid; Ellis, Matthew J.C.; Carr, Steven A.; Tabb, David L.; Coffey, Robert J.; Slebos, Robbert J.C.; Liebler, Daniel C.

2014-01-01

Summary We analyzed proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) and performed integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. mRNA transcript abundance did not reliably predict protein abundance differences between tumors. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA “MSI/CIMP” transcriptomic subtype, but had distinct mutation, methylation, and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates including HNF4A, TOMM34 and SRC. Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology. PMID:25043054

Proteogenomic insights into uranium tolerance of a Chernobyl's Microbacterium bacterial isolate.

PubMed

Gallois, Nicolas; Alpha-Bazin, Béatrice; Ortet, Philippe; Barakat, Mohamed; Piette, Laurie; Long, Justine; Berthomieu, Catherine; Armengaud, Jean; Chapon, Virginie

2018-04-15

Microbacterium oleivorans A9 is a uranium-tolerant actinobacteria isolated from the trench T22 located near the Chernobyl nuclear power plant. This site is contaminated with different radionuclides including uranium. To observe the molecular changes at the proteome level occurring in this strain upon uranyl exposure and understand molecular mechanisms explaining its uranium tolerance, we established its draft genome and used this raw information to perform an in-depth proteogenomics study. High-throughput proteomics were performed on cells exposed or not to 10μM uranyl nitrate sampled at three previously identified phases of uranyl tolerance. We experimentally detected and annotated 1532 proteins and highlighted a total of 591 proteins for which abundances were significantly differing between conditions. Notably, proteins involved in phosphate and iron metabolisms show high dynamics. A large ratio of proteins more abundant upon uranyl stress, are distant from functionally-annotated known proteins, highlighting the lack of fundamental knowledge regarding numerous key molecular players from soil bacteria. Microbacterium oleivorans A9 is an interesting environmental model to understand biological processes engaged in tolerance to radionuclides. Using an innovative proteogenomics approach, we explored its molecular mechanisms involved in uranium tolerance. We sequenced its genome, interpreted high-throughput proteomic data against a six-reading frame ORF database deduced from the draft genome, annotated the identified proteins and compared protein abundances from cells exposed or not to uranyl stress after a cascade search. These data show that a complex cellular response to uranium occurs in Microbacterium oleivorans A9, where one third of the experimental proteome is modified. In particular, the uranyl stress perturbed the phosphate and iron metabolic pathways. Furthermore, several transporters have been identified to be specifically associated to uranyl stress, paving the way to the development of biotechnological tools for uranium decontamination. Copyright © 2017. Published by Elsevier B.V.

An Analysis of the Sensitivity of Proteogenomic Mapping of Somatic Mutations and Novel Splicing Events in Cancer.

PubMed

Ruggles, Kelly V; Tang, Zuojian; Wang, Xuya; Grover, Himanshu; Askenazi, Manor; Teubl, Jennifer; Cao, Song; McLellan, Michael D; Clauser, Karl R; Tabb, David L; Mertins, Philipp; Slebos, Robbert; Erdmann-Gilmore, Petra; Li, Shunqiang; Gunawardena, Harsha P; Xie, Ling; Liu, Tao; Zhou, Jian-Ying; Sun, Shisheng; Hoadley, Katherine A; Perou, Charles M; Chen, Xian; Davies, Sherri R; Maher, Christopher A; Kinsinger, Christopher R; Rodland, Karen D; Zhang, Hui; Zhang, Zhen; Ding, Li; Townsend, R Reid; Rodriguez, Henry; Chan, Daniel; Smith, Richard D; Liebler, Daniel C; Carr, Steven A; Payne, Samuel; Ellis, Matthew J; Fenyő, David

2016-03-01

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (∼80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Proteogenomic analysis of NCC-S1M, a gastric cancer stem cell-like cell line that responds to anti-PD-1.

PubMed

Park, Jun Won; Um, Hyejin; Yang, Hanna; Ko, Woori; Kim, Dae-Yong; Kim, Hark Kyun

2017-03-11

To elucidate signaling pathways that regulate gastric cancer stem cell (CSC) phenotypes and immune checkpoint, we performed a proteogenomic analysis of NCC-S1M, which is a gastric cancer cell line with CSC-like characteristics and is the only syngeneic gastric tumor cell line transplant model created in the scientific community. We found that the NCC-S1M allograft was responsive to anti-PD-1 treatment, and overexpressed Cd274 encoding PD-L1. PD-L1 was transcriptionally activated by loss of the TGF-β signaling. Il1rl1 protein was overexpressed in NCC-S1M cells compared with NCC-S1 cells that are less tumorigenic and less chemoresistant. Il1rl1 knockdown in NCC-S1M cells reduced tumorigenic potential and in vivo chemoresistance. Our proteogenomic analysis demonstrates a role of Smad4 loss in the PD-L1 immune evasion, as well as Il1rl1's role in CSC-like properties of NCC-S1M. Copyright © 2017 Elsevier Inc. All rights reserved.

Rodriguez and Pennington Address Proteogenomics and Data Sharing in the Journal Cell | Office of Cancer Clinical Proteomics Research

Cancer.gov

Precision medicine is an approach that allows doctors to understand how a patient's genetic profile may cause cancer to grow and spread, leading to a more personalized treatment strategy based on molecular characterization of a person's tumor. However, precision medicine as a genomics-based approach does not yet apply to all patients because genetic mutations do not always lead to changes of the corresponding proteins. Therefore, integrating genomics and proteomics data, or proteogenomics, presents as a new approach that may help make precision medicine a more effective treatment option for patients.

Notice of Pre-Application Webinar (RFA-CA-15-021, RFA-CA-15-022, RFA-CA-15-023) | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute will hold a public pre-application webinar on Friday, December 11 at 12:00 p.m. (EST) for the Funding Opportunity Announcements (FOAs) RFA-CA-15-021 entitled “Proteome Characterization Centers for Clinical Proteomic Tumor Analysis Consortium (U24), RFA-CA-15-022 entitled “Proteogenomic Translational Research Centers for Clinical Proteomic Tumor Analysis Consortium (U01)”, and RFA-CA-15-023 entitled “Proteogenomic Data Analysis Centers for Clinical Proteomic Tumor Analysis Consortium (U24)”.

Comprehensive Annotation of the Parastagonospora nodorum Reference Genome Using Next-Generation Genomics, Transcriptomics and Proteogenomics

PubMed Central

Dodhia, Kejal; Stoll, Thomas; Hastie, Marcus; Furuki, Eiko; Ellwood, Simon R.; Williams, Angela H.; Tan, Yew-Foon; Testa, Alison C.; Gorman, Jeffrey J.; Oliver, Richard P.

2016-01-01

Parastagonospora nodorum, the causal agent of Septoria nodorum blotch (SNB), is an economically important pathogen of wheat (Triticum spp.), and a model for the study of necrotrophic pathology and genome evolution. The reference P. nodorum strain SN15 was the first Dothideomycete with a published genome sequence, and has been used as the basis for comparison within and between species. Here we present an updated reference genome assembly with corrections of SNP and indel errors in the underlying genome assembly from deep resequencing data as well as extensive manual annotation of gene models using transcriptomic and proteomic sources of evidence (https://github.com/robsyme/Parastagonospora_nodorum_SN15). The updated assembly and annotation includes 8,366 genes with modified protein sequence and 866 new genes. This study shows the benefits of using a wide variety of experimental methods allied to expert curation to generate a reliable set of gene models. PMID:26840125

Proteogenomics connects somatic mutations to signalling in breast cancer.

PubMed

Mertins, Philipp; Mani, D R; Ruggles, Kelly V; Gillette, Michael A; Clauser, Karl R; Wang, Pei; Wang, Xianlong; Qiao, Jana W; Cao, Song; Petralia, Francesca; Kawaler, Emily; Mundt, Filip; Krug, Karsten; Tu, Zhidong; Lei, Jonathan T; Gatza, Michael L; Wilkerson, Matthew; Perou, Charles M; Yellapantula, Venkata; Huang, Kuan-lin; Lin, Chenwei; McLellan, Michael D; Yan, Ping; Davies, Sherri R; Townsend, R Reid; Skates, Steven J; Wang, Jing; Zhang, Bing; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Ding, Li; Paulovich, Amanda G; Fenyö, David; Ellis, Matthew J; Carr, Steven A

2016-06-02

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

A proteomic map of the unsequenced kala-azar vector Phlebotomus papatasi using cell line.

PubMed

Pawar, Harsh; Chavan, Sandip; Mahale, Kiran; Khobragade, Sweta; Kulkarni, Aditi; Patil, Arun; Chaphekar, Deepa; Varriar, Pratyasha; Sudeep, Anakkathil; Pai, Kalpana; Prasad, T S K; Gowda, Harsha; Patole, Milind S

2015-12-01

The debilitating disease kala-azar or visceral leishmaniasis is caused by the kinetoplastid protozoan parasite Leishmania donovani. The parasite is transmitted by the hematophagous sand fly vector of the genus Phlebotomus in the old world and Lutzomyia in the new world. The predominant Phlebotomine species associated with the transmission of kala-azar are Phlebotomus papatasi and Phlebotomus argentipes. Understanding the molecular interaction of the sand fly and Leishmania, during the development of parasite within the sand fly gut is crucial to the understanding of the parasite life cycle. The complete genome sequences of sand flies (Phlebotomus and Lutzomyia) are currently not available and this hinders identification of proteins in the sand fly vector. The current study utilizes a three frame translated transcriptomic data of P. papatasi in the absence of genomic sequences to analyze the mass spectrometry data of P. papatasi cell line using a proteogenomic approach. Additionally, we have carried out the proteogenomic analysis of P. papatasi by comparative homology-based searches using related sequenced dipteran protein data. This study resulted in the identification of 1313 proteins from P. papatasi based on homology. Our study demonstrates the power of proteogenomic approaches in mapping the proteomes of unsequenced organisms. Copyright © 2015 Elsevier B.V. All rights reserved.

Discovery of rare protein-coding genes in model methylotroph Methylobacterium extorquens AM1.

PubMed

Kumar, Dhirendra; Mondal, Anupam Kumar; Yadav, Amit Kumar; Dash, Debasis

2014-12-01

Proteogenomics involves the use of MS to refine annotation of protein-coding genes and discover genes in a genome. We carried out comprehensive proteogenomic analysis of Methylobacterium extorquens AM1 (ME-AM1) from publicly available proteomics data with a motive to improve annotation for methylotrophs; organisms capable of surviving in reduced carbon compounds such as methanol. Besides identifying 2482(50%) proteins, 29 new genes were discovered and 66 annotated gene models were revised in ME-AM1 genome. One such novel gene is identified with 75 peptides, lacks homolog in other methylobacteria but has glycosyl transferase and lipopolysaccharide biosynthesis protein domains, indicating its potential role in outer membrane synthesis. Many novel genes are present only in ME-AM1 among methylobacteria. Distant homologs of these genes in unrelated taxonomic classes and low GC-content of few genes suggest lateral gene transfer as a potential mode of their origin. Annotations of methylotrophy related genes were also improved by the discovery of a short gene in methylotrophy gene island and redefining a gene important for pyrroquinoline quinone synthesis, essential for methylotrophy. The combined use of proteogenomics and rigorous bioinformatics analysis greatly enhanced the annotation of protein-coding genes in model methylotroph ME-AM1 genome. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteogenomics Dashboard for the Human Proteome Project.

PubMed

Tabas-Madrid, Daniel; Alves-Cruzeiro, Joao; Segura, Victor; Guruceaga, Elizabeth; Vialas, Vital; Prieto, Gorka; García, Carlos; Corrales, Fernando J; Albar, Juan Pablo; Pascual-Montano, Alberto

2015-09-04

dasHPPboard is a novel proteomics-based dashboard that collects and reports the experiments produced by the Spanish Human Proteome Project consortium (SpHPP) and aims to help HPP to map the entire human proteome. We have followed the strategy of analog genomics projects like the Encyclopedia of DNA Elements (ENCODE), which provides a vast amount of data on human cell lines experiments. The dashboard includes results of shotgun and selected reaction monitoring proteomics experiments, post-translational modifications information, as well as proteogenomics studies. We have also processed the transcriptomics data from the ENCODE and Human Body Map (HBM) projects for the identification of specific gene expression patterns in different cell lines and tissues, taking special interest in those genes having little proteomic evidence available (missing proteins). Peptide databases have been built using single nucleotide variants and novel junctions derived from RNA-Seq data that can be used in search engines for sample-specific protein identifications on the same cell lines or tissues. The dasHPPboard has been designed as a tool that can be used to share and visualize a combination of proteomic and transcriptomic data, providing at the same time easy access to resources for proteogenomics analyses. The dasHPPboard can be freely accessed at: http://sphppdashboard.cnb.csic.es.

Salt Stress Induced Changes in the Exoproteome of the Halotolerant Bacterium Tistlia consotensis Deciphered by Proteogenomics

PubMed Central

Rubiano-Labrador, Carolina; Bland, Céline; Miotello, Guylaine; Armengaud, Jean; Baena, Sandra

2015-01-01

The ability of bacteria to adapt to external osmotic changes is fundamental for their survival. Halotolerant microorganisms, such as Tistlia consotensis, have to cope with continuous fluctuations in the salinity of their natural environments which require effective adaptation strategies against salt stress. Changes of extracellular protein profiles from Tistlia consotensis in conditions of low and high salinities were monitored by proteogenomics using a bacterial draft genome. At low salinity, we detected greater amounts of the HpnM protein which is involved in the biosynthesis of hopanoids. This may represent a novel, and previously unreported, strategy by halotolerant microorganisms to prevent the entry of water into the cell under conditions of low salinity. At high salinity, proteins associated with osmosensing, exclusion of Na+ and transport of compatible solutes, such as glycine betaine or proline are abundant. We also found that, probably in response to the high salt concentration, T. consotensis activated the synthesis of flagella and triggered a chemotactic response neither of which were observed at the salt concentration which is optimal for growth. Our study demonstrates that the exoproteome is an appropriate indicator of adaptive response of T. consotensis to changes in salinity because it allowed the identification of key proteins within its osmoadaptive mechanism that had not previously been detected in its cell proteome. PMID:26287734

Ultra-Structure database design methodology for managing systems biology data and analyses

PubMed Central

Maier, Christopher W; Long, Jeffrey G; Hemminger, Bradley M; Giddings, Morgan C

2009-01-01

Background Modern, high-throughput biological experiments generate copious, heterogeneous, interconnected data sets. Research is dynamic, with frequently changing protocols, techniques, instruments, and file formats. Because of these factors, systems designed to manage and integrate modern biological data sets often end up as large, unwieldy databases that become difficult to maintain or evolve. The novel rule-based approach of the Ultra-Structure design methodology presents a potential solution to this problem. By representing both data and processes as formal rules within a database, an Ultra-Structure system constitutes a flexible framework that enables users to explicitly store domain knowledge in both a machine- and human-readable form. End users themselves can change the system's capabilities without programmer intervention, simply by altering database contents; no computer code or schemas need be modified. This provides flexibility in adapting to change, and allows integration of disparate, heterogenous data sets within a small core set of database tables, facilitating joint analysis and visualization without becoming unwieldy. Here, we examine the application of Ultra-Structure to our ongoing research program for the integration of large proteomic and genomic data sets (proteogenomic mapping). Results We transitioned our proteogenomic mapping information system from a traditional entity-relationship design to one based on Ultra-Structure. Our system integrates tandem mass spectrum data, genomic annotation sets, and spectrum/peptide mappings, all within a small, general framework implemented within a standard relational database system. General software procedures driven by user-modifiable rules can perform tasks such as logical deduction and location-based computations. The system is not tied specifically to proteogenomic research, but is rather designed to accommodate virtually any kind of biological research. Conclusion We find Ultra-Structure offers substantial benefits for biological information systems, the largest being the integration of diverse information sources into a common framework. This facilitates systems biology research by integrating data from disparate high-throughput techniques. It also enables us to readily incorporate new data types, sources, and domain knowledge with no change to the database structure or associated computer code. Ultra-Structure may be a significant step towards solving the hard problem of data management and integration in the systems biology era. PMID:19691849

Developments for Personalized Medicine of Lung Cancer Subtypes: Mass Spectrometry-Based Clinical Proteogenomic Analysis of Oncogenic Mutations.

PubMed

Nishimura, Toshihide; Nakamura, Haruhiko

2016-01-01

Molecular therapies targeting lung cancers with mutated epidermal growth factor receptor (EGFR) by EGFR-tyrosin kinase inhibitors (EGFR-TKIs), gefitinib and erlotinib, changed the treatment system of lung cancer. It was revealed that drug efficacy differs by race (e.g., Caucasians vs. Asians) due to oncogenic driver mutations specific to each race, exemplified by gefitinib / erlotinib. The molecular target drugs for lung cancer with anaplastic lymphoma kinase (ALK) gene translocation (the fusion gene, EML4-ALK) was approved, and those targeting lung cancers addicted ROS1, RET, and HER2 have been under development. Both identification and quantification of gatekeeper mutations need to be performed using lung cancer tissue specimens obtained from patients to improve the treatment for lung cancer patients: (1) identification and quantitation data of targeted mutated proteins, including investigation of mutation heterogeneity within a tissue; (2) exploratory mass spectrometry (MS)-based clinical proteogenomic analysis of mutated proteins; and also importantly (3) analysis of dynamic protein-protein interaction (PPI) networks of proteins significantly related to a subgroup of patients with lung cancer not only with good efficacy but also with acquired resistance. MS-based proteogenomics is a promising approach to directly capture mutated and fusion proteins expressed in a clinical sample. Technological developments are further expected, which will provide a powerful solution for the stratification of patients and drug discovery (Precision Medicine).

Proteogenomic Analysis of a Thermophilic Bacterial Consortium Adapted to Deconstruct Switchgrass

DOE Office of Scientific and Technical Information (OSTI.GOV)

D'haeseleer, Patrik; Gladden, John M.; Allgaier, Martin

2013-07-19

Thermophilic bacteria are a potential source of enzymes for the deconstruction of lignocellulosic biomass. However, the complement of proteins used to deconstruct biomass and the specific roles of different microbial groups in thermophilic biomass deconstruction are not well-explored. Here we report on the metagenomic and proteogenomic analyses of a compost-derived bacterial consortium adapted to switchgrass at elevated temperature with high levels of glycoside hydrolase activities. Near-complete genomes were reconstructed for the most abundant populations, which included composite genomes for populations closely related to sequenced strains of Thermus thermophilus and Rhodothermus marinus, and for novel populations that are related to thermophilicmore » Paenibacilli and an uncultivated subdivision of the littlestudied Gemmatimonadetes phylum. Partial genomes were also reconstructed for a number of lower abundance thermophilic Chloroflexi populations. Identification of genes for lignocellulose processing and metabolic reconstructions suggested Rhodothermus, Paenibacillus and Gemmatimonadetes as key groups for deconstructing biomass, and Thermus as a group that may primarily metabolize low molecular weight compounds. Mass spectrometry-based proteomic analysis of the consortium was used to identify .3000 proteins in fractionated samples from the cultures, and confirmed the importance of Paenibacillus and Gemmatimonadetes to biomass deconstruction. These studies also indicate that there are unexplored proteins with important roles in bacterial lignocellulose deconstruction.« less

Toward an Upgraded Honey Bee (Apis mellifera L.) Genome Annotation Using Proteogenomics.

PubMed

McAfee, Alison; Harpur, Brock A; Michaud, Sarah; Beavis, Ronald C; Kent, Clement F; Zayed, Amro; Foster, Leonard J

2016-02-05

The honey bee is a key pollinator in agricultural operations as well as a model organism for studying the genetics and evolution of social behavior. The Apis mellifera genome has been sequenced and annotated twice over, enabling proteomics and functional genomics methods for probing relevant aspects of their biology. One troubling trend that emerged from proteomic analyses is that honey bee peptide samples consistently result in lower peptide identification rates compared with other organisms. This suggests that the genome annotation can be improved, or atypical biological processes are interfering with the mass spectrometry workflow. First, we tested whether high levels of polymorphisms could explain some of the missed identifications by searching spectra against the reference proteome (OGSv3.2) versus a customized proteome of a single honey bee, but our results indicate that this contribution was minor. Likewise, error-tolerant peptide searches lead us to eliminate unexpected post-translational modifications as a major factor in missed identifications. We then used a proteogenomic approach with ~1500 raw files to search for missing genes and new exons, to revive discarded annotations and to identify over 2000 new coding regions. These results will contribute to a more comprehensive genome annotation and facilitate continued research on this important insect.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis

PubMed Central

Tellgren-Roth, Christian; Baudo, Charles D.; Kennell, John C.; Sun, Sheng; Billmyre, R. Blake; Schröder, Markus S.; Andersson, Anna; Holm, Tina; Sigurgeirsson, Benjamin; Wu, Guangxi; Sankaranarayanan, Sundar Ram; Siddharthan, Rahul; Sanyal, Kaustuv; Lundeberg, Joakim; Nystedt, Björn; Boekhout, Teun; Dawson, Thomas L.; Heitman, Joseph

2017-01-01

Abstract Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies. PMID:28100699

CPTAC | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.

Integrated proteomic and genomic analysis of colorectal cancer

Cancer.gov

Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

PubMed

Zhu, Yafeng; Engström, Pär G; Tellgren-Roth, Christian; Baudo, Charles D; Kennell, John C; Sun, Sheng; Billmyre, R Blake; Schröder, Markus S; Andersson, Anna; Holm, Tina; Sigurgeirsson, Benjamin; Wu, Guangxi; Sankaranarayanan, Sundar Ram; Siddharthan, Rahul; Sanyal, Kaustuv; Lundeberg, Joakim; Nystedt, Björn; Boekhout, Teun; Dawson, Thomas L; Heitman, Joseph; Scheynius, Annika; Lehtiö, Janne

2017-03-17

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics.

PubMed

Omasits, Ulrich; Varadarajan, Adithi R; Schmid, Michael; Goetze, Sandra; Melidis, Damianos; Bourqui, Marc; Nikolayeva, Olga; Québatte, Maxime; Patrignani, Andrea; Dehio, Christoph; Frey, Juerg E; Robinson, Mark D; Wollscheid, Bernd; Ahrens, Christian H

2017-12-01

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae , Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote. © 2017 Omasits et al.; Published by Cold Spring Harbor Laboratory Press.

Proteogenomic strategies for identification of aberrant cancer peptides using large-scale Next Generation Sequencing data

DOE PAGES

Woo, Sunghee; Cha, Seong Won; Na, Seungjin; ...

2014-11-17

Cancer is driven by the acquisition of somatic DNA lesions. Distinguishing the early driver mutations from subsequent passenger mutations is key to molecular sub-typing of cancers, and the discovery of novel biomarkers. The availability of genomics technologies (mainly wholegenome and exome sequencing, and transcript sampling via RNA-seq, collectively referred to as NGS) have fueled recent studies on somatic mutation discovery. However, the vision is challenged by the complexity, redundancy, and errors in genomic data, and the difficulty of investigating the proteome using only genomic approaches. Recently, combination of proteomic and genomic technologies are increasingly employed. However, the complexity and redundancymore » of NGS data remains a challenge for proteogenomics, and various trade-offs must be made to allow for the searches to take place. This paperprovides a discussion of two such trade-offs, relating to large database search, and FDR calculations, and their implication to cancer proteogenomics. Moreover, it extends and develops the idea of a unified genomic variant database that can be searched by any mass spectrometry sample. A total of 879 BAM files downloaded from TCGA repository were used to create a 4.34 GB unified FASTA database which contained 2,787,062 novel splice junctions, 38,464 deletions, 1105 insertions, and 182,302 substitutions. Proteomic data from a single ovarian carcinoma sample (439,858 spectra) was searched against the database. By applying the most conservative FDR measure, we have identified 524 novel peptides and 65,578 known peptides at 1% FDR threshold. The novel peptides include interesting examples of doubly mutated peptides, frame-shifts, and non-sample-recruited mutations, which emphasize the strength of our approach.« less

Brute-Force Approach for Mass Spectrometry-Based Variant Peptide Identification in Proteogenomics without Personalized Genomic Data

NASA Astrophysics Data System (ADS)

Ivanov, Mark V.; Lobas, Anna A.; Levitsky, Lev I.; Moshkovskii, Sergei A.; Gorshkov, Mikhail V.

2018-02-01

In a proteogenomic approach based on tandem mass spectrometry analysis of proteolytic peptide mixtures, customized exome or RNA-seq databases are employed for identifying protein sequence variants. However, the problem of variant peptide identification without personalized genomic data is important for a variety of applications. Following the recent proposal by Chick et al. (Nat. Biotechnol. 33, 743-749, 2015) on the feasibility of such variant peptide search, we evaluated two available approaches based on the previously suggested "open" search and the "brute-force" strategy. To improve the efficiency of these approaches, we propose an algorithm for exclusion of false variant identifications from the search results involving analysis of modifications mimicking single amino acid substitutions. Also, we propose a de novo based scoring scheme for assessment of identified point mutations. In the scheme, the search engine analyzes y-type fragment ions in MS/MS spectra to confirm the location of the mutation in the variant peptide sequence.

Proteogenomic Characterization of Monocyclic Aromatic Hydrocarbon Degradation Pathways in the Aniline-Degrading Bacterium Burkholderia sp. K24.

PubMed

Lee, Sang-Yeop; Kim, Gun-Hwa; Yun, Sung Ho; Choi, Chi-Won; Yi, Yoon-Sun; Kim, Jonghyun; Chung, Young-Ho; Park, Edmond Changkyun; Kim, Seung Il

2016-01-01

Burkholderia sp. K24, formerly known as Acinetobacter lwoffii K24, is a soil bacterium capable of utilizing aniline as its sole carbon and nitrogen source. Genomic sequence analysis revealed that this bacterium possesses putative gene clusters for biodegradation of various monocyclic aromatic hydrocarbons (MAHs), including benzene, toluene, and xylene (BTX), as well as aniline. We verified the proposed MAH biodegradation pathways by dioxygenase activity assays, RT-PCR, and LC/MS-based quantitative proteomic analyses. This proteogenomic approach revealed four independent degradation pathways, all converging into the citric acid cycle. Aniline and p-hydroxybenzoate degradation pathways converged into the β-ketoadipate pathway. Benzoate and toluene were degraded through the benzoyl-CoA degradation pathway. The xylene isomers, i.e., o-, m-, and p-xylene, were degraded via the extradiol cleavage pathways. Salicylate was degraded through the gentisate degradation pathway. Our results show that Burkholderia sp. K24 possesses versatile biodegradation pathways, which may be employed for efficient bioremediation of aniline and BTX.

Proteogenomic Characterization of Monocyclic Aromatic Hydrocarbon Degradation Pathways in the Aniline-Degrading Bacterium Burkholderia sp. K24

PubMed Central

Yun, Sung Ho; Choi, Chi-Won; Yi, Yoon-Sun; Kim, Jonghyun; Chung, Young-Ho; Park, Edmond Changkyun; Kim, Seung Il

2016-01-01

Burkholderia sp. K24, formerly known as Acinetobacter lwoffii K24, is a soil bacterium capable of utilizing aniline as its sole carbon and nitrogen source. Genomic sequence analysis revealed that this bacterium possesses putative gene clusters for biodegradation of various monocyclic aromatic hydrocarbons (MAHs), including benzene, toluene, and xylene (BTX), as well as aniline. We verified the proposed MAH biodegradation pathways by dioxygenase activity assays, RT-PCR, and LC/MS-based quantitative proteomic analyses. This proteogenomic approach revealed four independent degradation pathways, all converging into the citric acid cycle. Aniline and p-hydroxybenzoate degradation pathways converged into the β-ketoadipate pathway. Benzoate and toluene were degraded through the benzoyl-CoA degradation pathway. The xylene isomers, i.e., o-, m-, and p-xylene, were degraded via the extradiol cleavage pathways. Salicylate was degraded through the gentisate degradation pathway. Our results show that Burkholderia sp. K24 possesses versatile biodegradation pathways, which may be employed for efficient bioremediation of aniline and BTX. PMID:27124467

ICPC Pilots International Student Training, Paving a Path for Tomorrow’s Cancer Researchers | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Office of Cancer Clinical Proteomics Research at the National Cancer Institute, part of the United States National Institutes of Health, is spearheading the preparationand training of the proteogenomic research workforce on an international scale.

Proteogenomic insights into salt tolerance by a halotolerant alpha-proteobacterium isolated from an Andean saline spring.

PubMed

Rubiano-Labrador, Carolina; Bland, Céline; Miotello, Guylaine; Guérin, Philippe; Pible, Olivier; Baena, Sandra; Armengaud, Jean

2014-01-31

Tistlia consotensis is a halotolerant Rhodospirillaceae that was isolated from a saline spring located in the Colombian Andes with a salt concentration close to seawater (4.5%w/vol). We cultivated this microorganism in three NaCl concentrations, i.e. optimal (0.5%), without (0.0%) and high (4.0%) salt concentration, and analyzed its cellular proteome. For assigning tandem mass spectrometry data, we first sequenced its genome and constructed a six reading frame ORF database from the draft sequence. We annotated only the genes whose products (872) were detected. We compared the quantitative proteome data sets recorded for the three different growth conditions. At low salinity general stress proteins (chaperons, proteases and proteins associated with oxidative stress protection), were detected in higher amounts, probably linked to difficulties for proper protein folding and metabolism. Proteogenomics and comparative genomics pointed at the CrgA transcriptional regulator as a key-factor for the proteome remodeling upon low osmolarity. In hyper-osmotic condition, T. consotensis produced in larger amounts proteins involved in the sensing of changes in salt concentration, as well as a wide panel of transport systems for the transport of organic compatible solutes such as glutamate. We have described here a straightforward procedure in making a new environmental isolate quickly amenable to proteomics. The bacterium Tistlia consotensis was isolated from a saline spring in the Colombian Andes and represents an interesting environmental model to be compared with extremophiles or other moderate organisms. To explore the halotolerance molecular mechanisms of the bacterium T. consotensis, we developed an innovative proteogenomic strategy consisting of i) genome sequencing, ii) quick annotation of the genes whose products were detected by mass spectrometry, and iii) comparative proteomics of cells grown in three salt conditions. We highlighted in this manuscript how efficient such an approach can be compared to time-consuming genome annotation when pointing at the key proteins of a given biological question. We documented a large number of proteins found produced in greater amounts when cells are cultivated in either hypo-osmotic or hyper-osmotic conditions. This article is part of a Special Issue entitled: Trends in Microbial Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Comprehensive annotation of the Glossina pallidipes salivary gland hypertrophy virus from Ethiopian tsetse flies: a proteogenomics approach

USDA-ARS?s Scientific Manuscript database

The Glossina pallidipes salivary gland hypertrophy virus (GpSGHV; family Hytrosaviridae) can establish a chronic covert asymptomatic infection and an acute overt symptomatic infection in its tsetse fly host (Diptera: Glossinidae). Expression of the disease symptoms, the salivary gland hypertrophy sy...

White House Office of the Vice President Announces New Memorandum of Understanding in Clinical Proteogenomics Between the United States and Australia | Office of Cancer Clinical Proteomics Research

Cancer.gov

The White House Office of the Vice President has announced the signing of three Memoranda of Understanding (MOUs) that will make available an unprecedented international dataset to advance cancer research and care.

Software Tools | Office of Cancer Clinical Proteomics Research

Cancer.gov

The CPTAC program develops new approaches to elucidate aspects of the molecular complexity of cancer made from large-scale proteogenomic datasets, and advance them toward precision medicine.  Part of the CPTAC mission is to make data and tools available and accessible to the greater research community to accelerate the discovery process.

Notice of Changes to RFA-CA-15-022 and Pre-Application Webinar | Office of Cancer Clinical Proteomics Research

Cancer.gov

The National Cancer Institute will hold a public Pre-Application webinar on Wednesday, January 13, 2016 at 12:00 p.m. (EST) for the Funding Opportunity Announcement (FOA) RFA-CA-15-022 entitled “Proteogenomic Translational Research Centers for Clinical Proteomic Tumor Analysis Consortium (U01).”

Office Overview | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Office of Cancer Clinical Proteomics Research (OCCPR) at the National Cancer Institute (NCI) aims to improve prevention, early detection, diagnosis, and treatment of cancer by enhancing the understanding of the molecular mechanisms of cancer, advancing proteome/proteogenome science and technology development through community resources (data and reagents), and accelerating the translation of molecular findings into the clinic.

First Large-Scale Proteogenomic Study of Breast Cancer Provides Insight into Potential Therapeutic Targets | Office of Cancer Clinical Proteomics Research

Cancer.gov

News Release: May 25, 2016 — Building on data from The Cancer Genome Atlas (TCGA) project, a multi-institutional team of scientists has completed the first large-scale “proteogenomic” study of breast cancer, linking DNA mutations to protein signaling and helping pinpoint the genes that drive cancer.

47th Vice President of the United States Joseph R. Biden, Jr. to deliver keynote address at HUPO2017 Global Leadership Gala Dinner | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Human Proteome Organization (HUPO) and Prof Steve Pennington, UCD, chair of the organizing committee of HUPO2017 (the 16th HUPO World Congress) in collaboration with the National Cancer Institute’s (NCI) International Cancer Proteogenome Consortium (ICPC) ann

A Proteogenomic Approach to Understanding MYC Function in Metastatic Medulloblastoma Tumors.

PubMed

Staal, Jerome A; Pei, Yanxin; Rood, Brian R

2016-10-19

Brain tumors are the leading cause of cancer-related deaths in children, and medulloblastoma is the most prevalent malignant childhood/pediatric brain tumor. Providing effective treatment for these cancers, with minimal damage to the still-developing brain, remains one of the greatest challenges faced by clinicians. Understanding the diverse events driving tumor formation, maintenance, progression, and recurrence is necessary for identifying novel targeted therapeutics and improving survival of patients with this disease. Genomic copy number alteration data, together with clinical studies, identifies c-MYC amplification as an important risk factor associated with the most aggressive forms of medulloblastoma with marked metastatic potential. Yet despite this, very little is known regarding the impact of such genomic abnormalities upon the functional biology of the tumor cell. We discuss here how recent advances in quantitative proteomic techniques are now providing new insights into the functional biology of these aggressive tumors, as illustrated by the use of proteomics to bridge the gap between the genotype and phenotype in the case of c-MYC -amplified/associated medulloblastoma. These integrated proteogenomic approaches now provide a new platform for understanding cancer biology by providing a functional context to frame genomic abnormalities.

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hui; Liu, Tao; Zhang, Zhen

Ovarian cancer remains the most lethal gynecological malignancy in the developed world, despite recent advances in genomic information and treatment. To better understand this disease, define an integrated proteogenomic landscape, and identify factors associated with homologous repair deficiency (HRD) and overall survival, we performed a comprehensive proteomic characterization of ovarian high-grade serous carcinomas (HGSC) previously characterized by The Cancer Genome Atlas (TCGA). We observed that messenger RNA transcript abundance did not reliably predict abundance for 10,030 proteins across 174 tumors. Clustering of tumors based on protein abundance identified five subtypes, two of which correlated robustly with mesenchymal and proliferative subtypes,more » while tumors characterized as immunoreactive or differentiated at the transcript level were intermixed at the protein level. At the genome level, HGSC is characterized by a complex landscape of somatic copy number alterations (CNA), which individually do not correlate significantly with survival. Correlation of CNAs with protein abundances identified loci with significant trans regulatory effects mapping to pathways associated with proliferation, cell motility/invasion, and immune regulation, three known hallmarks of cancer. Using the trans regulated proteins we also created models significantly correlated with patient survival by multivariate analysis. Integrating protein abundance with specific post-translational modification data identified subnetworks correlated with HRD status; specifically, acetylation of Lys12 and Lys16 on histone H4 was associated with HRD status. Using quantitative phosphoproteomics data covering 4,420 proteins as reflective of pathway activity, we identified the PDGFR and VEGFR signaling pathways as significantly up-regulated in patients with short overall survival, independent of PDGFR and VEGFR protein levels, potentially informing the use of anti-angiogenic therapies. Components of the Rho/Rac/Cdc42 cell motility pathways were also significantly enriched for short survival. Overall, proteomics provided new insights into ovarian cancer not apparent from genomic analysis and enabling a deeper understanding of HGSC with the potential to inform targeted therapeutics.« less

CPTAC Announces New PTRCs, PCCs, and PGDACs | Office of Cancer Clinical Proteomics Research

Cancer.gov

This week, the Office of Cancer Clinical Proteomics Research (OCCPR) at the National Cancer Institute (NCI), part of the National Institutes of Health, announced its aim to further the convergence of proteomics with genomics – “proteogenomics,” to better understand the molecular basis of cancer and accelerate research in these areas by disseminating research resources to the scientific community.

In Planta Proteomics and Proteogenomics of the Biotrophic Barley Fungal Pathogen Blumeria graminis f. sp. hordei*

PubMed Central

Bindschedler, Laurence V.; Burgis, Timothy A.; Mills, Davinia J. S.; Ho, Jenny T. C.; Cramer, Rainer; Spanu, Pietro D.

2009-01-01

To further our understanding of powdery mildew biology during infection, we undertook a systematic shotgun proteomics analysis of the obligate biotroph Blumeria graminis f. sp. hordei at different stages of development in the host. Moreover we used a proteogenomics approach to feed information into the annotation of the newly sequenced genome. We analyzed and compared the proteomes from three stages of development representing different functions during the plant-dependent vegetative life cycle of this fungus. We identified 441 proteins in ungerminated spores, 775 proteins in epiphytic sporulating hyphae, and 47 proteins from haustoria inside barley leaf epidermal cells and used the data to aid annotation of the B. graminis f. sp. hordei genome. We also compared the differences in the protein complement of these key stages. Although confirming some of the previously reported findings and models derived from the analysis of transcriptome dynamics, our results also suggest that the intracellular haustoria are subject to stress possibly as a result of the plant defense strategy, including the production of reactive oxygen species. In addition, a number of small haustorial proteins with a predicted N-terminal signal peptide for secretion were identified in infected tissues: these represent candidate effector proteins that may play a role in controlling host metabolism and immunity. PMID:19602707

From proteomics to systems biology: MAPA, MASS WESTERN, PROMEX, and COVAIN as a user-oriented platform.

PubMed

Weckwerth, Wolfram; Wienkoop, Stefanie; Hoehenwarter, Wolfgang; Egelhofer, Volker; Sun, Xiaoliang

2014-01-01

Genome sequencing and systems biology are revolutionizing life sciences. Proteomics emerged as a fundamental technique of this novel research area as it is the basis for gene function analysis and modeling of dynamic protein networks. Here a complete proteomics platform suited for functional genomics and systems biology is presented. The strategy includes MAPA (mass accuracy precursor alignment; http://www.univie.ac.at/mosys/software.html ) as a rapid exploratory analysis step; MASS WESTERN for targeted proteomics; COVAIN ( http://www.univie.ac.at/mosys/software.html ) for multivariate statistical analysis, data integration, and data mining; and PROMEX ( http://www.univie.ac.at/mosys/databases.html ) as a database module for proteogenomics and proteotypic peptides for targeted analysis. Moreover, the presented platform can also be utilized to integrate metabolomics and transcriptomics data for the analysis of metabolite-protein-transcript correlations and time course analysis using COVAIN. Examples for the integration of MAPA and MASS WESTERN data, proteogenomic and metabolic modeling approaches for functional genomics, phosphoproteomics by integration of MOAC (metal-oxide affinity chromatography) with MAPA, and the integration of metabolomics, transcriptomics, proteomics, and physiological data using this platform are presented. All software and step-by-step tutorials for data processing and data mining can be downloaded from http://www.univie.ac.at/mosys/software.html.

Proteogenomic Investigation of Strain Variation in Clinical Mycobacterium tuberculosis Isolates.

PubMed

Heunis, Tiaan; Dippenaar, Anzaan; Warren, Robin M; van Helden, Paul D; van der Merwe, Ruben G; Gey van Pittius, Nicolaas C; Pain, Arnab; Sampson, Samantha L; Tabb, David L

2017-10-06

Mycobacterium tuberculosis consists of a large number of different strains that display unique virulence characteristics. Whole-genome sequencing has revealed substantial genetic diversity among clinical M. tuberculosis isolates, and elucidating the phenotypic variation encoded by this genetic diversity will be of the utmost importance to fully understand M. tuberculosis biology and pathogenicity. In this study, we integrated whole-genome sequencing and mass spectrometry (GeLC-MS/MS) to reveal strain-specific characteristics in the proteomes of two clinical M. tuberculosis Latin American-Mediterranean isolates. Using this approach, we identified 59 peptides containing single amino acid variants, which covered ∼9% of all coding nonsynonymous single nucleotide variants detected by whole-genome sequencing. Furthermore, we identified 29 distinct peptides that mapped to a hypothetical protein not present in the M. tuberculosis H37Rv reference proteome. Here, we provide evidence for the expression of this protein in the clinical M. tuberculosis SAWC3651 isolate. The strain-specific databases enabled confirmation of genomic differences (i.e., large genomic regions of difference and nonsynonymous single nucleotide variants) in these two clinical M. tuberculosis isolates and allowed strain differentiation at the proteome level. Our results contribute to the growing field of clinical microbial proteogenomics and can improve our understanding of phenotypic variation in clinical M. tuberculosis isolates.

Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yao, Qiuming; Li, Zhou; Song, Yang

Phosphorus (P) is a scarce nutrient in many tropical ecosystems, yet how soil microbial communities cope with growth-limiting P deficiency at the gene and protein levels remains unknown. Here we report a metagenomic and metaproteomic comparison of microbial communities in P-deficient and P-rich soils in a 17-year fertilization experiment in a tropical forest. The large-scale proteogenomics analyses provided extensive coverage of many microbial functions and taxa in the complex soil communities. A >4-fold increase in the gene abundance of 3-phytase was the strongest response of soil communities to P deficiency. Phytase catalyzes the release of phosphate from phytate, the mostmore » recalcitrant P-containing compound in soil organic matter. Genes and proteins for the degradation of P-containing nucleic acids and phospholipids as well as the decomposition of labile carbon and nitrogen were also enhanced in the P-deficient soils. In contrast, microbial communities in the P-rich soils showed increased gene abundances for the degradation of recalcitrant aromatic compounds, the transformation of nitrogenous compounds, and the assimilation of sulfur. Overall, these results demonstrate the adaptive allocation of genes and proteins in soil microbial communities in response to shifting nutrient constraints.« less

Keep your Sox on: Community genomics-directed isolation and microscopic characterization of the dominant subsurface sulfur-oxidizing bacterium in a sediment aquifer

NASA Astrophysics Data System (ADS)

Mullin, S. W.; Wrighton, K. C.; Luef, B.; Wilkins, M. J.; Handley, K. M.; Williams, K. H.; Banfield, J. F.

2012-12-01

Community genomics and proteomics (proteogenomics) can be used to predict the metabolic potential of complex microbial communities and provide insight into microbial activity and nutrient cycling in situ. Inferences regarding the physiology of specific organisms then can guide isolation efforts, which, if successful, can yield strains that can be metabolically and structurally characterized to further test metagenomic predictions. Here we used proteogenomic data from an acetate-stimulated, sulfidic sediment column deployed in a groundwater well in Rifle, CO to direct laboratory amendment experiments to isolate a bacterial strain potentially involved in sulfur oxidation for physiological and microscopic characterization (Handley et al, submitted 2012). Field strains of Sulfurovum (genome r9c2) were predicted to be capable of CO2 fixation via the reverse TCA cycle and sulfur oxidation (Sox and SQR) coupled to either nitrate reduction (Nap, Nir, Nos) in anaerobic environments or oxygen reduction in microaerobic (cbb3 and bd oxidases) environments; however, key genes for sulfur oxidation (soxXAB) were not identified. Sulfidic groundwater and sediment from the Rifle site were used to inoculate cultures that contained various sulfur species, with and without nitrate and oxygen. We isolated a bacterium, Sulfurovum sp. OBA, whose 16S rRNA gene shares 99.8 % identity to the gene of the dominant genomically characterized strain (genome r9c2) in the Rifle sediment column. The 16S rRNA gene of the isolate most closely matches (95 % sequence identity) the gene of Sulfurovum sp. NBC37-1, a genome-sequenced deep-sea sulfur oxidizer. Strain OBA grew via polysulfide, colloidal sulfur, and tetrathionate oxidation coupled to nitrate reduction under autotrophic and mixotrophic conditions. Strain OBA also grew heterotrophically, oxidizing glucose, fructose, mannose, and maltose with nitrate as an electron acceptor. Over the range of oxygen concentrations tested, strain OBA was not capable of aerobic growth, but it could tolerate low oxygen conditions in the polysulfide/nitrate growth medium, suggesting that oxidases identified by genomics may play a role in detoxification rather than energy generation. Cryo-TEM imaging showed that strain OBA cells are rod-shaped and ~0.4 wide and 1.0 μm in length, and confirmed metagenomics-based predictions of a Gram-negative cell envelope, pili and polyphosphate body production. Our results show the value of integrating metagenomics, culturing, and microscopic imaging to discern the physiology of bacteria involved in biogeochemical transformations in the subsurface.

Integrated proteogenomic characterization of human high grade serous ovarian cancer

PubMed Central

Zhang, Bai; McDermott, Jason E; Zhou, Jian-Ying; Petyuk, Vladislav A; Chen, Li; Ray, Debjit; Sun, Shisheng; Yang, Feng; Chen, Lijun; Wang, Jing; Shah, Punit; Cha, Seong Won; Aiyetan, Paul; Woo, Sunghee; Tian, Yuan; Gritsenko, Marina A; Clauss, Therese R; Choi, Caitlin; Monroe, Matthew E; Thomas, Stefani; Nie, Song; Wu, Chaochao; Moore, Ronald J; Yu, Kun-Hsing; Tabb, David L; Fenyö, David; Bafna, Vineet; Wang, Yue; Rodriguez, Henry; Boja, Emily S; Hiltke, Tara; Rivers, Robert C; Sokoll, Lori; Zhu, Heng; Shih, Ie-Ming; Cope, Leslie; Pandey, Akhilesh; Zhang, Bing; Snyder, Michael P; Levine, Douglas A; Smith, Richard D

2016-01-01

SUMMARY To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSC). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease such as how different copy number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, as well as the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. PMID:27372738

Unravelling ancient microbial history with community proteogenomics and lipid geochemistry.

PubMed

Brocks, Jochen J; Banfield, Jillian

2009-08-01

Our window into the Earth's ancient microbial past is narrow and obscured by missing data. However, we can glean information about ancient microbial ecosystems using fossil lipids (biomarkers) that are extracted from billion-year-old sedimentary rocks. In this Opinion article, we describe how environmental genomics and related methodologies will give molecular fossil research a boost, by increasing our knowledge about how evolutionary innovations in microorganisms have changed the surface of planet Earth.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruggles, Kelly V.; Tang, Zuojian; Wang, Xuya

Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations and splice variants identified in cancer cells are translated. Herein we therefore describe a proteogenomic data integration tool (QUILTS) and illustrate its application to whole genome, transcriptome and global MS peptide sequence datasets generated from a pair of luminal and basal-like breast cancer patient derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS process replicates. Despite over thirty sample replicates, only about 10% of all SNV (somatic andmore » germline) were detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNV without a detectable mRNA transcript were also observed demonstrating the transcriptome coverage was also incomplete (~80%). In contrast to germ-line variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than the luminal tumor raising the possibility of differential translation or protein degradation effects. In conclusion, the QUILTS program integrates DNA, RNA and peptide sequencing to assess the degree to which somatic mutations are translated and therefore biologically active. By identifying gaps in sequence coverage QUILTS benchmarks current technology and assesses progress towards whole cancer proteome and transcriptome analysis.« less

CPTAC Team Releases Targeted Proteomic Assays for Ovarian Cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Pacific Northwest National Laboratory (PNNL) investigators in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), announces the public release of 98 targeted mass spectrometry-based assays for ovarian cancer research studies.  Chosen based on proteogenomic observations from the recently published multi-institutional collaborative project between PNNL and Johns Hopkins University that comprehensively examined the collections of proteins in the tumors of ovarian cancer patients (highlighted in a paper in

CPTAC Releases Cancer Proteome Confirmatory Breast Study Data | Office of Cancer Clinical Proteomics Research

Cancer.gov

An estimated 252,710 new cases of female breast cancer, accounting for 15% of all new cancer cases, occurred in 2017. To better understand proteogenomic abnormalities in breast cancer, the National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) announces the release of the cancer proteome confirmatory breast study data. The goal of the study was to comprehensively characterize the proteome and phosphoproteome on approximately 100 prospectively collected breast tumor and adjacent normal tissues.

Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

PubMed

Shukla, Hem D

2017-10-25

During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics data, are indispensable to glean into the cancer genome and proteome and these approaches have generated multidimensional universal studies of genes and proteins (OMICS) data which has the potential to facilitate precision medicine. However, due to slow progress in computational technologies, the translation of big omics data into their clinical aspects have been slow. In this review, attempts have been made to describe the role of high-throughput genomic and proteomic technologies in identifying a panel of biomarkers which could be used for the early diagnosis and prognosis of cancer.

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer.

PubMed

Zhang, Hui; Liu, Tao; Zhang, Zhen; Payne, Samuel H; Zhang, Bai; McDermott, Jason E; Zhou, Jian-Ying; Petyuk, Vladislav A; Chen, Li; Ray, Debjit; Sun, Shisheng; Yang, Feng; Chen, Lijun; Wang, Jing; Shah, Punit; Cha, Seong Won; Aiyetan, Paul; Woo, Sunghee; Tian, Yuan; Gritsenko, Marina A; Clauss, Therese R; Choi, Caitlin; Monroe, Matthew E; Thomas, Stefani; Nie, Song; Wu, Chaochao; Moore, Ronald J; Yu, Kun-Hsing; Tabb, David L; Fenyö, David; Bafna, Vineet; Wang, Yue; Rodriguez, Henry; Boja, Emily S; Hiltke, Tara; Rivers, Robert C; Sokoll, Lori; Zhu, Heng; Shih, Ie-Ming; Cope, Leslie; Pandey, Akhilesh; Zhang, Bing; Snyder, Michael P; Levine, Douglas A; Smith, Richard D; Chan, Daniel W; Rodland, Karin D

2016-07-28

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT. Copyright © 2016 Elsevier Inc. All rights reserved.

A Pilot Proteogenomic Study with Data Integration Identifies MCT1 and GLUT1 as Prognostic Markers in Lung Adenocarcinoma.

PubMed

Stewart, Paul A; Parapatics, Katja; Welsh, Eric A; Müller, André C; Cao, Haoyun; Fang, Bin; Koomen, John M; Eschrich, Steven A; Bennett, Keiryn L; Haura, Eric B

2015-01-01

We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma. Data are available via ProteomeXchange with identifier PXD002622.

Proteogenomics Identifies New Biology in Ovarian Cancer and Insights to Diagnosis, Treatment | Office of Cancer Clinical Proteomics Research

Cancer.gov

June 29, 2016 — In what is believed to be the largest study of its kind, scientists at Johns Hopkins University (JHU) and Pacific Northwest National Laboratory (PNNL) led a multi-institutional collaborative project that comprehensively examined the collections of proteins in the tumors of 169 ovarian cancer patients to identify critical proteins expressed by their tumors. By integrating their findings about the collection of proteins (the proteome) with information already known about the tumors’ genetic data (the genome), the investigators r

Fred Hutch's Paulovich Laboratory to Lead Protein Assay Work for National Beau Biden Cancer Moonshot | Office of Cancer Clinical Proteomics Research

Cancer.gov

The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network, which is a partnership among the National Cancer Institute, Department of Defense, and Department of Veterans Affairs, has tapped the Paulovich Laboratory at Fred Hutchinson Cancer Research Center to create a panel of tests to measure key proteins that can serve as markers for tumors. The effort could ultimately lead to treatments that are more specifically targeted to a patient’s distinct type of cancer.  

CPTAC researchers report first large-scale integrated proteomic and genomic analysis of a human cancer | Office of Cancer Clinical Proteomics Research

Cancer.gov

Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, provides a more comprehensive view of the biological features that drive cancer than genomic analysis alone and may help identify the most important targets for cancer detection and intervention.

A Pan-Cancer Proteogenomic Atlas of PI3K/AKT/mTOR Pathway Alterations | Office of Cancer Genomics

Cancer.gov

Molecular alterations involving the PI3K/Akt/mTOR pathway (including mutation, copy number, protein, or RNA) were examined across 11,219 human cancers representing 32 major types. Within specific mutated genes, frequency, mutation hotspot residues, in silico predictions, and functional assays were all informative in distinguishing the subset of genetic variants more likely to have functional relevance. Multiple oncogenic pathways including PI3K/Akt/mTOR converged on similar sets of downstream transcriptional targets.

Multi-Omics Driven Assembly and Annotation of the Sandalwood (Santalum album) Genome.

PubMed

Mahesh, Hirehally Basavarajegowda; Subba, Pratigya; Advani, Jayshree; Shirke, Meghana Deepak; Loganathan, Ramya Malarini; Chandana, Shankara Lingu; Shilpa, Siddappa; Chatterjee, Oishi; Pinto, Sneha Maria; Prasad, Thottethodi Subrahmanya Keshava; Gowda, Malali

2018-04-01

Indian sandalwood ( Santalum album ) is an important tropical evergreen tree known for its fragrant heartwood-derived essential oil and its valuable carving wood. Here, we applied an integrated genomic, transcriptomic, and proteomic approach to assemble and annotate the Indian sandalwood genome. Our genome sequencing resulted in the establishment of a draft map of the smallest genome for any woody tree species to date (221 Mb). The genome annotation predicted 38,119 protein-coding genes and 27.42% repetitive DNA elements. In-depth proteome analysis revealed the identities of 72,325 unique peptides, which confirmed 10,076 of the predicted genes. The addition of transcriptomic and proteogenomic approaches resulted in the identification of 53 novel proteins and 34 gene-correction events that were missed by genomic approaches. Proteogenomic analysis also helped in reassigning 1,348 potential noncoding RNAs as bona fide protein-coding messenger RNAs. Gene expression patterns at the RNA and protein levels indicated that peptide sequencing was useful in capturing proteins encoded by nuclear and organellar genomes alike. Mass spectrometry-based proteomic evidence provided an unbiased approach toward the identification of proteins encoded by organellar genomes. Such proteins are often missed in transcriptome data sets due to the enrichment of only messenger RNAs that contain poly(A) tails. Overall, the use of integrated omic approaches enhanced the quality of the assembly and annotation of this nonmodel plant genome. The availability of genomic, transcriptomic, and proteomic data will enhance genomics-assisted breeding, germplasm characterization, and conservation of sandalwood trees. © 2018 American Society of Plant Biologists. All Rights Reserved.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications.

PubMed

Jimenez, Connie R; Verheul, Henk M W

2014-01-01

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

pyGeno: A Python package for precision medicine and proteogenomics.

PubMed

Daouda, Tariq; Perreault, Claude; Lemieux, Sébastien

2016-01-01

pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standalone program, pyGeno gives the user access to the complete expressivity of Python, a general programming language. Its range of application therefore encompasses both short scripts and large scale genome-wide studies.

pyGeno: A Python package for precision medicine and proteogenomics

PubMed Central

Daouda, Tariq; Perreault, Claude; Lemieux, Sébastien

2016-01-01

pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standalone program, pyGeno gives the user access to the complete expressivity of Python, a general programming language. Its range of application therefore encompasses both short scripts and large scale genome-wide studies. PMID:27785359

Biomolecular pathogenesis of borderline ovarian tumors: focusing target discovery through proteogenomics.

PubMed

Vergara, D; Tinelli, A; Martignago, R; Malvasi, A; Chiuri, V E; Leo, G

2010-02-01

Tumors of the epithelial surface account for about 80% of all ovarian neoplasms and exhibit a heterogeneous histological classification affecting survival. Tumors of low malignant potential, defined as borderline ovarian tumors(BOTs), have a markedly better survival and low recurrence, even if surgery still represents the common management for this type of cancer. It is still debated in the literature if BOTs can be considered as intermediate precursors in the progression to high grade ovarian tumors. Evidences now propose that high-grade serous carcinomas are not associated with a defined precursor lesion. Together with histopathological studies, mutations of KRAS, BRAF and p53 genes, microsatellite instability (MSI)and under- or over-expression of many genes and proteins have been used to address this question. Despite the large body of data summarized, a limited number of molecules proved to be useful in elucidating BOTs pathogenesis and only a few of these showed possible application in the therapy. We believe that high-throughput technologies would help to overcome these limitations offering the promise of a better understanding of BOTs classification. The aim is to guide the diagnosis and prognosis of BOTs to develop new possible therapeutic molecular targets avoiding surgery.

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

PubMed

Park, Gun Wook; Hwang, Heeyoun; Kim, Kwang Hoe; Lee, Ju Yeon; Lee, Hyun Kyoung; Park, Ji Yeong; Ji, Eun Sun; Park, Sung-Kyu Robin; Yates, John R; Kwon, Kyung-Hoon; Park, Young Mok; Lee, Hyoung-Joo; Paik, Young-Ki; Kim, Jin Young; Yoo, Jong Shin

2016-11-04

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Proteogenomic Analysis Greatly Expands the Identification of Proteins Related to Reproduction in the Apogamous Fern Dryopteris affinis ssp. affinis.

PubMed

Grossmann, Jonas; Fernández, Helena; Chaubey, Pururawa M; Valdés, Ana E; Gagliardini, Valeria; Cañal, María J; Russo, Giancarlo; Grossniklaus, Ueli

2017-01-01

Performing proteomic studies on non-model organisms with little or no genomic information is still difficult. However, many specific processes and biochemical pathways occur only in species that are poorly characterized at the genomic level. For example, many plants can reproduce both sexually and asexually, the first one allowing the generation of new genotypes and the latter their fixation. Thus, both modes of reproduction are of great agronomic value. However, the molecular basis of asexual reproduction is not well understood in any plant. In ferns, it combines the production of unreduced spores (diplospory) and the formation of sporophytes from somatic cells (apogamy). To set the basis to study these processes, we performed transcriptomics by next-generation sequencing (NGS) and shotgun proteomics by tandem mass spectrometry in the apogamous fern D. affinis ssp. affinis . For protein identification we used the public viridiplantae database (VPDB) to identify orthologous proteins from other plant species and new transcriptomics data to generate a "species-specific transcriptome database" (SSTDB). In total 1,397 protein clusters with 5,865 unique peptide sequences were identified (13 decoy proteins out of 1,410, protFDR 0.93% on protein cluster level). We show that using the SSTDB for protein identification increases the number of identified peptides almost four times compared to using only the publically available VPDB. We identified homologs of proteins involved in reproduction of higher plants, including proteins with a potential role in apogamy. With the increasing availability of genomic data from non-model species, similar proteogenomics approaches will improve the sensitivity in protein identification for species only distantly related to models.

Metaproteogenomic Profiling of Microbial Communities Colonizing Actively Venting Hydrothermal Chimneys

PubMed Central

Pjevac, Petra; Meier, Dimitri V.; Markert, Stephanie; Hentschker, Christian; Schweder, Thomas; Becher, Dörte; Gruber-Vodicka, Harald R.; Richter, Michael; Bach, Wolfgang; Amann, Rudolf; Meyerdierks, Anke

2018-01-01

At hydrothermal vent sites, chimneys consisting of sulfides, sulfates, and oxides are formed upon contact of reduced hydrothermal fluids with oxygenated seawater. The walls and surfaces of these chimneys are an important habitat for vent-associated microorganisms. We used community proteogenomics to investigate and compare the composition, metabolic potential and relative in situ protein abundance of microbial communities colonizing two actively venting hydrothermal chimneys from the Manus Basin back-arc spreading center (Papua New Guinea). We identified overlaps in the in situ functional profiles of both chimneys, despite differences in microbial community composition and venting regime. Carbon fixation on both chimneys seems to have been primarily mediated through the reverse tricarboxylic acid cycle and fueled by sulfur-oxidation, while the abundant metabolic potential for hydrogen oxidation and carbon fixation via the Calvin–Benson–Bassham cycle was hardly utilized. Notably, the highly diverse microbial community colonizing the analyzed black smoker chimney had a highly redundant metabolic potential. In contrast, the considerably less diverse community colonizing the diffusely venting chimney displayed a higher metabolic versatility. An increased diversity on the phylogenetic level is thus not directly linked to an increased metabolic diversity in microbial communities that colonize hydrothermal chimneys. PMID:29696004

Assessing the Exoproteome of Marine Bacteria, Lesson from a RTX-Toxin Abundantly Secreted by Phaeobacter Strain DSM 17395

PubMed Central

Durighello, Emie; Christie-Oleza, Joseph Alexander; Armengaud, Jean

2014-01-01

Bacteria from the Roseobacter clade are abundant in surface marine ecosystems as over 10% of bacterial cells in the open ocean and 20% in coastal waters belong to this group. In order to document how these marine bacteria interact with their environment, we analyzed the exoproteome of Phaeobacter strain DSM 17395. We grew the strain in marine medium, collected the exoproteome and catalogued its content with high-throughput nanoLC-MS/MS shotgun proteomics. The major component represented 60% of the total protein content but was refractory to either classical proteomic identification or proteogenomics. We de novo sequenced this abundant protein with high-resolution tandem mass spectra which turned out being the 53 kDa RTX-toxin ZP_02147451. It comprised a peptidase M10 serralysin domain. We explained its recalcitrance to trypsin proteolysis and proteomic identification by its unusual low number of basic residues. We found this is a conserved trait in RTX-toxins from Roseobacter strains which probably explains their persistence in the harsh conditions around bacteria. Comprehensive analysis of exoproteomes from environmental bacteria should take into account this proteolytic recalcitrance. PMID:24586966

Assessing the exoproteome of marine bacteria, lesson from a RTX-toxin abundantly secreted by Phaeobacter strain DSM 17395.

PubMed

Durighello, Emie; Christie-Oleza, Joseph Alexander; Armengaud, Jean

2014-01-01

Bacteria from the Roseobacter clade are abundant in surface marine ecosystems as over 10% of bacterial cells in the open ocean and 20% in coastal waters belong to this group. In order to document how these marine bacteria interact with their environment, we analyzed the exoproteome of Phaeobacter strain DSM 17395. We grew the strain in marine medium, collected the exoproteome and catalogued its content with high-throughput nanoLC-MS/MS shotgun proteomics. The major component represented 60% of the total protein content but was refractory to either classical proteomic identification or proteogenomics. We de novo sequenced this abundant protein with high-resolution tandem mass spectra which turned out being the 53 kDa RTX-toxin ZP_02147451. It comprised a peptidase M10 serralysin domain. We explained its recalcitrance to trypsin proteolysis and proteomic identification by its unusual low number of basic residues. We found this is a conserved trait in RTX-toxins from Roseobacter strains which probably explains their persistence in the harsh conditions around bacteria. Comprehensive analysis of exoproteomes from environmental bacteria should take into account this proteolytic recalcitrance.

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline

PubMed Central

Rudnick, Paul A.; Markey, Sanford P.; Roth, Jeri; Mirokhin, Yuri; Yan, Xinjian; Tchekhovskoi, Dmitrii V.; Edwards, Nathan J.; Thangudu, Ratna R.; Ketchum, Karen A.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Stephen E.

2016-01-01

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics datasets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and non-reference markers of cancer. The CPTAC labs have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these datasets were produced from 2D LC-MS/MS analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) Peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false discovery rate (FDR)-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the datasets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level (“rolled-up”) precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ™. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data, enabling comparisons between different samples and cancer types as well as across the major ‘omics fields. PMID:26860878

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline.

PubMed

Rudnick, Paul A; Markey, Sanford P; Roth, Jeri; Mirokhin, Yuri; Yan, Xinjian; Tchekhovskoi, Dmitrii V; Edwards, Nathan J; Thangudu, Ratna R; Ketchum, Karen A; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Stein, Stephen E

2016-03-04

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics data sets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and nonreference markers of cancer. The CPTAC laboratories have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these data sets were produced from 2D liquid chromatography-tandem mass spectrometry analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) peak-picking and quantitative data extraction, (2) database searching, (3) gene-based protein parsimony, and (4) false-discovery rate-based filtering. The pipeline also produces localization scores for the phosphopeptide enrichment studies using the PhosphoRS program. Quantitative information for each of the data sets is specific to the sample processing, with PSM and protein reports containing the spectrum-level or gene-level ("rolled-up") precursor peak areas and spectral counts for label-free or reporter ion log-ratios for 4plex iTRAQ. The reports are available in simple tab-delimited formats and, for the PSM-reports, in mzIdentML. The goal of the CDAP is to provide standard, uniform reports for all of the CPTAC data to enable comparisons between different samples and cancer types as well as across the major omics fields.

Proteogenemic Approaches for the Molecular Characterization of Natural Microbial Communities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banfield, Jillian F.

2014-04-25

Microbial biofilms involved in acid mine drainage formation have served as a model systems for the study of microbial communities. Over the grant period we developed community metagenomic methods for recovery of genomes of uncultivated bacteria, archaea, viruses/phage, and plasmids from natural systems. We leveraged highly curated metagenomic datasets to develop methods to monitor microbial function in situ. Beyond new insight into extremophilic microbial ecosystems, we have shown that our strain-resolved proteogenomic methods can be applied to other systems. Our studies have uncovered new patters of inter-species recombination that likely lead to fine-scale environmental adaptation, defined the importance of inter-speciesmore » vs. intra-species recombination in archaea, and evaluated the processes shaping fine-scale sequence variation. The project was the subject of study for six Ph.D. students, two of whom are now Associate Professors, the others are post docs; for M.S. or undergraduate researchers, and thirteen post docs, ten of which are now Assistant or Associate professors. The research generated 53 publications, five of which appeard in Science or Nature.« less

A year (2014-2015) of plants in Proteomics journal. Progress in wet and dry methodologies, moving from protein catalogs, and the view of classic plant biochemists.

PubMed

Sanchez-Lucas, Rosa; Mehta, Angela; Valledor, Luis; Cabello-Hurtado, Francisco; Romero-Rodrıguez, M Cristina; Simova-Stoilova, Lyudmila; Demir, Sekvan; Rodriguez-de-Francisco, Luis E; Maldonado-Alconada, Ana M; Jorrin-Prieto, Ana L; Jorrín-Novo, Jesus V

2016-03-01

The present review is an update of the previous one published in Proteomics 2015 Reviews special issue [Jorrin-Novo, J. V. et al., Proteomics 2015, 15, 1089-1112] covering the July 2014-2015 period. It has been written on the bases of the publications that appeared in Proteomics journal during that period and the most relevant ones that have been published in other high-impact journals. Methodological advances and the contribution of the field to the knowledge of plant biology processes and its translation to agroforestry and environmental sectors will be discussed. This review has been organized in four blocks, with a starting general introduction (literature survey) followed by sections focusing on the methodology (in vitro, in vivo, wet, and dry), proteomics integration with other approaches (systems biology and proteogenomics), biological information, and knowledge (cell communication, receptors, and signaling), ending with a brief mention of some other biological and translational topics to which proteomics has made some contribution. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comprehensive annotation of Glossina pallidipes salivary gland hypertrophy virus from Ethiopian tsetse flies: a proteogenomics approach

PubMed Central

Kariithi, Henry M.; Cousserans, François; Parker, Nicolas J.; İnce, İkbal Agah; Scully, Erin D.; Boeren, Sjef; Geib, Scott M.; Mekonnen, Solomon; Vlak, Just M.; Parker, Andrew G.; Vreysen, Marc J. B.; Bergoin, Max

2016-01-01

Glossina pallidipes salivary gland hypertrophy virus (GpSGHV; family Hytrosaviridae) can establish asymptomatic and symptomatic infection in its tsetse fly host. Here, we present a comprehensive annotation of the genome of an Ethiopian GpSGHV isolate (GpSGHV-Eth) compared with the reference Ugandan GpSGHV isolate (GpSGHV-Uga; GenBank accession number EF568108). GpSGHV-Eth has higher salivary gland hypertrophy syndrome prevalence than GpSGHV-Uga. We show that the GpSGHV-Eth genome has 190 291 nt, a low G+C content (27.9 %) and encodes 174 putative ORFs. Using proteogenomic and transcriptome mapping, 141 and 86 ORFs were mapped by transcripts and peptides, respectively. Furthermore, of the 174 ORFs, 132 had putative transcriptional signals [TATA-like box and poly(A) signals]. Sixty ORFs had both TATA-like box promoter and poly(A) signals, and mapped by both transcripts and peptides, implying that these ORFs encode functional proteins. Of the 60 ORFs, 10 ORFs are homologues to baculovirus and nudivirus core genes, including three per os infectivity factors and four RNA polymerase subunits (LEF4, 5, 8 and 9). Whereas GpSGHV-Eth and GpSGHV-Uga are 98.1 % similar at the nucleotide level, 37 ORFs in the GpSGHV-Eth genome had nucleotide insertions (n = 17) and deletions (n = 20) compared with their homologues in GpSGHV-Uga. Furthermore, compared with the GpSGHV-Uga genome, 11 and 24 GpSGHV ORFs were deleted and novel, respectively. Further, 13 GpSGHV-Eth ORFs were non-canonical; they had either CTG or TTG start codons instead of ATG. Taken together, these data suggest that GpSGHV-Eth and GpSGHV-Uga represent two different lineages of the same virus. Genetic differences combined with host and environmental factors possibly explain the differential GpSGHV pathogenesis observed in different G. pallidipes colonies. PMID:26801744

Exploiting Helminth-Host Interactomes through Big Data.

PubMed

Sotillo, Javier; Toledo, Rafael; Mulvenna, Jason; Loukas, Alex

2017-11-01

Helminths facilitate their parasitic existence through the production and secretion of different molecules, including proteins. Some helminth proteins can manipulate the host's immune system, a phenomenon that is now being exploited with a view to developing therapeutics for inflammatory diseases. In recent years, hundreds of helminth genomes have been sequenced, but as a community we are still taking baby steps when it comes to identifying proteins that govern host-helminth interactions. The information generated from genomic, immunomic, and proteomic studies, as well as from cutting-edge approaches such as proteogenomics, is leading to a substantial volume of big data that can be utilised to shed light on fundamental biology and provide solutions for the development of bioactive-molecule-based therapeutics. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Inducible Operon Is Involved in Inulin Utilization in Lactobacillus plantarum Strains, as Revealed by Comparative Proteogenomics and Metabolic Profiling.

PubMed

Buntin, Nirunya; Hongpattarakere, Tipparat; Ritari, Jarmo; Douillard, François P; Paulin, Lars; Boeren, Sjef; Shetty, Sudarshan A; de Vos, Willem M

2017-01-15

The draft genomes of Lactobacillus plantarum strains isolated from Asian fermented foods, infant feces, and shrimp intestines were sequenced and compared to those of well-studied strains. Among 28 strains of L. plantarum, variations in the genomic features involved in ecological adaptation were elucidated. The genome sizes ranged from approximately 3.1 to 3.5 Mb, of which about 2,932 to 3,345 protein-coding sequences (CDS) were predicted. The food-derived isolates contained a higher number of carbohydrate metabolism-associated genes than those from infant feces. This observation correlated to their phenotypic carbohydrate metabolic profile, indicating their ability to metabolize the largest range of sugars. Surprisingly, two strains (P14 and P76) isolated from fermented fish utilized inulin. β-Fructosidase, the inulin-degrading enzyme, was detected in the supernatants and cell wall extracts of both strains. No activity was observed in the cytoplasmic fraction, indicating that this key enzyme was either membrane-bound or extracellularly secreted. From genomic mining analysis, a predicted inulin operon of fosRABCDXE, which encodes β-fructosidase and many fructose transporting proteins, was found within the genomes of strains P14 and P76. Moreover, pts1BCA genes, encoding sucrose-specific IIBCA components involved in sucrose transport, were also identified. The proteomic analysis revealed the mechanism and functional characteristic of the fosRABCDXE operon involved in the inulin utilization of L. plantarum The expression levels of the fos operon and pst genes were upregulated at mid-log phase. FosE and the LPXTG-motif cell wall anchored β-fructosidase were induced to a high abundance when inulin was present as a carbon source. Inulin is a long-chain carbohydrate that may act as a prebiotic, which provides many health benefits to the host by selectively stimulating the growth and activity of beneficial bacteria in the colon. While certain lactobacilli can catabolize inulin, this has not yet been described for Lactobacillus plantarum, and an associated putative inulin operon has not been reported in this species. By using comparative and functional genomics, we showed that two L. plantarum strains utilized inulin and identified functional inulin operons in their genomes. The proteogenomic data revealed that inulin degradation and uptake routes, which related to the fosRABCDXE operon and pstBCA genes, were widely expressed among L. plantarum strains. The present work provides a novel understanding of gene regulation and mechanisms of inulin utilization in probiotic L. plantarum generating opportunities for synbiotic product development. Copyright © 2016 American Society for Microbiology.

An Inducible Operon Is Involved in Inulin Utilization in Lactobacillus plantarum Strains, as Revealed by Comparative Proteogenomics and Metabolic Profiling

PubMed Central

Buntin, Nirunya; Hongpattarakere, Tipparat; Ritari, Jarmo; Douillard, François P.; Paulin, Lars; Boeren, Sjef; Shetty, Sudarshan A.

2016-01-01

ABSTRACT The draft genomes of Lactobacillus plantarum strains isolated from Asian fermented foods, infant feces, and shrimp intestines were sequenced and compared to those of well-studied strains. Among 28 strains of L. plantarum, variations in the genomic features involved in ecological adaptation were elucidated. The genome sizes ranged from approximately 3.1 to 3.5 Mb, of which about 2,932 to 3,345 protein-coding sequences (CDS) were predicted. The food-derived isolates contained a higher number of carbohydrate metabolism-associated genes than those from infant feces. This observation correlated to their phenotypic carbohydrate metabolic profile, indicating their ability to metabolize the largest range of sugars. Surprisingly, two strains (P14 and P76) isolated from fermented fish utilized inulin. β-Fructosidase, the inulin-degrading enzyme, was detected in the supernatants and cell wall extracts of both strains. No activity was observed in the cytoplasmic fraction, indicating that this key enzyme was either membrane-bound or extracellularly secreted. From genomic mining analysis, a predicted inulin operon of fosRABCDXE, which encodes β-fructosidase and many fructose transporting proteins, was found within the genomes of strains P14 and P76. Moreover, pts1BCA genes, encoding sucrose-specific IIBCA components involved in sucrose transport, were also identified. The proteomic analysis revealed the mechanism and functional characteristic of the fosRABCDXE operon involved in the inulin utilization of L. plantarum. The expression levels of the fos operon and pst genes were upregulated at mid-log phase. FosE and the LPXTG-motif cell wall anchored β-fructosidase were induced to a high abundance when inulin was present as a carbon source. IMPORTANCE Inulin is a long-chain carbohydrate that may act as a prebiotic, which provides many health benefits to the host by selectively stimulating the growth and activity of beneficial bacteria in the colon. While certain lactobacilli can catabolize inulin, this has not yet been described for Lactobacillus plantarum, and an associated putative inulin operon has not been reported in this species. By using comparative and functional genomics, we showed that two L. plantarum strains utilized inulin and identified functional inulin operons in their genomes. The proteogenomic data revealed that inulin degradation and uptake routes, which related to the fosRABCDXE operon and pstBCA genes, were widely expressed among L. plantarum strains. The present work provides a novel understanding of gene regulation and mechanisms of inulin utilization in probiotic L. plantarum generating opportunities for synbiotic product development. PMID:27815279

proBAMconvert: A Conversion Tool for proBAM/proBed.

PubMed

Olexiouk, Volodimir; Menschaert, Gerben

2017-07-07

The introduction of new standard formats, proBAM and proBed, improves the integration of genomics and proteomics information, thus aiding proteogenomics applications. These novel formats enable peptide spectrum matches (PSM) to be stored, inspected, and analyzed within the context of the genome. However, an easy-to-use and transparent tool to convert mass spectrometry identification files to these new formats is indispensable. proBAMconvert enables the conversion of common identification file formats (mzIdentML, mzTab, and pepXML) to proBAM/proBed using an intuitive interface. Furthermore, ProBAMconvert enables information to be output both at the PSM and peptide levels and has a command line interface next to the graphical user interface. Detailed documentation and a completely worked-out tutorial is available at http://probam.biobix.be .

Gapped Spectral Dictionaries and Their Applications for Database Searches of Tandem Mass Spectra*

PubMed Central

Jeong, Kyowon; Kim, Sangtae; Bandeira, Nuno; Pevzner, Pavel A.

2011-01-01

Generating all plausible de novo interpretations of a peptide tandem mass (MS/MS) spectrum (Spectral Dictionary) and quickly matching them against the database represent a recently emerged alternative approach to peptide identification. However, the sizes of the Spectral Dictionaries quickly grow with the peptide length making their generation impractical for long peptides. We introduce Gapped Spectral Dictionaries (all plausible de novo interpretations with gaps) that can be easily generated for any peptide length thus addressing the limitation of the Spectral Dictionary approach. We show that Gapped Spectral Dictionaries are small thus opening a possibility of using them to speed-up MS/MS searches. Our MS-GappedDictionary algorithm (based on Gapped Spectral Dictionaries) enables proteogenomics applications (such as searches in the six-frame translation of the human genome) that are prohibitively time consuming with existing approaches. MS-GappedDictionary generates gapped peptides that occupy a niche between accurate but short peptide sequence tags and long but inaccurate full length peptide reconstructions. We show that, contrary to conventional wisdom, some high-quality spectra do not have good peptide sequence tags and introduce gapped tags that have advantages over the conventional peptide sequence tags in MS/MS database searches. PMID:21444829

A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers

PubMed Central

2012-01-01

Background Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble? Results The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity. Conclusion Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway. PMID:23216969

A computational pipeline for the development of multi-marker bio-signature panels and ensemble classifiers.

PubMed

Günther, Oliver P; Chen, Virginia; Freue, Gabriela Cohen; Balshaw, Robert F; Tebbutt, Scott J; Hollander, Zsuzsanna; Takhar, Mandeep; McMaster, W Robert; McManus, Bruce M; Keown, Paul A; Ng, Raymond T

2012-12-08

Biomarker panels derived separately from genomic and proteomic data and with a variety of computational methods have demonstrated promising classification performance in various diseases. An open question is how to create effective proteo-genomic panels. The framework of ensemble classifiers has been applied successfully in various analytical domains to combine classifiers so that the performance of the ensemble exceeds the performance of individual classifiers. Using blood-based diagnosis of acute renal allograft rejection as a case study, we address the following question in this paper: Can acute rejection classification performance be improved by combining individual genomic and proteomic classifiers in an ensemble? The first part of the paper presents a computational biomarker development pipeline for genomic and proteomic data. The pipeline begins with data acquisition (e.g., from bio-samples to microarray data), quality control, statistical analysis and mining of the data, and finally various forms of validation. The pipeline ensures that the various classifiers to be combined later in an ensemble are diverse and adequate for clinical use. Five mRNA genomic and five proteomic classifiers were developed independently using single time-point blood samples from 11 acute-rejection and 22 non-rejection renal transplant patients. The second part of the paper examines five ensembles ranging in size from two to 10 individual classifiers. Performance of ensembles is characterized by area under the curve (AUC), sensitivity, and specificity, as derived from the probability of acute rejection for individual classifiers in the ensemble in combination with one of two aggregation methods: (1) Average Probability or (2) Vote Threshold. One ensemble demonstrated superior performance and was able to improve sensitivity and AUC beyond the best values observed for any of the individual classifiers in the ensemble, while staying within the range of observed specificity. The Vote Threshold aggregation method achieved improved sensitivity for all 5 ensembles, but typically at the cost of decreased specificity. Proteo-genomic biomarker ensemble classifiers show promise in the diagnosis of acute renal allograft rejection and can improve classification performance beyond that of individual genomic or proteomic classifiers alone. Validation of our results in an international multicenter study is currently underway.

MHC class I-associated peptides derive from selective regions of the human genome.

PubMed

Pearson, Hillary; Daouda, Tariq; Granados, Diana Paola; Durette, Chantal; Bonneil, Eric; Courcelles, Mathieu; Rodenbrock, Anja; Laverdure, Jean-Philippe; Côté, Caroline; Mader, Sylvie; Lemieux, Sébastien; Thibault, Pierre; Perreault, Claude

2016-12-01

MHC class I-associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology.

MHC class I–associated peptides derive from selective regions of the human genome

PubMed Central

Pearson, Hillary; Granados, Diana Paola; Durette, Chantal; Bonneil, Eric; Courcelles, Mathieu; Rodenbrock, Anja; Laverdure, Jean-Philippe; Côté, Caroline; Thibault, Pierre

2016-01-01

MHC class I–associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology. PMID:27841757

Translational plant proteomics: a perspective.

PubMed

Agrawal, Ganesh Kumar; Pedreschi, Romina; Barkla, Bronwyn J; Bindschedler, Laurence Veronique; Cramer, Rainer; Sarkar, Abhijit; Renaut, Jenny; Job, Dominique; Rakwal, Randeep

2012-08-03

Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic values of plants, food security and safety, and energy sustainability. In this review, we highlight the substantial progress reached in plant proteomics during the past decade which has paved the way for translational plant proteomics. Increasing proteomics knowledge in plants is not limited to model and non-model plants, proteogenomics, crop improvement, and food analysis, safety, and nutrition but to many more potential applications. Given the wealth of information generated and to some extent applied, there is the need for more efficient and broader channels to freely disseminate the information to the scientific community. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Assessment of meat authenticity using bioinformatics, targeted peptide biomarkers and high-resolution mass spectrometry.

PubMed

Ruiz Orduna, Alberto; Husby, Erik; Yang, Charles T; Ghosh, Dipankar; Beaudry, Francis

2015-01-01

In recent years a significant increase of food fraud has been observed, ranging from false label claims to the use of additives and fillers to increase profitability. Recently in 2013 horse and pig DNAs were detected in beef products sold from several retailers. Mass spectrometry (MS) has become the workhorse in protein research, and the detection of marker proteins could serve for both animal species and tissue authentication. Meat species authenticity is performed in this paper using a well-defined proteogenomic annotation, carefully chosen surrogate tryptic peptides and analysis using a hybrid quadrupole-Orbitrap MS. Selected mammalian meat samples were homogenised and proteins were extracted and digested with trypsin. The samples were analysed using a high-resolution MS. Chromatography was achieved using a 30-min linear gradient along with a BioBasic C8 100 × 1 mm column at a flow rate of 75 µl min(-1). The MS was operated in full-scan high resolution and accurate mass. MS/MS spectra were collected for selected proteotypic peptides. Muscular proteins were methodically analysed in silico in order to generate tryptic peptide mass lists and theoretical MS/MS spectra. Following a comprehensive bottom-up proteomic analysis, we detected and identified a proteotypic myoglobin tryptic peptide (120-134) for each species with observed m/z below 1.3 ppm compared with theoretical values. Moreover, proteotypic peptides from myosin-1, myosin-2 and β-haemoglobin were also identified. This targeted method allowed comprehensive meat speciation down to 1% (w/w) of undesired product.

Community proteogenomics reveals insights into the physiology of phyllosphere bacteria

PubMed Central

Delmotte, Nathanaël; Knief, Claudia; Chaffron, Samuel; Innerebner, Gerd; Roschitzki, Bernd; Schlapbach, Ralph; von Mering, Christian; Vorholt, Julia A.

2009-01-01

Aerial plant surfaces represent the largest biological interface on Earth and provide essential services as sites of carbon dioxide fixation, molecular oxygen release, and primary biomass production. Rather than existing as axenic organisms, plants are colonized by microorganisms that affect both their health and growth. To gain insight into the physiology of phyllosphere bacteria under in situ conditions, we performed a culture-independent analysis of the microbiota associated with leaves of soybean, clover, and Arabidopsis thaliana plants using a metaproteogenomic approach. We found a high consistency of the communities on the 3 different plant species, both with respect to the predominant community members (including the alphaproteobacterial genera Sphingomonas and Methylo bacterium) and with respect to their proteomes. Observed known proteins of Methylobacterium were to a large extent related to the ability of these bacteria to use methanol as a source of carbon and energy. A remarkably high expression of various TonB-dependent receptors was observed for Sphingomonas. Because these outer membrane proteins are involved in transport processes of various carbohydrates, a particularly large substrate utilization pattern for Sphingomonads can be assumed to occur in the phyllosphere. These adaptations at the genus level can be expected to contribute to the success and coexistence of these 2 taxa on plant leaves. We anticipate that our results will form the basis for the identification of unique traits of phyllosphere bacteria, and for uncovering previously unrecorded mechanisms of bacteria-plant and bacteria-bacteria relationships. PMID:19805315

Three dimensional amorphous silicon/microcrystalline silicon solar cells

DOEpatents

Kaschmitter, James L.

1996-01-01

Three dimensional deep contact amorphous silicon/microcrystalline silicon (a-Si/.mu.c-Si) solar cells which use deep (high aspect ratio) p and n contacts to create high electric fields within the carrier collection volume material of the cell. The deep contacts are fabricated using repetitive pulsed laser doping so as to create the high aspect p and n contacts. By the provision of the deep contacts which penetrate the electric field deep into the material where the high strength of the field can collect many of the carriers, thereby resulting in a high efficiency solar cell.

Three dimensional amorphous silicon/microcrystalline silicon solar cells

DOEpatents

Kaschmitter, J.L.

1996-07-23

Three dimensional deep contact amorphous silicon/microcrystalline silicon (a-Si/{micro}c-Si) solar cells are disclosed which use deep (high aspect ratio) p and n contacts to create high electric fields within the carrier collection volume material of the cell. The deep contacts are fabricated using repetitive pulsed laser doping so as to create the high aspect p and n contacts. By the provision of the deep contacts which penetrate the electric field deep into the material where the high strength of the field can collect many of the carriers, thereby resulting in a high efficiency solar cell. 4 figs.

Sulfide Generation by Dominant Halanaerobium Microorganisms in Hydraulically Fractured Shales

PubMed Central

Booker, Anne E.; Borton, Mikayla A.; Daly, Rebecca A.; Welch, Susan A.; Nicora, Carrie D.; Hoyt, David W.; Wilson, Travis; Purvine, Samuel O.; Wolfe, Richard A.; Sharma, Shikha; Mouser, Paula J.; Cole, David R.; Lipton, Mary S.; Wrighton, Kelly C.

2017-01-01

ABSTRACT Hydraulic fracturing of black shale formations has greatly increased United States oil and natural gas recovery. However, the accumulation of biomass in subsurface reservoirs and pipelines is detrimental because of possible well souring, microbially induced corrosion, and pore clogging. Temporal sampling of produced fluids from a well in the Utica Shale revealed the dominance of Halanaerobium strains within the in situ microbial community and the potential for these microorganisms to catalyze thiosulfate-dependent sulfidogenesis. From these field data, we investigated biogenic sulfide production catalyzed by a Halanaerobium strain isolated from the produced fluids using proteogenomics and laboratory growth experiments. Analysis of Halanaerobium isolate genomes and reconstructed genomes from metagenomic data sets revealed the conserved presence of rhodanese-like proteins and anaerobic sulfite reductase complexes capable of converting thiosulfate to sulfide. Shotgun proteomics measurements using a Halanaerobium isolate verified that these proteins were more abundant when thiosulfate was present in the growth medium, and culture-based assays identified thiosulfate-dependent sulfide production by the same isolate. Increased production of sulfide and organic acids during the stationary growth phase suggests that fermentative Halanaerobium uses thiosulfate to remove excess reductant. These findings emphasize the potential detrimental effects that could arise from thiosulfate-reducing microorganisms in hydraulically fractured shales, which are undetected by current industry-wide corrosion diagnostics. IMPORTANCE Although thousands of wells in deep shale formations across the United States have been hydraulically fractured for oil and gas recovery, the impact of microbial metabolism within these environments is poorly understood. Our research demonstrates that dominant microbial populations in these subsurface ecosystems contain the conserved capacity for the reduction of thiosulfate to sulfide and that this process is likely occurring in the environment. Sulfide generation (also known as “souring”) is considered deleterious in the oil and gas industry because of both toxicity issues and impacts on corrosion of the subsurface infrastructure. Critically, the capacity for sulfide generation via reduction of sulfate was not detected in our data sets. Given that current industry wellhead tests for sulfidogenesis target canonical sulfate-reducing microorganisms, these data suggest that new approaches to the detection of sulfide-producing microorganisms may be necessary. PMID:28685163

Sulfide Generation by Dominant Halanaerobium Microorganisms in Hydraulically Fractured Shales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booker, Anne E.; Borton, Mikayla A.; Daly, Rebecca A.

ABSTRACT Hydraulic fracturing of black shale formations has greatly increased United States oil and natural gas recovery. However, the accumulation of biomass in subsurface reservoirs and pipelines is detrimental because of possible well souring, microbially induced corrosion, and pore clogging. Temporal sampling of produced fluids from a well in the Utica Shale revealed the dominance ofHalanaerobiumstrains within thein situmicrobial community and the potential for these microorganisms to catalyze thiosulfate-dependent sulfidogenesis. From these field data, we investigated biogenic sulfide production catalyzed by aHalanaerobiumstrain isolated from the produced fluids using proteogenomics and laboratory growth experiments. Analysis ofHalanaerobiumisolate genomes and reconstructed genomes frommore » metagenomic data sets revealed the conserved presence of rhodanese-like proteins and anaerobic sulfite reductase complexes capable of converting thiosulfate to sulfide. Shotgun proteomics measurements using aHalanaerobiumisolate verified that these proteins were more abundant when thiosulfate was present in the growth medium, and culture-based assays identified thiosulfate-dependent sulfide production by the same isolate. Increased production of sulfide and organic acids during the stationary growth phase suggests that fermentativeHalanaerobiumuses thiosulfate to remove excess reductant. These findings emphasize the potential detrimental effects that could arise from thiosulfate-reducing microorganisms in hydraulically fractured shales, which are undetected by current industry-wide corrosion diagnostics. IMPORTANCEAlthough thousands of wells in deep shale formations across the United States have been hydraulically fractured for oil and gas recovery, the impact of microbial metabolism within these environments is poorly understood. Our research demonstrates that dominant microbial populations in these subsurface ecosystems contain the conserved capacity for the reduction of thiosulfate to sulfide and that this process is likely occurring in the environment. Sulfide generation (also known as “souring”) is considered deleterious in the oil and gas industry because of both toxicity issues and impacts on corrosion of the subsurface infrastructure. Critically, the capacity for sulfide generation via reduction of sulfate was not detected in our data sets. Given that current industry wellhead tests for sulfidogenesis target canonical sulfate-reducing microorganisms, these data suggest that new approaches to the detection of sulfide-producing microorganisms may be necessary.« less

Development of Proteogenomic Approaches to Analyze the Role of Virus-Microbe Interactions in Shaping Natural Microbial Communities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banfield, Jillian; Breitbart, Mya; VerBerkmoes, Nathan

CRISPRs (clustered regularly interspaced short palindromic repeats) are adaptive immune systems in Bacteria and Archaea. Transcripts of the spacers that separate the repeats confer immunity through sequence identity with a targeted region (proto-spacer) in phage/viral, plasmid, or other foreign DNA. Short sequences immediately flanking the proto-spacer (proto-spacer adjacent motifs—PAMs) are important in both procuring spacers from and providing immunity to targeted sequences. New spacers are incorporated unidirectionally at the leader end of the CRISPR loci, thus recording a timeline of recent viral exposure. In the early phase of our research, we documented extremely rapid diversification of the CRISPR loci inmore » natural populations [Tyson and Banfield, 2008] matched by high levels of sequence variation in natural viral populations [Andersson and Banfield, 2008]. Since then, in a genetically tractable model laboratory system, we have 1) tracked phage mutation and CRISPR diversification, and in a natural model system, we have 2) examined population history via over time, 3) investigated the timescale over which spacers become ineffective and the process by which ineffective spacers are removed, and 4) analyzed viral diversity. In addition to research activities, our group has organized five international CRISPR meetings, the fifth to be held at University of California, Berkeley in June 2012. Most importantly, the project provided the majority of funding support for Christine Sun (Ph.D. 2012).« less

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer

DOE PAGES

Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...

2017-07-19

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

The effects of deep level traps on the electrical properties of semi-insulating CdZnTe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zha, Gangqiang; Yang, Jian; Xu, Lingyan

2014-01-28

Deep level traps have considerable effects on the electrical properties and radiation detection performance of high resistivity CdZnTe. A deep-trap model for high resistivity CdZnTe was proposed in this paper. The high resistivity mechanism and the electrical properties were analyzed based on this model. High resistivity CdZnTe with high trap ionization energy E{sub t} can withstand high bias voltages. The leakage current is dependent on both the deep traps and the shallow impurities. The performance of a CdZnTe radiation detector will deteriorate at low temperatures, and the way in which sub-bandgap light excitation could improve the low temperature performance canmore » be explained using the deep trap model.« less

Automated analysis of high-content microscopy data with deep learning.

PubMed

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Exploitation of deep-sea resources: the urgent need to understand the role of high pressure in the toxicity of chemical pollutants to deep-sea organisms.

PubMed

Mestre, Nélia C; Calado, Ricardo; Soares, Amadeu M V M

2014-02-01

The advent of industrial activities in the deep sea will inevitably expose deep-sea organisms to potentially toxic compounds. Although international regulations require environmental risk assessment prior to exploitation activities, toxicity tests remain focused on shallow-water model species. Moreover, current tests overlook potential synergies that may arise from the interaction of chemicals with natural stressors, such as the high pressures prevailing in the deep sea. As pressure affects chemical reactions and the physiology of marine organisms, it will certainly affect the toxicity of pollutants arising from the exploitation of deep-sea resources. We emphasize the need for environmental risk assessments based on information generated from ecotoxicological trials that mimic, as close as possible, the deep-sea environment, with emphasis to a key environmental factor - high hydrostatic pressure. Copyright © 2013 Elsevier Ltd. All rights reserved.

Method and apparatus for delivering high power laser energy over long distances

DOEpatents

Zediker, Mark S; Rinzler, Charles C; Faircloth, Brian O; Koblick, Yeshaya; Moxley, Joel F

2015-04-07

Systems, devices and methods for the transmission and delivery of high power laser energy deep into the earth and for the suppression of associated nonlinear phenomena. Systems, devices and methods for the laser drilling of a borehole in the earth. These systems can deliver high power laser energy down a deep borehole, while maintaining the high power to advance such boreholes deep into the earth and at highly efficient advancement rates.

The deep-sea under global change.

PubMed

Danovaro, Roberto; Corinaldesi, Cinzia; Dell'Anno, Antonio; Snelgrove, Paul V R

2017-06-05

The deep ocean encompasses 95% of the oceans' volume and is the largest and least explored biome of Earth's Biosphere. New life forms are continuously being discovered. The physiological mechanisms allowing organisms to adapt to extreme conditions of the deep ocean (high pressures, from very low to very high temperatures, food shortage, lack of solar light) are still largely unknown. Some deep-sea species have very long life-spans, whereas others can tolerate toxic compounds at high concentrations; these characteristics offer an opportunity to explore the specialized biochemical and physiological mechanisms associated with these responses. Widespread symbiotic relationships play fundamental roles in driving host functions, nutrition, health, and evolution. Deep-sea organisms communicate and interact through sound emissions, chemical signals and bioluminescence. Several giants of the oceans hunt exclusively at depth, and new studies reveal a tight connection between processes in the shallow water and some deep-sea species. Limited biological knowledge of the deep-sea limits our capacity to predict future response of deep-sea organisms subject to increasing human pressure and changing global environmental conditions. Molecular tools, sensor-tagged animals, in situ and laboratory experiments, and new technologies can enable unprecedented advancement of deep-sea biology, and facilitate the sustainable management of deep ocean use under global change. Copyright © 2017. Published by Elsevier Ltd.

Reconstructing metabolic pathways of a member of the genus Pelotomaculum suggesting its potential to oxidize benzene to carbon dioxide with direct reduction of sulfate.

PubMed

Dong, Xiyang; Dröge, Johannes; von Toerne, Christine; Marozava, Sviatlana; McHardy, Alice C; Meckenstock, Rainer U

2017-03-01

The enrichment culture BPL is able to degrade benzene with sulfate as electron acceptor and is dominated by an organism of the genus Pelotomaculum. Members of Pelotomaculum are usually known to be fermenters, undergoing syntrophy with anaerobic respiring microorganisms or methanogens. By using a metagenomic approach, we reconstructed a high-quality genome (∼2.97 Mbp, 99% completeness) for Pelotomaculum candidate BPL. The proteogenomic data suggested that (1) anaerobic benzene degradation was activated by a yet unknown mechanism for conversion of benzene to benzoyl-CoA; (2) the central benzoyl-CoA degradation pathway involved reductive dearomatization by a class II benzoyl-CoA reductase followed by hydrolytic ring cleavage and modified β-oxidation; (3) the oxidative acetyl-CoA pathway was utilized for complete oxidation to CO2. Interestingly, the genome of Pelotomaculum candidate BPL has all the genes for a complete sulfate reduction pathway including a similar electron transfer mechanism for dissimilatory sulfate reduction as in other Gram-positive sulfate-reducing bacteria. The proteome analysis revealed that the essential enzymes for sulfate reduction were all formed during growth with benzene. Thus, our data indicated that, besides its potential to anaerobically degrade benzene, Pelotomaculum candidate BPL is the first member of the genus that can perform sulfate reduction. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Proteomic profiling of the planarian Schmidtea mediterranea and its mucous reveals similarities with human secretions and those predicted for parasitic flatworms.

PubMed

Bocchinfuso, Donald G; Taylor, Paul; Ross, Eric; Ignatchenko, Alex; Ignatchenko, Vladimir; Kislinger, Thomas; Pearson, Bret J; Moran, Michael F

2012-09-01

The freshwater planarian Schmidtea mediterranea has been used in research for over 100 years, and is an emerging stem cell model because of its capability of regenerating large portions of missing body parts. Exteriorly, planarians are covered in mucous secretions of unknown composition, implicated in locomotion, predation, innate immunity, and substrate adhesion. Although the planarian genome has been sequenced, it remains mostly unannotated, challenging both genomic and proteomic analyses. The goal of the current study was to annotate the proteome of the whole planarian and its mucous fraction. The S. mediterranea proteome was analyzed via mass spectrometry by using multidimensional protein identification technology with whole-worm tryptic digests. By using a proteogenomics approach, MS data were searched against an in silico translated planarian transcript database, and by using the Swiss-Prot BLAST algorithm to identify proteins similar to planarian queries. A total of 1604 proteins were identified. The mucous subproteome was defined through analysis of a mucous trail fraction and an extract obtained by treating whole worms with the mucolytic agent N-acetylcysteine. Gene Ontology analysis confirmed that the mucous fractions were enriched with secreted proteins. The S. mediterranea proteome is highly similar to that predicted for the trematode Schistosoma mansoni associated with intestinal schistosomiasis, with the mucous subproteome particularly highly conserved. Remarkably, orthologs of 119 planarian mucous proteins are present in human mucosal secretions and tear fluid. We suggest planarians have potential to be a model system for the characterization of mucous protein function and relevant to parasitic flatworm infections and diseases underlined by mucous aberrancies, such as cystic fibrosis, asthma, and other lung diseases.

Adaptation and evolution of deep-sea scale worms (Annelida: Polynoidae): insights from transcriptome comparison with a shallow-water species

NASA Astrophysics Data System (ADS)

Zhang, Yanjie; Sun, Jin; Chen, Chong; Watanabe, Hiromi K.; Feng, Dong; Zhang, Yu; Chiu, Jill M. Y.; Qian, Pei-Yuan; Qiu, Jian-Wen

2017-04-01

Polynoid scale worms (Polynoidae, Annelida) invaded deep-sea chemosynthesis-based ecosystems approximately 60 million years ago, but little is known about their genetic adaptation to the extreme deep-sea environment. In this study, we reported the first two transcriptomes of deep-sea polynoids (Branchipolynoe pettiboneae, Lepidonotopodium sp.) and compared them with the transcriptome of a shallow-water polynoid (Harmothoe imbricata). We determined codon and amino acid usage, positive selected genes, highly expressed genes and putative duplicated genes. Transcriptome assembly produced 98,806 to 225,709 contigs in the three species. There were more positively charged amino acids (i.e., histidine and arginine) and less negatively charged amino acids (i.e., aspartic acid and glutamic acid) in the deep-sea species. There were 120 genes showing clear evidence of positive selection. Among the 10% most highly expressed genes, there were more hemoglobin genes with high expression levels in both deep-sea species. The duplicated genes related to DNA recombination and metabolism, and gene expression were only enriched in deep-sea species. Deep-sea scale worms adopted two strategies of adaptation to hypoxia in the chemosynthesis-based habitats (i.e., rapid evolution of tetra-domain hemoglobin in Branchipolynoe or high expression of single-domain hemoglobin in Lepidonotopodium sp.).

Mechanism of deep-sea fish α-actin pressure tolerance investigated by molecular dynamics simulations.

PubMed

Wakai, Nobuhiko; Takemura, Kazuhiro; Morita, Takami; Kitao, Akio

2014-01-01

The pressure tolerance of monomeric α-actin proteins from the deep-sea fish Coryphaenoides armatus and C. yaquinae was compared to that of non-deep-sea fish C. acrolepis, carp, and rabbit/human/chicken actins using molecular dynamics simulations at 0.1 and 60 MPa. The amino acid sequences of actins are highly conserved across a variety of species. The actins from C. armatus and C. yaquinae have the specific substitutions Q137K/V54A and Q137K/L67P, respectively, relative to C. acrolepis, and are pressure tolerant to depths of at least 6000 m. At high pressure, we observed significant changes in the salt bridge patterns in deep-sea fish actins, and these changes are expected to stabilize ATP binding and subdomain arrangement. Salt bridges between ATP and K137, formed in deep-sea fish actins, are expected to stabilize ATP binding even at high pressure. At high pressure, deep-sea fish actins also formed a greater total number of salt bridges than non-deep-sea fish actins owing to the formation of inter-helix/strand and inter-subdomain salt bridges. Free energy analysis suggests that deep-sea fish actins are stabilized to a greater degree by the conformational energy decrease associated with pressure effect.

Adaptation and evolution of deep-sea scale worms (Annelida: Polynoidae): insights from transcriptome comparison with a shallow-water species

PubMed Central

Zhang, Yanjie; Sun, Jin; Chen, Chong; Watanabe, Hiromi K.; Feng, Dong; Zhang, Yu; Chiu, Jill M.Y.; Qian, Pei-Yuan; Qiu, Jian-Wen

2017-01-01

Polynoid scale worms (Polynoidae, Annelida) invaded deep-sea chemosynthesis-based ecosystems approximately 60 million years ago, but little is known about their genetic adaptation to the extreme deep-sea environment. In this study, we reported the first two transcriptomes of deep-sea polynoids (Branchipolynoe pettiboneae, Lepidonotopodium sp.) and compared them with the transcriptome of a shallow-water polynoid (Harmothoe imbricata). We determined codon and amino acid usage, positive selected genes, highly expressed genes and putative duplicated genes. Transcriptome assembly produced 98,806 to 225,709 contigs in the three species. There were more positively charged amino acids (i.e., histidine and arginine) and less negatively charged amino acids (i.e., aspartic acid and glutamic acid) in the deep-sea species. There were 120 genes showing clear evidence of positive selection. Among the 10% most highly expressed genes, there were more hemoglobin genes with high expression levels in both deep-sea species. The duplicated genes related to DNA recombination and metabolism, and gene expression were only enriched in deep-sea species. Deep-sea scale worms adopted two strategies of adaptation to hypoxia in the chemosynthesis-based habitats (i.e., rapid evolution of tetra-domain hemoglobin in Branchipolynoe or high expression of single-domain hemoglobin in Lepidonotopodium sp.). PMID:28397791

Mechanism of Deep-Sea Fish α-Actin Pressure Tolerance Investigated by Molecular Dynamics Simulations

PubMed Central

Wakai, Nobuhiko; Takemura, Kazuhiro; Morita, Takami; Kitao, Akio

2014-01-01

The pressure tolerance of monomeric α-actin proteins from the deep-sea fish Coryphaenoides armatus and C. yaquinae was compared to that of non-deep-sea fish C. acrolepis, carp, and rabbit/human/chicken actins using molecular dynamics simulations at 0.1 and 60 MPa. The amino acid sequences of actins are highly conserved across a variety of species. The actins from C. armatus and C. yaquinae have the specific substitutions Q137K/V54A and Q137K/L67P, respectively, relative to C. acrolepis, and are pressure tolerant to depths of at least 6000 m. At high pressure, we observed significant changes in the salt bridge patterns in deep-sea fish actins, and these changes are expected to stabilize ATP binding and subdomain arrangement. Salt bridges between ATP and K137, formed in deep-sea fish actins, are expected to stabilize ATP binding even at high pressure. At high pressure, deep-sea fish actins also formed a greater total number of salt bridges than non-deep-sea fish actins owing to the formation of inter-helix/strand and inter-subdomain salt bridges. Free energy analysis suggests that deep-sea fish actins are stabilized to a greater degree by the conformational energy decrease associated with pressure effect. PMID:24465747

Deep Crustal Melting and the Survival of Continental Crust

NASA Astrophysics Data System (ADS)

Whitney, D.; Teyssier, C. P.; Rey, P. F.; Korchinski, M.

2017-12-01

Plate convergence involving continental lithosphere leads to crustal melting, which ultimately stabilizes the crust because it drives rapid upward flow of hot deep crust, followed by rapid cooling at shallow levels. Collision drives partial melting during crustal thickening (at 40-75 km) and/or continental subduction (at 75-100 km). These depths are not typically exceeded by crustal rocks that are exhumed in each setting because partial melting significantly decreases viscosity, facilitating upward flow of deep crust. Results from numerical models and nature indicate that deep crust moves laterally and then vertically, crystallizing at depths as shallow as 2 km. Deep crust flows en masse, without significant segregation of melt into magmatic bodies, over 10s of kms of vertical transport. This is a major mechanism by which deep crust is exhumed and is therefore a significant process of heat and mass transfer in continental evolution. The result of vertical flow of deep, partially molten crust is a migmatite dome. When lithosphere is under extension or transtension, the deep crust is solicited by faulting of the brittle upper crust, and the flow of deep crust in migmatite domes traverses nearly the entire thickness of orogenic crust in <10 million years. This cycle of burial, partial melting, rapid ascent, and crystallization/cooling preserves the continents from being recycled into the mantle by convergent tectonic processes over geologic time. Migmatite domes commonly preserve a record of high-T - low-P metamorphism. Domes may also contain rocks or minerals that record high-T - high-P conditions, including high-P metamorphism broadly coeval with host migmatite, evidence for the deep crustal origin of migmatite. There exists a spectrum of domes, from entirely deep-sourced to mixtures of deep and shallow sources. Controlling factors in deep vs. shallow sources are relative densities of crustal layers and rate of extension: fast extension (cm/yr) promotes efficient ascent of deep crust, whereas slow extension (mm/yr) produces significantly less exhumation. Recognition of the importance of migmatite (gneiss) domes as archives of orogenic deep crust is applicable to determining the chemical and physical properties of continental crust, as well as mechanisms and timescales of crustal differentiation.

Method and apparatus for delivering high power laser energy over long distances

DOEpatents

Zediker, Mark S; Rinzler, Charles C; Faircloth, Brian O; Koblick, Yeshaya; Moxley, Joel F

2013-08-20

Systems, devices and methods for the transmission of 1 kW or more of laser energy deep into the earth and for the suppression of associated nonlinear phenomena. Systems, devices and methods for the laser drilling of a borehole in the earth. These systems can deliver high power laser energy down a deep borehole, while maintaining the high power to advance such boreholes deep into the earth and at highly efficient advancement rates.

Soil moisture depletion under simulated drought in the Amazon: impacts on deep root uptake.

PubMed

Markewitz, Daniel; Devine, Scott; Davidson, Eric A; Brando, Paulo; Nepstad, Daniel C

2010-08-01

*Deep root water uptake in tropical Amazonian forests has been a major discovery during the last 15 yr. However, the effects of extended droughts, which may increase with climate change, on deep soil moisture utilization remain uncertain. *The current study utilized a 1999-2005 record of volumetric water content (VWC) under a throughfall exclusion experiment to calibrate a one-dimensional model of the hydrologic system to estimate VWC, and to quantify the rate of root uptake through 11.5 m of soil. *Simulations with root uptake compensation had a relative root mean square error (RRMSE) of 11% at 0-40 cm and < 5% at 350-1150 cm. The simulated contribution of deep root uptake under the control was c. 20% of water demand from 250 to 550 cm and c. 10% from 550 to 1150 cm. Furthermore, in years 2 (2001) and 3 (2002) of throughfall exclusion, deep root uptake increased as soil moisture was available but then declined to near zero in deep layers in 2003 and 2004. *Deep root uptake was limited despite high VWC (i.e. > 0.30 cm(3) cm(-3)). This limitation may partly be attributable to high residual water contents (theta(r)) in these high-clay (70-90%) soils or due to high soil-to-root resistance. The ability of deep roots and soils to contribute increasing amounts of water with extended drought will be limited.

High power laser downhole cutting tools and systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zediker, Mark S; Rinzler, Charles C; Faircloth, Brian O

Downhole cutting systems, devices and methods for utilizing 10 kW or more laser energy transmitted deep into the earth with the suppression of associated nonlinear phenomena. Systems and devices for the laser cutting operations within a borehole in the earth. These systems and devices can deliver high power laser energy down a deep borehole, while maintaining the high power to perform cutting operations in such boreholes deep within the earth.

Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project.

PubMed

Horvatovich, Péter; Lundberg, Emma K; Chen, Yu-Ju; Sung, Ting-Yi; He, Fuchu; Nice, Edouard C; Goode, Robert J; Yu, Simon; Ranganathan, Shoba; Baker, Mark S; Domont, Gilberto B; Velasquez, Erika; Li, Dong; Liu, Siqi; Wang, Quanhui; He, Qing-Yu; Menon, Rajasree; Guan, Yuanfang; Corrales, Fernando J; Segura, Victor; Casal, J Ignacio; Pascual-Montano, Alberto; Albar, Juan P; Fuentes, Manuel; Gonzalez-Gonzalez, Maria; Diez, Paula; Ibarrola, Nieves; Degano, Rosa M; Mohammed, Yassene; Borchers, Christoph H; Urbani, Andrea; Soggiu, Alessio; Yamamoto, Tadashi; Salekdeh, Ghasem Hosseini; Archakov, Alexander; Ponomarenko, Elena; Lisitsa, Andrey; Lichti, Cheryl F; Mostovenko, Ekaterina; Kroes, Roger A; Rezeli, Melinda; Végvári, Ákos; Fehniger, Thomas E; Bischoff, Rainer; Vizcaíno, Juan Antonio; Deutsch, Eric W; Lane, Lydie; Nilsson, Carol L; Marko-Varga, György; Omenn, Gilbert S; Jeong, Seul-Ki; Lim, Jong-Sun; Paik, Young-Ki; Hancock, William S

2015-09-04

This paper summarizes the recent activities of the Chromosome-Centric Human Proteome Project (C-HPP) consortium, which develops new technologies to identify yet-to-be annotated proteins (termed "missing proteins") in biological samples that lack sufficient experimental evidence at the protein level for confident protein identification. The C-HPP also aims to identify new protein forms that may be caused by genetic variability, post-translational modifications, and alternative splicing. Proteogenomic data integration forms the basis of the C-HPP's activities; therefore, we have summarized some of the key approaches and their roles in the project. We present new analytical technologies that improve the chemical space and lower detection limits coupled to bioinformatics tools and some publicly available resources that can be used to improve data analysis or support the development of analytical assays. Most of this paper's content has been compiled from posters, slides, and discussions presented in the series of C-HPP workshops held during 2014. All data (posters, presentations) used are available at the C-HPP Wiki (http://c-hpp.webhosting.rug.nl/) and in the Supporting Information.

Optimal Management of the Critically Ill: Anaesthesia, Monitoring, Data Capture, and Point-of-Care Technological Practices in Ovine Models of Critical Care

PubMed Central

Shekar, Kiran; Tung, John-Paul; Dunster, Kimble R.; Platts, David; Watts, Ryan P.; Gregory, Shaun D.; Simonova, Gabriela; McDonald, Charles; Hayes, Rylan; Bellpart, Judith; Timms, Daniel; Fung, Yoke L.; Toon, Michael; Maybauer, Marc O.; Fraser, John F.

2014-01-01

Animal models of critical illness are vital in biomedical research. They provide possibilities for the investigation of pathophysiological processes that may not otherwise be possible in humans. In order to be clinically applicable, the model should simulate the critical care situation realistically, including anaesthesia, monitoring, sampling, utilising appropriate personnel skill mix, and therapeutic interventions. There are limited data documenting the constitution of ideal technologically advanced large animal critical care practices and all the processes of the animal model. In this paper, we describe the procedure of animal preparation, anaesthesia induction and maintenance, physiologic monitoring, data capture, point-of-care technology, and animal aftercare that has been successfully used to study several novel ovine models of critical illness. The relevant investigations are on respiratory failure due to smoke inhalation, transfusion related acute lung injury, endotoxin-induced proteogenomic alterations, haemorrhagic shock, septic shock, brain death, cerebral microcirculation, and artificial heart studies. We have demonstrated the functionality of monitoring practices during anaesthesia required to provide a platform for undertaking systematic investigations in complex ovine models of critical illness. PMID:24783206

High-Resolution Ultrasound-Switchable Fluorescence Imaging in Centimeter-Deep Tissue Phantoms with High Signal-To-Noise Ratio and High Sensitivity via Novel Contrast Agents

PubMed Central

Cheng, Bingbing; Bandi, Venugopal; Wei, Ming-Yuan; Pei, Yanbo; D’Souza, Francis; Nguyen, Kytai T.; Hong, Yi; Yuan, Baohong

2016-01-01

For many years, investigators have sought after high-resolution fluorescence imaging in centimeter-deep tissue because many interesting in vivo phenomena—such as the presence of immune system cells, tumor angiogenesis, and metastasis—may be located deep in tissue. Previously, we developed a new imaging technique to achieve high spatial resolution in sub-centimeter deep tissue phantoms named continuous-wave ultrasound-switchable fluorescence (CW-USF). The principle is to use a focused ultrasound wave to externally and locally switch on and off the fluorophore emission from a small volume (close to ultrasound focal volume). By making improvements in three aspects of this technique: excellent near-infrared USF contrast agents, a sensitive frequency-domain USF imaging system, and an effective signal processing algorithm, for the first time this study has achieved high spatial resolution (~ 900 μm) in 3-centimeter-deep tissue phantoms with high signal-to-noise ratio (SNR) and high sensitivity (3.4 picomoles of fluorophore in a volume of 68 nanoliters can be detected). We have achieved these results in both tissue-mimic phantoms and porcine muscle tissues. We have also demonstrated multi-color USF to image and distinguish two fluorophores with different wavelengths, which might be very useful for simultaneously imaging of multiple targets and observing their interactions in the future. This work has opened the door for future studies of high-resolution centimeter-deep tissue fluorescence imaging. PMID:27829050

High-Resolution Ultrasound-Switchable Fluorescence Imaging in Centimeter-Deep Tissue Phantoms with High Signal-To-Noise Ratio and High Sensitivity via Novel Contrast Agents.

PubMed

Cheng, Bingbing; Bandi, Venugopal; Wei, Ming-Yuan; Pei, Yanbo; D'Souza, Francis; Nguyen, Kytai T; Hong, Yi; Yuan, Baohong

2016-01-01

For many years, investigators have sought after high-resolution fluorescence imaging in centimeter-deep tissue because many interesting in vivo phenomena-such as the presence of immune system cells, tumor angiogenesis, and metastasis-may be located deep in tissue. Previously, we developed a new imaging technique to achieve high spatial resolution in sub-centimeter deep tissue phantoms named continuous-wave ultrasound-switchable fluorescence (CW-USF). The principle is to use a focused ultrasound wave to externally and locally switch on and off the fluorophore emission from a small volume (close to ultrasound focal volume). By making improvements in three aspects of this technique: excellent near-infrared USF contrast agents, a sensitive frequency-domain USF imaging system, and an effective signal processing algorithm, for the first time this study has achieved high spatial resolution (~ 900 μm) in 3-centimeter-deep tissue phantoms with high signal-to-noise ratio (SNR) and high sensitivity (3.4 picomoles of fluorophore in a volume of 68 nanoliters can be detected). We have achieved these results in both tissue-mimic phantoms and porcine muscle tissues. We have also demonstrated multi-color USF to image and distinguish two fluorophores with different wavelengths, which might be very useful for simultaneously imaging of multiple targets and observing their interactions in the future. This work has opened the door for future studies of high-resolution centimeter-deep tissue fluorescence imaging.

Low-cost, high-precision micro-lensed optical fiber providing deep-micrometer to deep-nanometer-level light focusing.

PubMed

Wen, Sy-Bor; Sundaram, Vijay M; McBride, Daniel; Yang, Yu

2016-04-15

A new type of micro-lensed optical fiber through stacking appropriate high-refractive microspheres at designed locations with respect to the cleaved end of an optical fiber is numerically and experimentally demonstrated. This new type of micro-lensed optical fiber can be precisely constructed with low cost and high speed. Deep micrometer-scale and submicrometer-scale far-field light spots can be achieved when the optical fibers are multimode and single mode, respectively. By placing an appropriate teardrop dielectric nanoscale scatterer at the far-field spot of this new type of micro-lensed optical fiber, a deep-nanometer near-field spot can also be generated with high intensity and minimum joule heating, which is valuable in high-speed, high-resolution, and high-power nanoscale detection compared with traditional near-field optical fibers containing a significant portion of metallic material.

Pyrimidine-based twisted donor-acceptor delayed fluorescence molecules: a new universal platform for highly efficient blue electroluminescence.

PubMed

Park, In Seob; Komiyama, Hideaki; Yasuda, Takuma

2017-02-01

Deep-blue emitters that can harvest both singlet and triplet excited states to give high electron-to-photon conversion efficiencies are highly desired for applications in full-color displays and white lighting devices based on organic light-emitting diodes (OLEDs). Thermally activated delayed fluorescence (TADF) molecules based on highly twisted donor-acceptor (D-A) configurations are promising emitting dopants for the construction of efficient deep-blue OLEDs. In this study, a simple and versatile D-A system combining acridan-based donors and pyrimidine-based acceptors has been developed as a new platform for high-efficiency deep-blue TADF emitters. The designed pre-twisted acridan-pyrimidine D-A molecules exhibit small singlet-triplet energy splitting and high photoluminescence quantum yields, functioning as efficient deep-blue TADF emitters. The OLEDs utilizing these TADF emitters display bright blue electroluminescence with external quantum efficiencies of up to 20.4%, maximum current efficiencies of 41.7 cd A -1 , maximum power efficiencies of 37.2 lm W -1 , and color coordinates of (0.16, 0.23). The design strategy featuring such acridan-pyrimidine D-A motifs can offer great prospects for further developing high-performance deep-blue TADF emitters and TADF-OLEDs.

Deep crustal earthquakes associated with continental rifts

NASA Astrophysics Data System (ADS)

Doser, Diane I.; Yarwood, Dennis R.

1994-01-01

Deep (> 20 km) crustal earthquakes have occurred within or along the margins of at least four continental rift zones. The largest of these deep crustal earthquakes ( M ⩾ 5.0) have strike-slip or oblique-slip mechanisms with T-axes oriented similarly to those associated with shallow normal faulting within the rift zones. The majority of deep crustal earthquakes occur along the rift margins in regions that have cooler, thicker crust. Several deep crustal events, however, occur in regions of high heat flow. These regions also appear to be regions of high strain, a factor that could account for the observed depths. We believe the deep crustal earthquakes represent either the relative motion of rift zones with respect to adjacent stable regions or the propagation of rifting into stable regions.

Survival of marine heterotrophic flagellates isolated from the surface and the deep sea at high hydrostatic pressure: Literature review and own experiments

NASA Astrophysics Data System (ADS)

Živaljić, Suzana; Schoenle, Alexandra; Nitsche, Frank; Hohlfeld, Manon; Piechocki, Julia; Reif, Farina; Shumo, Marwa; Weiss, Alexandra; Werner, Jennifer; Witt, Madeleine; Voss, Janine; Arndt, Hartmut

2018-02-01

Although the abyssal seafloor represents the most common benthic environment on Earth, eukaryotic microbial life at abyssal depths is still an uncharted territory. This is in striking contrast to their potential importance regarding the material flux and bacteria consumption in the deep sea. Flagellate genotypes determined from sedimentary DNA deep-sea samples might originate from vital deep-sea populations or from cysts of organisms sedimented down from surface waters. The latter one may have never been active under deep-sea conditions. We wanted to analyze the principal ability of cultivable heterotrophic flagellates of different phylogenetic groups (choanoflagellates, ancyromonads, euglenids, kinetoplastids, bicosoecids, chrysomonads, and cercozoans) to survive exposure to high hydrostatic pressure (up to 670 bar). We summarized our own studies and the few available data from literature on pressure tolerances of flagellates isolated from different marine habitats. Our results demonstrated that many different flagellate species isolated from the surface waters and deep-sea sediments survived drastic changes in hydrostatic pressure. Barophilic behavior was also recorded for several species isolated from the deep sea indicating their possible genetic adaptation to high pressures. This is in accordance with records of heterotrophic flagellates present in environmental DNA surveys based on clone libraries established for deep-sea environments.

Natural Microbial Assemblages Reflect Distinct Organismal and Functional Partitioning

NASA Astrophysics Data System (ADS)

Wilmes, P.; Andersson, A.; Kalnejais, L. H.; Verberkmoes, N. C.; Lefsrud, M. G.; Wexler, M.; Singer, S. W.; Shah, M.; Bond, P. L.; Thelen, M. P.; Hettich, R. L.; Banfield, J. F.

2007-12-01

The ability to link microbial community structure to function has long been a primary focus of environmental microbiology. With the advent of community genomic and proteomic techniques, along with advances in microscopic imaging techniques, it is now possible to gain insights into the organismal and functional makeup of microbial communities. Biofilms growing within highly acidic solutions inside the Richmond Mine (Iron Mountain, Redding, California) exhibit distinct macro- and microscopic morphologies. They are composed of microorganisms belonging to the three domains of life, including archaea, bacteria and eukarya. The proportion of each organismal type depends on sampling location and developmental stage. For example, mature biofilms floating on top of acid mine drainage (AMD) pools exhibit layers consisting of a densely packed bottom layer of the chemoautolithotroph Leptospirillum group II, a less dense top layer composed mainly of archaea, and fungal filaments spanning across the entire biofilm. The expression of cytochrome 579 (the most highly abundant protein in the biofilm, believed to be central to iron oxidation and encoded by Leptospirillum group II) is localized at the interface of the biofilm with the AMD solution, highlighting that biofilm architecture is reflected at the functional gene expression level. Distinct functional partitioning is also apparent in a biological wastewater treatment system that selects for distinct polyphosphate accumulating organisms. Community genomic data from " Candidatus Accumulibacter phosphatis" dominated activated sludge has enabled high mass-accuracy shotgun proteomics for identification of key metabolic pathways. Comprehensive genome-wide alignment of orthologous proteins suggests distinct partitioning of protein variants involved in both core-metabolism and specific metabolic pathways among the dominant population and closely related species. In addition, strain- resolved proteogenomic analysis of the AMD biofilms also highlights the importance of strain heterogeneity for the maintenance of community structure and function. These findings explain the importance of genetic diversity in facilitating the stable performance of complex microbial processes. Furthermore, although very different in terms of habitat, both microbial communities exhibit distinct functional compartmentalization and demonstrate its role in sustaining microbial community structure.

Methods for enhancing the efficiency of creating a borehole using high power laser systems

DOEpatents

Zediker, Mark S.; Rinzler, Charles C.; Faircloth, Brian O.; Koblick, Yeshaya; Moxley, Joel F.

2014-06-24

Methods for utilizing 10 kW or more laser energy transmitted deep into the earth with the suppression of associated nonlinear phenomena to enhance the formation of Boreholes. Methods for the laser operations to reduce the critical path for forming a borehole in the earth. These methods can deliver high power laser energy down a deep borehole, while maintaining the high power to perform operations in such boreholes deep within the earth.

High power laser workover and completion tools and systems

DOEpatents

Zediker, Mark S; Rinzler, Charles C; Faircloth, Brian O; Koblick, Yeshaya; Moxley, Joel F

2014-10-28

Workover and completion systems, devices and methods for utilizing 10 kW or more laser energy transmitted deep into the earth with the suppression of associated nonlinear phenomena. Systems and devices for the laser workover and completion of a borehole in the earth. These systems and devices can deliver high power laser energy down a deep borehole, while maintaining the high power to perform laser workover and completion operations in such boreholes deep within the earth.

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

PubMed

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .

Optical ground station site diversity for Deep Space Optical Communications the Mars Telecom Orbiter optical link

NASA Technical Reports Server (NTRS)

Wilson, K.; Parvin, B.; Fugate, R.; Kervin, P.; Zingales, S.

2003-01-01

Future NASA deep space missions will fly advanced high resolution imaging instruments that will require high bandwidth links to return the huge data volumes generated by these instruments. Optical communications is a key technology for returning these large data volumes from deep space probes. Yet to cost effectively realize the high bandwidth potential of the optical link will require deployment of ground receivers in diverse locations to provide high link availability. A recent analysis of GOES weather satellite data showed that a network of ground stations located in Hawaii and the Southwest continental US can provide an average of 90% availability for the deep space optical link. JPL and AFRL are exploring the use of large telescopes in Hawaii, California, and Albuquerque to support the Mars Telesat laser communications demonstration. Designed to demonstrate multi-Mbps communications from Mars, the mission will investigate key operational strategies of future deep space optical communications network.

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

PubMed

Yuan, Yuchen; Shi, Yi; Li, Changyang; Kim, Jinman; Cai, Weidong; Han, Zeguang; Feng, David Dagan

2016-12-23

With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types.

Leg ulceration as a long-term complication of deep vein thrombosis.

PubMed

Walker, Natalie; Rodgers, Anthony; Birchall, Nicholas; Norton, Robyn; MacMahon, Stephen

2003-12-01

To evaluate the role of deep vein thrombosis as a cause of leg ulcers. A population-based, case-control study was conducted in Central and North Auckland, New Zealand. Cases comprised 241 people aged 40 to 99 years and on the electoral roll, with current leg ulcers (all types). Cases were identified by means of notification from health professionals and by self-referral. Controls were 224 people in the same age group, without leg ulcers, who were selected from the electoral roll by using a stratified random sampling process. The occurrence of leg ulceration as a consequence of exposure to deep vein thrombosis or being at high risk of deep vein thrombosis (that is, people with a family history of deep vein thrombosis, and/or a history of leg fracture and/or hip, leg, or foot surgery). After adjustment for age, sex, and other potential confounding factors, people who had a diagnosed thromboembolism were at almost three times higher risk of having a leg ulcer (odds ratio, 2.92; 95% confidence interval (CI), 1.47 to 6.08). In addition, people who had been at high risk of a venous thrombosis but were not diagnosed with this condition (eg, people with a history of major leg surgery) were also at increased risk of ulceration (odds ratio, 2.25; 95% CI, 1.49-3.42). Overall, 56% (95% CI, 33% - 71%) of leg ulcers were attributed to being at high risk of deep vein thrombosis. Deep vein thrombosis and factors that place people at high risk of deep vein thrombosis are an important cause of leg ulcers in older people. This finding strengthens the rationale for the routine and long-term use of thromboprophylaxis, particularly in high-risk patients.

De novo transcriptome assembly and positive selection analysis of an individual deep-sea fish.

PubMed

Lan, Yi; Sun, Jin; Xu, Ting; Chen, Chong; Tian, Renmao; Qiu, Jian-Wen; Qian, Pei-Yuan

2018-05-24

High hydrostatic pressure and low temperatures make the deep sea a harsh environment for life forms. Actin organization and microtubules assembly, which are essential for intracellular transport and cell motility, can be disrupted by high hydrostatic pressure. High hydrostatic pressure can also damage DNA. Nucleic acids exposed to low temperatures can form secondary structures that hinder genetic information processing. To study how deep-sea creatures adapt to such a hostile environment, one of the most straightforward ways is to sequence and compare their genes with those of their shallow-water relatives. We captured an individual of the fish species Aldrovandia affinis, which is a typical deep-sea inhabitant, from the Okinawa Trough at a depth of 1550 m using a remotely operated vehicle (ROV). We sequenced its transcriptome and analyzed its molecular adaptation. We obtained 27,633 protein coding sequences using an Illumina platform and compared them with those of several shallow-water fish species. Analysis of 4918 single-copy orthologs identified 138 positively selected genes in A. affinis, including genes involved in microtubule regulation. Particularly, functional domains related to cold shock as well as DNA repair are exposed to positive selection pressure in both deep-sea fish and hadal amphipod. Overall, we have identified a set of positively selected genes related to cytoskeleton structures, DNA repair and genetic information processing, which shed light on molecular adaptation to the deep sea. These results suggest that amino acid substitutions of these positively selected genes may contribute crucially to the adaptation of deep-sea animals. Additionally, we provide a high-quality transcriptome of a deep-sea fish for future deep-sea studies.

Mechanisms of ultrafast laser-induced deep-subwavelength gratings on graphite and diamond

NASA Astrophysics Data System (ADS)

Huang, Min; Zhao, Fuli; Cheng, Ya; Xu, Ningsheg; Xu, Zhizhan

2009-03-01

Deep-subwavelength gratings with periodicities of 170, 120, and 70 nm can be observed on highly oriented pyrolytic graphite irradiated by a femtosecond (fs) laser at 800 nm. Under picosecond laser irradiation, such gratings likewise can be produced. Interestingly, the 170-nm grating is also observed on single-crystal diamond irradiated by the 800-nm fs laser. In our opinion, the optical properties of the high-excited state of material surface play a key role for the formation of the deep-subwavelength gratings. The numerical simulations of the graphite deep-subwavelength grating at normal and high-excited states confirm that in the groove the light intensity can be extraordinarily enhanced via cavity-mode excitation in the condition of transverse-magnetic wave irradiation with near-ablation-threshold fluences. This field enhancement of polarization sensitiveness in deep-subwavelength apertures acts as an important feedback mechanism for the growth and polarization dependence of the deep-subwavelength gratings. In addition, we suggest that surface plasmons are responsible for the formation of seed deep-subwavelength apertures with a particular periodicity and the initial polarization dependence. Finally, we propose that the nanoscale Coulomb explosion occurring in the groove is responsible for the ultrafast nonthermal ablation mechanism.

Applying a punch with microridges in multistage deep drawing processes.

PubMed

Lin, Bor-Tsuen; Yang, Cheng-Yu

2016-01-01

The developers of high aspect ratio components aim to minimize the processing stages in deep drawing processes. This study elucidates the application of microridge punches in multistage deep drawing processes. A microridge punch improves drawing performance, thereby reducing the number of stages required in deep forming processes. As an example, the original eight-stage deep forming process for a copper cylindrical cup with a high aspect ratio was analyzed by finite element simulation. Microridge punch designs were introduced in Stages 4 and 7 to replace the original punches. In addition, Stages 3 and 6 were eliminated. Finally, these changes were verified through experiments. The results showed that the microridge punches reduced the number of deep drawing stages yielding similar thickness difference percentages. Further, the numerical and experimental results demonstrated good consistency in the thickness distribution.

Exploring fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Yong; Wang, Guang-Hua; Xu, Xin-Ya; Nong, Xu-Hua; Wang, Jie; Amin, Muhammad; Qi, Shu-Hua

2016-10-01

The present study investigated the fungal diversity in four different deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing of the nuclear ribosomal internal transcribed spacer-1 (ITS1). A total of 40,297 fungal ITS1 sequences clustered into 420 operational taxonomic units (OTUs) with 97% sequence similarity and 170 taxa were recovered from these sediments. Most ITS1 sequences (78%) belonged to the phylum Ascomycota, followed by Basidiomycota (17.3%), Zygomycota (1.5%) and Chytridiomycota (0.8%), and a small proportion (2.4%) belonged to unassigned fungal phyla. Compared with previous studies on fungal diversity of sediments from deep-sea environments by culture-dependent approach and clone library analysis, the present result suggested that Illumina sequencing had been dramatically accelerating the discovery of fungal community of deep-sea sediments. Furthermore, our results revealed that Sordariomycetes was the most diverse and abundant fungal class in this study, challenging the traditional view that the diversity of Sordariomycetes phylotypes was low in the deep-sea environments. In addition, more than 12 taxa accounted for 21.5% sequences were found to be rarely reported as deep-sea fungi, suggesting the deep-sea sediments from Okinawa Trough harbored a plethora of different fungal communities compared with other deep-sea environments. To our knowledge, this study is the first exploration of the fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing.

Development of Deep-tow Autonomous Cable Seismic (ACS) for Seafloor Massive Sulfides (SMSs) Exploration.

NASA Astrophysics Data System (ADS)

Asakawa, Eiichi; Murakami, Fumitoshi; Tsukahara, Hitoshi; Saito, Shutaro; Lee, Sangkyun; Tara, Kenji; Kato, Masafumi; Jamali Hondori, Ehsan; Sumi, Tomonori; Kadoshima, Kazuyuki; Kose, Masami

2017-04-01

Within the EEZ of Japan, numerous surveys exploring ocean floor resources have been conducted. The exploration targets are gas hydrates, mineral resources (manganese, cobalt or rare earth) and especially seafloor massive sulphide (SMS) deposits. These resources exist in shallow subsurface areas in deep waters (>1500m). For seismic explorations very high resolution images are required. These cannot be effectively obtained with conventional marine seismic techniques. Therefore we have been developing autonomous seismic survey systems which record the data close to the seafloor to preserve high frequency seismic energy. Very high sampling rate (10kHz) and high accurate synchronization between recording systems and shot time are necessary. We adopted Cs-base atomic clock considering its power consumption. At first, we developed a Vertical Cable Seismic (VCS) system that uses hydrophone arrays moored vertically from the ocean bottom to record close to the target area. This system has been successfully applied to SMS exploration. Specifically it fixed over known sites to assess the amount of reserves with the resultant 3D volume. Based on the success of VCS, we modified the VCS system to use as a more efficient deep-tow seismic survey system. Although there are other examples of deep-tow seismic systems, signal transmission cables present challenges in deep waters. We use our autonomous recording system to avoid these problems. Combining a high frequency piezoelectric source (Sub Bottom Profiler:SBP) that automatically shots with a constant interval, we achieve the high resolution deep-tow seismic without data transmission/power cable to the board. Although the data cannot be monitored in real-time, the towing system becomes very simple. We have carried out survey trial, which showed the systems utility as a high-resolution deep-tow seismic survey system. Furthermore, the frequency ranges of deep-towed source (SBP) and surface towed sparker are 700-2300Hz and 10-200Hz respectively. Therefore we can use these sources simultaneously and distinguish the records of each source in the data processing stage. We have developed new marine seismic survey systems with autonomous recording for the exploration of the ocean floor resources. The applications are vertical cable seismic (VCS) and deep-tow seismic (ACS). These enable us the recording close to the seafloor and give the high resolution results with a simple, cost-effective configuration.

Regional distribution of the high-altitude clouds over the Indian subcontinent and surrounding oceanic regions based on seven years of satellite observations

NASA Astrophysics Data System (ADS)

Meenu, S.; Rajeev, K.; Parameswaran, K.; Suresh Raju, C.

2006-12-01

Quantitative estimates of the spatio-temporal variations in deep convective events over the Indian subcontinent, Arabian Sea, Bay of Bengal, and tropical Indian Ocean are carried out using the data obtained from Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-14 and NOAA-16 during the period 1996-2003. Pixels having thermal IR brightness temperature (BT) less than 245K are considered as high altitude clouds and those having BT<220 K are considered as very high altitude clouds. Very deep convective clouds are observed over north Bay of Bengal during the Asian summer monsoon season when the mean cloud top temperature reaches as low as 190K. Over the Head Bay of Bengal (HBoB) from June to September, more than 50% of the observed clouds are deep convective type and more than half of these deep convective clouds are very deep convective clouds. Histogram analysis of the cloud top temperatures during this period shows that over HBoB the most prominent cloud top temperature of the deep convective clouds is ~205K over the HBoB while that over southeast Arabian Sea (SEAS) is ~220K. This indicates that most probably the cloud top altitude over HBoB is ~2 km larger than that over SEAS during the Asian summer monsoon period. Another remarkable feature observed during the Asian summer monsoon period is the significantly low values of deep convective clouds observed over the south Bay of Bengal close to Srilanka, which appears as a large pool of reduced cloud amount surrounded by regions of large-scale deep convection. Over both SEAS and HBoB, the total, deep convective and very deep convective cloud amounts as well as their corresponding cloud top temperatures (or the altitude of the cloud top) undergo large seasonal variations, while such variations are less prominent over the eastern equatorial Indian Ocean.

2-(2-Hydroxyphenyl)benzimidazole-based four-coordinate boron-containing materials with highly efficient deep-blue photoluminescence and electroluminescence.

PubMed

Zhang, Zhenyu; Zhang, Houyu; Jiao, Chuanjun; Ye, Kaiqi; Zhang, Hongyu; Zhang, Jingying; Wang, Yue

2015-03-16

Two novel four-coordinate boron-containing emitters 1 and 2 with deep-blue emissions were synthesized by refluxing a 2-(2-hydroxyphenyl)benzimidazole ligand with triphenylborane or bromodibenzoborole. The boron chelation produced a new π-conjugated skeleton, which rendered the synthesized boron materials with intense fluorescence, good thermal stability, and high carrier mobility. Both compounds displayed deep-blue emissions in solutions with very high fluorescence quantum yields (over 0.70). More importantly, the samples showed identical fluorescence in the solution and solid states, and the efficiency was maintained at a high level (approximately 0.50) because of the bulky substituents between the boron atom and the benzimidazole unit, which can effectively separate the flat luminescent units. In addition, neat thin films composed of 1 or 2 exhibited high electron and hole mobility in the same order of magnitude 10(-4), as determined by time-of-flight. The fabricated electroluminescent devices that employed 1 or 2 as emitting materials showed high-performance deep-blue emissions with Commission Internationale de L'Eclairage (CIE) coordinates of (X = 0.15, Y = 0.09) and (X = 0.16, Y = 0.08), respectively. Thus, the synthesized boron-containing materials are ideal candidates for fabricating high-performance deep-blue organic light-emitting diodes.

Beta-gamma burst stimulations of the inferior olive induce high-frequency oscillations in the deep cerebellar nuclei.

PubMed

Cheron, Julian; Cheron, Guy

2018-02-20

The cerebellum displays various sorts of rhythmic activities covering both low- and high-frequency oscillations. These cerebellar high-frequency oscillations were observed in the cerebellar cortex. Here, we hypothesised that not only is the cerebellar cortex a generator of high-frequency oscillations but also that the deep cerebellar nuclei may also play a similar role. Thus, we analysed local field potentials and single-unit activities in the deep cerebellar nuclei before, during and after electric stimulation in the inferior olive of awake mice. A high-frequency oscillation of 350 Hz triggered by the stimulation of the inferior olive, within the beta-gamma range, was observed in the deep cerebellar nuclei. The amplitude and frequency of the oscillation were independent of the frequency of stimulation. This oscillation emerged during the period of stimulation and persisted after the end of the stimulation. The oscillation coincided with the inhibition of deep cerebellar neurons. As the inhibition of the deep cerebellar nuclei is related to inhibitory inputs from Purkinje cells, we speculate that the oscillation represents the unmasking of the synchronous activation of another subtype of deep cerebellar neuronal subtype, devoid of GABA receptors and under the direct control of the climbing fibres from the inferior olive. Still, the mechanism sustaining this oscillation remains to be deciphered. Our study sheds new light on the role of the olivo-cerebellar loop as the final output control of the intercerebellar circuitry. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Linear-array based full-view high-resolution photoacoustic computed tomography of whole mouse brain functions in vivo

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Pengfei; Wang, Lihong V.

2018-02-01

Photoacoustic computed tomography (PACT) is a non-invasive imaging technique offering high contrast, high resolution, and deep penetration in biological tissues. We report a photoacoustic computed tomography (PACT) system equipped with a high frequency linear array for anatomical and functional imaging of the mouse whole brain. The linear array was rotationally scanned in the coronal plane to achieve the full-view coverage. We investigated spontaneous neural activities in the deep brain by monitoring the hemodynamics and observed strong interhemispherical correlations between contralateral regions, both in the cortical layer and in the deep regions.

Microbial Life in the Deep Subsurface: Deep, Hot and Radioactive

NASA Technical Reports Server (NTRS)

DeStefano, Andrea L.; Ford, Jill C.; Winsor, Seana K.; Allen, Carlton C.; Miller, Judith; McNamara, Karen M.; Gibson, Everett K., Jr.

2000-01-01

Recent studies, motivated in part by the search for extraterrestrial life, continue to expand the recognized limits of Earth's biosphere. This work explored evidence for life a high-temperature, radioactive environment in the deep subsurface.

Occult pulmonary embolism: a common occurrence in deep venous thrombosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dorfman, G.S.; Cronan, J.J.; Tupper, T.B.

1987-02-01

Ventilation-perfusion scans were used in a prospective study to determine the prevalence of occult pulmonary embolus in proven deep venous thrombosis. Fifty-eight patients without symptoms of pulmonary embolism, but with venographically proven deep venous thrombosis, were subjected to chest radiographs, /sup 99m/Tc macroaggregated-albumin perfusion scans, and /sup 133/Xe ventilation scans. Of the 49 patients with deep venous thrombosis proximal to the calf veins, 17 (35%) had high-probability scans. Of all 58 patients, only 12 (21%) had normal scans. When the study population was compared with a group of 430 patients described in reports of pulmonary perfusion in asymptomatic persons, amore » significantly higher percentage of high-probability scans was found in the study population with deep venous thrombosis. Baseline ventilation-perfusion lung scanning is valuable for patients with proven above-knee deep venous thrombosis.« less

Thermal quenching effect of an infrared deep level in Mg-doped p-type GaN films

NASA Astrophysics Data System (ADS)

Kim, Keunjoo; Chung, Sang Jo

2002-03-01

The thermal quenching of an infrared deep level of 1.2-1.5 eV has been investigated on Mg-doped p-type GaN films, using one- and two-step annealing processes and photocurrent measurements. The deep level appeared in the one-step annealing process at a relatively high temperature of 900 °C, but disappeared in the two-step annealing process with a low-temperature step and a subsequent high-temperature step. The persistent photocurrent was residual in the sample including the deep level, while it was terminated in the sample without the deep level. This indicates that the deep level is a neutral hole center located above a quasi-Fermi level, estimated with an energy of EpF=0.1-0.15 eV above the valence band at a hole carrier concentration of 2.0-2.5×1017/cm3.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

PubMed

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Changes in chemical composition of frozen coated fish products during deep-frying.

PubMed

Pérez-Palacios, Trinidad; Petisca, Catarina; Casal, Susana; Ferreira, Isabel M P L V O

2014-03-01

This work evaluates the influence of deep-frying coated fish products on total fat, fatty acid (FA) and amino acid profile, and on the formation of volatile compounds, with special attention on furan and its derivatives due to their potential harmful characteristics. As expected, deep-frying in sunflower oil increased linoleic acid content, but total fat amount increased only by 2% on a dry basis. Eicosapentanoic and docosahexanoic acids were preserved while γ- and α-linoleic acids were oxidised. Deep-frying also induces proteolysis, releasing free AA, and the formation of volatile compounds, particularly aldehydes and ketones arising from polyunsaturated FA. In addition, high quantities of furanic compounds, particularly furan and furfuryl alcohol, are generated during deep-frying coated fish. The breaded crust formed could contribute simultaneously for the low uptake of fat, preservation of long chain n-3 FA, and for the high amounts of furanic compounds formed during the deep-frying process.

Deep Fracturing of the Hard Rock Surrounding a Large Underground Cavern Subjected to High Geostress: In Situ Observation and Mechanism Analysis

NASA Astrophysics Data System (ADS)

Feng, Xia-Ting; Pei, Shu-Feng; Jiang, Quan; Zhou, Yang-Yi; Li, Shao-Jun; Yao, Zhi-Bin

2017-08-01

Rocks that are far removed from caverns or tunnels peripheries and subjected to high geostress may undergo `deep fracturing'. Deep fracturing of hard rock can cause serious hazards that cause delays and increase the cost of construction of underground caverns with high sidewalls and large spans (especially when subjected to high geostress). To extensively investigate the mechanism responsible for deep fracturing, and the relationship between fracturing and the excavation & support of caverns, this paper presents a basic procedure for making in situ observations on the deep fracturing process in hard rock. The basic procedure involves predicting the stress concentration zones in the surrounding rocks of caverns induced by excavation using geomechanical techniques. Boreholes are then drilled through these stress concentration zones from pre-existing tunnels (such as auxiliary galleries) toward the caverns before its excavation. Continuous observations of the fracturing of the surrounding rocks are performed during excavation using a borehole camera in the boreholes in order to analyze the evolution of the fracturing process. The deep fracturing observed in a large underground cavern (high sidewalls and large span) in southwest China excavated in basalt under high geostress is also discussed. By continuously observing the hard rock surrounding the arch on the upstream side of the cavern during the excavation of the first three layers, it was observed that the fracturing developed into the surrounding rocks with downward excavation of the cavern. Fracturing was found at distances up to 8-9 m from the cavern periphery during the excavation of Layer III. Also, the cracks propagated along pre-existing joints or at the interfaces between quartz porphyry and the rock matrix. The relationship between deep fracturing of the surrounding rocks and the advance of the cavern working faces was analyzed during excavation of Layer Ib. The results indicate that the extent of the stress relief zone is about 7 m if footage of 3 m is adopted for the rate of advance of the cavern faces. An analysis of the effects of the initial geostress and evolving stress concentration on deep fracturing was also made. It could be concluded that the deep fracturing of the rocks in the upstream side of the cavern is caused by the combined effect of the high initial geostress, the transfer of the stress concentration zone toward the deep surrounding rocks, and the occurrence of discontinuities.

The importance of habitat and life history to extinction risk in sharks, skates, rays and chimaeras

PubMed Central

García, Verónica B; Lucifora, Luis O; Myers, Ransom A

2007-01-01

We compared life-history traits and extinction risk of chondrichthyans (sharks, rays and chimaeras), a group of high conservation concern, from the three major marine habitats (continental shelves, open ocean and deep sea), controlling for phylogenetic correlation. Deep-water chondrichthyans had a higher age at maturity and longevity, and a lower growth completion rate than shallow-water species. The average fishing mortality needed to drive a deep-water chondrichthyan species to extinction (Fextinct) was 38–58% of that estimated for oceanic and continental shelf species, respectively. Mean values of Fextinct were 0.149, 0.250 and 0.368 for deep-water, oceanic and continental shelf species, respectively. Reproductive mode was an important determinant of extinction risk, while body size had a weak effect on extinction risk. As extinction risk was highly correlated with phylogeny, the loss of species will be accompanied by a loss of phylogenetic diversity. Conservation priority should not be restricted to large species, as is usually suggested, since many small species, like those inhabiting the deep ocean, are also highly vulnerable to extinction. Fishing mortality of deep-water chondrichthyans already exploited should be minimized, and new deep-water fisheries affecting chondrichthyans should be prevented. PMID:17956843

Numerical investigation of deep-crust behavior under lithospheric extension

NASA Astrophysics Data System (ADS)

Korchinski, Megan; Rey, Patrice F.; Mondy, Luke; Teyssier, Christian; Whitney, Donna L.

2018-02-01

What are the conditions under which lithospheric extension drives exhumation of the deep orogenic crust during the formation of gneiss domes? The mechanical link between extension of shallow crust and flow of deep crust is investigated using two-dimensional numerical experiments of lithospheric extension in which the crust is 60 km thick and the deep-crust viscosity and density parameter space is explored. Results indicate that the style of extension of the shallow crust and the path, magnitude, and rate of flow of deep crust are dynamically linked through the deep-crust viscosity, with density playing an important role in experiments with a high-viscosity deep crust. Three main groups of domes are defined based on their mechanisms of exhumation across the viscosity-density parameter space. In the first group (low-viscosity, low-density deep crust), domes develop by lateral and upward flow of the deep crust at km m.y-1 velocity rates (i.e. rate of experiment boundary extension). In this case, extension in the shallow crust is localized on a single interface, and the deep crust traverses the entire thickness of the crust to the Earth's near-surface in 5 m.y. This high exhuming power relies on the dynamic feedback between the flow of deep crust and the localization of extension in the shallow crust. The second group (intermediate-viscosity, low-density deep crust) has less exhuming power because the stronger deep crust flows less readily and instead accommodates more uniform extension, which imparts distributed extension to the shallow crust. The third group represents the upper limits of viscosity and density for the deep crust; in this case the low buoyancy of the deep crust results in localized thinning of the crust with large upward motion of the Moho and lithosphere-asthenosphere boundary. These numerical experiments test the exhuming power of the deep crust in the formation of extensional gneiss domes.

Deep Reactive Ion Etching (DRIE) of High Aspect Ratio SiC Microstructures using a Time-Multiplexed Etch-Passivate Process

NASA Technical Reports Server (NTRS)

Evans, Laura J.; Beheim, Glenn M.

2006-01-01

High aspect ratio silicon carbide (SiC) microstructures are needed for microengines and other harsh environment micro-electro-mechanical systems (MEMS). Previously, deep reactive ion etching (DRIE) of low aspect ratio (AR less than or = 1) deep (greater than 100 micron) trenches in SiC has been reported. However, existing DRIE processes for SiC are not well-suited for definition of high aspect ratio features because such simple etch-only processes provide insufficient control over sidewall roughness and slope. Therefore, we have investigated the use of a time-multiplexed etch-passivate (TMEP) process, which alternates etching with polymer passivation of the etch sidewalls. An optimized TMEP process was used to etch high aspect ratio (AR greater than 5) deep (less than 100 micron) trenches in 6H-SiC. Power MEMS structures (micro turbine blades) in 6H-SiC were also fabricated.

All-photonic drying and sintering process via flash white light combined with deep-UV and near-infrared irradiation for highly conductive copper nano-ink

PubMed Central

Hwang, Hyun-Jun; Oh, Kyung-Hwan; Kim, Hak-Sung

2016-01-01

We developed an ultra-high speed photonic sintering method involving flash white light (FWL) combined with near infrared (NIR) and deep UV light irradiation to produce highly conductive copper nano-ink film. Flash white light irradiation energy and the power of NIR/deep UV were optimized to obtain high conductivity Cu films. Several microscopic and spectroscopic characterization techniques such as scanning electron microscopy (SEM), a x-ray diffraction (XRD), and Fourier-transform infrared (FT-IR) spectroscopy were employed to characterize the Cu nano-films. Optimally sintered Cu nano-ink films produced using a deep UV-assisted flash white light sintering technique had the lowest resistivity (7.62 μΩ·cm), which was only 4.5-fold higher than that of bulk Cu film (1.68 μΩ•cm). PMID:26806215

Highly efficient deep-blue organic light emitting diode with a carbazole based fluorescent emitter

NASA Astrophysics Data System (ADS)

Sahoo, Snehasis; Dubey, Deepak Kumar; Singh, Meenu; Joseph, Vellaichamy; Thomas, K. R. Justin; Jou, Jwo-Huei

2018-04-01

High efficiency deep-blue emission is essential to realize energy-saving, high-quality display and lighting applications. We demonstrate here a deep-blue organic light emitting diode using a novel carbazole based fluorescent emitter 7-[4-(diphenylamino)phenyl]-9-(2-ethylhexyl)-9H-carbazole-2-carbonitrile (JV234). The solution processed resultant device shows a maximum luminance above 1,750 cd m-2 and CIE coordinates (0.15,0.06) with a 1.3 lm W-1 power efficiency, 2.0 cd A-1 current efficiency, and 4.1% external quantum efficiency at 100 cd m-2. The resulting deep-blue emission enables a greater than 100% color saturation. The high efficiency may be attributed to the effective host-to-guest energy transfer, suitable device architecture facilitating balanced carrier injection and low doping concentration preventing efficiency roll-off caused by concentration quenching.

All-photonic drying and sintering process via flash white light combined with deep-UV and near-infrared irradiation for highly conductive copper nano-ink.

PubMed

Hwang, Hyun-Jun; Oh, Kyung-Hwan; Kim, Hak-Sung

2016-01-25

We developed an ultra-high speed photonic sintering method involving flash white light (FWL) combined with near infrared (NIR) and deep UV light irradiation to produce highly conductive copper nano-ink film. Flash white light irradiation energy and the power of NIR/deep UV were optimized to obtain high conductivity Cu films. Several microscopic and spectroscopic characterization techniques such as scanning electron microscopy (SEM), a x-ray diffraction (XRD), and Fourier-transform infrared (FT-IR) spectroscopy were employed to characterize the Cu nano-films. Optimally sintered Cu nano-ink films produced using a deep UV-assisted flash white light sintering technique had the lowest resistivity (7.62 μΩ·cm), which was only 4.5-fold higher than that of bulk Cu film (1.68 μΩ•cm).

Perylene-diimide-based nanoparticles as highly efficient photoacoustic agents for deep brain tumor imaging in living mice

DOE PAGES

Fan, Quli; Cheng, Kai; Yang, Zhen; ...

2014-11-06

In order to promote preclinical and clinical applications of photoacoustic imaging, novel photoacoustic contrast agents are highly desired for molecular imaging of diseases, especially for deep tumor imaging. In this paper, perylene-3,4,9,10-tetracarboxylic diiimide-based near-infrared-absorptive organic nanoparticles are reported as an efficient agent for photoacoustic imaging of deep brain tumors in living mice with enhanced permeability and retention effect

Highly Manufacturable Deep (Sub-Millimeter) Etching Enabled High Aspect Ratio Complex Geometry Lego-Like Silicon Electronics.

PubMed

Ghoneim, Mohamed Tarek; Hussain, Muhammad Mustafa

2017-04-01

A highly manufacturable deep reactive ion etching based process involving a hybrid soft/hard mask process technology shows high aspect ratio complex geometry Lego-like silicon electronics formation enabling free-form (physically flexible, stretchable, and reconfigurable) electronic systems. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of deep-ultraviolet metal vapor lasers

NASA Astrophysics Data System (ADS)

Sabotinov, Nikola V.

2004-06-01

Deep ultraviolet laser generation is of great interest in connection with both the development of new industrial technologies and applications in medicine, biology, chemistry, etc. The development of metal vapor UV lasers oscillating in the pulsed mode with high pulse repetition frequencies and producing high average output powers is of particular interest for microprocessing of polymers, photolithography and fluorescence applications. At present, metal vapor lasers generate deep-UV radiation on the base of two methods. The first method is non-linear conversion of powerful laser generation from the visible region into the deep ultraviolet region. The second method is direct UV laser action on ion and atomic transitions of different metals.

Acquiring High-Performance Deep-Blue OLED Emitters through an Unexpected Blueshift Color-Tuning Effect Induced by Electron-Donating -OMe Substituents.

PubMed

Peng, Song; Zhao, Yihuan; Fu, Caixia; Pu, Xuemei; Zhou, Liang; Huang, Yan; Lu, Zhiyun

2018-06-07

A series of blue-emissive 7-(diphenylamino)-4-phenoxycoumarin derivatives bearing -CF 3 , -OMe, or -N(Me) 2 substituents on the phenoxy subunit were synthesized. Although both the -CF 3 and -N(Me) 2 modifications were found to trigger redshifted fluorescence, the -OMe substitution was demonstrated to exert an unexpected blueshift color-tuning effect toward the deep-blue region. The reason is that the moderate electron-donating -OMe group can endow coumarins with unaltered HOMO but elevated LUMO energy levels. Moreover, the -OMe substitution was found to be beneficial to the thermal stability of these coumarins. Therefore, the trimethoxy-substituted objective compound can act as a high-performance deep-blue organic light-emitting diode (OLED) emitter, and OLED based on it emits deep-blue light with CIE coordinates of (0.148, 0.084), maximum luminance of 7800 cd m -2 , and maximum external quantum efficiency of 5.1 %. These results not only shed light on the molecular design strategy for high-performance deep-blue OLED emitters through color-tuning, but also show the perspective of coumarin derivatives as deep-blue OLED emitters. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Impact of Tropopause Structures on Deep Convective Transport Observed during MACPEX

NASA Astrophysics Data System (ADS)

Mullendore, G. L.; Bigelbach, B. C.; Christensen, L. E.; Maddox, E.; Pinkney, K.; Wagner, S.

2016-12-01

Deep convection is the most efficient method of transporting boundary layer mass to the upper troposphere and stratosphere (UTLS). The Mid-latitude Airborne Cirrus Properties Experiment (MACPEX) was conducted during April of 2011 over the central U.S. With a focus on cirrus clouds, the campaign flights often sampled large cirrus anvils downstream from deep convection and included an extensive observational suite of chemical measurements on a high altitude aircraft. As double-tropopause structures are a common feature in the central U.S. during the springtime, the MACPEX campaign provides a good opportunity to gather cases of deep convective transport in the context of both single and double tropopause structures. Sampling of chemical plumes well downstream from convection allows for sampling in relatively quiescent conditions and analysis of irreversible transport. The analysis presented includes multiple methods to assess air mass source and possible convective processing, including back trajectories and ratios of chemical concentrations. Although missions were flown downstream of deep convection, recent processing by convection does not seem likely in all cases that high altitude carbon monoxide plumes were observed. Additionally, the impact of single and double tropopause structures on deep convective transport is shown to be strongly dependent on high stability layers.

Deep Reconditioning Testing for near Earth Orbits

NASA Technical Reports Server (NTRS)

Betz, F. E.; Barnes, W. L.

1984-01-01

The problems and benefits of deep reconditioning to near Earth orbit missions with high cycle life and shallow discharge depth requirements is discussed. A simple battery level approach to deep reconditioning of nickel cadmium batteries in near Earth orbit is considered. A test plan was developed to perform deep reconditioning in direct comparison with an alternative trickle charge approach. The results demonstrate that the deep reconditioning procedure described for near Earth orbit application is inferior to the alternative of trickle charging.

Iris Transponder-Communications and Navigation for Deep Space

NASA Technical Reports Server (NTRS)

Duncan, Courtney B.; Smith, Amy E.; Aguirre, Fernando H.

2014-01-01

The Jet Propulsion Laboratory has developed the Iris CubeSat compatible deep space transponder for INSPIRE, the first CubeSat to deep space. Iris is 0.4 U, 0.4 kg, consumes 12.8 W, and interoperates with NASA's Deep Space Network (DSN) on X-Band frequencies (7.2 GHz uplink, 8.4 GHz downlink) for command, telemetry, and navigation. This talk discusses the Iris for INSPIRE, it's features and requirements; future developments and improvements underway; deep space and proximity operations applications for Iris; high rate earth orbit variants; and ground requirements, such as are implemented in the DSN, for deep space operations.

Imaging 3D crustal and upper mantle structures of the Northeast China using local and teleseismic data

NASA Astrophysics Data System (ADS)

Huang, J.

2017-12-01

Northeast China is located in the composite part of Paleo Asia ocean and Pacific ocean Domain, it undergone multi-stage tectonism and has complicated geological structure. In this region, two major geologic and geophysical boundaries are distinct, the NNE-trending North South Gravity Lineament (NSGL) and Tanlu fault. With respect to North China Craton (NCC), Northeast China is more closely adjacent to the subduction zone of Pacific slab. Along the eastern boundary of Northeast China, the subducting Pacific plate approaches depths of 600 km, many deep earthquakes occurred here. This region becomes an ideal place to investigate deep structure related to deep subduction, deep earthquakes as well as intraplate volcanism. In this study, we determined high-resolution three dimensional P- and S-wave velocity models of the crust and upper mantle to 800 km depth by jointly inverting arrival times from local events and relative residuals from teleseismic events. Our results show that main velocity anomalies exhibited block feature and are generally oriented in NE to NNE direction, which is consistent with regional tectonic direction. The NSGL is characterized by a high-velocity (high-V) anomaly belt with a width of approximately 100 km, and the high-V anomaly extents to the bottom of upper mantle or mantle transition zone. The songliao basin, which is located between NSGL and Tanlu fault tectonic boundaries, obvious low-velocity anomaly extends to about depth of 200 km(. Under the Great Xing'an Range on the west side of NSGL, the low velocity extend to the lithosphere. Our results also show that most of deep earthquakes all occurred in deep subduction zone with high-velocity anomaly. Further, we also observed that extensive low velocity exists above deep-earthquakes zones, this result suggests that deep subduction of the Pacific slab maybe affect overlying lithosphere, resulting in the state of molten, semi-molten or high water.This research is supported by the National Science Foundation of China (91114204) and National Key R&D Plan (2017YFC0601406)

High-pressure orthorhombic ferromagnesite as a potential deep-mantle carbon carrier

DOE PAGES

Liu, Jin; Lin, Jung -Fu; Prakapenka, Vitali B.

2015-01-06

In this study, knowledge of the physical and chemical properties of candidate deep-carbon carriers such as ferromagnesite [(Mg,Fe)CO 3] at high pressure and temperature of the deep mantle is necessary for our understanding of deep-carbon storage as well as the global carbon cycle of the planet. Previous studies have reported very different scenarios for the (Mg,Fe)CO 3 system at deep-mantle conditions including the chemical dissociation to (Mg,Fe)O+CO 2, the occurrence of the tetrahedrally-coordinated carbonates based on CO 4 structural units, and various high-pressure phase transitions. Here we have studied the phase stability and compressional behavior of (Mg,Fe)CO 3 carbonates upmore » to relevant lower-mantle conditions of approximately 120 GPa and 2400 K. Our experimental results show that the rhombohedral siderite (Phase I) transforms to an orthorhombic phase (Phase II with Pmm2 space group) at approximately 50 GPa and 1400 K. The structural transition is likely driven by the spin transition of iron accompanied by a volume collapse in the Fe-rich (Mg,Fe)CO 3 phases; the spin transition stabilizes the high-pressure phase II at much lower pressure conditions than its Mg-rich counterpart. It is conceivable that the low-spin ferromagnesite phase II becomes a major deep-carbon carrier at the deeper parts of the lower mantle below 1900 km in depth.« less

Highlights from the WIN 2017 Symposium, 26-27 June 2017, Paris, France: 'Expediting Global Innovation in Precision Cancer Medicine'.

PubMed

Davies, Will

2017-01-01

The Worldwide Innovative Networking (WIN) symposium brings together representatives from academic institutions, pharmaceutical partners, technology companies and charitable organisations from across the globe for an annual summit, discussing ongoing research and the latest developments in precision medicine. Now, in its seventh year, the aims of the WIN consortium's annual meeting, to foster communication and collaboration between members and deliver clinical trial results that improve the care and outcomes of patients are presented in open dialogue to encourage debate and discussion. This year, the meeting was held in Paris, France from 26-27 June and consisted of six plenary sessions, two debates, and poster presentations from attendees. In keeping with the consortium's goals, presentations and posters focused on the development and integration of new therapies and updates in genome-based medicine. Among the presentations at this year's meeting, much of the focus fell on design and implementation of new designs of clinical trials, moving away from decades-long assessments of thousands of patients towards a nimble, adaptive design fitting the edicts of personalised medicine and delving into greater depths within genomic data, ranging beyond genome analysis to chart new targets in ligandomics, proteogenomics and more.

Anaerobic Degradation of Benzene and Polycyclic Aromatic Hydrocarbons.

PubMed

Meckenstock, Rainer U; Boll, Matthias; Mouttaki, Housna; Koelschbach, Janina S; Cunha Tarouco, Paola; Weyrauch, Philip; Dong, Xiyang; Himmelberg, Anne M

2016-01-01

Aromatic hydrocarbons such as benzene and polycyclic aromatic hydrocarbons (PAHs) are very slowly degraded without molecular oxygen. Here, we review the recent advances in the elucidation of the first known degradation pathways of these environmental hazards. Anaerobic degradation of benzene and PAHs has been successfully documented in the environment by metabolite analysis, compound-specific isotope analysis and microcosm studies. Subsequently, also enrichments and pure cultures were obtained that anaerobically degrade benzene, naphthalene or methylnaphthalene, and even phenanthrene, the largest PAH currently known to be degradable under anoxic conditions. Although such cultures grow very slowly, with doubling times of around 2 weeks, and produce only very little biomass in batch cultures, successful proteogenomic, transcriptomic and biochemical studies revealed novel degradation pathways with exciting biochemical reactions such as for example the carboxylation of naphthalene or the ATP-independent reduction of naphthoyl-coenzyme A. The elucidation of the first anaerobic degradation pathways of naphthalene and methylnaphthalene at the genetic and biochemical level now opens the door to studying the anaerobic metabolism and ecology of anaerobic PAH degraders. This will contribute to assessing the fate of one of the most important contaminant classes in anoxic sediments and aquifers. © 2016 S. Karger AG, Basel.

Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

PubMed

Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei

2017-09-01

Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

PubMed Central

Bao, Wei; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

Process Studies on Laser Welding of Copper with Brilliant Green and Infrared Lasers

NASA Astrophysics Data System (ADS)

Engler, Sebastian; Ramsayer, Reiner; Poprawe, Reinhart

Copper materials are classified as difficult to weld with state-of-the-art lasers. High thermal conductivity in combination with low absorption at room temperature require high intensities for reaching a deep penetration welding process. The low absorption also causes high sensitivity to variations in surface conditions. Green laser radiation shows a considerable higher absorption at room temperature. This reduces the threshold intensity for deep penetration welding significantly. The influence of the green wavelength on energy coupling during heat conduction welding and deep penetration welding as well as the influence on the weld shape has been investigated.

Community Proteogenomics of a Cold-methane Seep Sediment at Nyegga, Mid-Norwegian Margin

NASA Astrophysics Data System (ADS)

Stokke, R.; Roalkvam, I.; Lanzen, A.; Chen, Y.; Haflidason, H.; Steen, I.

2010-12-01

Anaerobic oxidation of methane (AOM) is limited to anoxic environments and differs in its rates from a few pmol cm-3day-1 in subsurface SMTZ (sulfate-methane transition zone) of deep margins, to a few μmol cm-3 day-1 in surface sediments above gas hydrates [1]. This process is catalyzed by consortia of anaerobic methane oxidizing archaea (ANME) in association with sulfate-reducing bacteria. The Nyegga area is located on the Mid-Norwegian continental slope at the northern flank of the Storegga Slide at 700-800 mbsl. Hundreds of pockmarks are widespread on the seabed in Nyegga and sub-zero temperatures (-0.7 °C), and pingo-structures within the pockmarks are indicators of active fluid flow locations. Preliminary microbial and geochemical profiling of a 22 cm push-core within the G11 pockmark gave strong indications of an ANME-1 dominated community at 14-16 cmbsf. In light of these findings we submitted extracted DNA to 454-pyrosequencing. Sequencing data (829,527 reads) was assembled using the Newbler v2.3, resulting in 13,151 contigs (357,530 reads) over 500 bp with the longest contig being 24,521 bp. MEGAN taxonomic analysis supported the high abundance of Euryarchaea (70%) with 66% of the assembled metagenome belonging to ANME-1. In order to obtain functional information of the ANME-1 community, protein extraction protocols from sediment samples was established. Extracted proteins was separated on a large (18cm) 1D-SDS-PAGE and subsequently cut in 30 gel slices. Peptides extracted after In-gel tryptic digest was injected into an Ultimate 3000 nanoLC system connected to a linear quadropole ion trap-orbitrap (LTQ-Orbitrap XL) mass spectrometer equipped with a nanoelectrospray ion source. A custom database of open reading frames (ORFs) from the metagenome including known contaminants such as trypsin and human keratin was search against using Mascot 2.2. IRMa tool box [2] was used in peptide validation and peptides whose score >= 25.0 (i.e avg identity, p<0.05) and rank <= 1 was marked as significant. Validated protein ORFs were subjected to a local Blastp search against NCBInr with an E-value cut-off 0.001. A total of 370 proteins met the criteria with 254 of the proteins belonging to ANME-1. The protein dataset contained enzymes involved in C1-metabolism in the reverse metanogenesis pathway of ANME-1 as well as the enzymes sulfite reductase and APS-reductase (of presumably bacterial origin). Hence, the key enzymes involved in anaerobic methane oxidation were expressed in the environment. Results will be further discussed. [1] Knittel, K., and Boetius, A. (2009) Anaerobic Oxidation of Methane: Progress with an Unknown Process. Annu. Rev. Microbiol. 63, 311-334. [2] Dupierris, V., Masselon, C., Court, M., Kieffer-Jaquinod, S., and Bruley, C. (2009) A toolbox for validation of mass spectrometry peptides identification and generation of database: IRMa. Bioinformatics 25, 1980-1981.

Breaking the acoustic diffraction limit via nonlinear effect and thermal confinement for potential deep-tissue high-resolution imaging

PubMed Central

Yuan, Baohong; Pei, Yanbo; Kandukuri, Jayanth

2013-01-01

Our recently developed ultrasound-switchable fluorescence (USF) imaging technique showed that it was feasible to conduct high-resolution fluorescence imaging in a centimeter-deep turbid medium. Because the spatial resolution of this technique highly depends on the ultrasound-induced temperature focal size (UTFS), minimization of UTFS becomes important for further improving the spatial resolution USF technique. In this study, we found that UTFS can be significantly reduced below the diffraction-limited acoustic intensity focal size via nonlinear acoustic effects and thermal confinement by appropriately controlling ultrasound power and exposure time, which can be potentially used for deep-tissue high-resolution imaging. PMID:23479498

Development and applications of an acoustic package for deep-sea sub-bottom profiling and detailed seafloor imaging

NASA Astrophysics Data System (ADS)

Nishimura, Kiyokazu; Kisimoto, Kiyoyuki; Joshima, Masato; Arai, Kohsaku

In the deep-sea geological survey, good survey results are difficult to obtain by a conventional surface-towed acoustic survey system, because the horizontal resolution is limited due to the long distance between the sensor and the target (seafloor). In order to improve the horizontal resolution, a deep-tow system, which tows the sensor in the vicinity of seafloor, is most practical, and many such systems have been developed and used until today. It is not easy, however, to carry out a high-density survey in a small area by maneuvering the towing body altitude sufficiently close to the seafloor with rugged topography. A ROV (Remotely Operated Vehicle) can be used to solve this problem. The ROV makes a high-density 2D survey feasible because of its maneuverability, although a long-distance survey is difficult with it. Accordingly, we have developed an acoustic survey system installed on a ROV. The system named DAIPACK (Deep-sea Acoustic Imaging Package) consists of (1) a deep-sea sub-bottom profiler and (2) a deep-sea sidescan sonar. (1) Deep-sea sub-bottom profiler A light-weight and compact sub-bottom profiler for shallow water was chosen to improve and repackage for the deep sea usage. The system is composed of three units; a transducer, an electronic unit and a notebook computer for system control and data acquisition. The source frequency is 10kHz. To convert the system for the deep sea, the transducer was exchanged for the deep sea model, and the electronic unit was improved accordingly. The electronic unit and the notebook computer were installed in a spherical pressure vessel. (2) Deep-sea sidescan sonar We remodeled a compact shallow sea sidescan sonar(water depth limitation is 30m ) into a deep sea one. This sidescan sonar is composed of a sonar towfish (transducers and an electronic unit ), a cable and a notebook computer (data processor). To accommodate in the deep water, the transducers were remodeled into a high pressure resistance type, and the electronic unit and the computer unit were stored in a spherical pressure vessel. The frequency output of the sidescan sonar is 330kHz, and the ranging distance is variable from 15m to 120m (one side).

Controls on deep drainage beneath the root soil zone in snowmelt-dominated environments

NASA Astrophysics Data System (ADS)

Hammond, J. C.; Harpold, A. A.; Kampf, S. K.

2017-12-01

Snowmelt is the dominant source of streamflow generation and groundwater recharge in many high elevation and high latitude locations, yet we still lack a detailed understanding of how snowmelt is partitioned between the soil, deep drainage, and streamflow under a variety of soil, climate, and snow conditions. Here we use Hydrus 1-D simulations with historical inputs from five SNOTEL snow monitoring sites in each of three regions, Cascades, Sierra, and Southern Rockies, to investigate how inter-annual variability on water input rate and duration affects soil saturation and deep drainage. Each input scenario was run with three different soil profiles of varying hydraulic conductivity, soil texture, and bulk density. We also created artificial snowmelt scenarios to test how snowmelt intermittence affects deep drainage. Results indicate that precipitation is the strongest predictor (R2 = 0.83) of deep drainage below the root zone, with weaker relationships observed between deep drainage and snow persistence, peak snow water equivalent, and melt rate. The ratio of deep drainage to precipitation shows a stronger positive relationship to melt rate suggesting that a greater fraction of input becomes deep drainage at higher melt rates. For a given amount of precipitation, rapid, concentrated snowmelt may create greater deep drainage below the root zone than slower, intermittent melt. Deep drainage requires saturation below the root zone, so saturated hydraulic conductivity serves as a primary control on deep drainage magnitude. Deep drainage response to climate is mostly independent of soil texture because of its reliance on saturated conditions. Mean water year saturations of deep soil layers can predict deep drainage and may be a useful way to compare sites in soils with soil hydraulic porosities. The unit depth of surface runoff often is often greater than deep drainage at daily and annual timescales, as snowmelt exceeds infiltration capacity in near-surface soil layers. These results suggest that processes affecting the duration of saturation below the root zone could compromise deep recharge, including changes in snowmelt rate and duration as well as the depth and rate of ET losses from the soil profile.

The T-Reflection and the deep crustal structure of the Vøring Margin offshore Mid-Norway

NASA Astrophysics Data System (ADS)

Abdelmalak, M. M.; Faleide, J. I.; Planke, S.; Gernigon, L.; Zastrozhnov, D.; Shephard, G. E.; Myklebust, R.

2017-12-01

Volcanic passive margins are characterized by massive occurrence of mafic extrusive and intrusive rocks, before and during plate breakup, playing major role in determining the evolution pattern and the deep structure of magma-rich margins. Deep seismic reflection data frequently provide imaging of strong continuous reflections in the middle/lower crust. In this context, we have completed a detailed 2D seismic interpretation of the deep crustal structure of the Vøring volcanic margin, offshore mid-Norway, where high-quality seismic data allow the identification of high-amplitude reflections, locally referred to as the T-Reflection (TR). Using the dense seismic grid we have mapped the top of the TR in order to compare it with filtered Bouguer gravity anomalies and seismic refraction data. The TR is identified between 7 and 10 s. Sometimes it consists of one single smooth reflection. However, it is frequently associated with a set of rough multiple reflections displaying discontinuous segments with varying geometries, amplitude and contact relationships. The TR seems to be connected to deep sill networks and locally located at the continuation of basement high structures or terminates over fractures and faults. The spatial correlation between the filtered positive Bouguer gravity anomalies and the TR indicates that the latter represents a high impedance boundary contrast associated with a high-density/velocity body. Within an uncertainty of ± 2.5 km, the depth of the mapped TR is found to correspond to the depth of the top of the Lower Crustal Body (LCB), characterized by high P-wave velocities (>7 km/s), in 50% of the outer Vøring Margin areas, whereas different depths between the TR and the top LCB are estimated for the remaining areas. We present a tectonic scenario, where a large part of the deep structure could be composed of preserved upper continental basement and middle to lower crustal lenses of inherited and intruded high-grade metamorphic rocks. Deep intrusions into the faulted crustal blocks are responsible for the rough character of the TR, whereas intrusions into the lower crust and detachment faults are likely responsible for its smoother appearance. Deep magma intrusions can be responsible for metamorphic processes leading to an increased velocity of the lower crust of more than 7 km/s.

Comparative analysis of genomics and proteomics in Bacillus thuringiensis 4.0718.

PubMed

Rang, Jie; He, Hao; Wang, Ting; Ding, Xuezhi; Zuo, Mingxing; Quan, Meifang; Sun, Yunjun; Yu, Ziquan; Hu, Shengbiao; Xia, Liqiu

2015-01-01

Bacillus thuringiensis is a widely used biopesticide that produced various insecticidal active substances during its life cycle. Separation and purification of numerous insecticide active substances have been difficult because of the relatively short half-life of such substances. On the other hand, substances can be synthetized at different times during development, so samples at different stages have to be studied, further complicating the analysis. A dual genomic and proteomic approach would enhance our ability to identify such substances, and particularily using mass spectrometry-based proteomic methods. The comparative analysis for genomic and proteomic data have showed that not all of the products deduced from the annotated genome could be identified among the proteomic data. For instance, genome annotation results showed that 39 coding sequences in the whole genome were related to insect pathogenicity, including five cry genes. However, Cry2Ab, Cry1Ia, Cytotoxin K, Bacteriocin, Exoenzyme C3 and Alveolysin could not be detected in the proteomic data obtained. The sporulation-related proteins were also compared analysis, results showed that the great majority sporulation-related proteins can be detected by mass spectrometry. This analysis revealed Spo0A~P, SigF, SigE(+), SigK(+) and SigG(+), all known to play an important role in the process of spore formation regulatory network, also were displayed in the proteomic data. Through the comparison of the two data sets, it was possible to infer that some genes were silenced or were expressed at very low levels. For instance, found that cry2Ab seems to lack a functional promoter while cry1Ia may not be expressed due to the presence of transposons. With this comparative study a relatively complete database can be constructed and used to transform hereditary material, thereby prompting the high expression of toxic proteins. A theoretical basis is provided for constructing highly virulent engineered bacteria and for promoting the application of proteogenomics in the life sciences.

Wavelength-modulated photocapacitance spectroscopy

NASA Technical Reports Server (NTRS)

Kamieniecki, E.; Lagowski, J.; Gatos, H. C.

1980-01-01

Derivative deep-level spectroscopy was achieved with wavelength-modulated photocapacitance employing MOS structures and Schottky barriers. The energy position and photoionization characteristics of deep levels of melt-grown GaAs and the Cr level in high-resistivity GaAs were determined. The advantages of this method over existing methods for deep-level spectroscopy are discussed.

A novel bipolar phosphorescent host for highly efficient deep-red OLEDs at a wide luminance range of 1000-10 000 cd m(-2).

PubMed

Feng, Yansong; Li, Ping; Zhuang, Xuming; Ye, Kaiqi; Peng, Tai; Liu, Yu; Wang, Yue

2015-08-14

A novel phosphorescent host FPYPCA possessing the bipolar charge transporting ability realizes the most efficient deep-red PhOLED, which maintains very high-level EQEs of >23% at rather a high and wide luminance range of 1000-10 000 cd m(-2).

DeepBase: annotation and discovery of microRNAs and other noncoding RNAs from deep-sequencing data.

PubMed

Yang, Jian-Hua; Qu, Liang-Hu

2012-01-01

Recent advances in high-throughput deep-sequencing technology have produced large numbers of short and long RNA sequences and enabled the detection and profiling of known and novel microRNAs (miRNAs) and other noncoding RNAs (ncRNAs) at unprecedented sensitivity and depth. In this chapter, we describe the use of deepBase, a database that we have developed to integrate all public deep-sequencing data and to facilitate the comprehensive annotation and discovery of miRNAs and other ncRNAs from these data. deepBase provides an integrative, interactive, and versatile web graphical interface to evaluate miRBase-annotated miRNA genes and other known ncRNAs, explores the expression patterns of miRNAs and other ncRNAs, and discovers novel miRNAs and other ncRNAs from deep-sequencing data. deepBase also provides a deepView genome browser to comparatively analyze these data at multiple levels. deepBase is available at http://deepbase.sysu.edu.cn/.

Distributed deep learning networks among institutions for medical imaging.

PubMed

Chang, Ken; Balachandar, Niranjan; Lam, Carson; Yi, Darvin; Brown, James; Beers, Andrew; Rosen, Bruce; Rubin, Daniel L; Kalpathy-Cramer, Jayashree

2018-03-29

Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.

Comparative histometric analysis of the effects of high-intensity focused ultrasound and radiofrequency on skin.

PubMed

Suh, Dong Hye; Choi, Jeong Hwee; Lee, Sang Jun; Jeong, Ki-Heon; Song, Kye Yong; Shin, Min Kyung

2015-01-01

High-intensity focused ultrasound (HIFU) and radiofrequency (RF) are used for non-invasive skin tightening. Neocollagenesis and neoelastogenesis have been reported to have a mechanism of controlled thermal injury. To compare neocollagenesis and neoelastogenesis in each layer of the dermis after each session of HIFU and monopolar RF. We analyzed the area fraction of collagen and elastic fibers using the Masson's Trichrome and Victoria blue special stains, respectively, before and after 2 months of treatments. Histometric analyses were performed in each layer of the dermis, including the papillary dermis, and upper, mid, and deep reticular dermis. Monopolar RF led to neocollagenesis in the papillary dermis, and upper, mid, and deep reticular dermis, and neoelastogenesis in the papillary dermis, and upper and mid reticular dermis. HIFU led to neocollagenesis in the mid and deep reticular dermis and neoelastogenesis in the deep reticular dermis. Among these treatment methods, HIFU showed the highest level of neocollagenesis and neoelastogenesis in the deep reticular dermis. HIFU affects deep tissues and impacts focal regions. Monopolar RF also affects deep tissues, but impacts diffuse regions. We believe these data provide further insight into effective skin tightening.

Highly Efficient Deep Blue Organic Light-Emitting Diodes Based on Imidazole: Significantly Enhanced Performance by Effective Energy Transfer with Negligible Efficiency Roll-off.

PubMed

Shan, Tong; Liu, Yulong; Tang, Xiangyang; Bai, Qing; Gao, Yu; Gao, Zhao; Li, Jinyu; Deng, Jian; Yang, Bing; Lu, Ping; Ma, Yuguang

2016-10-26

Great efforts have been devoted to develop efficient deep blue organic light-emitting diodes (OLEDs) materials meeting the standards of European Broadcasting Union (EBU) standard with Commission International de L'Eclairage (CIE) coordinates of (0.15, 0.06) for flat-panel displays and solid-state lightings. However, high-performance deep blue OLEDs are still rare for applications. Herein, two efficient deep blue emitters, PIMNA and PyINA, are designed and synthesized by coupling naphthalene with phenanthreneimidazole and pyreneimidazole, respectively. The balanced ambipolar transporting natures of them are demonstrated by single-carrier devices. Their nondoped OLEDs show deep blue emissions with extremely small CIE y of 0.034 for PIMNA and 0.084 for PyINA, with negligible efficiency roll-off. To take advantage of high photoluminescence quantum efficiency of PIMNA and large fraction of singlet exciton formation of PyINA, doped devices are fabricated by dispersing PyINA into PIMNA. A significantly improved maximum external quantum efficiency (EQE) of 5.05% is obtained through very effective energy transfer with CIE coordinates of (0.156, 0.060), and the EQE remains 4.67% at 1000 cd m -2 , which is among the best of deep blue OLEDs reported matching stringent EBU standard well.

RD860 and RD860L Engines with Deep Thrust Throttling and a High Technology Readiness Level (TRL)

NASA Astrophysics Data System (ADS)

Prokopchuk, O. O.; Shul'ga, V. A.; Dibrivnyi, O. V.; Kukhta, A. S.

2018-04-01

To solve the problems of delivering payloads to Mars surface and returning them to the orbit, liquid rocket engines, operating on storable propellants with deep throttling possibility, are needed, besides having high energy-mass characteristics.

Low endemism, continued deep-shallow interchanges, and evidence for cosmopolitan distributions in free-living marine nematodes (order Enoplida)

PubMed Central

2010-01-01

Background Nematodes represent the most abundant benthic metazoa in one of the largest habitats on earth, the deep sea. Characterizing major patterns of biodiversity within this dominant group is a critical step towards understanding evolutionary patterns across this vast ecosystem. The present study has aimed to place deep-sea nematode species into a phylogenetic framework, investigate relationships between shallow water and deep-sea taxa, and elucidate phylogeographic patterns amongst the deep-sea fauna. Results Molecular data (18 S and 28 S rRNA) confirms a high diversity amongst deep-sea Enoplids. There is no evidence for endemic deep-sea lineages in Maximum Likelihood or Bayesian phylogenies, and Enoplids do not cluster according to depth or geographic location. Tree topologies suggest frequent interchanges between deep-sea and shallow water habitats, as well as a mixture of early radiations and more recently derived lineages amongst deep-sea taxa. This study also provides convincing evidence of cosmopolitan marine species, recovering a subset of Oncholaimid nematodes with identical gene sequences (18 S, 28 S and cox1) at trans-Atlantic sample sites. Conclusions The complex clade structures recovered within the Enoplida support a high global species richness for marine nematodes, with phylogeographic patterns suggesting the existence of closely related, globally distributed species complexes in the deep sea. True cosmopolitan species may additionally exist within this group, potentially driven by specific life history traits of Enoplids. Although this investigation aimed to intensively sample nematodes from the order Enoplida, specimens were only identified down to genus (at best) and our sampling regime focused on an infinitesimal small fraction of the deep-sea floor. Future nematode studies should incorporate an extended sample set covering a wide depth range (shelf, bathyal, and abyssal sites), utilize additional genetic loci (e.g. mtDNA) that are informative at the species level, and apply high-throughput sequencing methods to fully assay community diversity. Finally, further molecular studies are needed to determine whether phylogeographic patterns observed in Enoplids are common across other ubiquitous marine groups (e.g. Chromadorida, Monhysterida). PMID:21167065

Applications of Deep Learning in Biomedicine.

PubMed

Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

2016-05-02

Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

Is Multitask Deep Learning Practical for Pharma?

PubMed

Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

2017-08-28

Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.

Compact, High-Power, Fiber-Laser-Based Coherent Sources Tunable in the Mid-Infrared and THz Spectrum

DTIC Science & Technology

2015-02-20

conversion sources and optical parametric oscillators (OPOs) for the deep mid-infrared (mid-IR) spectral regions >5 μm. We have successfully developed... oscillators (OPOs) for the deep mid-infrared (mid-IR) spectral regions >5 µm. We have successfully developed tunable deep mid-IR systems in both...the advancement of nonlinear frequency conversion sources and optical parametric oscillators (OPOs) for the deep mid-infrared (mid- IR) spectral

Detecting atrial fibrillation by deep convolutional neural networks.

PubMed

Xia, Yong; Wulan, Naren; Wang, Kuanquan; Zhang, Henggui

2018-02-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks. Then, two different deep convolutional neural network models corresponding to STFT output and SWT output were developed. Our new method did not require detection of P or R peaks, nor feature designs for classification, in contrast to existing algorithms. Finally, the performances of the two models were evaluated and compared with those of existing algorithms. Our proposed method demonstrated favorable performances on ECG segments as short as 5 s. The deep convolutional neural network using input generated by STFT, presented a sensitivity of 98.34%, specificity of 98.24% and accuracy of 98.29%. For the deep convolutional neural network using input generated by SWT, a sensitivity of 98.79%, specificity of 97.87% and accuracy of 98.63% was achieved. The proposed method using deep convolutional neural networks shows high sensitivity, specificity and accuracy, and, therefore, is a valuable tool for AF detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Excellent deep-blue emitting materials based on anthracene derivatives for non-doped organic light-emitting diodes

NASA Astrophysics Data System (ADS)

Wang, Zhiqiang; Liu, Wei; Xu, Chen; Ji, Baoming; Zheng, Caijun; Zhang, Xiaohong

2016-08-01

Two deep-blue emitting materials 2-tert-butyl-9,10-bis(3,5-diphenylphenyl)anthracene (An-1) and 2-tert-butyl-9,10-bis(3,5-diphenylbiphenyl-4‧-yl)anthracene (An-2) were successfully synthesized by the Pd-catalyzed Suzuki coupling reaction. Both of these compounds have high thermal stabilities and show strong deep-blue emission as solid-state film as well as in n-hexane solution. Two non-doped electroluminescent devices employing An-1 and An-2 as emitting layers were fabricated by vacuum vapor deposition. These devices exhibited highly efficient and stable deep-blue emission with high color purity. The CIE coordinate and maximum EQE of An-1 based device are 4.2% and (0.16, 0.06), respectively. Device based on An-2 achieved a maximum EQE of 4.0% and a CIE coordinate of (0.16, 0.10).

A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.

PubMed

Pang, Shuchao; Yu, Zhezhou; Orgun, Mehmet A

2017-03-01

Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset. In this study, we propose a highly reliable and accurate end-to-end classifier for all kinds of biomedical images via deep learning and transfer learning. We first apply domain transferred deep convolutional neural network for building a deep model; and then develop an overall deep learning architecture based on the raw pixels of original biomedical images using supervised training. In our model, we do not need the manual design of the feature space, seek an effective feature vector classifier or segment specific detection object and image patches, which are the main technological difficulties in the adoption of traditional image classification methods. Moreover, we do not need to be concerned with whether there are large training sets of annotated biomedical images, affordable parallel computing resources featuring GPUs or long times to wait for training a perfect deep model, which are the main problems to train deep neural networks for biomedical image classification as observed in recent works. With the utilization of a simple data augmentation method and fast convergence speed, our algorithm can achieve the best accuracy rate and outstanding classification ability for biomedical images. We have evaluated our classifier on several well-known public biomedical datasets and compared it with several state-of-the-art approaches. We propose a robust automated end-to-end classifier for biomedical images based on a domain transferred deep convolutional neural network model that shows a highly reliable and accurate performance which has been confirmed on several public biomedical image datasets. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Southern Ocean Circulation: a High Resolution Examination of the Last Deglaciation from Deep-Sea Corals

NASA Astrophysics Data System (ADS)

Robinson, L. F.; Li, T.; Chen, T.; Burke, A.; Pegrum Haram, A.; Stewart, J.; Rae, J. W. B.; van de Flierdt, T.; Struve, T.; Wilson, D. J.

2017-12-01

Two decades ago it was first noted that the skeletal remains of deep-sea corals had the potential to provide absolutely dated archives of past ocean conditions. In the intervening twenty years this field has developed to the point where strategic collections and high throughput dating techniques now allow high resolution, well dated records of past deep sea behaviour to be produced. Likewise, efforts to improve understanding of biomineralisation and growth rates are leading to refinements in proxy tools useful for examining circulation, nutrient and carbon cycling, temperature and weathering processes. Deep-sea corals are particularly valuable archives in high latitude regions where radiocarbon-based age models are susceptible to large changes in surface reservoir ages. In this presentation we show new high resolution multiproxy records of the Southern Ocean (Drake Passage) made on U-Th dated corals spanning the last glacial cycle. With more than seventeen hundred reconnaissance ages, and around 200 precise isotope dilution U-Th ages, subtle changes in ocean behaviour can be identified during times of abrupt climate change. The geochemical signature of corals from the deepest sites, closest to modern day Lower Circumpolar Deep Waters, typically show a gradual shift from glacial to Holocene values during deglaciation, likely related to ventilation of the deep ocean. By contrast for the samples collected shallower in the water column (within sites currently bathed by Upper Circumpolar Deep Waters and Antarctic Intermediate and Mode Waters) the evidence points to a more complicated picture. Vertical zonation in the geochemical data suggests that periods of stratification are interspersed with mixing events within the upper 1500m of the water column. At the same time comparison to U-Th dated records from the low latitude Pacific and Atlantic points to an important role for the Southern Ocean in feeding the intermediate waters of both ocean basins throughout the deglaciation.

Gating mass cytometry data by deep learning.

PubMed

Li, Huamin; Shaham, Uri; Stanton, Kelly P; Yao, Yi; Montgomery, Ruth R; Kluger, Yuval

2017-11-01

Mass cytometry or CyTOF is an emerging technology for high-dimensional multiparameter single cell analysis that overcomes many limitations of fluorescence-based flow cytometry. New methods for analyzing CyTOF data attempt to improve automation, scalability, performance and interpretation of data generated in large studies. Assigning individual cells into discrete groups of cell types (gating) involves time-consuming sequential manual steps, untenable for larger studies. We introduce DeepCyTOF, a standardization approach for gating, based on deep learning techniques. DeepCyTOF requires labeled cells from only a single sample. It is based on domain adaptation principles and is a generalization of previous work that allows us to calibrate between a target distribution and a source distribution in an unsupervised manner. We show that DeepCyTOF is highly concordant (98%) with cell classification obtained by individual manual gating of each sample when applied to a collection of 16 biological replicates of primary immune blood cells, even when measured across several instruments. Further, DeepCyTOF achieves very high accuracy on the semi-automated gating challenge of the FlowCAP-I competition as well as two CyTOF datasets generated from primary immune blood cells: (i) 14 subjects with a history of infection with West Nile virus (WNV), (ii) 34 healthy subjects of different ages. We conclude that deep learning in general, and DeepCyTOF specifically, offers a powerful computational approach for semi-automated gating of CyTOF and flow cytometry data. Our codes and data are publicly available at https://github.com/KlugerLab/deepcytof.git. yuval.kluger@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Deep X-ray lithography for the fabrication of microstructures at ELSA

NASA Astrophysics Data System (ADS)

Pantenburg, F. J.; Mohr, J.

2001-07-01

Two beamlines at the Electron Stretcher Accelerator (ELSA) of Bonn University are dedicated for the production of microstructures by deep X-ray lithography with synchrotron radiation. They are equipped with state-of-the-art X-ray scanners, maintained and used by Forschungszentrum Karlsruhe. Polymer microstructure heights between 30 and 3000 μm are manufactured regularly for research and industrial projects. This requires different characteristic energies. Therefore, ELSA operates routinely at 1.6, 2.3 and 2.7 GeV, for high-resolution X-ray mask fabrication, deep and ultra-deep X-ray lithography, respectively. The experimental setup, as well as the structure quality of deep and ultra deep X-ray lithographic microstructures are described.

Technology Development for High Efficiency Optical Communications

NASA Technical Reports Server (NTRS)

Farr, William H.

2012-01-01

Deep space optical communications is a significantly more challenging operational domain than near Earth space optical communications, primarily due to effects resulting from the vastly increased range between transmitter and receiver. The NASA Game Changing Development Program Deep Space Optical Communications Project is developing four key technologies for the implementation of a high efficiency telecommunications system that will enable greater than 10X the data rate of a state-of-the-art deep space RF system (Ka-band) for similar transceiver mass and power burden on the spacecraft. These technologies are a low mass spacecraft disturbance isolation assembly, a flight qualified photon counting detector array, a high efficiency flight laser amplifier and a high efficiency photon counting detector array for the ground-based receiver.

High power laser perforating tools and systems

DOEpatents

Zediker, Mark S; Rinzler, Charles C; Faircloth, Brian O; Koblick, Yeshaya; Moxley, Joel F

2014-04-22

ystems devices and methods for the transmission of 1 kW or more of laser energy deep into the earth and for the suppression of associated nonlinear phenomena. Systems, devices and methods for the laser perforation of a borehole in the earth. These systems can deliver high power laser energy down a deep borehole, while maintaining the high power to perforate such boreholes.

Hawaii Energy and Environmental Technologies Initiative

DTIC Science & Technology

2005-06-01

include a hydrate synthesis system, benthic pressure chambers to simulate deep seafloor sediment, and specialized instrumentation for high pressure...the high probability that a sulfide/oxygen microbial fuel cell can generate electricity in deep ocean sediments, and that prolonged power generation may...hydrogen generation (using an electrolyser) and storage, and on-line high -resolution gas analysis. In addition to installation and commissioning of

Compendium of Single Event Effects Test Results for Commercial Off-The-Shelf and Standard Electronics for Low Earth Orbit and Deep Space Applications

NASA Technical Reports Server (NTRS)

Reddell, Brandon D.; Bailey, Charles R.; Nguyen, Kyson V.; O'Neill, Patrick M.; Wheeler, Scott; Gaza, Razvan; Cooper, Jaime; Kalb, Theodore; Patel, Chirag; Beach, Elden R.;

Compendium of Single Event Effects (SEE) Test Results for COTS and Standard Electronics for Low Earth Orbit and Deep Space Applications

NASA Technical Reports Server (NTRS)

Reddell, Brandon; Bailey, Chuck; Nguyen, Kyson; O'Neill, Patrick; Gaza, Razvan; Patel, Chirag; Cooper, Jaime; Kalb, Theodore

2017-01-01

We present the results of SEE testing with high energy protons and with low and high energy heavy ions. This paper summarizes test results for components considered for Low Earth Orbit and Deep Space applications.

BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

PubMed

Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

2018-04-11

The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes by using deep learning on high-dimensional and small-scale biology data.

Do deep convolutional neural networks really need to be deep when applied for remote scene classification?

NASA Astrophysics Data System (ADS)

Luo, Chang; Wang, Jie; Feng, Gang; Xu, Suhui; Wang, Shiqiang

2017-10-01

Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, for remote scene classification, there are not sufficient images to train a very deep CNN from scratch. From two viewpoints of generalization power, we propose two promising kinds of deep CNNs for remote scenes and try to find whether deep CNNs need to be deep for remote scene classification. First, we transfer successful pretrained deep CNNs to remote scenes based on the theory that depth of CNNs brings the generalization power by learning available hypothesis for finite data samples. Second, according to the opposite viewpoint that generalization power of deep CNNs comes from massive memorization and shallow CNNs with enough neural nodes have perfect finite sample expressivity, we design a lightweight deep CNN (LDCNN) for remote scene classification. With five well-known pretrained deep CNNs, experimental results on two independent remote-sensing datasets demonstrate that transferred deep CNNs can achieve state-of-the-art results in an unsupervised setting. However, because of its shallow architecture, LDCNN cannot obtain satisfactory performance, regardless of whether in an unsupervised, semisupervised, or supervised setting. CNNs really need depth to obtain general features for remote scenes. This paper also provides baseline for applying deep CNNs to other remote sensing tasks.

Recovery of community genomes to assess subsurface metabolic potential: exploiting the capacity of next generation sequencing-based metagenomics

NASA Astrophysics Data System (ADS)

Wrighton, K. C.; Thomas, B.; Miller, C. S.; Sharon, I.; Wilkins, M. J.; VerBerkmoes, N. C.; Handley, K. M.; Lipton, M. S.; Hettich, R. L.; Williams, K. H.; Long, P. E.; Banfield, J. F.

2011-12-01

With the goal of developing a deterministic understanding of the microbiological and geochemical processes controlling subsurface environments, groundwater bacterial communities were collected from the Rifle Integrated Field Research Challenge (IFRC) site. Biomass from three temporal acetate-stimulated groundwater samples were collected during a period of dominant Fe(III)-reduction, in a region of the aquifer that had previously received acetate amendment the year prior. Phylogenetic analysis revealed a diverse Bacterial community, notably devoid of Archaea with 249 taxa from 9 Bacterial phyla including the dominance of uncultured candidate divisions, BD1-5, OD1, and OP11. We have reconstructed 86 partial to near-complete genomes and have performed a detailed characterization of the underlying metabolic potential of the ecosystem. We assessed the natural variation and redundancy in multi-heme c-type cytochromes, sulfite reductases, and central carbon metabolic pathways. Deep genomic sampling indicated the community contained various metabolic pathways: sulfur oxidation coupled to microaerophilic conditions, nitrate reduction with both acetate and inorganic compounds as donors, carbon and nitrogen fixation, antibiotic warfare, and heavy-metal detoxification. Proteomic investigations using predicted proteins from metagenomics corroborated that acetate oxidation is coupled to reduction of oxygen, sulfur, nitrogen, and iron across the samples. Of particular interest was the detection of acetate oxidizing and sulfate reducing proteins from a Desulfotalea-like bacterium in all three time points, suggesting that aqueous sulfide produced by active sulfate-reducing bacteria could contribute to abiotic iron reduction during the dominant iron reduction phase. Additionally, proteogenomic analysis verified that a large portion of the community, including members of the uncultivated BD1-5, are obligate fermenters, characterized by the presence of hydrogen-evolving hydrogenases, the capacity to oxidize complex organic carbon, as well as lack of membrane bound electron transport chains and an incomplete citric acid cycle. We propose that these organisms grow cryptically on residual biomass from previous biostimulation experiments and thus demonstrate that resource utilization and turnover in the aquifer can be decoupled from existing acetate amendment and external terminal electron accepting processes. In addition to the first recovery of multiple genomes from these novel candidate divisions, our community genomic approach uncovered viral diversity not yet observed at the site, with the reconstruction of six phage genomes and the presence of CRISPR loci detected in bacterial genomes from diverse lineages. These findings have implications for predictive ecosystem modeling, highlighting the importance of integrating the response, adaptation, as well as biological and geochemical feedback mechanisms existing within complex subsurface communities to long term organic carbon amendment.

Impacts on the deep-sea ecosystem by a severe coastal storm.

PubMed

Sanchez-Vidal, Anna; Canals, Miquel; Calafat, Antoni M; Lastras, Galderic; Pedrosa-Pàmies, Rut; Menéndez, Melisa; Medina, Raúl; Company, Joan B; Hereu, Bernat; Romero, Javier; Alcoverro, Teresa

2012-01-01

Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26(th) of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem.

Impacts on the Deep-Sea Ecosystem by a Severe Coastal Storm

PubMed Central

Sanchez-Vidal, Anna; Canals, Miquel; Calafat, Antoni M.; Lastras, Galderic; Pedrosa-Pàmies, Rut; Menéndez, Melisa; Medina, Raúl; Company, Joan B.; Hereu, Bernat; Romero, Javier; Alcoverro, Teresa

2012-01-01

Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26th of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem. PMID:22295084

Diversity in deep-sea benthic macrofauna: the importance of local ecology, the larger scale, history and the Antarctic

NASA Astrophysics Data System (ADS)

Gage, John D.

2004-07-01

High diversity in macrobenthos in the deep sea still lacks satisfactory explanation, even if this richness may not be exceptional compared to that in coastal soft sediments. Explanations have assumed a highly ecologically interactive, saturated local community with co-existence controlled by either niche heterogeneity, or spatio-temporal heterogeneity embodying disturbance. All have failed to provide convincing support. Local/regional scale biodiversity relationships support the idea of local richness in macrobenthos being predominantly dependent on the larger, rather local scale. Local-scale ecological interactions seem unlikely to have overriding importance in co-existence of species in the deep sea, even for relatively abundant, 'core' species with wide distributions. Variety in observed larger-scale pattern and the strong inter-regional pattern, particularly in the poorly known southern hemisphere, seem to have a pluralistic causation. These include regional-scale barriers and extinctions (e.g., Arctic), and ongoing adaptive zone re-colonisation (e.g., Mediterranean), along with other historical constraints on speciation and migration of species caused by changes in ocean and ocean-basin geometry. At the global scale lack of knowledge of the Antarctic deep sea, for example, blocks coherent understanding of latitudinal species diversity gradients. We need to reconcile emerging understanding of large-scale historical variability in the deep-sea environment—with massive extinctions among microfossil indicators as recently as the Pliocene—to results from cladistic studies indicating ancient lineages, such as asellote isopods, that have evolved entirely within the deep sea. The degree to which the great age, diversity, and high degree of endemism in Antarctic shelf benthos might have enriched biodiversity in the adjacent deep seas basins remains unclear. Basin confluence with the Atlantic, Indian and Pacific Oceans may have encouraged northwards dispersion of species from and into the deep Antarctic basins so that any regional identity is superficial. Interpretation of the Antarctic deep sea as a diversity pump for global deep-sea biodiversity may simply reflect re-colonisation, via basin confluence, of northern hemisphere areas impoverished by the consequences of rapid environmental change during the Quaternary.

Usefulness of DWI in preoperative assessment of deep myometrial invasion in patients with endometrial carcinoma: a systematic review and meta-analysis

PubMed Central

2014-01-01

Background The objective of this study was to perform a systematic review and a meta-analysis in order to estimate the diagnostic accuracy of diffusion weighted imaging (DWI) in the preoperative assessment of deep myometrial invasion in patients with endometrial carcinoma. Methods Studies evaluating DWI for the detection of deep myometrial invasion in patients with endometrial carcinoma were systematically searched for in the MEDLINE, EMBASE, and Cochrane Library from January 1995 to January 2014. Methodologic quality was assessed by using the Quality Assessment of Diagnostic Accuracy Studies tool. Bivariate random-effects meta-analytic methods were used to obtain pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR) and receiver operating characteristic (ROC) curves. The study also evaluated the clinical utility of DWI in preoperative assessment of deep myometrial invasion. Results Seven studies enrolling a total of 320 individuals met the study inclusion criteria. The summary area under the ROC curve was 0.91. There was no evidence of publication bias (P = 0.90, bias coefficient analysis). Sensitivity and specificity of DWI for detection of deep myometrial invasion across all studies were 0.90 and 0.89, respectively. Positive and negative likelihood ratios with DWI were 8 and 0.11 respectively. In patients with high pre-test probabilities, DWI enabled confirmation of deep myometrial invasion; in patients with low pre-test probabilities, DWI enabled exclusion of deep myometrial invasion. The worst case scenario (pre-test probability, 50%) post-test probabilities were 89% and 10% for positive and negative DWI results, respectively. Conclusion DWI has high sensitivity and specificity for detecting deep myometrial invasion and more importantly can reliably rule out deep myometrial invasion. Therefore, it would be worthwhile to add a DWI sequence to the standard MRI protocols in preoperative evaluation of endometrial cancer in order to detect deep myometrial invasion, which along with other poor prognostic factors like age, tumor grade, and LVSI would be useful in stratifying high risk groups thereby helping in the tailoring of surgical approach in patient with low risk of endometrial carcinoma. PMID:25608571

Conservative management in ureteric hydronephrosis due to deep endometriosis: Could the levonorgestrel-intrauterine device be an option?

PubMed

Simón, Elisa; Tejerizo, Álvaro; Muñoz, José Luis; Álvarez, Carmen; Marqueta, Laura; Jiménez, Jesús S

2017-07-01

Endometriosis can affect up to 10% of women of reproductive age, in a wide range of clinical presentations that vary from mild to severe or deep endometriosis. Deep endometriosis can affect the urinary tract in 1-5% to 15-25% cases. Even though deep endometriosis' surgeries are usually complex with higher rate of complications, conservative management is not always considered as an option because of its high failure rates. This paper describes two cases of deep endometriosis with ureteric involvement (hydronephrosis) treated conservatively with a double-pigtail stent plus a Levonorgestrel intrauterine device, after conservative surgery, who remained symptom free with no evidence of recurrence at 3 years follow-up, avoiding radical high-risk surgery. Impact statement Several treatments have been described for endometriosis. From a symptomatic perspective, conservative medical management has been proposed with a variable response. Concerning deep endometriosis (affecting the urinary or digestive tract), the definitive treatment has always been thought to be radical surgery. However, this can lead to several complications. To illustrate a possible more conservative approach this paper describes two cases of deep infiltrating endometriosis affecting the ureter, treated conservatively with a temporary pigtail ureter stent plus a Levonorgestrel intrauterine device. The management demonstrates that, in a selected population, conservative treatment solves the urinary disease avoiding the surgical complications and, what is more, improving patients' symptoms in a permanent way. Further prospective studies are needed to confirm whether the introduction of this management in clinical practice would reduce the need for surgery thereby, avoiding high-risk surgery and improving the success rate of conservative management.

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

PubMed

Zhu, Yanan; Ouyang, Qi; Mao, Youdong

2017-07-21

Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images. Particle extraction from experimental micrographs thus can be laborious and presents a major practical bottleneck in cryo-EM structural determination. Existing computational methods for particle picking often use low-resolution templates for particle matching, making them susceptible to reference-dependent bias. It is critical to develop a highly efficient template-free method for the automatic recognition of particle images from cryo-EM micrographs. We developed a deep learning-based algorithmic framework, DeepEM, for single-particle recognition from noisy cryo-EM micrographs, enabling automated particle picking, selection and verification in an integrated fashion. The kernel of DeepEM is built upon a convolutional neural network (CNN) composed of eight layers, which can be recursively trained to be highly "knowledgeable". Our approach exhibits an improved performance and accuracy when tested on the standard KLH dataset. Application of DeepEM to several challenging experimental cryo-EM datasets demonstrated its ability to avoid the selection of un-wanted particles and non-particles even when true particles contain fewer features. The DeepEM methodology, derived from a deep CNN, allows automated particle extraction from raw cryo-EM micrographs in the absence of a template. It demonstrates an improved performance, objectivity and accuracy. Application of this novel method is expected to free the labor involved in single-particle verification, significantly improving the efficiency of cryo-EM data processing.

Double seismic zone for deep earthquakes in the izu-bonin subduction zone.

PubMed

Iidaka, T; Furukawa, Y

1994-02-25

A double seismic zone for deep earthquakes was found in the Izu-Bonin region. An analysis of SP-converted phases confirms that the deep seismic zone consists of two layers separated by approximately 20 kilometers. Numerical modeling of the thermal structure implies that the hypocenters are located along isotherms of 500 degrees to 550 degrees C, which is consistent with the hypothesis that deep earthquakes result from the phase transition of metastable olivine to a high-pressure phase in the subducting slab.

Hello World Deep Learning in Medical Imaging.

PubMed

Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

2018-05-03

There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

Deep Operations in Airland Battle Doctrine: The Employment of U.S. Ground Forces in Deep Operational Maneuver

DTIC Science & Technology

1989-05-16

development and is manifested today in the Operational .Maneuver Group. As the name implies, the Soviet emphiasis is at the operational level. The mission of...high-intensity war! 10 answer this question I (1) analyze Soviet deep operations theory to determine how their concept developed and what they expect...USA, 32 pageF., In Soviet Army doctrine, deep operations has been a long time in development and is manifested today in the Operational Maneuver Group

Deep learning applications in ophthalmology.

PubMed

Rahimy, Ehsan

2018-05-01

To describe the emerging applications of deep learning in ophthalmology. Recent studies have shown that various deep learning models are capable of detecting and diagnosing various diseases afflicting the posterior segment of the eye with high accuracy. Most of the initial studies have centered around detection of referable diabetic retinopathy, age-related macular degeneration, and glaucoma. Deep learning has shown promising results in automated image analysis of fundus photographs and optical coherence tomography images. Additional testing and research is required to clinically validate this technology.

Strategies for Effective Faculty Involvement in Online Activities Aimed at Promoting Critical Thinking and Deep Learning

ERIC Educational Resources Information Center

Abdul Razzak, Nina

2016-01-01

Highly-traditional education systems that mainly offer what is known as "direct instruction" usually result in graduates with a surface approach to learning rather than a deep one. What is meant by deep-learning is learning that involves critical analysis, the linking of ideas and concepts, creative problem solving, and application…

High Speed Trimaran (HST) Seatrain Experiments, Model 5714

DTIC Science & Technology

2013-12-01

Marine Highway 1 Historical Seatrains 1 Objectives 2 Hull &: Model Description 4 Data Acquisition and Instrumentation 7 Carriage II - Deep ...Operational Demonstration Measurement System 10 Experimental Procedures 10 Carriage II - Deep Water Basin Test 10 Calm Water Resistance 11... Deep Water Basin Analysis 17 Calm Water Resistance 17 Longitudinal Flow Through The Propeller Plane 18 Body Forces & Moments 18

Dual-wavelength photo-Hall effect spectroscopy of deep levels in high resistive CdZnTe with negative differential photoconductivity

NASA Astrophysics Data System (ADS)

Musiienko, A.; Grill, R.; Moravec, P.; Korcsmáros, G.; Rejhon, M.; Pekárek, J.; Elhadidy, H.; Šedivý, L.; Vasylchenko, I.

2018-04-01

Photo-Hall effect spectroscopy was used in the study of deep levels in high resistive CdZnTe. The monochromator excitation in the photon energy range 0.65-1.77 eV was complemented by a laser diode high-intensity excitation at selected photon energies. A single sample characterized by multiple unusual features like negative differential photoconductivity and anomalous depression of electron mobility was chosen for the detailed study involving measurements at both the steady and dynamic regimes. We revealed that the Hall mobility and photoconductivity can be both enhanced and suppressed by an additional illumination at certain photon energies. The anomalous mobility decrease was explained by an excitation of the inhomogeneously distributed deep level at the energy Ev + 1.0 eV, thus enhancing potential non-uniformities. The appearance of negative differential photoconductivity was interpreted by an intensified electron occupancy of that level by a direct valence band-to-level excitation. Modified Shockley-Read-Hall theory was used for fitting experimental results by a model comprising five deep levels. Properties of the deep levels and their impact on the device performance were deduced.

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

PubMed

van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

The Deep Space Gateway Lightning Mapper (DLM) — Monitoring Global Change and Thunderstorm Processes through Observations of Earth's High-Latitude Lightning from Cis-Lunar Orbit

NASA Astrophysics Data System (ADS)

Lang, T. J.; Blakeslee, R. J.; Cecil, D. J.; Christian, H. J.; Gatlin, P. N.; Goodman, S. J.; Koshak, W. J.; Petersen, W. A.; Quick, M.; Schultz, C. J.; Tatum, P. F.

2018-02-01

We propose the Deep Space Gateway Lightning Mapper (DLM) instrument. The primary goal of the DLM is to optically monitor Earth's high-latitude (50° and poleward) total lightning not observed by current and planned spaceborne lightning mappers.

Natural Variation in Brachypodium disctachyon: Deep Sequencing of Highly Diverse Natural Accessions (2013 DOE JGI Genomics of Energy and Environment 8th Annual User Meeting)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gordon, Sean

2013-03-01

Sean Gordon of the USDA on Natural variation in Brachypodium disctachyon: Deep Sequencing of Highly Diverse Natural Accessions at the 8th Annual Genomics of Energy Environment Meeting on March 27, 2013 in Walnut Creek, CA.

NASA's 3D Flight Computer for Space Applications

NASA Technical Reports Server (NTRS)

Alkalai, Leon

2000-01-01

The New Millennium Program (NMP) Integrated Product Development Team (IPDT) for Microelectronics Systems was planning to validate a newly developed 3D Flight Computer system on its first deep-space flight, DS1, launched in October 1998. This computer, developed in the 1995-97 time frame, contains many new computer technologies previously never used in deep-space systems. They include: advanced 3D packaging architecture for future low-mass and low-volume avionics systems; high-density 3D packaged chip-stacks for both volatile and non-volatile mass memory: 400 Mbytes of local DRAM memory, and 128 Mbytes of Flash memory; high-bandwidth Peripheral Component Interface (Per) local-bus with a bridge to VME; high-bandwidth (20 Mbps) fiber-optic serial bus; and other attributes, such as standard support for Design for Testability (DFT). Even though this computer system did not complete on time for delivery to the DS1 project, it was an important development along a technology roadmap towards highly integrated and highly miniaturized avionics systems for deep-space applications. This continued technology development is now being performed by NASA's Deep Space System Development Program (also known as X2000) and within JPL's Center for Integrated Space Microsystems (CISM).

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Potok, Thomas E; Schuman, Catherine D; Young, Steven R

Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are intractable to train on current systems. Building the topologies of the deep learning network requires hand tuning, and implementing the network in hardware is expensive in both cost and power. In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determinemore » network topology, and neuromorphic computing for a low-power hardware implementation. Due to input size limitations of current quantum computers we use the MNIST dataset for our evaluation. The results show the possibility of using the three architectures in tandem to explore complex deep learning networks that are untrainable using a von Neumann architecture. We show that a quantum computer can find high quality values of intra-layer connections and weights, while yielding a tractable time result as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware. This represents a new capability that is not feasible with current von Neumann architecture. It potentially enables the ability to solve very complicated problems unsolvable with current computing technologies.« less

Deep Charging Evaluation of Satellite Power and Communication System Components

NASA Technical Reports Server (NTRS)

Schneider, T. A.; Vaughn, J. A.; Chu, B.; Wong, F.; Gardiner, G.; Wright, K. H.; Phillips, B.

2016-01-01

Deep charging, in contrast to surface charging, focuses on electron penetration deep into insulating materials applied over conductors. A classic example of this scenario is an insulated wire. Deep charging can pose a threat to material integrity, and to sensitive electronics, when it gives rise to an electrostatic discharge or arc. With the advent of Electric Orbit Raising, which requires spiraling through Earth's radiation belts, satellites are subjected to high energy electron environments which they normally would not encounter. Beyond Earth orbit, missions to Jupiter and Saturn face deep charging concerns due to the high energy radiation environments. While predictions can be made about charging in insulating materials, it is difficult to extend those predictions to complicated geometries, such as the case of an insulating coating around a small wire, or a non-uniform silicone grouting on a bus bar. Therefore, to conclusively determine the susceptibility of a system to arcs from deep charging, experimental investigations must be carried out. This paper will describe the evaluation carried out by NASA's Marshall Space Flight Center on subscale flight-like samples developed by Space Systems/Loral, LLC. Specifically, deep charging evaluations of solar array wire coupons, a photovoltaic cell coupon, and a coaxial microwave transmission cable, will be discussed. The results of each evaluation will be benchmarked against control sample tests, as well as typical power system levels, to show no significant deep charging threat existed for this set of samples under the conditions tested.

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE): Conceptual Design Report. Volume 1: The LBNF and DUNE Projects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acciarri, R.

2016-01-22

This document presents the Conceptual Design Report (CDR) put forward by an international neutrino community to pursue the Deep Underground Neutrino Experiment at the Long-Baseline Neutrino Facility (LBNF/DUNE), a groundbreaking science experiment for long-baseline neutrino oscillation studies and for neutrino astrophysics and nucleon decay searches. The DUNE far detector will be a very large modular liquid argon time-projection chamber (LArTPC) located deep underground, coupled to the LBNF multi-megawatt wide-band neutrino beam. DUNE will also have a high-resolution and high-precision near detector.

Crop response to deep tillage - a meta-analysis

NASA Astrophysics Data System (ADS)

Schneider, Florian; Don, Axel; Hennings, Inga; Schmittmann, Oliver; Seidel, Sabine J.

2017-04-01

Subsoil, i.e. the soil layer below the topsoil, stores tremendous stocks of nutrients and can keep water even under drought conditions. Deep tillage may be a method to enhance the plant-availability of subsoil resources. However, in field trials, deep tillage effects on crop yields were inconsistent. Therefore, we conducted a meta-analysis of crop yield response to subsoiling, deep ploughing and deep mixing of soil profiles. Our search resulted in 1530 yield comparisons following deep and conventional control tillage on 67 experimental cropping sites. The vast majority of the data derived from temperate latitudes, from trials conducted in the USA (679 observations) and Germany (630 observations). On average, crop yield response to deep tillage was slightly positive (6% increase). However, individual deep tillage effects were highly scattered including about 40% yield depressions after deep tillage. Deep tillage on soils with root restrictive layers increased crop yields about 20%, while soils containing >70% silt increased the risk of yield depressions following deep tillage. Generally, deep tillage effects increased with drought intensity indicating deep tillage as climate adaptation measure at certain sites. Our results suggest that deep tillage can facilitate the plant-availability of subsoil nutrients, which increases crop yields if (i) nutrients in the topsoil are growth limiting, and (ii) deep tillage does not come at the cost of impairing topsoil fertility. On sites with root restrictive soil layers, deep tillage can be an effective measure to mitigate drought stress and improve the resilience of crops. However, deep tillage should only be performed on soils with a stable structure, i.e. <70% silt content. We will discuss the contribution of deep tillage options to enhance the sustainability of agricultural production by facilitating the uptake of nutrients and water from the subsoil.

78 FR 36496 - International Fisheries; Western and Central Pacific Fisheries for Highly Migratory Species...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-18

... number of vessels that engaged in both deep-setting and shallow-setting ranged from 17 to 35. The number... shallow-set and deep-set longlining. Based on an average of 127 active vessels during that period, the... analyses prepared for the 2009 rule are: (3) Shallow-set longline fishing for swordfish (for deep-setting...

Distribution of Quercus agrifolia mycorrhizae deep within weathered bedrock: a potential mechanism for transport of stored water

Treesearch

M. Bornyasz; R. Graham; M. Allen

2002-01-01

In southwestern California, Quercus agrifolia distribution closely matches regions of granitic regolith. High annual evapotranspiration demand and inherent shallow soil conditions lead to a dependence on a deep rooting system and an ability to access water from deep within the regolith. Most of the plant available water in weathered granitic rock is...

Diamond formation in the deep lower mantle: a high-pressure reaction of MgCO3 and SiO2

PubMed Central

Maeda, Fumiya; Ohtani, Eiji; Kamada, Seiji; Sakamaki, Tatsuya; Hirao, Naohisa; Ohishi, Yasuo

2017-01-01

Diamond is an evidence for carbon existing in the deep Earth. Some diamonds are considered to have originated at various depth ranges from the mantle transition zone to the lower mantle. These diamonds are expected to carry significant information about the deep Earth. Here, we determined the phase relations in the MgCO3-SiO2 system up to 152 GPa and 3,100 K using a double sided laser-heated diamond anvil cell combined with in situ synchrotron X-ray diffraction. MgCO3 transforms from magnesite to the high-pressure polymorph of MgCO3, phase II, above 80 GPa. A reaction between MgCO3 phase II and SiO2 (CaCl2-type SiO2 or seifertite) to form diamond and MgSiO3 (bridgmanite or post-perovsktite) was identified in the deep lower mantle conditions. These observations suggested that the reaction of the MgCO3 phase II with SiO2 causes formation of super-deep diamond in cold slabs descending into the deep lower mantle. PMID:28084421

Viral infections as controlling factors for the deep biosphere? (Invited)

NASA Astrophysics Data System (ADS)

Engelen, B.; Engelhardt, T.; Sahlberg, M.; Cypionka, H.

2009-12-01

The marine deep biosphere represents the largest biotope on Earth. Throughout the last years, we have obtained interesting insights into its microbial community composition. However, one component that was completely overlooked so far is the viral inventory of deep-subsurface sediments. While viral infections were identified to have a major impact on the benthic microflora of deep-sea surface sediments (Danavaro et al. 2008), no studies were performed on deep-biosphere samples, so far. As grazers probably play only a minor role in anoxic and highly compressed deep sediments, viruses might be the main “predators” for indigenous microorganisms. Furthermore, the release of cell components, called “the viral shunt”, could have a major impact on the deep biosphere in providing labile organic compounds to non-infected microorganisms in these generally nutrient depleted sediments. However, direct counting of viruses in sediments is highly challenging due to the small size of viruses and the high background of small particles. Even molecular surveys using “universal” PCR primers that target phage-specific genes fail due to the vast phage diversity. One solution for this problem is the lysogenic viral life cycle as many bacteriophages integrate their DNA into the host genome. It is estimated that up to 70% of cultivated bacteria contain prophages within their genome. Therefore, culture collections (Batzke et al. 2007) represent an archive of the viral composition within the respective habitat. These prophages can be induced to become free phage particles in stimulation experiments in which the host cells are set under certain stress situations such as a treatment with UV exposure or DNA-damaging antibiotics. The study of the viral component within the deep biosphere offers to answer the following questions: To which extent are deep-biosphere populations controlled by viral infections? What is the inter- and intra-specific diversity and the host-specific viral biogeography? Can viral infections tell us something about the physiological state of indigenous microorganisms? Finally, we will obtain estimates for the viral shunt as an important factor for sustaining the deep biosphere. References: Batzke A, Engelen B, Sass H, Cypionka H (2007) Phylogenetic and physiological diversity of cultured deep-biosphere bacteria from Equatorial Pacific Ocean and Peru Margin sediments. Geomicrobiology J 24:261-273 Danovaro R, Dell'Anno A, Corinaldesi C, Magagnini M, Noble R, Tamburini C, Weinbauer M (2008) Major viral impact on the functioning of benthic deep-sea ecosystems. Nature 454: 1084-U1027.

Decadal trends in deep ocean salinity and regional effects on steric sea level

NASA Astrophysics Data System (ADS)

Purkey, S. G.; Llovel, W.

2017-12-01

We present deep (below 2000 m) and abyssal (below 4000 m) global ocean salinity trends from the 1990s through the 2010s and assess the role of deep salinity in local and global sea level budgets. Deep salinity trends are assessed using all deep basins with available full-depth, high-quality hydrographic section data that have been occupied two or more times since the 1980s through either the World Ocean Circulation Experiment (WOCE) Hydrographic Program or the Global Ship-Based Hydrographic Investigations Program (GO-SHIP). All salinity data is calibrated to standard seawater and any intercruise offsets applied. While the global mean deep halosteric contribution to sea level rise is close to zero (-0.017 +/- 0.023 mm/yr below 4000 m), there is a large regional variability with the southern deep basins becoming fresher and northern deep basins becoming more saline. This meridional gradient in the deep salinity trend reflects different mechanisms driving the deep salinity variability. The deep Southern Ocean is freshening owing to a recent increased flux of freshwater to the deep ocean. Outside of the Southern Ocean, the deep salinity and temperature changes are tied to isopycnal heave associated with a falling of deep isopycnals in recent decades. Therefore, regions of the ocean with a deep salinity minimum are experiencing both a halosteric contraction with a thermosteric expansion. While the thermosteric expansion is larger in most cases, in some regions the halosteric compensates for as much as 50% of the deep thermal expansion, making a significant contribution to local sea level rise budgets.

First biological measurements of deep-sea corals from the Red Sea

PubMed Central

Roder, C.; Berumen, M. L.; Bouwmeester, J.; Papathanassiou, E.; Al-Suwailem, A.; Voolstra, C. R.

2013-01-01

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with ‘deep-sea’ and ‘cold-water’ corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited. PMID:24091830

First biological measurements of deep-sea corals from the Red Sea.

PubMed

Roder, C; Berumen, M L; Bouwmeester, J; Papathanassiou, E; Al-Suwailem, A; Voolstra, C R

2013-10-03

It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with 'deep-sea' and 'cold-water' corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited.

Text feature extraction based on deep learning: a review.

PubMed

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

NASA Astrophysics Data System (ADS)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Improved process robustness by using closed loop control in deep drawing applications

NASA Astrophysics Data System (ADS)

Barthau, M.; Liewald, M.; Christian, Held

2017-09-01

The production of irregular shaped deep-drawing parts with high quality requirements, which are common in today’s automotive production, permanently challenges production processes. High requirements on lightweight construction of passenger car bodies following European regulations until 2020 have been massively increasing the use of high strength steels substantially for years and are also leading to bigger challenges in sheet metal part production. Of course, the more and more complex shapes of today’s car body shells also intensify the issue due to modern and future design criteria. The metal forming technology tries to meet these challenges by developing a highly sophisticated layout of deep drawing dies that consider part quality requirements, process robustness and controlled material flow during the deep or stretch drawing process phase. A new method for controlling material flow using a closed loop system was developed at the IFU Stuttgart. In contrast to previous approaches, this new method allows a control intervention during the deep-drawing stroke. The blank holder force around the outline of the drawn part is used as control variable. The closed loop is designed as trajectory follow up with feed forward control. The used command variable is the part-wall stress that is measured with a piezo-electric measuring pin. In this paper the used control loop will be described in detail. The experimental tool that was built for testing the new control approach is explained here with its features. A method for gaining the follow up trajectories from simulation will also be presented. Furthermore, experimental results considering the robustness of the deep drawing process and the gain in process performance with developed control loop will be shown. Finally, a new procedure for the industrial application of the new control method of deep drawing will be presented by using a new kind of active element to influence the local blank holder pressure onto part flange.

Deep catalytic oxidative desulfurization (ODS) of dibenzothiophene (DBT) with oxalate-based deep eutectic solvents (DESs).

PubMed

Lü, Hongying; Li, Pengcheng; Deng, Changliang; Ren, Wanzhong; Wang, Shunan; Liu, Pan; Zhang, Han

2015-07-07

An oxalate-based DES with a tetrabutyl ammonium chloride and oxalate acid molar ratio of 1/2 (TBO1 : 2) exhibited high activity in oxidative desulfurization (ODS) of dibenzothiophene (DBT) under mild reaction conditions. It is potentially a promising and highly environmentally friendly approach for desulfurization of fuels.

Insights into deep-sea adaptations and host-symbiont interactions: A comparative transcriptome study on Bathymodiolus mussels and their coastal relatives.

PubMed

Zheng, Ping; Wang, Minxiao; Li, Chaolun; Sun, Xiaoqing; Wang, Xiaocheng; Sun, Yan; Sun, Song

2017-10-01

Mussels (Bivalve: Mytilidae) have adapted to various habitats, from fresh water to the deep sea. To understand their adaptive characteristics in different habitats, particularly in the bathymodiolin mussels in deep-sea chemosynthetic ecosystems, we conducted a comparative transcriptomic analysis between deep-sea bathymodiolin mussels and their shallow-water relatives. A number of gene families related to stress responses were shared across all mussels, without specific or significantly expanded families in deep-sea species, indicating that all mussels are capable of adapting to diverse harsh environments, but that different members of the same gene family may be preferentially utilized by different species. One of the most extraordinary trait of bathymodiolin mussels is their endosymbiosis. Lineage-specific and positively selected TLRs and highly expressed C1QDC proteins were identified in the gills of the bathymodiolins, suggesting their possible functions in symbiont recognition. However, pattern recognition receptors of the bathymodiolins were globally reduced, facilitating the invasion and maintenance of the symbionts obtained by either endocytosis or phagocytosis. Additionally, various transporters were positively selected or more highly expressed in the deep-sea mussels, indicating a means by which necessary materials could be provided for the symbionts. Key genes supporting lysosomal activity were also positively selected or more highly expressed in the deep-sea mussels, suggesting that nutrition fixed by the symbionts can be absorbed in a "farming" way wherein the symbionts are digested by lysosomes. Regulation of key physiological processes including lysosome activity, apoptosis and immune reactions is needed to maintain a stable host-symbiont relationship, but the mechanisms are still unclear. © 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Comparative metagenomics of bathypelagic plankton and bottom sediment from the Sea of Marmara

PubMed Central

Quaiser, Achim; Zivanovic, Yvan; Moreira, David; López-García, Purificación

2011-01-01

To extend comparative metagenomic analyses of the deep-sea, we produced metagenomic data by direct 454 pyrosequencing from bathypelagic plankton (1000 m depth) and bottom sediment of the Sea of Marmara, the gateway between the Eastern Mediterranean and the Black Seas. Data from small subunit ribosomal RNA (SSU rRNA) gene libraries and direct pyrosequencing of the same samples indicated that Gamma- and Alpha-proteobacteria, followed by Bacteroidetes, dominated the bacterial fraction in Marmara deep-sea plankton, whereas Planctomycetes, Delta- and Gamma-proteobacteria were the most abundant groups in high bacterial-diversity sediment. Group I Crenarchaeota/Thaumarchaeota dominated the archaeal plankton fraction, although group II and III Euryarchaeota were also present. Eukaryotes were highly diverse in SSU rRNA gene libraries, with group I (Duboscquellida) and II (Syndiniales) alveolates and Radiozoa dominating plankton, and Opisthokonta and Alveolates, sediment. However, eukaryotic sequences were scarce in pyrosequence data. Archaeal amo genes were abundant in plankton, suggesting that Marmara planktonic Thaumarchaeota are ammonia oxidizers. Genes involved in sulfate reduction, carbon monoxide oxidation, anammox and sulfatases were over-represented in sediment. Genome recruitment analyses showed that Alteromonas macleodii ‘surface ecotype', Pelagibacter ubique and Nitrosopumilus maritimus were highly represented in 1000 m-deep plankton. A comparative analysis of Marmara metagenomes with ALOHA deep-sea and surface plankton, whale carcasses, Peru subsurface sediment and soil metagenomes clustered deep-sea Marmara plankton with deep-ALOHA plankton and whale carcasses, likely because of the suboxic conditions in the deep Marmara water column. The Marmara sediment clustered with the soil metagenome, highlighting the common ecological role of both types of microbial communities in the degradation of organic matter and the completion of biogeochemical cycles. PMID:20668488

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rigali, Mark J.; Pye, Steven; Hardin, Ernest

This study considers the feasibility of large diameter deep boreholes for waste disposal. The conceptual approach considers examples of deep large diameter boreholes that have been successfully drilled, and also other deep borehole designs proposed in the literature. The objective for large diameter boreholes would be disposal of waste packages with diameters of 22 to 29 inches, which could enable disposal of waste forms such as existing vitrified high level waste. A large-diameter deep borehole design option would also be amenable to other waste forms including calcine waste, treated Na-bonded and Na-bearing waste, and Cs and Sr capsules.

Geocoronal Imaging from the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Waldrop, L.; Immel, T.; Clarke, J.; Fillingim, M.; Rider, K.; Qin, J.; Bhattacharyya, D.; Doe, R.

2018-02-01

UV imaging of geocoronal emission at high spatial and temporal resolution from deep space would provide crucial new constraints on global exospheric structure and dynamics, significantly advancing models of space weather and atmospheric escape.

Deep Boreholes Seals Subjected to High P, T conditions – Preliminary Experimental Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caporuscio, Florie Andre; Norskog, Katherine Elizabeth; Maner, James Lavada

The objective of this planned experimental work is to evaluate physio-chemical processes for ‘seal’ components and materials relevant to deep borehole disposal. These evaluations will encompass multi-laboratory efforts for the development of seals concepts and application of Thermal-Mechanical-Chemical (TMC) modeling work to assess barrier material interactions with subsurface fluids, their stability at high temperatures, and the implications of these processes to the evaluation of thermal limits. Deep borehole experimental work will constrain the Pressure, Temperature (P, T) conditions which “seal” material will experience in deep borehole crystalline rock repositories. The rocks of interest to this study include the silicic (graniticmore » gneiss) end members. The experiments will systematically add components to capture discrete changes in both water and EBS component chemistries.« less

The Effects of Temperature and Hydrostatic Pressure on Metal Toxicity: Insights into Toxicity in the Deep Sea.

PubMed

Brown, Alastair; Thatje, Sven; Hauton, Chris

2017-09-05

Mineral prospecting in the deep sea is increasing, promoting concern regarding potential ecotoxicological impacts on deep-sea fauna. Technological difficulties in assessing toxicity in deep-sea species has promoted interest in developing shallow-water ecotoxicological proxy species. However, it is unclear how the low temperature and high hydrostatic pressure prevalent in the deep sea affect toxicity, and whether adaptation to deep-sea environmental conditions moderates any effects of these factors. To address these uncertainties we assessed the effects of temperature and hydrostatic pressure on lethal and sublethal (respiration rate, antioxidant enzyme activity) toxicity in acute (96 h) copper and cadmium exposures, using the shallow-water ecophysiological model organism Palaemon varians. Low temperature reduced toxicity in both metals, but reduced cadmium toxicity significantly more. In contrast, elevated hydrostatic pressure increased copper toxicity, but did not affect cadmium toxicity. The synergistic interaction between copper and cadmium was not affected by low temperature, but high hydrostatic pressure significantly enhanced the synergism. Differential environmental effects on toxicity suggest different mechanisms of action for copper and cadmium, and highlight that mechanistic understanding of toxicity is fundamental to predicting environmental effects on toxicity. Although results infer that sensitivity to toxicants differs across biogeographic ranges, shallow-water species may be suitable ecotoxicological proxies for deep-sea species, dependent on adaptation to habitats with similar environmental variability.

A Prototype Performance Assessment Model for Generic Deep Borehole Repository for High-Level Nuclear Waste - 12132

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joon H.; Arnold, Bill W.; Swift, Peter N.

2012-07-01

A deep borehole repository is one of the four geologic disposal system options currently under study by the U.S. DOE to support the development of a long-term strategy for geologic disposal of commercial used nuclear fuel (UNF) and high-level radioactive waste (HLW). The immediate goal of the generic deep borehole repository study is to develop the necessary modeling tools to evaluate and improve the understanding of the repository system response and processes relevant to long-term disposal of UNF and HLW in a deep borehole. A prototype performance assessment model for a generic deep borehole repository has been developed using themore » approach for a mined geological repository. The preliminary results from the simplified deep borehole generic repository performance assessment indicate that soluble, non-sorbing (or weakly sorbing) fission product radionuclides, such as I-129, Se-79 and Cl-36, are the likely major dose contributors, and that the annual radiation doses to hypothetical future humans associated with those releases may be extremely small. While much work needs to be done to validate the model assumptions and parameters, these preliminary results highlight the importance of a robust seal design in assuring long-term isolation, and suggest that deep boreholes may be a viable alternative to mined repositories for disposal of both HLW and UNF. (authors)« less

Effect of deep pressure input on parasympathetic system in patients with wisdom tooth surgery.

PubMed

Chen, Hsin-Yung; Yang, Hsiang; Meng, Ling-Fu; Chan, Pei-Ying Sarah; Yang, Chia-Yen; Chen, Hsin-Ming

2016-10-01

Deep pressure input is used to normalize physiological arousal due to stress. Wisdom tooth surgery is an invasive dental procedure with high stress levels, and an alleviation strategy is rarely applied during extraction. In this study, we investigated the effects of deep pressure input on autonomic responses to wisdom tooth extraction in healthy adults. A randomized, controlled, crossover design was used for dental patients who were allocated to experimental and control groups that received treatment with or without deep pressure input, respectively. Autonomic indicators, namely the heart rate (HR), percentage of low-frequency (LF) HR variability (LF-HRV), percentage of high-frequency (HF) HRV (HF-HRV), and LF/HF HRV ratio (LF/HF-HRV), were assessed at the baseline, during wisdom tooth extraction, and in the posttreatment phase. Wisdom tooth extraction caused significant autonomic parameter changes in both groups; however, differential response patterns were observed between the two groups. In particular, deep pressure input in the experimental group was associated with higher HF-HRV and lower LF/HF-HRV during extraction compared with those in the control group. LF/HF-HRV measurement revealed balanced sympathovagal activation in response to deep pressure application. The results suggest that the application of deep pressure alters the response of HF-HRV and facilitates maintaining sympathovagal balance during wisdom tooth extraction. Copyright © 2016. Published by Elsevier B.V.

Processes governing transient responses of the deep ocean buoyancy budget to a doubling of CO2

NASA Astrophysics Data System (ADS)

Palter, J. B.; Griffies, S. M.; Hunter Samuels, B. L.; Galbraith, E. D.; Gnanadesikan, A.

2012-12-01

Recent observational analyses suggest there is a temporal trend and high-frequency variability in deep ocean buoyancy in the last twenty years, a phenomenon reproduced even in low-mixing models. Here we use an earth system model (GFDL's ESM2M) to evaluate physical processes that influence buoyancy (and thus steric sea level) budget of the deep ocean in quasi-steady state and under a doubling of CO2. A new suite of model diagnostics allows us to quantitatively assess every process that influences the buoyancy budget and its temporal evolution, revealing surprising dynamics governing both the equilibrium budget and its transient response to climate change. The results suggest that the temporal evolution of the deep ocean contribution to sea level rise is due to a diversity of processes at high latitudes, whose net effect is then advected in the Eulerian mean flow to mid and low latitudes. In the Southern Ocean, a slowdown in convection and spin up of the residual mean advection are approximately equal players in the deep steric sea level rise. In the North Atlantic, the region of greatest deep steric sea level variability in our simulations, a decrease in mixing of cold, dense waters from the marginal seas and a reduction in open ocean convection causes an accumulation of buoyancy in the deep subpolar gyre, which is then advected equatorward.

Method and system for advancement of a borehole using a high power laser

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moxley, Joel F.; Land, Mark S.; Rinzler, Charles C.

2014-09-09

There is provided a system, apparatus and methods for the laser drilling of a borehole in the earth. There is further provided with in the systems a means for delivering high power laser energy down a deep borehole, while maintaining the high power to advance such boreholes deep into the earth and at highly efficient advancement rates, a laser bottom hole assembly, and fluid directing techniques and assemblies for removing the displaced material from the borehole.

Deep and surface learning in problem-based learning: a review of the literature.

PubMed

Dolmans, Diana H J M; Loyens, Sofie M M; Marcq, Hélène; Gijbels, David

2016-12-01

In problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested and try to understand what is being studied. This review investigates: (1) the effects of PBL on students' deep and surface approaches to learning, (2) whether and why these effects do differ across (a) the context of the learning environment (single vs. curriculum wide implementation), and (b) study quality. Studies were searched dealing with PBL and students' approaches to learning. Twenty-one studies were included. The results indicate that PBL does enhance deep learning with a small positive average effect size of .11 and a positive effect in eleven of the 21 studies. Four studies show a decrease in deep learning and six studies show no effect. PBL does not seem to have an effect on surface learning as indicated by a very small average effect size (.08) and eleven studies showing no increase in the surface approach. Six studies demonstrate a decrease and four an increase in surface learning. It is concluded that PBL does seem to enhance deep learning and has little effect on surface learning, although more longitudinal research using high quality measurement instruments is needed to support this conclusion with stronger evidence. Differences cannot be explained by the study quality but a curriculum wide implementation of PBL has a more positive impact on the deep approach (effect size .18) compared to an implementation within a single course (effect size of -.05). PBL is assumed to enhance active learning and students' intrinsic motivation, which enhances deep learning. A high perceived workload and assessment that is perceived as not rewarding deep learning are assumed to enhance surface learning.

The biodiversity of the deep Southern Ocean benthos.

PubMed

Brandt, A; De Broyer, C; De Mesel, I; Ellingsen, K E; Gooday, A J; Hilbig, B; Linse, K; Thomson, M R A; Tyler, P A

2007-01-29

Our knowledge of the biodiversity of the Southern Ocean (SO) deep benthos is scarce. In this review, we describe the general biodiversity patterns of meio-, macro- and megafaunal taxa, based on historical and recent expeditions, and against the background of the geological events and phylogenetic relationships that have influenced the biodiversity and evolution of the investigated taxa. The relationship of the fauna to environmental parameters, such as water depth, sediment type, food availability and carbonate solubility, as well as species interrelationships, probably have shaped present-day biodiversity patterns as much as evolution. However, different taxa exhibit different large-scale biodiversity and biogeographic patterns. Moreover, there is rarely any clear relationship of biodiversity pattern with depth, latitude or environmental parameters, such as sediment composition or grain size. Similarities and differences between the SO biodiversity and biodiversity of global oceans are outlined. The high percentage (often more than 90%) of new species in almost all taxa, as well as the high degree of endemism of many groups, may reflect undersampling of the area, and it is likely to decrease as more information is gathered about SO deep-sea biodiversity by future expeditions. Indeed, among certain taxa such as the Foraminifera, close links at the species level are already apparent between deep Weddell Sea faunas and those from similar depths in the North Atlantic and Arctic. With regard to the vertical zonation from the shelf edge into deep water, biodiversity patterns among some taxa in the SO might differ from those in other deep-sea areas, due to the deep Antarctic shelf and the evolution of eurybathy in many species, as well as to deep-water production that can fuel the SO deep sea with freshly produced organic matter derived not only from phytoplankton, but also from ice algae.

The biodiversity of the deep Southern Ocean benthos

PubMed Central

Brandt, A; De Broyer, C; De Mesel, I; Ellingsen, K.E; Gooday, A.J; Hilbig, B; Linse, K; Thomson, M.R.A; Tyler, P.A

2006-01-01

Our knowledge of the biodiversity of the Southern Ocean (SO) deep benthos is scarce. In this review, we describe the general biodiversity patterns of meio-, macro- and megafaunal taxa, based on historical and recent expeditions, and against the background of the geological events and phylogenetic relationships that have influenced the biodiversity and evolution of the investigated taxa. The relationship of the fauna to environmental parameters, such as water depth, sediment type, food availability and carbonate solubility, as well as species interrelationships, probably have shaped present-day biodiversity patterns as much as evolution. However, different taxa exhibit different large-scale biodiversity and biogeographic patterns. Moreover, there is rarely any clear relationship of biodiversity pattern with depth, latitude or environmental parameters, such as sediment composition or grain size. Similarities and differences between the SO biodiversity and biodiversity of global oceans are outlined. The high percentage (often more than 90%) of new species in almost all taxa, as well as the high degree of endemism of many groups, may reflect undersampling of the area, and it is likely to decrease as more information is gathered about SO deep-sea biodiversity by future expeditions. Indeed, among certain taxa such as the Foraminifera, close links at the species level are already apparent between deep Weddell Sea faunas and those from similar depths in the North Atlantic and Arctic. With regard to the vertical zonation from the shelf edge into deep water, biodiversity patterns among some taxa in the SO might differ from those in other deep-sea areas, due to the deep Antarctic shelf and the evolution of eurybathy in many species, as well as to deep-water production that can fuel the SO deep sea with freshly produced organic matter derived not only from phytoplankton, but also from ice algae. PMID:17405207

Holocene glacier and deep water dynamics, Adélie Land region, East Antarctica

NASA Astrophysics Data System (ADS)

Denis, Delphine; Crosta, Xavier; Schmidt, Sabine; Carson, Damien S.; Ganeshram, Raja S.; Renssen, Hans; Bout-Roumazeilles, Viviane; Zaragosi, Sebastien; Martin, Bernard; Cremer, Michel; Giraudeau, Jacques

2009-06-01

This study presents a high-resolution multi-proxy investigation of sediment core MD03-2601 and documents major glacier oscillations and deep water activity during the Holocene in the Adélie Land region, East Antarctica. A comparison with surface ocean conditions reveals synchronous changes of glaciers, sea ice and deep water formation at Milankovitch and sub-Milankovitch time scales. We report (1) a deglaciation of the Adélie Land continental shelf from 11 to 8.5 cal ka BP, which occurred in two phases of effective glacier grounding-line retreat at 10.6 and 9 cal ka BP, associated with active deep water formation; (2) a rapid glacier and sea ice readvance centred around 7.7 cal ka BP; and (3) five rapid expansions of the glacier-sea ice systems, during the Mid to Late Holocene, associated to a long-term increase of deep water formation. At Milankovich time scales, we show that the precessionnal component of insolation at high and low latitudes explains the major trend of the glacier-sea ice-ocean system throughout the Holocene, in the Adélie Land region. In addition, the orbitally-forced seasonality seems to control the coastal deep water formation via the sea ice-ocean coupling, which could lead to opposite patterns between north and south high latitudes during the Mid to Late Holocene. At sub-Milankovitch time scales, there are eight events of glacier-sea ice retreat and expansion that occurred during atmospheric cooling events over East Antarctica. Comparisons of our results with other peri-Antarctic records and model simulations from high southern latitudes may suggest that our interpretation on glacier-sea ice-ocean interactions and their Holocene evolutions reflect a more global Antarctic Holocene pattern.

Initial observations of cell-mediated drug delivery to the deep lung.

PubMed

Kumar, Arun; Glaum, Mark; El-Badri, Nagwa; Mohapatra, Shyam; Haller, Edward; Park, Seungjoo; Patrick, Leslie; Nattkemper, Leigh; Vo, Dawn; Cameron, Don F

2011-01-01

Using current methodologies, drug delivery to small airways, terminal bronchioles, and alveoli (deep lung) is inefficient, especially to the lower lungs. Urgent lung pathologies such as acute respiratory distress syndrome (ARDS) and post-lung transplantation complications are difficult to treat, in part due to the methodological limitations in targeting the deep lung with high efficiency drug distribution to the site of pathology. To overcome drug delivery limitations inhibiting the optimization of deep lung therapy, isolated rat Sertoli cells preloaded with chitosan nanoparticles were use to obtain a high-density distribution and concentration (92%) of the nanoparticles in the lungs of mice by way of the peripheral venous vasculature rather than the more commonly used pulmonary route. Additionally, Sertoli cells were preloaded with chitosan nanoparticles coupled with the anti-inflammatory compound curcumin and then injected intravenously into control or experimental mice with deep lung inflammation. By 24 h postinjection, most of the curcumin load (∼90%) delivered in the injected Sertoli cells was present and distributed throughout the lungs, including the perialveloar sac area in the lower lungs. This was based on the high-density, positive quantification of both nanoparticles and curcumin in the lungs. There was a marked positive therapeutic effect achieved 24 h following curcumin treatment delivered by this Sertoli cell nanoparticle protocol (SNAP). Results identify a novel and efficient protocol for targeted delivery of drugs to the deep lung mediated by extratesticular Sertoli cells. Utilization of SNAP delivery may optimize drug therapy for conditions such as ARDS, status asthmaticus, pulmonary hypertension, lung cancer, and complications following lung transplantation where the use of high concentrations of anti-inflammatory drugs is desirable, but often limited by risks of systemic drug toxicity.

Molecular Genetic and Crystal Structural Analysis of 1-(4-Hydroxyphenyl)-Ethanol Dehydrogenase from 'Aromatoleum aromaticum' EbN1.

PubMed

Büsing, Imke; Höffken, H Wolfgang; Breuer, Michael; Wöhlbrand, Lars; Hauer, Bernhard; Rabus, Ralf

2015-01-01

The dehydrogenation of 1-(4-hydroxyphenyl)-ethanol to 4-hydroxyacetophenone represents the second reaction step during anaerobic degradation of p-ethylphenol in the denitrifying bacterium 'Aromatoleum aromaticum' EbN1. Previous proteogenomic studies identified two different proteins (ChnA and EbA309) as possible candidates for catalyzing this reaction [Wöhlbrand et al: J Bacteriol 2008;190:5699-5709]. Physiological-molecular characterization of newly generated unmarked in-frame deletion and complementation mutants allowed defining ChnA (renamed here as Hped) as the enzyme responsible for 1-(4-hydroxyphenyl)-ethanol oxidation. Hped [1-(4-hydroxyphenyl)-ethanol dehydrogenase] belongs to the 'classical' family within the short-chain alcohol dehydrogenase/reductase (SDR) superfamily. Hped was overproduced in Escherichia coli, purified and crystallized. The X-ray structures of the apo- and NAD(+)-soaked form were resolved at 1.5 and 1.1 Å, respectively, and revealed Hped as a typical homotetrameric SDR. Modeling of the substrate 4-hydroxyacetophenone (reductive direction of Hped) into the active site revealed the structural determinants of the strict (R)-specificity of Hped (Phe(187)), contrasting the (S)-specificity of previously reported 1-phenylethanol dehydrogenase (Ped; Tyr(93)) from strain EbN1 [Höffken et al: Biochemistry 2006;45:82-93]. © 2015 S. Karger AG, Basel.

Insights into molecular therapy of glioma: current challenges and next generation blueprint

PubMed Central

Rajesh, Y; Pal, Ipsita; Banik, Payel; Chakraborty, Sandipan; Borkar, Sachin A; Dey, Goutam; Mukherjee, Ahona; Mandal, Mahitosh

2017-01-01

Glioma accounts for the majority of human brain tumors. With prevailing treatment regimens, the patients have poor survival rates. In spite of current development in mainstream glioma therapy, a cure for glioma appears to be out of reach. The infiltrative nature of glioma and acquired resistance substancially restrict the therapeutic options. Better elucidation of the complicated pathobiology of glioma and proteogenomic characterization might eventually open novel avenues for the design of more sophisticated and effective combination regimens. This could be accomplished by individually tailoring progressive neuroimaging techniques, terminating DNA synthesis with prodrug-activating genes, silencing gliomagenesis genes (gene therapy), targeting miRNA oncogenic activity (miRNA-mRNA interaction), combining Hedgehog-Gli/Akt inhibitors with stem cell therapy, employing tumor lysates as antigen sources for efficient depletion of tumor-specific cancer stem cells by cytotoxic T lymphocytes (dendritic cell vaccination), adoptive transfer of chimeric antigen receptor-modified T cells, and combining immune checkpoint inhibitors with conventional therapeutic modalities. Thus, the present review captures the latest trends associated with the molecular mechanisms involved in glial tumorigenesis as well as the limitations of surgery, radiation and chemotherapy. In this article we also critically discuss the next generation molecular therapeutic strategies and their mechanisms for the successful treatment of glioma. PMID:28317871

Proteomics Standards Initiative: Fifteen Years of Progress and Future Work

PubMed Central

2017-01-01

The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI. PMID:28849660

Proteomics Standards Initiative: Fifteen Years of Progress and Future Work.

PubMed

Deutsch, Eric W; Orchard, Sandra; Binz, Pierre-Alain; Bittremieux, Wout; Eisenacher, Martin; Hermjakob, Henning; Kawano, Shin; Lam, Henry; Mayer, Gerhard; Menschaert, Gerben; Perez-Riverol, Yasset; Salek, Reza M; Tabb, David L; Tenzer, Stefan; Vizcaíno, Juan Antonio; Walzer, Mathias; Jones, Andrew R

2017-12-01

The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.

Targeting invadopodia-mediated breast cancer metastasis by using ABL kinase inhibitors

PubMed Central

Meirson, Tomer; Genna, Alessandro; Lukic, Nikola; Makhnii, Tetiana; Alter, Joel; Sharma, Ved P.; Wang, Yarong; Samson, Abraham O.; Condeelis, John S.; Gil-Henn, Hava

2018-01-01

Metastatic dissemination of cancer cells from the primary tumor and their spread to distant sites in the body is the leading cause of mortality in breast cancer patients. While researchers have identified treatments that shrink or slow metastatic tumors, no treatment that permanently eradicates metastasis exists at present. Here, we show that the ABL kinase inhibitors imatinib, nilotinib, and GNF-5 impede invadopodium precursor formation and cortactin-phosphorylation dependent invadopodium maturation, leading to decreased actin polymerization in invadopodia, reduced extracellular matrix degradation, and impaired matrix proteolysis-dependent invasion. Using a mouse xenograft model we demonstrate that, while primary tumor size is not affected by ABL kinase inhibitors, the in vivo matrix metalloproteinase (MMP) activity, tumor cell invasion, and consequent spontaneous metastasis to lungs are significantly impaired in inhibitor-treated mice. Further proteogenomic analysis of breast cancer patient databases revealed co-expression of the Abl-related gene (Arg) and cortactin across all hormone- and human epidermal growth factor receptor 2 (HER2)-receptor status tumors, which correlates synergistically with distant metastasis and poor patient prognosis. Our findings establish a prognostic value for Arg and cortactin as predictors of metastatic dissemination and suggest that therapeutic inhibition of ABL kinases may be used for blocking breast cancer metastasis. PMID:29774130

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant-cyanobacteria symbiosis.

PubMed

Warshan, Denis; Espinoza, Josh L; Stuart, Rhona K; Richter, R Alexander; Kim, Sea-Yong; Shapiro, Nicole; Woyke, Tanja; C Kyrpides, Nikos; Barry, Kerrie; Singan, Vasanth; Lindquist, Erika; Ansong, Charles; Purvine, Samuel O; M Brewer, Heather; Weyman, Philip D; Dupont, Christopher L; Rasmussen, Ulla

2017-12-01

Dinitrogen (N 2 )-fixation by cyanobacteria in symbiosis with feathermosses is the primary pathway of biological nitrogen (N) input into boreal forests. Despite its significance, little is known about the cyanobacterial gene repertoire and regulatory rewiring needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions and regulatory changes allowing cyanobacteria to form and maintain this symbiosis, we compared genomically closely related symbiotic-competent and -incompetent Nostoc strains using a proteogenomics approach and an experimental set up allowing for controlled chemical and physical contact between partners. Thirty-two gene families were found only in the genomes of symbiotic strains, including some never before associated with cyanobacterial symbiosis. We identified conserved orthologs that were differentially expressed in symbiotic strains, including protein families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, and glycosyl-modifying and oxidative stress-mediating exoenzymes. The physical moss-cyanobacteria epiphytic symbiosis is distinct from other cyanobacteria-plant symbioses, with Nostoc retaining motility, and lacking modulation of N 2 -fixation, photosynthesis, GS-GOGAT cycle and heterocyst formation. The results expand our knowledge base of plant-cyanobacterial symbioses, provide a model of information and material exchange in this ecologically significant symbiosis, and suggest new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining the cyanobacteria-feathermoss symbiosis.

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warshan, Denis; Espinoza, Josh L.; Stuart, Rhona

Dinitrogen (N2)-fixation by cyanobacteria in symbiosis with feather mosses represents the main pathway of biological N input into boreal forests. Despite its significance, little is known about the gene repertoire needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions or regulatory rewiring allowing cyanobacteria to form this symbiosis, we compared closely related Nostoc strains that were either symbiosis-competent or non-competent, using a proteogenomics approach and a unique experimental setup allowing for controlled chemical and physical contact between partners. Thirty-two protein families were only in the genomes of competent strains, including some never before associated with symbiosis.more » We identified conserved orthologs that were differentially expressed in competent strains, including gene families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, sugar metabolism, and glycosyl-modifying and oxidative stress-mediating exoenzymes. In contrast to other cyanobacteria-plant symbioses, the moss-cyanobacteria epiphytic symbiosis is distinct, with the symbiont retaining motility and chemotaxis, and not modulating N-fixation, photosynthesis, GS-GOGAT cycle, and heterocyst formation. Our work expands our knowledge of plant cyanobacterial symbioses, provides an interaction model of this ecologically significant symbiosis, and suggests new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining this symbiosis.« less

Numerical Experiments on the Role of the Lower Crust in the Development of Extension-driven Gneiss Domes

NASA Astrophysics Data System (ADS)

Korchinski, M.; Rey, P. F.; Teyssier, C. P.; Mondy, L. S.; Whitney, D.

2016-12-01

Flow of orogenic crust is a critical geodynamic process in the chemical and physical evolution of continents. Deeply sourced rocks are transported to the near surface within gneiss domes, which are ubiquitous features in orogens and extensional regions. Exhumation of material within a gneiss dome can occur as the result of tectonic stresses, where material moves into space previously occupied by the shallow crust as the result of extension localized along a detachment system. Gravitationally driven flow may also contribute to exhumation. This research addresses how physical parameters (density, viscosity) of the deep crust (base of brittle crust to Moho) impact (1) the localization of extension in the shallow crust, and (2) the flow of deep crust by tectonic and non-tectonic stresses. We present 2D numerical experiments in which the density (2900-3100 kg m-3) and viscosity (1e19-1e21 Pa s) of the deep crust are systematically varied. Lateral and vertical transport of deep crustal rocks toward the gneiss dome occurs across the entire parameter space. A low viscosity deep crust yields localized extension in the upper crust and crustal-scale upward flow; this case produces the highest exhumation. A high viscosity deep crust results in distributed thinning of the upper crust, which suppresses upward mass transport. The density of the deep crust has only a second-order effect on the shallow crust extension regime. We capture the flow field generated after the cessation of extension to evaluate mass transport that is not driven by tectonic stresses. Upward transport of material within the gneiss dome is present across the entire parameter space. In the case of a low-viscosity deep crust, horizontal flow occurs adjacent to the dome above the Moho; this flow is an order of magnitude higher than that within the dome. Density variations do not drastically alter the flow field in the low viscosity lower crust. However, a high density and high viscosity deep crust results in boudinage of the whole crust, which generates significant upward flow from the buoyant asthenosphere.

The T-Reflection and the Deep Crustal Structure of the Vøring Margin, Offshore mid-Norway

NASA Astrophysics Data System (ADS)

Abdelmalak, M. M.; Faleide, J. I.; Planke, S.; Gernigon, L.; Zastrozhnov, D.; Shephard, G. E.; Myklebust, R.

2017-11-01

Seismic reflection data along volcanic passive margins frequently provide imaging of strong and laterally continuous reflections in the middle and lower crust. We have completed a detailed 2-D seismic interpretation of the deep crustal structure of the Vøring Margin, offshore mid-Norway, where high-quality seismic data allow the identification of high-amplitude reflections, locally referred to as the T-Reflection. Using a dense seismic grid, we have mapped the geometry of the T-Reflection in order to compare it with filtered Bouguer gravity anomalies and seismic refraction data. The T-Reflection is identified between 7 and 10 s. Sometimes it consists of one single smooth reflection. However, it is frequently associated with a set of rough multiple reflections displaying discontinuous segments with varying geometries, amplitudes, and contact relationships. The T-Reflection seems to be connected to deep sill networks and is locally identified at the continuation of basement high structures or terminates over fractures and faults. The T-Reflection presents a low magnetic signal. The spatial correlation between the filtered positive Bouguer gravity anomalies and the deep dome-shaped reflections indicates that the latter represent a high-impedance boundary contrast associated with a high-density and high-velocity body. In 50% of the outer Vøring Margin, the depth of the mapped T-Reflection is found to correspond to the depth of the top of the Lower Crustal Body (LCB), which is characterized by high P wave velocities (>7 km/s). We present a tectonic scenario, where a large part of the deep crustal structure is composed of preserved upper continental crustal blocks and middle to lower crustal lenses of inherited high-grade metamorphic rocks. Deep intrusions into the faulted crustal blocks are responsible for the rough character of the T-Reflection, whereas intrusions into the ductile lower crust and detachment faults are likely responsible for its smoother character. Deep magma intrusions can be responsible for regional metamorphic processes leading to an increasing velocity of the lower crust to more than 7 km/s. The result is a heterogeneous LCB that likely represents a complex mixture of pre- to syn-breakup mafic and ultramafic rocks (cumulates and sills) and old metamorphic rocks such as granulites and eclogites. An increasing degree of melting toward the breakup axis is responsible for an increasing proportion of cumulates and sill intrusions in the lower crust.

Wide Bandgap Extrinsic Photoconductive Switches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sullivan, James S.

2013-07-03

Semi-insulating Gallium Nitride, 4H and 6H Silicon Carbide are attractive materials for compact, high voltage, extrinsic, photoconductive switches due to their wide bandgap, high dark resistance, high critical electric field strength and high electron saturation velocity. These wide bandgap semiconductors are made semi-insulating by the addition of vanadium (4H and 6HSiC) and iron (2H-GaN) impurities that form deep acceptors. These deep acceptors trap electrons donated from shallow donor impurities. The electrons can be optically excited from these deep acceptor levels into the conduction band to transition the wide bandgap semiconductor materials from a semi-insulating to a conducting state. Extrinsic photoconductivemore » switches with opposing electrodes have been constructed using vanadium compensated 6H-SiC and iron compensated 2H-GaN. These extrinsic photoconductive switches were tested at high voltage and high power to determine if they could be successfully used as the closing switch in compact medical accelerators.« less

Fish debris record the hydrothermal activity in the Atlantis II deep sediments (Red Sea)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oudin, E.; Cocherie, A.

1988-01-01

The REE and U, Th, Zr, Hf, Sc have been analyzed in samples from Atlantis II and Shaban/Jean Charcot Deeps in the Red Sea. The high Zr/Hf ratio in some sediments indicates the presence of fish debris or of finely crystallized apatite. The positive ..sigma..REE vs P/sub 2/O/sub 5/ and ..sigma..REE vs Zr/Hf correlations show that fish debris and finely crystallized apatite are the main REE sink in Atlantis II Deep sediments as in other marine environments. The hydrothermal sediments and the fish debris concentrates have similar REE patterns, characterized by a LREE enrichment and a large positive Eu anomaly.more » This REE pattern is also observed in E.P.R. hydrothermal solutions. Fish debris from marine environments acquire their REE content and signature mostly from sea water during early diagenesis. The hydrothermal REE signature of Atlantis II Deep fish debris indicate that they probably record the REE signature of their hydrothermal sedimentation and diagenetic environment. The different REE signatures of the Shaban/Jean Charcot and Atlantis II Deep hydrothermal sediments suggest a sea water-dominated brine in the Shaban/Jean Charcot Deep as opposed to the predominantly hydrothermal brine in Atlantis II Deep. Atlantis II Deep fish debris are also characterized by their high U but low Th contents. Their low Th contents probably reflect the low Th content of the various possible sources (sea water, brine, sediments). Their U contents are probably controlled by the redox conditions of sedimentation.« less

A Study of Highly Qualified Science Teachers' Career Trajectory in the Deep, Rural South: Examining a Link between Deprofessionalization and Teacher Dissatisfaction

ERIC Educational Resources Information Center

Hodges, Georgia W.; Tippins, Deborah; Oliver, J. Steve

2013-01-01

Science teacher retention, attrition, and migration continue to perplex educational scholars, political entities, as well as the general public. This study utilized an interpretive methodological design to generate assertions regarding career choice made by highly qualified science teachers in the deep, rural South through analysis of documents,…

Attention to Semantic versus Phonetic Verbal Attributes as a Function of Individual Differences in Arousal and Learning Strategy.

ERIC Educational Resources Information Center

Schmeck, Ronald R; Spofford, Mark

1982-01-01

An investigation was undertaken to determine whether highly aroused (e.g. highly anxious) students are handicapped with regard to their ability to learn through deep processing and elaboration. The hypothesis that well-developed deep and elaborative habits of thought might counteract the disruptive effects that excessive arousal has upon students…

Synthesis of novel lidocaine-releasing poly(diol-co-citrate) elastomers by using deep eutectic solvents.

PubMed

Serrano, M Concepción; Gutiérrez, María C; Jiménez, Ricardo; Ferrer, M Luisa; del Monte, Francisco

2012-01-14

Poly(octanediol-co-citrate) elastomers containing high loading of lidocaine were synthesized at temperatures below 100 °C by means of using deep eutectic mixtures of 1,8-octanediol and lidocaine. The preservation of lidocaine integrity resulted in high-capacity drug-eluting elastomers. This journal is © The Royal Society of Chemistry 2012

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

PubMed

Sadeghi, Zahra; Testolin, Alberto

2017-08-01

In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

Dining in the Deep: The Feeding Ecology of Deep-Sea Fishes

NASA Astrophysics Data System (ADS)

Drazen, Jeffrey C.; Sutton, Tracey T.

2017-01-01

Deep-sea fishes inhabit ˜75% of the biosphere and are a critical part of deep-sea food webs. Diet analysis and more recent trophic biomarker approaches, such as stable isotopes and fatty-acid profiles, have enabled the description of feeding guilds and an increased recognition of the vertical connectivity in food webs in a whole-water-column sense, including benthic-pelagic coupling. Ecosystem modeling requires data on feeding rates; the available estimates indicate that deep-sea fishes have lower per-individual feeding rates than coastal and epipelagic fishes, but the overall predation impact may be high. A limited number of studies have measured the vertical flux of carbon by mesopelagic fishes, which appears to be substantial. Anthropogenic activities are altering deep-sea ecosystems and their services, which are mediated by trophic interactions. We also summarize outstanding data gaps.

Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions

PubMed Central

2014-01-01

Deep sequencing harnesses the high throughput nature of next generation sequencing technologies to generate population samples, treating information contained in individual reads as meaningful. Here, we review applications of deep sequencing to pathogen evolution. Pioneering deep sequencing studies from the virology literature are discussed, such as whole genome Roche-454 sequencing analyses of the dynamics of the rapidly mutating pathogens hepatitis C virus and HIV. Extension of the deep sequencing approach to bacterial populations is then discussed, including the impacts of emerging sequencing technologies. While it is clear that deep sequencing has unprecedented potential for assessing the genetic structure and evolutionary history of pathogen populations, bioinformatic challenges remain. We summarise current approaches to overcoming these challenges, in particular methods for detecting low frequency variants in the context of sequencing error and reconstructing individual haplotypes from short reads. PMID:24428920

Mooring Measurements of the Abyssal Circulations in the Western Pacific Ocean

NASA Astrophysics Data System (ADS)

Wang, J.; Wang, F.

2016-12-01

A scientific observing network in the western tropical Pacific has initially been established by the Institute of Oceanology, Chinese Academy of Sciences (IOCAS). Using fifteen moorings that gives unprecedented measurements in the intermediate and abyssal layers, we present multi-timescale variations of the deep ocean circulations prior to and during 2015 El Niño event. The deep ocean velocities increase equatorward with high standard deviation and nearly zero mean. The deep ocean currents mainly flow in meridional direction in the central Philippine Basin, and are dominated by a series of alternating westward and eastward zonal jets in the Caroline Basin. The currents in the deep channel connecting the East and West Mariana Basins mainly flow southeastward. Seasonal variation is only present in the deep jets in the Caroline Basin, associating with vertical propagating annual Rossby wave. The high-frequency flow bands are dominated by diurnal, and semi-diurnal tidal currents, and near-inertial currents. The rough topography has a strong influence on the abyssal circulations, including the intensifications in velocity and internal tidal energy, and the formation of upwelling flow.

Deep learning for studies of galaxy morphology

NASA Astrophysics Data System (ADS)

Tuccillo, D.; Huertas-Company, M.; Decencière, E.; Velasco-Forero, S.

2017-06-01

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because of its high level of abstraction with little human intervention, deep learning appears to be a promising approach. Deep learning is a rapidly growing discipline that models high-level patterns in data as complex multilayered networks. In this work we test the ability of deep convolutional networks to provide parametric properties of Hubble Space Telescope like galaxies (half-light radii, Sérsic indices, total flux etc..). We simulate a set of galaxies including point spread function and realistic noise from the CANDELS survey and try to recover the main galaxy parameters using deep-learning. We compare the results with the ones obtained with the commonly used profile fitting based software GALFIT. This way showing that with our method we obtain results at least equally good as the ones obtained with GALFIT but, once trained, with a factor 5 hundred time faster.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

Effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit.

PubMed

Xi, Peng; Li, Yan; Ge, Xiaojin; Liu, Dandan; Miao, Mingsan

2018-05-01

Observing the effect of nano-silver hydrogel coating film on deep partial thickness scald model of rabbit. We prepared boiling water scalded rabbits with deep II degree scald models and applied high, medium and low doses of nano-silver hydrogel coating film for different time and area. Then we compared the difference of burned paper weight before administration and after administration model burns, burn local skin irritation points infection, skin crusting and scabs from the time, and the impact of local skin tissue morphology. Rabbits deep II degree burn model successful modeling; on day 12, 18, high, medium and low doses of nano-silver hydrogel coating film significantly reduced skin irritation of rabbits infected with the integral value ( P  < 0.01, P  < 0.05); high, medium and low doses of nano-silver hydrogel coating film group significantly decreased skin irritation, infection integral value ( P  < 0.01, P  < 0.05); high, medium and low doses of nano-silver hydrogel coating film significantly reduced film rabbits' scalded skin crusting time ( P  < 0.01), significantly shortened the rabbit skin burns from the scab time ( P  < 0.01), and significantly improved the treatment of skin diseases in rabbits scald model change ( P  < 0.01, P  < 0.05). The nano-silver hydrogel coating film on the deep partial thickness burns has a significant therapeutic effect; external use has a significant role in wound healing.

Vapor Pressure Data and Analysis for Selected Organophosphorus Compounds, CMMP, DPMP, DMEP, and DEEP: Extrapolation of High-Temperature Data

DTIC Science & Technology

2018-04-01

EXTRAPOLATION OF HIGH -TEMPERATURE DATA ECBC-TR-1507 Ann Brozena Patrice Abercrombie-Thomas RESEARCH AND TECHNOLOGY DIRECTORATE David E. Tevault...Compounds, CMMP, DPMP, DMEP, and DEEP: Extrapolation of High - Temperature Data 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR...22060-6201 10. SPONSOR/MONITOR’S ACRONYM(S) DTRA 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT Approved

[The high pressure life of piezophiles].

PubMed

Oger, Philippe; Cario, Anaïs

2014-01-01

The deep biosphere is composed of very different biotopes located in the depth of the oceans, the ocean crust or the lithosphere. Although very different, deep biosphere biotopes share one common feature, high hydrostatic pressure. The deep biosphere is colonized by specific organisms, called piezophiles, that are able to grow under high hydrostatic pressure. Bacterial piezophiles are mainly psychrophiles belonging to five genera of γ-proteobacteria, Photobacterium, Shewanella, Colwellia, Psychromonas and Moritella, while piezophilic Archaea are mostly (hyper)thermophiles from the Thermococcales. None of these genera are specific for the deep biosphere. High pressure deeply impacts the activity of cells and cellular components, and reduces the activity of numerous key processes, eventually leading to cell death of piezosensitive organisms. Biochemical and genomic studies yield a fragmented view on the adaptive mechanisms in piezophiles. It is yet unclear whether piezophilic adaptation requires the modification of a few genes, or metabolic pathways, or a more profound reorganization of the genome, the fine tuning of gene expression to compensate the pressure-induced loss of activity of the proteins most affected by high pressure, or a stress-like physiological cell response. In contrast to what has been seen for thermophily or halophily, the adaptation to high pressure is diffuse in the genome and may concern only a small fraction of the genes. © Société de Biologie, 2014.

Deep Impact on Its Way

NASA Image and Video Library

2005-01-18

The high speed of NASA Deep Impact spacecraft causes it to appear as a long streak across the sky in the constellation Virgo during the 10-minute exposure time of this photograph taken by Mr. Palomar 200-inch telescope.

Two-photon absorption measurements of deep UV transmissible materials at 213 nm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patankar, S.; Yang, S. T.; Moody, J. D.

We report on two photon absorption measurements at 213nm of deep UV transmissible media including LiF, MgF 2, CaF 2, BaF 2, Sapphire (Al 2O 3) and high purity grades of fused-silica (SiO 2). A high stability 24ps Nd:YAG laser operating at the 5th harmonic (213nm) was used to generate a high intensity, long Rayleigh length Gaussian focus inside the samples. The measurements of the Fluoride crystals and Sapphire indicate two photon absorption coefficients between 0.004 and 0.82 cm/GW. We find that different grades of fused silica performed near identically for two photon absorption, however, there are differences in linearmore » losses associated with purity. A low two photon absorption cross section is measured for MgF 2 making it an ideal material for the propagation of high intensity deep UV lasers.« less

Two-photon absorption measurements of deep UV transmissible materials at 213 nm

DOE PAGES

Patankar, S.; Yang, S. T.; Moody, J. D.; ...

2017-09-19

We report on two photon absorption measurements at 213nm of deep UV transmissible media including LiF, MgF 2, CaF 2, BaF 2, Sapphire (Al 2O 3) and high purity grades of fused-silica (SiO 2). A high stability 24ps Nd:YAG laser operating at the 5th harmonic (213nm) was used to generate a high intensity, long Rayleigh length Gaussian focus inside the samples. The measurements of the Fluoride crystals and Sapphire indicate two photon absorption coefficients between 0.004 and 0.82 cm/GW. We find that different grades of fused silica performed near identically for two photon absorption, however, there are differences in linearmore » losses associated with purity. A low two photon absorption cross section is measured for MgF 2 making it an ideal material for the propagation of high intensity deep UV lasers.« less

Note: long range and accurate measurement of deep trench microstructures by a specialized scanning tunneling microscope.

PubMed

Ju, Bing-Feng; Chen, Yuan-Liu; Zhang, Wei; Zhu, Wule; Jin, Chao; Fang, F Z

2012-05-01

A compact but practical scanning tunneling microscope (STM) with high aspect ratio and high depth capability has been specially developed. Long range scanning mechanism with tilt-adjustment stage is adopted for the purpose of adjusting the probe-sample relative angle to compensate the non-parallel effects. A periodical trench microstructure with a pitch of 10 μm has been successfully imaged with a long scanning range up to 2.0 mm. More innovatively, a deep trench with depth and step height of 23.0 μm has also been successfully measured, and slope angle of the sidewall can approximately achieve 67°. The probe can continuously climb the high step and exploring the trench bottom without tip crashing. The new STM could perform long range measurement for the deep trench and high step surfaces without image distortion. It enables accurate measurement and quality control of periodical trench microstructures.

Two-photon absorption measurements of deep UV transmissible materials at 213  nm.

PubMed

Patankar, S; Yang, S T; Moody, J D; Swadling, G F; Erlandson, A C; Bayramian, A J; Barker, D; Datte, P; Acree, R L; Pepmeier, B; Madden, R E; Borden, M R; Ross, J S

2017-10-20

We report on two-photon absorption measurements at 213 nm of deep UV transmissible media, including LiF, MgF 2 , CaF 2 , BaF 2 , sapphire (Al 2 O 3 ), and high-purity grades of fused-silica (SiO 2 ). A high-stability 24 ps Nd:YAG laser operating at the 5th harmonic (213 nm) was used to generate a high-intensity, long-Rayleigh-length Gaussian focus inside the samples. The measurements of the fluoride crystals and sapphire indicate two-photon absorption coefficients between 0.004 and 0.82 cm/GW. We find that different grades of fused silica performed near identically for two-photon absorption; however, there are differences in linear losses associated with purity. A low two-photon absorption cross section is measured for MgF 2 , making it an ideal material for the propagation of high-intensity deep UV lasers.

The Deep Space Atomic Clock: Ushering in a New Paradigm for Radio Navigation and Science

NASA Technical Reports Server (NTRS)

Ely, Todd; Seubert, Jill; Prestage, John; Tjoelker, Robert

2013-01-01

The Deep Space Atomic Clock (DSAC) mission will demonstrate the on-orbit performance of a high-accuracy, high-stability miniaturized mercury ion atomic clock during a year-long experiment in Low Earth Orbit. DSAC's timing error requirement provides the frequency stability necessary to perform deep space navigation based solely on one-way radiometric tracking data. Compared to a two-way tracking paradigm, DSAC-enabled one-way tracking will benefit navigation and radio science by increasing the quantity and quality of tracking data. Additionally, DSAC also enables fully-autonomous onboard navigation useful for time-sensitive situations. The technology behind the mercury ion atomic clock and a DSAC mission overview are presented. Example deep space applications of DSAC, including navigation of a Mars orbiter and Europa flyby gravity science, highlight the benefits of DSAC-enabled one-way Doppler tracking.

The effects of illumination on deep levels observed in as-grown and low-energy electron irradiated high-purity semi-insulating 4H-SiC

NASA Astrophysics Data System (ADS)

Alfieri, G.; Knoll, L.; Kranz, L.; Sundaramoorthy, V.

2018-05-01

High-purity semi-insulating 4H-SiC can find a variety of applications, ranging from power electronics to quantum computing applications. However, data on the electronic properties of deep levels in this material are scarce. For this reason, we present a deep level transient spectroscopy study on HPSI 4H-SiC substrates, both as-grown and irradiated with low-energy electrons (to displace only C-atoms). Our investigation reveals the presence of four deep levels with activation energies in the 0.4-0.9 eV range. The concentrations of three of these levels increase by at least one order of magnitude after irradiation. Furthermore, we analyzed the behavior of these traps under sub- and above-band gap illumination. The nature of the traps is discussed in the light of the present data and results reported in the literature.

High virus-to-cell ratios indicate ongoing production of viruses in deep subsurface sediments.

PubMed

Engelhardt, Tim; Kallmeyer, Jens; Cypionka, Heribert; Engelen, Bert

2014-07-01

Marine sediments cover two-thirds of our planet and harbor huge numbers of living prokaryotes. Long-term survival of indigenous microorganisms within the deep subsurface is still enigmatic, as sources of organic carbon are vanishingly small. To better understand controlling factors of microbial life, we have analyzed viral abundance within a comprehensive set of globally distributed subsurface sediments. Phages were detected by electron microscopy in deep (320 m below seafloor), ancient (∼14 Ma old) and the most oligotrophic subsurface sediments of the world's oceans (South Pacific Gyre (SPG)). The numbers of viruses (10(4)-10(9) cm(-3), counted by epifluorescence microscopy) generally decreased with sediment depth, but always exceeded the total cell counts. The enormous numbers of viruses indicate their impact as a controlling factor for prokaryotic mortality in the marine deep biosphere. The virus-to-cell ratios increased in deeper and more oligotrophic layers, exhibiting values of up to 225 in the deep subsurface of the SPG. High numbers of phages might be due to absorption onto the sediment matrix and a diminished degradation by exoenzymes. However, even in the oldest sediments, microbial communities are capable of maintaining viral populations, indicating an ongoing viral production and thus, viruses provide an independent indicator for microbial life in the marine deep biosphere.

DEEP SPACE: High Resolution VR Platform for Multi-user Interactive Narratives

NASA Astrophysics Data System (ADS)

Kuka, Daniela; Elias, Oliver; Martins, Ronald; Lindinger, Christopher; Pramböck, Andreas; Jalsovec, Andreas; Maresch, Pascal; Hörtner, Horst; Brandl, Peter

DEEP SPACE is a large-scale platform for interactive, stereoscopic and high resolution content. The spatial and the system design of DEEP SPACE are facing constraints of CAVETM-like systems in respect to multi-user interactive storytelling. To be used as research platform and as public exhibition space for many people, DEEP SPACE is capable to process interactive, stereoscopic applications on two projection walls with a size of 16 by 9 meters and a resolution of four times 1080p (4K) each. The processed applications are ranging from Virtual Reality (VR)-environments to 3D-movies to computationally intensive 2D-productions. In this paper, we are describing DEEP SPACE as an experimental VR platform for multi-user interactive storytelling. We are focusing on the system design relevant for the platform, including the integration of the Apple iPod Touch technology as VR control, and a special case study that is demonstrating the research efforts in the field of multi-user interactive storytelling. The described case study, entitled "Papyrate's Island", provides a prototypical scenario of how physical drawings may impact on digital narratives. In this special case, DEEP SPACE helps us to explore the hypothesis that drawing, a primordial human creative skill, gives us access to entirely new creative possibilities in the domain of interactive storytelling.

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

PubMed

Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

2016-09-01

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

How to study deep roots—and why it matters

PubMed Central

Maeght, Jean-Luc; Rewald, Boris; Pierret, Alain

2013-01-01

The drivers underlying the development of deep root systems, whether genetic or environmental, are poorly understood but evidence has accumulated that deep rooting could be a more widespread and important trait among plants than commonly anticipated from their share of root biomass. Even though a distinct classification of “deep roots” is missing to date, deep roots provide important functions for individual plants such as nutrient and water uptake but can also shape plant communities by hydraulic lift (HL). Subterranean fauna and microbial communities are highly influenced by resources provided in the deep rhizosphere and deep roots can influence soil pedogenesis and carbon storage.Despite recent technological advances, the study of deep roots and their rhizosphere remains inherently time-consuming, technically demanding and costly, which explains why deep roots have yet to be given the attention they deserve. While state-of-the-art technologies are promising for laboratory studies involving relatively small soil volumes, they remain of limited use for the in situ observation of deep roots. Thus, basic techniques such as destructive sampling or observations at transparent interfaces with the soil (e.g., root windows) which have been known and used for decades to observe roots near the soil surface, must be adapted to the specific requirements of deep root observation. In this review, we successively address major physical, biogeochemical and ecological functions of deep roots to emphasize the significance of deep roots and to illustrate the yet limited knowledge. In the second part we describe the main methodological options to observe and measure deep roots, providing researchers interested in the field of deep root/rhizosphere studies with a comprehensive overview. Addressed methodologies are: excavations, trenches and soil coring approaches, minirhizotrons (MR), access shafts, caves and mines, and indirect approaches such as tracer-based techniques. PMID:23964281

Constraining the source location of the 30 May 2015 (Mw 7.9) Bonin deep-focus earthquake using seismogram envelopes of high-frequency P waveforms: Occurrence of deep-focus earthquake at the bottom of a subducting slab

NASA Astrophysics Data System (ADS)

Takemura, Shunsuke; Maeda, Takuto; Furumura, Takashi; Obara, Kazushige

2016-05-01

In this study, the source location of the 30 May 2015 (Mw 7.9) deep-focus Bonin earthquake was constrained using P wave seismograms recorded across Japan. We focus on propagation characteristics of high-frequency P wave. Deep-focus intraslab earthquakes typically show spindle-shaped seismogram envelopes with peak delays of several seconds and subsequent long-duration coda waves; however, both the main shock and aftershock of the 2015 Bonin event exhibited pulse-like P wave propagations with high apparent velocities (~12.2 km/s). Such P wave propagation features were reproduced by finite-difference method simulations of seismic wave propagation in the case of slab-bottom source. The pulse-like P wave seismogram envelopes observed from the 2015 Bonin earthquake show that its source was located at the bottom of the Pacific slab at a depth of ~680 km, rather than within its middle or upper regions.

Deep Extragalactic X-Ray Surveys

NASA Astrophysics Data System (ADS)

Brandt, W. N.; Hasinger, G.

2005-09-01

Deep surveys of the cosmic X-ray background are reviewed in the context of observational progress enabled by the Chandra X-Ray Observatory and the X-Ray Multi-Mirror Mission-Newton. The sources found by deep surveys are described along with their redshift and luminosity distributions, and the effectiveness of such surveys at selecting active galactic nuclei (AGN) is assessed. Some key results from deep surveys are highlighted, including (a) measurements of AGN evolution and the growth of supermassive black holes, (b) constraints on the demography and physics of high-redshift AGN, (c) the X-ray AGN content of infrared and submillimeter galaxies, and (d) X-ray emission from distant starburst and normal galaxies. We also describe some outstanding problems and future prospects for deep extragalactic X-ray surveys.

Comparison of hospitalization among German coastal and deep sea fishermen.

PubMed

Oldenburg, M; Harth, V; Manuwald, U

2015-08-01

This study aims to compare the hospitalization of German fishermen employed on German-flagged fishing vessels with that of the general German population in consideration of differences between coastal and deep sea fishery. By means of a database from the health insurance company for seafarers, diagnoses of German fishermen treated in German hospitals were determined from January 1997 to December 2007. Compared with the general German population, the fishermen's risk for specific diseases leading to hospitalization was calculated as standardized hospitalization ratio (SHR). Compared with the German reference population, German fishermen showed a considerably high SHR for malignant neoplasms at all sites (SHR 1.46; 95% CI 1.37-1.56), for respiratory cancer, and for non-Hodgkin lymphoma (NHL). Furthermore, they had more often been hospitalized due to diabetes mellitus, diseases of the respiratory and digestive systems as well as due to injury and poisoning. The risk for respiratory cancer and NHL among coastal fishermen exceeded that of deep sea fishermen, whereas the latter displayed a considerably higher SHR for diabetes mellitus, diseases of the respiratory system and metabolic and nutritional disorders. In contrast, the SHR for hypertensive and ischemic heart diseases was decreased among deep sea fishermen. Less qualified deep sea fishermen displayed a considerably higher SHR for malignant neoplasms at all sites than more highly qualified ones. Fishery is still an occupation which poses a high risk for malignant neoplasms and injuries. This is likely due to lifestyle and work-related factors. Further studies are needed to evaluate the different working and living conditions of coastal and deep sea fishermen.

Fungal diversity in deep-sea sediments of a hydrothermal vent system in the Southwest Indian Ridge

NASA Astrophysics Data System (ADS)

Xu, Wei; Gong, Lin-feng; Pang, Ka-Lai; Luo, Zhu-Hua

2018-01-01

Deep-sea hydrothermal sediment is known to support remarkably diverse microbial consortia. In deep sea environments, fungal communities remain less studied despite their known taxonomic and functional diversity. High-throughput sequencing methods have augmented our capacity to assess eukaryotic diversity and their functions in microbial ecology. Here we provide the first description of the fungal community diversity found in deep sea sediments collected at the Southwest Indian Ridge (SWIR) using culture-dependent and high-throughput sequencing approaches. A total of 138 fungal isolates were cultured from seven different sediment samples using various nutrient media, and these isolates were identified to 14 fungal taxa, including 11 Ascomycota taxa (7 genera) and 3 Basidiomycota taxa (2 genera) based on internal transcribed spacers (ITS1, ITS2 and 5.8S) of rDNA. Using illumina HiSeq sequencing, a total of 757,467 fungal ITS2 tags were recovered from the samples and clustered into 723 operational taxonomic units (OTUs) belonging to 79 taxa (Ascomycota and Basidiomycota contributed to 99% of all samples) based on 97% sequence similarity. Results from both approaches suggest that there is a high fungal diversity in the deep-sea sediments collected in the SWIR and fungal communities were shown to be slightly different by location, although all were collected from adjacent sites at the SWIR. This study provides baseline data of the fungal diversity and biogeography, and a glimpse to the microbial ecology associated with the deep-sea sediments of the hydrothermal vent system of the Southwest Indian Ridge.

Numerical and Experimental Study on Manufacture of a Novel High-Capacity Engine Oil Pan Subjected to Hydro-Mechanical Deep Drawing

NASA Astrophysics Data System (ADS)

Chen, D. Y.; Xu, Y.; Zhang, S. H.; El-Aty, A. Abd; Ma, Y.

2017-09-01

The oil pan is equipped at the bottom of engine crankcase of the automobile to prevent impurity and collect the lubrication oil from the surfaces of the engine which is helpful for heat dissipation and oxidation prevention. The present study aims at manufacturing a novel high-capacity engine oil pan, which is considered as a complex shaped component with features of thin wall, large size and asymmetric deep cavity through both numerical and experimental methods. The result indicated that it is difficult to form the current part through the common deep drawing process. Accordingly, the hydro-mechanical deep drawing technology was conducted, which consisted of two steps, previous local drawing and the final integral deep drawing with hydraulic pressure. The finite element analysis (FEA) was carried out to investigate the influence of initial blank dimension and the key process parameters such as loading path, draw-bead force and fillet radius on the formability of the sheet blank. Compared with the common deep drawing, the limit drawing ratio by hydro-mechanical deep drawing can be increased from 2.34 to 2.77, while the reduction in blank wall thickness can be controlled in the range of 28%. The formability is greatly improved without any defects such as crack and wrinkle by means of parameters optimisation. The results gained from simulation keep a reasonable agreement with that obtained from experiment trials.

Lunar Volatile System Dynamics: Observations Enabled by the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Honniball, C. I.; Lucey, P. G.; Petro, N.; Hurley, D.; Farrell, W.

2018-02-01

A UV spectrometer-imager and IR spectrometer are proposed to solve questions regarding the lunar volatile system. The instrument takes advantage of highly elliptical orbits and the thermal management system of the Deep Space Gateway.

The JPL optical communications telescope laboratory (OCTL) test bed for the future optical Deep Space Network

NASA Technical Reports Server (NTRS)

Wilson, K. E.; Page, N.; Wu, J.; Srinivasan, M.

2003-01-01

Relative to RF, the lower power-consumption and lower mass of high bandwidth optical telecommunications make this technology extremely attractive for returning data from future NASA/JPL deep space probes.

Using The Global Positioning System For Earth Orbiter and Deep Space Network

NASA Technical Reports Server (NTRS)

Lichten, Stephen M.; Haines, Bruce J.; Young, Lawrence E.; Dunn, Charles; Srinivasan, Jeff; Sweeney, Dennis; Nandi, Sumita; Spitzmesser, Don

1994-01-01

The Global Positioning System (GPS) can play a major role in supporting orbit and trajectory determination for spacecraft in a wide range of applications, including low-Earth, high-earth, and even deep space (interplanetary) tracking.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

Numerical experiments of volcanic dominated rifts and passive margins

NASA Astrophysics Data System (ADS)

Korchinski, Megan; Teyssier, Christian; Rey, Patrice; Whitney, Donna; Mondy, Luke

2017-04-01

Continental rifting is driven by plate tectonic forces (passive rifting), thermal thinning of the lithosphere over a hotspot (active rifting), or a combination of the two. Successful rifts develop into passive margins where pre-drift stretching is accompanied by normal faulting, clastic sedimentation, and various degrees of magmatism. The structure of volcanic passive margins (VPM) differs substantially from margins that are dominated by sedimentation. VPMs are typically narrow, with a lower continental crust that is intruded by magma and can flow as a low-viscosity layer. To investigate the role of the deep crust in the early development of VPMs, we have developed a suite of 2D thermomechanical numerical experiments (Underworld code) in which the density and viscosity of the deep crust and the density of the rift basin fill are systematically varied. Our experiments show that, for a given rifting velocity, the viscosity of the deep crust and the density of the rift basin fill exert primary controls on early VPM development. The viscosity of the deep crust controls the degree to which the shallow crust undergoes localised faulting or distributed thinning. A weak deep crust localises rifting and is efficiently exhumed to the near-surface, whereas a strong deep crust distributes shallow crust extension and remains buried. A high density rift basin fill results in gravitational loading and increased subsidence rate in cases in which the viscosity of the deep crust is sufficiently low to allow that layer to be displaced by the sinking basin fill. At the limit, a low viscosity deep crust overlain by a thick basalt-dominated fill generates a gravitational instability, with a drip of cool basalt that sinks and ponds at the Moho. Experiment results indicate that the deep crust plays a critical role in the dynamic development of volcanic dominated rifts and passive margins. During rifting, the deep continental crust is heated and readily responds to solicitations of the shallow crust (rooting of normal faults, exhumation of the deep crust in normal fault footwalls). Gravitational instabilities caused by high density rift infill similar to those observed in our numerical experiments may be present in the Mesoproterozoic ( 1100 Ma) North American Midcontinent Rift System (MRS). The MRS is a failed rift that is filled with >20 km of dominantly basaltic volcanic deposits, and therefore represents an end member VPM (high density basin fill) where the initial structure of a pre-drift VPM is preserved. Magmatism occurred in two pulses over <15 Ma involving deep mantle melting first (>150 km), then shallow melting (40-70 km). Post-rift subsidence accumulated up to 10 km of clastic sediments in the center of the basin. Evidence of cool, dense rocks sinking into a low-viscosity deep crust as predicted in our numerical experiments may be present in the western arm of the MRS, where crustal density analyses suggest the presence of dense bodies (eclogite) at the base of the crust.

Deep learning with convolutional neural network in radiology.

PubMed

Yasaka, Koichiro; Akai, Hiroyuki; Kunimatsu, Akira; Kiryu, Shigeru; Abe, Osamu

2018-04-01

Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the learning process is not required. Important features can be automatically learned. Thanks to the development of hardware and software in addition to techniques regarding deep learning, application of this technique to radiological images for predicting clinically useful information, such as the detection and the evaluation of lesions, etc., are beginning to be investigated. This article illustrates basic technical knowledge regarding deep learning with CNNs along the actual course (collecting data, implementing CNNs, and training and testing phases). Pitfalls regarding this technique and how to manage them are also illustrated. We also described some advanced topics of deep learning, results of recent clinical studies, and the future directions of clinical application of deep learning techniques.

Effect of swift heavy ion irradiation on deep levels in Au /n-Si (100) Schottky diode studied by deep level transient spectroscopy

NASA Astrophysics Data System (ADS)

Kumar, Sandeep; Katharria, Y. S.; Kumar, Sugam; Kanjilal, D.

2007-12-01

In situ deep level transient spectroscopy has been applied to investigate the influence of 100MeV Si7+ ion irradiation on the deep levels present in Au/n-Si (100) Schottky structure in a wide fluence range from 5×109to1×1012ions cm-2. The swift heavy ion irradiation introduces a deep level at Ec-0.32eV. It is found that initially, trap level concentration of the energy level at Ec-0.40eV increases with irradiation up to a fluence value of 1×1010cm-2 while the deep level concentration decreases as irradiation fluence increases beyond the fluence value of 5×1010cm-2. These results are discussed, taking into account the role of energy transfer mechanism of high energy ions in material.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Introduction: From pathogenesis to therapy, deep endometriosis remains a source of controversy.

PubMed

Donnez, Jacques

2017-12-01

Deep endometriosis remains a source of controversy. A number of theories may explain its pathogenesis and many arguments support the hypothesis that genetic or epigenetic changes are a prerequisite for development of lesions into deep endometriosis. Deep endometriosis is frequently responsible for pelvic pain, dysmenorrhea, and/or deep dyspareunia, but can also cause obstetrical complications. Diagnosis may be improved by high-quality imaging. Therapeutic approaches are a source of contention as well. In this issue's Views and Reviews, medical and surgical strategies are discussed, and it is emphasized that treatment should be designed according to a patient's symptoms and individual needs. It is also vital that referral centers have the knowledge and experience to treat deep endometriosis medically and/or surgically. The debate must continue because emerging trends in therapy need to be followed and investigated for optimal management. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Noé, Frank

2018-06-01

Inspired by the success of deep learning techniques in the physical and chemical sciences, we apply a modification of an autoencoder type deep neural network to the task of dimension reduction of molecular dynamics data. We can show that our time-lagged autoencoder reliably finds low-dimensional embeddings for high-dimensional feature spaces which capture the slow dynamics of the underlying stochastic processes—beyond the capabilities of linear dimension reduction techniques.

Widespread Miocene deep-sea hiatuses: coincidence with periods of global cooling.

USGS Publications Warehouse

Barron, J.A.; Keller, G.

1982-01-01

High-resolution biostratigraphic analyses of Miocene deep-sea cores reveal eight intervals of widespread hiatuses in the world ocean. In complete sections these hiatuses correspond to intervals of cool faunal and floral assemblages, rapid enrichment of delta 18O, and sea-level regressions. These factors suggest that Miocene deep-sea hiatuses result from an increased intensity of circulation and corrosiveness of bottom currents during periods of increased polar refrigeration.-Authors

A randomised crossover trial of the acute effects of a deep-fried Mars bar or porridge on the cerebral vasculature.

PubMed

Dunn, William G; Walters, Matthew R

2014-11-01

The deep-fried Mars bar has been cited as 'all that is wrong with the high-fat, high-sugar Scottish diet'. We investigated the effect of ingestion of a deep-fried Mars bar or porridge on cerebrovascular reactivity. We hypothesised that deep-fried Mars bar ingestion would impair cerebrovascular reactivity, which is associated with increased risk of ischaemic stroke. Twenty-four fasted volunteers were randomised to receive a deep-fried Mars bar and then porridge (control), or vice-versa. We used transcranial Doppler ultrasound to calculate Breath Holding Index as a surrogate measure of cerebrovascular reactivity. Change in Breath Holding Index post-ingestion was the primary outcome measure. Twenty-four healthy adults (mean (SD) age 21.5 (1.7) years, 14 males) completed the protocol. Deep-fried Mars bar ingestion caused a non-significant reduction in cerebrovascular reactivity relative to control (mean difference in absolute Breath Holding Index after deep-fried Mars bar versus porridge -0.11, p = 0.40). Comparison of the difference between the absolute change in Breath Holding Index between genders demonstrated a significant impairment of cerebrovascular reactivity in males (mean difference women minus men of 0.65, 95% CI 0.30 to 1.00, p = 0.0003). Ingestion of a bolus of sugar and fat caused no overall difference in cerebrovascular reactivity, but there was a modest decrease in males. Impaired cerebrovascular reactivity is associated with increased stroke risk, and therefore deep-fried Mars bar ingestion may acutely contribute to cerebral hypoperfusion in men. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Making sense of deep sequencing

PubMed Central

Goldman, D.; Domschke, K.

2016-01-01

This review, the first of an occasional series, tries to make sense of the concepts and uses of deep sequencing of polynucleic acids (DNA and RNA). Deep sequencing, synonymous with next-generation sequencing, high-throughput sequencing and massively parallel sequencing, includes whole genome sequencing but is more often and diversely applied to specific parts of the genome captured in different ways, for example the highly expressed portion of the genome known as the exome and portions of the genome that are epigenetically marked either by DNA methylation, the binding of proteins including histones, or that are in different configurations and thus more or less accessible to enzymes that cleave DNA. Deep sequencing of RNA (RNASeq) reverse-transcribed to complementary DNA is invaluable for measuring RNA expression and detecting changes in RNA structure. Important concepts in deep sequencing include the length and depth of sequence reads, mapping and assembly of reads, sequencing error, haplotypes, and the propensity of deep sequencing, as with other types of ‘big data’, to generate large numbers of errors, requiring monitoring for methodologic biases and strategies for replication and validation. Deep sequencing yields a unique genetic fingerprint that can be used to identify a person, and a trove of predictors of genetic medical diseases. Deep sequencing to identify epigenetic events including changes in DNA methylation and RNA expression can reveal the history and impact of environmental exposures. Because of the power of sequencing to identify and deliver biomedically significant information about a person and their blood relatives, it creates ethical dilemmas and practical challenges in research and clinical care, for example the decision and procedures to report incidental findings that will increasingly and frequently be discovered. PMID:24925306

Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks.

PubMed

Pan, Xiaoyong; Shen, Hong-Bin

2018-05-02

RNA-binding proteins (RBPs) take over 5∼10% of the eukaryotic proteome and play key roles in many biological processes, e.g. gene regulation. Experimental detection of RBP binding sites is still time-intensive and high-costly. Instead, computational prediction of the RBP binding sites using pattern learned from existing annotation knowledge is a fast approach. From the biological point of view, the local structure context derived from local sequences will be recognized by specific RBPs. However, in computational modeling using deep learning, to our best knowledge, only global representations of entire RNA sequences are employed. So far, the local sequence information is ignored in the deep model construction process. In this study, we present a computational method iDeepE to predict RNA-protein binding sites from RNA sequences by combining global and local convolutional neural networks (CNNs). For the global CNN, we pad the RNA sequences into the same length. For the local CNN, we split a RNA sequence into multiple overlapping fixed-length subsequences, where each subsequence is a signal channel of the whole sequence. Next, we train deep CNNs for multiple subsequences and the padded sequences to learn high-level features, respectively. Finally, the outputs from local and global CNNs are combined to improve the prediction. iDeepE demonstrates a better performance over state-of-the-art methods on two large-scale datasets derived from CLIP-seq. We also find that the local CNN run 1.8 times faster than the global CNN with comparable performance when using GPUs. Our results show that iDeepE has captured experimentally verified binding motifs. https://github.com/xypan1232/iDeepE. xypan172436@gmail.com or hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online.

[Risk factors associated with the severity of pulmonary embolism in patients with acute deep venous thrombosis of lower extremities].

PubMed

Luo, Xiaoyun; Zhang, Fuxian; Zhang, Changming; Hu, Lu; Feng, Yaping; Liang, Gangzhu; Niu, Luyuan; Zhang, Huan; Cheng, Long; Qi, Haoshan

2015-08-01

To identify the risk factors associated with the severity of pulmonary embolism among patients with deep venous thrombosis of lower extremities. This prospective study enrolled 208 patients with acute deep venous thrombosis to screen for pulmonary embolism between July 2010 and July 2012 in Beijing Shijitan Hospital. There were 101 male and 107 female patients, with a mean age of (59 ± 16) years. Gender, age, extension, side of lower extremities of deep venous thrombosis was analyzed by χ² test. Ordinal Logistic regression was used to determine risk factors associated with severity of pulmonary embolism. There were 83 patients with iliofemoral deep venous thrombosis, 102 patients with femoropopliteal and 23 patients with calf deep venous thrombosis. Pulmonary embolism was detected in 70 patients with the incidence of 33.7%. Pulmonary embolism was significantly correlated with extension (χ² = 17.286, P = 0.004) and sides (χ² = 15.602, P = 0.008) of deep venous thrombosis, not with age (χ² = 7.099, P = 0.260), gender (χ² = 7.014, P = 0.067), thrombotic risk factors (χ² = 3.335, P = 0.345) in univariate analysis. Results of multivariate ordinal logistic regression showed that iliofemoral vein thrombosis (OR = 6.172, 95% CI: 1.590 to 23.975, P = 0.009) and bilateral venous thrombosis (OR = 7.140, 95% CI: 2.406 to 24.730, P = 0.001) are associated with more serious pulmonary embolism. Incidence of pulmonary embolism is still high in patients with deep venous thrombosis. Extensive iliofemoral and bilateral vein thrombosis may increase risk of severity of pulmonary embolism. Clinicians should pay more attention to these high-risk patients.

Precision-cut liver slices to investigate responsiveness of deep-sea fish to contaminants at high pressure.

PubMed

Lemaire, Benjamin; Debier, Cathy; Calderon, Pedro Buc; Thomé, Jean Pierre; Stegeman, John; Mork, Jarle; Rees, Jean François

2012-09-18

While deep-sea fish accumulate high levels of persistent organic pollutants (POPs), the toxicity associated with this contamination remains unknown. Indeed, the recurrent collection of moribund individuals precludes experimental studies to investigate POP effects in this fauna. We show that precision-cut liver slices (PCLS), an in vitro tool commonly used in human and rodent toxicology, can overcome such limitation. This technology was applied to individuals of the deep-sea grenadier Coryphaenoides rupestris directly upon retrieval from 530-m depth in Trondheimsfjord (Norway). PCLS remained viable and functional for 15 h when maintained in an appropriate culture media at 4 °C. This allowed experimental exposure of liver slices to the model POP 3-methylcholanthrene (3-MC; 25 μM) at levels of hydrostatic pressure mimicking shallow (0.1 megapascal or MPa) and deep-sea (5-15 MPa; representative of 500-1500 m depth) environments. As in shallow water fish, 3-MC induced the transcription of the detoxification enzyme cytochrome P4501A (CYP1A; a biomarker of exposure to POPs). This induction was diminished at elevated pressure, suggesting a limited responsiveness of C. rupestris toward POPs in its native environment. This very first in vitro toxicological investigation on a deep-sea fish opens the route for understanding pollutants effects in this highly exposed fauna.

Advanced Microelectronics Technologies for Future Small Satellite Systems

NASA Technical Reports Server (NTRS)

Alkalai, Leon

1999-01-01

Future small satellite systems for both Earth observation as well as deep-space exploration are greatly enabled by the technological advances in deep sub-micron microelectronics technologies. Whereas these technological advances are being fueled by the commercial (non-space) industries, more recently there has been an exciting new synergism evolving between the two otherwise disjointed markets. In other words, both the commercial and space industries are enabled by advances in low-power, highly integrated, miniaturized (low-volume), lightweight, and reliable real-time embedded systems. Recent announcements by commercial semiconductor manufacturers to introduce Silicon On Insulator (SOI) technology into their commercial product lines is driven by the need for high-performance low-power integrated devices. Moreover, SOI has been the technology of choice for many space semiconductor manufacturers where radiation requirements are critical. This technology has inherent radiation latch-up immunity built into the process, which makes it very attractive to space applications. In this paper, we describe the advanced microelectronics and avionics technologies under development by NASA's Deep Space Systems Technology Program (also known as X2000). These technologies are of significant benefit to both the commercial satellite as well as the deep-space and Earth orbiting science missions. Such a synergistic technology roadmap may truly enable quick turn-around, low-cost, and highly capable small satellite systems for both Earth observation as well as deep-space missions.

How safe is deep sedation or general anesthesia while providing dental care?

PubMed

Bennett, Jeffrey D; Kramer, Kyle J; Bosack, Robert C

2015-09-01

Deep sedation and general anesthesia are administered daily in dental offices, most commonly by oral and maxillofacial surgeons and dentist anesthesiologists. The goal of deep sedation or general anesthesia is to establish a safe environment in which the patient is comfortable and cooperative. This requires meticulous care in which the practitioner balances the patient's depth of sedation and level of responsiveness while maintaining airway integrity, ventilation, and cardiovascular hemodynamics. Using the available data and informational reports, the authors estimate that the incidence of death and brain injury associated with deep sedation or general anesthesia administered by all dentists most likely exceeds 1 per month. Airway compromise is a significant contributing factor to anesthetic complications. The American Society of Anesthesiology closed claim analysis also concluded that human error contributed highly to anesthetic mishaps. The establishment of a patient safety database for anesthetic management in dentistry would allow for a more complete assessment of morbidity and mortality that could direct efforts to further increase safe anesthetic care. Deep sedation and general anesthesia can be safely administered in the dental office. Optimization of patient care requires appropriate patient selection, selection of appropriate anesthetic agents, utilization of appropriate monitoring, and a highly trained anesthetic team. Achieving a highly trained anesthetic team requires emergency management preparation that can foster decision making, leadership, communication, and task management. Copyright © 2015 American Dental Association. Published by Elsevier Inc. All rights reserved.

Origin and distribution of the organic matter in the distal lobe of the Congo deep-sea fan - A Rock-Eval survey

NASA Astrophysics Data System (ADS)

Baudin, François; Stetten, Elsa; Schnyder, Johann; Charlier, Karine; Martinez, Philippe; Dennielou, Bernard; Droz, Laurence

2017-08-01

The Congo River, the second largest river in the world, is a major source of organic matter for the deep Atlantic Ocean because of the connection of its estuary to the deep offshore area by a submarine canyon which feeds a vast deep-sea fan. The lobe zone of this deep-sea fan is the final receptacle of the sedimentary inputs presently channelled by the canyon and covers an area of 2500 km². The quantity and the source of organic matter preserved in recent turbiditic sediments from the distal lobe of the Congo deep-sea fan were assessed using Rock-Eval pyrolysis analyses. Six sites, located at approximately 5000 m water-depth, were investigated. The mud-rich sediments of the distal lobe contain high amounts of organic matter ( 3.5 to 4% Corg), the origin of which is a mixture of terrestrial higher-plant debris, soil organic matter and deeply oxidized phytoplanktonic material. Although the respective contribution of terrestrial and marine sources of organic matter cannot be precisely quantified using Rock-Eval analyses, the terrestrial fraction is dominant according to similar hydrogen and oxygen indices of both suspended and bedload sediments from the Congo River and that deposited in the lobe complex. The Rock-Eval signature supports the 70% to 80% of the terrestrial fraction previously estimated using C/N and δ13Corg data. In the background sediment, the organic matter distribution is homogeneous at different scales, from a single turbiditic event to the entire lobe, and changes in accumulation rates only have a limited effect on the quantity and quality of the preserved organic matter. Peculiar areas with chemosynthetic bivalves and/or bacterial mats, explored using ROV Victor 6000, show a Rock-Eval signature similar to background sediment. This high organic carbon content associated to high sedimentation rates (> 2 to 20 mm.yr-1) in the Congo distal lobe complex implies a high burial rate for organic carbon. Consequently, the Congo deep-sea fan represents an enormous sink of terrestrial organic matter when compared to other turbiditic systems over the world.

Cryogenically cooled low-noise amplifier for radio-astronomical observations and centimeter-wave deep-space communications systems

NASA Astrophysics Data System (ADS)

Vdovin, V. F.; Grachev, V. G.; Dryagin, S. Yu.; Eliseev, A. I.; Kamaletdinov, R. K.; Korotaev, D. V.; Lesnov, I. V.; Mansfeld, M. A.; Pevzner, E. L.; Perminov, V. G.; Pilipenko, A. M.; Sapozhnikov, B. D.; Saurin, V. P.

2016-01-01

We report a design solution for a highly reliable, low-noise and extremely efficient cryogenically cooled transmit/receive unit for a large antenna system meant for radio-astronomical observations and deep-space communications in the X band. We describe our design solution and the results of a series of laboratory and antenna tests carried out in order to investigate the properties of the cryogenically cooled low-noise amplifier developed. The transmit/receive unit designed for deep-space communications (Mars missions, radio observatories located at Lagrangian point L2, etc.) was used in practice for communication with live satellites including "Radioastron" observatory, which moves in a highly elliptical orbit.

LMT imaging of the Extended Groth Strip: a search for the high-redshift tail of the sub-mm galaxy population

NASA Astrophysics Data System (ADS)

Aretxaga, Itziar

2015-08-01

The combination of short and long-wavelength deep (sub-)mm surveys can effectively be used to identify high-redshift sub-millimeter galaxies (z>4). Having star formation rates in excess of 500 Msun/yr, these bright (sub-)mm sources have been identified with the progenitors of massive elliptical galaxies undergoing rapid growth. With this purpose in mind, we are surveying a 20 sq. arcmin field within the Extended Groth Strip with the 1.1mm AzTEC camera mounted at the Large Millimeter Telescope that overlaps with the deep 450/850um SCUBA-2 Cosmology Legacy Survey and the CANDELS deep NIR imaging. The improved beamsize of the LMT (8”) over previous surveys aids the identification of the most prominent optical/IR counterparts. We discuss the high-redshift candidates found.

Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms.

PubMed

Li, Hui; Giger, Maryellen L; Huynh, Benjamin Q; Antropova, Natalia O

2017-10-01

To evaluate deep learning in the assessment of breast cancer risk in which convolutional neural networks (CNNs) with transfer learning are used to extract parenchymal characteristics directly from full-field digital mammographic (FFDM) images instead of using computerized radiographic texture analysis (RTA), 456 clinical FFDM cases were included: a "high-risk" BRCA1/2 gene-mutation carriers dataset (53 cases), a "high-risk" unilateral cancer patients dataset (75 cases), and a "low-risk dataset" (328 cases). Deep learning was compared to the use of features from RTA, as well as to a combination of both in the task of distinguishing between high- and low-risk subjects. Similar classification performances were obtained using CNN [area under the curve [Formula: see text]; standard error [Formula: see text

From top to bottom: Do Lake Trout diversify along a depth gradient in Great Bear Lake, NT, Canada?

USGS Publications Warehouse

Chavarie, Louise; Howland, Kimberly L.; Harris, Les N.; Hansen, Michael J.; Harford, William J.; Gallagher, Colin P.; Baillie, Shauna M.; Malley, Brendan; Tonn, William M.; Muir, Andrew M.; Krueger, Charles C.

2018-01-01

Depth is usually considered the main driver of Lake Trout intraspecific diversity across lakes in North America. Given that Great Bear Lake is one of the largest and deepest freshwater systems in North America, we predicted that Lake Trout intraspecific diversity to be organized along a depth axis within this system. Thus, we investigated whether a deep-water morph of Lake Trout co-existed with four shallow-water morphs previously described in Great Bear Lake. Morphology, neutral genetic variation, isotopic niches, and life-history traits of Lake Trout across depths (0–150 m) were compared among morphs. Due to the propensity of Lake Trout with high levels of morphological diversity to occupy multiple habitat niches, a novel multivariate grouping method using a suite of composite variables was applied in addition to two other commonly used grouping methods to classify individuals. Depth alone did not explain Lake Trout diversity in Great Bear Lake; a distinct fifth deep-water morph was not found. Rather, Lake Trout diversity followed an ecological continuum, with some evidence for adaptation to local conditions in deep-water habitat. Overall, trout caught from deep-water showed low levels of genetic and phenotypic differentiation from shallow-water trout, and displayed higher lipid content (C:N ratio) and occupied a higher trophic level that suggested an potential increase of piscivory (including cannibalism) than the previously described four morphs. Why phenotypic divergence between shallow- and deep-water Lake Trout was low is unknown, especially when the potential for phenotypic variation should be high in deep and large Great Bear Lake. Given that variation in complexity of freshwater environments has dramatic consequences for divergence, variation in the complexity in Great Bear Lake (i.e., shallow being more complex than deep), may explain the observed dichotomy in the expression of intraspecific phenotypic diversity between shallow- vs. deep-water habitats. The ambiguity surrounding mechanisms driving divergence of Lake Trout in Great Bear Lake should be seen as reflective of the highly variable nature of ecological opportunity and divergent natural selection itself.

From top to bottom: Do Lake Trout diversify along a depth gradient in Great Bear Lake, NT, Canada?

PubMed

Chavarie, Louise; Howland, Kimberly L; Harris, Les N; Hansen, Michael J; Harford, William J; Gallagher, Colin P; Baillie, Shauna M; Malley, Brendan; Tonn, William M; Muir, Andrew M; Krueger, Charles C

2018-01-01

Depth is usually considered the main driver of Lake Trout intraspecific diversity across lakes in North America. Given that Great Bear Lake is one of the largest and deepest freshwater systems in North America, we predicted that Lake Trout intraspecific diversity to be organized along a depth axis within this system. Thus, we investigated whether a deep-water morph of Lake Trout co-existed with four shallow-water morphs previously described in Great Bear Lake. Morphology, neutral genetic variation, isotopic niches, and life-history traits of Lake Trout across depths (0-150 m) were compared among morphs. Due to the propensity of Lake Trout with high levels of morphological diversity to occupy multiple habitat niches, a novel multivariate grouping method using a suite of composite variables was applied in addition to two other commonly used grouping methods to classify individuals. Depth alone did not explain Lake Trout diversity in Great Bear Lake; a distinct fifth deep-water morph was not found. Rather, Lake Trout diversity followed an ecological continuum, with some evidence for adaptation to local conditions in deep-water habitat. Overall, trout caught from deep-water showed low levels of genetic and phenotypic differentiation from shallow-water trout, and displayed higher lipid content (C:N ratio) and occupied a higher trophic level that suggested an potential increase of piscivory (including cannibalism) than the previously described four morphs. Why phenotypic divergence between shallow- and deep-water Lake Trout was low is unknown, especially when the potential for phenotypic variation should be high in deep and large Great Bear Lake. Given that variation in complexity of freshwater environments has dramatic consequences for divergence, variation in the complexity in Great Bear Lake (i.e., shallow being more complex than deep), may explain the observed dichotomy in the expression of intraspecific phenotypic diversity between shallow- vs. deep-water habitats. The ambiguity surrounding mechanisms driving divergence of Lake Trout in Great Bear Lake should be seen as reflective of the highly variable nature of ecological opportunity and divergent natural selection itself.

Bottom-up and top-down triggers of diversification: A new look at the evolutionary ecology of scavenging amphipods in the deep sea

NASA Astrophysics Data System (ADS)

Havermans, Charlotte; Smetacek, Victor

2018-05-01

The initial, anthropocentric view of the deep ocean was that of a hostile environment inhabited by organisms rendered lethargic by constant high pressure, low temperature and sparse food supply, hence evolving slowly. This conceptual framework of a spatially and temporally homogeneous, connected, strongly bottom-up controlled habitat implied a strong constraint on, or poor incentive for, speciation. Hence, the discovery in the late 1960s of high species diversity of abyssal benthic invertebrates came as a surprise. Since then, the slow-motion view of deep-sea ecology and evolution has speeded up and diversified in the light of increasing evidence accumulating from in situ visual observations complemented by molecular and other tools. The emerging picture is that of a much livelier, highly diversified and more complex deep-sea fauna than previously assumed. In this review we examine the consequences of the incoming information for developing a broader view of evolutionary ecology in the deep sea, and for scavenging amphipods in particular. We revisit the food supply to the deep-sea floor and hypothesize that the dead bodies of animals, ranging from zooplankton to large fish are likely to be a more important source of food than their friable faeces. Camera observations of baited traps indicate that amphipod carrion-feeders arrive within hours at the bait which continues to draw new individuals for days to months later, presumably by scent trails in tidal currents. We explore the different stages of food acquisition upon which natural selection may have acted, from detection to ingestion, and discuss the possibility of a broader range of food acquisition strategies, including predation and specializations. Although currently neglected in deep-sea ecology, top-down factors are likely to play a more important role in the evolution of deep-sea organisms. Predation on amphipods at baits by bathyal and abyssal fishes, and large predatory crustaceans in the hadal zone, is often observed. Finally, we develop hypotheses regarding the effects of past, present and imminent anthropogenic activities on scavenger biomass and how these can be tested with the most modern tools.

Testing deep-sea biodiversity paradigms on abyssal nematode genera and Acantholaimus species

NASA Astrophysics Data System (ADS)

Lins, Lidia; da Silva, Maria Cristina; Neres, Patrícia; Esteves, André Morgado; Vanreusel, Ann

2018-02-01

Biodiversity patterns in the deep sea have been extensively studied in the last decades. In this study, we investigated whether reputable concepts in deep-sea ecology also explain diversity and distribution patterns of nematode genera and species in the abyss. Among them, three paradigms were tackled: (1) the deep sea is a highly diverse environment at a local scale, while on a regional and even larger geographical scale, species and genus turnover is limited; (2) the biodiversity of deep-sea nematode communities changes with the nature and amount of organic matter input from the surface; and (3) patch-mosaic dynamics of the deep-sea environment drive local diversity. To test these hypotheses, diversity and density of nematode assemblages and of species of the genus Acantholaimus were studied along two abyssal E-W transects. These two transects were situated in the Southern Ocean ( 50°S) and the North Atlantic ( 10°N). Four different hierarchical scales were used to compare biodiversity: at the scale of cores, between stations from the same region, and between regions. Results revealed that the deep sea harbours a high diversity at a local scale (alpha diversity), but that turnover can be shaped by different environmental drivers. Therefore, these results question the second part of the paradigm about limited species turnover in the deep sea. Higher surface primary productivity was correlated with greater nematode densities, whereas diversity responses to the augmentation of surface productivity showed no trend. Areas subjected to a constant and low food input revealed similar nematode communities to other oligotrophic abyssal areas, while stations under high productivity were characterized by different dominant genera and Acantholaimus species, and by a generally low local diversity. Our results corroborate the species-energy hypothesis, where productivity can set a limit to the richness of an ecosystem. Finally, we observed no correlation between sediment variability and local diversity. Although differences in sediment variability were significant across stations, these had to be considered without effect on the nematode community structure in the studied abyssal areas.

From top to bottom: Do Lake Trout diversify along a depth gradient in Great Bear Lake, NT, Canada?

PubMed Central

Howland, Kimberly L.; Harris, Les N.; Hansen, Michael J.; Harford, William J.; Gallagher, Colin P.; Baillie, Shauna M.; Malley, Brendan; Tonn, William M.; Muir, Andrew M.; Krueger, Charles C.

2018-01-01

Depth is usually considered the main driver of Lake Trout intraspecific diversity across lakes in North America. Given that Great Bear Lake is one of the largest and deepest freshwater systems in North America, we predicted that Lake Trout intraspecific diversity to be organized along a depth axis within this system. Thus, we investigated whether a deep-water morph of Lake Trout co-existed with four shallow-water morphs previously described in Great Bear Lake. Morphology, neutral genetic variation, isotopic niches, and life-history traits of Lake Trout across depths (0–150 m) were compared among morphs. Due to the propensity of Lake Trout with high levels of morphological diversity to occupy multiple habitat niches, a novel multivariate grouping method using a suite of composite variables was applied in addition to two other commonly used grouping methods to classify individuals. Depth alone did not explain Lake Trout diversity in Great Bear Lake; a distinct fifth deep-water morph was not found. Rather, Lake Trout diversity followed an ecological continuum, with some evidence for adaptation to local conditions in deep-water habitat. Overall, trout caught from deep-water showed low levels of genetic and phenotypic differentiation from shallow-water trout, and displayed higher lipid content (C:N ratio) and occupied a higher trophic level that suggested an potential increase of piscivory (including cannibalism) than the previously described four morphs. Why phenotypic divergence between shallow- and deep-water Lake Trout was low is unknown, especially when the potential for phenotypic variation should be high in deep and large Great Bear Lake. Given that variation in complexity of freshwater environments has dramatic consequences for divergence, variation in the complexity in Great Bear Lake (i.e., shallow being more complex than deep), may explain the observed dichotomy in the expression of intraspecific phenotypic diversity between shallow- vs. deep-water habitats. The ambiguity surrounding mechanisms driving divergence of Lake Trout in Great Bear Lake should be seen as reflective of the highly variable nature of ecological opportunity and divergent natural selection itself. PMID:29566015

High latitude control on tropical North Pacific thermocline oxygen via deep ocean circulation: implications for atmospheric CO2 and N2O concentrations over TERM1.

NASA Astrophysics Data System (ADS)

Jaccard, S. L.; Eric, G. D.; Haug, G. H.; Sigman, D. M.; Francois, R.; Dulski, P.

2006-12-01

Low-latitude Pacific Ocean records of past changes in productivity and denitrification have often been ascribed to local processes, including changes in local wind forcing, with some recent hypothesis calling on remote control by thermocline ventilation processes. Here we show that deep thermohaline circulation, a fundamentally high-latitude process, is also linked to the low-latitude thermocline biogeochemistry through its impact on nutrient and dissolved oxygen distributions. We present new, multi-proxy evidence from sediment records from the abyssal subarctic North Pacific, including sedimentary redox-sensitive trace metal distribution, Th-normalized biogenic barium, calcium carbonate, and opal mass accumulation rates, and bulk sedimentary 15N measurements. These proxies show that the abyss was significantly depleted in oxygen, and low 13C, all consistent with high DIC concentrations. Meanwhile, above a deep chemical divide, the overlying waters were relatively well-oxygenated and nutrient-poor. At the mid-point of the deglaciation, the glacial deep water mass dissipated upwards in the water column, releasing deeply-sequestered CO2 to the atmosphere and shifting nutrients into the thermocline. The flux of regenerated nutrients to the sunlit surface ocean associated with this breakdown of the deep water mass enhanced primary productivity throughout the subarctic Pacific, while records from lower latitudes of the North Pacific show a parallel boom in export production. The accelerated flux of organic matter from the surface contributed towards an intensification of the thermocline oxygen minimum zone, accelerating denitrification in the Eastern (sub)tropical North Pacific and the production of nitrous oxide. These observations, taken together with our evidence for changes in the deep North Pacific, suggest that the flux of nutrients from the deep North Pacific into the upper water column increased at the end of the ice age. This release may have occurred via the polar oceans, which today feed nutrients into the lower latitude thermocline. Alternatively, it may have occurred directly, by vertical mixing in the ocean interior. Regardless of the mechanism, this transition led to the modern configuration of a relatively well-ventilated deep sea, overlain by an oxygen minimum.

Fusion of shallow and deep features for classification of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Gao, Lang; Tian, Tian; Sun, Xiao; Li, Hang

2018-02-01

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.

Setup for in situ deep level transient spectroscopy of semiconductors during swift heavy ion irradiation.

PubMed

Kumar, Sandeep; Kumar, Sugam; Katharria, Y S; Safvan, C P; Kanjilal, D

2008-05-01

A computerized system for in situ deep level characterization during irradiation in semiconductors has been set up and tested in the beam line for materials science studies of the 15 MV Pelletron accelerator at the Inter-University Accelerator Centre, New Delhi. This is a new facility for in situ irradiation-induced deep level studies, available in the beam line of an accelerator laboratory. It is based on the well-known deep level transient spectroscopy (DLTS) technique. High versatility for data manipulation is achieved through multifunction data acquisition card and LABVIEW. In situ DLTS studies of deep levels produced by impact of 100 MeV Si ions on Aun-Si(100) Schottky barrier diode are presented to illustrate performance of the automated DLTS facility in the beam line.

Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

NASA Astrophysics Data System (ADS)

Xin, L.

2018-04-01

Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

50 CFR 679.28 - Equipment and operational requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... sampling table. The observer must be able to stand upright and have a work area at least 0.9 m deep in the... least 0.6 m deep, 1.2 m wide and 0.9 m high and no more than 1.1 m high. The entire surface area of the... Station available on the NMFS Alaska Region Web site at http://www.fakr.noaa.gov. Inspections will be...

Beacon Beams for Deep Turbulence High Energy Laser Beam Directors

DTIC Science & Technology

2012-11-02

variance and nC is the atmospheric refractive index structure constant. The effect of turbulence on the focused beacon beam on target, TR...complete phase conjugation of the beacon beam is accomplished by employing Brillouin enhanced optical four wave mixing. A beacon beam formed by...Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/6790--12-9445 Beacon Beams for Deep Turbulence High Energy Laser Beam Directors P

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

PubMed

Li, Zhixi; He, Yifan; Keel, Stuart; Meng, Wei; Chang, Robert T; He, Mingguang

2018-03-02

To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs. A deep learning system for the classification of GON was developed for automated classification of GON on color fundus photographs. We retrospectively included 48 116 fundus photographs for the development and validation of a deep learning algorithm. This study recruited 21 trained ophthalmologists to classify the photographs. Referable GON was defined as vertical cup-to-disc ratio of 0.7 or more and other typical changes of GON. The reference standard was made until 3 graders achieved agreement. A separate validation dataset of 8000 fully gradable fundus photographs was used to assess the performance of this algorithm. The area under receiver operator characteristic curve (AUC) with sensitivity and specificity was applied to evaluate the efficacy of the deep learning algorithm detecting referable GON. In the validation dataset, this deep learning system achieved an AUC of 0.986 with sensitivity of 95.6% and specificity of 92.0%. The most common reasons for false-negative grading (n = 87) were GON with coexisting eye conditions (n = 44 [50.6%]), including pathologic or high myopia (n = 37 [42.6%]), diabetic retinopathy (n = 4 [4.6%]), and age-related macular degeneration (n = 3 [3.4%]). The leading reason for false-positive results (n = 480) was having other eye conditions (n = 458 [95.4%]), mainly including physiologic cupping (n = 267 [55.6%]). Misclassification as false-positive results amidst a normal-appearing fundus occurred in only 22 eyes (4.6%). A deep learning system can detect referable GON with high sensitivity and specificity. Coexistence of high or pathologic myopia is the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

The intensification of deep-water mass changes in the deep Atlantic Ocean throughout the Mid-Pleistocene climate transition

NASA Astrophysics Data System (ADS)

Poirier, R. K.; Billups, K.

2012-12-01

We examine the deep-water hydrography at Ocean Drilling Project (ODP) Site 1063 (subtropical North Atlantic, ~4600 meter water depth) using high-resolution benthic stable isotope (δ18O, δ13C) and grain size (% coarse, % Sortable Silt - SS, SS mean diameter) analyses from ~490 to 740 ka. The benthic foraminiferal δ13C record from Site 1063 provides a proxy for changes in the relative flux of lower North Atlantic Deep Water (NADW) through time. This record will refine the timing of increases in the formation of the densest components of NADW on the orbital and millennial-scale. We explore whether or not grain size analyses provide a proxy for changes in the relative velocity of the deep current. The new stable isotope data from Site 1063, when combined with the records of Poli et al. (2000), Ferretti et al. (2005), and Billups et al. (2011), tuned to the global benthic isotope stack (LR05) of Liesicki and Raymo (2004), provides a complete deep water record spanning Marine Isotope Stage (MIS) 25 to MIS 8 (~1020 to ~240 ka). Compiling published records from 16 additional sites, we use the Ocean Data View (ODV) program (Schlitzer, 2012) to map deep-water mass distributions through time. Results reveal an increasing distribution and influence of the NADW in relation to the Antarctic Bottom Water mass within interglacial periods beginning at MIS 15 continuing though the end of the Site 1063 record within MIS 9. Preliminary grain size analyses over a short interval of time reveal regular high frequency variations on the millennial scale. We anticipate having complete, high-resolution stable isotope and grain size records to discuss the hydrographic changes within the MIS 16/15 glacial/interglacial transition, as well as throughout the Mid-Pleistocene transition (MPT).

Highly Survivable Avionics Systems for Long-Term Deep Space Exploration

NASA Technical Reports Server (NTRS)

Alkalai, L.; Chau, S.; Tai, A. T.

2001-01-01

The design of highly survivable avionics systems for long-term (> 10 years) exploration of space is an essential technology for all current and future missions in the Outer Planets roadmap. Long-term exposure to extreme environmental conditions such as high radiation and low-temperatures make survivability in space a major challenge. Moreover, current and future missions are increasingly using commercial technology such as deep sub-micron (0.25 microns) fabrication processes with specialized circuit designs, commercial interfaces, processors, memory, and other commercial off the shelf components that were not designed for long-term survivability in space. Therefore, the design of highly reliable, and available systems for the exploration of Europa, Pluto and other destinations in deep-space require a comprehensive and fresh approach to this problem. This paper summarizes work in progress in three different areas: a framework for the design of highly reliable and highly available space avionics systems, distributed reliable computing architecture, and Guarded Software Upgrading (GSU) techniques for software upgrading during long-term missions. Additional information is contained in the original extended abstract.

The dynamics of biogeographic ranges in the deep sea.

PubMed

McClain, Craig R; Hardy, Sarah Mincks

2010-12-07

Anthropogenic disturbances such as fishing, mining, oil drilling, bioprospecting, warming, and acidification in the deep sea are increasing, yet generalities about deep-sea biogeography remain elusive. Owing to the lack of perceived environmental variability and geographical barriers, ranges of deep-sea species were traditionally assumed to be exceedingly large. In contrast, seamount and chemosynthetic habitats with reported high endemicity challenge the broad applicability of a single biogeographic paradigm for the deep sea. New research benefiting from higher resolution sampling, molecular methods and public databases can now more rigorously examine dispersal distances and species ranges on the vast ocean floor. Here, we explore the major outstanding questions in deep-sea biogeography. Based on current evidence, many taxa appear broadly distributed across the deep sea, a pattern replicated in both the abyssal plains and specialized environments such as hydrothermal vents. Cold waters may slow larval metabolism and development augmenting the great intrinsic ability for dispersal among many deep-sea species. Currents, environmental shifts, and topography can prove to be dispersal barriers but are often semipermeable. Evidence of historical events such as points of faunal origin and climatic fluctuations are also evident in contemporary biogeographic ranges. Continued synthetic analysis, database construction, theoretical advancement and field sampling will be required to further refine hypotheses regarding deep-sea biogeography.

The dynamics of biogeographic ranges in the deep sea

PubMed Central

McClain, Craig R.; Hardy, Sarah Mincks

2010-01-01

Anthropogenic disturbances such as fishing, mining, oil drilling, bioprospecting, warming, and acidification in the deep sea are increasing, yet generalities about deep-sea biogeography remain elusive. Owing to the lack of perceived environmental variability and geographical barriers, ranges of deep-sea species were traditionally assumed to be exceedingly large. In contrast, seamount and chemosynthetic habitats with reported high endemicity challenge the broad applicability of a single biogeographic paradigm for the deep sea. New research benefiting from higher resolution sampling, molecular methods and public databases can now more rigorously examine dispersal distances and species ranges on the vast ocean floor. Here, we explore the major outstanding questions in deep-sea biogeography. Based on current evidence, many taxa appear broadly distributed across the deep sea, a pattern replicated in both the abyssal plains and specialized environments such as hydrothermal vents. Cold waters may slow larval metabolism and development augmenting the great intrinsic ability for dispersal among many deep-sea species. Currents, environmental shifts, and topography can prove to be dispersal barriers but are often semipermeable. Evidence of historical events such as points of faunal origin and climatic fluctuations are also evident in contemporary biogeographic ranges. Continued synthetic analysis, database construction, theoretical advancement and field sampling will be required to further refine hypotheses regarding deep-sea biogeography. PMID:20667884

Temperature impacts on deep-sea biodiversity.

PubMed

Yasuhara, Moriaki; Danovaro, Roberto

2016-05-01

Temperature is considered to be a fundamental factor controlling biodiversity in marine ecosystems, but precisely what role temperature plays in modulating diversity is still not clear. The deep ocean, lacking light and in situ photosynthetic primary production, is an ideal model system to test the effects of temperature changes on biodiversity. Here we synthesize current knowledge on temperature-diversity relationships in the deep sea. Our results from both present and past deep-sea assemblages suggest that, when a wide range of deep-sea bottom-water temperatures is considered, a unimodal relationship exists between temperature and diversity (that may be right skewed). It is possible that temperature is important only when at relatively high and low levels but does not play a major role in the intermediate temperature range. Possible mechanisms explaining the temperature-biodiversity relationship include the physiological-tolerance hypothesis, the metabolic hypothesis, island biogeography theory, or some combination of these. The possible unimodal relationship discussed here may allow us to identify tipping points at which on-going global change and deep-water warming may increase or decrease deep-sea biodiversity. Predicted changes in deep-sea temperatures due to human-induced climate change may have more adverse consequences than expected considering the sensitivity of deep-sea ecosystems to temperature changes. © 2014 Cambridge Philosophical Society.

Benthic foraminiferal faunal and geochemical proxies as tracers for paleoenvironmental and paleoceanographic changes in the western Mediterranean over the last 24 ka

NASA Astrophysics Data System (ADS)

Pérez-Asensio, José N.; Cacho, Isabel; Frigola, Jaime; Pena, Leopoldo D.; Sierro, Francisco J.; Asioli, Alessandra; Kuhlmann, Jannis; Huhn, Katrin

2017-04-01

Paleoenvironmental and paleoceanographic changes in the western Mediterranean are reconstructed for the last 24 ka using a combination of benthic foraminiferal assemblages and geochemical proxies measured on benthic foraminiferal shells (Mg/Ca-deep water temperatures and stable isotopes). The studied materials are sediment cores HER-GC-UB06 and MD95-2043recovered at 946 m and 1841 m, respectively, from the Alboran Sea. At present, both core sites are bathed by the Western Mediterranean Deep Water (WMDW), although UB06 core is close to the boundary with the overlying Levantine Intermediate Water (LIW). Therefore, past variability of both water masses can potentially be recorded by the benthic foraminiferal proxies from the studied sites. Benthic foraminiferal assemblages and geochemical data show fluctuations in bottom-water ventilation, organic matter accumulation and deep-water temperatures related to WMDW and LIW circulation. During the glacial interval, an alternation of events showing better ventilation (higher abundance of Cibicides pachyderma) with lower temperatures and events of warmer deep water temperatures with poorer ventilation (Nonionella iridea assemblage, lower abundance of C. pachyderma) are observed. This variability might reflect stronger WMDW formation during the Last Glacial Maximum (LGM) and Heinrich Stadial 1. During the Bølling-Allerød and Younger Dryas (YD) periods, cold temperatures and the lowest oxygenation rates are recorded coinciding with the highest abundance of deep infaunal taxa on both UB06 and MD95-2043 cores. This interval was coetaneous to the deposition of an Organic Rich Layer in the Alboran Sea. However, a re-ventilation trend started at the end of the YD in the shallower site (UB06 core) whereas low-oxygen conditions prevailed until the end of the early Holocene in the deep site (MD95-2043 core). During the early Holocene a significant deep water temperature increase occurred at the shallower site suggesting the replacement of WMDW by warmer water mass, likely LIW. In the middle Holocene, highly variable bottom-water oxygenation and temperatures are observed showing warmer deep waters with less oxygen content (higher deep and intermediate infaunal abundances). The late Holocene (last 4 ka) was characterized by slightly cooler deep water temperatures and enhanced oxygen levels supporting that WMDW became dominant at the shallower site. These observations reveal that Mediterranean thermohaline system has been highly variable during the studied period supporting its high sensitivity to changing climate conditions. These results open a new insight into the Mediterranean sensitivity to Holocene climate variability.

Group III Acceptors with Shallow and Deep Levels in Silicon Carbide: ESR and ENDOR Studies

NASA Astrophysics Data System (ADS)

Il'in, I. V.; Uspenskaya, Yu. A.; Kramushchenko, D. D.; Muzafarova, M. V.; Soltamov, V. A.; Mokhov, E. N.; Baranov, P. G.

2018-04-01

Results of investigations of Group III acceptors (B, Al, and Ga) in crystals of silicon carbide using the most informative electron spin resonance and electron nuclear double resonance methods are presented. Structural models of the acceptors with shallow and deep levels are considered. In addition to the data obtained earlier, studies using high-frequency magnetic resonance were obtained, which allowed revealing orthorhombic deviations from the axial symmetry for the deep acceptors; theoretical analysis explains experimentally found shifts of g factors for the deep acceptors arising due to the orthorhombic deviations, which appear probably due to the Jahn-Teller effect.

Deep data fusion method for missile-borne inertial/celestial system

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Chen, Xiaofei; Lu, Jiazhen; Zhang, Hao

2018-05-01

Strap-down inertial-celestial integrated navigation system has the advantages of autonomy and high precision and is very useful for ballistic missiles. The star sensor installation error and inertial measurement error have a great influence for the system performance. Based on deep data fusion, this paper establishes measurement equations including star sensor installation error and proposes the deep fusion filter method. Simulations including misalignment error, star sensor installation error, IMU error are analyzed. Simulation results indicate that the deep fusion method can estimate the star sensor installation error and IMU error. Meanwhile, the method can restrain the misalignment errors caused by instrument errors.

Deep Drawing Behavior of CoCrFeMnNi High-Entropy Alloys

NASA Astrophysics Data System (ADS)

Bae, Jae Wung; Moon, Jongun; Jang, Min Ji; Ahn, Dong-Hyun; Joo, Soo-Hyun; Jung, Jaimyun; Yim, Dami; Kim, Hyoung Seop

2017-09-01

Herein, the deep drawability and deep drawing behavior of an equiatomic CoCrFeMnNi HEA and its microstructure and texture evolution are first studied for future applications. The CoCrFeMnNi HEA is successfully drawn to a limit drawing ratio (LDR) of 2.14, while the planar anisotropy of the drawn cup specimen is negligible. The moderate combination of strain hardening exponent and strain rate sensitivity and the formation of deformation twins in the edge region play important roles in successful deep drawing. In the meanwhile, the texture evolution of CoCrFeMnNi HEA has similarities with conventional fcc metals.

Enhancing Return from Lunar Surface Missions via the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Chavers, D. G.; Whitley, R. J.; Percy, T. K.; Needham, D. H.; Polsgrove, T. T.

2018-02-01

The Deep Space Gateway (DSG) will facilitate access to and communication with lunar surface assets. With a science airlock, docking port, and refueling capability in an accessible orbit, the DSG will enable high priority science across the lunar surface.

Deep Tissue Fluorescent Imaging in Scattering Specimens Using Confocal Microscopy

PubMed Central

Clendenon, Sherry G.; Young, Pamela A.; Ferkowicz, Michael; Phillips, Carrie; Dunn, Kenneth W.

2015-01-01

In scattering specimens, multiphoton excitation and nondescanned detection improve imaging depth by a factor of 2 or more over confocal microscopy; however, imaging depth is still limited by scattering. We applied the concept of clearing to deep tissue imaging of highly scattering specimens. Clearing is a remarkably effective approach to improving image quality at depth using either confocal or multiphoton microscopy. Tissue clearing appears to eliminate the need for multiphoton excitation for deep tissue imaging. PMID:21729357

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

NASA Astrophysics Data System (ADS)

Chernoded, Andrey; Dudko, Lev; Myagkov, Igor; Volkov, Petr

2017-10-01

Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

Effects of frying oils' fatty acids profile on the formation of polar lipids components and their retention in French fries over deep-frying process.

PubMed

Li, Xiaodan; Li, Jinwei; Wang, Yong; Cao, Peirang; Liu, Yuanfa

2017-12-15

The effects of frying oils' fatty acids profile on the formation of polar components and their retention in French fries and corresponding deep-fried oils were investigated in the present study, using oils with different fatty acids composition. Our analysis showed that the total polar compounds (TPCs) content in French fries was only slightly lower than that in deep-fried oils, indicating that there was no significant difference considering the amounts of TPCs in French fries and deep-fried oils. Our further analysis showed that different polar components in TPCs distributed differently in deep-fried oils and oils extracted from French fries. Specifically, the level of oligomeric and dimeric triacylglycerols was higher in French fries while oxidized triacylglycerols and diacylglycerols content was higher in deep-fried oils. The different retention of TPCs components in French fries may be explained by their interactions with carbohydrates, which are shown to enhance with the increase of hydrophobic property. Chemometric analysis showed that no correlation between the polar compounds level and saturated fatty acids profile was observed. Meanwhile, the polar compounds content was highly correlated with the formation of trans-C18:1, and a highly positive association between polar compounds and C18:2 content was also observed in palm oil. Copyright © 2017 Elsevier Ltd. All rights reserved.

DANoC: An Efficient Algorithm and Hardware Codesign of Deep Neural Networks on Chip.

PubMed

Zhou, Xichuan; Li, Shengli; Tang, Fang; Hu, Shengdong; Lin, Zhi; Zhang, Lei

2017-07-18

Deep neural networks (NNs) are the state-of-the-art models for understanding the content of images and videos. However, implementing deep NNs in embedded systems is a challenging task, e.g., a typical deep belief network could exhaust gigabytes of memory and result in bandwidth and computational bottlenecks. To address this challenge, this paper presents an algorithm and hardware codesign for efficient deep neural computation. A hardware-oriented deep learning algorithm, named the deep adaptive network, is proposed to explore the sparsity of neural connections. By adaptively removing the majority of neural connections and robustly representing the reserved connections using binary integers, the proposed algorithm could save up to 99.9% memory utility and computational resources without undermining classification accuracy. An efficient sparse-mapping-memory-based hardware architecture is proposed to fully take advantage of the algorithmic optimization. Different from traditional Von Neumann architecture, the deep-adaptive network on chip (DANoC) brings communication and computation in close proximity to avoid power-hungry parameter transfers between on-board memory and on-chip computational units. Experiments over different image classification benchmarks show that the DANoC system achieves competitively high accuracy and efficiency comparing with the state-of-the-art approaches.

The National Deep-Sea Coral and Sponge Database: A Comprehensive Resource for United States Deep-Sea Coral and Sponge Records

NASA Astrophysics Data System (ADS)

Dornback, M.; Hourigan, T.; Etnoyer, P.; McGuinn, R.; Cross, S. L.

2014-12-01

Research on deep-sea corals has expanded rapidly over the last two decades, as scientists began to realize their value as long-lived structural components of high biodiversity habitats and archives of environmental information. The NOAA Deep Sea Coral Research and Technology Program's National Database for Deep-Sea Corals and Sponges is a comprehensive resource for georeferenced data on these organisms in U.S. waters. The National Database currently includes more than 220,000 deep-sea coral records representing approximately 880 unique species. Database records from museum archives, commercial and scientific bycatch, and from journal publications provide baseline information with relatively coarse spatial resolution dating back as far as 1842. These data are complemented by modern, in-situ submersible observations with high spatial resolution, from surveys conducted by NOAA and NOAA partners. Management of high volumes of modern high-resolution observational data can be challenging. NOAA is working with our data partners to incorporate this occurrence data into the National Database, along with images and associated information related to geoposition, time, biology, taxonomy, environment, provenance, and accuracy. NOAA is also working to link associated datasets collected by our program's research, to properly archive them to the NOAA National Data Centers, to build a robust metadata record, and to establish a standard protocol to simplify the process. Access to the National Database is provided through an online mapping portal. The map displays point based records from the database. Records can be refined by taxon, region, time, and depth. The queries and extent used to view the map can also be used to download subsets of the database. The database, map, and website is already in use by NOAA, regional fishery management councils, and regional ocean planning bodies, but we envision it as a model that can expand to accommodate data on a global scale.

Albedo Neutron Dosimetry in a Deep Geological Disposal Repository for High-Level Nuclear Waste.

PubMed

Pang, Bo; Becker, Frank

2017-04-28

Albedo neutron dosemeter is the German official personal neutron dosemeter in mixed radiation fields where neutrons contribute to personal dose. In deep geological repositories for high-level nuclear waste, where neutrons can dominate the radiation field, it is of interest to investigate the performance of albedo neutron dosemeter in such facilities. In this study, the deep geological repository is represented by a shielding cask loaded with spent nuclear fuel placed inside a rock salt emplacement drift. Due to the backscattering of neutrons in the drift, issues concerning calibration of the dosemeter arise. Field-specific calibration of the albedo neutron dosemeter was hence performed with Monte Carlo simulations. In order to assess the applicability of the albedo neutron dosemeter in a deep geological repository over a long time scale, spent nuclear fuel with different ages of 50, 100 and 500 years were investigated. It was found out, that the neutron radiation field in a deep geological repository can be assigned to the application area 'N1' of the albedo neutron dosemeter, which is typical in reactors and accelerators with heavy shielding. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparison of Travel-Time and Amplitude Measurements for Deep-Focusing Time-Distance Helioseismology

NASA Astrophysics Data System (ADS)

Pourabdian, Majid; Fournier, Damien; Gizon, Laurent

2018-04-01

The purpose of deep-focusing time-distance helioseismology is to construct seismic measurements that have a high sensitivity to the physical conditions at a desired target point in the solar interior. With this technique, pairs of points on the solar surface are chosen such that acoustic ray paths intersect at this target (focus) point. Considering acoustic waves in a homogeneous medium, we compare travel-time and amplitude measurements extracted from the deep-focusing cross-covariance functions. Using a single-scattering approximation, we find that the spatial sensitivity of deep-focusing travel times to sound-speed perturbations is zero at the target location and maximum in a surrounding shell. This is unlike the deep-focusing amplitude measurements, which have maximum sensitivity at the target point. We compare the signal-to-noise ratio for travel-time and amplitude measurements for different types of sound-speed perturbations, under the assumption that noise is solely due to the random excitation of the waves. We find that, for highly localized perturbations in sound speed, the signal-to-noise ratio is higher for amplitude measurements than for travel-time measurements. We conclude that amplitude measurements are a useful complement to travel-time measurements in time-distance helioseismology.

Reproductive biology of the deep-water coral Acanella arbuscula (Phylum Cnidaria: Class Anthozoa: Order Alcyonacea), northwest Atlantic

NASA Astrophysics Data System (ADS)

Beazley, Lindsay I.; Kenchington, Ellen L.

2012-10-01

Knowledge of the reproductive life-history of deep-water corals is important for assessing their vulnerability to anthropogenic impacts. Yet, the reproductive biology of many deep-water corals, especially members of the subclass Octocorallia, has not been examined. We used histological techniques to describe the reproductive biology of the deep-water gorgonian coral Acanella arbuscula from the northwest Atlantic. All colonies examined were gonochoric, and no embryos or planula larvae were observed in the polyps. Mean polyp-level fecundity (females: 21.0±17.5 oocytes polyp-1, and males: 13.9±13.5 sperm sacs polyp-1) is high compared to other deep-water gorgonians, and polyps closer to the branch tips had the highest fecundities in both females and males. The presence of large oocytes (maximum diameter 717.8 μm) suggests that A. arbuscula produces lecithotrophic larvae. Despite the potentially high fecundity and small size at first reproduction, the paucity of information on dispersal and recruitment, combined with its longevity, vulnerability to bottom fishing gear, and ecological role as a structure-forming species, still warrants the classification of A. arbuscula as a vulnerable marine ecosystem indicator.

Deep, diverse and definitely different: unique attributes of the world's largest ecosystem

NASA Astrophysics Data System (ADS)

Ramirez-Llodra, E.; Brandt, A.; Danovaro, R.; Escobar, E.; German, C. R.; Levin, L. A.; Martinez Arbizu, P.; Menot, L.; Buhl-Mortensen, P.; Narayanaswamy, B. E.; Smith, C. R.; Tittensor, D. P.; Tyler, P. A.; Vanreusel, A.; Vecchione, M.

2010-04-01

The deep sea, the largest biome on Earth, has a series of characteristics that make this environment both distinct from other marine and land ecosystems and unique for the entire planet. This review describes these patterns and processes, from geological settings to biological processes, biodiversity and biogeographical patterns. It concludes with a brief discussion of current threats from anthropogenic activities to deep-sea habitats and their fauna. Investigations of deep-sea habitats and their fauna began in the late 19th Century. In the intervening years, technological developments and stimulating discoveries have promoted deep-sea research and changed our way of understanding life on the planet. Nevertheless, the deep sea is still mostly unknown and current discovery rates of both habitats and species remain high. The geological, physical and geochemical settings of the deep-sea floor and the water column form a series of different habitats with unique characteristics that support specific faunal communities. Since 1840, 27 new habitats/ecosystems have been discovered from the shelf break to the deep trenches and discoveries of new habitats are still happening in the early 21st Century. However, for most of these habitats, the global area covered is unknown or has been only very roughly estimated; an even smaller - indeed, minimal - proportion has actually been sampled and investigated. We currently perceive most of the deep-sea ecosystems as heterotrophic, depending ultimately on the flux on organic matter produced in the overlying surface ocean through photosynthesis. The resulting strong food limitation, thus, shapes deep-sea biota and communities, with exceptions only in reducing ecosystems such as inter alia hydrothermal vents or cold seeps, where chemoautolithotrophic bacteria play the role of primary producers fuelled by chemical energy sources rather than sunlight. Other ecosystems, such as seamounts, canyons or cold-water corals have an increased productivity through specific physical processes, such as topographic modification of currents and enhanced transport of particles and detrital matter. Because of its unique abiotic attributes, the deep sea hosts a specialized fauna. Although there are no phyla unique to deep waters, at lower taxonomic levels the composition of the fauna is distinct from that found in the upper ocean. Amongst other characteristic patterns, deep-sea species may exhibit either gigantism or dwarfism, related to the decrease in food availability with depth. Food limitation on the seafloor and water column is also reflected in the trophic structure of deep-sea communities, which are adapted to low energy availability. In most of the heterotrophic deep-sea settings, the dominant megafauna is composed of detritivores, while filter feeders are abundant in habitats with hard substrata (e.g. mid-ocean ridges, seamounts, canyon walls and coral reefs) and chemoautotrophy through symbiotic relationships is dominant in reducing habitats. Deep-sea biodiversity is among of the highest on the planet, mainly composed of macro and meiofauna, with high evenness. This is true for most of the continental margins and abyssal plains with hot spots of diversity such as seamounts or cold-water corals. However, in some ecosystems with particularly "extreme" physicochemical processes (e.g. hydrothermal vents), biodiversity is low but abundance and biomass are high and the communities are dominated by a few species. Two large-scale diversity patterns have been discussed for deep-sea benthic communities. First, a unimodal relationship between diversity and depth is observed, with a peak at intermediate depths (2000-3000 m), although this is not universal and particular abiotic processes can modify the trend. Secondly, a poleward trend of decreasing diversity has been discussed, but this remains controversial and studies with larger and more robust datasets are needed. Because of the paucity in our knowledge of habitat coverage and species composition, biogeographic studies are mostly based on regional data or on specific taxonomic groups. Recently, global biogeographic provinces for the pelagic and benthic deep ocean have been described, using environmental and, where data were available, taxonomic information. This classification described 30 pelagic provinces and 38 benthic provinces divided into 4 depth ranges, as well as 10 hydrothermal vent provinces. One of the major issues faced by deep-sea biodiversity and biogeographical studies is related to the high number of species new to science that are collected regularly, together with the slow description rates for these new species. Taxonomic coordination at the global scale is particularly difficult but is essential if we are to analyse large diversity and biogeographic trends. Because of their remoteness, anthropogenic impacts on deep-sea ecosystems have not been addressed very thoroughly until recently. The depletion of biological and mineral resources on land and in shallow waters, coupled with technological developments, is promoting the increased interest in services provided by deep-water resources. Although often largely unknown, evidence for the effects of human activities in deep-water ecosystems - such as deep-sea mining, hydrocarbon exploration and exploitation, fishing, dumping and littering - is already accumulating. Because of our limited knowledge of deep-sea biodiversity and ecosystem functioning and because of the specific life-history adaptations of many deep-sea species (e.g. slow growth and delayed maturity), it is essential that the scientific community works closely with industry, conservation organisations and policy makers to develop conservation and management options.

[Distribution Characteristics and Source of Fluoride in Groundwater in Lower Plain Area of North China Plain: A Case Study in Nanpi County].

PubMed

Kong, Xiao-le; Wang, Shi-qin; Zhao, Huan; Yuan, Rui-qiang

2015-11-01

There is an obvious regional contradiction between water resources and agricultural produce in lower plain area of North China, however, excessive fluorine in deep groundwater further limits the use of regional water resources. In order to understand the spatial distribution characteristics and source of F(-) in groundwater, study was carried out in Nanpi County by field survey and sampling, hydrogeochemical analysis and stable isotopes methods. The results showed that the center of low fluoride concentrations of shallow groundwater was located around reservoir of Dalang Lake, and centers of high fluoride concentrations were located in southeast and southwest of the study area. The region with high fluoride concentration was consistent with the over-exploitation region of deep groundwater. Point source pollution of subsurface drainage and non-point source of irrigation with deep groundwater in some regions were the main causes for the increasing F(-) concentrations of shallow groundwater in parts of the sampling sites. Rock deposition and hydrogeology conditions were the main causes for the high F(-) concentrations (1.00 mg x L(-1), threshold of drinking water quality standard in China) in deep groundwater. F(-) released from clay minerals into the water increased the F(-) concentrations in deep groundwater because of over-exploitation. With the increasing exploitation and utilization of brackish shallow groundwater and the compressing and restricting of deep groundwater exploitation, the water environment in the middle and east lower plain area of North China will undergo significant change, and it is important to identify the distribution and source of F(-) in surface water and groundwater for reasonable development and use of water resources in future.

Effectiveness of deep cleaning followed by hydrogen peroxide decontamination during high Clostridium difficile infection incidence.

PubMed

Best, E L; Parnell, P; Thirkell, G; Verity, P; Copland, M; Else, P; Denton, M; Hobson, R P; Wilcox, M H

2014-05-01

Clostridium difficile infection (CDI) remains an infection control challenge, especially when environmental spore contamination and suboptimal cleaning may increase transmission risk. To substantiate the long-term effectiveness throughout a stroke rehabilitation unit (SRU) of deep cleaning and hydrogen peroxide decontamination (HPD), following a high incidence of CDI. Extensive environmental sampling (342 sites on each occasion) for C. difficile using sponge wipes was performed: before and after deep cleaning with detergent/chlorine agent; immediately following HPD; and on two further occasions, 19 days and 20 weeks following HPD. C. difficile isolates underwent polymerase chain reaction ribotyping and multi-locus variable repeat analysis (MLVA). C. difficile was recovered from 10.8%, 6.1%, 0.9%, 0% and 3.5% of sites at baseline, following deep cleaning, immediately after HPD, and 19 days and 20 weeks after HPD, respectively. C. difficile ribotypes recovered after deep cleaning matched those from CDI cases in the SRU during the previous 10 months. Similarly, 10/12 of the positive sites identified at 20 weeks post-HPD harboured the same C. difficile ribotype (002) and MLVA pattern as the isolate from the first post-HPD CDI case. CDI incidence [number of cases on SRU per 10 months (January-October 2011)] declined from 20 before to seven after the intervention. HPD, after deep cleaning with a detergent/chlorine agent, was highly effective for removing environmental C. difficile contamination. Long-term follow-up demonstrated that a CDI symptomatic patient can rapidly recontaminate the immediate environment. Determining a role for HPD should include long-term cost-effectiveness evaluations. Copyright © 2014 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Advancing an In situ Laser Spectrometer for Carbon Isotope Analyses in the Deep Ocean

NASA Astrophysics Data System (ADS)

Michel, A.; Wankel, S. D.; Kapit, J.; Girguis, P. R.

2016-02-01

Development of in situ chemical sensors is critical for improving our understanding of deep-ocean biogeochemistry and recent advances in chemical sensors are already expanding the breadth and depth of deep sea/seafloor exploration and research. Although initially developed for high sensitivity measurements of atmospheric gases, laser-based spectroscopic sensors are now being developed for research in the deep sea by incorporating the use of semi-permeable membranes. Here we present on recent deep-sea deployments of an in situ laser-based analyzer of carbon isotopes of methane (δ13CH4), highlighting several advances including a new capability for also measuring δ13C of DIC or CO2 by incorporating a second laser and an in line acidification module. A bubble trapping approach was designed and implemented for the collection and analysis of both CH4 and CO2 from deep-sea bubbles. The newly advanced laser spectrometer was deployed at both Kick `Em Jenny volcano off of the island of Grenada and in a brine pool in the western Gulf of Mexico ("The Jacuzzi of Despair") using the E/V Nautilus and the ROV Hercules. At Kick `Em Jenny, seafloor measurements were made of both emanating fluids and bubbles from within and around the crater - revealing high levels of magmatic CO2 with minor amounts of CH4 and hydrogen sulfide. At the brine pool, spot measurements and depth profile measurements into the brine pool were made for chemical mapping, revealing fluids that were saturated with respect to methane. New technologies such as the laser spectrometer will enable us to obtain high resolution and near real-time, in situ chemical and isotopic data and to make geochemical maps over a range of spatial and temporal scales.

Origin and assessment of deep groundwater inflow in the Ca' Lita landslide using hydrochemistry and in situ monitoring

NASA Astrophysics Data System (ADS)

Cervi, F.; Ronchetti, F.; Martinelli, G.; Bogaard, T. A.; Corsini, A.

2012-06-01

Changes in soil water content, groundwater flow and a rise in pore water pressure are well-known causal or triggering factors for hillslope instability. Rainfall and snowmelt are generally assumed as the only sources of groundwater recharge. This assumption neglects the role of deep water inflow in highly tectonized areas, a factor that can influence long-term pore-pressure regimes and play a role on local slope instability. This paper aims to assess the origin of groundwater in the Ca' Lita landslide (northern Italian Apennines) and to qualify and quantify the aliquot attributable to deep water inflow. The research is essentially based on in situ monitoring and hydrochemical analyses. It involved 5 yr of continuous monitoring of groundwater levels, electrical conductivity and temperature, and with groundwater sampling followed by determination of major ions, tracers (such as Boron and Strontium), and isotopes (Oxygen, Deuterium, Tritium). Leaching experiments on soil samples and water recharge estimation were also carried out. Results show that the groundwater balance in the Ca' Lita landslide must take into account an inflow of highly mineralized Na-SO4 water (more than 9500 μS cm-1) with non-negligible amounts of Chloride (up to 800 mg l-1). The deep water inflow recharges the aquifer hosted in the bedrock underlying the sliding surface (at a rate of about 7800-17 500 m3 yr-1). It also partly recharges the landslide body, where the hydrochemical imprint of deep water mixed with rainfall and snowmelt water was observed. This points to a probable influence of deep water inflow on the mobility of the Ca' Lita landslide, a finding that could be applicable to other large landslides occurring in highly tectonized areas in the northern Apennines or in other mountain chains.

Terrestrial source to deep-sea sink sediment budgets at high and low sea levels: Insights from tectonically active Southern California

USGS Publications Warehouse

Covault, J.A.; Romans, B.W.; Graham, S.A.; Fildani, A.; Hilley, G.E.

2011-01-01

Sediment routing from terrestrial source areas to the deep sea influences landscapes and seascapes and supply and filling of sedimentary basins. However, a comprehensive assessment of land-to-deep-sea sediment budgets over millennia with significant climate change is lacking. We provide source to sink sediment budgets using cosmogenic radionuclide-derived terrestrial denudation rates and submarine-fan deposition rates through sea-level fluctuations since oxygen isotope stage 3 (younger than 40 ka) in tectonically active, spatially restricted sediment-routing systems of Southern California. We show that source-area denudation and deep-sea deposition are balanced during a period of generally falling and low sea level (40-13 ka), but that deep-sea deposition exceeds terrestrial denudation during the subsequent period of rising and high sea level (younger than 13 ka). This additional supply of sediment is likely owed to enhanced dispersal of sediment across the shelf caused by seacliff erosion during postglacial shoreline transgression and initiation of submarine mass wasting. During periods of both low and high sea level, land and deep-sea sediment fluxes do not show orders of magnitude imbalances that might be expected in the wake of major sea-level changes. Thus, sediment-routing processes in a globally significant class of small, tectonically active systems might be fundamentally different from those of larger systems that drain entire orogens, in which sediment storage in coastal plains and wide continental shelves can exceed millions of years. Furthermore, in such small systems, depositional changes offshore can reflect onshore changes when viewed over time scales of several thousand years to more than 10 k.y. ?? 2011 Geological Society of America.

Projected pH reductions by 2100 might put deep North Atlantic biodiversity at risk

NASA Astrophysics Data System (ADS)

Gehlen, M.; Séférian, R.; Jones, D. O. B.; Roy, T.; Roth, R.; Barry, J.; Bopp, L.; Doney, S. C.; Dunne, J. P.; Heinze, C.; Joos, F.; Orr, J. C.; Resplandy, L.; Segschneider, J.; Tjiputra, J.

2014-12-01

This study aims to evaluate the potential for impacts of ocean acidification on North Atlantic deep-sea ecosystems in response to IPCC AR5 Representative Concentration Pathways (RCPs). Deep-sea biota is likely highly vulnerable to changes in seawater chemistry and sensitive to moderate excursions in pH. Here we show, from seven fully coupled Earth system models, that for three out of four RCPs over 17% of the seafloor area below 500 m depth in the North Atlantic sector will experience pH reductions exceeding -0.2 units by 2100. Increased stratification in response to climate change partially alleviates the impact of ocean acidification on deep benthic environments. We report on major pH reductions over the deep North Atlantic seafloor (depth >500 m) and at important deep-sea features, such as seamounts and canyons. By 2100, and under the high CO2 scenario RCP8.5, pH reductions exceeding -0.2 (-0.3) units are projected in close to 23% (~15%) of North Atlantic deep-sea canyons and ~8% (3%) of seamounts - including seamounts proposed as sites of marine protected areas. The spatial pattern of impacts reflects the depth of the pH perturbation and does not scale linearly with atmospheric CO2 concentration. Impacts may cause negative changes of the same magnitude or exceeding the current target of 10% of preservation of marine biomes set by the convention on biological diversity, implying that ocean acidification may offset benefits from conservation/management strategies relying on the regulation of resource exploitation.

The Excitation of High Spin States with Quasielastic and Deep Inelastic Reactions.

NASA Astrophysics Data System (ADS)

Knott, Clinton Neal

1988-12-01

The feasibility of populating high spin states using reactions induced by a 220 MeV ^{22 }Ne beam on a ^{170} Er target was studied. The experiment was carried out using a multidetector array for high resolution gamma-ray spectroscopy, a 14 element sum multiplicity spectrometer and six DeltaE-E particle telescopes. Detailed information was obtained concerning the reaction mechanisms associated with various reaction channels. Deep inelastic collisions are shown to be a promising tool for high spin spectroscopy in regions of the chart of nuclides which are not accessible by other reactions.

Population of high spin states by quasi-elastic and deep inelastic collisions

NASA Astrophysics Data System (ADS)

Takai, H.; Knott, C. N.; Winchell, D. F.; Saladin, J. X.; Kaplan, M. S.; de Faro, L.; Aryaeinejad, R.; Blue, R. A.; Ronningen, R. M.; Morrissey, D. J.; Lee, I. Y.; Dietzsch, O.

1988-09-01

The feasibility of populating high spin states using reactions induced by a 10 MeV/nucleon 22Ne beam on 170Er was studied. The experiment was carried out using a multidetector array for high resolution γ-ray spectroscopy, a 14 element sum-multiplicity spectrometer and six ΔE-E telescopes. Detailed information was obtained concerning the reaction mechanisms associated with various reaction channels. Deep inelastic collisions are shown to be a promising tool for high spin spectroscopy in regions of the chart of nuclides which are not accessible by other reactions.

deepTools: a flexible platform for exploring deep-sequencing data.

PubMed

Ramírez, Fidel; Dündar, Friederike; Diehl, Sarah; Grüning, Björn A; Manke, Thomas

2014-07-01

We present a Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner. In addition, we offer several tools for the analysis of files containing aligned reads and enable efficient and reproducible generation of normalized coverage files. As a modular and open-source platform, deepTools can easily be expanded and customized to future demands and developments. The deepTools webserver is freely available at http://deeptools.ie-freiburg.mpg.de and is accompanied by extensive documentation and tutorials aimed at conveying the principles of deep-sequencing data analysis. The web server can be used without registration. deepTools can be installed locally either stand-alone or as part of Galaxy. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Towards ecosystem based management and monitoring of the deep Mediterranean, North-East Atlantic and Beyond

NASA Astrophysics Data System (ADS)

Grehan, Anthony J.; Arnaud-Haond, Sophie; D'Onghia, Gianfranco; Savini, Alessandra; Yesson, Chris

2017-11-01

The deep sea covers 65% of the earth's surface and 95% of the biosphere but only a very small fraction (less than 0.0001%) of this has been explored (Rogers et al., 2015; Taylor and Roterman, 2017). However, current knowledge indicates that the deep ocean is characterized by a high level of biodiversity and by the presence of important biological and non-renewable resources. As well as vast flat and muddy plains, the topography of the deep ocean contains a variety of complex and heterogeneous seafloor features, such as canyons, seamounts, cold seeps, hydrothermal vents and biogenic (deep-water coral) reefs and sponge bioherms that harbour an unquantified and diverse array of organisms. The deep sea, despite its remoteness, provides a variety of supporting, provisioning, regulating and cultural, ecosystem goods and services (Thurber et al., 2014). The recent push for 'Blue Growth', to unlock the potential of seas and oceans (European Commission, 2017) has increased the focus on the potential to exploit resources in the deep-sea and consequently the need for improved management (Thurber et al., 2014).

Extracting Databases from Dark Data with DeepDive.

PubMed

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data : the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data - scientific papers, Web classified ads, customer service notes, and so on - were instead in a relational database, it would give analysts a massive and valuable new set of "big data." DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference.

Contrasting effects of deep ploughing of croplands and forests on SOC stocks and SOC bioavailability

NASA Astrophysics Data System (ADS)

Alcántara, Viridiana; Don, Axel; Vesterdal, Lars; Well, Reinhard; Nieder, Rolf

2016-04-01

Subsoils are essential within the global C cycle since they have a high soil organic carbon (SOC) storage capacity due to a high SOC saturation deficit. However, measures for enhancing SOC stocks commonly focus on topsoils. We assessed the long-term stability of topsoil SOC buried in cropland and forest subsoils by deep ploughing. Deep ploughing was promoted until the 1970s for breaking up hardpan and improving soil structure to optimize crop growth conditions. In forests deep ploughing is performed as a site preparation measure for afforestation of sandy soil aiming at increasing water availability in deeper layers and decreasing weed competition by burial of seeds. An effect of deep ploughing was the translocation of topsoil SOC into subsoils, with a concomitant mixing of SOC-poor subsoil material into the "new" topsoil horizon. Deep ploughed croplands and forests represent unique long-term "in-situ incubations" of SOC-rich material in subsoils in order to assess the effect of soil depth on SOC turnover. In this study, we sampled soil from five loamy and five sandy cropland sites as well as from five sandy forest sites, which were ploughed to 55-127 cm depth 25 to 53 years ago. Adjacent, equally managed but conventionally ploughed or not ploughed (forests) subplots were sampled as reference. On average 45 years after the deep ploughing operation, at the cropland sites, the deep ploughed soils contained 42±13 Mg ha-1 more SOC than the reference subplots down to 100 cm depth. On the contrary, at the forest sites, the SOC stocks of the deep ploughed soils contained 18±9 Mg ha-1 less SOC compared to the reference soils on average 38 years deep ploughing. These contrasting results can be explained, on the one hand, by the slower SOC accumulation in the newly formed topsoils of the deep ploughed forest soil (on average 48% lower SOC stocks in topsoil) compared to the croplands (on average 15% lower SOC stocks in topsoil). On the other hand, the buried topsoils at the forest sites exhibited similar bioavailability of SOC (measured as net C mineralization rates from short-term in-vitro incubations) as compared to the reference topsoils. In contrast, at the sandy cropland sites, net C mineralization rates were significantly lower (67%) in the buried topsoil material compared to the reference topsoil. Buried SOC in the sandy soils is thus highly stable. Together with these results, we will present data on SOC fractions and discuss their implications for our view on stability of buried SOC in croplands and forests. Our results show that deep ploughing contributes to SOC sequestration by enlarging the storage space for SOC-rich material but only under the preconditions that i) burial is accompanied by decrease in SOC bioavailability and ii) SOC accumulates considerably in the newly formed topsoil.

Interactions between deep bedrock aquifers and surface water in function of recharge and topography: a numerical study

NASA Astrophysics Data System (ADS)

Goderniaux, P.; Davy, P.; Le Borgne, T.; Bresciani, E.; Jimenez-Martinez, J.

2011-12-01

In crystalline rock regions, such as Brittany (France), important reserves of groundwater into deep fractured aquifers are increasingly used and provide high quality water compared to shallow aquifers which can be subject to agricultural contamination. However, recharge processes of these deep aquifers and interactions with surface water are not yet fully understood. In some areas, intensive pumping is carried out without guarantee of the resource quantity and quality. Understanding these processes is crucial for sustainable management of the resource. In this study, we study how deep groundwater fluxes, pathways, ages, and river-aquifer interactions vary according to recharge. We assume that water flowing from the ground surface is distributed between shallow more permeable layers and deep layers. This repartition mostly depends on recharge rates. With high recharge, groundwater levels are high and subsurface streamlines are relatively short between recharge areas and existing draining rivers, which constitutes a very dense network. Therefore, most of the groundwater fluxes occur through the more permeable shallow layers. With low recharge, groundwater levels are lower, and river and shallow permeable levels are partly disconnected from each other. This induces a general increase of the groundwater streamlines length from the recharge areas to more sporadic discharge areas, and more fluxes occur through the deep layers. Recharge conditions and river-aquifer interactions have changed over the last thousands of years, due to change in precipitation, temperatures, existence of permafrost, etc. They have strongly influenced deep groundwater fluxes and can explain current groundwater age and flux distribution. To study these interactions, a regional-scale finite difference flow model was implemented. The model covers an area of 1400 km 2 , a depth of 1 km, and the topography is characteristic of Brittany. As rivers are mainly fed by groundwater drainage, seepages faces are used on the whole modelled area, so that the river network is not prescribed but dependent on simulated groundwater conditions. Different recharge conditions were tested (from 20 to 500 mm/yr). Results show that streamline lengths and groundwater ages have exponential distributions with characteristic lengths increasing with decreasing recharge. The total area of discharge zones decreases with recharge. Groundwater age is quite variable and increases with depth, but the variability is much more important in discharge areas than recharge areas. The proportion of groundwater discharge into the sea (compared to total recharge) increases when total recharge decreases. The model was also used to test the influence of heterogeneity or hydraulic conductivity contrast between shallow and deep layers on deep groundwater fluxes. In a completely homogeneous model, deep fluxes are correlated with recharge fluxes. Correlation decreases while contrast increases. If the permeability of the shallow weather zone is now 3 orders of magnitude larger than of deep aquifer, we observed that simulated deep groundwater fluxes increase locally, despite total recharge at the level of the ground surface decreases.

Single-crystal structure determination of hydrous minerals and insights into a wet deep lower mantle

NASA Astrophysics Data System (ADS)

Zhang, L.; Yuan, H.; Meng, Y.; Popov, D.

2017-12-01

Water enters the Earth's interior through hydrated subducting slabs. How deep within the lower mantle (670-2900 km depth) can water be transported down and stored depends upon the availability of hydrous phases that is thermodynamically stable under the high P-T conditions and have a sufficiently high density to sink through the lower mantle. Phase H [MgSiH2O4] (1) and the δ-AlOOH (2) form solid solutions that are stable in the deep lower mantle (3), but the solid solution phase is 10% lighter than the corresponding lower mantle. Recent experimental discoveries of the pyrite (Py) structured FeO2 and FeOOH (4-6) suggest that these Fe-enriched phases can be transported to the deepest lower mantle owing to their high density. We have further discovered a very dense hydrous phase in (Fe,Al)OOH with a previously unknown hexagonal symmetry and this phase is stable relative to the Py-phase under extreme high P-T conditions in the deep lower mantle. Through in situ multigrain analysis (7) and single-crystal structure determination of the hydrous minerals at P-Tconditions of the deep lower mantle, we can obtain detailed structure information of the hydrous phases and therefore provide insights into the hydration mechanism in the deep lower mantle. These highly stable hydrous minerals extend the water cycle at least to the depth of 2900 km. 1. M. Nishi et al., Nature Geoscience 7, 224-227 (2014). 2. E. Ohtani, K. Litasov, A. Suzuki, T. Kondo, Geophysical Research Letters 28, 3991-3993 (2001). 3. I. Ohira et al., Earth and Planetary Science Letters 401, 12-17 (2014). 4. Q. Hu et al., Proceedings of the National Academy of Sciences of the United States of America 114, 1498-1501 (2017). 5. M. Nishi, Y. Kuwayama, J. Tsuchiya, T. Tsuchiya, Nature 547, 205-208 (2017). 6. Q. Hu et al., Nature 534, 241-244 (2016). 7. L. Zhang et al., American Mineralogist 101, 231-234 (2016).

Microbiome composition and geochemical characteristics of deep subsurface high-pressure environment, Pyhäsalmi mine Finland

PubMed Central

Miettinen, Hanna; Kietäväinen, Riikka; Sohlberg, Elina; Numminen, Mikko; Ahonen, Lasse; Itävaara, Merja

2015-01-01

Pyhäsalmi mine in central Finland provides an excellent opportunity to study microbial and geochemical processes in a deep subsurface crystalline rock environment through near-vertical drill holes that reach to a depth of more than two kilometers below the surface. However, microbial sampling was challenging in this high-pressure environment. Nucleic acid yields obtained were extremely low when compared to the cell counts detected (1.4 × 104 cells mL−1) in water. The water for nucleic acid analysis went through high decompression (60–130 bar) during sampling, whereas water samples for detection of cell counts by microscopy could be collected with slow decompression. No clear cells could be identified in water that went through high decompression. The high-pressure decompression may have damaged part of the cells and the nucleic acids escaped through the filter. The microbial diversity was analyzed from two drill holes by pyrosequencing amplicons of the bacterial and archaeal 16S rRNA genes and from the fungal ITS regions from both DNA and RNA fractions. The identified prokaryotic diversity was low, dominated by Firmicute, Beta- and Gammaproteobacteria species that are common in deep subsurface environments. The archaeal diversity consisted mainly of Methanobacteriales. Ascomycota dominated the fungal diversity and fungi were discovered to be active and to produce ribosomes in the deep oligotrophic biosphere. The deep fluids from the Pyhäsalmi mine shared several features with other deep Precambrian continental subsurface environments including saline, Ca-dominated water and stable isotope compositions positioning left from the meteoric water line. The dissolved gas phase was dominated by nitrogen but the gas composition clearly differed from that of atmospheric air. Despite carbon-poor conditions indicated by the lack of carbon-rich fracture fillings and only minor amounts of dissolved carbon detected in formation waters, some methane was found in the drill holes. No dramatic differences in gas compositions were observed between different gas sampling methods tested. For simple characterization of gas composition the most convenient way to collect samples is from free flowing fluid. However, compared to a pressurized method a relative decrease in the least soluble gases may appear. PMID:26579109

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

NASA Technical Reports Server (NTRS)

Newman, Jeffrey A.; Cooper, Michael C.; Davis, Marc; Faber, S. M.; Coil, Alison L; Guhathakurta, Puraga; Koo, David C.; Phillips, Andrew C.; Conroy, Charlie; Dutton, Aaron A.;

Characterization of interactions between sub-surface compartments and a deep sub-vertical aquifer in crystalline basement (St-Brice en Coglès, French Brittany)

NASA Astrophysics Data System (ADS)

Roques, C.; Bour, O.; Aquilina, L.; Longuevergne, L.; Dewandel, B.; Hochreutener, R.; Schroetter, J.; Labasque, T.; Lavenant, N.

2012-12-01

Hard-rock aquifers constitute in general a limited groundwater resource whose upper part is particularly sensitive to anthropogenic activities. Locally, some high production aquifers can be encountered, typically near regional tectonic discontinuities which may constitute preferential flow paths. However, this kind of aquifer, in particular their interactions with sub-surface, is often very difficult to characterize. We investigated the hydrogeological functioning of a deep vertical conductive fractured zone, focusing on the interactions between hydrologic compartments, thanks to a multidisciplinary approach and a variety of field experiments. A specific field site located in north east of French Brittany, in crystalline bedrock, was selected because of high measured yields during drilling (100 m3/h), essentially related to permeable fractures at 120 m depth and deeper. Three deep boreholes 80 to 250 deep were drilled at relatively short distances (typically 30 meters); one of them has been cored for detailed geological information. Shallower boreholes were also drilled (7 to 20 m deep) to characterize the upper weathered compartment and the hydraulic connections with the deep compartment. The system was characterized both in natural conditions and during a 9-week large scale pumping test carried out at a pumping rate of 45 m3/h. To describe the hydraulic properties and the functioning of the deep hydraulic structure, we used a multidisciplinary approach: (a) well head variations and traditional pumping test interpretations, (b) high-resolution flow loggings to identify fracture connectivity, (c) tracer tests to estimate transfer times and groundwater fluxes between main compartments and (d) multi-parameters fluid logging, geochemistry and groundwater dating to identify water origin and mixing processes between different reservoirs. The geometry of the main permeable structure has been identified combining geological information and hydraulic interpretations. It shows a clear compartmentalization of the aquifer with a strong spatial heterogeneity in permeability. Although using a packer to force the pumping to be deeper than 80 meters, a very fast reaction of the upper aquifer during pumping with clear leaky effects was observed. Heat-Pulse Flowmeter logs also show the interconnections between compartments. During the pumping, we also monitored a high decrease of groundwater ages of the water pumped. Combination of all these methods allowed the flow connections between compartments to be identified and the fluxes between the different compartments to be quantified. We show in particular how the deep groundwater resource is strongly dependent of shallower compartments. Identifying flow properties and origin of water in a deep aquifer is an important issue to optimize the management of such groundwater resources. In particular the estimation of the groundwater capacity, and also to predict groundwater quality changes are essential. This study allows quantifying fluxes between compartments both in natural and pumping conditions. Such a characterization is crucial to assess the sustainability of deep hard-rock aquifers for groundwater supply.

Global Lunar Topography from the Deep Space Gateway for Science and Exploration

NASA Astrophysics Data System (ADS)

Archinal, B.; Gaddis, L.; Kirk, R.; Edmundson, K.; Stone, T.; Portree, D.; Keszthelyi, L.

2018-02-01

The Deep Space Gateway, in low lunar orbit, could be used to achieve a long standing goal of lunar science, collecting stereo images in two months to make a complete, uniform, high resolution, known accuracy, global topographic model of the Moon.

Earth-from-Luna Limb Imager (ELLI) for Deep Space Gateway

NASA Astrophysics Data System (ADS)

Gorkavyi, N.; DeLand, M.

2018-02-01

The new type of limb imager with a high-frequency imaging proposed for Deep Space Gateway. Each day this CubeSat' scale imager will generate the global 3D model of the aerosol component of the Earth's atmosphere and Polar Mesospheric Clouds.

High-power transmitter automation. [deep space network

NASA Technical Reports Server (NTRS)

Gosline, R.

1980-01-01

The current status of the transmitter automation development applicable to all transmitters in the deep space network is described. Interface and software designs are described that improve reliability and reduce the time required for subsystem turn-on and klystron saturation to less than 10 minutes.

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

PubMed

Gopakumar, G; Hari Babu, K; Mishra, Deepak; Gorthi, Sai Siva; Sai Subrahmanyam, Gorthi R K

2017-01-01

Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep-learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell lines (K562, MOLT, and HL60). The cell images used in the classification are captured using a low-cost, high-throughput cell imaging technique: microfluidics-based imaging flow cytometry. We demonstrate that without any conventional fine segmentation followed by explicit feature extraction, the proposed deep-learning algorithms effectively classify the coarsely localized cell lines. We show that the designed deep belief network as well as the deeply pretrained convolutional neural network outperform the conventionally used decision systems and are important in the medical domain, where the availability of labeled data is limited for training. We hope that our work enables the development of a clinically significant high-throughput microfluidic microscopy-based tool for disease screening/triaging, especially in resource-limited settings.

Effects of Slow Deep Breathing at High Altitude on Oxygen Saturation, Pulmonary and Systemic Hemodynamics

PubMed Central

Bilo, Grzegorz; Revera, Miriam; Bussotti, Maurizio; Bonacina, Daniele; Styczkiewicz, Katarzyna; Caldara, Gianluca; Giglio, Alessia; Faini, Andrea; Giuliano, Andrea; Lombardi, Carolina; Kawecka-Jaszcz, Kalina; Mancia, Giuseppe; Agostoni, Piergiuseppe; Parati, Gianfranco

2012-01-01

Slow deep breathing improves blood oxygenation (SpO2) and affects hemodynamics in hypoxic patients. We investigated the ventilatory and hemodynamic effects of slow deep breathing in normal subjects at high altitude. We collected data in healthy lowlanders staying either at 4559 m for 2–3 days (Study A; N = 39) or at 5400 m for 12–16 days (Study B; N = 28). Study variables, including SpO2 and systemic and pulmonary arterial pressure, were assessed before, during and after 15 minutes of breathing at 6 breaths/min. At the end of slow breathing, an increase in SpO2 (Study A: from 80.2±7.7% to 89.5±8.2%; Study B: from 81.0±4.2% to 88.6±4.5; both p<0.001) and significant reductions in systemic and pulmonary arterial pressure occurred. This was associated with increased tidal volume and no changes in minute ventilation or pulmonary CO diffusion. Slow deep breathing improves ventilation efficiency for oxygen as shown by blood oxygenation increase, and it reduces systemic and pulmonary blood pressure at high altitude but does not change pulmonary gas diffusion. PMID:23152851

Effects of slow deep breathing at high altitude on oxygen saturation, pulmonary and systemic hemodynamics.

PubMed

Bilo, Grzegorz; Revera, Miriam; Bussotti, Maurizio; Bonacina, Daniele; Styczkiewicz, Katarzyna; Caldara, Gianluca; Giglio, Alessia; Faini, Andrea; Giuliano, Andrea; Lombardi, Carolina; Kawecka-Jaszcz, Kalina; Mancia, Giuseppe; Agostoni, Piergiuseppe; Parati, Gianfranco

2012-01-01

Slow deep breathing improves blood oxygenation (Sp(O2)) and affects hemodynamics in hypoxic patients. We investigated the ventilatory and hemodynamic effects of slow deep breathing in normal subjects at high altitude. We collected data in healthy lowlanders staying either at 4559 m for 2-3 days (Study A; N = 39) or at 5400 m for 12-16 days (Study B; N = 28). Study variables, including Sp(O2) and systemic and pulmonary arterial pressure, were assessed before, during and after 15 minutes of breathing at 6 breaths/min. At the end of slow breathing, an increase in Sp(O2) (Study A: from 80.2±7.7% to 89.5±8.2%; Study B: from 81.0±4.2% to 88.6±4.5; both p<0.001) and significant reductions in systemic and pulmonary arterial pressure occurred. This was associated with increased tidal volume and no changes in minute ventilation or pulmonary CO diffusion. Slow deep breathing improves ventilation efficiency for oxygen as shown by blood oxygenation increase, and it reduces systemic and pulmonary blood pressure at high altitude but does not change pulmonary gas diffusion.

Quantum dots versus organic fluorophores in fluorescent deep-tissue imaging--merits and demerits.

PubMed

Bakalova, Rumiana; Zhelev, Zhivko; Gadjeva, Veselina

2008-12-01

The use of fluorescence in deep-tissue imaging is rapidly expanding in last several years. The progress in fluorescent molecular probes and fluorescent imaging techniques gives an opportunity to detect single cells and even molecular targets in live organisms. The highly sensitive and high-speed fluorescent molecular sensors and detection devices allow the application of fluorescence in functional imaging. With the development of novel bright fluorophores based on nanotechnologies and 3D fluorescence scanners with high spatial and temporal resolution, the fluorescent imaging has a potential to become an alternative of the other non-invasive imaging techniques as magnetic resonance imaging, positron-emission tomography, X-ray, computing tomography. The fluorescent imaging has also a potential to give a real map of human anatomy and physiology. The current review outlines the advantages of fluorescent nanoparticles over conventional organic dyes in deep-tissue imaging in vivo and defines the major requirements to the "perfect fluorophore". The analysis proceeds from the basic principles of fluorescence and major characteristics of fluorophores, light-tissue interactions, and major limitations of fluorescent deep-tissue imaging. The article is addressed to a broad readership - from specialists in this field to university students.

Ship detection leveraging deep neural networks in WorldView-2 images

NASA Astrophysics Data System (ADS)

Yamamoto, T.; Kazama, Y.

2017-10-01

Interpretation of high-resolution satellite images has been so difficult that skilled interpreters must have checked the satellite images manually because of the following issues. One is the requirement of the high detection accuracy rate. The other is the variety of the target, taking ships for example, there are many kinds of ships, such as boat, cruise ship, cargo ship, aircraft carrier, and so on. Furthermore, there are similar appearance objects throughout the image; therefore, it is often difficult even for the skilled interpreters to distinguish what object the pixels really compose. In this paper, we explore the feasibility of object extraction leveraging deep learning with high-resolution satellite images, especially focusing on ship detection. We calculated the detection accuracy using the WorldView-2 images. First, we collected the training images labelled as "ship" and "not ship". After preparing the training data, we defined the deep neural network model to judge whether ships are existing or not, and trained them with about 50,000 training images for each label. Subsequently, we scanned the evaluation image with different resolution windows and extracted the "ship" images. Experimental result shows the effectiveness of the deep learning based object detection.

Hydrogen-bearing iron peroxide and its implications to the deep Earth

NASA Astrophysics Data System (ADS)

Liu, J.; Hu, Q.; Kim, D. Y.; Wu, Z.; Wang, W.; Alp, E. E.; Yang, L.; Xiao, Y.; Meng, Y.; Chow, P.; Greenberg, E.; Prakapenka, V. B.; Mao, H. K.; Mao, W. L.

2017-12-01

Hydrous materials subducted into the deep mantle may play a significant role in the geophysical and geochemical processes of the lower mantle through geological time, but their roles have not become clear yet in the region. Hydrogen-bearing iron peroxide (FeO2Hx) was recently discovered to form through dehydrogenation of goethite (e.g., FeOOH) and the reaction between hematite (Fe2O3) and water under deep lower mantle conditions. We conducted synchrotron Mössbauer, X-ray absorption, and X-ray emission spectroscopy measurements to investigate the electronic spin and valence states of iron in hydrogen-bearing iron peroxide (FeO2Hx) in-situ at high pressures. Combined with theoretical calculations and other high-pressure experiments (i.e., nuclear resonant inelastic x-ray scattering spectroscopy and X-ray diffraction coupled with laser-heated diamond-anvil cell techniques), we find that the intriguing properties of FeO2Hx could shed light on the origin of a number of the observed geochemical and geophysical anomalies in the deep Earth.

Macroecological drivers of archaea and bacteria in benthic deep-sea ecosystems

PubMed Central

Danovaro, Roberto; Molari, Massimiliano; Corinaldesi, Cinzia; Dell’Anno, Antonio

2016-01-01

Bacteria and archaea dominate the biomass of benthic deep-sea ecosystems at all latitudes, playing a crucial role in global biogeochemical cycles, but their macroscale patterns and macroecological drivers are still largely unknown. We show the results of the most extensive field study conducted so far to investigate patterns and drivers of the distribution and structure of benthic prokaryote assemblages from 228 samples collected at latitudes comprising 34°N to 79°N, and from ca. 400- to 5570-m depth. We provide evidence that, in deep-sea ecosystems, benthic bacterial and archaeal abundances significantly increase from middle to high latitudes, with patterns more pronounced for archaea, and particularly for Marine Group I Thaumarchaeota. Our results also reveal that different microbial components show varying sensitivities to changes in temperature conditions and food supply. We conclude that climate change will primarily affect deep-sea benthic archaea, with important consequences on global biogeochemical cycles, particularly at high latitudes. PMID:27386507

Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes.

PubMed

Burkholder, William F; Newell, Evan W; Poidinger, Michael; Chen, Swaine; Fink, Katja

2017-01-01

The inaugural workshop "Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes" was held in Singapore on 13-14 October 2016. The aim of the workshop was to discuss the latest trends in using high-throughput sequencing, bioinformatics, and allied technologies to analyze immune and pathogen repertoires and their interplay within the host, bringing together key international players in the field and Singapore-based researchers and clinician-scientists. The focus was in particular on the application of these technologies for the improvement of patient diagnosis, prognosis and treatment, and for other broad public health outcomes. The presentations by scientists and clinicians showed the potential of deep sequencing technology to capture the coevolution of adaptive immunity and pathogens. For clinical applications, some key challenges remain, such as the long turnaround time and relatively high cost of deep sequencing for pathogen identification and characterization and the lack of international standardization in immune repertoire analysis.

Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes

PubMed Central

Burkholder, William F.; Newell, Evan W.; Poidinger, Michael; Chen, Swaine; Fink, Katja

2017-01-01

The inaugural workshop “Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes” was held in Singapore on 13–14 October 2016. The aim of the workshop was to discuss the latest trends in using high-throughput sequencing, bioinformatics, and allied technologies to analyze immune and pathogen repertoires and their interplay within the host, bringing together key international players in the field and Singapore-based researchers and clinician-scientists. The focus was in particular on the application of these technologies for the improvement of patient diagnosis, prognosis and treatment, and for other broad public health outcomes. The presentations by scientists and clinicians showed the potential of deep sequencing technology to capture the coevolution of adaptive immunity and pathogens. For clinical applications, some key challenges remain, such as the long turnaround time and relatively high cost of deep sequencing for pathogen identification and characterization and the lack of international standardization in immune repertoire analysis. PMID:28620372

Optimizing the flow of care for prevention and treatment of deep vein thrombosis and pulmonary embolism.

PubMed

Ecklund, M M

1995-11-01

Critically ill patients have multiple risk factors for deep vein thrombosis and pulmonary embolism. The majority of patients with pulmonary embolism have a lower extremity deep vein thrombosis as a source of origin. Pulmonary embolism causes a high mortality rate in the hemodynamically compromised individual. Awareness of risk factors relative to the development of deep vein thrombosis and pulmonary embolism is important for the critical care nurse. Understanding the pathophysiology can help guide prophylaxis and treatment plans. The therapies, from invasive to mechanical, all carry risks and benefits, and are weighed for each patient. The advanced practice nurse, whether in the direct or indirect role, has an opportunity to impact the care of the high risk patient. Options range from teaching the nurse who is new to critical care, to teaching patients and families. Development of multidisciplinary protocols and clinical pathways are ways to impact the standard of care. Improved delivery of care methods can optimize the care rendered in an ever changing field of critical care.

RETINAL DEEP CAPILLARY ISCHEMIA ASSOCIATED WITH AN OCCLUDED CONGENITAL RETINAL MACROVESSEL.

PubMed

Hasegawa, Taiji; Ogata, Nahoko

2017-01-01

To report the case of a patient with an occluded congenital retinal macrovessel accompanied by retinal deep capillary ischemia. A 38-year-old woman presented with a 2-day history of a paracentral scotoma of her right eye. Fundus photograph showed a dilated congenital retinal macrovessel with arteriovenous anastomosis, an intravascular white region indicating the thrombus at arteriovenous anastomotic region, and an area of retinal whitening temporal to the fovea. The spectral domain optical coherence tomography images through the area of retinal whitening showed a thickening and highly reflectivity at the level of the inner nuclear layer, which is likely due to the deep capillary ischemia. After 6 weeks, spectral domain optical coherence tomography images through the same area demonstrated a thinning and atrophy of only the inner nuclear layer, and the patient's paracentral scotoma persisted. Acute capillary hemodynamic changes caused deep capillary ischemia. The spectral domain optical coherence tomography showed a highly reflective lesion at the level of the inner nuclear layer in the acute phase.

Balanced bilinguals favor lexical processing in their opaque language and conversion system in their shallow language.

PubMed

Buetler, Karin A; de León Rodríguez, Diego; Laganaro, Marina; Müri, René; Nyffeler, Thomas; Spierer, Lucas; Annoni, Jean-Marie

2015-11-01

Referred to as orthographic depth, the degree of consistency of grapheme/phoneme correspondences varies across languages from high in shallow orthographies to low in deep orthographies. The present study investigates the impact of orthographic depth on reading route by analyzing evoked potentials to words in a deep (French) and shallow (German) language presented to highly proficient bilinguals. ERP analyses to German and French words revealed significant topographic modulations 240-280 ms post-stimulus onset, indicative of distinct brain networks engaged in reading over this time window. Source estimations revealed that these effects stemmed from modulations of left insular, inferior frontal and dorsolateral regions (German>French) previously associated to phonological processing. Our results show that reading in a shallow language was associated to a stronger engagement of phonological pathways than reading in a deep language. Thus, the lexical pathways favored in word reading are reinforced by phonological networks more strongly in the shallow than deep orthography. Copyright © 2015 Elsevier Inc. All rights reserved.

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer

NASA Astrophysics Data System (ADS)

Vandenberghe, Michel E.; Scott, Marietta L. J.; Scorer, Paul W.; Söderberg, Magnus; Balcerzak, Denis; Barker, Craig

2017-04-01

Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a computational approach based on deep learning that automatically scores HER2, a biomarker that defines patient eligibility for anti-HER2 targeted therapies in breast cancer. In a cohort of 71 breast tumour resection samples, automated scoring showed a concordance of 83% with a pathologist. The twelve discordant cases were then independently reviewed, leading to a modification of diagnosis from initial pathologist assessment for eight cases. Diagnostic discordance was found to be largely caused by perceptual differences in assessing HER2 expression due to high HER2 staining heterogeneity. This study provides evidence that deep learning aided diagnosis can facilitate clinical decision making in breast cancer by identifying cases at high risk of misdiagnosis.

Deep, diverse and definitely different: unique attributes of the world's largest ecosystem

NASA Astrophysics Data System (ADS)

Ramirez-Llodra, E.; Brandt, A.; Danovaro, R.; de Mol, B.; Escobar, E.; German, C. R.; Levin, L. A.; Martinez Arbizu, P.; Menot, L.; Buhl-Mortensen, P.; Narayanaswamy, B. E.; Smith, C. R.; Tittensor, D. P.; Tyler, P. A.; Vanreusel, A.; Vecchione, M.

2010-09-01

The deep sea, the largest biome on Earth, has a series of characteristics that make this environment both distinct from other marine and land ecosystems and unique for the entire planet. This review describes these patterns and processes, from geological settings to biological processes, biodiversity and biogeographical patterns. It concludes with a brief discussion of current threats from anthropogenic activities to deep-sea habitats and their fauna. Investigations of deep-sea habitats and their fauna began in the late 19th century. In the intervening years, technological developments and stimulating discoveries have promoted deep-sea research and changed our way of understanding life on the planet. Nevertheless, the deep sea is still mostly unknown and current discovery rates of both habitats and species remain high. The geological, physical and geochemical settings of the deep-sea floor and the water column form a series of different habitats with unique characteristics that support specific faunal communities. Since 1840, 28 new habitats/ecosystems have been discovered from the shelf break to the deep trenches and discoveries of new habitats are still happening in the early 21st century. However, for most of these habitats the global area covered is unknown or has been only very roughly estimated; an even smaller - indeed, minimal - proportion has actually been sampled and investigated. We currently perceive most of the deep-sea ecosystems as heterotrophic, depending ultimately on the flux on organic matter produced in the overlying surface ocean through photosynthesis. The resulting strong food limitation thus shapes deep-sea biota and communities, with exceptions only in reducing ecosystems such as inter alia hydrothermal vents or cold seeps. Here, chemoautolithotrophic bacteria play the role of primary producers fuelled by chemical energy sources rather than sunlight. Other ecosystems, such as seamounts, canyons or cold-water corals have an increased productivity through specific physical processes, such as topographic modification of currents and enhanced transport of particles and detrital matter. Because of its unique abiotic attributes, the deep sea hosts a specialized fauna. Although there are no phyla unique to deep waters, at lower taxonomic levels the composition of the fauna is distinct from that found in the upper ocean. Amongst other characteristic patterns, deep-sea species may exhibit either gigantism or dwarfism, related to the decrease in food availability with depth. Food limitation on the seafloor and water column is also reflected in the trophic structure of heterotrophic deep-sea communities, which are adapted to low energy availability. In most of these heterotrophic habitats, the dominant megafauna is composed of detritivores, while filter feeders are abundant in habitats with hard substrata (e.g. mid-ocean ridges, seamounts, canyon walls and coral reefs). Chemoautotrophy through symbiotic relationships is dominant in reducing habitats. Deep-sea biodiversity is among of the highest on the planet, mainly composed of macro and meiofauna, with high evenness. This is true for most of the continental margins and abyssal plains with hot spots of diversity such as seamounts or cold-water corals. However, in some ecosystems with particularly "extreme" physicochemical processes (e.g. hydrothermal vents), biodiversity is low but abundance and biomass are high and the communities are dominated by a few species. Two large-scale diversity patterns have been discussed for deep-sea benthic communities. First, a unimodal relationship between diversity and depth is observed, with a peak at intermediate depths (2000-3000 m), although this is not universal and particular abiotic processes can modify the trend. Secondly, a poleward trend of decreasing diversity has been discussed, but this remains controversial and studies with larger and more robust data sets are needed. Because of the paucity in our knowledge of habitat coverage and species composition, biogeographic studies are mostly based on regional data or on specific taxonomic groups. Recently, global biogeographic provinces for the pelagic and benthic deep ocean have been described, using environmental and, where data were available, taxonomic information. This classification described 30 pelagic provinces and 38 benthic provinces divided into 4 depth ranges, as well as 10 hydrothermal vent provinces. One of the major issues faced by deep-sea biodiversity and biogeographical studies is related to the high number of species new to science that are collected regularly, together with the slow description rates for these new species. Taxonomic coordination at the global scale is particularly difficult, but is essential if we are to analyse large diversity and biogeographic trends.

AdS Black Disk Model for Small-x Deep Inelastic Scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cornalba, Lorenzo; Costa, Miguel S.; Penedones, Joao

2010-08-13

Using the approximate conformal invariance of QCD at high energies we consider a simple anti-de Sitter black disk model to describe saturation in deep inelastic scattering. Deep inside saturation the structure functions have the same power law scaling, F{sub T}{approx}F{sub L}{approx}x{sup -{omega}}, where {omega} is related to the expansion rate of the black disk with energy. Furthermore, the ratio F{sub L}/F{sub T} is given by the universal value (1+{omega}/3+{omega}), independently of the target. For {gamma}*-{gamma}* scattering at high energies we obtain explicit expressions and ratios for the total cross sections of transverse and longitudinal photons in terms of the singlemore » parameter {omega}.« less

The Neutron Tomography Studies of the Rocks from the Kola Superdeep Borehole

NASA Astrophysics Data System (ADS)

Kichanov, S. E.; Kozlenko, D. P.; Ivankina, T. I.; Rutkauskas, A. V.; Lukin, E. V.; Savenko, B. N.

The volume morphology of a gneiss sample K-8802 recovered from the deep of 8802 m of the Kola Superdeep Borehole and its surface homologue sample PL-36 have been studied by means of neutron radiography and tomography methods. The volumes and size distributions of a biotite-muscovite grains as well as grains orientation distribution have been obtained from experimental data. It was found that the average volumes of the biotite-muscovite grains in surface homologue sample is noticeably larger than the average volume of grains in the deep-seated gneiss sample K-8802. This drastically differences in grains volumes can be explained by the recrystallization processes in deep of the Kola Superdeep Borehole at high temperatures and high pressures.

DEEP UNDERGROUND NEUTRINO EXPERIMENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, Robert J.

2016-03-03

The Deep Underground Neutrino Experiment (DUNE) collaboration will perform an experiment centered on accelerator-based long-baseline neutrino studies along with nucleon decay and topics in neutrino astrophysics. It will consist of a modular 40-kt (fiducial) mass liquid argon TPC detector located deep underground at the Sanford Underground Research Facility in South Dakota and a high-resolution near detector at Fermilab in Illinois. This conguration provides a 1300-km baseline in a megawatt-scale neutrino beam provided by the Fermilab- hosted international Long-Baseline Neutrino Facility.

Size of the thrombus in acute deep vein thrombosis and the significance of patients' age and sex.

PubMed

Kierkegaard, A

1981-01-01

To determine the significance of patients' age and sex on the size of the thrombus in acute deep vein thrombosis, 420 consecutive phlebograms with acute deep vein thrombosis were studied. A significant correlation between the size of the thrombus and increasing age of the patient as well as the sex of male was noted. It is concluded that older patients and men often are at a high risk of pulmonary embolism at the time of diagnosis.

Advancing Navigation, Timing, and Science with the Deep Space Atomic Clock

NASA Technical Reports Server (NTRS)

Ely, Todd A.; Seubert, Jill; Bell, Julia

2014-01-01

NASA's Deep Space Atomic Clock mission is developing a small, highly stable mercury ion atomic clock with an Allan deviation of at most 1e-14 at one day, and with current estimates near 3e-15. This stability enables one-way radiometric tracking data with accuracy equivalent to and, in certain conditions, better than current two-way deep space tracking data; allowing a shift to a more efficient and flexible one-way deep space navigation architecture. DSAC-enabled one-way tracking will benefit navigation and radio science by increasing the quantity and quality of tracking data. Additionally, DSAC would be a key component to fully-autonomous onboard radio navigation useful for time-sensitive situations. Potential deep space applications of DSAC are presented, including orbit determination of a Mars orbiter and gravity science on a Europa flyby mission.

Deep Vadose Zone Treatability Test of Soil Desiccation for the Hanford Central Plateau: Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truex, Michael J.; Chronister, Glen B.; Strickland, Christopher E.

Some of the inorganic and radionuclide contaminants in the deep vadose zone at the Hanford Site are at depths where direct exposure pathways are not of concern, but may need to be remediated to protect groundwater. The Department of Energy developed a treatability test program for technologies to address Tc-99 and uranium in the deep vadose zone. These contaminants are mobile in the subsurface environment, have been detected at high concentrations deep in the vadose zone, and at some locations have reached groundwater. The treatability test of desiccation described herein was conducted as an element of the deep vadose zonemore » treatability test program. Desiccation was shown to be a potentially effective vadose zone remediation technology to protect groundwater when used in conjunction with a surface infiltration barrier.« less

Deep learning decision fusion for the classification of urban remote sensing data

NASA Astrophysics Data System (ADS)

Abdi, Ghasem; Samadzadegan, Farhad; Reinartz, Peter

2018-01-01

Multisensor data fusion is one of the most common and popular remote sensing data classification topics by considering a robust and complete description about the objects of interest. Furthermore, deep feature extraction has recently attracted significant interest and has become a hot research topic in the geoscience and remote sensing research community. A deep learning decision fusion approach is presented to perform multisensor urban remote sensing data classification. After deep features are extracted by utilizing joint spectral-spatial information, a soft-decision made classifier is applied to train high-level feature representations and to fine-tune the deep learning framework. Next, a decision-level fusion classifies objects of interest by the joint use of sensors. Finally, a context-aware object-based postprocessing is used to enhance the classification results. A series of comparative experiments are conducted on the widely used dataset of 2014 IEEE GRSS data fusion contest. The obtained results illustrate the considerable advantages of the proposed deep learning decision fusion over the traditional classifiers.

Deep-towed high resolution seismic imaging II: Determination of P-wave velocity distribution

NASA Astrophysics Data System (ADS)

Marsset, B.; Ker, S.; Thomas, Y.; Colin, F.

2018-02-01

The acquisition of high resolution seismic data in deep waters requires the development of deep towed seismic sources and receivers able to deal with the high hydrostatic pressure environment. The low frequency piezoelectric transducer of the SYSIF (SYstème Sismique Fond) deep towed seismic device comply with the former requirement taking advantage of the coupling of a mechanical resonance (Janus driver) and a fluid resonance (Helmholtz cavity) to produce a large frequency bandwidth acoustic signal (220-1050 Hz). The ability to perform deep towed multichannel seismic imaging with SYSIF was demonstrated in 2014, yet, the ability to determine P-wave velocity distribution wasn't achieved. P-wave velocity analysis relies on the ratio between the source-receiver offset range and the depth of the seismic reflectors, thus towing the seismic source and receivers closer to the sea bed will provide a better geometry for P-wave velocity determination. Yet, technical issues, related to the acoustic source directivity, arise for this approach in the particular framework of piezoelectric sources. A signal processing sequence is therefore added to the initial processing flow. Data acquisition took place during the GHASS (Gas Hydrates, fluid Activities and Sediment deformations in the western Black Sea) cruise in the Romanian waters of the Black Sea. The results of the imaging processing are presented for two seismic data sets acquired over gas hydrates and gas bearing sediments. The improvement in the final seismic resolution demonstrates the validity of the velocity model.

Inert gas narcosis and the encoding and retrieval of long-term memory.

PubMed

Kneller, Wendy; Hobbs, Malcolm

2013-12-01

Prior research has indicated that inert gas narcosis (IGN) causes decrements in free recall memory performance and that these result from disruption of either encoding or self-guided search in the retrieval process. In a recent study we provided evidence, using a Levels of Processing approach, for the hypothesis that IGN affects the encoding of new information. The current study sought to replicate these results with an improved methodology. The effect of ambient pressure (111.5-212.8 kPa/1-11 msw vs. 456-516.8 kPa/35-41 msw) and level of processing (shallow vs. deep) on free recall memory performance was measured in 34 divers in the context of an underwater field experiment. Free recall was significantly worse at high ambient pressure compared to low ambient pressure in the deep processing condition (low pressure: M = 5.6; SD = 2.7; high pressure: M = 3.3; SD = 1.4), but not in the shallow processing condition (low pressure: M = 3.9; SD = 1.7; high pressure: M = 3.1; SD = 1.8), indicating IGN impaired memory ability in the deep processing condition. In the shallow water, deep processing improved recall over shallow processing but, significantly, this effect was eliminated in the deep water. In contrast to our earlier study this supported the hypothesis that IGN affects the self-guided search of information and not encoding. It is suggested that IGN may affect both encoding and self-guided search and further research is recommended.

Initial geochemistry data of the Lake Ohrid (Macedonia, Albania) "DEEP" site sediment record: The ICDP SCOPSCO drilling project

NASA Astrophysics Data System (ADS)

Francke, Alexander; Wagner, Bernd; Krastel, Sebastian; Lindhorst, Katja; Mantke, Nicole; Klinghardt, Dorothea

2014-05-01

Lake Ohrid, located at the border of Macedonia and Albania is about 30 km long, 15 km wide and up to 290 m deep. Formed within a tectonic graben, Lake Ohrid is considered to be the oldest lake in Europe. The ICDP SCOPSCO (Scientific Collaboration of Past Speciation Conditions in Lake Ohrid) deep drilling campaign at Lake Ohrid in spring 2013 aimed (a) to obtain more precise information about the age and origin of the lake, (b) to unravel the seismotectonic history of the lake area including effects of major earthquakes and associated mass wasting events, (c) to obtain a continuous record containing information on volcanic activities and climate changes in the central northern Mediterranean region, and (d) to better understand the impact of major geological/environmental events on general evolutionary patterns and shaping an extraordinary degree of endemic biodiversity as a matter of global significance. Drilling was carried out by DOSECC (Salt Lake City, USA) using the DLDS (Deep Lake Drilling System) with a hydraulic piston corer for surface sediments and rotation drilling for harder, deeper sediments. Overall, about 2,100 m of sediment were recovered from 4 drill sites. At the "DEEP" site in the center of the lake, seismic data indicated a maximum sediment fill of ca. 700 m, of which the uppermost 568 m sediment were recovered. Initial data from core catcher samples and on-site susceptibility measurements indicate that the sediment sequence covers more than 1.2 million years and provides a continuous archive of environmental and climatological variability in the area. Currently, core opening, core description, XRF and MSCL -scanning, core correlation, and sub-sampling of the sediment cores from the "DEEP" site is conducted at the University of Cologne. High-resolution geochemical data obtained from XRF-scanning imply that the sediments from the "DEEP" site are highly sensitive to climate and environmental variations in the Balkan area over the last few glacial-interglacial cycles. Interglacial periods are characterized by high Ca counts, likely associated with a high content of calcite in the sediments. Previous studies have shown that the calcite contents in sediments from Lake Ohrid are predominantly triggered by precipitation of endogenic calcite resulting from enhanced photosynthesis and higher temperatures. Moreover, high Ca counts mostly correspond to low K counts indicating reduced clastic input and a denser vegetation cover in the catchment. In contrast, high K and low Ca counts characterize glacial periods, indicating reduced precipitation of endognic calcite and enhanced deposition of clastic material. The variations in Ca and K counts mainly represent climatic variations on a glacial-interglacial timescale. Inorganic geochemistry data shall also be used to improve the age control of the "DEEP" site sequence. First findings of macroscopic tephra horizons allow a preliminary age control on the sediment succession, and peaks in K, Sr, Zr, and magnetic susceptibility might indicate the occurrence of cryptotephralayers in the sediment sequence.

A sub-atmospheric chemical vapor deposition process for deposition of oxide liner in high aspect ratio through silicon vias.

PubMed

Lisker, Marco; Marschmeyer, Steffen; Kaynak, Mehmet; Tekin, Ibrahim

2011-09-01

The formation of a Through Silicon Via (TSV) includes a deep Si trench etching and the formation of an insulating layer along the high-aspect-ratio trench and the filling of a conductive material into the via hole. The isolation of the filling conductor from the silicon substrate becomes more important for higher frequencies due to the high coupling of the signal to the silicon. The importance of the oxide thickness on the via wall isolation can be verified using electromagnetic field simulators. To satisfy the needs on the Silicon dioxide deposition, a sub-atmospheric chemical vapor deposition (SA-CVD) process has been developed to deposit an isolation oxide to the walls of deep silicon trenches. The technique provides excellent step coverage of the 100 microm depth silicon trenches with the high aspect ratio of 20 and more. The developed technique allows covering the deep silicon trenches by oxide and makes the high isolation of TSVs from silicon substrate feasible which is the key factor for the performance of TSVs for mm-wave 3D packaging.

Utilizing the Deep Space Gateway to Characterize DNA Damage Due to Space Radiation and Repair Mechanisms

NASA Astrophysics Data System (ADS)

Zea, L.; Niederwieser, T.; Anthony, J.; Stodieck, L.

2018-02-01

The radiation environment experienced in the Deep Space Gateway enables the interrogation of DNA damage and repair mechanisms, which may serve to determine the likelihood and consequence of the high radiation risk to prolonged human presence beyond LEO.

High-Resolution Measurements of Coastal Bioluminescence

DTIC Science & Technology

2006-09-30

cover) Dunn, C.W., P.R. Pugh, and S.H.D. Haddock (2005) Marrus claudanielis, a new species of deep- sea physonect siphonophore (Siphonophora...in a deep-sea siphonophore . Science. 309:263 Haddock, S.H.D., C.W. Dunn, P.R. Pugh. (2005) A reexamination of siphonophore terminology and

A Model of Economics Learning in the High Schools.

ERIC Educational Resources Information Center

Walstad, William B.; Soper, John C.

1982-01-01

Evaluates the effectiveness of the Developmental Economic Education Project (DEEP) of the Joint Council of Economic Education and the awards program of the International Paper Company Foundation (IPCF). DEEP schools had a positive effect on students. The results of the IPCF program are less encouraging. (RM)

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

PubMed

Katzman, Jared L; Shaham, Uri; Cloninger, Alexander; Bates, Jonathan; Jiang, Tingting; Kluger, Yuval

2018-02-26

Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems. We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations. We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients. The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.

Liquid Water Oceans in Ice Giants

NASA Technical Reports Server (NTRS)

Wiktorowicz, Sloane J.; Ingersoll, Andrew P.

2007-01-01

Aptly named, ice giants such as Uranus and Neptune contain significant amounts of water. While this water cannot be present near the cloud tops, it must be abundant in the deep interior. We investigate the likelihood of a liquid water ocean existing in the hydrogen-rich region between the cloud tops and deep interior. Starting from an assumed temperature at a given upper tropospheric pressure (the photosphere), we follow a moist adiabat downward. The mixing ratio of water to hydrogen in the gas phase is small in the photosphere and increases with depth. The mixing ratio in the condensed phase is near unity in the photosphere and decreases with depth; this gives two possible outcomes. If at some pressure level the mixing ratio of water in the gas phase is equal to that in the deep interior, then that level is the cloud base. The gas below the cloud base has constant mixing ratio. Alternately, if the mixing ratio of water in the condensed phase reaches that in the deep interior, then the surface of a liquid ocean will occur. Below this ocean surface, the mixing ratio of water will be constant. A cloud base occurs when the photospheric temperature is high. For a family of ice giants with different photospheric temperatures, the cooler ice giants will have warmer cloud bases. For an ice giant with a cool enough photospheric temperature, the cloud base will exist at the critical temperature. For still cooler ice giants, ocean surfaces will result. A high mixing ratio of water in the deep interior favors a liquid ocean. We find that Neptune is both too warm (photospheric temperature too high) and too dry (mixing ratio of water in the deep interior too low) for liquid oceans to exist at present. To have a liquid ocean, Neptune s deep interior water to gas ratio would have to be higher than current models allow, and the density at 19 kbar would have to be approx. equal to 0.8 g/cu cm. Such a high density is inconsistent with gravitational data obtained during the Voyager flyby. In our model, Neptune s water cloud base occurs around 660 K and 11 kbar, and the density there is consistent with Voyager gravitational data. As Neptune cools, the probability of a liquid ocean increases. Extrasolar "hot Neptunes," which presumably migrate inward toward their parent stars, cannot harbor liquid water oceans unless they have lost almost all of the hydrogen and helium from their deep interiors.

Cyclometalated Iridium(III) Carbene Phosphors for Highly Efficient Blue Organic Light-Emitting Diodes.

PubMed

Chen, Zhao; Wang, Liqi; Su, Sikai; Zheng, Xingyu; Zhu, Nianyong; Ho, Cheuk-Lam; Chen, Shuming; Wong, Wai-Yeung

2017-11-22

Five deep blue carbene-based iridium(III) phosphors were synthesized and characterized. Interestingly, one of them can be fabricated into deep blue, sky blue and white organic light-emitting diodes (OLEDs) through changing the host materials and exciton blocking layers. These deep and sky blue devices exhibit Commission Internationale de l'Éclairage (CIE) coordinates of (0.145, 0.186) and (0.152, 0.277) with external quantum efficiency (EQE) of 15.2% and 9.6%, respectively. The EQE of the deep blue device can be further improved up to 19.0% by choosing a host with suitable energy level of its lowest unoccupied molecular orbital (LUMO).

[Trismus, pseudobulbar syndrome and cerebral deep venous thrombosis].

PubMed

Alecu, C; De Bray, J M; Penisson-Besnier, I; Pasco-Papon, A; Dubas, F

2001-03-01

We report a case of cerebral deep venous thrombosis that manifested clinically by a pseudobulbar syndrome with major trismus, abnormal movements and static cerebellar syndrome. To our knowledge, only three other cases of deep cerebral venous thrombosis associated with cerebellar or pseudobulbar syndrome have been published since 1985. The relatively good prognosis in our patient could be explained by the partially intact internal cerebral veins as well as use of early anticoagulant therapy. There was a spontaneous hyperdensity of the falx cerebri and the tentorium cerebelli on the brain CT scan, an aspect highly contributive to diagnosis. This hyperdensity of the falx cerebri was found in 19 out of 22 cases of deep venous thrombosis detailed in the literature.

Taxonomic revision of deep-sea Ostracoda from the Arctic Ocean

USGS Publications Warehouse

Yasuhara, Moriaki; Stepanova, Anna; Okahashi, Hisayo; Cronin, Thomas M.; Brouwers, Elisabeth M.

2015-01-01

Taxonomic revision of deep-sea Ostracoda from the Arctic Ocean was conducted to reduce taxonomic uncertainty that will improve our understanding of species ecology, biogeography and relationship to faunas from other deep-sea regions. Fifteen genera and 40 species were examined and (re-)illustrated with high-resolution scanning electron microscopy images, covering most of known deep-sea species in the central Arctic Ocean. Seven new species are described: Bythoceratina lomonosovensis n. sp., Cytheropteron parahamatum n. sp., Cytheropteron lanceae n. sp.,Cytheropteron irizukii n. sp., Pedicythere arctica n. sp., Cluthiawhatleyi n. sp., Krithe hunti n. sp. This study provides a robust taxonomic baseline for application to paleoceanographical reconstruction and biodiversity analyses in this climatically sensitive region.

Incidence of deep vein thrombosis in patients undergoing breast reconstruction with autologous tissue transfer.

PubMed

Konoeda, Hisato; Yamaki, Takashi; Hamahata, Atsumori; Ochi, Masakazu; Osada, Atsuyoshi; Hasegawa, Yuki; Kirita, Miho; Sakurai, Hiroyuki

2017-05-01

Background Breast reconstruction is associated with multiple risk factors for venous thromboembolism. However, the incidence of deep vein thrombosis in patients undergoing breast reconstruction is uncertain. Objective The aim of this study was to prospectively evaluate the incidence of deep vein thrombosis in patients undergoing breast reconstruction using autologous tissue transfer and to identify potential risk factors for deep vein thrombosis. Methods Thirty-five patients undergoing breast reconstruction were enrolled. We measured patients' preoperative characteristics including age, body mass index (kg/m 2 ), and risk factors for deep vein thrombosis. The preoperative diameter of each venous segment in the deep veins was measured using duplex ultrasound. All patients received intermittent pneumatic pump and elastic compression stockings for postoperative thromboprophylaxis. Results Among the 35 patients evaluated, 11 (31.4%) were found to have deep vein thrombosis postoperatively, and one patient was found to have pulmonary embolism postoperatively. All instances of deep vein thrombosis developed in the calf and were asymptomatic. Ten of 11 patients underwent free flap transfer, and the remaining one patient received a latissimus dorsi pedicled flap. Deep vein thrombosis incidence did not significantly differ between patients with a free flap or pedicled flap (P = 0.13). Documented risk factors for deep vein thrombosis demonstrated no significant differences between patients with and without deep vein thrombosis. The diameter of the common femoral vein was significantly larger in patients who developed postoperative deep vein thrombosis than in those who did not ( P < 0.05). Conclusions The morbidity of deep vein thrombosis in patients who underwent breast reconstruction using autologous tissue transfer was relatively high. Since only the diameter of the common femoral vein was predictive of developing postoperative deep vein thrombosis, postoperative pharmacological thromboprophylaxis should be considered for all patients undergoing breast reconstruction regardless of operative procedure.

Deep water characteristics and circulation in the South China Sea

NASA Astrophysics Data System (ADS)

Wang, Aimei; Du, Yan; Peng, Shiqiu; Liu, Kexiu; Huang, Rui Xin

2018-04-01

This study investigates the deep circulation in the South China Sea (SCS) using oceanographic observations combined with results from a bottom layer reduced gravity model. The SCS water, 2000 m below the surface, is quite different from that in the adjacent Pacific Ocean, and it is characterized by its low dissolved oxygen (DO), high temperature and low salinity. The horizontal distribution of deep water properties indicates a basin-scale cyclonic circulation driven by the Luzon overflow. The results of the bottom layer reduced gravity model are consistent with the existence of the cyclonic circulation in the deep SCS. The circulation is stronger at the northern/western boundary. After overflowing the sill of the Luzon Strait, the deep water moves broadly southwestward, constrained by the 3500 m isobath. The broadening of the southward flow is induced by the downwelling velocity in the interior of the deep basin. The main deep circulation bifurcates into two branches after the Zhongsha Islands. The southward branch continues flowing along the 3500 m isobath, and the eastward branch forms the sub-basin scale cyclonic circulation around the seamounts in the central deep SCS. The returning flow along the east boundary is fairly weak. The numerical experiments of the bottom layer reduced gravity model reveal the important roles of topography, bottom friction, and the upwelling/downwelling pattern in controlling the spatial structure, particularly the strong, deep western boundary current.

High intraspecific variability in the diet of a deep-sea nematode: Stable isotope and fatty acid analyses of Deontostoma tridentum on Chatham Rise, Southwest Pacific

NASA Astrophysics Data System (ADS)

Leduc, Daniel; Brown, Julie C. S.; Bury, Sarah J.; Lörz, Anne-Nina

2015-03-01

Small deep-sea organisms may exhibit a high degree of intraspecific variability in diet due to their ability to exploit a wide range of food sources and patchiness in food availability. Trophic interactions of small deep-sea benthic organisms, however, remain poorly understood. Here we describe spatial variation in diet/trophic level of the common deep-sea nematode Deontostoma tridentum on Chatham Rise, Southwest Pacific, using carbon and nitrogen stable isotope and fatty acid analyses. We also analysed sediment organic matter (SOM) and compared the isotopic composition of D. tridentum to other benthic and suprabenthic macrofaunal taxa with a variety of feeding modes. Variability in D. tridentum δ13C and δ15N signatures was high both among sites and within a single site on the southern flank of Chatham Rise. Among-site variation in SOM δ13C signatures was not sufficient to explain variation in nematode isotopic signatures. The presence of a positive correlation between δ13C and δ15N signatures of D. tridentum (both among and within sites) could suggest that differences in trophic level is the cause behind this variation. Nitrogen isotope data suggest the presence of 1-3 trophic levels in this species, which may reflect differences in prey availability, nematode body size, or habitat (benthic versus epizoic). Nematode δ15N values exceeded those of all other taxa we investigated, including other predators, but reasons for this enrichment remain unclear. The fatty acid composition of D. tridentum did not vary substantially between sites and was characterised by relatively high levels of 18:1n9 (15-20%) and polyunsaturated fatty acids (PUFAs; 22%). Although limited inferences can be made based on fatty acid composition due to the potential impacts of non-dietary factors, high levels of PUFAs indicate that D. tridentum represents a good source of these essential nutrients to higher trophic levels. In conclusion, our results show that (1) some deep-sea organisms exhibit a high degree of intraspecific variability in diet, and (2) nematodes may be an important source of PUFAs for larger animals in deep-sea environments, where the quality of SOM is low.

Origin of reduced efficiency in high Ga concentration Cu(In,Ga)Se2 solar cell

NASA Astrophysics Data System (ADS)

Wei, S.-H.; Huang, B.; Deng, H.; Contreras, M. A.; Noufi, R.; Chen, S.; Wang, L. W.

2014-03-01

CuInSe2 (CIS) is one of the most attractive thin-film materials for solar cells. It is well know that alloying Ga into CIS forming Cu(In,Ga)Se2 (CIGS) alloy is crucial to achieve the high efficiency, but adding too much Ga will lead to a decline of the solar cell efficiency. The exact origin of this puzzling phenomenon is currently still under debate. Using first-principles method, we have systemically studied the structural and electronic properties of CIGS alloys. Our phase diagram calculations suggest that increasing growth temperature may not be a critical factor in enhancing the cell performance of CIGS under equilibrium growth condition. On the other hand, our defect calculations identify that high concentration of antisite defects MCu(M =In, Ga) rather than anion defects are the key deep-trap centers in CIGS. The more the Ga concentration in CIGS, the more harmful the deep-trap is. Self-compensation in CIGS, which forms 2VCu + MCudefect complexes, is found to be beneficial to quench the deep-trap levels induced by MCu in CIGS, especially at low Ga concentration. Unfortunately, the density of isolated MCu is quite high and cannot be largely converted into 2VCu + MCu complexes under thermal equilibrium condition. Thus, nonequilibrium growth conditions or low growth temperature that can suppress the formation of the deep-trap centers MCu may be necessary for improving the efficiency of CIGS solar cells with high Ga concentrations.

Proteogenomic analysis reveals alternative splicing and translation as part of the abscisic acid response in Arabidopsis seedlings.

PubMed

Zhu, Fu-Yuan; Chen, Mo-Xian; Ye, Neng-Hui; Shi, Lu; Ma, Kai-Long; Yang, Jing-Fang; Cao, Yun-Ying; Zhang, Youjun; Yoshida, Takuya; Fernie, Alisdair R; Fan, Guang-Yi; Wen, Bo; Zhou, Ruo; Liu, Tie-Yuan; Fan, Tao; Gao, Bei; Zhang, Di; Hao, Ge-Fei; Xiao, Shi; Liu, Ying-Gao; Zhang, Jianhua

2017-08-01

In eukaryotes, mechanisms such as alternative splicing (AS) and alternative translation initiation (ATI) contribute to organismal protein diversity. Specifically, splicing factors play crucial roles in responses to environment and development cues; however, the underlying mechanisms are not well investigated in plants. Here, we report the parallel employment of short-read RNA sequencing, single molecule long-read sequencing and proteomic identification to unravel AS isoforms and previously unannotated proteins in response to abscisic acid (ABA) treatment. Combining the data from the two sequencing methods, approximately 83.4% of intron-containing genes were alternatively spliced. Two AS types, which are referred to as alternative first exon (AFE) and alternative last exon (ALE), were more abundant than intron retention (IR); however, by contrast to AS events detected under normal conditions, differentially expressed AS isoforms were more likely to be translated. ABA extensively affects the AS pattern, indicated by the increasing number of non-conventional splicing sites. This work also identified thousands of unannotated peptides and proteins by ATI based on mass spectrometry and a virtual peptide library deduced from both strands of coding regions within the Arabidopsis genome. The results enhance our understanding of AS and alternative translation mechanisms under normal conditions, and in response to ABA treatment. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wrighton, Kelly C.; Castelle, Cindy; Wilkins, Michael J.

Fermentation-based metabolism is an important ecosystem function often associated with environments rich in organic carbon, such as wetlands, sewage sludge, and the mammalian gut. The diversity of microorganisms and pathways involved in carbon and hydrogen cycling in sediments and aquifers and the impacts of these processes on other biogeochemical cycles remain poorly understood. Here we used metagenomics and proteomics to characterize microbial communities sampled from an aquifer adjacent to the Colorado River at Rifle, Colorado, USA, and document interlinked microbial roles in geochemical cycling. The organic carbon content in the aquifer was elevated via two acetate-based biostimulation treatments. Samples weremore » collected at three time points, with the objective of extensive genome recovery to enable metabolic reconstruction of the community. Fermentative community members include genomes from a new phylum (ACD20), phylogenetically novel members of the Chloroflexi and Bacteroidetes, as well as candidate phyla genomes (OD1, BD1-5, SR1, WWE3, ACD58, TM6, PER, and OP11). These organisms have the capacity to produce hydrogen, acetate, formate, ethanol, butyrate, and lactate, activities supported by proteomic data. The diversity and expression of hydrogenases suggests the importance of hydrogen currency in the subsurface. Our proteogenomic data further indicate the consumption of fermentation intermediates by Proteobacteria can be coupled to nitrate, sulfate, and iron reduction. Thus, fermentation carried out by previously unstudied members of sediment microbial communities may be an important driver of diverse subsurface biogeochemical cycles.« less

ActiveDriverDB: human disease mutations and genome variation in post-translational modification sites of proteins

PubMed Central

Krassowski, Michal; Paczkowska, Marta; Cullion, Kim; Huang, Tina; Dzneladze, Irakli; Ouellette, B F Francis; Yamada, Joseph T; Fradet-Turcotte, Amelie

2018-01-01

Abstract Interpretation of genetic variation is needed for deciphering genotype-phenotype associations, mechanisms of inherited disease, and cancer driver mutations. Millions of single nucleotide variants (SNVs) in human genomes are known and thousands are associated with disease. An estimated 21% of disease-associated amino acid substitutions corresponding to missense SNVs are located in protein sites of post-translational modifications (PTMs), chemical modifications of amino acids that extend protein function. ActiveDriverDB is a comprehensive human proteo-genomics database that annotates disease mutations and population variants through the lens of PTMs. We integrated >385,000 published PTM sites with ∼3.6 million substitutions from The Cancer Genome Atlas (TCGA), the ClinVar database of disease genes, and human genome sequencing projects. The database includes site-specific interaction networks of proteins, upstream enzymes such as kinases, and drugs targeting these enzymes. We also predicted network-rewiring impact of mutations by analyzing gains and losses of kinase-bound sequence motifs. ActiveDriverDB provides detailed visualization, filtering, browsing and searching options for studying PTM-associated mutations. Users can upload mutation datasets interactively and use our application programming interface in pipelines. Integrative analysis of mutations and PTMs may help decipher molecular mechanisms of phenotypes and disease, as exemplified by case studies of TP53, BRCA2 and VHL. The open-source database is available at https://www.ActiveDriverDB.org. PMID:29126202

ACTG: novel peptide mapping onto gene models.

PubMed

Choi, Seunghyuk; Kim, Hyunwoo; Paek, Eunok

2017-04-15

In many proteogenomic applications, mapping peptide sequences onto genome sequences can be very useful, because it allows us to understand origins of the gene products. Existing software tools either take the genomic position of a peptide start site as an input or assume that the peptide sequence exactly matches the coding sequence of a given gene model. In case of novel peptides resulting from genomic variations, especially structural variations such as alternative splicing, these existing tools cannot be directly applied unless users supply information about the variant, either its genomic position or its transcription model. Mapping potentially novel peptides to genome sequences, while allowing certain genomic variations, requires introducing novel gene models when aligning peptide sequences to gene structures. We have developed a new tool called ACTG (Amino aCids To Genome), which maps peptides to genome, assuming all possible single exon skipping, junction variation allowing three edit distances from the original splice sites, exon extension and frame shift. In addition, it can also consider SNVs (single nucleotide variations) during mapping phase if a user provides the VCF (variant call format) file as an input. Available at http://prix.hanyang.ac.kr/ACTG/search.jsp . eunokpaek@hanyang.ac.kr. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warshan, Denis; Espinoza, Josh L.; Stuart, Rhona K.

Dinitrogen (N 2)-fixation by cyanobacteria in symbiosis with feathermosses is the primary pathway of biological nitrogen (N) input into boreal forests. Despite its significance, little is known about the cyanobacterial gene repertoire and regulatory rewiring needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions and regulatory changes allowing cyanobacteria to form and maintain this symbiosis, we compared genomically closely related symbiotic-competent and -incompetent Nostoc strains using a proteogenomics approach and an experimental set up allowing for controlled chemical and physical contact between partners. Thirty-two gene families were found only in the genomes of symbiotic strains, includingmore » some never before associated with cyanobacterial symbiosis. We identified conserved orthologs that were differentially expressed in symbiotic strains, including protein families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, and glycosyl-modifying and oxidative stress-mediating exoenzymes. The physical moss–cyanobacteria epiphytic symbiosis is distinct from other cyanobacteria–plant symbioses, with Nostoc retaining motility, and lacking modulation of N 2-fixation, photosynthesis, GS-GOGAT cycle and heterocyst formation. The results expand our knowledge base of plant–cyanobacterial symbioses, provide a model of information and material exchange in this ecologically significant symbiosis, and suggest new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining the cyanobacteria–feathermoss symbiosis.« less

Development of a biomarker for Geobacter activity and strain composition: Proteogenomic analysis of the citrate synthase protein during bioremediation of U(VI)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilkins, M.J.; Callister, S.J.; Miletto, M.

2010-02-15

Monitoring the activity of target microorganisms during stimulated bioremediation is a key problem for the development of effective remediation strategies. At the US Department of Energy's Integrated Field Research Challenge (IFRC) site in Rifle, CO, the stimulation of Geobacter growth and activity via subsurface acetate addition leads to precipitation of U(VI) from groundwater as U(IV). Citrate synthase (gltA) is a key enzyme in Geobacter central metabolism that controls flux into the TCA cycle. Here, we utilize shotgun proteomic methods to demonstrate that the measurement of gltA peptides can be used to track Geobacter activity and strain evolution during in situmore » biostimulation. Abundances of conserved gltA peptides tracked Fe(III) reduction and changes in U(VI) concentrations during biostimulation, whereas changing patterns of unique peptide abundances between samples suggested sample-specific strain shifts within the Geobacter population. Abundances of unique peptides indicated potential differences at the strain level between Fe(III)-reducing populations stimulated during in situ biostimulation experiments conducted a year apart at the Rifle IFRC. These results offer a novel technique for the rapid screening of large numbers of proteomic samples for Geobacter species and will aid monitoring of subsurface bioremediation efforts that rely on metal reduction for desired outcomes.« less

Development of a biomarker for Geobacter activity and strain composition; Proteogenomic analysis of the citrate synthase protein during bioremediation of U(VI).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilkins, Michael J.; Callister, Stephen J.; Miletto, Marzia

2011-01-01

Monitoring the activity of target microorganisms during stimulated bioremediation is a key problem for the development of effective remediation strategies. At the U.S. Department of Energy’s Integrated Field Research Challenge (IFRC) site in Rifle, CO, the stimulation of Geobacter growth and activity via subsurface acetate addition leads to precipitation of U(VI) from groundwater as U(IV). Citrate synthase (gltA) is a key enzyme in Geobacter central metabolism that controls flux into the TCA cycle. Here, we utilize shotgun proteomic methods to demonstrate that the measurement of gltA peptides can be used to track Geobacter activity and strain evolution during in situmore » biostimulation. Abundances of conserved gltA peptides tracked Fe(III) reduction and changes in U(VI) concentrations during biostimulation, whereas changing patterns of unique peptide abundances between samples suggested sample-specific strain shifts within the Geobacter population. Abundances of unique peptides indicated potential differences at the strain level between Fe(III)-reducing populations stimulated during in situ biostimulation experiments conducted a year apart at the Rifle IFRC. These results offer a novel technique for the rapid screening of large numbers of proteomic samples for Geobacter species and will aid monitoring of subsurface bioremediation efforts that rely on metal reduction for desired outcomes.« less

Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing.

PubMed

Pang, Chi Nam Ignatius; Tay, Aidan P; Aya, Carlos; Twine, Natalie A; Harkness, Linda; Hart-Smith, Gene; Chia, Samantha Z; Chen, Zhiliang; Deshpande, Nandan P; Kaakoush, Nadeem O; Mitchell, Hazel M; Kassem, Moustapha; Wilkins, Marc R

2014-01-03

Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis

PubMed Central

Warshan, Denis; Espinoza, Josh L; Stuart, Rhona K; Richter, R Alexander; Kim, Sea-Yong; Shapiro, Nicole; Woyke, Tanja; C Kyrpides, Nikos; Barry, Kerrie; Singan, Vasanth; Lindquist, Erika; Ansong, Charles; Purvine, Samuel O; M Brewer, Heather; Weyman, Philip D; Dupont, Christopher L; Rasmussen, Ulla

2017-01-01

Dinitrogen (N2)-fixation by cyanobacteria in symbiosis with feathermosses is the primary pathway of biological nitrogen (N) input into boreal forests. Despite its significance, little is known about the cyanobacterial gene repertoire and regulatory rewiring needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions and regulatory changes allowing cyanobacteria to form and maintain this symbiosis, we compared genomically closely related symbiotic-competent and -incompetent Nostoc strains using a proteogenomics approach and an experimental set up allowing for controlled chemical and physical contact between partners. Thirty-two gene families were found only in the genomes of symbiotic strains, including some never before associated with cyanobacterial symbiosis. We identified conserved orthologs that were differentially expressed in symbiotic strains, including protein families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, and glycosyl-modifying and oxidative stress-mediating exoenzymes. The physical moss–cyanobacteria epiphytic symbiosis is distinct from other cyanobacteria–plant symbioses, with Nostoc retaining motility, and lacking modulation of N2-fixation, photosynthesis, GS-GOGAT cycle and heterocyst formation. The results expand our knowledge base of plant–cyanobacterial symbioses, provide a model of information and material exchange in this ecologically significant symbiosis, and suggest new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining the cyanobacteria–feathermoss symbiosis. PMID:28800136

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis

DOE PAGES

Warshan, Denis; Espinoza, Josh L.; Stuart, Rhona K.; ...

2017-08-11

Dinitrogen (N 2)-fixation by cyanobacteria in symbiosis with feathermosses is the primary pathway of biological nitrogen (N) input into boreal forests. Despite its significance, little is known about the cyanobacterial gene repertoire and regulatory rewiring needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions and regulatory changes allowing cyanobacteria to form and maintain this symbiosis, we compared genomically closely related symbiotic-competent and -incompetent Nostoc strains using a proteogenomics approach and an experimental set up allowing for controlled chemical and physical contact between partners. Thirty-two gene families were found only in the genomes of symbiotic strains, includingmore » some never before associated with cyanobacterial symbiosis. We identified conserved orthologs that were differentially expressed in symbiotic strains, including protein families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, and glycosyl-modifying and oxidative stress-mediating exoenzymes. The physical moss–cyanobacteria epiphytic symbiosis is distinct from other cyanobacteria–plant symbioses, with Nostoc retaining motility, and lacking modulation of N 2-fixation, photosynthesis, GS-GOGAT cycle and heterocyst formation. The results expand our knowledge base of plant–cyanobacterial symbioses, provide a model of information and material exchange in this ecologically significant symbiosis, and suggest new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining the cyanobacteria–feathermoss symbiosis.« less

GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes.

PubMed

Zhang, Jia; Yang, Ming-Kun; Zeng, Honghui; Ge, Feng

2016-11-01

Although the number of sequenced prokaryotic genomes is growing rapidly, experimentally verified annotation of prokaryotic genome remains patchy and challenging. To facilitate genome annotation efforts for prokaryotes, we developed an open source software called GAPP for genome annotation and global profiling of post-translational modifications (PTMs) in prokaryotes. With a single command, it provides a standard workflow to validate and refine predicted genetic models and discover diverse PTM events. We demonstrated the utility of GAPP using proteomic data from Helicobacter pylori, one of the major human pathogens that is responsible for many gastric diseases. Our results confirmed 84.9% of the existing predicted H. pylori proteins, identified 20 novel protein coding genes, and corrected four existing gene models with regard to translation initiation sites. In particular, GAPP revealed a large repertoire of PTMs using the same proteomic data and provided a rich resource that can be used to examine the functions of reversible modifications in this human pathogen. This software is a powerful tool for genome annotation and global discovery of PTMs and is applicable to any sequenced prokaryotic organism; we expect that it will become an integral part of ongoing genome annotation efforts for prokaryotes. GAPP is freely available at https://sourceforge.net/projects/gappproteogenomic/. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Functional correlates of the therapeutic and adverse effects evoked by thalamic stimulation for essential tremor

PubMed Central

Gibson, William S.; Jo, Hang Joon; Testini, Paola; Cho, Shinho; Felmlee, Joel P.; Welker, Kirk M.; Klassen, Bryan T.; Min, Hoon-Ki

2016-01-01

Deep brain stimulation is an established neurosurgical therapy for movement disorders including essential tremor and Parkinson’s disease. While typically highly effective, deep brain stimulation can sometimes yield suboptimal therapeutic benefit and can cause adverse effects. In this study, we tested the hypothesis that intraoperative functional magnetic resonance imaging could be used to detect deep brain stimulation-evoked changes in functional and effective connectivity that would correlate with the therapeutic and adverse effects of stimulation. Ten patients receiving deep brain stimulation of the ventralis intermedius thalamic nucleus for essential tremor underwent functional magnetic resonance imaging during stimulation applied at a series of stimulation localizations, followed by evaluation of deep brain stimulation-evoked therapeutic and adverse effects. Correlations between the therapeutic effectiveness of deep brain stimulation (3 months postoperatively) and deep brain stimulation-evoked changes in functional and effective connectivity were assessed using region of interest-based correlation analysis and dynamic causal modelling, respectively. Further, we investigated whether brain regions might exist in which activation resulting from deep brain stimulation might correlate with the presence of paraesthesias, the most common deep brain stimulation-evoked adverse effect. Thalamic deep brain stimulation resulted in activation within established nodes of the tremor circuit: sensorimotor cortex, thalamus, contralateral cerebellar cortex and deep cerebellar nuclei (FDR q < 0.05). Stimulation-evoked activation in all these regions of interest, as well as activation within the supplementary motor area, brainstem, and inferior frontal gyrus, exhibited significant correlations with the long-term therapeutic effectiveness of deep brain stimulation (P < 0.05), with the strongest correlation (P < 0.001) observed within the contralateral cerebellum. Dynamic causal modelling revealed a correlation between therapeutic effectiveness and attenuated within-region inhibitory connectivity in cerebellum. Finally, specific subregions of sensorimotor cortex were identified in which deep brain stimulation-evoked activation correlated with the presence of unwanted paraesthesias. These results suggest that thalamic deep brain stimulation in tremor likely exerts its effects through modulation of both olivocerebellar and thalamocortical circuits. In addition, our findings indicate that deep brain stimulation-evoked functional activation maps obtained intraoperatively may contain predictive information pertaining to the therapeutic and adverse effects induced by deep brain stimulation. PMID:27329768

Break-up of the Atlantic deep western boundary current into eddies at 8 degrees S.

PubMed

Dengler, M; Schott, F A; Eden, C; Brandt, P; Fischer, J; Zantopp, R J

2004-12-23

The existence in the ocean of deep western boundary currents, which connect the high-latitude regions where deep water is formed with upwelling regions as part of the global ocean circulation, was postulated more than 40 years ago. These ocean currents have been found adjacent to the continental slopes of all ocean basins, and have core depths between 1,500 and 4,000 m. In the Atlantic Ocean, the deep western boundary current is estimated to carry (10-40) x 10(6) m3 s(-1) of water, transporting North Atlantic Deep Water--from the overflow regions between Greenland and Scotland and from the Labrador Sea--into the South Atlantic and the Antarctic circumpolar current. Here we present direct velocity and water mass observations obtained in the period 2000 to 2003, as well as results from a numerical ocean circulation model, showing that the Atlantic deep western boundary current breaks up at 8 degrees S. Southward of this latitude, the transport of North Atlantic Deep Water into the South Atlantic Ocean is accomplished by migrating eddies, rather than by a continuous flow. Our model simulation indicates that the deep western boundary current breaks up into eddies at the present intensity of meridional overturning circulation. For weaker overturning, continuation as a stable, laminar boundary flow seems possible.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

PubMed

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling

PubMed Central

Wang, Sheng; Sun, Siqi

2017-01-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC. PMID:28884168

Integrated Metagenomic and Metatranscriptomic Analyses of Microbial Communities in the Meso- and Bathypelagic Realm of North Pacific Ocean

PubMed Central

Wu, Jieying; Gao, Weimin; Johnson, Roger H.; Zhang, Weiwen; Meldrum, Deirdre R.

2013-01-01

Although emerging evidence indicates that deep-sea water contains an untapped reservoir of high metabolic and genetic diversity, this realm has not been studied well compared with surface sea water. The study provided the first integrated meta-genomic and -transcriptomic analysis of the microbial communities in deep-sea water of North Pacific Ocean. DNA/RNA amplifications and simultaneous metagenomic and metatranscriptomic analyses were employed to discover information concerning deep-sea microbial communities from four different deep-sea sites ranging from the mesopelagic to pelagic ocean. Within the prokaryotic community, bacteria is absolutely dominant (~90%) over archaea in both metagenomic and metatranscriptomic data pools. The emergence of archaeal phyla Crenarchaeota, Euryarchaeota, Thaumarchaeota, bacterial phyla Actinobacteria, Firmicutes, sub-phyla Betaproteobacteria, Deltaproteobacteria, and Gammaproteobacteria, and the decrease of bacterial phyla Bacteroidetes and Alphaproteobacteria are the main composition changes of prokaryotic communities in the deep-sea water, when compared with the reference Global Ocean Sampling Expedition (GOS) surface water. Photosynthetic Cyanobacteria exist in all four metagenomic libraries and two metatranscriptomic libraries. In Eukaryota community, decreased abundance of fungi and algae in deep sea was observed. RNA/DNA ratio was employed as an index to show metabolic activity strength of microbes in deep sea. Functional analysis indicated that deep-sea microbes are leading a defensive lifestyle. PMID:24152557

Challenging Oil Bioremediation at Deep-Sea Hydrostatic Pressure

PubMed Central

Scoma, Alberto; Yakimov, Michail M.; Boon, Nico

2016-01-01

The Deepwater Horizon accident has brought oil contamination of deep-sea environments to worldwide attention. The risk for new deep-sea spills is not expected to decrease in the future, as political pressure mounts to access deep-water fossil reserves, and poorly tested technologies are used to access oil. This also applies to the response to oil-contamination events, with bioremediation the only (bio)technology presently available to combat deep-sea spills. Many questions about the fate of petroleum-hydrocarbons within deep-sea environments remain unanswered, as well as the main constraints limiting bioremediation under increased hydrostatic pressures and low temperatures. The microbial pathways fueling oil bioassimilation are unclear, and the mild upregulation observed for beta-oxidation-related genes in both water and sediments contrasts with the high amount of alkanes present in the spilled oil. The fate of solid alkanes (tar), hydrocarbon degradation rates and the reason why the most predominant hydrocarbonoclastic genera were not enriched at deep-sea despite being present at hydrocarbon seeps at the Gulf of Mexico have been largely overlooked. This mini-review aims at highlighting the missing information in the field, proposing a holistic approach where in situ and ex situ studies are integrated to reveal the principal mechanisms accounting for deep-sea oil bioremediation. PMID:27536290

AlGaN UV LED and Photodiodes Radiation Hardness and Space Qualifications and Their Applications in Space Science and High Energy Density Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, K. X.

2011-05-31

This presentation provides an overview of robust, radiation hard AlGaN optoelectronic devices and their applications in space exploration & high energy density physics. Particularly, deep UV LED and deep UV photodiodes are discussed with regard to their applications, radiation hardness and space qualification. AC charge management of UV LED satellite payload instruments, which were to be launched in late 2012, is covered.

Is the genetic landscape of the deep subsurface biosphere affected by viruses?

PubMed

Anderson, Rika E; Brazelton, William J; Baross, John A

2011-01-01

Viruses are powerful manipulators of microbial diversity, biogeochemistry, and evolution in the marine environment. Viruses can directly influence the genetic capabilities and the fitness of their hosts through the use of fitness factors and through horizontal gene transfer. However, the impact of viruses on microbial ecology and evolution is often overlooked in studies of the deep subsurface biosphere. Subsurface habitats connected to hydrothermal vent systems are characterized by constant fluid flux, dynamic environmental variability, and high microbial diversity. In such conditions, high adaptability would be an evolutionary asset, and the potential for frequent host-virus interactions would be high, increasing the likelihood that cellular hosts could acquire novel functions. Here, we review evidence supporting this hypothesis, including data indicating that microbial communities in subsurface hydrothermal fluids are exposed to a high rate of viral infection, as well as viral metagenomic data suggesting that the vent viral assemblage is particularly enriched in genes that facilitate horizontal gene transfer and host adaptability. Therefore, viruses are likely to play a crucial role in facilitating adaptability to the extreme conditions of these regions of the deep subsurface biosphere. We also discuss how these results might apply to other regions of the deep subsurface, where the nature of virus-host interactions would be altered, but possibly no less important, compared to more energetic hydrothermal systems.

Is the Genetic Landscape of the Deep Subsurface Biosphere Affected by Viruses?

PubMed Central

Anderson, Rika E.; Brazelton, William J.; Baross, John A.

2011-01-01

Viruses are powerful manipulators of microbial diversity, biogeochemistry, and evolution in the marine environment. Viruses can directly influence the genetic capabilities and the fitness of their hosts through the use of fitness factors and through horizontal gene transfer. However, the impact of viruses on microbial ecology and evolution is often overlooked in studies of the deep subsurface biosphere. Subsurface habitats connected to hydrothermal vent systems are characterized by constant fluid flux, dynamic environmental variability, and high microbial diversity. In such conditions, high adaptability would be an evolutionary asset, and the potential for frequent host–virus interactions would be high, increasing the likelihood that cellular hosts could acquire novel functions. Here, we review evidence supporting this hypothesis, including data indicating that microbial communities in subsurface hydrothermal fluids are exposed to a high rate of viral infection, as well as viral metagenomic data suggesting that the vent viral assemblage is particularly enriched in genes that facilitate horizontal gene transfer and host adaptability. Therefore, viruses are likely to play a crucial role in facilitating adaptability to the extreme conditions of these regions of the deep subsurface biosphere. We also discuss how these results might apply to other regions of the deep subsurface, where the nature of virus–host interactions would be altered, but possibly no less important, compared to more energetic hydrothermal systems. PMID:22084639

NCI Scientists Get Deep Look at CRISPR Complex Through Deep Freeze | Poster

Cancer.gov

To get a closer look at one CRISPR complex, researchers from NCI’s Center for Cancer Research and their collaborators recently put it “on ice” with cryo-electron microscopy, creating highly detailed images that show its biological structures in multiple states at a molecular level.

Exploration of Near-Earth Objects from the Deep Space Gateway

NASA Astrophysics Data System (ADS)

Dunham, D. W.; Stakkestad, K.; Vedder, P.; McAdams, J.; Horsewood, J.; Genova, A. L.

2018-02-01

The paper will show how clever use of orbital dynamics can lower delta-V costs to enable scientifically interesting missions. The high-energy Deep Space Gateway orbits can be used to reach NEOs, a trans node for crews, or to deploy small sats. Examples are given.

Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study.

PubMed

Ebert, Lars C; Heimer, Jakob; Schweitzer, Wolf; Sieberth, Till; Leipner, Anja; Thali, Michael; Ampanozi, Garyfalia

2017-12-01

Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be generated by modern medical scanners, especially in a forensic setting where the entire body is documented at high resolution. A solution for the resulting issues could be the use of deep learning techniques for automatic analysis of radiological images. In this article, we wanted to test the feasibility of such methods for forensic imaging by hypothesizing that deep learning methods can detect and segment a hemopericardium in PMCT. For deep learning image analysis software, we used the ViDi Suite 2.0. We retrospectively selected 28 cases with, and 24 cases without, hemopericardium. Based on these data, we trained two separate deep learning networks. The first one classified images into hemopericardium/not hemopericardium, and the second one segmented the blood content. We randomly selected 50% of the data for training and 50% for validation. This process was repeated 20 times. The best performing classification network classified all cases of hemopericardium from the validation images correctly with only a few false positives. The best performing segmentation network would tend to underestimate the amount of blood in the pericardium, which is the case for most networks. This is the first study that shows that deep learning has potential for automated image analysis of radiological images in forensic medicine.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales.

PubMed

Schiro, Kathleen A; Ahmed, Fiaz; Giangrande, Scott E; Neelin, J David

2018-05-01

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

Lytic viral infection of bacterioplankton in deep waters of the western Pacific Ocean

NASA Astrophysics Data System (ADS)

Li, Y.; Luo, T.; Sun, J.; Cai, L.; Liang, Y.; Jiao, N.; Zhang, R.

2014-05-01

As the most abundant biological entities in the ocean, viruses influence host mortality and nutrient recycling mainly through lytic infection. Yet, the ecological characteristics of virioplankton and viral impacts on host mortality and biogeochemical cycling in the deep sea are largely unknown. In the present study, viral abundance and lytic infection were investigated throughout the water column in the western Pacific Ocean. Both the prokaryotic and viral abundance and production showed a significantly decreasing trend from epipelagic to meso- and bathypelagic waters. Viral abundance decreased from 0.36-1.05 × 1010 particles L-1 to 0.43-0.80 × 109 particles L-1, while the virus : prokaryote ratio varied from 7.21 to 16.23 to 2.45-23.40, at the surface and 2000 m, respectively. Lytic viral production rates in surface and 2000 m waters were, on average, 1.03 × 1010 L-1 day-1 and 5.74 × 108 L-1 day-1. Relatively high percentages of prokaryotic cells lysed by viruses at 1000 and 2000 m were observed, suggesting a significant contribution of viruses to prokaryotic mortality in the deep ocean. The carbon released by viral lysis in deep western Pacific Ocean waters was from 0.03 to 2.32 μg C L-1 day-1. Our findings demonstrated a highly dynamic and active viral population in these deep waters and suggested that virioplankton play an important role in the microbial loop and subsequently biogeochemical cycling in deep oceans.

Lytic viral infection of bacterioplankton in deep waters of the western Pacific Ocean

NASA Astrophysics Data System (ADS)

Li, Y.; Luo, T.; Sun, J.; Cai, L.; Jiao, N.; Zhang, R.

2013-12-01

As the most abundant biological entities in the ocean, viruses can influence host mortality and nutrients recycling mainly through lytic infection. Yet ecological characteristics of virioplankton and viral impacts on host mortality and biogeochemical cycling in the deep sea are largely unknown. In present study, viral abundance and lytic infection was investigated throughout the water column in the western Pacific Ocean. Both the prokaryotic and viral abundance and production showed a significantly decreasing trend from epipelagic to meso- and bathypelagic waters. Viral abundance decreased from 0.36-1.05 × 1010 particles L-1 to 0.43-0.80 × 109 particles L-1, while the virus : prokaryote ratio varied from 7.21-16.23 to 2.45-23.40, at surface and 2000 m depth, respectively. The lytic viral production rates in surface and 2000 m waters were, averagely, 1.03 × 1010 L-1 day-1 and 5.74 × 108 L-1 day-1, respectively. Relatively high percentages of prokaryotic cells lysed by virus in 1000 m and 2000 m were observed, suggesting a significant contribution of viruses to prokaryotic mortality in deep ocean. The carbon released by viral lysis in deep western Pacific Ocean waters was from 0.03 to 2.32 μg C L-1 day-1. Our findings demonstrated a highly dynamic and active viral population in the deep western Pacific Ocean and suggested that virioplankton play an important role in the microbial loop and subsequently biogeochemical cycling in deep oceans.

Tracer constraints on organic particle transfer efficiency to the deep ocean

NASA Astrophysics Data System (ADS)

Weber, T. S.; Cram, J. A.; Deutsch, C. A.

2016-02-01

The "transfer efficiency" of sinking organic particles through the mesopelagic zone is a critical determinant of ocean carbon sequestration timescales, and the atmosphere-ocean partition of CO2. Our ability to detect large-scale variations in transfer efficiency is limited by the paucity of particle flux data from the deep ocean, and the potential biases of bottom-moored sediment traps used to collect it. Here we show that deep-ocean particle fluxes can be reconstructed by diagnosing the rate of phosphate accumulation and oxygen disappearance along deep circulation pathways in an observationally constrained Ocean General Circulation Model (OGCM). Combined with satellite and model estimates of carbon export from the surface ocean, these diagnosed fluxes reveal a global pattern of transfer efficiency to 1000m and 2000m that is high ( 20%) at high latitudes and negligible (<5%) throughout subtropical gyres, with intermediate values in the tropics. This pattern is at odds with previous estimates of deep transfer efficiency derived from bottom-moored sediment traps, but is consistent with upper-ocean flux profiles measured by neutrally buoyant sediment traps, which show strong attenuation of low latitude particle fluxes over the top 500m. Mechanistically, the pattern can be explained by spatial variations in particle size distributions, and the temperature-dependence of remineralization. We demonstrate the biogeochemical significance of our findings by comparing estimates of deep-ocean carbon sequestration in a scenario with spatially varying transfer efficiency to one with a globally uniform "Martin-curve" particle flux profile.

Projected pH reductions by 2100 might put deep North Atlantic biodiversity at risk

NASA Astrophysics Data System (ADS)

Gehlen, M.; Séférian, R.; Jones, D. O. B.; Roy, T.; Roth, R.; Barry, J.; Bopp, L.; Doney, S. C.; Dunne, J. P.; Heinze, C.; Joos, F.; Orr, J. C.; Resplandy, L.; Segschneider, J.; Tjiputra, J.

2014-06-01

This study aims at evaluating the potential for impacts of ocean acidification on North Atlantic deep-sea ecosystems in response to IPCC AR5 Representative Concentration Pathways (RCP). Deep-sea biota is likely highly vulnerable to changes in seawater chemistry and sensitive to moderate excursions in pH. Here we show, from seven fully-coupled Earth system models, that for three out of four RCPs over 17% of the seafloor area below 500 m depth in the North Atlantic sector will experience pH reductions exceeding -0.2 units by 2100. Increased stratification in response to climate change partially alleviates the impact of ocean acidification on deep benthic environment. We report major potential consequences of pH reductions for deep-sea biodiversity hotspots, such as seamounts and canyons. By 2100 and under the high CO2 scenario RCP8.5 pH reductions exceeding -0.2, (respectively -0.3) units are projected in close to 23% (~ 15%) of North Atlantic deep-sea canyons and ~ 8% (3%) of seamounts - including seamounts proposed as sites of marine protected areas. The spatial pattern of impacts reflects the depth of the pH perturbation and does not scale linearly with atmospheric CO2 concentration. Impacts may cause negative changes of the same magnitude or exceeding the current target of 10% of preservation of marine biomes set by the convention on biological diversity implying that ocean acidification may offset benefits from conservation/management strategies relying on the regulation of resource exploitation.

Reconstructing Deep Ocean Circulation in the North Atlantic from Bermuda Rise, and Beyond

NASA Astrophysics Data System (ADS)

McManus, J. F.

2016-12-01

The large-scale subsurface circulation of the ocean is an important component of the Earth's climate system, and contributes to the global and regional transport of heat and mass. Assessing how this system has changed in the past is thus a priority for understanding natural climate variability. A long-coring campaign on Bermuda Rise has provided additional abundant high-quality sediments from this site of rapid accumulation in the deep western basin, situated beneath the subtropical gyre of the North Atlantic Ocean. These sediments allow the high-resolution reconstruction of deepwater chemistry and export from this key location throughout the last 150,000 years, covering the entire last glacial cycle in a continuous section of 35 meters in core KNR191-CDH19. The suite of proxy indicators analyzed includes uranium-series disequilibria, neodymium isotopes, and benthic stable isotopes. Combined with multiple previous studies of nearby cores on Bermuda Rise, the published and new proxy data from CDH19 confirm the variability of the deep circulation in the Atlantic Ocean in association with past climate changes. The multiple indicators, along with complementary data from other locations, display coherent evidence for contrasts between deep circulation during glacial and interglacial intervals, with persistent strong, deep ventilation only within the peak interglacial of marine isotope stage 5e (MIS 5e) and the Holocene. In contrast, repeated, dramatic variability in deep ocean circulation accompanied the millennial climate changes of the last glaciation and deglaciation. The largest magnitude circulation shifts occurred at the transitions into stadials associated with the Hudson strait iceberg discharges and between them and the ensuing northern interstadial warmings, significantly exceeding that of the overall glacial-interglacial difference, highlighting the potential oceanographic and climatic importance of short-term perturbations to the deep ocean circulation.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Progress on applications of high temperature superconducting microwave filters

NASA Astrophysics Data System (ADS)

Chunguang, Li; Xu, Wang; Jia, Wang; Liang, Sun; Yusheng, He

2017-07-01

In the past two decades, various kinds of high performance high temperature superconducting (HTS) filters have been constructed and the HTS filters and their front-end subsystems have been successfully applied in many fields. The HTS filters with small insertion loss, narrow bandwidth, flat in-band group delay, deep out-of-band rejection, and steep skirt slope are reviewed. Novel HTS filter design technologies, including those in high power handling filters, multiband filters and frequency tunable filters, are reviewed, as well as the all-HTS integrated front-end receivers. The successful applications to various civilian fields, such as mobile communication, radar, deep space detection, and satellite technology, are also reviewed.

The role of Southern Ocean mixing and upwelling in glacial-interglacial atmospheric CO2 change

NASA Astrophysics Data System (ADS)

Watson, Andrew J.; Naveira Garabato, Alberto C.

2006-02-01

Decreased ventilation of the Southern Ocean in glacial time is implicated in most explanations of lower glacial atmospheric CO2. Today, the deep (>2000 m) ocean south of the Polar Front is rapidly ventilated from below, with the interaction of deep currents with topography driving high mixing rates well up into the water column. We show from a buoyancy budget that mixing rates are high in all the deep waters of the Southern Ocean. Between the surface and ~2000 m depth, water is upwelled by a residual meridional overturning that is directly linked to buoyancy fluxes through the ocean surface. Combined with the rapid deep mixing, this upwelling serves to return deep water to the surface on a short time scale. We propose two new mechanisms by which, in glacial time, the deep Southern Ocean may have been more isolated from the surface. Firstly, the deep ocean appears to have been more stratified because of denser bottom water resulting from intense sea ice formation near Antarctica. The greater stratification would have slowed the deep mixing. Secondly, subzero atmospheric temperatures may have meant that the present-day buoyancy flux from the atmosphere to the ocean surface was reduced or reversed. This in turn would have reduced or eliminated the upwelling (contrary to a common assumption, upwelling is not solely a function of the wind stress but is coupled to the air-sea buoyancy flux too). The observed very close link between Antarctic temperatures and atmospheric CO2 could then be explained as a natural consequence of the connection between the air-sea buoyancy flux and upwelling in the Southern Ocean, if slower ventilation of the Southern Ocean led to lower atmospheric CO2. Here we use a box model, similar to those of previous authors, to show that weaker mixing and reduced upwelling in the Southern Ocean can explain the low glacial atmospheric CO2 in such a formulation.

Deep Unsupervised Learning on a Desktop PC: A Primer for Cognitive Scientists.

PubMed

Testolin, Alberto; Stoianov, Ivilin; De Filippo De Grazia, Michele; Zorzi, Marco

2013-01-01

Deep belief networks hold great promise for the simulation of human cognition because they show how structured and abstract representations may emerge from probabilistic unsupervised learning. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. However, learning in deep networks typically requires big datasets and it can involve millions of connection weights, which implies that simulations on standard computers are unfeasible. Developing realistic, medium-to-large-scale learning models of cognition would therefore seem to require expertise in programing parallel-computing hardware, and this might explain why the use of this promising approach is still largely confined to the machine learning community. Here we show how simulations of deep unsupervised learning can be easily performed on a desktop PC by exploiting the processors of low cost graphic cards (graphic processor units) without any specific programing effort, thanks to the use of high-level programming routines (available in MATLAB or Python). We also show that even an entry-level graphic card can outperform a small high-performance computing cluster in terms of learning time and with no loss of learning quality. We therefore conclude that graphic card implementations pave the way for a widespread use of deep learning among cognitive scientists for modeling cognition and behavior.

Deep Unsupervised Learning on a Desktop PC: A Primer for Cognitive Scientists

PubMed Central

Testolin, Alberto; Stoianov, Ivilin; De Filippo De Grazia, Michele; Zorzi, Marco

2013-01-01

Deep belief networks hold great promise for the simulation of human cognition because they show how structured and abstract representations may emerge from probabilistic unsupervised learning. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. However, learning in deep networks typically requires big datasets and it can involve millions of connection weights, which implies that simulations on standard computers are unfeasible. Developing realistic, medium-to-large-scale learning models of cognition would therefore seem to require expertise in programing parallel-computing hardware, and this might explain why the use of this promising approach is still largely confined to the machine learning community. Here we show how simulations of deep unsupervised learning can be easily performed on a desktop PC by exploiting the processors of low cost graphic cards (graphic processor units) without any specific programing effort, thanks to the use of high-level programming routines (available in MATLAB or Python). We also show that even an entry-level graphic card can outperform a small high-performance computing cluster in terms of learning time and with no loss of learning quality. We therefore conclude that graphic card implementations pave the way for a widespread use of deep learning among cognitive scientists for modeling cognition and behavior. PMID:23653617

The Secret to Successful Deep-Sea Invasion: Does Low Temperature Hold the Key?

PubMed Central

Smith, Kathryn E.; Thatje, Sven

2012-01-01

There is a general consensus that today’s deep-sea biodiversity has largely resulted from recurrent invasions and speciations occurring through homogenous waters during periods of the Phanerozoic eon. Migrations likely continue today, primarily via isothermal water columns, such as those typical of Polar Regions, but the necessary ecological and physiological adaptations behind them are poorly understood. In an evolutionary context, understanding the adaptations, which allow for colonisation to high-pressure environments, may enable us to predict future events. In this investigation, we examine pressure tolerance during development, in the shallow-water neogastropod Buccinum undatum using thermally acclimated egg masses from temperate and sub-polar regions across the species range. Fossil records indicate neogastropods to have a deep-water origin, suggesting shallow-water species may be likely candidates for re-emergence into the deep sea. Our results show population level differences in physiological thresholds, which indicate low temperature acclimation to increase pressure tolerance. These findings imply this species is capable of deep-sea penetration through isothermal water columns prevailing at high latitudes. This study gives new insight into the fundamentals behind past and future colonisation events. Such knowledge is instrumental to understand better how changes in climate envelopes affect the distribution and radiation of species along latitudinal as well as bathymetric temperature gradients. PMID:23227254

The secret to successful deep-sea invasion: does low temperature hold the key?

PubMed

Smith, Kathryn E; Thatje, Sven

2012-01-01

There is a general consensus that today's deep-sea biodiversity has largely resulted from recurrent invasions and speciations occurring through homogenous waters during periods of the Phanerozoic eon. Migrations likely continue today, primarily via isothermal water columns, such as those typical of Polar Regions, but the necessary ecological and physiological adaptations behind them are poorly understood. In an evolutionary context, understanding the adaptations, which allow for colonisation to high-pressure environments, may enable us to predict future events. In this investigation, we examine pressure tolerance during development, in the shallow-water neogastropod Buccinum undatum using thermally acclimated egg masses from temperate and sub-polar regions across the species range. Fossil records indicate neogastropods to have a deep-water origin, suggesting shallow-water species may be likely candidates for re-emergence into the deep sea. Our results show population level differences in physiological thresholds, which indicate low temperature acclimation to increase pressure tolerance. These findings imply this species is capable of deep-sea penetration through isothermal water columns prevailing at high latitudes. This study gives new insight into the fundamentals behind past and future colonisation events. Such knowledge is instrumental to understand better how changes in climate envelopes affect the distribution and radiation of species along latitudinal as well as bathymetric temperature gradients.

Seafloor heterogeneity influences the biodiversity–ecosystem functioning relationships in the deep sea

PubMed Central

Zeppilli, Daniela; Pusceddu, Antonio; Trincardi, Fabio; Danovaro, Roberto

2016-01-01

Theoretical ecology predicts that heterogeneous habitats allow more species to co-exist in a given area. In the deep sea, biodiversity is positively linked with ecosystem functioning, suggesting that deep-seabed heterogeneity could influence ecosystem functions and the relationships between biodiversity and ecosystem functioning (BEF). To shed light on the BEF relationships in a heterogeneous deep seabed, we investigated variations in meiofaunal biodiversity, biomass and ecosystem efficiency within and among different seabed morphologies (e.g., furrows, erosional troughs, sediment waves and other depositional structures, landslide scars and deposits) in a narrow geo-morphologically articulated sector of the Adriatic Sea. We show that distinct seafloor morphologies are characterized by highly diverse nematode assemblages, whereas areas sharing similar seabed morphologies host similar nematode assemblages. BEF relationships are consistently positive across the entire region, but different seabed morphologies are characterised by different slope coefficients of the relationship. Our results suggest that seafloor heterogeneity, allowing diversified assemblages across different habitats, increases diversity and influence ecosystem processes at the regional scale, and BEF relationships at smaller spatial scales. We conclude that high-resolution seabed mapping and a detailed analysis of the species distribution at the habitat scale are crucial for improving management of goods and services delivered by deep-sea ecosystems. PMID:27211908

Low Thrust, Deep Throttling, US/CIS Integrated NTRE

NASA Astrophysics Data System (ADS)

Culver, Donald W.; Kolganov, Vyacheslav; Rochow, Richard F.

1994-07-01

In 1993 our international team performed a follow-on ``Nuclear Thermal Rocket Engine (NTRE) Extended Life Feasibility Assessment'' study for the Nuclear Propulsion Office (NPO) at NASAs Lewis Research Center. The main purpose of this study was to complete the 1992 study matrix to assess NTRE designs at thrust levels of 22.5, 11.3, and 6.8 tonnes, using Commonwealth of Independent States (CIS) reactor technology. An additional Aerojet goal was to continue improving the NTRE concept we had generated. Deep throttling, mission performance optimized engine design parametrics, and reliability/cost enhancing engine system simplifications were studied, because they seem to be the last three basic design improvements sorely needed by post-NERVA NTRE. Deep throttling improves engine life by eliminating damaging thermal and mechanical shocks caused by after-cooling with pulsed coolant flow. Alternately, it improves mission performance with steady flow after-cooling by minimizing reactor over-cooling. Deep throttling also provides a practical transition from high pressures and powers of the high thrust power cycle to the low pressures and powers of our electric power generating mode. Two deep throttling designs are discussed; a workable system that was studied and a simplified system that is recommended for future study. Mission-optimized engine thrust/weight (T/W) and Isp predictions are included along with system flow schemes and concept sketches.

Deep ice and salty oceans of icy worlds, how high pressures influence their thermodynamics and provide constrains on extraterrestrial habitability

NASA Astrophysics Data System (ADS)

Journaux, B.; Brown, J. M.; Bollengier, O.; Abramson, E.

2017-12-01

As in Earth arctic and Antarctic regions, suspected extraterrestrial deep oceans in icy worlds (i.e. icy moons and water-rich exoplanets) chemistry and thermodynamic state will strongly depend on their equilibrium with H2O ice and present solutes. Na-Mg-Cl-SO4 salt species are currently the main suspected ionic solutes to be present in deep oceans based on remote sensing, magnetic field measurements, cryovolcanism ice grains chemical analysis and chondritic material aqueous alteration chemical models. Unlike on our planet, deep extraterrestrial ocean might also be interacting at depth with high pressure ices (e.g. III, V, VI, VI, X) which have different behavior compared to ice Ih. Unfortunately, the pressures and temperatures inside these hydrospheres differ significantly from the one found in Earth aqueous environments, so most of our current thermodynamic databases do not cover the range of conditions relevant for modeling realistically large icy worlds interiors. Recent experimental results have shown that the presence of solutes, and more particularly salts, in equilibrium with high pressure ices have large effects on the stability, buoyancy and chemistry of all the phases present at these extreme conditions. High pressure in-situ measurements using diamond anvil cell apparatus were operated both at the University of washington and at the European Synchrotron Radiation Facility on aqueous systems phase diagrams with Na-Mg-Cl-SO4 species, salt incorporation in high pressure ices and density inversions between the solid and the fluids. These results suggest a more complex picture of the interior structure, dynamic and chemical evolution of large icy worlds hydrospheres when solutes are taken into account, compared to current models mainly using pure water. Based on our in-situ experimental measurements, we propose the existence of new liquid environments at greater depths and the possibility of solid state transport of solute through the high pressure ices(s) layers suggesting that large icy worlds like Enceladus, Titan or water-rich exoplanets could have habitable deep oceans, even when high pressure ices are present.

Structural control on the deep hydrogeological and geothermal aquifers related to the fractured Campanian-Miocene reservoirs of north-eastern Tunisia foreland constrained by subsurface data

NASA Astrophysics Data System (ADS)

Khomsi, Sami; Echihi, Oussema; Slimani, Naji

2012-03-01

A set of different data including high resolution seismic sections, petroleum wire-logging well data, borehole piezometry, structural cross-sections and outcrop analysis allowed us to characterise the tectonic framework, and its relationships with the deep aquifers seated in Cretaceous-Miocene deep reservoirs. The structural framework, based on major structures, controls the occurrence of deep aquifers and sub-basin aquifer distributions. Five structural domains can be defined, having different morphostructural characteristics. The northernmost domain lying on the north-south axis and Zaghouan thrust system is a domain of recharge by underflow of the different subsurface reservoirs and aquifers from outcrops of highly fractured reservoirs. On the other hand, the morphostructural configuration controls the piezometry of underground flows in the Plio-Quaternary unconfined aquifer. In the subsurface the Late Cretaceous-Miocene reservoirs are widespread with high thicknesses in many places and high porosities and connectivities especially along major fault corridors and on the crestal parts of major anticlines. Among all reservoirs, the Oligo-Miocene, detritic series are widespread and present high cumulative thicknesses. Subsurface and fieldwork outline the occurrence of 10 fractured sandy reservoirs for these series with packages having high hydrodynamic and petrophysical characteristics. These series show low salinities (maximum 5 g/l) in the northern part of the study area and will constitute an important source of drinkable water for the next generations. A regional structural cross-section is presented, compiled from all the different data sets, allowing us to define the major characteristics of the hydrogeological-hydrogeothermal sub-basins. Eight hydrogeological provinces are defined from north-west to south-east. A major thermal anomaly is clearly identified in the south-eastern part of the study area in Sfax-Sidi Il Itayem. This anomaly is possibly related to major faults pertaining to the Sirt basin and controlled by a deep thermal anomaly. Many exploration targets are identified especially along the Cherichira-Kondar thrust where the Oligocene subcropping reservoirs are well developed. They are highly fractured and show good hydrodynamic characteristics.

In-Situ Contained And Of Volatile Soil Contaminants

DOEpatents

Varvel, Mark Darrell

2005-12-27

The invention relates to a novel approach to containing and removing toxic waste from a subsurface environment. More specifically the present invention relates to a system for containing and removing volatile toxic chemicals from a subsurface environment using differences in surface and subsurface pressures. The present embodiment generally comprises a deep well, a horizontal tube, at least one injection well, at least one extraction well and a means for containing the waste within the waste zone (in-situ barrier). During operation the deep well air at the bottom of well (which is at a high pressure relative to the land surface as well as relative to the air in the contaminated soil) flows upward through the deep well (or deep well tube). This stream of deep well air is directed into the horizontal tube, down through the injection tube(s) (injection well(s)) and into the contaminate plume where it enhances volatization and/or removal of the contaminants.

In-Situ Containment and Extraction of Volatile Soil Contaminants

DOEpatents

Varvel, Mark Darrell

2005-12-27

The invention relates to a novel approach to containing and removing toxic waste from a subsurface environment. More specifically the present invention relates to a system for containing and removing volatile toxic chemicals from a subsurface environment using differences in surface and subsurface pressures. The present embodiment generally comprises a deep well, a horizontal tube, at least one injection well, at least one extraction well and a means for containing the waste within the waste zone (in-situ barrier). During operation the deep well air at the bottom of well (which is at a high pressure relative to the land surface as well as relative to the air in the contaminated soil) flows upward through the deep well (or deep well tube). This stream of deep well air is directed into the horizontal tube, down through the injection tube(s) (injection well(s)) and into the contaminate plume where it enhances volatization and/or removal of the contaminants.

The Deep Space Atomic Clock Mission

NASA Technical Reports Server (NTRS)

Ely, Todd A.; Koch, Timothy; Kuang, Da; Lee, Karen; Murphy, David; Prestage, John; Tjoelker, Robert; Seubert, Jill

2012-01-01

The Deep Space Atomic Clock (DSAC) mission will demonstrate the space flight performance of a small, low-mass, high-stability mercury-ion atomic clock with long term stability and accuracy on par with that of the Deep Space Network. The timing stability introduced by DSAC allows for a 1-Way radiometric tracking paradigm for deep space navigation, with benefits including increased tracking via utilization of the DSN's Multiple Spacecraft Per Aperture (MSPA) capability and full ground station-spacecraft view periods, more accurate radio occultation signals, decreased single-frequency measurement noise, and the possibility for fully autonomous on-board navigation. Specific examples of navigation and radio science benefits to deep space missions are highlighted through simulations of Mars orbiter and Europa flyby missions. Additionally, this paper provides an overview of the mercury-ion trap technology behind DSAC, details of and options for the upcoming 2015/2016 space demonstration, and expected on-orbit clock performance.

Frameless Stereotactic Insertion of Viewsite Brain Access System with Microscope-Mounted Tracking Device for Resection of Deep Brain Lesions: Technical Report

PubMed Central

Chakraborty, Shamik; Lall, Rohan; Fanous, Andrew A; Boockvar, John; Langer, David J

2017-01-01

The surgical management of deep brain tumors is often challenging due to the limitations of stereotactic needle biopsies and the morbidity associated with transcortical approaches. We present a novel microscopic navigational technique utilizing the Viewsite Brain Access System (VBAS) (Vycor Medical, Boca Raton, FL, USA) for resection of a deep parietal periventricular high-grade glioma as well as another glioma and a cavernoma with no related morbidity. The approach utilized a navigational tracker mounted on a microscope, which was set to the desired trajectory and depth. It allowed gentle continuous insertion of the VBAS directly to a deep lesion under continuous microscopic visualization, increasing safety by obviating the need to look up from the microscope and thus avoiding loss of trajectory. This technique has broad value for the resection of a variety of deep brain lesions. PMID:28331774

Frameless Stereotactic Insertion of Viewsite Brain Access System with Microscope-Mounted Tracking Device for Resection of Deep Brain Lesions: Technical Report.

PubMed

White, Tim; Chakraborty, Shamik; Lall, Rohan; Fanous, Andrew A; Boockvar, John; Langer, David J

2017-02-04

The surgical management of deep brain tumors is often challenging due to the limitations of stereotactic needle biopsies and the morbidity associated with transcortical approaches. We present a novel microscopic navigational technique utilizing the Viewsite Brain Access System (VBAS) (Vycor Medical, Boca Raton, FL, USA) for resection of a deep parietal periventricular high-grade glioma as well as another glioma and a cavernoma with no related morbidity. The approach utilized a navigational tracker mounted on a microscope, which was set to the desired trajectory and depth. It allowed gentle continuous insertion of the VBAS directly to a deep lesion under continuous microscopic visualization, increasing safety by obviating the need to look up from the microscope and thus avoiding loss of trajectory. This technique has broad value for the resection of a variety of deep brain lesions.

Ultra-Deep Drilling Cost Reduction; Design and Fabrication of an Ultra-Deep Drilling Simulator (UDS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindstrom, Jason

2010-01-31

Ultra-deep drilling, below about 20,000 ft (6,096 m), is extremely expensive and limits the recovery of hydrocarbons at these depths. Unfortunately, rock breakage and cuttings removal under these conditions is not understood. To better understand and thus reduce cost at these conditions an ultra-deep single cutter drilling simulator (UDS) capable of drill cutter and mud tests to sustained pressure and temperature of 30,000 psi (207 MPa) and 482 °F (250 °C), respectively, was designed and manufactured at TerraTek, a Schlumberger company, in cooperation with the Department of Energy’s National Energy Technology Laboratory. UDS testing under ultra-deep drilling conditions offers anmore » economical alternative to high day rates and can prove or disprove the viability of a particular drilling technique or fluid to provide opportunity for future domestic energy needs.« less

A Stepwise Approach: Decreasing Infection in Deep Brain Stimulation for Childhood Dystonic Cerebral Palsy.

PubMed

Johans, Stephen J; Swong, Kevin N; Hofler, Ryan C; Anderson, Douglas E

2017-09-01

Dystonia is a movement disorder characterized by involuntary muscle contractions, which cause twisting movements or abnormal postures. Deep brain stimulation has been used to improve the quality of life for secondary dystonia caused by cerebral palsy. Despite being a viable treatment option for childhood dystonic cerebral palsy, deep brain stimulation is associated with a high rate of infection in children. The authors present a small series of patients with dystonic cerebral palsy who underwent a stepwise approach for bilateral globus pallidus interna deep brain stimulation placement in order to decrease the rate of infection. Four children with dystonic cerebral palsy who underwent a total of 13 surgical procedures (electrode and battery placement) were identified via a retrospective review. There were zero postoperative infections. Using a multistaged surgical plan for pediatric patients with dystonic cerebral palsy undergoing deep brain stimulation may help to reduce the risk of infection.

Deep neck infection after third molar extraction: A case report.

PubMed

da Silva Junior, Alberto Ferreira; de Magalhaes Rocha, Gustavo Silvestre; da Silva Neves de Araujo, Camila Fialho; Franco, Ademir; Silva, Rhonan Ferreira

2017-01-01

Deep neck infections are associated with high morbidity rates in dentistry. Early diagnosis and intervention play an essential part in decreasing morbidity rates. The present study aims to report a case of odontogenic deep neck infection after third molar extraction. A 51-year-old male patient underwent extraction of the mandibular right third molar. Seven days later, the patient developed symptoms and signs of progressive infection. Laboratorial and radiologic examinations in association with clinical investigations confirmed deep neck infection. Extraoral drainage was performed under orotracheal intubation. Postoperative laboratory tests and clinical examinations revealed signs of complete remission within a follow-up period of 10 days. Considering the invasive nature of pathogens related to deep neck infections, it is possible to infer that a combination of accurate diagnosis and early intervention plays an essential role in the field of maxillofacial surgery and pathology.

High level of intergenera gene exchange shapes the evolution of haloarchaea in an isolated Antarctic lake.

PubMed

DeMaere, Matthew Z; Williams, Timothy J; Allen, Michelle A; Brown, Mark V; Gibson, John A E; Rich, John; Lauro, Federico M; Dyall-Smith, Michael; Davenport, Karen W; Woyke, Tanja; Kyrpides, Nikos C; Tringe, Susannah G; Cavicchioli, Ricardo

2013-10-15

Deep Lake in Antarctica is a globally isolated, hypersaline system that remains liquid at temperatures down to -20 °C. By analyzing metagenome data and genomes of four isolates we assessed genome variation and patterns of gene exchange to learn how the lake community evolved. The lake is completely and uniformly dominated by haloarchaea, comprising a hierarchically structured, low-complexity community that differs greatly to temperate and tropical hypersaline environments. The four Deep Lake isolates represent distinct genera (∼85% 16S rRNA gene similarity and ∼73% genome average nucleotide identity) with genomic characteristics indicative of niche adaptation, and collectively account for ∼72% of the cellular community. Network analysis revealed a remarkable level of intergenera gene exchange, including the sharing of long contiguous regions (up to 35 kb) of high identity (∼100%). Although the genomes of closely related Halobacterium, Haloquadratum, and Haloarcula (>90% average nucleotide identity) shared regions of high identity between species or strains, the four Deep Lake isolates were the only distantly related haloarchaea to share long high-identity regions. Moreover, the Deep Lake high-identity regions did not match to any other hypersaline environment metagenome data. The most abundant species, tADL, appears to play a central role in the exchange of insertion sequences, but not the exchange of high-identity regions. The genomic characteristics of the four haloarchaea are consistent with a lake ecosystem that sustains a high level of intergenera gene exchange while selecting for ecotypes that maintain sympatric speciation. The peculiarities of this polar system restrict which species can grow and provide a tempo and mode for accentuating gene exchange.

An Exciplex Host for Deep-Blue Phosphorescent Organic Light-Emitting Diodes.

PubMed

Lim, Hyoungcheol; Shin, Hyun; Kim, Kwon-Hyeon; Yoo, Seung-Jun; Huh, Jin-Suk; Kim, Jang-Joo

2017-11-01

The use of exciplex hosts is attractive for high-performance phosphorescent organic light-emitting diodes (PhOLEDs) and thermally activated delayed fluorescence OLEDs, which have high external quantum efficiency, low driving voltage, and low efficiency roll-off. However, exciplex hosts for deep-blue OLEDs have not yet been reported because of the difficulties in identifying suitable molecules. Here, we report a deep-blue-emitting exciplex system with an exciplex energy of 3.0 eV. It is composed of a carbazole-based hole-transporting material (mCP) and a phosphine-oxide-based electron-transporting material (BM-A10). The blue PhOLEDs exhibited maximum external quantum efficiency of 24% with CIE coordinates of (0.15, 0.21) and longer lifetime than the single host devices.

Jet-images — deep learning edition

DOE PAGES

de Oliveira, Luke; Kagan, Michael; Mackey, Lester; ...

2016-07-13

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Jet-images — deep learning edition

DOE Office of Scientific and Technical Information (OSTI.GOV)

de Oliveira, Luke; Kagan, Michael; Mackey, Lester

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. Finally, this interplay between physically-motivated feature driven tools and supervised learning algorithms is generalmore » and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.« less

Muonium in Stishovite: Implications for the Possible Existence of Neutral Atomic Hydrogen in the Earth's Deep Mantle

PubMed Central

Funamori, Nobumasa; Kojima, Kenji M.; Wakabayashi, Daisuke; Sato, Tomoko; Taniguchi, Takashi; Nishiyama, Norimasa; Irifune, Tetsuo; Tomono, Dai; Matsuzaki, Teiichiro; Miyazaki, Masanori; Hiraishi, Masatoshi; Koda, Akihiro; Kadono, Ryosuke

2015-01-01

Hydrogen in the Earth's deep interior has been thought to exist as a hydroxyl group in high-pressure minerals. We present Muon Spin Rotation experiments on SiO2 stishovite, which is an archetypal high-pressure mineral. Positive muon (which can be considered as a light isotope of proton) implanted in stishovite was found to capture electron to form muonium (corresponding to neutral hydrogen). The hyperfine-coupling parameter and the relaxation rate of spin polarization of muonium in stishovite were measured to be very large, suggesting that muonium is squeezed in small and anisotropic interstitial voids without binding to silicon or oxygen. These results imply that hydrogen may also exist in the form of neutral atomic hydrogen in the deep mantle. PMID:25675890

Sunspot drawings handwritten character recognition method based on deep learning

NASA Astrophysics Data System (ADS)

Zheng, Sheng; Zeng, Xiangyun; Lin, Ganghua; Zhao, Cui; Feng, Yongli; Tao, Jinping; Zhu, Daoyuan; Xiong, Li

2016-05-01

High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.

An electrophysiological investigation of memory encoding, depth of processing, and word frequency in humans.

PubMed

Guo, Chunyan; Zhu, Ying; Ding, Jinhong; Fan, Silu; Paller, Ken A

2004-02-12

Memory encoding can be studied by monitoring brain activity correlated with subsequent remembering. To understand brain potentials associated with encoding, we compared multiple factors known to affect encoding. Depth of processing was manipulated by requiring subjects to detect animal names (deep encoding) or boldface (shallow encoding) in a series of Chinese words. Recognition was more accurate with deep than shallow encoding, and for low- compared to high-frequency words. Potentials were generally more positive for subsequently recognized versus forgotten words; for deep compared to shallow processing; and, for remembered words only, for low- than for high-frequency words. Latency and topographic differences between these potentials suggested that several factors influence the effectiveness of encoding and can be distinguished using these methods, even with Chinese logographic symbols.

Muonium in Stishovite: Implications for the Possible Existence of Neutral Atomic Hydrogen in the Earth's Deep Mantle

NASA Astrophysics Data System (ADS)

Funamori, Nobumasa; Kojima, Kenji M.; Wakabayashi, Daisuke; Sato, Tomoko; Taniguchi, Takashi; Nishiyama, Norimasa; Irifune, Tetsuo; Tomono, Dai; Matsuzaki, Teiichiro; Miyazaki, Masanori; Hiraishi, Masatoshi; Koda, Akihiro; Kadono, Ryosuke

2015-02-01

Hydrogen in the Earth's deep interior has been thought to exist as a hydroxyl group in high-pressure minerals. We present Muon Spin Rotation experiments on SiO2 stishovite, which is an archetypal high-pressure mineral. Positive muon (which can be considered as a light isotope of proton) implanted in stishovite was found to capture electron to form muonium (corresponding to neutral hydrogen). The hyperfine-coupling parameter and the relaxation rate of spin polarization of muonium in stishovite were measured to be very large, suggesting that muonium is squeezed in small and anisotropic interstitial voids without binding to silicon or oxygen. These results imply that hydrogen may also exist in the form of neutral atomic hydrogen in the deep mantle.

The Future of the Deep Space Network: Technology Development for K2-Band Deep Space Communications

NASA Technical Reports Server (NTRS)

Bhanji, Alaudin M.

1999-01-01

Projections indicate that in the future the number of NASA's robotic deep space missions is likely to increase significantly. A launch rate of up to 4-6 launches per year is projected with up to 25 simultaneous missions active [I]. Future high resolution mapping missions to other planetary bodies as well as other experiments are likely to require increased downlink capacity. These future deep space communications requirements will, according to baseline loading analysis, exceed the capacity of NASA's Deep Space Network in its present form. There are essentially two approaches for increasing the channel capacity of the Deep Space Network. Given the near-optimum performance of the network at the two deep space communications bands, S-Band (uplink 2.025-2.120 GHz, downlink 2.2-2.3 GHz), and X-Band (uplink 7.145-7.19 GHz, downlink 8.48.5 GHz), additional improvements bring only marginal return for the investment. Thus the only way to increase channel capacity is simply to construct more antennas, receivers, transmitters and other hardware. This approach is relatively low-risk but involves increasing both the number of assets in the network and operational costs.

Extracting Databases from Dark Data with DeepDive

PubMed Central

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data: the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data — scientific papers, Web classified ads, customer service notes, and so on — were instead in a relational database, it would give analysts a massive and valuable new set of “big data.” DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference. PMID:28316365

Role of Southern Ocean stratification in glacial atmospheric CO2 reduction

NASA Astrophysics Data System (ADS)

Kobayashi, H.; Oka, A.

2014-12-01

Paleoclimate proxy data at the glacial period shows high salinity of more than 37.0 psu in the deep South Atlantic. At the same time, data also indicate that the residence time of the water mass was more than 3000 years. These data implies that the stratification by salinity was stronger in the deep Southern Ocean (SO) in the Last Glacial Maximum (LGM). Previous studies using Ocean General Circulation Model (OGCM) fail to explain the low glacial atmospheric carbon dioxide (CO2) concentration at LGM. The reproducibility of salinity and water mass age is considered insufficient in these OGCMs, which may in turn affect the reproducibility of the atmospheric CO2concentration. In coarse-resolution OGCMs, The deep water is formed by unrealistic open-ocean deep convection in the SO. Considering these facts, we guessed previous studies using OGCM underestimated the salinity and water mass age at LGM. This study investigate the role of the enhanced stratification in the glacial SO on the variation of atmospheric CO2 concentration by using OGCM. In order to reproduce the recorded salinity of the deep water, relaxation of salinity toward value of recorded data is introduced in our OGCM simulations. It was found that deep water formation in East Antarctica is required for explaining the high salinity in the South Atlantic. In contrast, it is difficult to explain the glacial water mass age, even if we assume the situation vertical mixing is very weak in the SO. Contrary to previous estimate, the high salinity of the deep SO resulted in increase of Antarctic Bottom water (AABW) flow and decrease the residence time of carbon in the deep ocean, which increased atmospheric CO2 concentration. On the other hand, the weakening of the vertical mixing in the SO contributed to increase the vertical gradient of dissolved inorganic carbon (DIC), which decreased atmospheric CO2 concentration. Adding the contribution of the enhanced stratification in the glacial SO, we obtained larger reduction in atmospheric CO2 concentration than previous studies. However, we still fail to explain the full amplitude of recorded glacial reduction of atmospheric CO2 concentration. The carbonate compensation process, which is not incorporated in our simulations, might be required for further reduction in atmospheric CO2 concentration.

Modulation of cosmic rays on geomagnetically most quiet days

NASA Astrophysics Data System (ADS)

Agarwal Mishra, Rekha; Agarwal Mishra, Rekha; Mishra, Rajesh Kumar

The aim of this work is to study the first three harmonics of cosmic ray intensity on geomagnetically quiet days over the period 1980-1990 for Deep River and Tokyo neutron monitoring stations. The amplitude of first harmonic remains high for Deep River having low cutoff rigidity as compared to Tokyo neutron monitor having high cutoff rigidity on quiet days.. The diurnal time of maximum significantly shifts to an earlier time as compared to the corotational/1800 Hr direction at both the stations having different cutoff rigidities. The time of maximum for first harmonic significantly shifts towards later hours and for second harmonic it shifts towards earlier hours at low cutoff rigidity station i.e. Deep River as compared to the high cut off rigidity station i.e. Tokyo on quiet days. The amplitude of semi/tri-diurnal anisotropy have a good positive correlation with solar wind velocity, while the others (i.e. amplitude and phase) have no significant correlation on quiet days for Deep River and Tokyo having different cutoff rigidity during 1980-1990. The solar wind velocity significantly remains in the range 350 to 425 km/s i.e. being nearly average on quiet days. The amplitude and direction of the anisotropy on quiet days are weakly dependent on high-speed solar wind streams for two neutron monitoring station of low and high cutoff rigidity threshold. The semi-diurnal amplitude has a significant anti-correlation, whereas the amplitude of third harmonic and direction of first harmonic has a good anti-correlation with IMF Bz and the product V x Bz on quiet days at Deep River station. However, the direction of first harmonic has a significant anti-correlation and the direction of second harmonic has a good anti-correlation with IMF Bz and the product V x Bz on quiet days at Tokyo station.

High diving metabolic rate indicated by high-speed transit to depth in negatively buoyant long-finned pilot whales.

PubMed

Aoki, Kagari; Sato, Katsufumi; Isojunno, Saana; Narazaki, Tomoko; Miller, Patrick J O

2017-10-15

To maximize foraging duration at depth, diving mammals are expected to use the lowest cost optimal speed during descent and ascent transit and to minimize the cost of transport by achieving neutral buoyancy. Here, we outfitted 18 deep-diving long-finned pilot whales with multi-sensor data loggers and found indications that their diving strategy is associated with higher costs than those of other deep-diving toothed whales . Theoretical models predict that optimal speed is proportional to (basal metabolic rate/drag) 1/3 and therefore to body mass 0.05 The transit speed of tagged animals (2.7±0.3 m s -1 ) was substantially higher than the optimal speed predicted from body mass (1.4-1.7 m s -1 ). According to the theoretical models, this choice of high transit speed, given a similar drag coefficient (median, 0.0035) to that in other cetaceans, indicated greater basal metabolic costs during diving than for other cetaceans. This could explain the comparatively short duration (8.9±1.5 min) of their deep dives (maximum depth, 444±85 m). Hydrodynamic gliding models indicated negative buoyancy of tissue body density (1038.8±1.6 kg m -3 , ±95% credible interval, CI) and similar diving gas volume (34.6±0.6 ml kg -1 , ±95% CI) to those in other deep-diving toothed whales. High diving metabolic rate and costly negative buoyancy imply a 'spend more, gain more' strategy of long-finned pilot whales, differing from that in other deep-diving toothed whales, which limits the costs of locomotion during foraging. We also found that net buoyancy affected the optimal speed: high transit speeds gradually decreased during ascent as the whales approached neutral buoyancy owing to gas expansion. © 2017. Published by The Company of Biologists Ltd.

Nonhydrostatic thermohaline convection in the polar oceans

NASA Astrophysics Data System (ADS)

Potts, Mark Allen

Sea ice cover in the polar and sub-polar seas is an important and sensitive component of the Earth's climate system. It mediates the transfer of heat and momentum between the ocean and the atmosphere in high latitude oceans. Where open patches occur in the ice cover a large transfer of heat from the ocean to the atmosphere occurs that accounts for a large fraction of energy exchange between the wintertime polar ocean and atmosphere. Although the circumstances under which leads and polynyas form are considerably different, similar brine driven convection occurs under both. Convection beneath freezing ice in leads and polynyas can be modeled using either the hydrostatic or nonhydrostatic form of the governing equations. One important question is the degree of nonhydrostaticity, which depends on the vertical accelerations present. This issue is addressed through the application of a nonhydrostatic model, with accurate treatment of the turbulent mixing. The results suggest that mixing and re-freezing considerably modify the fluid dynamical processes underneath, such as the periodic shedding of saline plumes. It also appears that overall, the magnitude of the nonhydrostaticity is small, and hydrostatic models are generally adequate to deal with the problem of convection under leads. Strong wintertime cooling drives deep convection in sub-polar seas and in the coastal waters surrounding Antarctica. Deep convection results in formation of deep water in the global oceans, which is of great importance to the maintenance of the stratification of its deep interior, and the resulting meridional circulation is central to the Earth's climatic state. Deep convection falls into two general categories: open ocean deep convection, which occurs in deep stretches of the high latitude seas far from topographical influences, and convection on or near the continental shelves, where topography exerts a considerable influence. Nonhydrostatic models are central to the study of deep convection, but the presence of the bottom leads to significant complications in shallower waters. This issue of deep convection in the presence of topography is addressed for the first time with a non-hydrostatic model through the adaptation of the virtual boundary method and used to simulate convection over the Mertz Glacier polynya in the Antarctic in both two and three dimensions.

Interannual variability (1979-2013) of the North-Western Mediterranean deep water mass formation: past observation reanalysis and coupled ocean-atmosphere high-resolution modelling

NASA Astrophysics Data System (ADS)

Somot, Samuel; Houpert, Loic; Sevault, Florence; Testor, Pierre; Bosse, Anthony; Durrieu de Madron, Xavier; Dubois, Clotilde; Herrmann, Marine; Waldman, Robin; Bouin, Marie-Noëlle; Cassou, Christophe

2015-04-01

The North-Western Mediterranean Sea is known as one of the only place in the world where open-sea deep convection occurs (often up to more than 2000m) with the formation of the Western Mediterranean Deep Water (WMDW). This phenomena is mostly driven by local preconditioning of the water column and strong buoyancy losses during Winter. At the event scale, the WMDW formation is characterized by different phases (preconditioning, strong mixing, restratification and spreading), intense air-sea interaction and strong meso-scale activity but, on a longer time scale, it also shows a large interannual variability and may be strongly affected by climate change with impact on the regional biogeochemistry. Therefore observing, simulating and understanding the long-term temporal variability of the North-Western Mediterranean deep water formation is still today a very challenging task. We try here to tackle those issues thanks to (1) a thorough reanalysis of past in-situ observations (CTD, Argo, surface and deep moorings, gliders) and (2) an ERA-Interim driven simulation using a recently-developed fully coupled Regional Climate System Model (CNRM-RCSM4, Sevault et al. 2014). The multi-decadal simulation (1979-2013) is designed to be temporally and spatially homogeneous with a realistic chronology, a high resolution representation of both the regional ocean and atmosphere, specific initial conditions, a long-term spin-up and a full ocean-atmosphere coupling without constraint at the air-sea interface. The observation reanalysis allows to reconstruct interannual time series of deep water formation indicators (ocean surface variables, mixed layer depth, surface of the convective area, dense water volumes and characteristics of the deep water). Using the observation-based indicators and the model outputs, the 34 Winters of the period 1979-2013 are analysed in terms of weather regimes, related Winter air-sea fluxes, ocean preconditioning, mixed layer depth, surface of the convective area, deep water formation rate and long-term evolution of the deep water hydrology.

Oxygen uptake and vertical transport during deep convection events

NASA Astrophysics Data System (ADS)

Sun, D.; Ito, T.; Bracco, A.

2016-02-01

Dissolved oxygen (O2) is essential for the chemistry and living organisms of the oceans. O2 is consumed in the interior ocean due to the respiration of organic matter, and must be replenished by physical ventilation with the O2-rich surface waters. The O2 supply to the deep waters happens only through the subduction and deep convection during cold seasons at high latitude oceans. The Labrador Sea is one of the few regions where deep ventilation occurs. According to observational and modeling studies, the intensity, duration and timing of deep convection events have varied significantly on the interannual and decadal timescales. In this study we develop a theoretical framework to understand the air-sea transfer of O2 during open-ocean deep convection events. The theory is tested against a suite of numerical integrations using MITgcm in non-hydrostatic configuration including the parameterization of diffusive and bubble mediated gas transfer. Forced with realistic air-sea buoyancy fluxes, the model can reproduce the evolution of temperature, salinity and dissolved O2 observed by ARGO floats in the Labrador Sea. Idealized sensitivity experiments are performed changing the intensity and duration of the buoyancy forcing as well as the wind speed for the gas exchange parameterizations. The downward transport of O2 results from the combination of vertical homogenization of existing O2 and the uptake from the air-sea flux. The intensity of the buoyancy forcing controls the vertical extent of convective mixing which brings O2 to the deep ocean. Integrated O2 uptake increases with the duration of convection even when the total buoyancy loss is held constant. The air-sea fluxes are highly sensitive to the wind speed especially for the bubble injection flux, which is a major addition to the diffusive flux under strong winds. However, the bubble injection flux can be partially compensated by the diffusive outgassing in response to the elevated saturation state. Under strong buoyancy forcing, this compensation is suppressed by the entrainment of relatively O2-poor deep waters. These results imply and allow to quantify the direct link between variability of deep convection and the supply of O2 in the North Atlantic.

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning

PubMed Central

Preuer, Kristina; Lewis, Richard P I; Hochreiter, Sepp; Bender, Andreas; Bulusu, Krishna C; Klambauer, Günter

2018-01-01

Abstract Motivation While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a time- and cost-efficient way to prioritize combinations to test, based on recently available large-scale combination screening data. Recently, Deep Learning has had an impact in many research areas by achieving new state-of-the-art model performance. However, Deep Learning has not yet been applied to drug synergy prediction, which is the approach we present here, termed DeepSynergy. DeepSynergy uses chemical and genomic information as input information, a normalization strategy to account for input data heterogeneity, and conical layers to model drug synergies. Results DeepSynergy was compared to other machine learning methods such as Gradient Boosting Machines, Random Forests, Support Vector Machines and Elastic Nets on the largest publicly available synergy dataset with respect to mean squared error. DeepSynergy significantly outperformed the other methods with an improvement of 7.2% over the second best method at the prediction of novel drug combinations within the space of explored drugs and cell lines. At this task, the mean Pearson correlation coefficient between the measured and the predicted values of DeepSynergy was 0.73. Applying DeepSynergy for classification of these novel drug combinations resulted in a high predictive performance of an AUC of 0.90. Furthermore, we found that all compared methods exhibit low predictive performance when extrapolating to unexplored drugs or cell lines, which we suggest is due to limitations in the size and diversity of the dataset. We envision that DeepSynergy could be a valuable tool for selecting novel synergistic drug combinations. Availability and implementation DeepSynergy is available via www.bioinf.jku.at/software/DeepSynergy. Contact klambauer@bioinf.jku.at Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253077

Deep-sea ciliates: Recorded diversity and experimental studies on pressure tolerance

NASA Astrophysics Data System (ADS)

Schoenle, Alexandra; Nitsche, Frank; Werner, Jennifer; Arndt, Hartmut

2017-10-01

Microbial eukaryotes play an important role in biogeochemical cycles not only in productive surface waters but also in the deep sea. Recent studies based on metagenomics report deep-sea protistan assemblages totally different from continental slopes and shelf waters. To give an overview about the ciliate fauna recorded from the deep sea we summarized the available information on ciliate occurrence in the deep sea. Our literature review revealed that representatives of the major phylogenetic groups of ciliates were recorded from the deep sea (> 1000 m depth): Karyorelictea, Heterotrichea, Spirotrichea (Protohypotrichia, Euplotia, Oligotrichia, Choreotrichia, Hypotrichia), Armophorea (Armophorida), Litostomatea (Haptoria), Conthreep (Phyllopharyngea incl. Cyrtophoria, Chonotrichia, Suctoria; Nassophorea incl. Microthoracida, Synhymeniida, Nassulida; Colpodea incl. Bursariomorphida, Cyrtolophosidida; Prostomatea; Plagiopylea incl. Plagiopylida, Odontostomatida; Oligohymenophorea incl. Peniculia, Scuticociliatia, Hymenostomatia, Apostomatia, Peritrichia, Astomatia). Species occurring in both habitats, deep sea and shallow water, are rarely found to our knowledge to date. This indicates a high deep-sea specific ciliate fauna. Our own studies of similar genotypes (SSU rDNA and cox1 gene) revealed that two small scuticociliate species (Pseudocohnilembus persalinus and Uronema sp.) could be isolated from surface as well as deep waters (2687 m, 5276 m, 5719 m) of the Pacific. The adaptation to deep-sea conditions was investigated by exposing the ciliate isolates directly or stepwise to different hydrostatic pressures ranging from 1 to 550 atm at temperatures of 2 °C and 13 °C. Although the results indicated no general barophilic behavior, all four isolated strains survived the highest established pressure. A better survival at 550 atm could be observed for the lower temperature. Among microbial eukaryotes, ciliates should be considered as a diverse and potentially important component of deep-sea microeukaryote communities.

Deep-Sea Biodiversity in the Mediterranean Sea: The Known, the Unknown, and the Unknowable

PubMed Central

Danovaro, Roberto; Company, Joan Batista; Corinaldesi, Cinzia; D'Onghia, Gianfranco; Galil, Bella; Gambi, Cristina; Gooday, Andrew J.; Lampadariou, Nikolaos; Luna, Gian Marco; Morigi, Caterina; Olu, Karine; Polymenakou, Paraskevi; Ramirez-Llodra, Eva; Sabbatini, Anna; Sardà, Francesc; Sibuet, Myriam; Tselepides, Anastasios

2010-01-01

Deep-sea ecosystems represent the largest biome of the global biosphere, but knowledge of their biodiversity is still scant. The Mediterranean basin has been proposed as a hot spot of terrestrial and coastal marine biodiversity but has been supposed to be impoverished of deep-sea species richness. We summarized all available information on benthic biodiversity (Prokaryotes, Foraminifera, Meiofauna, Macrofauna, and Megafauna) in different deep-sea ecosystems of the Mediterranean Sea (200 to more than 4,000 m depth), including open slopes, deep basins, canyons, cold seeps, seamounts, deep-water corals and deep-hypersaline anoxic basins and analyzed overall longitudinal and bathymetric patterns. We show that in contrast to what was expected from the sharp decrease in organic carbon fluxes and reduced faunal abundance, the deep-sea biodiversity of both the eastern and the western basins of the Mediterranean Sea is similarly high. All of the biodiversity components, except Bacteria and Archaea, displayed a decreasing pattern with increasing water depth, but to a different extent for each component. Unlike patterns observed for faunal abundance, highest negative values of the slopes of the biodiversity patterns were observed for Meiofauna, followed by Macrofauna and Megafauna. Comparison of the biodiversity associated with open slopes, deep basins, canyons, and deep-water corals showed that the deep basins were the least diverse. Rarefaction curves allowed us to estimate the expected number of species for each benthic component in different bathymetric ranges. A large fraction of exclusive species was associated with each specific habitat or ecosystem. Thus, each deep-sea ecosystem contributes significantly to overall biodiversity. From theoretical extrapolations we estimate that the overall deep-sea Mediterranean biodiversity (excluding prokaryotes) reaches approximately 2805 species of which about 66% is still undiscovered. Among the biotic components investigated (Prokaryotes excluded), most of the unknown species are within the phylum Nematoda, followed by Foraminifera, but an important fraction of macrofaunal and megafaunal species also remains unknown. Data reported here provide new insights into the patterns of biodiversity in the deep-sea Mediterranean and new clues for future investigations aimed at identifying the factors controlling and threatening deep-sea biodiversity. PMID:20689848

Deep-sea biodiversity in the Mediterranean Sea: the known, the unknown, and the unknowable.

PubMed

Danovaro, Roberto; Company, Joan Batista; Corinaldesi, Cinzia; D'Onghia, Gianfranco; Galil, Bella; Gambi, Cristina; Gooday, Andrew J; Lampadariou, Nikolaos; Luna, Gian Marco; Morigi, Caterina; Olu, Karine; Polymenakou, Paraskevi; Ramirez-Llodra, Eva; Sabbatini, Anna; Sardà, Francesc; Sibuet, Myriam; Tselepides, Anastasios

2010-08-02

Deep-sea ecosystems represent the largest biome of the global biosphere, but knowledge of their biodiversity is still scant. The Mediterranean basin has been proposed as a hot spot of terrestrial and coastal marine biodiversity but has been supposed to be impoverished of deep-sea species richness. We summarized all available information on benthic biodiversity (Prokaryotes, Foraminifera, Meiofauna, Macrofauna, and Megafauna) in different deep-sea ecosystems of the Mediterranean Sea (200 to more than 4,000 m depth), including open slopes, deep basins, canyons, cold seeps, seamounts, deep-water corals and deep-hypersaline anoxic basins and analyzed overall longitudinal and bathymetric patterns. We show that in contrast to what was expected from the sharp decrease in organic carbon fluxes and reduced faunal abundance, the deep-sea biodiversity of both the eastern and the western basins of the Mediterranean Sea is similarly high. All of the biodiversity components, except Bacteria and Archaea, displayed a decreasing pattern with increasing water depth, but to a different extent for each component. Unlike patterns observed for faunal abundance, highest negative values of the slopes of the biodiversity patterns were observed for Meiofauna, followed by Macrofauna and Megafauna. Comparison of the biodiversity associated with open slopes, deep basins, canyons, and deep-water corals showed that the deep basins were the least diverse. Rarefaction curves allowed us to estimate the expected number of species for each benthic component in different bathymetric ranges. A large fraction of exclusive species was associated with each specific habitat or ecosystem. Thus, each deep-sea ecosystem contributes significantly to overall biodiversity. From theoretical extrapolations we estimate that the overall deep-sea Mediterranean biodiversity (excluding prokaryotes) reaches approximately 2805 species of which about 66% is still undiscovered. Among the biotic components investigated (Prokaryotes excluded), most of the unknown species are within the phylum Nematoda, followed by Foraminifera, but an important fraction of macrofaunal and megafaunal species also remains unknown. Data reported here provide new insights into the patterns of biodiversity in the deep-sea Mediterranean and new clues for future investigations aimed at identifying the factors controlling and threatening deep-sea biodiversity.

An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications.

PubMed

Park, Seong-Wook; Park, Junyoung; Bong, Kyeongryeol; Shin, Dongjoo; Lee, Jinmook; Choi, Sungpill; Yoo, Hoi-Jun

2015-12-01

Deep Learning algorithm is widely used for various pattern recognition applications such as text recognition, object recognition and action recognition because of its best-in-class recognition accuracy compared to hand-crafted algorithm and shallow learning based algorithms. Long learning time caused by its complex structure, however, limits its usage only in high-cost servers or many-core GPU platforms so far. On the other hand, the demand on customized pattern recognition within personal devices will grow gradually as more deep learning applications will be developed. This paper presents a SoC implementation to enable deep learning applications to run with low cost platforms such as mobile or portable devices. Different from conventional works which have adopted massively-parallel architecture, this work adopts task-flexible architecture and exploits multiple parallelism to cover complex functions of convolutional deep belief network which is one of popular deep learning/inference algorithms. In this paper, we implement the most energy-efficient deep learning and inference processor for wearable system. The implemented 2.5 mm × 4.0 mm deep learning/inference processor is fabricated using 65 nm 8-metal CMOS technology for a battery-powered platform with real-time deep inference and deep learning operation. It consumes 185 mW average power, and 213.1 mW peak power at 200 MHz operating frequency and 1.2 V supply voltage. It achieves 411.3 GOPS peak performance and 1.93 TOPS/W energy efficiency, which is 2.07× higher than the state-of-the-art.

Evidence for Extending the Duration of Chemoprophylaxis following Free Flap Harvest from the Lower Extremity: Prospective Screening for Deep Venous Thrombosis.

PubMed

Rau, Aline S; Harry, Brian L; Leem, Ted H; Song, John I; Deleyiannis, Frederic W-B

2016-08-01

The purpose of this study was to investigate the incidence of symptomatic and asymptomatic deep venous thrombosis in patients undergoing harvest of a free flap from the lower extremity who were receiving standard chemoprophylaxis while hospitalized. A retrospective review of 65 consecutive patients undergoing surgery between 2011 and 2013 was performed to determine the incidence of symptomatic deep venous thrombosis. These patients were screened for deep venous thrombosis based on development of symptoms. Prospective evaluation of a similar consecutive population of 37 patients between 2014 and 2015 was then performed to determine the incidence of asymptomatic deep venous thrombosis. These patients underwent routine duplex ultrasonography of both legs at postoperative weeks 1 and 4. Symptomatic deep venous thrombosis occurred in 2.9 percent of all patients. In the prospective cohort, 8.1 percent of the patients were found to have an acute deep venous thrombosis by postoperative week 1. At postoperative week 4, 16.7 percent of the patients developed a new, acute deep venous thrombosis. The estimated costs of screening and treating deep venous thrombosis in the retrospective group and the prospective group were $222 and $2259, respectively. The cost of routine chemoprophylaxis without duplex screening for an additional 14 days after discharge was $125 per patient. The rate of asymptomatic deep venous thrombosis may be much higher than previously appreciated in this population of very high-risk patients, especially during the 2 weeks after discharge. Extending the duration of chemoprophylaxis to 4 weeks after surgery may be warranted. Therapeutic, IV.

Long Range Effect of The M7.8 April 2015 Nepal Earth Quake on the Deep Groudwater Outflow in a Thousand-Mile-Away Geothermal Field in Southern China's Guangdong

NASA Astrophysics Data System (ADS)

Lu, G.; Yu, S.; Xu, F.; Wang, X.; Yan, K.; Yuen, D. A.

2015-12-01

Deep ground waters sustain high temperature and pressure and are susceptible to impact from an earthquake. How an earthquake would have been associated with long-range effect on geological environment of deep groundwater is a question of interest to the scientific community and general public. The massive Richter 8.1 Nepal Earthquake (on April 25, 2015) provided a rare opportunity to test the response of deep groundwater systems. Deep ground waters at elevated temperature would naturally flow to ground surface along preferential flow path such as a deep fault, forming geothermal water flows. Geothermal water flows are susceptible to stress variation and can reflect the physical conditions of supercritical hot water kilometers deep down inside the crust. This paper introduces the monitoring work on the outflow in Xijiang Geothermal Field of Xinyi City, Guangdong Province in southern China. The geothermal field is one of typical geothermal fields with deep faults in Guangdong. The geothermal spring has characteristic daily variation of up to 72% in flow rate, which results from being associated with a north-south run deep fault susceptible to earthquake event. We use year-long monitoring data to illustrate how the Nepal earthquake would have affected the flows at the field site over 2.5 thousand kilometers away. The irregularity of flow is judged by deviation from otherwise good correlation of geothermal spring flow with solid earth tidal waves. This work could potentially provide the basis for further study of deep groundwater systems and insight to earthquake prediction.

Root growth and water relations of oak and birch seedlings.

PubMed

Osonubi, O; Davies, W J

1981-01-01

First year seedlings of English oak (Quercus Cobur) and silver birch (Betula pendula) were subjected to pressure-volume analysis to investigate the water potential components and cell wall properties of single leaves. It was hoped that this rapid-drying technique would differentiate between reductions in plant solute potential resulting from dehydration and the effects of solute accumulation.Comparison of results from these experiments with those of slow drying treatments (over a number of days) with plants growing in tubes of soil, indicated that some solute accumulation may have occurred in drying oak leaves. High leaf turgor and leaf conductance were maintained for a significant period of the drying cycle. Roots of well-watered oak plants extended deep into the soil profile, and possibly as a result of solute regulation and therefore turgor maintenance, root growth of unwatered plants was greater than that of their well-watered counterparts. This was particularly the case deep in the profile. As a result of deep root penetration, water deep in the soil core was used by oak plants to maintain plant turgor, and quite low soil water potentials were recorded in the lower soil segments.Root growth of well-watered birch seedlings was prolific but roots of both well-watered and unwatered plants were restricted to the upper part of the profile. Root growth of unwatered plants was reduced despite the existence of high soil water potentials deep in the profile. Shallow rooting birch seedlings were unable to use this water.Pressure-volume analysis indicated that significant reductions of water potential, which are required for water uptake from drying soil, would occur in oak with only a small reduction in plant water content compared to the situation in birch. This was a result of the low solute potential in oak leaves combined with a high modulus of elasticity of cell walls. Deep rooting of oak seedlings, combined with these characteristics, which will be particularly important when soil deep in the profile begins to dry, mean that this species may be comparatively successful when growing on dry sites.

Observation of events with an energetic forward neutron in deep inelastic scattering at HERA

NASA Astrophysics Data System (ADS)

Derrick, M.; Krakauer, D.; Magill, S.; Mikunas, D.; Musgrave, B.; Okrasinski, J. R.; Repond, J.; Stanek, R.; Talaga, R. L.; Zhang, H.; Mattingly, M. C. K.; Bari, G.; Basile, M.; Bellagamba, L.; Boscherini, D.; Bruni, A.; Bruni, G.; Bruni, P.; Cara Romeo, G.; Castellini, G.; Cifarelli, L.; Cindolo, F.; Contin, A.; Corradi, M.; Gialas, I.; Giusti, P.; Iacobucci, G.; Laurenti, G.; Levi, G.; Margotti, A.; Massam, T.; Nania, R.; Palmonari, F.; Polini, A.; Sartorelli, G.; Zamora Garcia, Y.; Zichichi, A.; Amelung, C.; Bornheim, A.; Crittenden, J.; Deffner, R.; Doeker, T.; Eckert, M.; Feld, L.; Frey, A.; Geerts, M.; Grothe, M.; Hartmann, H.; Heinloth, K.; Heinz, L.; Hilger, E.; Jakob, H.-P.; Katz, U. F.; Mengel, S.; Paul, E.; Pfeiffer, M.; Rembser, Ch.; Schramm, D.; Stamm, J.; Wedemeyer, R.; Campbell-Robson, S.; Cassidy, A.; Cottingham, W. N.; Dyce, N.; Foster, B.; George, S.; Hayes, M. E.; Heath, G. P.; Heath, H. F.; Piccioni, D.; Roff, D. G.; Tapper, R. J.; Yoshida, R.; Arneodo, M.; Ayad, R.; Capua, M.; Garfagnini, A.; Iannotti, L.; Schioppa, M.; Susinno, G.; Caldwell, A.; Cartiglia, N.; Jing, Z.; Liu, W.; Parsons, J. A.; Titz, S.; Sciulli, F.; Straub, P. B.; Wai, L.; Yang, S.; Zhu, Q.; Borzemski, P.; Chwastowski, J.; Eskreys, A.; Jakubowski, Z.; Przybycień, M. B.; Zachara, M.; Zawiejski, L.; Adamczyk, L.; Bednarek, B.; Jeleń, K.; Kisielewska, D.; Kowalski, T.; Przybycień, M.; Rulikowska-Zarȩbska, E.; Suszycki, L.; Zajaç, J.; Duliński, Z.; Kotański, A.; Abbiendi, G.; Bauerdick, L. A. T.; Behrens, U.; Beier, H.; Bienlein, J. K.; Cases, G.; Deppe, O.; Desler, K.; Drews, G.; Flasiński, M.; Gilkinson, D. J.; Glasman, C.; Göttlicher, P.; Große-Knetter, J.; Haas, T.; Hain, W.; Hasell, D.; Heßling, H.; Iga, Y.; Johnson, K. F.; Joos, P.; Kasemann, M.; Klanner, R.; Koch, W.; Kötz, U.; Kowalski, H.; Labs, J.; Ladage, A.; Löhr, B.; Löwe, M.; Lüke, D.; Mainusch, J.; Mańczak, O.; Milewski, J.; Monteiro, T.; Ng, J. S. T.; Notz, D.; Ohrenberg, K.; Poitrzkowski, K.; Roco, M.; Rohde, M.; Roldán, J.; Schneekloth, U.; Schulz, W.; Selonke, F.; Surrow, B.; Voß, T.; Westphal, D.; Wolf, G.; Wollmer, U.; Youngman, C.; Zeuner, W.; Grabosch, H. J.; Kharchilava, A.; Mari, S. M.; Meyer, A.; Schlenstedt, S.; Wulff, N.; Barbagli, G.; Gallo, E.; Pelfer, P.; Maccarrone, G.; De Pasquale, S.; Votano, L.; Bamberger, A.; Eisenhardt, S.; Trefzger, T.; Wölfle, S.; Bromley, J. T.; Brook, N. H.; Bussey, P. J.; Doyle, A. T.; Saxon, D. H.; Sinclair, L. E.; Utley, M. L.; Wilson, A. S.; Dannemann, A.; Holm, U.; Horstmann, D.; Sinkus, R.; Wick, K.; Burow, B. D.; Hagge, L.; Lohrmann, E.; Poelz, G.; Schott, W.; Zetsche, F.; Bacon, T. C.; Brümmer, N.; Butterworth, I.; Harris, V. L.; Howell, G.; Hung, B. H. Y.; Lamberti, L.; Long, K. R.; Miller, D. B.; Pavel, N.; Prinias, A.; Sedgbeer, J. K.; Sideris, D.; Whitfield, A. F.; Mallik, U.; Wang, M. Z.; Wang, S. M.; Wu, J. T.; Cloth, P.; Filges, D.; An, S. H.; Cho, G. H.; Ko, B. J.; Lee, S. B.; Nam, S. W.; Park, H. S.; Park, S. K.; Kartik, S.; Kim, H.-J.; McNeil, R. R.; Metcalf, W.; Nadendla, V. K.; Barreiro, F.; Fernandez, J. P.; Graciani, R.; Hernández, J. M.; Hervás, L.; Labarga, L.; Martinez, M.; del Peso, J.; Puga, J.; Terron, J.; de Trocóniz, J. F.; Corriveau, F.; Hanna, D. S.; Hartmann, J.; Hung, L. W.; Lim, J. N.; Matthews, C. G.; Patel, P. M.; Riveline, M.; Stairs, D. G.; St-Laurent, M.; Ullmann, R.; Zacek, G.; Tsurugai, T.; Bashkirov, V.; Dolgoshein, B. A.; Stifutkin, A.; Bashindzhagyan, G. L.; Ermolov, P. F.; Gladilin, L. K.; Golubkov, Yu. A.; Kobrin, V. D.; Korzhavina, I. A.; Kuzmin, V. A.; Lukina, O. Yu.; Proskuryakov, A. S.; Savin, A. A.; Shcheglova, L. M.; Solomin, A. N.; Zotov, N. P.; Botje, M.; Chlebana, F.; Engelen, J.; de Kamps, M.; Kooijman, P.; Kruse, A.; van Sighem, A.; Tiecke, H.; Verkerke, W.; Vossebeld, J.; Vreeswijk, M.; Wiggers, L.; de Wolf, E.; van Woudenberg, R.; Acosta, D.; Bylsma, B.; Durkin, L. S.; Gilmore, J.; Li, C.; Ling, T. Y.; Nylander, P.; Park, I. H.; Romanowski, T. A.; Bailey, D. S.; Cashmore, R. J.; Cooper-Sarkar, A. M.; Devenish, R. C. E.; Harnew, N.; Lancaster, M.; Lindemann, L.; McFall, J. D.; Nath, C.; Noyes, V. A.; Quadt, A.; Tickner, J. R.; Uijterwaal, H.; Walczak, R.; Waters, D. S.; Wilson, F. F.; Yip, T.; Bertolin, A.; Brugnera, R.; Carlin, R.; Dal Corso, F.; De Giorgi, M.; Dosselli, U.; Limentani, S.; Morandin, M.; Posocco, M.; Stanco, L.; Stroili, R.; Voci, C.; Zuin, F.; Bulmahn, J.; Feild, R. G.; Oh, B. Y.; Whitmore, J. J.; D'Agostini, G.; Marini, G.; Nigro, A.; Tassi, E.; Hart, J. C.; McCubbin, N. A.; Shah, T. P.; Barberis, E.; Dubbs, T.; Heusch, C.; Van Hook, M.; Lockman, W.; Rahn, J. T.; Sadrozinski, H. F.-W.; Seiden, A.; Williams, D. C.; Biltzinger, J.; Seifert, R. J.; Schwarzer, O.; Walenta, A. H.; Zech, G.; Abramowicz, H.; Briskin, G.; Dagan, S.; Levy, A.; Fleck, J. I.; Inuzuka, M.; Ishii, T.; Kuze, M.; Mine, S.; Nakao, M.; Suzuki, I.; Tokushuku, K.; Umemori, K.; Yamada, S.; Yamazaki, Y.; Chiba, M.; Hamatsu, R.; Hirose, T.; Homma, K.; Kitamura, S.; Matsushita, T.; Yamauchi, K.; Cirio, R.; Costa, M.; Ferrero, M. I.; Maselli, S.; Peroni, C.; Sacchi, R.; Solano, A.; Staiano, A.; Dardo, M.; Bailey, D. C.; Benard, F.; Brkic, M.; Fagerstroem, C.-P.; Hartner, G. F.; Joo, K. K.; Levman, G. M.; Martin, J. F.; Orr, R. S.; Polenz, S.; Sampson, C. R.; Simmons, D.; Teuscher, R. J.; Butterworth, J. M.; Catterall, C. D.; Jones, T. W.; Kaziewicz, P. B.; Lane, J. B.; Saunders, R. L.; Shulman, J.; Sutton, M. R.; Lu, B.; Mo, L. W.; Bogusz, W.; Ciborowski, J.; Gajewski, J.; Grzelak, G.; Kasprzak, M.; Krzyżanowski, M.; Muchorowski, K.; Nowak, R. J.; Pawlak, J. M.; Tymieniecka, T.; Wróblewski, A. K.; Zakrzewski, J. A.; Żarnecki, A. F.; Adamus, M.; Coldewey, C.; Eisenberg, Y.; Hochman, D.; Karshon, U.; Revel, D.; Zer-Zion, D.; Badgett, W. F.; Breitweg, J.; Chapin, D.; Cross, R.; Dasu, S.; Foudas, C.; Loveless, R. J.; Mattingly, S.; Reeder, D. D.; Silverstein, S.; Smith, W. H.; Vaiciulis, A.; Wodarczyk, M.; Bhadra, S.; Cardy, M. L.; Fagerstroem, C.-P.; Frisken, W. R.; Furutani, K. M.; Khakzad, M.; Murray, W. N.; Schmidke, W. B.; ZEUS Collaboration

1996-02-01

In deep inelastic neutral current scattering of positrons and protons at the center of mass energy of 300 GeV, we observe, with the ZEUS detector, events with a high energy neutron produced at very small scattering angles with respect to the proton direction. The events constitute a fixed fraction of the deep inelastic, neutral current event sample independent of Bjorken x and Q2 in the range 3 · 10 -4 < xBJ < 6 · 10 -3 and 10 < Q2 < 100 GeV 2.

A Parameter-Free Dynamic Alternative to Hyper-Viscosity for Coupled Transport Equations: Application to the Simulation of 3D Squall Lines Using Spectral Elements

DTIC Science & Technology

2015-06-04

that involve physics coupling with phase change in the simulation of 3D deep convection. We show that the VMS+DC approach is a robust technique that can...of 3D deep convection. We show that the VMS+DC approach is a robust technique that can damp the high order modes characterizing the spectral element...of Spectral Elements, Deep Convection, Kessler Microphysics Preprint J. Comput. Phys. 283 (2015) 360-373 June 4, 2015 1. Introduction In the field of

Distribution of Linearly Polarized Gluons and Elliptic Azimuthal Anisotropy in Deep Inelastic Scattering Dijet Production at High Energy

DOE PAGES

Dumitru, Adrian; Lappi, Tuomas; Skokov, Vladimir

2015-12-17

In this study, we determine the distribution of linearly polarized gluons of a dense target at small x by solving the Balitsky–Jalilian-Marian–Iancu–McLerran–Weigert–Leonidov–Kovner rapidity evolution equations. From these solutions, we estimate the amplitude of cos2Φ azimuthal asymmetries in deep inelastic scattering dijet production at high energies. We find sizable long-range in rapidity azimuthal asymmetries with a magnitude in the range of v 2=~10%.

In vivo multiphoton microscopy beyond 1 mm in the brain

NASA Astrophysics Data System (ADS)

Miller, David R.; Medina, Flor A.; Hassan, Ahmed; Perillo, Evan P.; Hagan, Kristen; Kazmi, S. M. Shams; Zemelman, Boris V.; Dunn, Andrew K.

2017-02-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. We demonstrate an imaging depth of 1,200 μm in vasculature and 1,160 μm in neurons. We also demonstrate deep-tissue imaging using Indocyanine Green (ICG), which is FDA approved and a promising route to translate multiphoton microscopy to human applications.

Deep Ultraviolet Light Emitters Based on (Al,Ga)N/GaN Semiconductor Heterostructures

NASA Astrophysics Data System (ADS)

Liang, Yu-Han

Deep ultraviolet (UV) light sources are useful in a number of applications that include sterilization, medical diagnostics, as well as chemical and biological identification. However, state-of-the-art deep UV light-emitting diodes and lasers made from semiconductors still suffer from low external quantum efficiency and low output powers. These limitations make them costly and ineffective in a wide range of applications. Deep UV sources such as lasers that currently exist are prohibitively bulky, complicated, and expensive. This is typically because they are constituted of an assemblage of two to three other lasers in tandem to facilitate sequential harmonic generation that ultimately results in the desired deep UV wavelength. For semiconductor-based deep UV sources, the most challenging difficulty has been finding ways to optimally dope the (Al,Ga)N/GaN heterostructures essential for UV-C light sources. It has proven to be very difficult to achieve high free carrier concentrations and low resistivities in high-aluminum-containing III-nitrides. As a result, p-type doped aluminum-free III-nitrides are employed as the p-type contact layers in UV light-emitting diode structures. However, because of impedance-mismatch issues, light extraction from the device and consequently the overall external quantum efficiency is drastically reduced. This problem is compounded with high losses and low gain when one tries to make UV nitride lasers. In this thesis, we provide a robust and reproducible approach to resolving most of these challenges. By using a liquid-metal-enabled growth mode in a plasma-assisted molecular beam epitaxy process, we show that highly-doped aluminum containing III-nitride films can be achieved. This growth mode is driven by kinetics. Using this approach, we have been able to achieve extremely high p-type and n-type doping in (Al,Ga)N films with high aluminum content. By incorporating a very high density of Mg atoms in (Al,Ga)N films, we have been able to show, by temperature-dependent photoluminescence, that the activation energy of the acceptors is substantially lower, thus allowing a higher hole concentration than usual to be available for conduction. It is believed that the lower activation energy is a result of an impurity band tail induced by the high Mg concentration. The successful p-type doping of high aluminum-content (Al,Ga)N has allowed us to demonstrate operation of deep ultraviolet LEDs emitting at 274 nm. This achievement paves the way for making lasers that emit in the UV-C region of the spectrum. In this thesis, we performed preliminary work on using our structures to make UV-C lasers based on photonic crystal nanocavity structures. The nanocavity laser structures show that the threshold optical pumping power necessary to reach lasing is much lower than in conventional edge-emitting lasers. Furthermore, the photonic crystal nanocavity structure has a small mode volume and does not need mirrors for optical feedback. These advantages significantly reduce material loss and eliminate mirror loss. This structure therefore potentially opens the door to achieving efficient and compact lasers in the UV-C region of the spectrum.

FAR-TECH's Nanoparticle Plasma Jet System and its Application to Disruptions, Deep Fueling, and Diagnostics

NASA Astrophysics Data System (ADS)

Thompson, J. R.; Bogatu, I. N.; Galkin, S. A.; Kim, J. S.

2012-10-01

Hyper-velocity plasma jets have potential applications in tokamaks for disruption mitigation, deep fueling and diagnostics. Pulsed power based solid-state sources and plasma accelerators offer advantages of rapid response and mass delivery at high velocities. Fast response is critical for some disruption mitigation scenario needs, while high velocity is especially important for penetration into tokamak plasma and its confining magnetic field, as in the case of deep fueling. FAR-TECH is developing the capability of producing large-mass hyper-velocity plasma jets. The prototype solid-state source has produced: 1) >8.4 mg of H2 gas only, and 2) >25 mg of H2 and >180 mg of C60 in a H2/C60 gas mixture. Using a coaxial plasma gun coupled to the source, we have successfully demonstrated the acceleration of composite H/C60 plasma jets, with momentum as high as 0.6 g.km/s, and containing an estimated C60 mass of ˜75 mg. We present the status of FAR-TECH's nanoparticle plasma jet system and discuss its application to disruptions, deep fueling, and diagnostics. A new TiH2/C60 solid-state source capable of generating significantly higher quantities of H2 and C60 in <0.5 ms will be discussed.

Water mass dynamics shape Ross Sea protist communities in mesopelagic and bathypelagic layers

NASA Astrophysics Data System (ADS)

Zoccarato, Luca; Pallavicini, Alberto; Cerino, Federica; Fonda Umani, Serena; Celussi, Mauro

2016-12-01

Deep-sea environments host the largest pool of microbes and represent the last largely unexplored and poorly known ecosystems on Earth. The Ross Sea is characterized by unique oceanographic dynamics and harbors several water masses deeply involved in cooling and ventilation of deep oceans. In this study the V9 region of the 18S rDNA was targeted and sequenced with the Ion Torrent high-throughput sequencing technology to unveil differences in protist communities (>2 μm) correlated with biogeochemical properties of the water masses. The analyzed samples were significantly different in terms of environmental parameters and community composition outlining significant structuring effects of temperature and salinity. Overall, Alveolata (especially Dinophyta), Stramenopiles and Excavata groups dominated mesopelagic and bathypelagic layers, and protist communities were shaped according to the biogeochemistry of the water masses (advection effect and mixing events). Newly-formed High Salinity Shelf Water (HSSW) was characterized by high relative abundance of phototrophic organisms that bloom at the surface during the austral summer. Oxygen-depleted Circumpolar Deep Water (CDW) showed higher abundance of Excavata, common bacterivores in deep water masses. At the shelf-break, Antarctic Bottom Water (AABW), formed by the entrainment of shelf waters in CDW, maintained the eukaryotic genetic signature typical of both parental water masses.

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

PubMed

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

Experimental investigation of the stability of Fe-rich carbonates in the lower mantle

NASA Astrophysics Data System (ADS)

Boulard, E.; Menguy, N.; Auzende, A.; Benzerara, K.; Bureau, H.; Antonangeli, D.; Corgne, A.; Morard, G.; Siebert, J.; Perrillat, J.; Guyot, F. J.; Fiquet, G.

2011-12-01

Carbonates are the main C-bearing minerals that are transported deep in the Earth's mantle via subduction of the oceanic lithosphere [1]. The fate of carbonates at mantle conditions plays a key role in the deep carbon cycle. Decarbonation, melting or reduction of carbonates will affect the extent and the way carbon is recycled into the deep Earth. To clarify the fate of carbonates in the deep mantle, high-pressure high-temperature experiments were carried out up to 105 GPa and 2850 K on oxide assemblages of (Mg,Fe)O + CO2. The presence of Fe(II) in starting materials induces redox reactions from which Fe(II) is oxidized and a part of the carbon is reduced. This leads to an assemblage of magnetite, diamonds, and carbonates or, pressure depending, their newly discovered Fe(III)-bearing high-pressure polymorphs based on a silicate-like chemistry with tetrahedrally coordinated carbon [2]. Our results show the possibility for carbon to be recycled in the lowermost mantle and provide evidence of a possible coexistence of reduced and oxidized carbon at lower mantle conditions. [1] Sleep, N. H., and K. Zahnle (2001) J. Geophys. Res.-Planets 106(E1), 1373-1399. [2] Boulard et al. (2011) PNAS, 108, 5184-5187.

Biogeography and ecology of the rare and abundant microbial lineages in deep-sea hydrothermal vents.

PubMed

Anderson, Rika E; Sogin, Mitchell L; Baross, John A

2015-01-01

Environmental gradients generate countless ecological niches in deep-sea hydrothermal vent systems, which foster diverse microbial communities. The majority of distinct microbial lineages in these communities occur in very low abundance. However, the ecological role and distribution of rare and abundant lineages, particularly in deep, hot subsurface environments, remain unclear. Here, we use 16S rRNA tag sequencing to describe biogeographic patterning and microbial community structure of both rare and abundant archaea and bacteria in hydrothermal vent systems. We show that while rare archaeal lineages and almost all bacterial lineages displayed geographically restricted community structuring patterns, the abundant lineages of archaeal communities displayed a much more cosmopolitan distribution. Finally, analysis of one high-volume, high-temperature fluid sample representative of the deep hot biosphere described a unique microbial community that differed from microbial populations in diffuse flow fluid or sulfide samples, yet the rare thermophilic archaeal groups showed similarities to those that occur in sulfides. These results suggest that while most archaeal and bacterial lineages in vents are rare and display a highly regional distribution, a small percentage of lineages, particularly within the archaeal domain, are successful at widespread dispersal and colonization. © FEMS 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Compact Deep-Space Optical Communications Transceiver

NASA Technical Reports Server (NTRS)

Roberts, W. Thomas; Charles, Jeffrey R.

2009-01-01

Deep space optical communication transceivers must be very efficient receivers and transmitters of optical communication signals. For deep space missions, communication systems require high performance well beyond the scope of mere power efficiency, demanding maximum performance in relation to the precious and limited mass, volume, and power allocated. This paper describes the opto-mechanical design of a compact, efficient, functional brassboard deep space transceiver that is capable of achieving megabyte-per-second rates at Mars ranges. The special features embodied to enhance the system operability and functionality, and to reduce the mass and volume of the system are detailed. System tests and performance characteristics are described in detail. Finally, lessons learned in the implementation of the brassboard design and suggestions for improvements appropriate for a flight prototype are covered.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

PubMed

Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

2016-05-01

Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson’s disease

PubMed Central

Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir

2016-01-01

Abstract Chronic dopamine depletion in Parkinson’s disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus–cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment. PMID:27017189

1.5 My benthic foraminiferal B/Ca record of carbonate chemistry in the deep Atlantic: Implications for ocean alkalinity and atmospheric CO2

NASA Astrophysics Data System (ADS)

Rosenthal, Y.; Sosdian, S. M.; Toggweiler, J. R.

2017-12-01

Most hypotheses to explain glacial-interglacial changes in atmospheric CO2 invoke shifts in ocean alkalinity explain roughly half the reduction in glacial CO2 via CaCO3 compensatory mechanism. It follows that changes in CaCO3 burial occur in response to an increase in deep ocean respired carbon content. To date our understanding of this process comes from benthic carbon isotope and %CaCO3 records. However, to understand the nature of the ocean's buffering capacity and its role in modulating pCO2, orbitally resolved reconstructions of the deep ocean carbonate system parameters are necessary. Here we present a 1.5 Myr orbitally resolved deep ocean calcite saturation record (ΔCO32-) derived from benthic foraminiferal B/Ca ratios in the North Atlantic. Glacial B/Ca values decline across the mid-Pleistocene transition (MPT) suggesting increased sequestration of carbon in the deep Atlantic. The magnitude, timing, and structure of deep Atlantic Ocean ΔCO32- and %CaCO3 cycles contrast with the small amplitude, anti-phased swings in IndoPacific ΔCO32- and %CaCO3 during the mid-to-late Pleistocene. Increasing corrosivity of the deep Atlantic causes the locus of CaCO3 burial to shift into the equatorial Pacific where the flux of CaCO3 to the seafloor is high enough to establish and maintain a new "hot spot". We propose that the CO32- in the deep IndoPacific rises in response to the same mechanism that keeps the CO32- in the deep Atlantic low and the atmospheric CO2 low. The increase in interglacial atmospheric pCO2 levels following the Mid-Brunhes event ( 400ka) are associated with increased G/IG ΔCO3 amplitude, expressed by a decrease in the glacial ΔCO32- values. We propose the low persistent ΔCO32- levels at Marine Isotope Stage (MIS) 12 set the stage for the high pCO2 levels at MIS 11 via an increase in whole ocean alkalinity followed by enhanced CaCO3 preservation. Based on this, we suggest that the development of classic (`anticorrelated') CaCO3 patterns was driven by increased stratification and worsening ventilation in the deep Atlantic across the MPT.

Non-Motor Symptom Burdens Are Not Associated with Iron Accumulation in Early Parkinson's Disease: a Quantitative Susceptibility Mapping Study.

PubMed

Shin, Chaewon; Lee, Seon; Lee, Jee Young; Rhim, Jung Hyo; Park, Sun Won

2018-03-26

Quantitative susceptibility mapping (QSM) has been used to measure iron accumulation in the deep nuclei of patients with Parkinson's disease (PD). This study examined the relationship between non-motor symptoms (NMSs) and iron accumulation in the deep nuclei of patients with PD. The QSM data were acquired from 3-Tesla magnetic resonance imaging (MRI) in 29 patients with early PD and 19 normal controls. The Korean version of the NMS scale (K-NMSS) was used for evaluation of NMSs in patients. The patients were divided into high NMS and low NMS groups. The region-of-interest analyses were performed in the following deep nuclei: red nucleus, substantia nigra pars compacta, substantia nigra pars reticulata, dentate nucleus, globus pallidus, putamen, and head of the caudate nucleus. Thirteen patients had high NMS scores (total K-NMSS score, mean = 32.1), and 16 had low NMS scores (10.6). The QSM values in the deep were not different among the patients with high NMS scores, low NMS scores, and controls. The QSM values were not correlated linearly with K-NMSS total score after adjusting the age at acquisition of brain MRI. The study demonstrated that the NMS burdens are not associated with iron accumulation in the deep nuclei of patients with PD. These results suggest that future neuroimaging studies on the pathology of NMSs in PD should use more specific and detailed clinical tools and recruit PD patients with severe NMSs. © 2018 The Korean Academy of Medical Sciences.

Polymer dots enable deep in vivo multiphoton fluorescence imaging of cerebrovascular architecture

NASA Astrophysics Data System (ADS)

Hassan, Ahmed M.; Wu, Xu; Jarrett, Jeremy W.; Xu, Shihan; Miller, David R.; Yu, Jiangbo; Perillo, Evan P.; Liu, Yen-Liang; Chiu, Daniel T.; Yeh, Hsin-Chih; Dunn, Andrew K.

2018-02-01

Deep in vivo imaging of vasculature requires small, bright, and photostable fluorophores suitable for multiphoton microscopy (MPM). Although semiconducting polymer dots (pdots) are an emerging class of highly fluorescent contrast agents with favorable advantages for the next generation of in vivo imaging, their use for deep multiphoton imaging has never before been demonstrated. Here we characterize the multiphoton properties of three pdot variants (CNPPV, PFBT, and PFPV) and demonstrate deep imaging of cortical microvasculature in C57 mice. Specifically, we measure the two- versus three-photon power dependence of these pdots and observe a clear three-photon excitation signature at wavelengths longer than 1300 nm, and a transition from two-photon to three-photon excitation within a 1060 - 1300 nm excitation range. Furthermore, we show that pdots enable in vivo two-photon imaging of cerebrovascular architecture in mice up to 850 μm beneath the pial surface using 800 nm excitation. In contrast with traditional multiphoton probes, we also demonstrate that the broad multiphoton absorption spectrum of pdots permits imaging at longer wavelengths (λex = 1,060 and 1225 nm). These wavelengths approach an ideal biological imaging wavelength near 1,300 nm and confer compatibility with a high-power ytterbium-fiber laser and a high pulse energy optical parametric amplifier, resulting in substantial improvements in signal-to-background ratio (>3.5-fold) and greater cortical imaging depths of 900 μm and 1300 μm. Ultimately, pdots are a versatile tool for MPM due to their extraordinary brightness and broad absorption, which will undoubtedly unlock the ability to interrogate deep structures in vivo.