Loss of temporal coherence in the circadian metabolome across multiple tissues during ageing in mice.

Publisher: Wiley-Blackwell Country of Publication: France NLM ID: 8918110 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1460-9568 (Electronic) Linking ISSN: 0953816X NLM ISO Abbreviation: Eur J Neurosci Subsets: MEDLINE

Publication: : Oxford : Wiley-Blackwell
Original Publication: Oxford, UK : Published on behalf of the European Neuroscience Association by Oxford University Press, c1989-

Aging*/metabolism ; Aging*/physiology ; Suprachiasmatic Nucleus*/metabolism ; Metabolome* ; Circadian Rhythm*/physiology ; Liver*/metabolism ; Paraventricular Hypothalamic Nucleus*/metabolism; Animals ; Mice ; Male ; Mice, Inbred C57BL ; Circadian Clocks/physiology ; Amines/metabolism

Circadian clock function declines with ageing, which can aggravate ageing-related diseases such as type 2 diabetes and neurodegenerative disorders. Understanding age-related changes in the circadian system at a systemic level can contribute to the development of strategies to promote healthy ageing. The goal of this study was to investigate the impact of ageing on 24-h rhythms in amine metabolites across four tissues in young (2 months of age) and old (22-25 months of age) mice using a targeted metabolomics approach. Liver, plasma, the suprachiasmatic nucleus (SCN; the location of the central circadian clock in the hypothalamus) and the paraventricular nucleus (PVN; a downstream target of the SCN) were collected from young and old mice every 4 h during a 24-h period (n = 6-7 mice per group). Differential rhythmicity analysis revealed that ageing impacts 24-h rhythms in the amine metabolome in a tissue-specific manner. Most profound changes were observed in the liver, in which rhythmicity was lost in 60% of the metabolites in aged mice. Furthermore, we found strong correlations in metabolite levels between the liver and plasma and between the SCN and the PVN in young mice. These correlations were almost completely abolished in old mice. These results indicate that ageing is accompanied by a severe loss of the circadian coordination between tissues and by disturbed rhythmicity of metabolic processes. The tissue-specific impact of ageing may help to differentiate mechanisms of ageing-related disorders in the brain versus peripheral tissues and thereby contribute to the development of potential therapies for these disorders.
(© 2024 The Author(s). European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Acosta‐Rodriguez, V. A., Rijo‐Ferreira, F., Green, C. B., & Takahashi, J. S. (2021). Importance of circadian timing for aging and longevity. Nature Communications, 12, 2862. https://doi.org/10.1038/s41467-021-22922-6.
Atger, F., Gobet, C., Marquis, J., Martin, E., Wang, J., Weger, B., Lefebvre, G., Descombes, P., Naef, F., & Gachon, F. (2015). Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver. Proceedings of the National Academy of Sciences of the United States of America, 112, E6579–E6588. https://doi.org/10.1073/pnas.1515308112.
Atwood, A., DeConde, R., Wang, S. S., Mockler, T. C., Sabir, J. S., Ideker, T., & Kay, S. A. (2011). Cell‐autonomous circadian clock of hepatocytes drives rhythms in transcription and polyamine synthesis. Proceedings of the National Academy of Sciences of the United States of America, 108, 18560–18565. https://doi.org/10.1073/pnas.1115753108.
Bresilla, D., Habisch, H., Pritisanac, I., Zarse, K., Parichatikanond, W., Ristow, M., Madl, T., & Madreiter‐Sokolowski, C. T. (2022). The sex‐specific metabolic signature of C57BL/6NRj mice during aging. Scientific Reports, 12, 21050. https://doi.org/10.1038/s41598-022-25396-8.
Brown, S. A. (2016). Circadian metabolism: From mechanisms to metabolomics and medicine. Trends in Endocrinology and Metabolism, 27, 415–426. https://doi.org/10.1016/j.tem.2016.03.015.
Buijink, M. R., & Michel, S. (2021). A multi‐level assessment of the bidirectional relationship between aging and the circadian clock. Journal of Neurochemistry, 157, 73–94. https://doi.org/10.1111/jnc.15286.
Buijink, M. R., Olde Engberink, A. H. O., Wit, C. B., Almog, A., Meijer, J. H., Rohling, J. H. T., & Michel, S. (2020). Aging affects the capacity of photoperiodic adaptation downstream from the central molecular clock. Journal of Biological Rhythms, 35, 167–179. https://doi.org/10.1177/0748730419900867.
Buijink, M. R., van Weeghel, M., Gülersönmez, M. C., Harms, A. C., Rohling, J. H. T., Meijer, J. H., Hankemeier, T., & Michel, S. (2018). The influence of neuronal electrical activity on the mammalian central clock metabolome. Metabolomics, 14, 122. https://doi.org/10.1007/s11306-018-1423-z.
Buijs, R., Hermes, M. H. L. J., & Kalsbeek, A. (1999). The suprachiasmatic nucleus—paraventricular nucleus interactions: A bridge to the neuroendocrine and autonomic nervous system. In I. J. A. Urban, J. P. H. Burbach, & D. De Wed (Eds.), Progress in brain research (pp. 365–382). Elsevier. https://doi.org/10.1016/S0079-6123(08)61581-2.
Buijs, R. M., Guzman Ruiz, M. A., Mendez Hernandez, R., & Rodriguez Cortes, B. (2019). The suprachiasmatic nucleus; a responsive clock regulating homeostasis by daily changing the setpoints of physiological parameters. Autonomic Neuroscience, 218, 43–50. https://doi.org/10.1016/j.autneu.2019.02.001.
Butler, M. P., & Silver, R. (2009). Basis of robustness and resilience in the suprachiasmatic nucleus: Individual neurons form nodes in circuits that cycle daily. Journal of Biological Rhythms, 24, 340–352. https://doi.org/10.1177/0748730409344800.
Castanon‐Cervantes, O., Wu, M., Ehlen, J. C., Paul, K., Gamble, K. L., Johnson, R. L., Besing, R. C., Menaker, M., Gewirtz, A. T., & Davidson, A. J. (2010). Dysregulation of inflammatory responses by chronic circadian disruption. Journal of Immunology, 185, 5796–5805. https://doi.org/10.4049/jimmunol.1001026.
Chen, C. Y., Logan, R. W., Ma, T., Lewis, D. A., Tseng, G. C., Sibille, E., & McClung, C. A. (2016). Effects of aging on circadian patterns of gene expression in the human prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 113, 206–211. https://doi.org/10.1073/pnas.1508249112.
Cogswell, D., Bisesi, P., Markwald, R. R., Cruickshank‐Quinn, C., Quinn, K., McHill, A., Melanson, E. L., Reisdorph, N., Wright, K. P. Jr., & Depner, C. M. (2021). Identification of a preliminary plasma metabolome‐based biomarker for circadian phase in humans. Journal of Biological Rhythms, 36, 369–383. https://doi.org/10.1177/07487304211025402.
Cornelissen, G. (2014). Cosinor‐based rhythmometry. Theoretical Biology & Medical Modelling, 11, 16. https://doi.org/10.1186/1742-4682-11-16.
Dallmann, R., Viola, A. U., Tarokh, L., Cajochen, C., & Brown, S. A. (2012). The human circadian metabolome. Proceedings of the National Academy of Sciences of the United States of America, 109, 2625–2629. https://doi.org/10.1073/pnas.1114410109.
Damiola, F., Le Minh, N., Preitner, N., Kornmann, B., Fleury‐Olela, F., & Schibler, U. (2000). Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes & Development, 14, 2950–2961. https://doi.org/10.1101/gad.183500.
Dyar, K. A. (2018). Raw “origscale” 24‐h metabolomics intensity data from 8 different murine tissues under chow or high fat diet. Mendeley Data V1.
Dyar, K. A., Lutter, D., Artati, A., Ceglia, N. J., Liu, Y., Armenta, D., Jastroch, M., Schneider, S., de Mateo, S., Cervantes, M., Abbondante, S., Tognini, P., Orozco‐Solis, R., Kinouchi, K., Wang, C., Swerdloff, R., Nadeef, S., Masri, S., Magistretti, P., … Sassone‐Corsi, P. (2018). Atlas of circadian metabolism reveals system‐wide coordination and communication between clocks. Cell, 174, 1571–1585.e11. https://doi.org/10.1016/j.cell.2018.08.042.
Eckel‐Mahan, K., & Sassone‐Corsi, P. (2013). Metabolism and the circadian clock converge. Physiological Reviews, 93, 107–135. https://doi.org/10.1152/physrev.00016.2012.
Eisenberg, T., Abdellatif, M., Schroeder, S., Primessnig, U., Stekovic, S., Pendl, T., Harger, A., Schipke, J., Zimmermann, A., Schmidt, A., Tong, M., Ruckenstuhl, C., Dammbrueck, C., Gross, A. S., Herbst, V., Magnes, C., Trausinger, G., Narath, S., Meinitzer, A., … Madeo, F. (2016). Cardioprotection and lifespan extension by the natural polyamine spermidine. Nature Medicine, 22, 1428–1438. https://doi.org/10.1038/nm.4222.
Eisenberg, T., Knauer, H., Schauer, A., Buttner, S., Ruckenstuhl, C., Carmona‐Gutierrez, D., Ring, J., Schroeder, S., Magnes, C., Antonacci, L., Fussi, H., Deszcz, L., Hartl, R., Schraml, E., Criollo, A., Megalou, E., Weiskopf, D., Laun, P., Heeren, G., … Madeo, F. (2009). Induction of autophagy by spermidine promotes longevity. Nature Cell Biology, 11, 1305–1314. https://doi.org/10.1038/ncb1975.
Farajnia, S., Michel, S., Deboer, T., van der Leest, H. T., Houben, T., Rohling, J. H., Ramkisoensing, A., Yasenkov, R., & Meijer, J. H. (2012). Evidence for neuronal desynchrony in the aged suprachiasmatic nucleus clock. The Journal of Neuroscience, 32, 5891–5899. https://doi.org/10.1523/JNEUROSCI.0469-12.2012.
Fernandez, F. X., Kaladchibachi, S., & Negelspach, D. C. (2021). Resilience in the suprachiasmatic nucleus: Implications for aging and Alzheimer's disease. Experimental Gerontology, 147, 111258. https://doi.org/10.1016/j.exger.2021.111258.
Finger, A. M., & Kramer, A. (2021). Mammalian circadian systems: Organization and modern life challenges. Acta Physiologica (Oxford, England), 231, e13548. https://doi.org/10.1111/apha.13548.
Held, N. M., Buijink, M. R., Elfrink, H. L., Kooijman, S., Janssens, G. E., Luyf, A. C. M., Pras‐Raves, M. L., Vaz, F. M., Michel, S., Houtkooper, R. H., & van Weeghel, M. (2021). Aging selectively dampens oscillation of lipid abundance in white and brown adipose tissue. Scientific Reports, 11, 5932. https://doi.org/10.1038/s41598-021-85455-4.
Hofer, S. J., Simon, A. K., Bergmann, M., Eisenberg, T., Kroemer, G., & Madeo, F. (2022). Mechanisms of spermidine‐induced autophagy and geroprotection. Nature Aging, 2, 1112–1129. https://doi.org/10.1038/s43587-022-00322-9.
Hood, S., & Amir, S. (2017). The aging clock: Circadian rhythms and later life. The Journal of Clinical Investigation, 127, 437–446. https://doi.org/10.1172/JCI90328.
Houtkooper, R. H., Argmann, C., Houten, S. M., Cantó, C., Jeninga, E. H., Andreux, P. A., Thomas, C., Doenlen, R., Schoonjans, K., & Auwerx, J. (2011). The metabolic footprint of aging in mice. Scientific Reports, 1, 134. https://doi.org/10.1038/srep00134.
Kalsbeek, A., & Buijs, R. M. (2002). Output pathways of the mammalian suprachiasmatic nucleus: Coding circadian time by transmitter selection and specific targeting. Cell and Tissue Research, 309, 109–118. https://doi.org/10.1007/s00441-002-0577-0.
Kalsbeek, A., La Fleur, S., Van Heijningen, C., & Buijs, R. M. (2004). Suprachiasmatic GABAergic inputs to the paraventricular nucleus control plasma glucose concentrations in the rat via sympathetic innervation of the liver. The Journal of Neuroscience, 24, 7604–7613. https://doi.org/10.1523/JNEUROSCI.5328-03.2004.
Kalsbeek, A., Yi, C. X., La Fleur, S. E., & Fliers, E. (2010). The hypothalamic clock and its control of glucose homeostasis. Trends in Endocrinology and Metabolism, 21, 402–410. https://doi.org/10.1016/j.tem.2010.02.005.
Kasukawa, T., Sugimoto, M., Hida, A., Minami, Y., Mori, M., Honma, S., Honma, K., Mishima, K., Soga, T., & Ueda, H. R. (2012). Human blood metabolite timetable indicates internal body time. Proceedings of the National Academy of Sciences of the United States of America, 109, 15036–15041. https://doi.org/10.1073/pnas.1207768109.
Kervezee, L., Cermakian, N., & Boivin, D. B. (2019). Individual metabolomic signatures of circadian misalignment during simulated night shifts in humans. PLoS Biology, 17, e3000303. https://doi.org/10.1371/journal.pbio.3000303.
Kervezee, L., Cuesta, M., Cermakian, N., & Boivin, D. B. (2018). Simulated night shift work induces circadian misalignment of the human peripheral blood mononuclear cell transcriptome. Proceedings of the National Academy of Sciences of the United States of America, 115, 5540–5545. https://doi.org/10.1073/pnas.1720719115.
Kolker, D. E., Fukuyama, H., Huang, D. S., Takahashi, J. S., Horton, T. H., & Turek, F. W. (2003). Aging alters circadian and light‐induced expression of clock genes in golden hamsters. Journal of Biological Rhythms, 18, 159–169. https://doi.org/10.1177/0748730403251802.
Lai, Y., Liu, C. W., Yang, Y., Hsiao, Y. C., Ru, H., & Lu, K. (2021). High‐coverage metabolomics uncovers microbiota‐driven biochemical landscape of interorgan transport and gut‐brain communication in mice. Nature Communications, 12, 6000. https://doi.org/10.1038/s41467-021-26209-8.
Lawton, K. A., Berger, A., Mitchell, M., Milgram, K. E., Evans, A. M., Guo, L., Hanson, R. W., Kalhan, S. C., Ryals, J. A., & Milburn, M. V. (2008). Analysis of the adult human plasma metabolome. Pharmacogenomics, 9, 383–397. https://doi.org/10.2217/14622416.9.4.383.
Lee, W., Milewski, T. M., Dwortz, M. F., Young, R. L., Gaudet, A. D., Fonken, L. K., Champagne, F. A., & Curley, J. P. (2022). Distinct immune and transcriptomic profiles in dominant versus subordinate males in mouse social hierarchies. Brain, Behavior, and Immunity, 103, 130–144. https://doi.org/10.1016/j.bbi.2022.04.015.
Leng, Y., Musiek, E. S., Hu, K., Cappuccio, F. P., & Yaffe, K. (2019). Association between circadian rhythms and neurodegenerative diseases. Lancet Neurology, 18, 307–318. https://doi.org/10.1016/S1474-4422(18)30461-7.
Lu, Q., & Kim, J. Y. (2022). Mammalian circadian networks mediated by the suprachiasmatic nucleus. The FEBS Journal, 289, 6589–6604. https://doi.org/10.1111/febs.16233.
Madeo, F., Eisenberg, T., Pietrocola, F., & Kroemer, G. (2018). Spermidine in health and disease. Science, 359(6374):eaan2788. https://doi.org/10.1126/science.aan2788.
Mathers, C. D., Stevens, G. A., Boerma, T., White, R. A., & Tobias, M. I. (2015). Causes of international increases in older age life expectancy. Lancet, 385, 540–548. https://doi.org/10.1016/S0140-6736(14)60569-9.
Mauvoisin, D., Wang, J., Jouffe, C., Martin, E., Atger, F., Waridel, P., Quadroni, M., Gachon, F., & Naef, F. (2014). Circadian clock‐dependent and ‐independent rhythmic proteomes implement distinct diurnal functions in mouse liver. Proceedings of the National Academy of Sciences of the United States of America, 111, 167–172. https://doi.org/10.1073/pnas.1314066111.
Nakamura, T. J., Nakamura, W., Yamazaki, S., Kudo, T., Cutler, T., Colwell, C. S., & Block, G. D. (2011). Age‐related decline in circadian output. The Journal of Neuroscience, 31, 10201–10205. https://doi.org/10.1523/JNEUROSCI.0451-11.2011.
Nishimura, K., Shiina, R., Kashiwagi, K., & Igarashi, K. (2006). Decrease in polyamines with aging and their ingestion from food and drink. Journal of Biochemistry, 139, 81–90. https://doi.org/10.1093/jb/mvj003.
Panagiotou, M., Vyazovskiy, V. V., Meijer, J. H., & Deboer, T. (2017). Differences in electroencephalographic non‐rapid‐eye movement sleep slow‐wave characteristics between young and old mice. Scientific Reports, 7, 43656. https://doi.org/10.1038/srep43656.
Panyard, D. J., Yu, B., & Snyder, M. P. (2022). The metabolomics of human aging: Advances, challenges, and opportunities. Science Advances, 8, eadd6155. https://doi.org/10.1126/sciadv.add6155.
Pelikan, A., Herzel, H., Kramer, A., & Ananthasubramaniam, B. (2022). Venn diagram analysis overestimates the extent of circadian rhythm reprogramming. The FEBS Journal, 289, 6605–6621. https://doi.org/10.1111/febs.16095.
Plenis, A., Oledzka, I., Kowalski, P., Miekus, N., & Baczek, T. (2019). Recent trends in the quantification of biogenic amines in biofluids as biomarkers of various disorders: A review. Journal of Clinical Medicine, 8, 640. https://doi.org/10.3390/jcm8050640.
R Core Team. (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Rahman, S. A., Gathungu, R. M., Marur, V. R., St Hilaire, M. A., Scheuermaier, K., Belenky, M., Struble, J. S., Czeisler, C. A., Lockley, S. W., Klerman, E. B., Duffy, J. F., & Kristal, B. S. (2023). Age‐related changes in circadian regulation of the human plasma lipidome. Communications Biology, 6, 756. https://doi.org/10.1038/s42003-023-05102-8.
Rui, L. (2014). Energy metabolism in the liver. Comprehensive Physiology, 4, 177–197. https://doi.org/10.1002/cphy.c130024.
Santin, Y., Resta, J., Parini, A., & Mialet‐Perez, J. (2021). Monoamine oxidases in age‐associated diseases: New perspectives for old enzymes. Ageing Research Reviews, 66, 101256. https://doi.org/10.1016/j.arr.2021.101256.
Sato, S., Solanas, G., Peixoto, F. O., Bee, L., Symeonidi, A., Schmidt, M. S., Brenner, C., Masri, S., Benitah, S. A., & Sassone‐Corsi, P. (2017). Circadian reprogramming in the liver identifies metabolic pathways of aging. Cell, 170, 664–677.e11. https://doi.org/10.1016/j.cell.2017.07.042.
Schilperoort, M., van den Berg, R., Bosmans, L. A., van Os, B. W., Dolle, M. E. T., Smits, N. A. M., Guichelaar, T., van Baarle, D., Koemans, L., Berbee, J. F. P., Deboer, T., Meijer, J. H., de Vries, M. R., Vreeken, D., van Gils, J. M., Willems van Dijk, K., van Kerkhof, L. W. M., Lutgens, E., Biermasz, N. R., … Kooijman, S. (2020). Disruption of circadian rhythm by alternating light‐dark cycles aggravates atherosclerosis development in APOE*3‐Leiden.CETP mice. Journal of Pineal Research, 68, e12614. https://doi.org/10.1111/jpi.12614.
Skene, D. J., Skornyakov, E., Chowdhury, N. R., Gajula, R. P., Middleton, B., Satterfield, B. C., Porter, K. I., Van Dongen, H. P. A., & Gaddameedhi, S. (2018). Separation of circadian‐ and behavior‐driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism. Proceedings of the National Academy of Sciences of the United States of America, 115, 7825–7830. https://doi.org/10.1073/pnas.1801183115.
Srivastava, S. (2019). Emerging insights into the metabolic alterations in aging using metabolomics. Metabolites, 9, 301. https://doi.org/10.3390/metabo9120301.
Toledo, J. B., Arnold, M., Kastenmuller, G., Chang, R., Baillie, R. A., Han, X., Thambisetty, M., Tenenbaum, J. D., Suhre, K., Thompson, J. W., John‐Williams, L. S., MahmoudianDehkordi, S., Rotroff, D. M., Jack, J. R., Motsinger‐Reif, A., Risacher, S. L., Blach, C., Lucas, J. E., Massaro, T., … Alzheimer's Disease Neuroimaging Initiative and the Alzheimer Disease Metabolomics Consortium. (2017). Metabolic network failures in Alzheimer's disease: A biochemical road map. Alzheimers Dement, 13, 965–984. https://doi.org/10.1016/j.jalz.2017.01.020.
Wikoff, W. R., Anfora, A. T., Liu, J., Schultz, P. G., Lesley, S. A., Peters, E. C., & Siuzdak, G. (2009). Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proceedings of the National Academy of Sciences of the United States of America, 106, 3698–3703. https://doi.org/10.1073/pnas.0812874106.
Woelders, T., Revell, V. L., Middleton, B., Ackermann, K., Kayser, M., Raynaud, F. I., Skene, D. J., & Hut, R. A. (2023). Machine learning estimation of human body time using metabolomic profiling. Proceedings of the National Academy of Sciences of the United States of America, 120, e2212685120. https://doi.org/10.1073/pnas.2212685120.
Wolff, C. A., Gutierrez‐Monreal, M. A., Meng, L., Zhang, X., Douma, L. G., Costello, H. M., Douglas, C. M., Ebrahimi, E., Pham, A., Oliveira, A. C., Fu, C., Nguyen, A., Alava, B. R., Hesketh, S. J., Morris, A. R., Endale, M. M., Crislip, G. R., Cheng, K. Y., Schroder, E. A., … Esser, K. A. (2023). Defining the age‐dependent and tissue‐specific circadian transcriptome in male mice. Cell Reports, 42, 111982. https://doi.org/10.1016/j.celrep.2022.111982.
Wu, G. (2009). Amino acids: Metabolism, functions, and nutrition. Amino Acids, 37, 1–17. https://doi.org/10.1007/s00726-009-0269-0.
Xin, H., Deng, F., Zhou, M., Huang, R., Ma, X., Tian, H., Tan, Y., Chen, X., Deng, D., Shui, G., Zhang, Z., & Li, M. D. (2021). A multi‐tissue multi‐omics analysis reveals distinct kinetics in entrainment of diurnal transcriptomes by inverted feeding. iScience, 24, 102335. https://doi.org/10.1016/j.isci.2021.102335.
Yamazaki, S., Straume, M., Tei, H., Sakaki, Y., Menaker, M., & Block, G. D. (2002). Effects of aging on central and peripheral mammalian clocks. Proceedings of the National Academy of Sciences of the United States of America, 99, 10801–10806. https://doi.org/10.1073/pnas.152318499.
Zierer, J., Menni, C., Kastenmuller, G., & Spector, T. D. (2015). Integration of ‘omics’ data in aging research: From biomarkers to systems biology. Aging Cell, 14, 933–944. https://doi.org/10.1111/acel.12386.
Zwighaft, Z., Aviram, R., Shalev, M., Rousso‐Noori, L., Kraut‐Cohen, J., Golik, M., Brandis, A., Reinke, H., Aharoni, A., Kahana, C., & Asher, G. (2015). Circadian clock control by polyamine levels through a mechanism that declines with age. Cell Metabolism, 22, 874–885. https://doi.org/10.1016/j.cmet.2015.09.011.

2020-09150161910128 Netherlands Organisation for Health Research and Development; 12191 Dutch Technology Foundation; 834513/EC International ERC_ European Research Council; 1292.19.077 Netherlands NWO_ Dutch Research Council

Keywords: ageing; amine metabolism; chronobiology; circadian rhythms; hypothalamus; liver; metabolomics; plasma

0 (Amines)

Date Created: 20240527 Date Completed: 20240720 Latest Revision: 20240720

20240720

10.1111/ejn.16428

38802069