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Amaro Alves Romariz S, Klippel Zanona Q, Vendramin Pasquetti M, Cardozo Muller G, de Almeida Xavier J, Hermanus Schoorlemmer G, Monteiro Longo B, Calcagnotto ME. Modification of pre-ictal cortico-hippocampal oscillations by medial ganglionic eminence precursor cells grafting in the pilocarpine model of epilepsy. Epilepsy Behav 2024; 159:110027. [PMID: 39217756 DOI: 10.1016/j.yebeh.2024.110027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Revised: 08/27/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024]
Abstract
Cell replacement therapies using medial ganglionic eminence (MGE)-derived GABAergic precursors reduce seizures by restoring inhibition in animal models of epilepsy. However, how MGE-derived cells affect abnormal neuronal networks and consequently brain oscillations to reduce ictogenesis is still under investigation. We performed quantitative analysis of pre-ictal local field potentials (LFP) of cortical and hippocampal CA1 areas recorded in vivo in the pilocarpine rat model of epilepsy, with or without intrahippocampal MGE-precursor grafts (PILO and PILO+MGE groups, respectively). The PILO+MGE animals had a significant reduction in the number of seizures. The quantitative analysis of pre-ictal LFP showed decreased power of cortical and hippocampal delta, theta and beta oscillations from the 5 min. interictal baseline to the 20 s. pre-ictal period in both groups. However, PILO+MGE animals had higher power of slow and fast oscillations in the cortex and lower power of slow and fast oscillations in the hippocampus compared to the PILO group. Additionally, PILO+MGE animals exhibited decreased cortico-hippocampal synchrony for theta and gamma oscillations at seizure onset and lower hippocampal CA1 synchrony between delta and theta with slow gamma oscillations compared to PILO animals. These findings suggest that MGE-derived cell integration into the abnormally rewired network may help control ictogenesis.
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Affiliation(s)
- Simone Amaro Alves Romariz
- Laboratório de Neurofisiologia, Departamento de Fisiologia, Universidade Federal de São Paulo (UNIFESP/SP), São Paulo, Brazil
| | - Querusche Klippel Zanona
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Neuroscience, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Mayara Vendramin Pasquetti
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Biological Science: Biochemistry, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Gabriel Cardozo Muller
- Graduate Program in Epidemiology, Medical School, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Medical Science, Universidade do Vale do Taquari, Lajeado, RS, Brazil
| | - Jaqueline de Almeida Xavier
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Guus Hermanus Schoorlemmer
- Laboratório de Fisiologia Cardiovascular e Respiratória, Departamento de Fisiologia, Universidade Federal de São Paulo (UNIFESP/SP), São Paulo, Brazil
| | - Beatriz Monteiro Longo
- Laboratório de Neurofisiologia, Departamento de Fisiologia, Universidade Federal de São Paulo (UNIFESP/SP), São Paulo, Brazil
| | - Maria Elisa Calcagnotto
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Neuroscience, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Biological Science: Biochemistry, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil.
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Shibata T, Tsuchiya H, Akiyama M, Akiyama T, Kobayashi K. Modulation index predicts the effect of ethosuximide on developmental and epileptic encephalopathy with spike-and-wave activation in sleep. Epilepsy Res 2024; 202:107359. [PMID: 38582072 DOI: 10.1016/j.eplepsyres.2024.107359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/27/2024] [Accepted: 04/03/2024] [Indexed: 04/08/2024]
Abstract
PURPOSE In developmental and epileptic encephalopathy with spike-and-wave activation in sleep (DEE-SWAS), the thalamocortical network is suggested to play an important role in the pathophysiology of the progression from focal epilepsy to DEE-SWAS. Ethosuximide (ESM) exerts effects by blocking T-type calcium channels in thalamic neurons. With the thalamocortical network in mind, we studied the prediction of ESM effectiveness in DEE-SWAS treatment using phase-amplitude coupling (PAC) analysis. METHODS We retrospectively enrolled children with DEE-SWAS who had an electroencephalogram (EEG) recorded between January 2009 and September 2022 and were prescribed ESM at Okayama University Hospital. Only patients whose EEG showed continuous spike-and-wave during sleep were included. We extracted 5-min non-rapid eye movement sleep stage N2 segments from EEG recorded before starting ESM. We calculated the modulation index (MI) as the measure of PAC in pair combination comprising one of two fast oscillation types (gamma, 40-80 Hz; ripples, 80-150 Hz) and one of five slow-wave bands (delta, 0.5-1, 1-2, 2-3, and 3-4 Hz; theta, 4-8 Hz), and compared it between ESM responders and non-responders. RESULTS We identified 20 children with a diagnosis of DEE-SWAS who took ESM. Fifteen were ESM responders. Regarding gamma oscillations, significant differences were seen only in MI with 0.5-1 Hz slow waves in the frontal pole and occipital regions. Regarding ripples, ESM responders had significantly higher MI in coupling with all slow waves in the frontal pole region, 0.5-1, 3-4, and 4-8 Hz slow waves in the frontal region, 3-4 Hz slow waves in the parietal region, 0.5-1, 2-3, 3-4, and 4-8 Hz slow waves in the occipital region, and 3-4 Hz slow waves in the anterior-temporal region. SIGNIFICANCE High MI in a wider area of the brain may represent the epileptic network mediated by the thalamus in DEE-SWAS and may be a predictor of ESM effectiveness.
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Affiliation(s)
- Takashi Shibata
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan.
| | - Hiroki Tsuchiya
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Mari Akiyama
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Tomoyuki Akiyama
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
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Drew VJ, Wang C, Kim T. Progressive sleep disturbance in various transgenic mouse models of Alzheimer's disease. Front Aging Neurosci 2023; 15:1119810. [PMID: 37273656 PMCID: PMC10235623 DOI: 10.3389/fnagi.2023.1119810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/24/2023] [Indexed: 06/06/2023] Open
Abstract
Alzheimer's disease (AD) is the leading cause of dementia. The relationship between AD and sleep dysfunction has received increased attention over the past decade. The use of genetically engineered mouse models with enhanced production of amyloid beta (Aβ) or hyperphosphorylated tau has played a critical role in the understanding of the pathophysiology of AD. However, their revelations regarding the progression of sleep impairment in AD have been highly dependent on the mouse model used and the specific techniques employed to examine sleep. Here, we discuss the sleep disturbances and general pathology of 15 mouse models of AD. Sleep disturbances covered in this review include changes to NREM and REM sleep duration, bout lengths, bout counts and power spectra. Our aim is to describe in detail the severity and chronology of sleep disturbances within individual mouse models of AD, as well as reveal broader trends of sleep deterioration that are shared among most models. This review also explores a variety of potential mechanisms relating Aβ accumulation and tau neurofibrillary tangles to the progressive deterioration of sleep observed in AD. Lastly, this review offers perspective on how study design might impact our current understanding of sleep disturbances in AD and provides strategies for future research.
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Affiliation(s)
- Victor J. Drew
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Chanung Wang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Tae Kim
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
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Li X, Zhang H, Lai H, Wang J, Wang W, Yang X. High-Frequency Oscillations and Epileptogenic Network. Curr Neuropharmacol 2022; 20:1687-1703. [PMID: 34503414 PMCID: PMC9881061 DOI: 10.2174/1570159x19666210908165641] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/26/2021] [Accepted: 08/31/2021] [Indexed: 11/22/2022] Open
Abstract
Epilepsy is a network disease caused by aberrant neocortical large-scale connectivity spanning regions on the scale of several centimeters. High-frequency oscillations, characterized by the 80-600 Hz signals in electroencephalography, have been proven to be a promising biomarker of epilepsy that can be used in assessing the severity and susceptibility of epilepsy as well as the location of the epileptogenic zone. However, the presence of a high-frequency oscillation network remains a topic of debate as high-frequency oscillations have been previously thought to be incapable of propagation, and the relationship between high-frequency oscillations and the epileptogenic network has rarely been discussed. Some recent studies reported that high-frequency oscillations may behave like networks that are closely relevant to the epileptogenic network. Pathological highfrequency oscillations are network-driven phenomena and elucidate epileptogenic network development; high-frequency oscillations show different characteristics coincident with the epileptogenic network dynamics, and cross-frequency coupling between high-frequency oscillations and other signals may mediate the generation and propagation of abnormal discharges across the network.
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Affiliation(s)
- Xiaonan Li
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | | | | | - Jiaoyang Wang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | - Wei Wang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
| | - Xiaofeng Yang
- Bioland Laboratory, Guangzhou, China; ,Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China,Address correspondence to this author at the Bioland Laboratory, Guangzhou, China; Tel: 86+ 18515855127; E-mail:
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Penner C, Minxha J, Chandravadia N, Mamelak AN, Rutishauser U. Properties and hemispheric differences of theta oscillations in the human hippocampus. Hippocampus 2022; 32:335-341. [PMID: 35231153 PMCID: PMC9067167 DOI: 10.1002/hipo.23412] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 02/15/2022] [Accepted: 02/16/2022] [Indexed: 11/11/2022]
Abstract
The left and right primate hippocampi (LH and RH) are thought to support distinct functions, but little is known about differences between the hemispheres at the neuronal level. We recorded single-neuron and local field potentials from the human hippocampus in epilepsy patients implanted with depth electrodes. We detected theta-frequency bouts of oscillatory activity while patients performed a visual recognition memory task. Theta appeared in bouts of 3.16 cycles, with sawtooth-shaped oscillations that had a prolonged downswing period. Outside the seizure onset zone, the average frequency of theta bouts was higher in the RH compared to the LH (6.0 vs. 5.3 Hz). LH theta bouts had lower amplitudes and a higher prevalence compared to the RH (26% vs. 21% of total time). Additionally, the RH contained a population of thin spiking visually tuned neurons that were not present in the LH. These data show that human theta appears in short oscillatory bouts whose properties vary between hemispheres, thereby revealing neurophysiological properties of the hippocampus that differ between the hemispheres.
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Affiliation(s)
- Cooper Penner
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Juri Minxha
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Center for Theoretical Neuroscience, College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Nand Chandravadia
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Adam N Mamelak
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ueli Rutishauser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
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Ali R, Gollwitzer S, Reindl C, Hamer H, Coras R, Blümcke I, Buchfelder M, Hastreiter P, Rampp S. Phase-Amplitude Coupling measures for determination of the epileptic network: A methodological comparison. J Neurosci Methods 2022; 370:109484. [DOI: 10.1016/j.jneumeth.2022.109484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 12/29/2021] [Accepted: 01/18/2022] [Indexed: 12/01/2022]
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Lundstrom BN, Brinkmann BH, Worrell GA. Low frequency novel interictal EEG biomarker for localizing seizures and predicting outcomes. Brain Commun 2021; 3:fcab231. [PMID: 34704030 PMCID: PMC8536865 DOI: 10.1093/braincomms/fcab231] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 08/17/2021] [Accepted: 08/31/2021] [Indexed: 11/14/2022] Open
Abstract
Localizing hyperexcitable brain tissue to treat focal seizures remains challenging. We want to identify the seizure onset zone from interictal EEG biomarkers. We hypothesize that a combination of interictal EEG biomarkers, including a novel low frequency marker, can predict mesial temporal involvement and can assist in prognosis related to surgical resections. Interictal direct current wide bandwidth invasive EEG recordings from 83 patients implanted with 5111 electrodes were retrospectively studied. Logistic regression was used to classify electrodes and patient outcomes. A feed-forward neural network was implemented to understand putative mechanisms. Interictal infraslow frequency EEG activity was decreased for seizure onset zone electrodes while faster frequencies such as delta (2-4 Hz) and beta-gamma (20-50 Hz) activity were increased. These spectral changes comprised a novel interictal EEG biomarker that was significantly increased for mesial temporal seizure onset zone electrodes compared to non-seizure onset zone electrodes. Interictal EEG biomarkers correctly classified mesial temporal seizure onset zone electrodes with a specificity of 87% and positive predictive value of 80%. These interictal EEG biomarkers also correctly classified patient outcomes after surgical resection with a specificity of 91% and positive predictive value of 87%. Interictal infraslow EEG activity is decreased near the seizure onset zone while higher frequency power is increased, which may suggest distinct underlying physiologic mechanisms. Narrowband interictal EEG power bands provide information about the seizure onset zone and can help predict mesial temporal involvement in seizure onset. Narrowband interictal EEG power bands may be less useful for predictions related to non-mesial temporal electrodes. Together with interictal epileptiform discharges and high-frequency oscillations, these interictal biomarkers may provide prognostic information prior to surgical resection. Computational modelling suggests changes in neural adaptation may be related to the observed low frequency power changes.
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Hashimoto H, Khoo HM, Yanagisawa T, Tani N, Oshino S, Kishima H, Hirata M. Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states. Sci Rep 2021; 11:17405. [PMID: 34465798 PMCID: PMC8408139 DOI: 10.1038/s41598-021-96479-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 08/11/2021] [Indexed: 11/23/2022] Open
Abstract
Infraslow activity (ISA) and high-frequency activity (HFA) are key biomarkers for studying epileptic seizures. We aimed to elucidate the relationship between ISA and HFA around seizure onset. We enrolled seven patients with drug-resistant focal epilepsy who underwent intracranial electrode placement. We comparatively analyzed the ISA, HFA, and ISA-HFA phase-amplitude coupling (PAC) in the seizure onset zone (SOZ) or non-SOZ (nSOZ) in the interictal, preictal, and ictal states. We recorded 15 seizures. HFA and ISA were larger in the ictal states than in the interictal or preictal state. During seizures, the HFA and ISA of the SOZ were larger and occurred earlier than those of nSOZ. In the preictal state, the ISA-HFA PAC of the SOZ was larger than that of the interictal state, and it began increasing at approximately 87 s before the seizure onset. The receiver-operating characteristic curve revealed that the ISA-HFA PAC of the SOZ showed the highest discrimination performance in the preictal and interictal states, with an area under the curve of 0.926. This study demonstrated the novel insight that ISA-HFA PAC increases before the onset of seizures. Our findings indicate that ISA-HFA PAC could be a useful biomarker for discriminating between the preictal and interictal states.
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Affiliation(s)
- Hiroaki Hashimoto
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka, 565-0871, Japan. .,Department of Neurosurgery, Otemae Hospital, Osaka, Osaka, 540-0008, Japan.
| | - Hui Ming Khoo
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Takufumi Yanagisawa
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Naoki Tani
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Satoru Oshino
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Masayuki Hirata
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka, 565-0871, Japan.,Department of Neurosurgery, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
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9
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Sheybani L, Mégevand P, Spinelli L, Bénar CG, Momjian S, Seeck M, Quairiaux C, Kleinschmidt A, Vulliémoz S. Slow oscillations open susceptible time windows for epileptic discharges. Epilepsia 2021; 62:2357-2371. [PMID: 34338315 PMCID: PMC9290693 DOI: 10.1111/epi.17020] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 12/15/2022]
Abstract
Objective In patients with epilepsy, interictal epileptic discharges are a diagnostic hallmark of epilepsy and represent abnormal, so‐called “irritative” activity that disrupts normal cognitive functions. Despite their clinical relevance, their mechanisms of generation remain poorly understood. It is assumed that brain activity switches abruptly, unpredictably, and supposedly randomly to these epileptic transients. We aim to study the period preceding these epileptic discharges, to extract potential proepileptogenic mechanisms supporting their expression. Methods We used multisite intracortical recordings from patients who underwent intracranial monitoring for refractory epilepsy, the majority of whom had a mesial temporal lobe seizure onset zone. Our objective was to evaluate the existence of proepileptogenic windows before interictal epileptic discharges. We tested whether the amplitude and phase synchronization of slow oscillations (.5–4 Hz and 4–7 Hz) increase before epileptic discharges and whether the latter are phase‐locked to slow oscillations. Then, we tested whether the phase‐locking of neuronal activity (assessed by high‐gamma activity, 60–160 Hz) to slow oscillations increases before epileptic discharges to provide a potential mechanism linking slow oscillations to interictal activities. Results Changes in widespread slow oscillations anticipate upcoming epileptic discharges. The network extends beyond the irritative zone, but the increase in amplitude and phase synchronization is rather specific to the irritative zone. In contrast, epileptic discharges are phase‐locked to widespread slow oscillations and the degree of phase‐locking tends to be higher outside the irritative zone. Then, within the irritative zone only, we observe an increased coupling between slow oscillations and neuronal discharges before epileptic discharges. Significance Our results show that epileptic discharges occur during vulnerable time windows set up by a specific phase of slow oscillations. The specificity of these permissive windows is further reinforced by the increased coupling of neuronal activity to slow oscillations. These findings contribute to our understanding of epilepsy as a distributed oscillopathy and open avenues for future neuromodulation strategies aiming at disrupting proepileptic mechanisms.
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Affiliation(s)
- Laurent Sheybani
- EEG and Epilepsy Unit / Neurology, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland
| | - Pierre Mégevand
- EEG and Epilepsy Unit / Neurology, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland.,Department of Basic Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Laurent Spinelli
- EEG and Epilepsy Unit / Neurology, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland
| | - Christian G Bénar
- Aix-Marseille University, National Institute of Health and Medical Research, Institute of Systems Neurosciences, Marseille, France
| | - Shahan Momjian
- Neurosurgery, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit / Neurology, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland
| | - Charles Quairiaux
- Functional Brain Mapping Laboratory, Department of Basic Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Andreas Kleinschmidt
- EEG and Epilepsy Unit / Neurology, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit / Neurology, Department of Clinical Neuroscience, University Hospitals and Faculty of Medicine of University of Geneva, Geneva, Switzerland
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Hashimoto H, Takahashi K, Kameda S, Yoshida F, Maezawa H, Oshino S, Tani N, Khoo HM, Yanagisawa T, Yoshimine T, Kishima H, Hirata M. Motor and sensory cortical processing of neural oscillatory activities revealed by human swallowing using intracranial electrodes. iScience 2021; 24:102786. [PMID: 34308292 PMCID: PMC8283146 DOI: 10.1016/j.isci.2021.102786] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 05/28/2021] [Accepted: 06/23/2021] [Indexed: 11/28/2022] Open
Abstract
Swallowing is attributed to the orchestration of motor output and sensory input. We hypothesized that swallowing can illustrate differences between motor and sensory neural processing. Eight epileptic participants fitted with intracranial electrodes over the orofacial cortex were asked to swallow a water bolus. Mouth opening and swallowing were treated as motor tasks, whereas water injection was treated as a sensory task. Phase-amplitude coupling between lower-frequency and high γ (HG) bands (75–150 Hz) was investigated. An α (10–16 Hz)-HG coupling appeared before motor-related HG power increases (burst), and a θ (5–9 Hz)-HG coupling appeared during sensory-related HG bursts. The peaks of motor-related coupling were 0.6–0.7 s earlier than that of HG power. The motor-related HG was modulated at the trough of the α oscillation, and the sensory-related HG amplitude was modulated at the peak of the θ oscillation. These contrasting results can help to elucidate the brain's sensory motor functions. Swallowing has two aspects; sensory input and motor output Phase-amplitude coupling showed differences of motor and sensory neural processing Coupling between the α and high γ band occurred before motor-related high γ activities Coupling between the θ and high γ band occurred during sensory-related high γ activities
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Affiliation(s)
- Hiroaki Hashimoto
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan.,Department of Neurosurgery, Otemae Hospital, Chuo-ku Otemae 1-5-34, Osaka, Osaka 540-0008, Japan.,Endowed Research Department of Clinical Neuroengineering, Global Center for Medical Engineering and Informatics, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Kazutaka Takahashi
- Department of Organismal Biology and Anatomy, The University of Chicago, 1027 E 57 St, Chicago, IL 60637, USA
| | - Seiji Kameda
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Fumiaki Yoshida
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan.,Department of Anatomy and Physiology, Saga Medical School Faculty of Medicine, Saga University, Nabeshima 5-1-1, Saga, Saga 849-8501, Japan
| | - Hitoshi Maezawa
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Satoru Oshino
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Naoki Tani
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Hui Ming Khoo
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Takufumi Yanagisawa
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Toshiki Yoshimine
- Endowed Research Department of Clinical Neuroengineering, Global Center for Medical Engineering and Informatics, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
| | - Masayuki Hirata
- Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan.,Endowed Research Department of Clinical Neuroengineering, Global Center for Medical Engineering and Informatics, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan.,Department of Neurosurgery, Graduate School of Medicine, Osaka University, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
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Kuroda N, Sonoda M, Miyakoshi M, Nariai H, Jeong JW, Motoi H, Luat AF, Sood S, Asano E. Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome. Brain Commun 2021; 3:fcab042. [PMID: 33959709 PMCID: PMC8088817 DOI: 10.1093/braincomms/fcab042] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/09/2021] [Accepted: 02/02/2021] [Indexed: 12/12/2022] Open
Abstract
Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3–4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.
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Affiliation(s)
- Naoto Kuroda
- Department of Paediatrics, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA.,Department of Epileptology, Tohoku University Graduate School of Medicine, Sendai 9808575, Japan
| | - Masaki Sonoda
- Department of Paediatrics, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA.,Department of Neurosurgery, Yokohama City University, Yokohama 2360004, Japan
| | - Makoto Miyakoshi
- Swartz Centre for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA 92093, USA
| | - Hiroki Nariai
- Division of Paediatric Neurology, Department of Paediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA 90095, USA
| | - Jeong-Won Jeong
- Department of Paediatrics, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA.,Department of Neurology, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA
| | - Hirotaka Motoi
- Department of Paediatrics, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA.,Department of Paediatrics, Yokohama City University Medical Centre, Yokohama 2320024, Japan
| | - Aimee F Luat
- Department of Paediatrics, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA.,Department of Neurology, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA
| | - Eishi Asano
- Department of Paediatrics, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA.,Department of Neurology, Children's Hospital of Michigan, Detroit Medical Centre, Wayne State University, Detroit, MI 48201, USA
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12
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Alegre-Cortés J, Sáez M, Montanari R, Reig R. Medium spiny neurons activity reveals the discrete segregation of mouse dorsal striatum. eLife 2021; 10:e60580. [PMID: 33599609 PMCID: PMC7924950 DOI: 10.7554/elife.60580] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 02/15/2021] [Indexed: 01/08/2023] Open
Abstract
Behavioral studies differentiate the rodent dorsal striatum (DS) into lateral and medial regions; however, anatomical evidence suggests that it is a unified structure. To understand striatal dynamics and basal ganglia functions, it is essential to clarify the circuitry that supports this behavioral-based segregation. Here, we show that the mouse DS is made of two non-overlapping functional circuits divided by a boundary. Combining in vivo optopatch-clamp and extracellular recordings of spontaneous and evoked sensory activity, we demonstrate different coupling of lateral and medial striatum to the cortex together with an independent integration of the spontaneous activity, due to particular corticostriatal connectivity and local attributes of each region. Additionally, we show differences in slow and fast oscillations and in the electrophysiological properties between striatonigral and striatopallidal neurons. In summary, these results demonstrate that the rodent DS is segregated in two neuronal circuits, in homology with the caudate and putamen nuclei of primates.
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Affiliation(s)
| | - María Sáez
- Instituto de Neurociencias CSIC-UMHSan Juan de AlicanteSpain
| | | | - Ramon Reig
- Instituto de Neurociencias CSIC-UMHSan Juan de AlicanteSpain
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13
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Grigorovsky V, Jacobs D, Breton VL, Tufa U, Lucasius C, Del Campo JM, Chinvarun Y, Carlen PL, Wennberg R, Bardakjian BL. Delta-gamma phase-amplitude coupling as a biomarker of postictal generalized EEG suppression. Brain Commun 2020; 2:fcaa182. [PMID: 33376988 PMCID: PMC7750942 DOI: 10.1093/braincomms/fcaa182] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 12/15/2022] Open
Abstract
Postictal generalized EEG suppression is the state of suppression of electrical activity at the end of a seizure. Prolongation of this state has been associated with increased risk of sudden unexpected death in epilepsy, making characterization of underlying electrical rhythmic activity during postictal suppression an important step in improving epilepsy treatment. Phase-amplitude coupling in EEG reflects cognitive coding within brain networks and some of those codes highlight epileptic activity; therefore, we hypothesized that there are distinct phase-amplitude coupling features in the postictal suppression state that can provide an improved estimate of this state in the context of patient risk for sudden unexpected death in epilepsy. We used both intracranial and scalp EEG data from eleven patients (six male, five female; age range 21–41 years) containing 25 seizures, to identify frequency dynamics, both in the ictal and postictal EEG suppression states. Cross-frequency coupling analysis identified that during seizures there was a gradual decrease of phase frequency in the coupling between delta (0.5–4 Hz) and gamma (30+ Hz), which was followed by an increased coupling between the phase of 0.5–1.5 Hz signal and amplitude of 30–50 Hz signal in the postictal state as compared to the pre-seizure baseline. This marker was consistent across patients. Then, using these postictal-specific features, an unsupervised state classifier—a hidden Markov model—was able to reliably classify four distinct states of seizure episodes, including a postictal suppression state. Furthermore, a connectome analysis of the postictal suppression states showed increased information flow within the network during postictal suppression states as compared to the pre-seizure baseline, suggesting enhanced network communication. When the same tools were applied to the EEG of an epilepsy patient who died unexpectedly, ictal coupling dynamics disappeared and postictal phase-amplitude coupling remained constant throughout. Overall, our findings suggest that there are active postictal networks, as defined through coupling dynamics that can be used to objectively classify the postictal suppression state; furthermore, in a case study of sudden unexpected death in epilepsy, the network does not show ictal-like phase-amplitude coupling features despite the presence of convulsive seizures, and instead demonstrates activity similar to postictal. The postictal suppression state is a period of elevated network activity as compared to the baseline activity which can provide key insights into the epileptic pathology.
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Affiliation(s)
| | - Daniel Jacobs
- Institute of Biomedical Engineering, University of Toronto, Canada
| | | | - Uilki Tufa
- Institute of Biomedical Engineering, University of Toronto, Canada
| | - Christopher Lucasius
- Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto, Canada
| | | | - Yotin Chinvarun
- Comprehensive Epilepsy Program and Neurology Unit, Phramongkutklao Hospital, Thailand
| | - Peter L Carlen
- Institute of Biomedical Engineering, University of Toronto, Canada.,Department of Physiology, University of Toronto, Canada.,Division of Neurology, Toronto Western Hospital, Canada
| | | | - Berj L Bardakjian
- Institute of Biomedical Engineering, University of Toronto, Canada.,Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto, Canada
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14
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Ren G, Yan J, Sun Y, Ren J, Dai J, Mei S, Li Y, Wang X, Yang X, Wang Q. Association Between Interictal High-Frequency Oscillations and Slow Wave in Refractory Focal Epilepsy With Good Surgical Outcome. Front Hum Neurosci 2020; 14:335. [PMID: 33005137 PMCID: PMC7479180 DOI: 10.3389/fnhum.2020.00335] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 07/29/2020] [Indexed: 11/13/2022] Open
Abstract
High-frequency oscillations (HFOs) have been proposed as a promising biomarker of the epileptogenic zone (EZ). But accurate delineation of EZ based on HFOs is still challenging. Our study compared HFOs from EZ and non-EZ on the basis of their associations with interictal slow waves, aiming at exploring a new way to localize EZ. Nineteen medically intractable epilepsy patients with good surgical outcome were included. Five minute interictal intracranial electroencephalography (EEG) epochs of slow-wave sleep were randomly selected; then ripples (80–200 Hz), fast ripples (FRs; 200–500 Hz), and slow waves (0.1–4 Hz) were automatically analyzed. The EZ and non-EZ were identified by resection range during the surgeries. We found that both ripples and FRs superimposed more frequently on slow waves in EZ than in non-EZ (P < 0.01). Although ripples preferred to occur on the down state of slow waves in both two groups, ripples in EZ tended to be closer to the down-state peak of slow wave than in non-EZ (-174 vs. -231 ms, P = 0.008). As for FR, no statistical difference was found between the two groups (P = 0.430). Additionally, slow wave-containing ripples in EZ had a steeper slope (1.7 vs. 1.5 μV/ms, P < 0.001) and wider distribution ratio (32.3 vs. 30.1%, P < 0.001) than those in the non-EZ. But for slow wave-containing FR, only a steeper slope (1.7 vs. 1.4 μV/ms, P < 0.001) was observed. Our study innovatively compared the different features of association between HFOs and slow wave in EZ and non-EZ from refractory focal epilepsy with good surgical outcome, proposing a new method to localize EZ and facilitating the surgical plan.
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Affiliation(s)
- Guoping Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jiaqing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, China
| | - Yueqian Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jindong Dai
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Shanshan Mei
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Yunlin Li
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Xiaofei Wang
- Department of Functional Neurosurgery, Beijing Haidian Hospital, Beijing, China
| | - Xiaofeng Yang
- Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China.,Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.,Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Laboratory of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Beijing Institute of Brain Disorders, Capital Medical University, Ministry of Science and Technology, Beijing, China
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