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van Nifterick AM, Mulder D, Duineveld DJ, Diachenko M, Scheltens P, Stam CJ, van Kesteren RE, Linkenkaer-Hansen K, Hillebrand A, Gouw AA. Resting-state oscillations reveal disturbed excitation-inhibition ratio in Alzheimer's disease patients. Sci Rep 2023; 13:7419. [PMID: 37150756 PMCID: PMC10164744 DOI: 10.1038/s41598-023-33973-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 04/21/2023] [Indexed: 05/09/2023] Open
Abstract
An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models of Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and non-invasively in humans. Here, we examined known and novel neurophysiological measures sensitive to E-I in patients across the AD continuum. Resting-state magnetoencephalography (MEG) data of 86 amyloid-biomarker-confirmed subjects across the AD continuum (17 patients diagnosed with subjective cognitive decline, 18 with mild cognitive impairment (MCI) and 51 with dementia due to probable AD (AD dementia)), 46 healthy elderly and 20 young control subjects were reconstructed to source-space. E-I balance was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, and the aperiodic exponent of the power spectrum. We found a disrupted E-I ratio in AD dementia patients specifically, by a lower DFA, and a shift towards higher excitation, by a higher fE/I and a lower aperiodic exponent. Healthy subjects showed lower fE/I ratios (< 1.0) than reported in previous literature, not explained by age or choice of an arbitrary threshold parameter, which warrants caution in interpretation of fE/I results. Correlation analyses showed that a lower DFA (E-I imbalance) and a lower aperiodic exponent (more excitation) was associated with a worse cognitive score in AD dementia patients. In contrast, a higher DFA in the hippocampi of MCI patients was associated with a worse cognitive score. This MEG-study showed E-I imbalance, likely due to increased excitation, in AD dementia, but not in early stage AD patients. To accurately determine the direction of shift in E-I balance, validations of the currently used markers and additional in vivo markers of E-I are required.
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Affiliation(s)
- Anne M van Nifterick
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands.
| | - Danique Mulder
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Denise J Duineveld
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Marina Diachenko
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Ronald E van Kesteren
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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Weiler R, Diachenko M, Juarez-Martinez EL, Avramiea AE, Bloem P, Linkenkaer-Hansen K. Robin's Viewer: Using deep-learning predictions to assist EEG annotation. Front Neuroinform 2023; 16:1025847. [PMID: 36844437 PMCID: PMC9951202 DOI: 10.3389/fninf.2022.1025847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 12/20/2022] [Indexed: 02/12/2023] Open
Abstract
Machine learning techniques such as deep learning have been increasingly used to assist EEG annotation, by automating artifact recognition, sleep staging, and seizure detection. In lack of automation, the annotation process is prone to bias, even for trained annotators. On the other hand, completely automated processes do not offer the users the opportunity to inspect the models' output and re-evaluate potential false predictions. As a first step toward addressing these challenges, we developed Robin's Viewer (RV), a Python-based EEG viewer for annotating time-series EEG data. The key feature distinguishing RV from existing EEG viewers is the visualization of output predictions of deep-learning models trained to recognize patterns in EEG data. RV was developed on top of the plotting library Plotly, the app-building framework Dash, and the popular M/EEG analysis toolbox MNE. It is an open-source, platform-independent, interactive web application, which supports common EEG-file formats to facilitate easy integration with other EEG toolboxes. RV includes common features of other EEG viewers, e.g., a view-slider, tools for marking bad channels and transient artifacts, and customizable preprocessing. Altogether, RV is an EEG viewer that combines the predictive power of deep-learning models and the knowledge of scientists and clinicians to optimize EEG annotation. With the training of new deep-learning models, RV could be developed to detect clinical patterns other than artifacts, for example sleep stages and EEG abnormalities.
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Affiliation(s)
- Robin Weiler
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands
| | - Marina Diachenko
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands
| | - Erika L. Juarez-Martinez
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands
| | - Arthur-Ervin Avramiea
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands
| | - Peter Bloem
- Department of Computer Science, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands,*Correspondence: Klaus Linkenkaer-Hansen,
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Diachenko M, Smith KK, Fjorback L, Hansen NV, Linkenkaer-Hansen K, Pallesen KJ. Pre-retirement Employees Experience Lasting Improvements in Resilience and Well-Being After Mindfulness-Based Stress Reduction. Front Psychol 2021; 12:699088. [PMID: 34335417 PMCID: PMC8321239 DOI: 10.3389/fpsyg.2021.699088] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 06/17/2021] [Indexed: 01/07/2023] Open
Abstract
The socio-economic benefits of interventions to prevent stress and related mental health problems are enormous. In the labor market, it is becoming desirable to keep employees for as long as possible. Since aging implies additional stressors such as increased risk of illness, and added pressure by professional tasks such as transferring knowledge, or learning new technologies, it is of particular relevance to offer stress-reduction to pre-retirement employees. Here, we report the effects of an eight-week Mindfulness-Based Stress Reduction (MBSR) intervention on mental well-being in 60-65-year-old work-active Danish employees, compared to a waiting-list control group. We observed improvements in resilience (Brief Resilience Scale) and mental well-being (WHO-5) not only at the end of the intervention, but also at the 12-month follow-up measurement that was preceded by monthly booster sessions. Interestingly, whereas well-being usually refers to experiences in the past weeks or months, we observed increasing Comfort in the MBSR-intervention group during a 5-minute eyes-closed rest session suggesting that this therapeutic effect of MBSR is measurable in how we feel even during short periods of time. We argue that MBSR is a cost-effective intervention suited for pre-retirement employees to cultivate resilience to prevent stress, feel more comfortable with themselves, maintain a healthy work-life in the last years before retirement, and, potentially, stay in their work-life a few more years than originally planned.
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Affiliation(s)
- Marina Diachenko
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam, Neuroscience, VU Amsterdam, Amsterdam, Netherlands
| | - Kristina K Smith
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam, Neuroscience, VU Amsterdam, Amsterdam, Netherlands
| | - Lone Fjorback
- Danish Center for Mindfulness, Department of Clinical Medicine, Aarhus University, Brabrand, Denmark
| | - Niels Viggo Hansen
- Danish Center for Mindfulness, Department of Clinical Medicine, Aarhus University, Brabrand, Denmark
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, (CNCR), Amsterdam, Neuroscience, VU Amsterdam, Amsterdam, Netherlands
| | - Karen Johanne Pallesen
- Danish Center for Mindfulness, Department of Clinical Medicine, Aarhus University, Brabrand, Denmark
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Perekhrestenko T, Diachenko M, Sviezhentseva I, Gordienko A, Bilko D. Mechanisms of resistance in patients with chronic myeloid leukemia treated with tyrosine kinase inhibitors. Georgian Med News 2015:43-50. [PMID: 25879558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Up to date, two major mechanisms have been proposed as an explanation for myeloid cells expansion in chronic myeloid leukemia (CML). One is a reduced susceptibility of hematopoietic stem or progenitor cells to apoptosis, while the other one is an increased activity within the hematopoietic progenitor cell population. The aim of the study was to identify specific features of functional activity, proliferation rates and differentiation potential of CML hematopoietic progenitor cells of patients treated with tyrosine kinase inhibitors (TKI) by identifying number of Ki-67, Bcl-2 and CD34 positive cells in bone marrow, as well as in vitro colony-forming unit assay in patients with different response to the TKI therapy. Our results indicated that there was a significant decline in proliferation activity of HSCs and HPCs in group of patients with optimal response to the TKI therapy. Correlation analysis, performed on individual basis for patients independently of response to the TKI therapy demonstrated that there was a negative correlation (ρ=0.7648) between the number of Ki67+ and CD34+ cells. As to colony to cluster ratio our results showed, that there is a correlation (ρ=0.6783) between CCR index and number of bone marrow cells with Philadelphia chromosome. It was indicated, that index of maturation correlates with level of bone marrow cells, containing Philadelphia chromosome, so as with percentage of CD34+, Bcl-2+, Pgp-170+ and Ki67+ cells in bone marrow of CML patients. In summary, obtained results suggest that different mechanisms (bcr-abl dependent and independent) may be involved in CML progression process in the same time. Disease prognosis should be preferably carried out on an individual basis.
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MESH Headings
- Antigens, CD34/biosynthesis
- Antigens, CD34/genetics
- Apoptosis/drug effects
- Apoptosis/genetics
- Bone Marrow Cells/drug effects
- Bone Marrow Cells/pathology
- Carcinogenesis/drug effects
- Carcinogenesis/genetics
- Cell Differentiation/drug effects
- Cell Differentiation/genetics
- Cell Proliferation/drug effects
- Cell Proliferation/genetics
- Drug Resistance, Neoplasm/genetics
- Fusion Proteins, bcr-abl/genetics
- Gene Expression Regulation, Leukemic/drug effects
- Hematopoietic Stem Cells/pathology
- Humans
- Ki-67 Antigen/biosynthesis
- Ki-67 Antigen/genetics
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/genetics
- Leukemia, Myelogenous, Chronic, BCR-ABL Positive/pathology
- Neoplastic Stem Cells/pathology
- Protein Kinase Inhibitors/administration & dosage
- Proto-Oncogene Proteins c-bcl-2/biosynthesis
- Proto-Oncogene Proteins c-bcl-2/genetics
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Affiliation(s)
- T Perekhrestenko
- 1SI "Institute of Hematology and Transfusiology of the NAMS of Ukraine", Kyiv; 2National University "Kyiv-Mohyla Academy", Center for Molecular and Cell Research, Kyiv, Ukraine
| | - M Diachenko
- 1SI "Institute of Hematology and Transfusiology of the NAMS of Ukraine", Kyiv; 2National University "Kyiv-Mohyla Academy", Center for Molecular and Cell Research, Kyiv, Ukraine
| | - I Sviezhentseva
- 1SI "Institute of Hematology and Transfusiology of the NAMS of Ukraine", Kyiv; 2National University "Kyiv-Mohyla Academy", Center for Molecular and Cell Research, Kyiv, Ukraine
| | - A Gordienko
- 1SI "Institute of Hematology and Transfusiology of the NAMS of Ukraine", Kyiv; 2National University "Kyiv-Mohyla Academy", Center for Molecular and Cell Research, Kyiv, Ukraine
| | - D Bilko
- 1SI "Institute of Hematology and Transfusiology of the NAMS of Ukraine", Kyiv; 2National University "Kyiv-Mohyla Academy", Center for Molecular and Cell Research, Kyiv, Ukraine
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