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Pascovich C, Serantes D, Rodriguez A, Mateos D, González J, Gallo D, Rivas M, Devera A, Lagos P, Rubido N, Torterolo P. Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures. PLoS Comput Biol 2024; 20:e1012111. [PMID: 38805554 PMCID: PMC11161118 DOI: 10.1371/journal.pcbi.1012111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 06/07/2024] [Accepted: 04/25/2024] [Indexed: 05/30/2024] Open
Abstract
The dorsal (DRN) and median (MRN) raphe are important nuclei involved in similar functions, including mood and sleep, but playing distinct roles. These nuclei have a different composition of neuronal types and set of neuronal connections, which among other factors, determine their neuronal dynamics. Most works characterize the neuronal dynamics using classic measures, such as using the average spiking frequency (FR), the coefficient of variation (CV), and action potential duration (APD). In the current study, to refine the characterization of neuronal firing profiles, we examined the neurons within the raphe nuclei. Through the utilization of nonlinear measures, our objective was to discern the redundancy and complementarity of these measures, particularly in comparison with classic methods. To do this, we analyzed the neuronal basal firing profile in both nuclei of urethane-anesthetized rats using the Shannon entropy (Bins Entropy) of the inter-spike intervals, permutation entropy of ordinal patterns (OP Entropy), and Permutation Lempel-Ziv Complexity (PLZC). Firstly, we found that classic (i.e., FR, CV, and APD) and nonlinear measures fail to distinguish between the dynamics of DRN and MRN neurons, except for the OP Entropy. We also found strong relationships between measures, including the CV with FR, CV with Bins entropy, and FR with PLZC, which imply redundant information. However, APD and OP Entropy have either a weak or no relationship with the rest of the measures tested, suggesting that they provide complementary information to the characterization of the neuronal firing profiles. Secondly, we studied how these measures are affected by the oscillatory properties of the firing patterns, including rhythmicity, bursting patterns, and clock-like behavior. We found that all measures are sensitive to rhythmicity, except for the OP Entropy. Overall, our work highlights OP Entropy as a powerful and useful quantity for the characterization of neuronal discharge patterns.
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Affiliation(s)
- Claudia Pascovich
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
- Consciousness and Cognition Laboratory, Department of Psychology, King’s College, University of Cambridge, Cambridge, United Kingdom
| | - Diego Serantes
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Alejo Rodriguez
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Diego Mateos
- Achucarro Basque Center for Neuroscience, Leioa (Bizkaia), Spain
- Instituto de Matemática Aplicada del Litoral (IMAL-CONICET-UNL), Santa Fé, Argentina
- Universidad Autónoma de Entre Ríos (UADER), Oro Verde, Entre Ríos, Argentina
| | - Joaquín González
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Diego Gallo
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Mayda Rivas
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Andrea Devera
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Patricia Lagos
- Laboratory of Neuropeptide Transmission, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
| | - Nicolás Rubido
- Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen, United Kingdom
| | - Pablo Torterolo
- Laboratory of Sleep Neurobiology, Department of Physiology, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay
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Nałęcz-Jawecki P, Gagliardi PA, Kochańczyk M, Dessauges C, Pertz O, Lipniacki T. The MAPK/ERK channel capacity exceeds 6 bit/hour. PLoS Comput Biol 2023; 19:e1011155. [PMID: 37216347 PMCID: PMC10237675 DOI: 10.1371/journal.pcbi.1011155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 06/02/2023] [Accepted: 05/04/2023] [Indexed: 05/24/2023] Open
Abstract
Living cells utilize signaling pathways to sense, transduce, and process information. As the extracellular stimulation often has rich temporal characteristics which may govern dynamic cellular responses, it is important to quantify the rate of information flow through the signaling pathways. In this study, we used an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter to assess the ability of the MAPK/ERK pathway to transduce signal encoded in a sequence of pulses. By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour. The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence. The high information transmission rate may enable the pathway to coordinate multiple processes including cell movement and respond to rapidly varying stimuli such as chemoattracting gradients created by other cells.
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Affiliation(s)
- Paweł Nałęcz-Jawecki
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | | | - Marek Kochańczyk
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
| | | | - Olivier Pertz
- Institute of Cell Biology, University of Bern, Bern, Switzerland
| | - Tomasz Lipniacki
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
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Zhu GY, Zhang RL, Chen YC, Liu YY, Liu DF, Wang SY, Jiang Y, Zhang JG. Characteristics of globus pallidus internus local field potentials in generalized dystonia patients with TWNK mutation. Clin Neurophysiol 2020; 131:1453-1461. [PMID: 32387964 DOI: 10.1016/j.clinph.2020.03.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 12/11/2019] [Accepted: 03/07/2020] [Indexed: 01/16/2023]
Abstract
OBJECTIVE We focused on a rare gene mutation causing dystonia in two siblings who received globus pallidus internus deep brain stimulation (GPi-DBS). The aim was to characterize the relationship between neuronal activity patterns and clinical syndromes. METHODS Whole exome sequencing was applied to identify the TWNK (previous symbol C10orf2) mutation; Two siblings with TWNK mutation presented as generalized dystonia with rigidity and bradykinesia; four other sporadic generalized dystonia patients underwent GPi-DBS and local field potentials (LFPs) were recorded. Oscillatory activities were illustrated with power spectra and temporal dynamics measured by the Lempel-Ziv complexity (LZC). RESULTS Normalized power spectra of GPi LFPs differed between patients with TWNK mutation and dystonia over the low beta bands. Patients with TWNK mutation had higher low beta power (15-27 Hz, unpaired t-test, corrected P < 0.0022) and lower LZC (15-27 Hz, unpaired t-test, P < 0.01) than other patients with generalized dystonia. On the other hand, the TWNK mutation patients showed decreased low frequency and beta oscillation in the GPi after DBS, as well as improved movement performance. CONCLUSION The LFPs were different in TWNK mutation dystonia siblings than other patients with generalized dystonia, which indicate the abnormal LFPs were related to symptoms rather than specific disease. In addition, the inhibited effect on oscillations also provided a potential evidence for DBS treatment on rare movement disorders. SIGNIFICANCE This study could potentially aid in the future development of adaptive DBS via rare disease LFPs comparison.
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Affiliation(s)
- Guan-Yu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Rui-Li Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Ying-Chuan Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yu-Ye Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - De-Feng Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shou-Yan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
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Pregowska A, Proniewska K, van Dam P, Szczepanski J. Using Lempel-Ziv complexity as effective classification tool of the sleep-related breathing disorders. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 182:105052. [PMID: 31476448 DOI: 10.1016/j.cmpb.2019.105052] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 08/14/2019] [Accepted: 08/24/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND OBJECTIVE People suffer from sleep disorders caused by work-related stress, irregular lifestyle or mental health problems. Therefore, development of effective tools to diagnose sleep disorders is important. Recently, to analyze biomedical signals Information Theory is exploited. We propose efficient classification method of sleep anomalies by applying entropy estimating algorithms to encoded ECGs signals coming from patients suffering from Sleep-Related Breathing Disorders (SRBD). METHODS First, ECGs were discretized using the encoding method which captures the biosignals variability. It takes into account oscillations of ECG measurements around signals averages. Next, to estimate entropy of encoded signals Lempel-Ziv complexity algorithm (LZ) which measures patterns generation rate was applied. Then, optimal encoding parameters, which allow distinguishing normal versus abnormal events during sleep with high sensitivity and specificity were determined numerically. Simultaneously, subjects' states were identified using acoustic signal of breathing recorded in the same period during sleep. RESULTS Random sequences show normalized LZ close to 1 while for more regular sequences it is closer to 0. Our calculations show that SRBDs have normalized LZ around 0.32 (on average), while control group has complexity around 0.85. The results obtained to public database are similar, i.e. LZ for SRBDs around 0.48 and for control group 0.7. These show that signals within the control group are more random whereas for the SRBD group ECGs are more deterministic. This finding remained valid for both signals acquired during the whole duration of experiment, and when shorter time intervals were considered. Proposed classifier provided sleep disorders diagnostics with a sensitivity of 93.75 and specificity of 73.00%. To validate our method we have considered also different variants as a training and as testing sets. In all cases, the optimal encoding parameter, sensitivity and specificity values were similar to our results above. CONCLUSIONS Our pilot study suggests that LZ based algorithm could be used as a clinical tool to classify sleep disorders since the LZ complexities for SRBD positives versus healthy individuals show a significant difference. Moreover, normalized LZ complexity changes are related to the snoring level. This study also indicates that LZ technique is able to detect sleep abnormalities in early disorders stage.
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Affiliation(s)
- Agnieszka Pregowska
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, 02-106 Warsaw, Poland
| | - Klaudia Proniewska
- Jagiellonian University Medical College, Lazarza 16, 31-530 Krakow, Poland
| | - Peter van Dam
- PEACS BV, Weyland 38 2415 BC Nieuwerbrug, the Netherlands
| | - Janusz Szczepanski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, 02-106 Warsaw, Poland.
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Zhu G, Geng X, Tan Z, Chen Y, Zhang R, Wang X, Aziz T, Wang S, Zhang J. Characteristics of Globus Pallidus Internus Local Field Potentials in Hyperkinetic Disease. Front Neurol 2018; 9:934. [PMID: 30455666 PMCID: PMC6230660 DOI: 10.3389/fneur.2018.00934] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Accepted: 10/15/2018] [Indexed: 01/26/2023] Open
Abstract
Background: Dystonia and Huntington's disease (HD) are both hyperkinetic movement disorders but exhibit distinct clinical characteristics. Aberrant output from the globus pallidus internus (GPi) is involved in the pathophysiology of both HD and dystonia, and deep brain stimulation (DBS) of the GPi shows good clinical efficacy in both disorders. The electrode externalized period provides an opportunity to record local field potentials (LFPs) from the GPi to examine if activity patterns differ between hyperkinetic disorders and are associated with specific clinical characteristics. Methods: LFPs were recorded from 7 chorea-dominant HD and nine cervical dystonia patients. Differences in oscillatory activities were compared by power spectrum and Lempel-Ziv complexity (LZC). The discrepancy band power ratio was used to control for the influence of absolute power differences between groups. We further identified discrepant frequency bands and frequency band ratios for each subject and examined the correlations with clinical scores. Results: Dystonia patients exhibited greater low frequency power (6–14 Hz) while HD patients demonstrated greater high-beta and low-gamma power (26–43 Hz) (p < 0.0298, corrected). United Huntington Disease Rating Scale chorea sub-score was positively correlated with 26–43 Hz frequency band power and negatively correlated with the 6–14 Hz/26–43 Hz band power ratio. Conclusion: Dystonia and HD are characterized by distinct oscillatory activity patterns, which may relate to distinct clinical characteristics. Specifically, chorea may be related to elevated high-beta and low-gamma band power, while dystonia may be related to elevated low frequency band power. These LFPs may be useful biomarkers for adaptive DBS to treat hyperkinetic diseases.
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Affiliation(s)
- Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xinyi Geng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Zheng Tan
- Department of Psychology, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Yingchuan Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ruili Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tipu Aziz
- Medical Sciences Division, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Shouyan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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Characterisation of the Effects of Sleep Deprivation on the Electroencephalogram Using Permutation Lempel–Ziv Complexity, a Non-Linear Analysis Tool. ENTROPY 2017. [DOI: 10.3390/e19120673] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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Pregowska A, Szczepanski J, Wajnryb E. Temporal code versus rate code for binary Information Sources. Neurocomputing 2016. [DOI: 10.1016/j.neucom.2016.08.034] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Pregowska A, Szczepanski J, Wajnryb E. Mutual information against correlations in binary communication channels. BMC Neurosci 2015; 16:32. [PMID: 25986973 PMCID: PMC4445332 DOI: 10.1186/s12868-015-0168-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2014] [Accepted: 04/21/2015] [Indexed: 11/25/2022] Open
Abstract
Background Explaining how the brain processing is so fast remains an open problem (van Hemmen JL, Sejnowski T., 2004). Thus, the analysis of neural transmission (Shannon CE, Weaver W., 1963) processes basically focuses on searching for effective encoding and decoding schemes. According to the Shannon fundamental theorem, mutual information plays a crucial role in characterizing the efficiency of communication channels. It is well known that this efficiency is determined by the channel capacity that is already the maximal mutual information between input and output signals. On the other hand, intuitively speaking, when input and output signals are more correlated, the transmission should be more efficient. A natural question arises about the relation between mutual information and correlation. We analyze the relation between these quantities using the binary representation of signals, which is the most common approach taken in studying neuronal processes of the brain. Results We present binary communication channels for which mutual information and correlation coefficients behave differently both quantitatively and qualitatively. Despite this difference in behavior, we show that the noncorrelation of binary signals implies their independence, in contrast to the case for general types of signals. Conclusions Our research shows that the mutual information cannot be replaced by sheer correlations. Our results indicate that neuronal encoding has more complicated nature which cannot be captured by straightforward correlations between input and output signals once the mutual information takes into account the structure and patterns of the signals.
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Affiliation(s)
- Agnieszka Pregowska
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5BWarsaw, PL.
| | - Janusz Szczepanski
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5BWarsaw, PL.
| | - Eligiusz Wajnryb
- Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5BWarsaw, PL.
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Amigó JM, Monetti R, Tort-Colet N, Sanchez-Vives MV. Infragranular layers lead information flow during slow oscillations according to information directionality indicators. J Comput Neurosci 2015; 39:53-62. [DOI: 10.1007/s10827-015-0563-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Revised: 04/10/2015] [Accepted: 04/15/2015] [Indexed: 11/28/2022]
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Abásolo D, Simons S, Morgado da Silva R, Tononi G, Vyazovskiy VV. Lempel-Ziv complexity of cortical activity during sleep and waking in rats. J Neurophysiol 2015; 113:2742-52. [PMID: 25717159 PMCID: PMC4416627 DOI: 10.1152/jn.00575.2014] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2014] [Accepted: 02/23/2015] [Indexed: 01/01/2023] Open
Abstract
Understanding the dynamics of brain activity manifested in the EEG, local field potentials (LFP), and neuronal spiking is essential for explaining their underlying mechanisms and physiological significance. Much has been learned about sleep regulation using conventional EEG power spectrum, coherence, and period-amplitude analyses, which focus primarily on frequency and amplitude characteristics of the signals and on their spatio-temporal synchronicity. However, little is known about the effects of ongoing brain state or preceding sleep-wake history on the nonlinear dynamics of brain activity. Recent advances in developing novel mathematical approaches for investigating temporal structure of brain activity based on such measures, as Lempel-Ziv complexity (LZC) can provide insights that go beyond those obtained with conventional techniques of signal analysis. Here, we used extensive data sets obtained in spontaneously awake and sleeping adult male laboratory rats, as well as during and after sleep deprivation, to perform a detailed analysis of cortical LFP and neuronal activity with LZC approach. We found that activated brain states—waking and rapid eye movement (REM) sleep are characterized by higher LZC compared with non-rapid eye movement (NREM) sleep. Notably, LZC values derived from the LFP were especially low during early NREM sleep after sleep deprivation and toward the middle of individual NREM sleep episodes. We conclude that LZC is an important and yet largely unexplored measure with a high potential for investigating neurophysiological mechanisms of brain activity in health and disease.
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Affiliation(s)
- Daniel Abásolo
- Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (J5), University of Surrey, Guildford, United Kingdom
| | - Samantha Simons
- Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (J5), University of Surrey, Guildford, United Kingdom
| | - Rita Morgado da Silva
- Centre for Biomedical Engineering, Department of Mechanical Engineering Sciences, Faculty of Engineering and Physical Sciences (J5), University of Surrey, Guildford, United Kingdom
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin; and
| | - Vladyslav V Vyazovskiy
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
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