120 research outputs found
Nipah Virus in Lyle's Flying Foxes, Cambodia
We conducted a survey in Cambodia in 2000 on henipavirus infection among several bat species, including flying foxes, and persons exposed to these animals. Among 1,072 bat serum samples tested by enzyme-linked immunosorbent assay, antibodies reactive to Nipah virus (NiV) antigen were detected only in Pteropus lylei species; Cynopterus sphinx, Hipposideros larvatus, Scotophilus kuhlii, Chaerephon plicata, Taphozous melanopogon, and T. theobaldi species were negative. Seroneutralization applied on a subset of 156 serum samples confirmed these results. None of the 8 human serum samples was NiV seropositive with the seroneutralization test. One virus isolate exhibiting cytopathic effect with syncytia was obtained from 769 urine samples collected at roosts of P. lylei specimens. Partial molecular characterization of this isolate demonstrated that it was closely related to NiV. These results strengthen the hypothesis that flying foxes could be the natural host of NiV. Surveillance of human cases should be implemented
Binge Drinking Following Resistance Exercise: Effect on Muscle Power Recovery
Alcohol impairs recovery of isokinetic performance following muscle damaging resistance exercise but no knowledge exists regarding alcohol’s effect on recovery of performance in explosive isotonic movements following resistance exercise that induces only limited muscle damage. Purpose: To investigate the effect of alcohol on recovery from resistance exercise for explosive performance measures. Methods: Nine healthy men (Mean ± SD: 24.8 ± 3.2 years, 176 ± 7 cm, 86.4 ± 14.6 kg) completed 2 identical acute heavy resistance exercise tests (AHRET) separated by 1 week. The AHRET consisted of 6 sets of 10 repetitions of smith machine squats at 80% of 1-repetition maximum (1-RM) with 2 min of rest between sets. From 10-20 minutes post-AHRET participants consumed either 190 proof grain alcohol (EtOH) equal to 1.086 g of alcohol per kg lean mass (82-122 ml total) or no alcohol (Placebo) diluted in an artificially sweetened and calorie free beverage. The participants were blinded to conditions and the order of conditions was counter-balanced. Blood alcohol concentration (BAC) was measured using a breathalyzer. Sixty-five minutes pre-exercise, participants ingested a meal replacement beverage (33.5 kJ per kg body mass). Before the AHRET (PRE) and the following morning (AM), participants performed three high pulls and three bench press throws with 30% of 1-RM, and 10 consecutive vertical jumps, all at maximal effort. Peak power was measured for all exercises. Muscle soreness was measured using analog scales at PRE and AM. Results: BAC peaked 60-90 min post-exercise in all participants (0.084 ± 0.017 g·dl-1) on alcohol ingestion days. No effect of alcohol was found for peak power in the high pull (EtOH, PRE: 1658 ± 432 W, AM: 1659 ± 260 W; Placebo, PRE: 1599 ± 397 W, AM: 1579 ± 301 W), bench press throw (EtOH, PRE: 1120 ± 276 W, AM: 1105 ± 295 W; Placebo, PRE: 1119 ± 202 W, AM: 1089 ± 257 W), or vertical jump (EtOH, PRE: 52.6 ± 13.5 W·kg-1, AM: 48.5 ± 6.3 W·kg-1; Placebo, PRE: 52.2 ± 9.4 W·kg-1, AM: 47.9 ± 9.0 W·kg-1). Leg soreness increased moderately from PRE to AM with no difference between conditions. CONCLUSION: A moderate BAC does not appear to affect explosive upper or lower body power capability on the morning following a heavy squat session that induces only limited muscle damage
Approaches for Handling Immunopathological and Clinical Data Using Deep Learning Methodology: Multiplex IHC/IF Data as a Paradigm
Recent advancements in deep learning based artificial intelligence have enabled us to analyse complex data in order to provide patients with improved cancer prognosis, which is an important goal in precision health medicine. In this chapter, we would be discussing how deep learning could be applied to clinical data and immunopathological images to accurately determine survival rate prediction for patients. Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) is a relatively new technology for simultaneous detection of multiple specific proteins from a single tissue section. To adopt deep learning, we collected and pre-processed the clinical and mIHC/IF data from a group of patients into three branches of data. These data were subsequently used to train and validate a neural network. The specific process and our recommendations will be further discussed in this chapter. We believe that our work will help the community to better handle their data for AI implementation while improving its performance and accuracy
Antibodies to Nipah-Like Virus in Bats (Pteropus lylei), Cambodia
Serum specimens from fruit bats were obtained at restaurants in Cambodia. We detected antibodies cross-reactive to Nipah virus by enzyme immunoassay in 11 (11.5%) of 96 Lyle’s flying foxes (Pteropus lylei). Our study suggests that viruses closely related to Nipah or Hendra viruses are more widespread in Southeast Asia than previously documented
Gastrointestinal perforation in metastatic colorectal cancer patients with peritoneal metastases receiving bevacizumab
AIM To investigate the safety and efficacy of adding bevacizumab to first-line chemotherapy in metastatic colorectal cancer patients with peritoneal disease. METHODS We compared rates of gastrointestinal perforation in patients with metastatic colorectal cancer and peritoneal disease receiving first-line chemotherapy with and without bevacizumab in three distinct cohorts: (1) the AGITG MAX trial (Phase III randomised clinical trial comparing capecitabine vs capecitabine and bevacizumab vs capecitabine, bevacizumab and mitomycinC); (2) the prospective Treatment of Recurrent and Advanced Colorectal Cancer (TRACC) registry (any first-line regimen ± bevacizumab); and (3) two cancer centres in New South Wales, Australia [Macarthur Cancer Therapy Centre and Liverpool Cancer Therapy Centre (NSWCC) from January 2005 to Decenber 2012, (any first-line regimen ± bevacizumab). For the AGITG MAX trial capecitabine was compared to the other two arms (capecitabine/bevacizumab and capecitabine/bevacizumab/mitomycinC). In the AGITG MAX trial and the TRACC registry rates of gastrointestinal perforation were also collected in patients who did not have peritoneal metastases. Secondary endpoints included progression-free survival, chemotherapy duration, and overall survival. Time-to-event outcomes were estimated using the Kaplan-Meier method and compared using the log-rank test. RESULTS Eighty-four MAX, 179 TRACC and 69 NSWCC patients had peritoneal disease. There were no gastrointestinal perforations recorded in either the MAX subgroup or the NSWCC cohorts. Of the patients without peritoneal disease in the MAX trial, 4/300 (1.3%) in the bevacizumab arms had gastrointestinal perforations compared to 1/123 (0.8%) in the capecitabine alone arm. In the TRACC registry 3/126 (2.4%) patients who had received bevacizumab had a gastrointestinal perforation compared to 1/53 (1.9%) in the chemotherapy alone arm. In a further analysis of patients without peritoneal metastases in the TRACC registry, the rate of gastrointestinal perforations was 9/369 (2.4%) in the chemotherapy/bevacizumab group and 5/177 (2.8%) in the chemotherapy alone group. The addition of bevacizumab to chemotherapy was associated with improved progression-free survival in all three cohorts: MAX 6.9 m vs 4.9 m, HR = 0.64 (95%CI: 0.42-1.02); P = 0.063; TRACC 9.1 m vs 5.5 m, HR = 0.61 (95%CI: 0.37-0.86); P = 0.009; NSWCC 8.7 m vs 6.8 m, HR = 0.75 (95%CI: 0.43-1.32); P = 0.32. Chemotherapy duration was similar across the groups. CONCLUSION Patients with peritoneal disease do not appear to have an increased risk of gastrointestinal perforations when receiving first-line therapy with bevacizumab compared to systemic therapy alone
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LARG at chromosome 11q23 has functional characteristics of a tumor suppressor in human breast cancer
Deletion of 11q23-q24 is frequent in a diverse variety of malignancies, including breast and colorectal carcinoma, implicating the presence of a tumor suppressor gene at that chromosomal region. We show here that LARG, from 11q23, has functional characteristics of a tumor suppressor. We examined a 6-Mb region on 11q23 by high-resolution deletion mapping, utilizing both loss of heterozygosity (LOH) analysis and microarray comparative genomic hybridization (CGH). LARG (also called ARHGEF12), identified from the analyzed region, was underexpressed in 34% of primary breast carcinomas and 80% of breast cancer cell lines including the MCF-7 line. Multiplex ligation-dependent probe amplification on 30 primary breast cancers and six breast cancer cell lines showed that LARG had the highest frequency of deletion compared to the BCSC-1 and TSLC1 genes, two known candidate tumor suppressor genes from 11q. In vitro analysis of breast cancer cell lines that underexpress LARG showed that LARG could be reactivated by trichostatin A, a histone deacetylase inhibitor, but not by 5-Aza-2{prime}-deoxycytidine, a demethylating agent. Bisulfite sequencing and quantitative high-throughput analysis of DNA methylation confirmed the lack of CpG island methylation in LARG in breast cancer. Restoration of LARG expression in MCF-7 cells by stable transfection resulted in reduced proliferation and colony formation, suggesting that LARG has functional characteristics of a tumor suppressor gene
The BRICS (Bronchiectasis Radiologically Indexed CT Score)- a multi-center study score for use in idiopathic and post infective bronchiectasis
OBJECTIVES: The goal of this study was to develop a simplified radiological score that could assess clinical disease severity in bronchiectasis. METHODS: The Bronchiectasis Radiologically Indexed CT Score (BRICS) was devised based on a multivariable analysis of the Bhalla score and its ability in predicting clinical parameters of severity. The score was then externally validated in six centers in 302 patients. RESULTS: A total of 184 high-resolution CT scans were scored for the validation cohort. In a multiple logistic regression model, disease severity markers significantly associated with the Bhalla score were percent predicted FEV1, sputum purulence, and exacerbations requiring hospital admission. Components of the Bhalla score that were significantly associated with the disease severity markers were bronchial dilatation and number of bronchopulmonary segments with emphysema. The BRICS was developed with these two parameters. The receiver operating-characteristic curve values for BRICS in the derivation cohort were 0.79 for percent predicted FEV1, 0.71 for sputum purulence, and 0.75 for hospital admissions per year; these values were 0.81, 0.70, and 0.70, respectively, in the validation cohort. Sputum free neutrophil elastase activity was significantly elevated in the group with emphysema on CT imaging. CONCLUSIONS: A simplified CT scoring system can be used as an adjunct to clinical parameters to predict disease severity in patients with idiopathic and postinfective bronchiectasis
Meta-GWAS identifies the heritability of acute radiation-induced toxicities in head and neck cancer
Background and purpose: We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). Materials and methods: We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNP-based heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS. Results: From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 × 10-8). In-silico functional analyses identified “3′-5'-exoribonuclease activity” (FDR = 1.6e-10) for dysphagia, “inositol phosphate-mediated signalling” for mucositis (FDR = 2.20e-09), and “drug catabolic process” for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (±standard error) was 29 ± 0.08 % for dysphagia, 9 ± 0.12 % (mucositis) and 27 ± 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %). Conclusion: In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be replicated in larger studies
Common non-synonymous SNPs associated with breast cancer susceptibility: findings from the Breast Cancer Association Consortium.
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 × 10(-6)], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 × 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 × 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 × 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 × 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community’s Seventh Framework Programme under grant agreement n8 223175
(HEALTH-F2–2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast
Cancer’ program and the Ministry of Economic Development, Innovation and Export Trade of Quebec (PSR-SIIRI-701). Additional support for the iCOGS infrastructure was provided by the
National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME-ON initiative), the Department
of Defence (W81XWH-10-1-0341), Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The ABCFS and OFBCR work was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products or organizations imply endorsement t by the US Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia) and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow and M.C.S. is a NHMRC Senior Research Fellow. The OFBCR work was also supported by the Canadian Institutes of Health Research ‘CIHR Team in Familial Risks of Breast Cancer’ program. The ABCS was funded by the Dutch Cancer Society Grant no. NKI2007-3839 and NKI2009-4363. The ACP study is funded by the Breast Cancer Research Trust, UK. The work of the BBCC was partly funded by ELAN-Programme of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). E.S. is supported by NIHR Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust in partnership with King’s College London, UK. Core funding to the Wellcome Trust Centre for Human Genetics was provided by the Wellcome Trust (090532/Z/09/Z). I.T. is
supported by the Oxford Biomedical Research Centre. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CECILE study was funded by the Fondation de France, the French National Institute of Cancer (INCa), The National League against Cancer, the National Agency for Environmental l and Occupational Health and Food Safety (ANSES), the National Agency for Research (ANR), and the Association for Research against Cancer (ARC). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital.The CNIO-BCS was supported by the Genome Spain Foundation the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit, CNIO is supported by the Instituto de Salud Carlos III. D.A. was supported by a Fellowship from the Michael Manzella Foundation (MMF) and was a participant in the CNIO Summer Training Program. The
CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398). Collection of cancer incidence e data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. HAC receives support from the Lon V Smith Foundation (LVS39420). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0 and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), as well as the Department of Internal Medicine , Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus Bonn, Germany. The HEBCS was supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (132473), the Finnish Cancer Society, The Nordic Cancer Union and the Sigrid Juselius Foundation.
The HERPACC was supported by a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a
Grant-in-Aid for the Third Term Comprehensive 10-Year strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by a research grant from Takeda Science Foundation , by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan and by National Cancer Center Research and Development Fund. The HMBCS was supported by short-term fellowships from the German Academic Exchange Program (to N.B), and the Friends of Hannover Medical School (to N.B.). Financial support for KARBAC was provided
through the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, the Stockholm Cancer Foundation and the Swedish Cancer Society. The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish
Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. kConFab is supported by grants from the National Breast Cancer Foundation , the NHMRC, the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia and the Cancer Foundation of Western Australia.
The kConFab Clinical Follow Up Study was funded by the NHMRC (145684, 288704, 454508). Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command (DAMD17-01-1-0729), the Cancer Council of Tasmania and Cancer Foundation of Western Australia and the NHMRC (199600). G.C.T. and P.W. are supported by the NHMRC. LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018 and 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP) which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. LMBC is supported by the ‘Stichting tegen Kanker’ (232-2008 and 196-2010). The MARIE study was supported by the Deutsche Krebshilfe e.V. (70-2892-BR I), the Federal Ministry of Education Research (BMBF) Germany (01KH0402), the Hamburg Cancer Society and the German Cancer Research Center (DKFZ). MBCSG is supported by grants from the Italian Association ciation for Cancer Research (AIRC) and by funds from the Italian citizens who allocated a 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects ‘5 × 1000’). The MCBCS was supported by the NIH grants (CA122340, CA128978) and a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. The MEC was supported by NIH grants CA63464, CA54281, CA098758 and CA132839. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research (grant CRN-87521) and the Ministry of Economic Development, Innovation and Export Trade (grant PSR-SIIRI-701). MYBRCA is funded by research grants from the Malaysian Ministry of Science, Technology and Innovation (MOSTI), Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation (CARIF). Additional controls were recruited by the Singapore Eye Research Institute, which was supported by a grant from the Biomedical Research Council (BMRC08/1/35/19,tel:08/1/35/19./550), Singapore and the National medical Research
Council, Singapore (NMRC/CG/SERI/2010). The NBCS was supported by grants from the Norwegian Research council (155218/V40, 175240/S10 to A.L.B.D., FUGE-NFR 181600/
V11 to V.N.K. and a Swizz Bridge Award to A.L.B.D.). The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen
Shared Resource, which is supported by P30 CA68485. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the
Academy of Finland, the University of Oulu, and the Oulu University Hospital. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NLCP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and
Human Services, USA. pKARMA is a combination of the KARMA and LIBRO-1 studies. KARMA was supported by Ma¨rit and Hans Rausings Initiative Against Breast Cancer.
KARMA and LIBRO-1 were supported the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linnaeus Centre (Contract ID 70867902) financed by the Swedish Research Council. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SASBAC was supported by funding from the Agency for Science, Technology and Research of Singapore (A∗STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation KC was financed by the Swedish Cancer Society (5128-B07-01PAF). The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30
CA68485. The SBCS was supported by Yorkshire Cancer Research S305PA, S299 and S295. Funding for the SCCS was provided by NIH grant R01 CA092447. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the
authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by a programme grant from Cancer Research UK
(C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the National Medical Research Council Start-up Grant and Centre Grant (NMRC/CG/NCIS /2010). The recruitment of controls by the Singapore Consortium of Cohort
Studies-Multi-ethnic cohort (SCCS-MEC) was funded by the Biomedical Research Council (grant number: 05/1/21/19/425).
SKKDKFZS is supported by the DKFZ. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. K. J. is a fellow of International PhD program, Postgraduate School of Molecular Medicine, Warsaw Medical University, supported by the Polish Foundation of Science. The TNBCC was supported by the NIH grant (CA128978), the Breast Cancer Research Foundation , Komen Foundation for the Cure, the Ohio State University
Comprehensive Cancer Center, the Stefanie Spielman Fund for Breast Cancer Research and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting
Tsung and Wei Fong Chao Foundation. Part of the TNBCC (DEMOKRITOS) has been co-financed by the European Union (European Social Fund – ESF) and Greek National
Funds through the Operational Program ‘Education and Life-long Learning’ of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: ARISTEIA. The TWBCS is supported by the Institute of Biomedical Sciences, Academia Sinica and the National Science Council, Taiwan. The
UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR). ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. Funding to pay the
Open Access publication charges for this article was provided by the Wellcome Trust.This is the advanced access published version distributed under a Creative Commons Attribution License 2.0, which can also be viewed on the publisher's webstie at: http://hmg.oxfordjournals.org/content/early/2014/07/04/hmg.ddu311.full.pdf+htm
Multi-messenger observations of a binary neutron star merger
On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
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