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  • 1
    Publication Date: 2014-09-13
    Description: In its largest outbreak, Ebola virus disease is spreading through Guinea, Liberia, Sierra Leone, and Nigeria. We sequenced 99 Ebola virus genomes from 78 patients in Sierra Leone to ~2000x coverage. We observed a rapid accumulation of interhost and intrahost genetic variation, allowing us to characterize patterns of viral transmission over the initial weeks of the epidemic. This West African variant likely diverged from central African lineages around 2004, crossed from Guinea to Sierra Leone in May 2014, and has exhibited sustained human-to-human transmission subsequently, with no evidence of additional zoonotic sources. Because many of the mutations alter protein sequences and other biologically meaningful targets, they should be monitored for impact on diagnostics, vaccines, and therapies critical to outbreak response.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431643/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431643/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Gire, Stephen K -- Goba, Augustine -- Andersen, Kristian G -- Sealfon, Rachel S G -- Park, Daniel J -- Kanneh, Lansana -- Jalloh, Simbirie -- Momoh, Mambu -- Fullah, Mohamed -- Dudas, Gytis -- Wohl, Shirlee -- Moses, Lina M -- Yozwiak, Nathan L -- Winnicki, Sarah -- Matranga, Christian B -- Malboeuf, Christine M -- Qu, James -- Gladden, Adrianne D -- Schaffner, Stephen F -- Yang, Xiao -- Jiang, Pan-Pan -- Nekoui, Mahan -- Colubri, Andres -- Coomber, Moinya Ruth -- Fonnie, Mbalu -- Moigboi, Alex -- Gbakie, Michael -- Kamara, Fatima K -- Tucker, Veronica -- Konuwa, Edwin -- Saffa, Sidiki -- Sellu, Josephine -- Jalloh, Abdul Azziz -- Kovoma, Alice -- Koninga, James -- Mustapha, Ibrahim -- Kargbo, Kandeh -- Foday, Momoh -- Yillah, Mohamed -- Kanneh, Franklyn -- Robert, Willie -- Massally, James L B -- Chapman, Sinead B -- Bochicchio, James -- Murphy, Cheryl -- Nusbaum, Chad -- Young, Sarah -- Birren, Bruce W -- Grant, Donald S -- Scheiffelin, John S -- Lander, Eric S -- Happi, Christian -- Gevao, Sahr M -- Gnirke, Andreas -- Rambaut, Andrew -- Garry, Robert F -- Khan, S Humarr -- Sabeti, Pardis C -- 095831/Wellcome Trust/United Kingdom -- 1DP2OD006514-01/OD/NIH HHS/ -- 1U01HG007480-01/HG/NHGRI NIH HHS/ -- 260864/European Research Council/International -- DP2 OD006514/OD/NIH HHS/ -- GM080177/GM/NIGMS NIH HHS/ -- HHSN272200900049C/AI/NIAID NIH HHS/ -- HHSN272200900049C/PHS HHS/ -- T32 GM080177/GM/NIGMS NIH HHS/ -- U01 HG007480/HG/NHGRI NIH HHS/ -- U19 AI110818/AI/NIAID NIH HHS/ -- U19 AI115589/AI/NIAID NIH HHS/ -- New York, N.Y. -- Science. 2014 Sep 12;345(6202):1369-72. doi: 10.1126/science.1259657. Epub 2014 Aug 28.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. ; Kenema Government Hospital, Kenema, Sierra Leone. andersen@broadinstitute.org augstgoba@yahoo.com psabeti@oeb.harvard.edu. ; Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. andersen@broadinstitute.org augstgoba@yahoo.com psabeti@oeb.harvard.edu. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. ; Kenema Government Hospital, Kenema, Sierra Leone. ; Kenema Government Hospital, Kenema, Sierra Leone. Eastern Polytechnic College, Kenema, Sierra Leone. ; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. ; Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Systems Biology, Harvard Medical School, Boston, MA 02115, USA. ; Tulane University Medical Center, New Orleans, LA 70112, USA. ; Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Systems Biology, Harvard Medical School, Boston, MA 02115, USA. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. ; Redeemer's University, Ogun State, Nigeria. ; University of Sierra Leone, Freetown, Sierra Leone. ; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. Fogarty International Center, National Institutes of Health, Bethesda, MD 20892, USA. Centre for Immunity, Infection and Evolution, University of Edinburgh, Edinburgh EH9 3JT, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25214632" target="_blank"〉PubMed〈/a〉
    Keywords: Base Sequence ; *Disease Outbreaks ; Ebolavirus/*genetics/isolation & purification ; *Epidemiological Monitoring ; Genetic Variation ; Genome, Viral/genetics ; Genomics/methods ; Hemorrhagic Fever, Ebola/epidemiology/*transmission/*virology ; Humans ; Mutation ; Sequence Analysis, DNA ; Sierra Leone/epidemiology
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
  • 3
    Publication Date: 2018-03-06
    Description: The tumor suppressor BRCA1 regulates the DNA damage response (DDR) and other processes that remain incompletely defined. Among these, BRCA1 heterodimerizes with BARD1 to ubiquitylate targets via its N-terminal E3 ligase activity. Here, it is demonstrated that BRCA1 promotes oxidative metabolism by degrading Oct1 (POU2F1), a transcription factor with proglycolytic and tumorigenic effects. BRCA1 E3 ubiquitin ligase mutation skews cells toward a glycolytic metabolic profile while elevating Oct1 protein. CRISPR-mediated Oct1 deletion reverts the glycolytic phenotype. RNA sequencing (RNAseq) confirms deregulation of metabolic genes downstream of Oct1. BRCA1 mediates Oct1 ubiquitylation and degradation, and mutation of two ubiquitylated Oct1 lysines insulates the protein against BRCA1-mediated destabilization. Oct1 deletion in MCF-7 breast cancer cells does not perturb growth in standard culture, but inhibits growth in soft agar and xenograft assays. In primary breast cancer clinical specimens, Oct1 protein levels correlate positively with tumor aggressiveness and inversely with BRCA1. These results identify BRCA1 as an Oct1 ubiquitin ligase that catalyzes Oct1 degradation to promote oxidative metabolism and restrict tumorigenicity. Mol Cancer Res; 16(3); 439–52. ©2018 AACR .
    Print ISSN: 1541-7786
    Electronic ISSN: 1557-3125
    Topics: Medicine
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  • 4
    Electronic Resource
    Electronic Resource
    Woodbury, NY : American Institute of Physics (AIP)
    Applied Physics Letters 81 (2002), S. 13-15 
    ISSN: 1077-3118
    Source: AIP Digital Archive
    Topics: Physics
    Notes: Femtosecond pulse shaping and photomixing methods are combined to make a tunable terahertz source. Grating-pair pulse shaper selects two main frequency components to produce pulses that are modulated with a period which is inversely proportional to the frequency separation. The shaped pulse is then photomixed in semi-insulating GaAs under external bias. Terahertz (THz) emission frequency follows the modulation frequency of the excitation pulses, from 0.5 to 3 THz. Contrary to cw photomixing, this method can easily be combined with electro-optic and photoconductive sampling detection methods. © 2002 American Institute of Physics.
    Type of Medium: Electronic Resource
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  • 5
    Publication Date: 2018-12-15
    Description: Purpose: Lauren diffuse-type gastric adenocarcinomas (DGAs) are generally genomically stable. We identified lysine (K)-specific methyltransferase 2C ( KMT2C ) as a frequently mutated gene and examined its role in DGA progression. Experimental Design: We performed whole exome sequencing on tumor samples of 27 patients with DGA who underwent gastrectomy. Lysine (K)-specific methyltransferase 2C ( KMT2C ) was analyzed in DGA cell lines and in patient tumors. Results: KMT2C was the most frequently mutated gene (11 of 27 tumors [41%]). KMT2C expression by immunohistochemistry in tumors from 135 patients with DGA undergoing gastrectomy inversely correlated with more advanced tumor stage ( P = 0.023) and worse overall survival ( P = 0.017). KMT2C shRNA knockdown in non-transformed HFE-145 gastric epithelial cells promoted epithelial-to-mesenchymal transition (EMT) as demonstrated by increased expression of EMT-related proteins N-cadherin and Slug. Migration and invasion in gastric epithelial cells following KMT2C knockdown increased by 47- to 88-fold. In the DGA cell lines MKN-45 and SNU-668, which have lost KMT2C expression, KMT2C re-expression decreased expression of EMT-related proteins, reduced cell migration by 52% to 60%, and reduced cell invasion by 50% to 74%. Flank xenografts derived from KMT2C-expressing DGA organoids, compared with wild-type organoids, grew more slowly and lost their infiltrative leading edge. EMT can lead to the acquisition of cancer stem cell (CSC) phenotypes. KMT2C re-expression in DGA cell lines reduced spheroid formation by 77% to 78% and reversed CSC resistance to chemotherapy via promotion of DNA damage and apoptosis. Conclusions: KMT2C is frequently mutated in certain populations with DGA. KMT2C loss in DGA promotes EMT and is associated with worse overall survival.
    Print ISSN: 1078-0432
    Electronic ISSN: 1557-3265
    Topics: Medicine
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  • 6
    Publication Date: 2018-08-02
    Description: Background: Most patients with gastric cancer rapidly lose weight after gastrectomy. Therefore, analysis of the effect of body mass index (BMI) on patients with gastric cancer survival should include postoperative BMI and BMI loss and preoperative BMI. This retrospective cohort study analyzed the effect of three BMI variables and their interaction on long-term outcomes. Methods: Preoperative BMI analysis included 2,063 patients with gastric cancer who underwent curative gastrectomy between January 2009 and December 2013 at Seoul National University Bundang Hospital. BMI at postoperative 6 to 12 months was available in 1,845 of these cases. Results: Patients with preoperative BMI 23.0 to 〈27.5 [HR, 0.63; 95% confidence interval (CI), 0.48–0.82 for BMI 23.0 to 〈25.0 and HR, 0.57; 95% CI, 0.42–0.78 for BMI 25.0 to 〈27.5] and postoperative BMI 23.0 to 〈25.0 (HR, 0.67; 95% CI, 0.46–0.98) showed significantly better overall survival (OS) than pre- and postoperative patients with BMI 18.5 to 〈23.0, respectively. Postoperative underweight (BMI 〈18.5; HR, 1.74; 95% CI, 1.27–2.37) and postoperative severe BMI loss (〉4.5; HR, 1.79; 95% CI, 1.29–2.50) were associated with higher mortality. Severe BMI loss and preoperative BMI 〈23.0 had an adverse synergistic effect; patients with BMI 〈23.0 were more vulnerable to severe BMI loss than those with BMI ≥23.0. Associations with cancer-specific survival were similar. Conclusions: All three BMI variables were prognostic factors for survival of patients with gastric cancer. Preoperative BMI and severe BMI loss had an interaction. Impact: Perioperative BMI and weight loss should be analyzed collectively in patients with gastric cancer undergoing gastrectomy. Cancer Epidemiol Biomarkers Prev; 27(8); 955–62. ©2018 AACR .
    Print ISSN: 1055-9965
    Electronic ISSN: 1538-7755
    Topics: Medicine
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