Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos
Antecedentes: El propósito de este estudio fue determinar la relevancia de la relación entre la red cerebral y el manejo de los lazos sociales. Método: los participantes son 52 adultos mayores coreanos de 65 años o más que viven en Ganghwa-gun, Incheon. Utilizamos un índice de tríada cerrada (CTI), que es la unidad de análisis más básica en el estudio de los fenómenos grupales. Este índice es una variable de red social que ha demostrado tener una implicación diferente dependiendo de la condición y el rol del sujeto. Después de realizar dos encuestas por cuestionario a intervalos de tres años, los participantes se clasificaron en un grupo aumentado y un grupo disminuido de acuerdo con el cambio de CTI. Se siguió el análisis de fMRI en estado... Ver más
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International Journal of Psychological Research - 2020
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| institution |
UNIVERSIDAD DE SAN BUENAVENTURA |
| thumbnail |
https://nuevo.metarevistas.org/UNIVERSIDADDESANBUENAVENTURA_COLOMBIA/logo.png |
| country_str |
Colombia |
| collection |
International Journal of Psychological Research |
| title |
Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos |
| spellingShingle |
Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos Oh, Seolah Kim, Aran Kang, Eunji Choi, Sungwon Red cerebral fMRI en estado de reposo lazos sociales relación tríada personas mayores Seniors Resting State fMRI Social Ties Brain Network Triad-relationship |
| title_short |
Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos |
| title_full |
Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos |
| title_fullStr |
Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos |
| title_full_unstemmed |
Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos |
| title_sort |
red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos |
| description |
Antecedentes: El propósito de este estudio fue determinar la relevancia de la relación entre la red cerebral y el manejo de los lazos sociales. Método: los participantes son 52 adultos mayores coreanos de 65 años o más que viven en Ganghwa-gun, Incheon. Utilizamos un índice de tríada cerrada (CTI), que es la unidad de análisis más básica en el estudio de los fenómenos grupales. Este índice es una variable de red social que ha demostrado tener una implicación diferente dependiendo de la condición y el rol del sujeto. Después de realizar dos encuestas por cuestionario a intervalos de tres años, los participantes se clasificaron en un grupo aumentado y un grupo disminuido de acuerdo con el cambio de CTI. Se siguió el análisis de fMRI en estado de reposo para investigar la diferencia de las redes cerebrales entre los grupos.Resultados: Según el análisis del estudio, todos los participantes que habían aumentado en número de CTI tienen una mayor eficiencia local que el grupo de participantes que no tuvieron ningún efecto o disminuyeron en CTI. Conclusiones: Nuestro estudio sugiere que la relación social que está sustancialmente relacionada con la red cerebral es un factor importante en el envejecimiento exitoso. Por último, dado que existe una restricción de que el estudio no puede explicar el aspecto causal de la red cerebral y la relación tríada, existe la necesidad de una mayor investigación.
|
| description_eng |
Background: The purpose of this study is to determine the relevance of the relationship between brain network and the social ties management.Methods: Participants are based on 52 Korean seniors aged 65 and older who live in Ganghwa-gun, Incheon. We used a closed-triad index (CTI), which is the most basic unit of analysis in the study of group phenomena. This index is a social networking variable that has been shown to have a different implication depending on the subject’s condition and role. After two questionnaire surveys were conducted at three years intervals, participants were classified into an increased group and a decreased group according to the change of CTI. Resting-state fMRI analysis were followed to investigate the difference of brain networks between groups. Results: According to the analysis of the study, the whole participants who had increased in number of CTI has higher local efficiency than the group of the participants who had no effect or decreased in CTI. Conclusions: Our study suggests that social relationship, which is substantially related to brain network, is a major factor in successful aging. Lastly, since there is a restriction that the study cannot explain the causal aspect of the brain network and the triad-relationship, there is a need for further investigation.
|
| author |
Oh, Seolah Kim, Aran Kang, Eunji Choi, Sungwon |
| author_facet |
Oh, Seolah Kim, Aran Kang, Eunji Choi, Sungwon |
| topicspa_str_mv |
Red cerebral fMRI en estado de reposo lazos sociales relación tríada personas mayores |
| topic |
Red cerebral fMRI en estado de reposo lazos sociales relación tríada personas mayores Seniors Resting State fMRI Social Ties Brain Network Triad-relationship |
| topic_facet |
Red cerebral fMRI en estado de reposo lazos sociales relación tríada personas mayores Seniors Resting State fMRI Social Ties Brain Network Triad-relationship |
| citationvolume |
13 |
| citationissue |
2 |
| citationedition |
Núm. 2 , Año 2020 : Volume 13(2) |
| publisher |
Universidad San Buenaventura - USB (Colombia) |
| ispartofjournal |
International Journal of Psychological Research |
| source |
https://revistas.usb.edu.co/index.php/IJPR/article/view/4422 |
| language |
Inglés |
| format |
Article |
| rights |
https://creativecommons.org/licenses/by-nc-sa/4.0/ International Journal of Psychological Research - 2020 info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 |
| references_eng |
Bae, K. H., & Kim, Y. H. (2006). The study on the relationship between social capital and organizational commitment: Focusing on burt’s structural holes. Korean Journal of Public Administration, 44 (3), 1–32. Barrera, M., Sandler, I. N., & Ramsay, T. B. (1981). Preliminary development of a scale of social support: Studies on college students. American Journal of Community Psychology, 9 (4), 435–447. https://doi.org/10.1007/BF00918174. Bechara, A., Damasio, H., & Damasio, A. R. (2000). Emotion, decision making and the orbitofrontal cortex. Cerebral cortex, 10 (3), 295–307. https://doi.org/10.1093/cercor/10.3.295. Bherer, L., Erickson, K. I., & Liu-Ambrose, T. (2013). A review of the effects of physical activity and exercise on cognitive and brain functions in older adults. Journal of aging research, 2013, 657508. https://doi.org/10.1155/2013/657508. Brothers, L. (2001). Friday’s footprint: How society shapes the human mind. Oxford University Press. Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nat. Rev. Neuroscience, 10 (3), 186–198. https://doi.org/10.1038/nrn2575. Burt, R. S. (1992). Structural hole. Harvard Business School Press. Cornwell, B., Laumann, E. O., & Schumm, L. P. (2008). The social connectedness of older adults: A national profile. American sociological review, 73 (2), 185–203. https://doi.org/10.1177%2F000312240807300201. Cornwell, &Waite, L. J. (2009). Social disconnectedness, perceived isolation, and health among older adults. Journal of health and social behavior, 50 (1), 31–48. https://dx.doi.org/10.1177/2F002214650905000103. Costenbaderm, E., & Valente, T. W. (2003). The stability of centrality measures when networks are sampled. Social networks, 25 (4), 283–307. Decety, J., & Grèzes, J. (2006). The power of simulation: Imagining one’s own and other’s behavior. Brain research, 1079 (1), 4–14. https://doi.org/10.1016/j.brainres.2005.12.115. de Vico Fallani, F., Richiardi, J., Chavez, M., & Achard, S. (2014). Graph analysis of functional brain networks: Practical issues in translational neuroscience. Philosophical Transactions of the Royal Society B: Biological Sciences, 369 (1653), 20130521. https://dx.doi.org/10.1098/2Frstb.2013.0521. Dugan, E., & Kivett, V. R. (1994). The importance of emotional and social isolation to loneliness among very old rural adults. The Gerontologist, 34 (3), 340–346. https://doi.org/10.1093/geront/34.3.340. Dunkle, R. E., Roberts, B., & Haug, M. R. (2001). The oldest old in everyday life: Self perception, coping with change, and stress. Springer Publishing Company. Fiori, K. L., Antonucci, T. C., & Cortina, K. S. (2006). Social network typologies and mental health among older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 61 (1), P25–P32. https://doi.org/10.1093/geronb/61.1.p25. Fratiglioni, L., Wang, H. X., Ericsson, K., Maytan, M., & Winblad, B. (2000). Influence of social network on occurrence of dementia: A communitybased longitudinal study. The lancet, 355 (9212), 1315–1319. https://doi.org/10.1016/s0140-6736(00)02113-9. Frith, U., & Frith, C. (2001). The biological basis of social interaction. Current Directions in Psychological Science, 10 (5), 151–155. https://doi.org/ 10.1111/1467-8721.00137. Gargiulo, M., & Benassi, M. (2000). Trapped in your own net? network cohesion, structural holes, and the adaptation of social capital. Organization science, 11 (2), 183–196. https://doi.org/10.1287/orsc.11.2.183.12514. Green, M. F., & Horan, W. P. (2010). Social cognition in schizophrenia. Current Directions in Psychological Science, 19 (4), 243–248. https://doi.org/10.1177%2F0963721410377600. Holtzman, R. E., Rebok, G. W., Saczynski, J. S., Kouzis, A. C., WilcoxDoyle, K., & Eaton, W. W. (2004). Social network characteristics and cognition in middle-aged and older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 59 (6), P278–P284. https://doi.org/10.1177%2F0963721410377600. Huang, H., Tang, J., Wu, S., & Liu, L. (2014, April). Mining triadic closure patterns in social networks. In Proceedings of the 23rd International Conference on World Wide Web(pp. 499-504). ACM. Hynes, C. A., Baird, A. A., & Grafton, S. T. (2006). Differential role of the orbital frontal lobe in emotional versus cognitive perspective-taking. Neuropsychologia, 44 (3), 374–383. https://doi.org/10.1016/j.neuropsychologia.2005.06.011. Kennedy, D. P., Redcay, E., & Courchesne, E. (2006). Failing to deactivate: Resting functional abnormalities in autism. Proceedings of the National Academy of Sciences, 103 (21), 8275–8280. https://doi.org/10.1073/pnas.0600674103. Kim, H. Y., & Choi, J. Y. (2016). Aging and efficiency of brain functional networks : Preliminary study in korean women. Korean Journal of Cognitive and Biological Psychology, 28 (4), 675–682. Kwak, S., Joo, W., Youm, Y., & Chey, J. (2018). Social brain volume is associated with in-degree social network size among older adults. Proceedings of the Royal Society B: Biological Sciences, 285 (1871), 20172708. https://doi.org/10.1098/rspb.2017.2708. Latora, V., & Marchiori, M. (2001). Efficient behavior of small-world networks. Physical review letters, 87 (19), 198701. https://doi.org/10.1103/PhysRevLett.87.198701. Latora, V., & Marchiori, M. (2003). Economic smallworld behavior in weighted networks. The European Physical Journal B-Condensed Matter and Complex Systems, 32 (2), 249–263. https://doi.org/10.1140/epjb/e2003-00095-5. Lewis, J. D., Evans, A. C., Pruett, J. R., Botteron, K., Zwaigenbaum, L., Estes, A., Gerig, G., Collins, L., Kostopoulos, P., McKinstry, R., Dager, S., Paterson, S., Schultz, R. T., Styner, M., & Hazlett, S., H.and Dager. (2014). Network inefficiencies in autism spectrum disorder at 24 months. Translational psychiatry, 4 (5), e388–e388. https://dx.doi.org/10.1038%2Ftp.2014.24. Liu, Y., & et al. (2008). Disrupted small-world networks in schizophrenia. Brain, 131 (4), 945–961. https://doi.org/10.1093/brain/awn018. Petrella, J. R. (2011). Use of graph theory to evaluate brain networks: A clinical tool for a small world? Reviews and Commentary, 259 (2), 317–320. https://doi.org/10.1148/radiol.11110380. Pinkham, A. E., Hopfinger, J. B., Pelphrey, K. A., Piven, J., & Penn, D. L. (2008). Neural bases for impaired social cognition in schizophrenia and autism spectrum disorders. Schizophrenia research, 99 (1), 164–175. https://doi.org/10.1016/j.schres.2007.10.024. Prince, M. J., Harwood, R. H., Blizard, R. A., Thomas, A., & Mann, A. H. (1997). Social support deficits, loneliness and life events as risk factors for depression in old age. the gospel oak project vi. 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The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 53 (6), S313–S323. https://doi.org/10.1093/geronb/53b.6.s313. Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’networks. Nature, 393 (6684), 440–442. https://doi.org/10.1038/30918. Welchew, D. E., & et al. (2005). Functional disconnectivity of the medial temporal lobe in aspergers syndrome. Biological psychiatry, 57 (9), 991– 998. https://doi.org/10.1016/j.biopsych.2005.01.028. Winningham, R. G., & Pike, N. L. (2007). A cognitive intervention to enhance institutionalized older adults social support networks and decrease loneliness. Aging & mental health, 11 (6), 716–721. https://doi.org/10.1080/1360786070136622. Ybarra, O., Burnstein, E., Winkielman, P., Keller, M. C., Manis, M., Chan, E., & Rodriguez, J. (2008). Mental exercising through simple socializing: Social interaction promotes general cognitive functioning. Personality and Social Psychology Bulletin, 34 (2), 248–259. https://doi.org/10.1177/0146167207310454. Youm, Y., Laumann, E. O., Ferraro, K. F., Waite, L. J., Kim, H. C., Park, Y., Chu, S. H., Joo, W., & Lee, J. A. (2014). Social network properties and self-rated health in later life: Comparisons from the korean social life, health, and aging project and the national social life, health and aging project. BMC geriatrics, 14, 1–15. https://doi.org/10.1186/1471-2318-14-102. Zunzunegui, M. V., Alvarado, B. E., Del Ser, T., & Otero, A. (2003). Social networks, social integration, and social engagement determine cognitive decline in community-dwelling Spanish older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 2, S93–S100. |
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Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos Red cerebral Antecedentes: El propósito de este estudio fue determinar la relevancia de la relación entre la red cerebral y el manejo de los lazos sociales. Método: los participantes son 52 adultos mayores coreanos de 65 años o más que viven en Ganghwa-gun, Incheon. Utilizamos un índice de tríada cerrada (CTI), que es la unidad de análisis más básica en el estudio de los fenómenos grupales. Este índice es una variable de red social que ha demostrado tener una implicación diferente dependiendo de la condición y el rol del sujeto. Después de realizar dos encuestas por cuestionario a intervalos de tres años, los participantes se clasificaron en un grupo aumentado y un grupo disminuido de acuerdo con el cambio de CTI. Se siguió el análisis de fMRI en estado de reposo para investigar la diferencia de las redes cerebrales entre los grupos.Resultados: Según el análisis del estudio, todos los participantes que habían aumentado en número de CTI tienen una mayor eficiencia local que el grupo de participantes que no tuvieron ningún efecto o disminuyeron en CTI. Conclusiones: Nuestro estudio sugiere que la relación social que está sustancialmente relacionada con la red cerebral es un factor importante en el envejecimiento exitoso. Por último, dado que existe una restricción de que el estudio no puede explicar el aspecto causal de la red cerebral y la relación tríada, existe la necesidad de una mayor investigación. Artículo de revista fMRI en estado de reposo lazos sociales relación tríada personas mayores Red cerebral funcional en estado de reposo y la formación de lazos sociales en ancianos Universidad San Buenaventura - USB (Colombia) International Journal of Psychological Research https://revistas.usb.edu.co/index.php/IJPR/article/view/4422 Inglés https://creativecommons.org/licenses/by-nc-sa/4.0/ International Journal of Psychological Research - 2020 Bae, K. H., & Kim, Y. H. (2006). The study on the relationship between social capital and organizational commitment: Focusing on burt’s structural holes. Korean Journal of Public Administration, 44 (3), 1–32. Barrera, M., Sandler, I. N., & Ramsay, T. B. (1981). Preliminary development of a scale of social support: Studies on college students. American Journal of Community Psychology, 9 (4), 435–447. https://doi.org/10.1007/BF00918174. Bechara, A., Damasio, H., & Damasio, A. R. (2000). Emotion, decision making and the orbitofrontal cortex. Cerebral cortex, 10 (3), 295–307. https://doi.org/10.1093/cercor/10.3.295. Bherer, L., Erickson, K. I., & Liu-Ambrose, T. (2013). A review of the effects of physical activity and exercise on cognitive and brain functions in older adults. Journal of aging research, 2013, 657508. https://doi.org/10.1155/2013/657508. Brothers, L. (2001). Friday’s footprint: How society shapes the human mind. Oxford University Press. Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nat. Rev. Neuroscience, 10 (3), 186–198. https://doi.org/10.1038/nrn2575. Burt, R. S. (1992). Structural hole. Harvard Business School Press. Cornwell, B., Laumann, E. O., & Schumm, L. P. (2008). The social connectedness of older adults: A national profile. American sociological review, 73 (2), 185–203. https://doi.org/10.1177%2F000312240807300201. Cornwell, &Waite, L. J. (2009). Social disconnectedness, perceived isolation, and health among older adults. Journal of health and social behavior, 50 (1), 31–48. https://dx.doi.org/10.1177/2F002214650905000103. Costenbaderm, E., & Valente, T. W. (2003). The stability of centrality measures when networks are sampled. Social networks, 25 (4), 283–307. Decety, J., & Grèzes, J. (2006). The power of simulation: Imagining one’s own and other’s behavior. Brain research, 1079 (1), 4–14. https://doi.org/10.1016/j.brainres.2005.12.115. de Vico Fallani, F., Richiardi, J., Chavez, M., & Achard, S. (2014). Graph analysis of functional brain networks: Practical issues in translational neuroscience. Philosophical Transactions of the Royal Society B: Biological Sciences, 369 (1653), 20130521. https://dx.doi.org/10.1098/2Frstb.2013.0521. Dugan, E., & Kivett, V. R. (1994). The importance of emotional and social isolation to loneliness among very old rural adults. The Gerontologist, 34 (3), 340–346. https://doi.org/10.1093/geront/34.3.340. Dunkle, R. E., Roberts, B., & Haug, M. R. (2001). The oldest old in everyday life: Self perception, coping with change, and stress. Springer Publishing Company. Fiori, K. L., Antonucci, T. C., & Cortina, K. S. (2006). Social network typologies and mental health among older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 61 (1), P25–P32. https://doi.org/10.1093/geronb/61.1.p25. Fratiglioni, L., Wang, H. X., Ericsson, K., Maytan, M., & Winblad, B. (2000). Influence of social network on occurrence of dementia: A communitybased longitudinal study. The lancet, 355 (9212), 1315–1319. https://doi.org/10.1016/s0140-6736(00)02113-9. Frith, U., & Frith, C. (2001). The biological basis of social interaction. Current Directions in Psychological Science, 10 (5), 151–155. https://doi.org/ 10.1111/1467-8721.00137. Gargiulo, M., & Benassi, M. (2000). Trapped in your own net? network cohesion, structural holes, and the adaptation of social capital. Organization science, 11 (2), 183–196. https://doi.org/10.1287/orsc.11.2.183.12514. Green, M. F., & Horan, W. P. (2010). Social cognition in schizophrenia. Current Directions in Psychological Science, 19 (4), 243–248. https://doi.org/10.1177%2F0963721410377600. Holtzman, R. E., Rebok, G. W., Saczynski, J. S., Kouzis, A. C., WilcoxDoyle, K., & Eaton, W. W. (2004). Social network characteristics and cognition in middle-aged and older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 59 (6), P278–P284. https://doi.org/10.1177%2F0963721410377600. Huang, H., Tang, J., Wu, S., & Liu, L. (2014, April). Mining triadic closure patterns in social networks. In Proceedings of the 23rd International Conference on World Wide Web(pp. 499-504). ACM. Hynes, C. A., Baird, A. A., & Grafton, S. T. (2006). Differential role of the orbital frontal lobe in emotional versus cognitive perspective-taking. Neuropsychologia, 44 (3), 374–383. https://doi.org/10.1016/j.neuropsychologia.2005.06.011. Kennedy, D. P., Redcay, E., & Courchesne, E. (2006). Failing to deactivate: Resting functional abnormalities in autism. Proceedings of the National Academy of Sciences, 103 (21), 8275–8280. https://doi.org/10.1073/pnas.0600674103. Kim, H. Y., & Choi, J. Y. (2016). Aging and efficiency of brain functional networks : Preliminary study in korean women. Korean Journal of Cognitive and Biological Psychology, 28 (4), 675–682. Kwak, S., Joo, W., Youm, Y., & Chey, J. (2018). Social brain volume is associated with in-degree social network size among older adults. Proceedings of the Royal Society B: Biological Sciences, 285 (1871), 20172708. https://doi.org/10.1098/rspb.2017.2708. Latora, V., & Marchiori, M. (2001). Efficient behavior of small-world networks. Physical review letters, 87 (19), 198701. https://doi.org/10.1103/PhysRevLett.87.198701. Latora, V., & Marchiori, M. (2003). Economic smallworld behavior in weighted networks. The European Physical Journal B-Condensed Matter and Complex Systems, 32 (2), 249–263. https://doi.org/10.1140/epjb/e2003-00095-5. Lewis, J. D., Evans, A. C., Pruett, J. R., Botteron, K., Zwaigenbaum, L., Estes, A., Gerig, G., Collins, L., Kostopoulos, P., McKinstry, R., Dager, S., Paterson, S., Schultz, R. T., Styner, M., & Hazlett, S., H.and Dager. (2014). Network inefficiencies in autism spectrum disorder at 24 months. Translational psychiatry, 4 (5), e388–e388. https://dx.doi.org/10.1038%2Ftp.2014.24. Liu, Y., & et al. (2008). Disrupted small-world networks in schizophrenia. Brain, 131 (4), 945–961. https://doi.org/10.1093/brain/awn018. Petrella, J. R. (2011). Use of graph theory to evaluate brain networks: A clinical tool for a small world? 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BMC geriatrics, 14, 1–15. https://doi.org/10.1186/1471-2318-14-102. Zunzunegui, M. V., Alvarado, B. E., Del Ser, T., & Otero, A. (2003). Social networks, social integration, and social engagement determine cognitive decline in community-dwelling Spanish older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 2, S93–S100. info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 info:eu-repo/semantics/publishedVersion http://purl.org/coar/version/c_970fb48d4fbd8a85 info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 Text application/pdf Publication Seniors Journal article Núm. 2 , Año 2020 : Volume 13(2) Background: The purpose of this study is to determine the relevance of the relationship between brain network and the social ties management.Methods: Participants are based on 52 Korean seniors aged 65 and older who live in Ganghwa-gun, Incheon. We used a closed-triad index (CTI), which is the most basic unit of analysis in the study of group phenomena. This index is a social networking variable that has been shown to have a different implication depending on the subject’s condition and role. After two questionnaire surveys were conducted at three years intervals, participants were classified into an increased group and a decreased group according to the change of CTI. Resting-state fMRI analysis were followed to investigate the difference of brain networks between groups. Results: According to the analysis of the study, the whole participants who had increased in number of CTI has higher local efficiency than the group of the participants who had no effect or decreased in CTI. Conclusions: Our study suggests that social relationship, which is substantially related to brain network, is a major factor in successful aging. Lastly, since there is a restriction that the study cannot explain the causal aspect of the brain network and the triad-relationship, there is a need for further investigation. Oh, Seolah 2 Kim, Aran Kang, Eunji 13 Resting State fMRI Social Ties Choi, Sungwon Brain Network Triad-relationship 2020-08-20 59 https://revistas.usb.edu.co/index.php/IJPR/article/download/4422/3702 67 2020-08-20T02:38:00Z https://doi.org/10.21500/20112084.4422 10.21500/20112084.4422 2011-7922 2011-2084 2020-08-20T02:38:00Z |