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Kostoglou K, Bello-Robles F, Brassard P, Chacon M, Claassen JAHR, Czosnyka M, Elting JW, Hu K, Labrecque L, Liu J, Marmarelis VZ, Payne SJ, Shin DC, Simpson D, Smirl J, Panerai RB, Mitsis GD. Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet). J Cereb Blood Flow Metab 2024; 44:1480-1514. [PMID: 38688529 PMCID: PMC11418733 DOI: 10.1177/0271678x241249276] [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: 07/05/2023] [Revised: 03/22/2024] [Accepted: 03/28/2024] [Indexed: 05/02/2024]
Abstract
Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA.
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Affiliation(s)
- Kyriaki Kostoglou
- Department of Electrical and Computer Engineering, McGill University, Montreal, QC, Canada
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria
| | - Felipe Bello-Robles
- Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile
| | - Patrice Brassard
- Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC, Canada
- Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec, Quebec, QC, Canada
| | - Max Chacon
- Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile
| | - Jurgen AHR Claassen
- Department of Geriatrics, Radboud University Medical Center, Research Institute for Medical Innovation and Donders Institute, Nijmegen, The Netherlands
- Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM), Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Marek Czosnyka
- Department of Clinical Neurosciences, Neurosurgery Department, University of Cambridge, Cambridge, UK
| | - Jan-Willem Elting
- Department of Neurology and Clinical Neurophysiology, University Medical Center Groningen, Groningen, The Netherlands
| | - Kun Hu
- Medical Biodynamics Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Lawrence Labrecque
- Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC, Canada
- Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec, Quebec, QC, Canada
| | - Jia Liu
- Laboratory for Engineering and Scientific Computing, Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Vasilis Z Marmarelis
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Stephen J Payne
- Institute of Applied Mechanics, National Taiwan University, Taipei, Taiwan
| | - Dae Cheol Shin
- Department Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - David Simpson
- Institute of Sound and Vibration Research, University of Southampton, Southampton, UK
| | - Jonathan Smirl
- Cerebrovascular Concussion Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
- Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ronney B Panerai
- Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM), Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, British Heart Foundation, Glenfield Hospital, Leicester, UK
| | - Georgios D Mitsis
- Department of Bioengineering, McGill University, Montreal, QC, Canada
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Xiao W, Li J, Gao X, Yang H, Su J, Weng R, Gao Y, Ni W, Gu Y. Involvement of the gut-brain axis in vascular depression via tryptophan metabolism: A benefit of short chain fatty acids. Exp Neurol 2022; 358:114225. [PMID: 36100045 DOI: 10.1016/j.expneurol.2022.114225] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 08/23/2022] [Accepted: 09/05/2022] [Indexed: 11/04/2022]
Abstract
Cerebral hemodynamic dysfunction and hypoperfusion have been found to underlie vascular depression, but whether the gut-brain axis is involved remains unknown. In this study, a rat model of bilateral common carotid artery occlusion (BCCAO) was adopted to mimic chronic cerebral hypoperfusion. A reduced sucrose preference ratio, increased immobility time in the tail suspension test and forced swim test, and compromised gut homeostasis were found. A promoted conversion of tryptophan (Trp) into kynurenine (Kyn) instead of 5-hydroxytryptamine (5-HT) was observed in the hippocampus and gut of BCCAO rats. Meanwhile, 16S ribosomal RNA gene sequencing suggested a compromised profile of the gut SCFA-producing microbiome, with a decreased serum level of SCFAs revealed by targeted metabolomics analysis. With SCFA supplementation, BCCAO rats exhibited ameliorated depressive-like behaviors and improved gut dysbiosis, compared with the salt-matched BCCAO group. Enzyme-linked immunosorbent assays and quantitative RT-PCR suggested that SCFA supplementation suppressed the conversion of Trp to Kyn and rescued the reduction in 5-HT levels in the hippocampus and gut. In addition to inhibiting the upregulation of inflammatory cytokines, SCFA supplementation ameliorated the activated oxidative stress and reduced the number of microglia and the expression of its proinflammatory markers in the hippocampus post BCCAO. In conclusion, our data suggested the participation of the gut-brain axis in vascular depression, shedding light on the neuroprotective potential of treatment with gut-derived SCFAs.
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Affiliation(s)
- Weiping Xiao
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China
| | - Jiaying Li
- State Key Laboratory of Medical Neurobiology, MOE Frontier Center for Brain Science and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Xinjie Gao
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China
| | - Heng Yang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China
| | - Jiabin Su
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China
| | - Ruiyuan Weng
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China
| | - Yanqin Gao
- State Key Laboratory of Medical Neurobiology, MOE Frontier Center for Brain Science and Institutes of Brain Science, Fudan University, Shanghai, China.
| | - Wei Ni
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China.
| | - Yuxiang Gu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China; Institute of Neurosurgery, Fudan University, Shanghai 200052, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai 200052, China; National Medical Center for Neurological Disorders, Shanghai 200040, China
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