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McKenzie AT, Nnadi O, Slagell KD, Thorn EL, Farrell K, Crary JF. Fluid preservation in brain banking: a review. FREE NEUROPATHOLOGY 2024; 5:5-10. [PMID: 38690035 PMCID: PMC11058410 DOI: 10.17879/freeneuropathology-2024-5373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 03/29/2024] [Indexed: 05/02/2024]
Abstract
Fluid preservation is nearly universally used in brain banking to store fixed tissue specimens for future research applications. However, the effects of long-term immersion on neural circuitry and biomolecules are not well characterized. As a result, there is a need to synthesize studies investigating fluid preservation of brain tissue. We searched PubMed and other databases to identify studies measuring the effects of fluid preservation in nervous system tissue. We categorized studies based on the fluid preservative used: formaldehyde solutions, buffer solutions, alcohol solutions, storage after tissue clearing, and cryoprotectant solutions. We identified 91 studies containing 197 independent observations of the effects of long-term storage on cellular morphology. Most studies did not report any significant alterations due to long-term storage. When present, the most frequent alteration was decreased antigenicity, commonly attributed to progressive crosslinking by aldehydes that renders biomolecules increasingly inaccessible over time. To build a mechanistic understanding, we discuss biochemical aspects of long-term fluid preservation. A subset of lipids appears to be chemical altered or extracted over time due to incomplete retention in the crosslinked gel. Alternative storage fluids mitigate the problem of antigen masking but have not been extensively characterized and may have other downsides. We also compare fluid preservation to cryopreservation, paraffin embedding, and resin embedding. Overall, existing evidence suggests that fluid preservation provides maintenance of neural architecture for decades, including precise structural details. However, to avoid the well-established problem of overfixation caused by storage in high concentration formaldehyde solutions, fluid preservation procedures can use an initial fixation step followed by an alternative long-term storage fluid. Further research is warranted on optimizing protocols and characterizing the generalizability of the storage artifacts that have been identified.
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Affiliation(s)
| | - Oge Nnadi
- Brain Preservation Foundation, Ashburn, Virginia, USA
| | - Kat D. Slagell
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Emma L. Thorn
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Kurt Farrell
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - John F. Crary
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Tsujimura K, Shiohama T, Takahashi E. microRNA Biology on Brain Development and Neuroimaging Approach. Brain Sci 2022; 12:brainsci12101366. [PMID: 36291300 PMCID: PMC9599180 DOI: 10.3390/brainsci12101366] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 11/22/2022] Open
Abstract
Proper brain development requires the precise coordination and orchestration of various molecular and cellular processes and dysregulation of these processes can lead to neurological diseases. In the past decades, post-transcriptional regulation of gene expression has been shown to contribute to various aspects of brain development and function in the central nervous system. MicroRNAs (miRNAs), short non-coding RNAs, are emerging as crucial players in post-transcriptional gene regulation in a variety of tissues, such as the nervous system. In recent years, miRNAs have been implicated in multiple aspects of brain development, including neurogenesis, migration, axon and dendrite formation, and synaptogenesis. Moreover, altered expression and dysregulation of miRNAs have been linked to neurodevelopmental and psychiatric disorders. Magnetic resonance imaging (MRI) is a powerful imaging technology to obtain high-quality, detailed structural and functional information from the brains of human and animal models in a non-invasive manner. Because the spatial expression patterns of miRNAs in the brain, unlike those of DNA and RNA, remain largely unknown, a whole-brain imaging approach using MRI may be useful in revealing biological and pathological information about the brain affected by miRNAs. In this review, we highlight recent advancements in the research of miRNA-mediated modulation of neuronal processes that are important for brain development and their involvement in disease pathogenesis. Also, we overview each MRI technique, and its technological considerations, and discuss the applications of MRI techniques in miRNA research. This review aims to link miRNA biological study with MRI analytical technology and deepen our understanding of how miRNAs impact brain development and pathology of neurological diseases.
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Affiliation(s)
- Keita Tsujimura
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Group of Brain Function and Development, Nagoya University Neuroscience Institute of the Graduate School of Science, Nagoya 4648602, Japan
- Research Unit for Developmental Disorders, Institute for Advanced Research, Nagoya University, Nagoya 4648602, Japan
- Correspondence: (K.T.); (E.T.)
| | - Tadashi Shiohama
- Department of Pediatrics, Chiba University Hospital, Chiba 2608677, Japan
| | - Emi Takahashi
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Correspondence: (K.T.); (E.T.)
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Tendler BC, Hanayik T, Ansorge O, Bangerter-Christensen S, Berns GS, Bertelsen MF, Bryant KL, Foxley S, van den Heuvel MP, Howard AFD, Huszar IN, Khrapitchev AA, Leonte A, Manger PR, Menke RAL, Mollink J, Mortimer D, Pallebage-Gamarallage M, Roumazeilles L, Sallet J, Scholtens LH, Scott C, Smart A, Turner MR, Wang C, Jbabdi S, Mars RB, Miller KL. The Digital Brain Bank, an open access platform for post-mortem imaging datasets. eLife 2022; 11:e73153. [PMID: 35297760 PMCID: PMC9042233 DOI: 10.7554/elife.73153] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Olaf Ansorge
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sarah Bangerter-Christensen
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen ZooFrederiksbergDenmark
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Department of Radiology, University of ChicagoChicagoUnited States
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Amy FD Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alexandre A Khrapitchev
- Medical Research Council Oxford Institute for Radiation Oncology, University of OxfordOxfordUnited Kingdom
| | - Anna Leonte
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the WitwatersrandJohannesburgSouth Africa
| | - Ricarda AL Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Duncan Mortimer
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Menuka Pallebage-Gamarallage
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Stem Cell and Brain Research Institute, Université Lyon 1, INSERMBronFrance
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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Tendler BC, Qi F, Foxley S, Pallebage-Gamarallage M, Menke RAL, Ansorge O, Hurley SA, Miller KL. A method to remove the influence of fixative concentration on postmortem T 2 maps using a kinetic tensor model. Hum Brain Mapp 2021; 42:5956-5972. [PMID: 34541735 PMCID: PMC8596944 DOI: 10.1002/hbm.25661] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 08/06/2021] [Accepted: 08/30/2021] [Indexed: 12/20/2022] Open
Abstract
Formalin fixation has been shown to substantially reduce T2 estimates, primarily driven by the presence of fixative in tissue. Prior to scanning, post‐mortem samples are often placed into a fluid that has more favourable imaging properties. This study investigates whether there is evidence for a change in T2 in regions close to the tissue surface due to fixative outflux into this surrounding fluid. Furthermore, we investigate whether a simulated spatial map of fixative concentration can be used as a confound regressor to reduce T2 inhomogeneity. To achieve this, T2 maps and diffusion tensor estimates were obtained in 14 whole, formalin‐fixed post‐mortem brains placed in Fluorinert approximately 48 hr prior to scanning. Seven brains were fixed with 10% formalin and seven brains were fixed with 10% neutral buffered formalin (NBF). Fixative outflux was modelled using a proposed kinetic tensor (KT) model, which incorporates voxelwise diffusion tensor estimates to account for diffusion anisotropy and tissue‐specific diffusion coefficients. Brains fixed with 10% NBF revealed a spatial T2 pattern consistent with modelled fixative outflux. Confound regression of fixative concentration reduced T2 inhomogeneity across both white and grey matter, with the greatest reduction attributed to the KT model versus simpler models of fixative outflux. No such effect was observed in brains fixed with 10% formalin. Correlations between the transverse relaxation rate R2 and ferritin/myelin proteolipid protein (PLP) histology lead to an increased similarity for the relationship between R2 and PLP for the two fixative types after KT correction.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
| | - Feng Qi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford.,Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | | | - Ricarda A L Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Samuel A Hurley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
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