Complexity of Brain Dynamics as a Correlate of Consciousness in Anaesthetized Monkeys

• Bademosi, A. T., Steeves, J., Karunanithi, S., Zalucki, O. H., Gormal, R. S., Liu, S., Lauwers, E., Verstreken, P., Anggono, V., Meunier, F. A. et al. (2018). Trapping of syntaxin1a in presynaptic nanoclusters by a clinically relevant general anesthetic. Cell Reports, 22, 427–440.

• Bandt, C. (2017). A new kind of permutation entropy used to classify sleep stages from invisible EEG microstructure. Entropy, 19, 197.

  Article  Google Scholar 

• Bandt, C., & Pompe, B. (2002). Permutation entropy: a natural complexity measure for time series. Physical review letters, 88, 174102.

• Berger, H. (1929). Über das elektroenkephalogramm des menschen. Archiv für psychiatrie und nervenkrankheiten, 87, 527–570.

  Article  Google Scholar 

• Bonhomme, V., Vanhaudenhuyse, A., Demertzi, A., Bruno, M.-A., Jaquet, O., Bahri, M., Plenevaux, A., Boly, M., Boveroux, P., Soddu, A. et al. (2016). Resting-state network-specific breakdown of functional connectivity during ketamine alteration of consciousness in volunteers. Anesthesiology, 125, 873–888.

• Brake, N., Duc, F., Rokos, A., Arseneau, F., Shahiri, S., Khadra, A., & Plourde, G. (2021). Aperiodic eeg activity masks the dynamics of neural oscillations during loss of consciousness from propofol. bioRxiv.

• Brown, E., Purdon, P. L., & Van Dort, C. J. (2011). General anesthesia and altered states of arousal: a systems neuroscience analysis. Annual review of neuroscience, 34, 601–628.

  Article  CAS  PubMed  PubMed Central  Google Scholar 

• Bruhn, J., Röpcke, H., & Hoeft, A. (2000). Approximate entropy as an electroencephalographic measure of anesthetic drug effect during desflurane anesthesia. The Journal of the American Society of Anesthesiologists, 92, 715–726.

  CAS  Google Scholar 

• Carhart-Harris, R. L., & Friston, K. (2019). Rebus and the anarchic brain: toward a unified model of the brain action of psychedelics. Pharmacological reviews, 71, 316–344.

  Article  CAS  PubMed  PubMed Central  Google Scholar 

• Carhart-Harris, R. L., Leech, R., Hellyer, P. J., Shanahan, M., F., A., Tagliazucchi, E., Chialvo, D. R., & Nutt, D. (2014). The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs. Frontiers in human neuroscience, 8, 20.

• Casali, A., Gosseries, O., Rosanova, M., Boly, M., Sarasso, S., Casali, K., Casarotto, S., Bruno, M., Laureys, S., Tononi, G. et al. (2013). A theoretically based index of consciousness independent of sensory processing and behavior. Science translational medicine, 5, 198ra105–198ra105.

• Cascella, M., Bimonte, S., & Muzio, M. R. (2018). Towards a better understanding of anesthesia emergence mechanisms: Research and clinical implications. World journal of methodology, 8, 9.

  Article  PubMed  PubMed Central  Google Scholar 

• Colombo, M., Napolitani, M., Boly, M., Gosseries, O., Casarotto, S., Rosanova, M., Brichant, J.-F., Boveroux, P., Rex, S., Laureys, S. et al. (2019). The spectral exponent of the resting eeg indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine. Neuroimage, 189, 631–644.

• Cover, T. M., & Thomas, J. A. (2006). Elements of Information Theory. (2nd ed.). John Wiley & Sons.

• Domino, E., Chodoff, P., & Corssen, G. (1965). Pharmacologic effects of ci-581, a new dissociative anesthetic, in man. Clinical Pharmacology & Therapeutics, 6, 279–291.

  Article  CAS  Google Scholar 

• Ferenets, R., Vanluchene, A., Lipping, T., Heyse, B., & Struys, M. (2007). Behavior of entropy/complexity measures of the electroencephalogram during propofol-induced sedation: dose-dependent effects of remifentanil. The Journal of the American Society of Anesthesiologists, 106, 696–706.

  CAS  Google Scholar 

• Feshchenko, V., Veselis, R., & Reinsel, R. (2004). Propofol-induced alpha rhythm. Neuropsychobiology, 50, 257–266.

  Article  CAS  PubMed  Google Scholar 

• Fisher, R. A. (1922). On the mathematical foundations of theoretical statistics. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 222, 309–368.

  Google Scholar 

• Franks, N. (2006). Molecular targets underlying general anaesthesia. British journal of pharmacology, 147, S72–S81.

  Article  CAS  PubMed  PubMed Central  Google Scholar 

• Frieden, B. R. (2004). Science from Fisher information: a unification. Cambridge University Press.

  Book  Google Scholar 

• Grandjean, J., Schroeter, A., Batata, I., & Rudin, M. (2014). Optimization of anesthesia protocol for resting-state fmri in mice based on differential effects of anesthetics on functional connectivity patterns. Neuroimage, 102, 838–847.

  Article  PubMed  Google Scholar 

• Gugino, L., Chabot, R., Prichep, L., John, E., Formanek, V., & Aglio, L. (2001). Quantitative eeg changes associated with loss and return of consciousness in healthy adult volunteers anaesthetized with propofol or sevoflurane. British journal of anaesthesia, 87, 421–428.

  Article  CAS  PubMed  Google Scholar 

• Hahn, G., Zamora-López, G., Uhrig, L., Tagliazucchi, E., Laufs, H., Mantini, D., Kringelbach, M., Jarraya, B., & Deco, G. (2021). Signature of consciousness in brain-wide synchronization patterns of monkey and human fmri signals. NeuroImage, 226, 117470.

• Hansson, M., Gansler, T., & Salomonsson, G. (1998). A system for tracking changes in the mid-latency evoked potential during anesthesia. IEEE transactions on biomedical engineering, 45, 323–334.

  Article  CAS  PubMed  Google Scholar 

• Hantal, G., Fábián, B., Sega, M., Jójárt, B., & Jedlovszky, P. (2019). Effect of general anesthetics on the properties of lipid membranes of various compositions. Biochimica et Biophysica Acta (BBA)-Biomembranes, 1861, 594–609.

• Hemmings J., H. C., Riegelhaupt, P. M., Kelz, M. B., Solt, K., Eckenhoff, R. G., Orser, B. A., & Goldstein, P. A. (2019). Towards a comprehensive understanding of anesthetic mechanisms of action: a decade of discovery. Trends in pharmacological sciences, 40, 464–481.

• Hong, L., Summerfelt, A., Buchanan, R., O’donnell, P., Thaker, G., Weiler, M., & Lahti, A. (2010). Gamma and delta neural oscillations and association with clinical symptoms under subanesthetic ketamine. Neuropsychopharmacology, 35, 632–640.

• Hudetz, A. G., Liu, X., Pillay, S., Boly, M., & Tononi, G. (2016). Propofol anesthesia reduces lempel-ziv complexity of spontaneous brain activity in rats. Neuroscience letters, 628, 132–135.

  Article  CAS  PubMed  PubMed Central  Google Scholar 

• Hunt, M., Raynaud, B., & Garcia, R. (2006). Ketamine dose-dependently induces high-frequency oscillations in the nucleus accumbens in freely moving rats. Biological psychiatry, 60, 1206–1214.

  Article  CAS  PubMed  Google Scholar 

• Ibáñez-Molina, A., Iglesias-Parro, S., Soriano, M., & Aznarte, J. (2015). Multiscale lempel-ziv complexity for eeg measures. Clinical Neurophysiology, 126, 541–548.

  Article  PubMed  Google Scholar 

• Jensen, E. W., Litvan, H., Struys, M., & Vazquez, P. M. (2004). Pitfalls and challenges when assessing the depth of hypnosis during general anaesthesia by clinical signs and electronic indices. Acta anaesthesiologica scandinavica, 48, 1260–1267.

  Article  CAS  PubMed  Google Scholar 

• Kaspar, F., & Schuster, H. G. (1987). Easily calculable measure for the complexity of spatiotemporal patterns. Physical Review A, 36, 842.

  Article  CAS  Google Scholar 

• Keller, K., Mangold, T., Stolz, I., & Werner, J. (2017). Permutation entropy: New ideas and challenges. Entropy, 19, 134.

  Article  Google Scholar 

• Khan, K. S., Hayes, I., & Buggy, D. J. (2014). Pharmacology of anaesthetic agents i: intravenous anaesthetic agents. Continuing Education in Anaesthesia, Critical Care & Pain, 14, 100–105.

  Article  Google Scholar 

• Kim, H., Moon, J.-Y., Mashour, G. A., & Lee, U. (2018). Mechanisms of hysteresis in human brain networks during transitions of consciousness and unconsciousness: Theoretical principles and empirical evidence. PLoS computational biology, 14, e1006424.

• Kitazono, J., Kanai, R., & Oizumi, M. (2018). Efficient algorithms for searching the minimum information partition in integrated information theory. Entropy, 20, 173.

  Article  PubMed Central  Google Scholar 

• Kocsis, B., Brown, R., McCarley, R., & Hajos, M. (2013). Impact of ketamine on neuronal network dynamics: Translational modeling of schizophrenia-relevant deficits. CNS Neuroscience & Therapeutics, 19, 437–447.

  Article  CAS  Google Scholar 

• Krystal, J. H., Karper, L. P., Seibyl, J. P., Freeman, G. K., Delaney, R., Bremner, J. D., Heninger, G. R., Bowers, M. B., & Charney, D. S. (1994). Subanesthetic effects of the noncompetitive nmda antagonist, ketamine, in humans: psychotomimetic, perceptual, cognitive, and neuroendocrine responses. Archives of General Psychiatry, 51, 199–214.

• Krzemiński, D., Kamiński, M., Marchewka, A., & Bola, M. (2017). Breakdown of long-range temporal correlations in brain oscillations during general anesthesia. Neuroimage, 159, 146–158.

  Article  PubMed  Google Scholar 

• Kuo, C., & Liang, S. (2011). Automatic stage scoring of single-channel sleep eeg based on multiscale permutation entropy. In 2011 IEEE Biomedical Circuits and Systems Conference (BioCAS) (pp. 448–451). IEEE.

• Kushikata, T., & Hirota, K. (2014). Mechanisms of anesthetic emergence: evidence for active reanimation. Current Anesthesiology Reports, 4, 49–56.

  Article  Google Scholar 

• Lazarewicz, M., Ehrlichman, R., Maxwell, C., Gandal, M., Finkel, L. H., & Siegel, S. (2010). Ketamine modulates theta and gamma oscillations. Journal of Cognitive Neuroscience, 22, 1452–1464.

  Article  PubMed  Google Scholar 

• Lempel, A., & Ziv, J. (1976). On the complexity of finite sequences. IEEE Transactions on Information Theory, 22, 75–81.

  Article  Google Scholar 

• Lewis, L., Weiner, V., Mukamel, E., Donoghue, J., Eskandar, E., Madsen, J., Anderson, W., Hochberg, L., Cash, S., Brown, E. et al. (2012). Rapid fragmentation of neuronal networks at the onset of propofol-induced unconsciousness. Proceedings of the National Academy of Sciences, 109, E3377–E3386.

• Li, D., Li, X., Liang, Z., Voss, L. J., & Sleigh, J. W. (2010). Multiscale permutation entropy analysis of eeg recordings during sevoflurane anesthesia. Journal of Neural Engineering, 7, 046010.

• Li, X., Cui, S., & Voss, L. J. (2008). Using permutation entropy to measure the electroencephalographic effects of sevoflurane. The Journal of the American Society of Anesthesiologists, 109, 448–456.

  CAS  Google Scholar 

• Liang, Z., Wang, Y., Sun, X., Li, D., Voss, L. J., Sleigh, J. W., Hagihira, S., & Li, X. (2015). Eeg entropy measures in anesthesia. Frontiers in Computational Neuroscience, 9, 16.

• Liu, Q., Ma, L., Fan, S.-Z., Abbod, M. F., & Shieh, J.-S. (2018). Sample entropy analysis for the estimating depth of anaesthesia through human eeg signal at different levels of unconsciousness during surgeries. PeerJ, 6, e4817.

• Loomis, A. L., Harvey, E. N., & Hobart, G. A. (1937). Cerebral states during sleep, as studied by human brain potentials. Journal of Experimental Psychology, 21, 127.

  Article  Google Scholar 

• Luppi, A. I., Craig, M., Pappas, I., Finoia, P., Williams, G., Allanson, J., Pickard, J., Owen, A., Naci, L., Menon, D. et al. (2019). Consciousness-specific dynamic interactions of brain integration and functional diversity. Nature Communications, 10, 1–12.

• Mammone, N., & Morabito, F. C. (2011). Analysis of absence seizure eeg via permutation entropy spatio-temporal clustering. In The 2011 International Joint Conference on Neural Networks (pp. 1417–1422). IEEE.

• Martin, M. T., Plastino, A., & Rosso, O. A. (2006). Generalized statistical complexity measures: Geometrical and analytical properties. Physica A: Statistical Mechanics and its Applications, 369, 439–462.

  Article  Google Scholar 

• Mateos, D. M., Diaz, J. M., & Lamberti, P. W. (2014). Permutation entropy applied to the characterization of the clinical evolution of epileptic patients under pharmacologicaltreatment. Entropy, 16, 5668–5676.

  Article  Google Scholar 

• Mateos, D. M., Gómez-Ramírez, J., & Rosso, O. A. (2021). Using time causal quantifiers to characterize sleep stages. Chaos, Solitons & Fractals, 146, 110798.

• Mateos, D. M., Guevara Erra, R., Wennberg, R., & Perez Velazquez, J. L. (2018). Measures of entropy and complexity in altered states of consciousness. Cognitive Neurodynamics, 12, 73–84.

  Article  CAS  PubMed  Google Scholar 

• Mateos, D. M., Wennberg, R., Guevara Erra, R., & Perez Velazquez, J. L. (2017). Consciousness as a global property of brain dynamic activity. Physical Review E, 96, 062410.

• Mateos, D. M., Zozor, S., & Olivares, F. (2020). Contrasting stochasticity with chaos in a permutation lempel-ziv complexity–shannon entropy plane. Physica A: Statistical Mechanics and its Applications, 554, 124640.

• Mukamel, E., Wong, K., Prerau, M., Brown, E., & Purdon, P. (2011). Phase-based measures of cross-frequency coupling in brain electrical dynamics under general anesthesia. In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 1981–1984). IEEE.

• Mukamel, E. A., Pirondini, E., Babadi, B., Wong, K. K., Pierce, E., Harrell, P., Walsh, J., Salazar-Gomez, A., Cash, S., Eskandar, E. et al. (2014). A transition in brain state during propofol-induced unconsciousness. Journal of Neuroscience, 34, 839–845.

• Murphy, M., Bruno, M.-A., Riedner, B., Boveroux, P., Noirhomme, Q., Landsness, E., Brichant, J.-F., Phillips, C., Massimini, M., Laureys, S. et al. (2011). Propofol anesthesia and sleep: a high-density eeg study. Sleep, 34, 283–291.

• Muthukumaraswamy, S., Shaw, A., Jackson, L., Hall, J., Moran, R., & Saxena, N. (2015). Evidence that subanesthetic doses of ketamine cause sustained disruptions of nmda and ampa-mediated frontoparietal connectivity in humans. Journal of Neuroscience, 35, 11694–11706.

  Article  CAS  PubMed  Google Scholar 

• Nasrallah, F., Lew, S., Low, A.S.-M., & Chuang, K.-H. (2014). Neural correlate of resting-state functional connectivity under a2 adrenergic receptor agonist, medetomidine. Neuroimage, 84, 27–34.

  Article  PubMed  Google Scholar 

• Nasrallah, F., Tan, J., & Chuang, K.-H. (2012). Pharmacological modulation of functional connectivity: a2-adrenergic receptor agonist alters synchrony but not neural activation. Neuroimage, 60, 436–446.

  Article  CAS  PubMed  Google Scholar 

• Nicol, A., & Morton, A. (2020). Characteristic patterns of eeg oscillations in sheep (ovis aries) induced by ketamine may explain the psychotropic effects seen in humans. Scientific reports, 10, 1–10.

  Article  Google Scholar 

• Nicolaou, N., & Georgiou, J. (2011). The use of permutation entropy to characterize sleep electroencephalograms. Clinical EEG and Neuroscience, 42, 24–28.

  Article  CAS  PubMed  Google Scholar 

• Oizumi, M., Amari, S., Yanagawa, T., Fujii, N., & Tsuchiya, N. (2016). Measuring integrated information from the decoding perspective. PLoS Computational Biology, 12, e1004654.

• Pennini, F., & Plastino, A. (2005). Reciprocity relations between ordinary temperature and the Frieden-Soffer Fisher temperature. Physical Review E, 71, 47102.

  Article  CAS  Google Scholar 

• Purdon, P., Pierce, E., Mukamel, E., Prerau, M., Walsh, J., Wong, K., Salazar-Gomez, A., Harrell, P., Sampson, A. L., Cimenser, A. et al. (2013). Electroencephalogram signatures of loss and recovery of consciousness from propofol. Proceedings of the National Academy of Sciences, 110, E1142–E1151.

• Quintero-Quiroz, C., Montesano, A. J., L.and Pons, Torrent, M. C., García-Ojalvo, J., & Masoller, C. (2018). Differentiating resting brain states using ordinal symbolic analysis. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28, 106307.

• Rivolta, D., Sauer, A. H. T., & et al. (2012). Effect of ketamine on gamma-band oscillation in MEG-data a comparison with schizofrenia. In Society of neuroscience, Abstrac (p. 38).

• Rosso, O. A., Larrondo, H. A., Martin, M. T., Plastino, A., & Fuentes, M. A. (2007). Distinguishing noise from chaos. Physical Review Letters, 99, 154102.

• Saba, W., Goutal, S., Kuhnast, B., Dollé, F., Auvity, S., Fontyn, Y., Cayla, J., Peyronneau, M.-A., Valette, H., & Tournier, N. (2015). Differential influence of propofol and isoflurane anesthesia in a non-human primate on the brain kinetics and binding of [18f]DPA-714, a positron emission tomography imaging marker of glial activation. European Journal of Neuroscience, 42, 1738–1745.

• Sánchez-Moreno, P., Yánez, R., & Dehesa, J. (2009). Discrete densities and Fisher information. In Proceedings of the 14th International Conference on Difference Equations and Applications. Difference Equations and Applications. Istanbul, Turkey: Bahçesehir University Press (pp. 291–298).

• Sarasso, S., Boly, M., Napolitani, M., Gosseries, O., Charland-Verville, V., Casarotto, S., Rosanova, M., Casali, A. G., Brichant, J., Boveroux, P. et al. (2015). Consciousness and complexity during unresponsiveness induced by propofol, xenon, and ketamine. Current Biology, 25, 3099–3105.

• Sarasso, S., Casali, A. G., Casarotto, S., Rosanova, M., Sinigaglia, C., & Massimini, M. (2021). Consciousness and complexity: A consilience of evidence. Neuroscience of Consciousness, 7, 1–24.

  Google Scholar 

• Schartner, M., Seth, A., Noirhomme, Q., Boly, M., Bruno, M., Laureys, S., & Barrett, A. (2015). Complexity of multi-dimensional spontaneous eeg decreases during propofol induced general anaesthesia. PLoS One, 10, e0133532.

• Schartner, M. M., Carhart-Harris, R. L., Barrett, A. B., Seth, A. K., & Muthukumaraswamy, S. D. (2017). Increased spontaneous meg signal diversity for psychoactive doses of ketamine, lsd and psilocybin. Scientific Reports, 7, 1–12.

• Scheidegger, M., Walter, M., Lehmann, M., Metzger, C., Grimm, S., Boeker, H., Boesiger, P., Henning, A., & Seifritz, E. (2012). Ketamine decreases resting state functional network connectivity in healthy subjects: implications for antidepressant drug action.

• Senior, C., Russell, T., Gazzaniga, M. S., & Raessens, J. (2006). Methods in mind. MIT press.

• Shannon, C. E., & Weaver, W. (1998). The mathematical theory of communication. University of Illinois press.

• Shaw, A., Saxena, N., Jackson, L., Hall, J., Singh, K., & Muthukumaraswamy, S. (2015). Ketamine amplifies induced gamma frequency oscillations in the human cerebral cortex. European Neuropsychopharmacology, 25, 1136–1146.

  Article  CAS  PubMed  Google Scholar 

• Shumbayawonda, E., Tosun, P. D., Fernández, A., Hughes, M. P., & Abásolo, D. (2018). Complexity changes in brain activity in healthy ageing: A permutation lempel-ziv complexity study of magnetoencephalograms. Entropy, 20, 506.

  Article  PubMed Central  Google Scholar 

• Soriano, M. C., Zunino, L., Rosso, O. A., Fischer, I., & Mirasso, C. R. (2011). Time scales of a chaotic semiconductor laser with optical feedback under the lens of a permutation information analysis. IEEE Journal of Quantum Electronics, 47, 252–261.

  Article  CAS  Google Scholar 

• Todd, M. M. (1998). EEGs, EEG processing, and the bispectral index. The Journal of the American Society of Anesthesiologists, 89, 815–817.

  CAS  Google Scholar 

• Toker, D., Pappas, I., Lendner, J., Frohlich, J., Mateos, D., Muthukumaraswamy, S., Carhart-Harris, R., Paff, M., Vespa, P., Monti, M. et al. (2021). Consciousness is supported by near-critical cortical electrodynamics. bioRxiv.

• Tononi, G., & Edelman, G. (1998). Consciousness and complexity. Science, 282, 1846–1851.

  Article  CAS  PubMed  Google Scholar 

• Varley, T., Denny, V., Sporns, O., & Patania, A. (2020). Topological analysis of differential effects of ketamine and propofol anaesthesia on brain dynamics. Royal Society Open Science, 8, 201971.

• Varnäs, K., Finnema, S., Johnström, P., Arakawa, R., Halldin, C., Eriksson, L., & Farde, L. (2021). Effects of sevoflurane anaesthesia on radioligand binding to monoamine oxidase-b in vivo. British Journal of Anaesthesia, 126, 238–244.

• Xu, J., Zheng, C., Jing, G., & Lu, D. (2004). Monitoring depth of anesthesia based on complexity of electroencephalogram. In IEEE International Workshop on Biomedical Circuits and Systems, 2004. (pp. S2–5). IEEE.

• Yanagawa, T., Chao, Z., Hasegawa, N., & Fujii, N. (2013a). Large-scale information flow in conscious and unconscious states: an ecog study in monkeys. PLoS One, 8, e80845.

• Yanagawa, T., Chao, Z., Hasegawa, N., & Fujii, N. (2013b). Large-scale information flow in conscious and unconscious states: an ecog study in monkeys. PLoS One, 8, e80845.

• Zanin, M., Zunino, L., Rosso, O. A., & Papo, D. (2012). Permutation entropy and its main biomedical and econophysics applications: a review. Entropy, 14, 1553–1577.

  Article  Google Scholar 

• Zanos, P., Moaddel, R., Morris, P. J., Riggs, L. M., Highland, J. N., Georgiou, P., Pereira, E., Albuquerque, E. X., Thomas, C. J., Zarate, C. A. et al. (2018). Ketamine and ketamine metabolite pharmacology: insights into therapeutic mechanisms. Pharmacological reviews, 70, 621–660.

• Zhang, X.-S., Roy, R. J., & Jensen, E. W. (2001). Eeg complexity as a measure of depth of anesthesia for patients. IEEE transactions on biomedical engineering, 48, 1424–1433.

  Article  CAS  PubMed  Google Scholar 

• Zozor, S., Mateos, D. M., & Lamberti, P. W. (2014). Mixing Bandt-Pompe and Lempel-Ziv approaches: another way to analyze the complexity of continuous-state sequences. The European Physical Journal B, 87, 107.

  Article  Google Scholar 

• Zunino, L., Soriano, M. C., Fischer, I., Rosso, O. A., & Mirasso, C. R. (2010). Permutation-information-theory approach to unveil delay dynamics from time-series analysis. Physical Review E, 82, 46212.

  Article  CAS  Google Scholar 

• Zunino, L., Soriano, M. C., & Rosso, O. A. (2012). Distinguishing chaotic and stochastic dynamics from time series by using a multiscale symbolic approach. Physical Review E, 86, 46210.

  Article  CAS  Google Scholar 

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