215 research outputs found

    Recensiones [Revista de Historia Económica Año VII Invierno 1989 n. 1 pp. 219-253]

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    Linda Newson. The Cost Of Conquest. Indian decline in Honduras under the Spanish rule e Indian survival in colonial Nicaragua (Por Pedro PĂ©rez Herrero).-- Pedro RodrĂ­guez Campomanes. Reflexiones sobre el comercio español a Indias. (Por Luis Perdices Blas).-- Josep Fontana y otros. El comercio libre entre España y AmĂ©rica Latina, 1765- 1824 (Por AndrĂ©s JosĂ© Moreno MengĂ­bar).-- David-Sven Reher. Familia, poblaciĂłn y sociedad en la provincia de Cuenca, 1700- 1970 (Por ConcepciĂłn De Castro).-- Harvey J. Graff. The labyrinths of literacy. Reflections on literacy past and present (Por Clara E. NĂșñez).-- Bernard Elbaum y William Lazonick (Eds.) The decline of the Brittish Economy (Por Antonio F. Cubel Montesinos).-- Antonio GĂłmez Mendoza. Ferrocarril y mercado interior, Vol. 1: cereales, harinas y vinos, y Vol. 2: Manufacturas textiles, materias textiles, minerales, combustibles y metales (Por James Simpson).-- Carmen SanchĂ­s Deusa. El transporte en el PaĂ­s Valenciano. Carreteras y ferrocarriles (Por Javier Vidal Olivares).-- JosĂ© Manuel Naredo. La economĂ­a en evoluciĂłn. Historia y perspectivas de las categorĂ­as bĂĄsicas del pensamiento EeconĂłmico (Por Manuel Santos Redondo).-- Roger Backhouse. Historia del anĂĄlisis econĂłmico moderno (Por Fernando MĂ©ndez Ibisate).-- William N. Parker (Ed.). Economic History and the modern economist (Por Gabriel Tortella)Publicad

    General Microbiota of the Soft Tick Ornithodoros turicata Parasitizing the Bolson Tortoise (Gopherus flavomarginatus) in the Mapimi Biosphere Reserve, Mexico

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    The general bacterial microbiota of the soft tick Ornithodoros turicata found on Bolson tortoises (Gopherus flavomarginatus) were analyzed using next generation sequencing. The main aims of the study were to establish the relative abundance of bacterial taxa in the tick, and to document the presence of potentially pathogenic species for this tortoise, other animals, and humans. The study was carried-out in the Mapimi Biosphere Reserve in the northern-arid part of Mexico. Bolson tortoises (n = 45) were inspected for the presence of soft ticks, from which 11 tortoises (24.4%) had ticks in low loads (1–3 ticks per individual). Tick pools (five adult ticks each) were analyzed through 16S rRNA V3–V4 region amplification in a MiSeq Illumina, using EzBioCloud as a taxonomical reference. The operational taxonomic units (OTUs) revealed 28 phyla, 84 classes, 165 orders, 342 families, 1013 genera, and 1326 species. The high number of taxa registered for O. turicata may be the result of the variety of hosts that this tick parasitizes as they live inside G. flavomarginatus burrows. While the most abundant phyla were Proteobacteria, Actinobacteria, and Firmicutes, the most abundant species were two endosymbionts of ticks (Midichloria-like and Coxiella-like). Two bacteria documented as pathogenic to Gopherus spp. were registered (Mycoplasma spp. and Pasteurella testudinis). The bovine and ovine tick-borne pathogens A. marginale and A. ovis, respectively, were recorded, as well as the zoonotic bacteria A. phagocytophilum,Coxiella burnetii, and Neoehrlichia sp. Tortoises parasitized with O. turicata did not show evident signs of disease, which could indicate a possible ecological role as a reservoir that has yet to be demonstrated. In fact, the defense mechanisms of this tortoise against the microorganisms transmitted by ticks during their feeding process are still unknown. Future studies on soft ticks should expand our knowledge about what components of the microbiota are notable across multiple host–microbe dynamics. Likewise, studies are required to better understand the host competence of this tortoise, considered the largest terrestrial reptile in North America distributed throughout the Chihuahuan Desert since the late Pleistocene

    Comparison of Extracellular Vesicle Isolation Methods for miRNA Sequencing

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    MicroRNAs (miRNAs) encapsulated in extracellular vesicles (EVs) are potential diagnostic and prognostic biomarkers. However, discrepancies in miRNA patterns and their validation are still frequent due to differences in sample origin, EV isolation, and miRNA sequencing methods. The aim of the present study is to find a reliable EV isolation method for miRNA sequencing, adequate for clinical application. To this aim, two comparative studies were performed in parallel with the same human plasma sample: (i) isolation and characterization of EVs obtained using three procedures: size exclusion chromatography (SEC), iodixanol gradient (GRAD), and its combination (SEC+GRAD) and (ii) evaluation of the yield of miRNA sequences obtained using NextSeq 500 (Illumina) and three miRNA library preparation protocols: NEBNext, NEXTFlex, and SMARTer smRNA-seq. The conclusion of comparison (i) is that recovery of the largest amount of EVs and reproducibility were attained with SEC, but GRAD and SEC+GRAD yielded purer EV preparations. The conclusion of (ii) is that the NEBNext library showed the highest reproducibility in the number of miRNAs recovered and the highest diversity of miRNAs. These results render the combination of GRAD EV isolation and NEBNext library preparation for miRNA retrieval as adequate for clinical applications using plasma samples

    Insulin glargine affects the expression of Igf-1r, Insr, and Igf-1 genes in colon and liver of diabetic rats

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    Objective(s): The mitogenic effect of the analogous insulin glargine is currently under debate since several clinical studies have raised the possibility that insulin glargine treatment has a carcinogenic potential in different tissues. This study aimed to evaluate the Igf-1r, Insr, and Igf-1 gene expression in colon and liver of streptozotocin-induced diabetic rats in response to insulin glargine, neutral protamine Hagedorn (NPH) insulin, and metformin treatments. Materials and Methods: Male Wistar rats were induced during one week with streptozotocin to develop Type 2 Diabetes (T2D) and then randomly distributed into four groups. T2D rats included in the first group received insulin glargine, the second group received NPH insulin, the third group received metformin; finally, untreated T2D rats were included as the control group. All groups were treated for seven days; after the treatment, tissue samples of liver and colon were obtained. Quantitative PCR (qPCR) was performed to analyze the Igf-1r, Insr and Igf-1 gene expression in each tissue sample. Results: The liver tissue showed overexpression of the Insr and Igf-1r genes (P>0.001) in rats treated with insulin glargine in comparison with the control group. Similar results were observed for the Insr gene (P>0.011) in colonic tissue of rats treated with insulin glargine. Conclusion: These observations demonstrate that insulin glargine promote an excess of insulin and IGF-1 receptors in STZ-induced diabetic rats, which could overstimulate the mitogenic signaling pathways

    ESR1 gene promoter region methylation in free circulating DNA and its correlation with estrogen receptor protein expression in tumor tissue in breast cancer patients

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    [Background] Tumor expression of estrogen receptor (ER) is an important marker of prognosis, and is predictive of response to endocrine therapy in breast cancer. Several studies have observed that epigenetic events, such methylation of cytosines and deacetylation of histones, are involved in the complex mechanisms that regulate promoter transcription. However, the exact interplay of these factors in transcription activity is not well understood. In this study, we explored the relationship between ER expression status in tumor tissue samples and the methylation of the 5â€Č CpG promoter region of the estrogen receptor gene (ESR1) isolated from free circulating DNA (fcDNA) in plasma samples from breast cancer patients. [Methods] Patients (n = 110) with non-metastatic breast cancer had analyses performed of ER expression (luminal phenotype in tumor tissue, by immunohistochemistry method), and the ESR1-DNA methylation status (fcDNA in plasma, by quantitative methylation specific PCR technique). [Results] Our results showed a significant association between presence of methylated ESR1 in patients with breast cancer and ER negative status in the tumor tissue (p = 0.0179). There was a trend towards a higher probability of ESR1-methylation in those phenotypes with poor prognosis i.e. 80% of triple negative patients, 60% of HER2 patients, compared to 28% and 5.9% of patients with better prognosis such as luminal A and luminal B, respectively. [Conclusion] Silencing, by methylation, of the promoter region of the ESR1 affects the expression of the estrogen receptor protein in tumors of breast cancer patients; high methylation of ESR1-DNA is associated with estrogen receptor negative status which, in turn, may be implicated in the patient’s resistance to hormonal treatment in breast cancer. As such, epigenetic markers in plasma may be of interest as new targets for anticancer therapy, especially with respect to endocrine treatment.The study was funded, in part, by a grant from the Ministerio de EducaciĂłn y Ciencia (CICYT: SAF 2004–00889)

    Search of the early O3 LIGO data for continuous gravitational waves from the Cassiopeia A and Vela Jr. supernova remnants

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    partially_open1412sĂŹWe present directed searches for continuous gravitational waves from the neutron stars in the Cassiopeia A (Cas A) and Vela Jr. supernova remnants. We carry out the searches in the LIGO detector data from the first six months of the third Advanced LIGO and Virgo observing run using the weave semicoherent method, which sums matched-filter detection-statistic values over many time segments spanning the observation period. No gravitational wave signal is detected in the search band of 20–976 Hz for assumed source ages greater than 300 years for Cas A and greater than 700 years for Vela Jr. Estimates from simulated continuous wave signals indicate we achieve the most sensitive results to date across the explored parameter space volume, probing to strain magnitudes as low as ∌6.3×10^−26 for Cas A and ∌5.6×10^−26 for Vela Jr. at frequencies near 166 Hz at 95% efficiency.openAbbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adhikari, N.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agarwal, D.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Albanesi, S.; Allocca, A.; Altin, P. A.; Amato, A.; Anand, C.; Anand, S.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Andrade, T.; Andres, N.; Andrić, T.; Angelova, S. V.; Ansoldi, S.; Antelis, J. M.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; ArĂšne, M.; Arnaud, N.; Aronson, S. M.; Arun, K. G.; Asali, Y.; Ashton, G.; Assiduo, M.; Aston, S. M.; Astone, P.; Aubin, F.; Austin, C.; Babak, S.; Badaracco, F.; Bader, M. K. M.; Badger, C.; Bae, S.; Baer, A. M.; Bagnasco, S.; Bai, Y.; Baird, J.; Ball, M.; Ballardin, G.; Ballmer, S. W.; Balsamo, A.; Baltus, G.; Banagiri, S.; Bankar, D.; Barayoga, J. C.; Barbieri, C.; Barish, B. C.; Barker, D.; Barneo, P.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Bawaj, M.; Bayley, J. C.; Baylor, A. C.; Bazzan, M.; BĂ©csy, B.; Bedakihale, V. M.; Bejger, M.; Belahcene, I.; Benedetto, V.; Beniwal, D.; Bennett, T. F.; Bentley, J. D.; BenYaala, M.; Bergamin, F.; Berger, B. K.; Bernuzzi, S.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Beveridge, D.; Bhandare, R.; Bhardwaj, U.; Bhattacharjee, D.; Bhaumik, S.; Bilenko, I. A.; Billingsley, G.; Bini, S.; Birney, R.; Birnholtz, O.; Biscans, S.; Bischi, M.; Biscoveanu, S.; Bisht, A.; Biswas, B.; Bitossi, M.; Bizouard, M.-A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bobba, F.; Bode, N.; Boer, M.; Bogaert, G.; Boldrini, M.; Bonavena, L. D.; Bondu, F.; Bonilla, E.; Bonnand, R.; Booker, P.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, N.; Bose, S.; Bossilkov, V.; Boudart, V.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Bramley, A.; Branch, A.; Branchesi, M.; Brau, J. E.; Breschi, M.; Briant, T.; Briggs, J. H.; Brillet, A.; Brinkmann, M.; Brockill, P.; Brooks, A. F.; Brooks, J.; Brown, D. D.; Brunett, S.; Bruno, G.; Bruntz, R.; Bryant, J.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buscicchio, R.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Bustillo, J. CalderĂłn; Callaghan, J. D.; Callister, T. A.; Calloni, E.; Cameron, J.; Camp, J. B.; Canepa, M.; Canevarolo, S.; Cannavacciuolo, M.; Cannon, K. C.; Cao, H.; Capote, E.; Carapella, G.; Carbognani, F.; Carlin, J. B.; Carney, M. F.; Carpinelli, M.; Carrillo, G.; Carullo, G.; Carver, T. L.; Diaz, J. Casanueva; Casentini, C.; Castaldi, G.; Caudill, S.; CavagliĂ , M.; Cavalier, F.; Cavalieri, R.; Ceasar, M.; Cella, G.; CerdĂĄ-DurĂĄn, P.; Cesarini, E.; Chaibi, W.; Chakravarti, K.; Subrahmanya, S. Chalathadka; Champion, E.; Chan, C.-H.; Chan, C.; Chan, C. L.; Chan, K.; Chandra, K.; Chanial, P.; Chao, S.; Charlton, P.; Chase, E. A.; Chassande-Mottin, E.; Chatterjee, C.; Chatterjee, Debarati; Chatterjee, Deep; Chaturvedi, M.; Chaty, S.; Chen, H. Y.; Chen, J.; Chen, X.; Chen, Y.; Chen, Z.; Cheng, H.; Cheong, C. K.; Cheung, H. Y.; Chia, H. Y.; Chiadini, F.; Chiarini, G.; Chierici, R.; Chincarini, A.; Chiofalo, M. L.; Chiummo, A.; Cho, G.; Cho, H. S.; Choudhary, R. K.; Choudhary, S.; Christensen, N.; Chu, Q.; Chua, S.; Chung, K. W.; Ciani, G.; Ciecielag, P.; Cieƛlar, M.; Cifaldi, M.; Ciobanu, A. A.; Ciolfi, R.; Cipriano, F.; Cirone, A.; Clara, F.; Clark, E. N.; Clark, J. A.; Clarke, L.; Clearwater, P.; Clesse, S.; Cleva, F.; Coccia, E.; Codazzo, E.; Cohadon, P.-F.; Cohen, D. E.; Cohen, L.; Colleoni, M.; Collette, C. G.; Colombo, A.; Colpi, M.; Compton, C. M.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-CarriĂłn, I.; Corezzi, S.; Corley, K. R.; Cornish, N.; Corre, D.; Corsi, A.; Cortese, S.; Costa, C. A.; Cotesta, R.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S. T.; Cousins, B.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Criswell, A. W.; Croquette, M.; Crowder, S. G.; Cudell, J. R.; Cullen, T. J.; Cumming, A.; Cummings, R.; Cunningham, L.; Cuoco, E.; CuryƂo, M.; Dabadie, P.; Canton, T. Dal; Dall’Osso, S.; DĂĄlya, G.; Dana, A.; DaneshgaranBajastani, L. M.; D’Angelo, B.; Danilishin, S.; D’Antonio, S.; Danzmann, K.; Darsow-Fromm, C.; Dasgupta, A.; Datrier, L. E. H.; Datta, S.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Davis, M. C.; Daw, E. J.; Dean, R.; DeBra, D.; Deenadayalan, M.; Degallaix, J.; De Laurentis, M.; DelĂ©glise, S.; Del Favero, V.; De Lillo, F.; De Lillo, N.; Del Pozzo, W.; DeMarchi, L. M.; De Matteis, F.; D’Emilio, V.; Demos, N.; Dent, T.; Depasse, A.; De Pietri, R.; De Rosa, R.; De Rossi, C.; DeSalvo, R.; De Simone, R.; Dhurandhar, S.; DĂ­az, M. C.; Diaz-Ortiz, M.; Didio, N. A.; Dietrich, T.; Di Fiore, L.; Di Fronzo, C.; Di Giorgio, C.; Di Giovanni, F.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Ding, B.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Divakarla, A. K.; Dmitriev, A.; Doctor, Z.; D’Onofrio, L.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Drago, M.; Driggers, J. C.; Drori, Y.; Ducoin, J.-G.; Dupej, P.; Durante, O.; D’Urso, D.; Duverne, P.-A.; Dwyer, S. E.; Eassa, C.; Easter, P. J.; Ebersold, M.; Eckhardt, T.; Eddolls, G.; Edelman, B.; Edo, T. B.; Edy, O.; Effler, A.; Eichholz, J.; Eikenberry, S. S.; Eisenmann, M.; Eisenstein, R. A.; Ejlli, A.; Engelby, E.; Errico, L.; Essick, R. C.; EstellĂ©s, H.; Estevez, D.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Ewing, B. E.; Fafone, V.; Fair, H.; Fairhurst, S.; Farah, A. M.; Farinon, S.; Farr, B.; Farr, W. M.; Farrow, N. W.; Fauchon-Jones, E. J.; Favaro, G.; Favata, M.; Fays, M.; Fazio, M.; Feicht, J.; Fejer, M. M.; Fenyvesi, E.; Ferguson, D. L.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, T. A.; Fidecaro, F.; Figura, P.; Fiori, I.; Fishbach, M.; Fisher, R. P.; Fittipaldi, R.; Fiumara, V.; Flaminio, R.; Floden, E.; Fong, H.; Font, J. A.; Fornal, B.; Forsyth, P. W. F.; Franke, A.; Frasca, S.; Frasconi, F.; Frederick, C.; Freed, J. P.; Frei, Z.; Freise, A.; Frey, R.; Fritschel, P.; Frolov, V. V.; FronzĂ©, G. G.; Fulda, P.; Fyffe, M.; Gabbard, H. A.; Gadre, B. U.; Gair, J. R.; Gais, J.; Galaudage, S.; Gamba, R.; Ganapathy, D.; Ganguly, A.; Gaonkar, S. G.; Garaventa, B.; GarcĂ­a-NĂșñez, C.; GarcĂ­a-QuirĂłs, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gayathri, V.; Gemme, G.; Gennai, A.; George, J.; Gerberding, O.; Gergely, L.; Gewecke, P.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, Shaon; Ghosh, Shrobana; Giacomazzo, B.; Giacoppo, L.; Giaime, J. A.; Giardina, K. D.; Gibson, D. R.; Gier, C.; Giesler, M.; Giri, P.; Gissi, F.; Glanzer, J.; Gleckl, A. E.; Godwin, P.; Goetz, E.; Goetz, R.; Gohlke, N.; Goncharov, B.; GonzĂĄlez, G.; Gopakumar, A.; Gosselin, M.; Gouaty, R.; Gould, D. W.; Grace, B.; Grado, A.; Granata, M.; Granata, V.; Grant, A.; Gras, S.; Grassia, P.; Gray, C.; Gray, R.; Greco, G.; Green, A. C.; Green, R.; Gretarsson, A. M.; Gretarsson, E. M.; Griffith, D.; Griffiths, W.; Griggs, H. L.; Grignani, G.; Grimaldi, A.; Grimm, S. J.; Grote, H.; Grunewald, S.; Gruning, P.; Guerra, D.; Guidi, Gianluca; Guimaraes, A. R.; GuixĂ©, G.; Gulati, H. K.; Guo, H.-K.; Guo, Y.; Gupta, Anchal; Gupta, Anuradha; Gupta, P.; Gustafson, E. K.; Gustafson, R.; Guzman, F.; Haegel, L.; Halim, O.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O.; Hansen, H.; Hansen, T. J.; Hanson, J.; Harder, T.; Hardwick, T.; Haris, K.; Harms, J.; Harry, G. M.; Harry, I. W.; Hartwig, D.; Haskell, B.; Hasskew, R. K.; Haster, C.-J.; Haughian, K.; Hayes, F. J.; Healy, J.; Heidmann, A.; Heidt, A.; Heintze, M. C.; Heinze, J.; Heinzel, J.; Heitmann, H.; Hellman, F.; Hello, P.; Helmling-Cornell, A. F.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennes, E.; Hennig, J.; Hennig, M. H.; Hernandez, A. G.; Vivanco, F. Hernandez; Heurs, M.; Hild, S.; Hill, P.; Hines, A. S.; Hochheim, S.; Hofman, D.; Hohmann, J. N.; Holcomb, D. G.; Holland, N. A.; Hollows, I. J.; Holmes, Z. J.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Hourihane, S.; Howell, E. J.; Hoy, C. G.; Hoyland, D.; Hreibi, A.; Hsu, Y.; Huang, Y.; HĂŒbner, M. T.; Huddart, A. D.; Hughey, B.; Hui, V.; Husa, S.; Huttner, S. H.; Huxford, R.; Huynh-Dinh, T.; Idzkowski, B.; Iess, A.; Ingram, C.; Isi, M.; Isleif, K.; Iyer, B. R.; JaberianHamedan, V.; Jacqmin, T.; Jadhav, S. J.; Jadhav, S. P.; James, A. L.; Jan, A. Z.; Jani, K.; Janquart, J.; Janssens, K.; Janthalur, N. N.; Jaranowski, P.; Jariwala, D.; Jaume, R.; Jenkins, A. C.; Jenner, K.; Jeunon, M.; Jia, W.; Johns, G. R.; Jones, A. W.; Jones, D. I.; Jones, J. D.; Jones, P.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Juste, V.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kao, Y.; Kapadia, S. J.; Kapasi, D. P.; Karat, S.; Karathanasis, C.; Karki, S.; Kashyap, R.; Kasprzack, M.; Kastaun, W.; Katsanevas, S.; Katsavounidis, E.; Katzman, W.; Kaur, T.; Kawabe, K.; KĂ©fĂ©lian, F.; Keitel, D.; Key, J. S.; Khadka, S.; Khalili, F. Y.; Khan, S.; Khazanov, E. A.; Khetan, N.; Khursheed, M.; Kijbunchoo, N.; Kim, C.; Kim, J. C.; Kim, K.; Kim, W. S.; Kim, Y.-M.; Kimball, C.; Kinley-Hanlon, M.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Knee, A. M.; Knowles, T. D.; Knyazev, E.; Koch, P.; Koekoek, G.; Koley, S.; Kolitsidou, P.; Kolstein, M.; Komori, K.; Kondrashov, V.; Kontos, A.; Koper, N.; Korobko, M.; Kovalam, M.; Kozak, D. B.; Kringel, V.; Krishnendu, N. V.; KrĂłlak, A.; Kuehn, G.; Kuei, F.; Kuijer, P.; Kumar, A.; Kumar, P.; Kumar, Rahul; Kumar, Rakesh; Kuns, K.; Kuwahara, S.; Lagabbe, P.; Laghi, D.; Lalande, E.; Lam, T. L.; Lamberts, A.; Landry, M.; Lane, B. B.; Lang, R. N.; Lange, J.; Lantz, B.; La Rosa, I.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lecoeuche, Y. K.; Lee, H. M.; Lee, H. W.; Lee, J.; Lee, K.; Lehmann, J.; LemaĂźtre, A.; Leroy, N.; Letendre, N.; Levesque, C.; Levin, Y.; Leviton, J. N.; Leyde, K.; Li, A. K. Y.; Li, B.; Li, J.; Li, T. G. F.; Li, X.; Linde, F.; Linker, S. D.; Linley, J. N.; Littenberg, T. B.; Liu, J.; Liu, K.; Liu, X.; Llamas, F.; Llorens-Monteagudo, M.; Lo, R. K. L.; Lockwood, A.; London, L. T.; Longo, A.; Lopez, D.; Portilla, M. Lopez; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lott, T. P.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lucaccioni, J. F.; LĂŒck, H.; Lumaca, D.; Lundgren, A. P.; Lynam, J. E.; Macas, R.; MacInnis, M.; Macleod, D. M.; MacMillan, I. A. O.; Macquet, A.; Hernandez, I. Magaña; MagazzĂč, C.; Magee, R. M.; Maggiore, R.; Magnozzi, M.; Mahesh, S.; Majorana, E.; Makarem, C.; Maksimovic, I.; Maliakal, S.; Malik, A.; Man, N.; Mandic, V.; Mangano, V.; Mango, J. L.; Mansell, G. L.; Manske, M.; Mantovani, M.; Mapelli, M.; Marchesoni, F.; Marion, F.; Mark, Z.; MĂĄrka, S.; MĂĄrka, Z.; Markakis, C.; Markosyan, A. S.; Markowitz, A.; Maros, E.; Marquina, A.; Marsat, S.; Martelli, F.; Martin, I. W.; Martin, R. M.; Martinez, M.; Martinez, V. A.; Martinez, V.; Martinovic, K.; Martynov, D. V.; Marx, E. J.; Masalehdan, H.; Mason, K.; Massera, E.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Mateu-Lucena, M.; Matichard, F.; Matiushechkina, M.; Mavalvala, N.; McCann, J. J.; McCarthy, R.; McClelland, D. E.; McClincy, P. K.; McCormick, S.; McCuller, L.; McGhee, G. I.; McGuire, S. C.; McIsaac, C.; McIver, J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Mehmet, M.; Mehta, A. K.; Meijer, Q.; Melatos, A.; Melchor, D. A.; Mendell, G.; Menendez-Vazquez, A.; 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    Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

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    The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.Comment: 27 pages, 3 figure

    The population of merging compact binaries inferred using gravitational waves through GWTC-3

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    We report on the population properties of 76 compact binary mergers detected with gravitational waves below a false alarm rate of 1 per year through GWTC-3. The catalog contains three classes of binary mergers: BBH, BNS, and NSBH mergers. We infer the BNS merger rate to be between 10 Gpc−3yr−1\rm{Gpc^{-3} yr^{-1}} and 1700 Gpc−3yr−1\rm{Gpc^{-3} yr^{-1}} and the NSBH merger rate to be between 7.8 Gpc−3 yr−1\rm{Gpc^{-3}\, yr^{-1}} and 140 Gpc−3yr−1\rm{Gpc^{-3} yr^{-1}} , assuming a constant rate density versus comoving volume and taking the union of 90% credible intervals for methods used in this work. Accounting for the BBH merger rate to evolve with redshift, we find the BBH merger rate to be between 17.9 Gpc−3 yr−1\rm{Gpc^{-3}\, yr^{-1}} and 44 Gpc−3 yr−1\rm{Gpc^{-3}\, yr^{-1}} at a fiducial redshift (z=0.2). We obtain a broad neutron star mass distribution extending from 1.2−0.2+0.1M⊙1.2^{+0.1}_{-0.2} M_\odot to 2.0−0.3+0.3M⊙2.0^{+0.3}_{-0.3} M_\odot. We can confidently identify a rapid decrease in merger rate versus component mass between neutron star-like masses and black-hole-like masses, but there is no evidence that the merger rate increases again before 10 M⊙M_\odot. We also find the BBH mass distribution has localized over- and under-densities relative to a power law distribution. While we continue to find the mass distribution of a binary's more massive component strongly decreases as a function of primary mass, we observe no evidence of a strongly suppressed merger rate above ∌60M⊙\sim 60 M_\odot. The rate of BBH mergers is observed to increase with redshift at a rate proportional to (1+z)Îș(1+z)^{\kappa} with Îș=2.9−1.8+1.7\kappa = 2.9^{+1.7}_{-1.8} for zâ‰Č1z\lesssim 1. Observed black hole spins are small, with half of spin magnitudes below χi≃0.25\chi_i \simeq 0.25. We observe evidence of negative aligned spins in the population, and an increase in spin magnitude for systems with more unequal mass ratio

    Constraints on dark photon dark matter using data from LIGO's and Virgo's third observing run

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    We present a search for dark photon dark matter that could couple to gravitational-wave interferometers using data from Advanced LIGO and Virgo's third observing run. To perform this analysis, we use two methods, one based on cross-correlation of the strain channels in the two nearly aligned LIGO detectors, and one that looks for excess power in the strain channels of the LIGO and Virgo detectors. The excess power method optimizes the Fourier Transform coherence time as a function of frequency, to account for the expected signal width due to Doppler modulations. We do not find any evidence of dark photon dark matter with a mass between mA∌10−14−10−11m_{\rm A} \sim 10^{-14}-10^{-11} eV/c2c^2, which corresponds to frequencies between 10-2000 Hz, and therefore provide upper limits on the square of the minimum coupling of dark photons to baryons, i.e. U(1)BU(1)_{\rm B} dark matter. For the cross-correlation method, the best median constraint on the squared coupling is ∌1.31×10−47\sim1.31\times10^{-47} at mA∌4.2×10−13m_{\rm A}\sim4.2\times10^{-13} eV/c2c^2; for the other analysis, the best constraint is ∌2.4×10−47\sim 2.4\times 10^{-47} at mA∌5.7×10−13m_{\rm A}\sim 5.7\times 10^{-13} eV/c2c^2. These limits improve upon those obtained in direct dark matter detection experiments by a factor of ∌100\sim100 for mA∌[2−4]×10−13m_{\rm A}\sim [2-4]\times 10^{-13} eV/c2c^2, and are, in absolute terms, the most stringent constraint so far in a large mass range mA∌m_A\sim 2×10−13−8×10−122\times 10^{-13}-8\times 10^{-12} eV/c2c^2.Comment: 20 pages, 7 figure
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