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Dines M, Kes M, Ailán D, Cetkovich-Bakmas M, Born C, Grunze H. Bipolar disorders and schizophrenia: discrete disorders? Front Psychiatry 2024; 15:1352250. [PMID: 38745778 PMCID: PMC11091416 DOI: 10.3389/fpsyt.2024.1352250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/16/2024] [Indexed: 05/16/2024] Open
Abstract
Background With similarities in heritability, neurobiology and symptomatology, the question has been raised whether schizophrenia and bipolar disorder are truly distinctive disorders or belong to a continuum. This narrative review summarizes common and distinctive findings from genetics, neuroimaging, cognition and clinical course that may help to solve this ethiopathogenetic puzzle. Methods The authors conducted a literature search for papers listed in PubMed and Google Scholar, using the search terms "schizophrenia" and "bipolar disorder" combined with different terms such as "genes", "neuroimaging studies", "phenomenology differences", "cognition", "epidemiology". Articles were considered for inclusion if they were written in English or Spanish, published as full articles, if they compared subjects with schizophrenia and bipolar disorder, or subjects with either disorder with healthy controls, addressing differences between groups. Results Several findings support the hypothesis that schizophrenia and bipolar disorder are discrete disorders, yet some overlapping of findings exists. The evidence for heritability of both SZ and BD is obvious, as well as the environmental impact on individual manifestations of both disorders. Neuroimaging studies support subtle differences between disorders, it appears to be rather a pattern of irregularities than an unequivocally unique finding distinguishing schizophrenia from bipolar disorder. The cognitive profile displays differences between disorders in certain domains, such as premorbid intellectual functioning and executive functions. Finally, the timing and trajectory of cognitive impairment in both disorders also differs. Conclusion The question whether SZ and BD belong to a continuum or are separate disorders remains a challenge for further research. Currently, our research tools may be not precise enough to carve out distinctive, unique and undisputable differences between SZ and BD, but current evidence favors separate disorders. Given that differences are subtle, a way to overcome diagnostic uncertainties in the future could be the application of artificial intelligence based on BigData. Limitations Despite the detailed search, this article is not a full and complete review of all available studies on the topic. The search and selection of papers was also limited to articles in English and Spanish. Selection of papers and conclusions may be biased by the personal view and clinical experience of the authors.
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Affiliation(s)
- Micaela Dines
- Department of Psychiatry, Instituto de Neurología Cognitiva (INECO), Buenos Aires, Argentina
- Department of Psychiatry, Instituto de Neurociencia Cognitiva y Traslacional (Consejo Nacional de Investigaciones Científicas y Técnicas - Fundación INECO - Universidad Favaloro), Buenos Aires, Argentina
| | - Mariana Kes
- Department of Psychiatry, Instituto de Neurología Cognitiva (INECO), Buenos Aires, Argentina
- Department of Psychiatry, Instituto de Neurociencia Cognitiva y Traslacional (Consejo Nacional de Investigaciones Científicas y Técnicas - Fundación INECO - Universidad Favaloro), Buenos Aires, Argentina
| | - Delfina Ailán
- Department of Psychiatry, Instituto de Neurología Cognitiva (INECO), Buenos Aires, Argentina
- Department of Psychiatry, Instituto de Neurociencia Cognitiva y Traslacional (Consejo Nacional de Investigaciones Científicas y Técnicas - Fundación INECO - Universidad Favaloro), Buenos Aires, Argentina
| | - Marcelo Cetkovich-Bakmas
- Department of Psychiatry, Instituto de Neurología Cognitiva (INECO), Buenos Aires, Argentina
- Department of Psychiatry, Instituto de Neurociencia Cognitiva y Traslacional (Consejo Nacional de Investigaciones Científicas y Técnicas - Fundación INECO - Universidad Favaloro), Buenos Aires, Argentina
| | - Christoph Born
- Department of Psychiatry, Psychiatrie Schwäbisch Hall, Ringstraße, Germany
- Department of Psychiatry, Paracelsus Medical University, Nuremberg, Germany
| | - Heinz Grunze
- Department of Psychiatry, Psychiatrie Schwäbisch Hall, Ringstraße, Germany
- Department of Psychiatry, Paracelsus Medical University, Nuremberg, Germany
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2
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Baravalle R, Canavier CC. Synchrony in Networks of Type 2 Interneurons Is More Robust to Noise with Hyperpolarizing Inhibition Compared to Shunting Inhibition in Both the Stochastic Population Oscillator and the Coupled Oscillator Regimes. eNeuro 2024; 11:ENEURO.0399-23.2024. [PMID: 38471777 PMCID: PMC10972736 DOI: 10.1523/eneuro.0399-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/12/2024] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
Synchronization in the gamma band (25-150 Hz) is mediated by PV+ inhibitory interneurons, and evidence is accumulating for the essential role of gamma oscillations in cognition. Oscillations can arise in inhibitory networks via synaptic interactions between individual oscillatory neurons (mean-driven) or via strong recurrent inhibition that destabilizes the stationary background firing rate in the fluctuation-driven balanced state, causing an oscillation in the population firing rate. Previous theoretical work focused on model neurons with Hodgkin's Type 1 excitability (integrators) connected by current-based synapses. Here we show that networks comprised of simple Type 2 oscillators (resonators) exhibit a supercritical Hopf bifurcation between synchrony and asynchrony and a gradual transition via cycle skipping from coupled oscillators to stochastic population oscillator (SPO), as previously shown for Type 1. We extended our analysis to homogeneous networks with conductance rather than current based synapses and found that networks with hyperpolarizing inhibitory synapses were more robust to noise than those with shunting synapses, both in the coupled oscillator and SPO regime. Assuming that reversal potentials are uniformly distributed between shunting and hyperpolarized values, as observed in one experimental study, converting synapses to purely hyperpolarizing favored synchrony in all cases, whereas conversion to purely shunting synapses made synchrony less robust except at very high conductance strengths. In mature neurons the synaptic reversal potential is controlled by chloride cotransporters that control the intracellular concentrations of chloride and bicarbonate ions, suggesting these transporters as a potential therapeutic target to enhance gamma synchrony and cognition.
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Affiliation(s)
- Roman Baravalle
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center-New Orleans, New Orleans, Louisiana 70112
| | - Carmen C Canavier
- Department of Cell Biology and Anatomy, Louisiana State University Health Sciences Center-New Orleans, New Orleans, Louisiana 70112
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3
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Kleven H, Bjerke IE, Clascá F, Groenewegen HJ, Bjaalie JG, Leergaard TB. Waxholm Space atlas of the rat brain: a 3D atlas supporting data analysis and integration. Nat Methods 2023; 20:1822-1829. [PMID: 37783883 PMCID: PMC10630136 DOI: 10.1038/s41592-023-02034-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 09/01/2023] [Indexed: 10/04/2023]
Abstract
Volumetric brain atlases are increasingly used to integrate and analyze diverse experimental neuroscience data acquired from animal models, but until recently a publicly available digital atlas with complete coverage of the rat brain has been missing. Here we present an update of the Waxholm Space rat brain atlas, a comprehensive open-access volumetric atlas resource. This brain atlas features annotations of 222 structures, of which 112 are new and 57 revised compared to previous versions. It provides a detailed map of the cerebral cortex, hippocampal region, striatopallidal areas, midbrain dopaminergic system, thalamic cell groups, the auditory system and main fiber tracts. We document the criteria underlying the annotations and demonstrate how the atlas with related tools and workflows can be used to support interpretation, integration, analysis and dissemination of experimental rat brain data.
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Affiliation(s)
- Heidi Kleven
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ingvild E Bjerke
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Francisco Clascá
- Department of Anatomy and Neuroscience, Autónoma de Madrid University, Madrid, Spain
| | - Henk J Groenewegen
- Department of Anatomy and Neurosciences, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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4
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Han X, Guo S, Ji N, Li T, Liu J, Ye X, Wang Y, Yun Z, Xiong F, Rong J, Liu D, Ma H, Wang Y, Huang Y, Zhang P, Wu W, Ding L, Hawrylycz M, Lein E, Ascoli GA, Xie W, Liu L, Zhang L, Peng H. Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy. SCIENCE ADVANCES 2023; 9:eadf3771. [PMID: 37824619 PMCID: PMC10569712 DOI: 10.1126/sciadv.adf3771] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 04/18/2023] [Indexed: 10/14/2023]
Abstract
Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tomography (ACTomography), a low-cost, high-throughput, and high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and one donated fresh postmortem brain. We collected three-dimensional images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor field of neuron morphology to characterize anatomical modularity of a human brain.
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Affiliation(s)
- Xiaofeng Han
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Shuxia Guo
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Nan Ji
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Tian Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jian Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Xiangqiao Ye
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Yi Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhixi Yun
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Feng Xiong
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Jing Rong
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Di Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Hui Ma
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Yujin Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yue Huang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Peng Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wenhao Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Liya Ding
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | | | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Giorgio A. Ascoli
- Center for Neural Informatics, Krasnow Institute for Advanced Studies and Bioengineering Department, College of Engineering and Computing, George Mason University, Fairfax, VA, USA
| | - Wei Xie
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
- The Key Laboratory of Developmental Genes and Human Disease, Ministry of Education, School of Life Science and Technology, Southeast University, Nanjing, China
| | - Lijuan Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
| | - Liwei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Key Laboratory of Brain Tumor, Beijing, China
| | - Hanchuan Peng
- Institute for Brain and Intelligence, Southeast University, Nanjing, China
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5
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Carey H, Pegios M, Martin L, Saleeba C, Turner AJ, Everett NA, Bjerke IE, Puchades MA, Bjaalie JG, McMullan S. DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas. Nat Commun 2023; 14:5884. [PMID: 37735467 PMCID: PMC10514056 DOI: 10.1038/s41467-023-41645-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 09/12/2023] [Indexed: 09/23/2023] Open
Abstract
Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.
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Affiliation(s)
- Harry Carey
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Michael Pegios
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | | | - Chris Saleeba
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | - Anita J Turner
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | | | - Ingvild E Bjerke
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Simon McMullan
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia.
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6
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Bjerke IE, Yates SC, Carey H, Bjaalie JG, Leergaard TB. Scaling up cell-counting efforts in neuroscience through semi-automated methods. iScience 2023; 26:107562. [PMID: 37636060 PMCID: PMC10457595 DOI: 10.1016/j.isci.2023.107562] [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] [Indexed: 08/29/2023] Open
Abstract
Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.
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Affiliation(s)
- Ingvild Elise Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Sharon Christine Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Harry Carey
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan Gunnar Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve Brauns Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
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7
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Kleven H, Gillespie TH, Zehl L, Dickscheid T, Bjaalie JG, Martone ME, Leergaard TB. AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures. Sci Data 2023; 10:486. [PMID: 37495585 PMCID: PMC10372146 DOI: 10.1038/s41597-023-02389-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 07/14/2023] [Indexed: 07/28/2023] Open
Abstract
Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.
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Affiliation(s)
- Heidi Kleven
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | | | - Lyuba Zehl
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Timo Dickscheid
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute of Computer Science, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maryann E Martone
- Department of Neurosciences, University of California, San Diego, USA
| | - Trygve B Leergaard
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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8
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Lupori L, Totaro V, Cornuti S, Ciampi L, Carrara F, Grilli E, Viglione A, Tozzi F, Putignano E, Mazziotti R, Amato G, Gennaro C, Tognini P, Pizzorusso T. A comprehensive atlas of perineuronal net distribution and colocalization with parvalbumin in the adult mouse brain. Cell Rep 2023; 42:112788. [PMID: 37436896 DOI: 10.1016/j.celrep.2023.112788] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 05/03/2023] [Accepted: 06/25/2023] [Indexed: 07/14/2023] Open
Abstract
Perineuronal nets (PNNs) surround specific neurons in the brain and are involved in various forms of plasticity and clinical conditions. However, our understanding of the PNN role in these phenomena is limited by the lack of highly quantitative maps of PNN distribution and association with specific cell types. Here, we present a comprehensive atlas of Wisteria floribunda agglutinin (WFA)-positive PNNs and colocalization with parvalbumin (PV) cells for over 600 regions of the adult mouse brain. Data analysis shows that PV expression is a good predictor of PNN aggregation. In the cortex, PNNs are dramatically enriched in layer 4 of all primary sensory areas in correlation with thalamocortical input density, and their distribution mirrors intracortical connectivity patterns. Gene expression analysis identifies many PNN-correlated genes. Strikingly, PNN-anticorrelated transcripts are enriched in synaptic plasticity genes, generalizing PNNs' role as circuit stability factors.
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Affiliation(s)
| | | | - Sara Cornuti
- BIO@SNS Lab, Scuola Normale Superiore, 56126 Pisa, Italy
| | - Luca Ciampi
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Fabio Carrara
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Edda Grilli
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
| | | | | | | | | | - Giuseppe Amato
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Claudio Gennaro
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Paola Tognini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
| | - Tommaso Pizzorusso
- BIO@SNS Lab, Scuola Normale Superiore, 56126 Pisa, Italy; Institute of Neuroscience (IN-CNR), 56124 Pisa, Italy.
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9
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Christmas MJ, Kaplow IM, Genereux DP, Dong MX, Hughes GM, Li X, Sullivan PF, Hindle AG, Andrews G, Armstrong JC, Bianchi M, Breit AM, Diekhans M, Fanter C, Foley NM, Goodman DB, Goodman L, Keough KC, Kirilenko B, Kowalczyk A, Lawless C, Lind AL, Meadows JRS, Moreira LR, Redlich RW, Ryan L, Swofford R, Valenzuela A, Wagner F, Wallerman O, Brown AR, Damas J, Fan K, Gatesy J, Grimshaw J, Johnson J, Kozyrev SV, Lawler AJ, Marinescu VD, Morrill KM, Osmanski A, Paulat NS, Phan BN, Reilly SK, Schäffer DE, Steiner C, Supple MA, Wilder AP, Wirthlin ME, Xue JR, Birren BW, Gazal S, Hubley RM, Koepfli KP, Marques-Bonet T, Meyer WK, Nweeia M, Sabeti PC, Shapiro B, Smit AFA, Springer MS, Teeling EC, Weng Z, Hiller M, Levesque DL, Lewin HA, Murphy WJ, Navarro A, Paten B, Pollard KS, Ray DA, Ruf I, Ryder OA, Pfenning AR, Lindblad-Toh K, Karlsson EK. Evolutionary constraint and innovation across hundreds of placental mammals. Science 2023; 380:eabn3943. [PMID: 37104599 PMCID: PMC10250106 DOI: 10.1126/science.abn3943] [Citation(s) in RCA: 49] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 12/16/2022] [Indexed: 04/29/2023]
Abstract
Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.
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Affiliation(s)
- Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Irene M. Kaplow
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | | | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Allyson G. Hindle
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Joel C. Armstrong
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ana M. Breit
- School of Biology and Ecology, University of Maine, Orono, ME 04469, USA
| | - Mark Diekhans
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cornelia Fanter
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nicole M. Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Daniel B. Goodman
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Kathleen C. Keough
- Fauna Bio, Inc., Emeryville, CA 94608, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Bogdan Kirilenko
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | - Amanda Kowalczyk
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Colleen Lawless
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Abigail L. Lind
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Lucas R. Moreira
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Ruby W. Redlich
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Louise Ryan
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Alejandro Valenzuela
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Franziska Wagner
- Museum of Zoology, Senckenberg Natural History Collections Dresden, 01109 Dresden, Germany
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ashley R. Brown
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Joana Damas
- The Genome Center, University of California Davis, Davis, CA 95616, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA
| | - Jenna Grimshaw
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Sergey V. Kozyrev
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Kathleen M. Morrill
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Austin Osmanski
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nicole S. Paulat
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Daniel E. Schäffer
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Cynthia Steiner
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Megan A. Supple
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Aryn P. Wilder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Morgan E. Wirthlin
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - James R. Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | | | - Bruce W. Birren
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Steven Gazal
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | | | - Klaus-Peter Koepfli
- Center for Species Survival, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC 20008, USA
- Computer Technologies Laboratory, ITMO University, St. Petersburg 197101, Russia
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
| | - Tomas Marques-Bonet
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08036 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Martin Nweeia
- Department of Comprehensive Care, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Vertebrate Zoology, Canadian Museum of Nature, Ottawa, Ontario K2P 2R1, Canada
- Department of Vertebrate Zoology, Smithsonian Institution, Washington, DC 20002, USA
- Narwhal Genome Initiative, Department of Restorative Dentistry and Biomaterials Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Mark S. Springer
- Department of Evolution, Ecology and Organismal Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Emma C. Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Michael Hiller
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | | | - Harris A. Lewin
- The Genome Center, University of California Davis, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California Davis, Davis, CA 95616, USA
- John Muir Institute for the Environment, University of California Davis, Davis, CA 95616, USA
| | - William J. Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Arcadi Navarro
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, 08005 Barcelona, Spain
- CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Benedict Paten
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Katherine S. Pollard
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - David A. Ray
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Irina Ruf
- Division of Messel Research and Mammalogy, Senckenberg Research Institute and Natural History Museum Frankfurt, 60325 Frankfurt am Main, Germany
| | - Oliver A. Ryder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
- Department of Evolution, Behavior and Ecology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92039, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Elinor K. Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
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10
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Heck DH, Fox MB, Correia Chapman B, McAfee SS, Liu Y. Cerebellar control of thalamocortical circuits for cognitive function: A review of pathways and a proposed mechanism. Front Syst Neurosci 2023; 17:1126508. [PMID: 37064161 PMCID: PMC10097962 DOI: 10.3389/fnsys.2023.1126508] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 03/13/2023] [Indexed: 04/18/2023] Open
Abstract
There is general agreement that cerebrocerebellar interactions via cerebellothalamocortical pathways are essential for a cerebellar cognitive and motor functions. Cerebellothalamic projections were long believed target mainly the ventral lateral (VL) and part of the ventral anterior (VA) nuclei, which project to cortical motor and premotor areas. Here we review new insights from detailed tracing studies, which show that projections from the cerebellum to the thalamus are widespread and reach almost every thalamic subnucleus, including nuclei involved in cognitive functions. These new insights into cerebellothalamic pathways beyond the motor thalamus are consistent with the increasing evidence of cerebellar cognitive function. However, the function of cerebellothalamic pathways and how they are involved in the various motor and cognitive functions of the cerebellum is still unknown. We briefly review literature on the role of the thalamus in coordinating the coherence of neuronal oscillations in the neocortex. The coherence of oscillations, which measures the stability of the phase relationship between two oscillations of the same frequency, is considered an indicator of increased functional connectivity between two structures showing coherent oscillations. Through thalamocortical interactions coherence patterns dynamically create and dissolve functional cerebral cortical networks in a task dependent manner. Finally, we review evidence for an involvement of the cerebellum in coordinating coherence of oscillations between cerebral cortical structures. We conclude that cerebellothalamic pathways provide the necessary anatomical substrate for a proposed role of the cerebellum in coordinating neuronal communication between cerebral cortical areas by coordinating the coherence of oscillations.
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Affiliation(s)
- Detlef H. Heck
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
| | - Mia B. Fox
- Department of Anatomy and Neurobiology, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Brittany Correia Chapman
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Samuel S. McAfee
- St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Yu Liu
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
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11
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Kleven H, Reiten I, Blixhavn CH, Schlegel U, Øvsthus M, Papp EA, Puchades MA, Bjaalie JG, Leergaard TB, Bjerke IE. A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting. Front Neuroinform 2023; 17:1154080. [PMID: 36970659 PMCID: PMC10033636 DOI: 10.3389/fninf.2023.1154080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 02/21/2023] [Indexed: 03/12/2023] Open
Abstract
Brain atlases are widely used in neuroscience as resources for conducting experimental studies, and for integrating, analyzing, and reporting data from animal models. A variety of atlases are available, and it may be challenging to find the optimal atlas for a given purpose and to perform efficient atlas-based data analyses. Comparing findings reported using different atlases is also not trivial, and represents a barrier to reproducible science. With this perspective article, we provide a guide to how mouse and rat brain atlases can be used for analyzing and reporting data in accordance with the FAIR principles that advocate for data to be findable, accessible, interoperable, and re-usable. We first introduce how atlases can be interpreted and used for navigating to brain locations, before discussing how they can be used for different analytic purposes, including spatial registration and data visualization. We provide guidance on how neuroscientists can compare data mapped to different atlases and ensure transparent reporting of findings. Finally, we summarize key considerations when choosing an atlas and give an outlook on the relevance of increased uptake of atlas-based tools and workflows for FAIR data sharing.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Ingvild E. Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
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12
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Yang P, Davidson JO, Zhou KQ, Wilson R, Wassink G, Prasad JD, Bennet L, Gunn AJ, Dean JM. Therapeutic Hypothermia Attenuates Cortical Interneuron Loss after Cerebral Ischemia in Near-Term Fetal Sheep. Int J Mol Sci 2023; 24:ijms24043706. [PMID: 36835117 PMCID: PMC9962824 DOI: 10.3390/ijms24043706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/26/2023] [Accepted: 02/07/2023] [Indexed: 02/16/2023] Open
Abstract
Therapeutic hypothermia significantly improves outcomes after neonatal hypoxic-ischemic (HI) encephalopathy but is only partially protective. There is evidence that cortical inhibitory interneuron circuits are particularly vulnerable to HI and that loss of interneurons may be an important contributor to long-term neurological dysfunction in these infants. In the present study, we examined the hypothesis that the duration of hypothermia has differential effects on interneuron survival after HI. Near-term fetal sheep received sham ischemia or cerebral ischemia for 30 min, followed by cerebral hypothermia from 3 h after ischemia end and continued up to 48 h, 72 h, or 120 h recovery. Sheep were euthanized after 7 days for histology. Hypothermia up to 48 h recovery resulted in moderate neuroprotection of glutamate decarboxylase (GAD)+ and parvalbumin+ interneurons but did not improve survival of calbindin+ cells. Hypothermia up to 72 h recovery was associated with significantly increased survival of all three interneuron phenotypes compared with sham controls. By contrast, while hypothermia up to 120 h recovery did not further improve (or impair) GAD+ or parvalbumin+ neuronal survival compared with hypothermia up to 72 h, it was associated with decreased survival of calbindin+ interneurons. Finally, protection of parvalbumin+ and GAD+ interneurons, but not calbindin+ interneurons, with hypothermia was associated with improved recovery of electroencephalographic (EEG) power and frequency by day 7 after HI. The present study demonstrates differential effects of increasing the duration of hypothermia on interneuron survival after HI in near-term fetal sheep. These findings may contribute to the apparent preclinical and clinical lack of benefit of very prolonged hypothermia.
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13
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Retinoic Acid Prevents the Neuronal Damage Through the Regulation of Parvalbumin in an Ischemic Stroke Model. Neurochem Res 2023; 48:487-501. [PMID: 36245066 DOI: 10.1007/s11064-022-03769-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/22/2022] [Accepted: 09/24/2022] [Indexed: 02/04/2023]
Abstract
Ischemic stroke is a neurological disease that causes brain damage by increasing oxidative stress and ion imbalance. Retinoic acid is a major metabolite of vitamin A and regulates oxidative stress, calcium homeostasis, and cell death. Intracellular calcium is involved in neuronal growth and synaptic plasticity. Parvalbumin is a calcium-binding protein that is mainly expressed in brain. In this study, we investigated whether retinoic acid has neuroprotective effects by controlling intracellular calcium concentration and parvalbumin expression in ischemic brain damage. Middle cerebral artery occlusion (MCAO) was performed to induce cerebral ischemia. Retinoic acid (5 mg/kg) or vehicle was injected into the abdominal cavity for four days before surgery and cerebral cortices were collected 24 h after MCAO for further studies. MCAO damage induced neurological deficits and histopathological changes and decreased parvalbumin expression. However, retinoic acid treatment alleviated these changes. In cultured neurons, glutamate (5 mM) exposure induced neuronal cell death, increased intracellular calcium concentration, and decreased parvalbumin expression. Retinoic acid treatment attenuated these changes against glutamate toxicity in a dose-dependent manner. It also regulates glutamate induced change in bcl-2 and bax expression. The mitigation effects of retinoic acid were greater under non-transfection conditions than under parvalbumin siRNA transfection conditions. Our findings showed that retinoic acid modulates intracellular calcium concentration and parvalbumin expression and prevents apoptosis in ischemic brain injury. In conclusion, retinoic acid contributes to the preservation of neurons from ischemic stroke by controlling parvalbumin expression and apoptosis-related proteins.
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14
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Vijayaragavan K, Cannon BJ, Tebaykin D, Bossé M, Baranski A, Oliveria JP, Bukhari SA, Mrdjen D, Corces MR, McCaffrey EF, Greenwald NF, Sigal Y, Marquez D, Khair Z, Bruce T, Goldston M, Bharadwaj A, Montine KS, Angelo RM, Montine TJ, Bendall SC. Single-cell spatial proteomic imaging for human neuropathology. Acta Neuropathol Commun 2022; 10:158. [PMID: 36333818 PMCID: PMC9636771 DOI: 10.1186/s40478-022-01465-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022] Open
Abstract
Neurodegenerative disorders are characterized by phenotypic changes and hallmark proteopathies. Quantifying these in archival human brain tissues remains indispensable for validating animal models and understanding disease mechanisms. We present a framework for nanometer-scale, spatial proteomics with multiplex ion beam imaging (MIBI) for capturing neuropathological features. MIBI facilitated simultaneous, quantitative imaging of 36 proteins on archival human hippocampus from individuals spanning cognitively normal to dementia. Customized analysis strategies identified cell types and proteopathies in the hippocampus across stages of Alzheimer's disease (AD) neuropathologic change. We show microglia-pathologic tau interactions in hippocampal CA1 subfield in AD dementia. Data driven, sample independent creation of spatial proteomic regions identified persistent neurons in pathologic tau neighborhoods expressing mitochondrial protein MFN2, regardless of cognitive status, suggesting a survival advantage. Our study revealed unique insights from multiplexed imaging and data-driven approaches for neuropathologic analysis and serves broadly as a methodology for spatial proteomic analysis of archival human neuropathology. TEASER: Multiplex Ion beam Imaging enables deep spatial phenotyping of human neuropathology-associated cellular and disease features.
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Affiliation(s)
| | - Bryan J Cannon
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Dmitry Tebaykin
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Marc Bossé
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Alex Baranski
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - J P Oliveria
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Syed A Bukhari
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Dunja Mrdjen
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Erin F McCaffrey
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Noah F Greenwald
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Diana Marquez
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Zumana Khair
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Trevor Bruce
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Mako Goldston
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Anusha Bharadwaj
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Kathleen S Montine
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - R Michael Angelo
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Thomas J Montine
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sean C Bendall
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA.
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15
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Merkulyeva N, Mikhalkin А, Kostareva A, Vavilova T. Transient neurochemical features of the perigeniculate neurons during early postnatal development of the cat. J Comp Neurol 2022; 530:3193-3208. [PMID: 36036192 DOI: 10.1002/cne.25402] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 11/07/2022]
Abstract
The thalamic reticular nucleus receives axons from the thalamic sensory nuclei and the cerebral cortex. The visual part of this nucleus in carnivores is the perigeniculate nucleus located dorsal to the lateral geniculate nucleus. The perigeniculate nucleus participates in the modulation of visual processing and in the transition of synchronized slow rhythmicity during sleep into desynchronized high-frequency activity during arousal and consists of inhibitory neurons. The main neurochemical markers for perigeniculate neurons are glutamic acid decarboxylase and Ca2+ -binding protein parvalbumin. Previous studies of postnatal development focused on the morphological features of the perigeniculate nucleus; however, its neurochemistry remains poorly understood. In this study, we focused on the postnatal development of perigeniculate neurons using immunohistochemical labeling of parvalbumin, two related Ca2+ -binding proteins (calretinin and calbindin), glutamic acid decarboxylase, and a common neuronal protein, NeuN, in kittens that were 0-123 days old and in adult cats. In parallel with the well-known dominant neuronal populations expressing parvalbumin and GAD67 and persisting until adulthood, transient populations expressing calretinin and calbindin were observed. The calbindin-positive neurons were similar to the main perigeniculate population and showed close morphological features and parvalbumin coexpression. In contrast, the calretinin-positive neurons differed in their morphological characteristics and did not express GAD67, thus distinguishing them from the majority of perigeniculate neurons. A possible link between these populations was revealed, and the development of thalamocortical processing is discussed.
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Affiliation(s)
- Natalia Merkulyeva
- Lab Neuromorphology, Pavlov Institute of Physiology RAS, Saint-Petersburg, Russia
| | - Аleksandr Mikhalkin
- Lab Neuromorphology, Pavlov Institute of Physiology RAS, Saint-Petersburg, Russia
| | - Anna Kostareva
- Institution of Molecular Biology and Genetics, Almazov National Medical Research Centre, Saint-Petersburg, Russia
| | - Tatyana Vavilova
- Institution of Molecular Biology and Genetics, Almazov National Medical Research Centre, Saint-Petersburg, Russia
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16
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Li Y, Zhang B, Pan X, Wang Y, Xu X, Wang R, Liu Z. Dopamine-Mediated Major Depressive Disorder in the Neural Circuit of Ventral Tegmental Area-Nucleus Accumbens-Medial Prefrontal Cortex: From Biological Evidence to Computational Models. Front Cell Neurosci 2022; 16:923039. [PMID: 35966208 PMCID: PMC9373714 DOI: 10.3389/fncel.2022.923039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 06/06/2022] [Indexed: 12/01/2022] Open
Abstract
Major depressive disorder (MDD) is a serious psychiatric disorder, with an increasing incidence in recent years. The abnormal dopaminergic pathways of the midbrain cortical and limbic system are the key pathological regions of MDD, particularly the ventral tegmental area- nucleus accumbens- medial prefrontal cortex (VTA-NAc-mPFC) neural circuit. MDD usually occurs with the dysfunction of dopaminergic neurons in VTA, which decreases the dopamine concentration and metabolic rate in NAc/mPFC brain regions. However, it has not been fully explained how abnormal dopamine concentration levels affect this neural circuit dynamically through the modulations of ion channels and synaptic activities. We used Hodgkin-Huxley and dynamical receptor binding model to establish this network, which can quantitatively explain neural activity patterns observed in MDD with different dopamine concentrations by changing the kinetics of some ion channels. The simulation replicated some important pathological patterns of MDD at the level of neurons and circuits with low dopamine concentration, such as the decreased action potential frequency in pyramidal neurons of mPFC with significantly reduced burst firing frequency. The calculation results also revealed that NaP and KS channels of mPFC pyramidal neurons played key roles in the functional regulation of this neural circuit. In addition, we analyzed the synaptic currents and local field potentials to explain the mechanism of MDD from the perspective of dysfunction of excitation-inhibition balance, especially the disinhibition effect in the network. The significance of this article is that we built the first computational model to illuminate the effect of dopamine concentrations for the NAc-mPFC-VTA circuit between MDD and normal groups, which can be used to quantitatively explain the results of existing physiological experiments, predict the results for unperformed experiments and screen possible drug targets.
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Affiliation(s)
- Yuanxi Li
- Institute for Cognitive Neurodynamics, School of Mathematics, East China University of Science and Technology, Shanghai, China
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Bing Zhang
- Department of Anesthesiology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China
- Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China
| | - Xiaochuan Pan
- Institute for Cognitive Neurodynamics, School of Mathematics, East China University of Science and Technology, Shanghai, China
| | - Yihong Wang
- Institute for Cognitive Neurodynamics, School of Mathematics, East China University of Science and Technology, Shanghai, China
| | - Xuying Xu
- Institute for Cognitive Neurodynamics, School of Mathematics, East China University of Science and Technology, Shanghai, China
| | - Rubin Wang
- Institute for Cognitive Neurodynamics, School of Mathematics, East China University of Science and Technology, Shanghai, China
- *Correspondence: Rubin Wang, ;
| | - Zhiqiang Liu
- Department of Anesthesiology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China
- Anesthesia and Brain Function Research Institute, Tongji University School of Medicine, Shanghai, China
- Zhiqiang Liu,
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17
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Structural and Functional Deviations of the Hippocampus in Schizophrenia and Schizophrenia Animal Models. Int J Mol Sci 2022; 23:ijms23105482. [PMID: 35628292 PMCID: PMC9143100 DOI: 10.3390/ijms23105482] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/09/2022] [Accepted: 05/11/2022] [Indexed: 01/04/2023] Open
Abstract
Schizophrenia is a grave neuropsychiatric disease which frequently onsets between the end of adolescence and the beginning of adulthood. It is characterized by a variety of neuropsychiatric abnormalities which are categorized into positive, negative and cognitive symptoms. Most therapeutical strategies address the positive symptoms by antagonizing D2-dopamine-receptors (DR). However, negative and cognitive symptoms persist and highly impair the life quality of patients due to their disabling effects. Interestingly, hippocampal deviations are a hallmark of schizophrenia and can be observed in early as well as advanced phases of the disease progression. These alterations are commonly accompanied by a rise in neuronal activity. Therefore, hippocampal formation plays an important role in the manifestation of schizophrenia. Furthermore, studies with animal models revealed a link between environmental risk factors and morphological as well as electrophysiological abnormalities in the hippocampus. Here, we review recent findings on structural and functional hippocampal abnormalities in schizophrenic patients and in schizophrenia animal models, and we give an overview on current experimental approaches that especially target the hippocampus. A better understanding of hippocampal aberrations in schizophrenia might clarify their impact on the manifestation and on the outcome of this severe disease.
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18
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PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements. Nat Commun 2022; 13:2475. [PMID: 35513404 PMCID: PMC9072354 DOI: 10.1038/s41467-022-30168-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 04/20/2022] [Indexed: 12/19/2022] Open
Abstract
Ultra-multiplexed fluorescence imaging requires the use of spectrally overlapping fluorophores to label proteins and then to unmix the images of the fluorophores. However, doing this remains a challenge, especially in highly heterogeneous specimens, such as the brain, owing to the high degree of variation in the emission spectra of fluorophores in such specimens. Here, we propose PICASSO, which enables more than 15-color imaging of spatially overlapping proteins in a single imaging round without using any reference emission spectra. PICASSO requires an equal number of images and fluorophores, which enables such advanced multiplexed imaging, even with bandpass filter-based microscopy. We show that PICASSO can be used to achieve strong multiplexing capability in diverse applications. By combining PICASSO with cyclic immunofluorescence staining, we achieve 45-color imaging of the mouse brain in three cycles. PICASSO provides a tool for multiplexed imaging with high accessibility and accuracy for a broad range of researchers. Ultra-multiplexed fluorescence imaging is currently difficult. Here the authors report PICASSO which enables 15-colour imaging of spatially overlapping proteins in a single-round of imaging; they combine it with cyclic immunofluorescence to achieve 45-colour imaging of the mouse brain in 3 cycles.
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19
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Roohi N, Valizadeh A. Role of Interaction Delays in the Synchronization of Inhibitory Networks. Neural Comput 2022; 34:1425-1447. [PMID: 35534004 DOI: 10.1162/neco_a_01500] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 01/25/2022] [Indexed: 11/04/2022]
Abstract
Neural oscillations provide a means for efficient and flexible communication among different brain areas. Understanding the mechanisms of the generation of brain oscillations is crucial to determine principles of communication and information transfer in the brain circuits. It is well known that the inhibitory neurons play a major role in the generation of oscillations in the gamma range, in pure inhibitory networks, or in the networks composed of excitatory and inhibitory neurons. In this study, we explore the impact of different parameters and, in particular, the delay in the transmission of the signals between the neurons, on the dynamics of inhibitory networks. We show that increasing delay in a reasonable range increases the synchrony and stabilizes the oscillations. Unstable gamma oscillations characterized by a highly variable amplitude of oscillations can be observed in an intermediate range of delays. We show that in this range of delays, other experimentally observed phenomena such as sparse firing, variable amplitude and period, and the correlation between the instantaneous amplitude and period could be observed. The results broaden our understanding of the mechanism of the generation of the gamma oscillations in the inhibitory networks, known as the ING (interneuron-gamma) mechanism.
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Affiliation(s)
- Nariman Roohi
- Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran.,School of Biological Sciences, Institute for Research in Fundamental Sciences, Niavaran, Tehran, Iran
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DOPAMAP, high-resolution images of dopamine 1 and 2 receptor expression in developing and adult mouse brains. Sci Data 2022; 9:175. [PMID: 35440585 PMCID: PMC9018709 DOI: 10.1038/s41597-022-01268-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 03/08/2022] [Indexed: 11/21/2022] Open
Abstract
The dopaminergic system undergoes major reorganization during development, a period especially vulnerable to mental disorders. Forebrain neurons expressing dopamine 1 and 2 receptors (D1R and D2R, respectively) play a key role in this system. However, neuroanatomical information about the typical development of these neurons is sparse and scattered across publications investigating one or a few brain regions. We here present a public online collection of microscopic images of immunohistochemically stained serial sections from male and female mice at five stages of development (postnatal day 17 (P17), P25, P35, P49, and adult), showing the distribution of D1R and D2R expressing neurons across the forebrain. All images from adult brains are registered to the Allen Mouse brain Common Coordinate Framework, while images from P17-P35 age groups are registered to spatially modified atlas versions matching the morphology of young brains. This online resource provides microscopic visualization of the developing dopaminergic system in mice, which is suitable as a benchmark reference for performing new experiments and building computational models of the brain. Measurement(s) | mRNA expression | Technology Type(s) | transgenic Mouse • immunohistochemistry staining method | Sample Characteristic - Organism | Mus musculus |
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21
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Modular microcircuit organization of the presubicular head-direction map. Cell Rep 2022; 39:110684. [PMID: 35417686 DOI: 10.1016/j.celrep.2022.110684] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 02/16/2022] [Accepted: 03/24/2022] [Indexed: 11/22/2022] Open
Abstract
Our internal sense of direction is thought to rely on the activity of head-direction (HD) neurons. We find that the mouse dorsal presubiculum (PreS), a key structure in the cortical representation of HD, displays a modular "patch-matrix" organization, which is conserved across species (including human). Calbindin-positive layer 2 neurons within the "matrix" form modular recurrent microcircuits, while inputs from the anterodorsal and laterodorsal thalamic nuclei are non-overlapping and target the "patch" and "matrix" compartments, respectively. The apical dendrites of identified HD cells are largely restricted within the "matrix," pointing to a non-random sampling of patterned inputs and to a precise structure-function architecture. Optogenetic perturbation of modular recurrent microcircuits results in a drastic tonic suppression of firing only in a subpopulation of HD neurons. Altogether, our data reveal a modular microcircuit organization of the PreS HD map and point to the existence of cell-type-specific microcircuits that support the cortical HD representation.
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Attili SM, Moradi K, Wheeler DW, Ascoli GA. Quantification of neuron types in the rodent hippocampal formation by data mining and numerical optimization. Eur J Neurosci 2022; 55:1724-1741. [PMID: 35301768 PMCID: PMC10026515 DOI: 10.1111/ejn.15639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 01/25/2022] [Accepted: 02/28/2022] [Indexed: 11/29/2022]
Abstract
Quantifying the population sizes of distinct neuron types in different anatomical regions is an essential step towards establishing a brain cell census. Although estimates exist for the total neuronal populations in different species, the number and definition of each specific neuron type are still intensively investigated. Hippocampome.org is an open-source knowledge base with morphological, physiological and molecular information for 122 neuron types in the rodent hippocampal formation. While such framework identifies all known neuron types in this system, their relative abundances remain largely unknown. This work quantitatively estimates the counts of all Hippocampome.org neuron types by literature mining and numerical optimization. We report the number of neurons in each type identified by main neurotransmitter (glutamate or GABA) and axonal-dendritic patterns throughout 26 subregions and layers of the dentate gyrus, Ammon's horn, subiculum and entorhinal cortex. We produce by sensitivity analysis reliable numerical ranges for each type and summarize the amounts across broad neuronal families defined by biomarkers expression and firing dynamics. Study of density distributions indicates that the number of dendritic-targeting interneurons, but not of other neuronal classes, is independent of anatomical volumes. All extracted values, experimental evidence and related software code are released on Hippocampome.org.
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Affiliation(s)
- Sarojini M. Attili
- Center for Neural Informatics, Structures, & Plasticity, Interdisciplinary Neuroscience Program, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Keivan Moradi
- Center for Neural Informatics, Structures, & Plasticity, Interdisciplinary Neuroscience Program, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
| | - Diek W. Wheeler
- Bioengineering Department and Volgenau School of Engineering, George Mason University, Fairfax, VA, USA
| | - Giorgio A. Ascoli
- Center for Neural Informatics, Structures, & Plasticity, Interdisciplinary Neuroscience Program, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA, USA
- Bioengineering Department and Volgenau School of Engineering, George Mason University, Fairfax, VA, USA
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23
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Godoy LD, Prizon T, Rossignoli MT, Leite JP, Liberato JL. Parvalbumin Role in Epilepsy and Psychiatric Comorbidities: From Mechanism to Intervention. Front Integr Neurosci 2022; 16:765324. [PMID: 35250498 PMCID: PMC8891758 DOI: 10.3389/fnint.2022.765324] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 01/24/2022] [Indexed: 12/22/2022] Open
Abstract
Parvalbumin is a calcium-binding protein present in inhibitory interneurons that play an essential role in regulating many physiological processes, such as intracellular signaling and synaptic transmission. Changes in parvalbumin expression are deeply related to epilepsy, which is considered one of the most disabling neuropathologies. Epilepsy is a complex multi-factor group of disorders characterized by periods of hypersynchronous activity and hyperexcitability within brain networks. In this scenario, inhibitory neurotransmission dysfunction in modulating excitatory transmission related to the loss of subsets of parvalbumin-expressing inhibitory interneuron may have a prominent role in disrupted excitability. Some studies also reported that parvalbumin-positive interneurons altered function might contribute to psychiatric comorbidities associated with epilepsy, such as depression, anxiety, and psychosis. Understanding the epileptogenic process and comorbidities associated with epilepsy have significantly advanced through preclinical and clinical investigation. In this review, evidence from parvalbumin altered function in epilepsy and associated psychiatric comorbidities were explored with a translational perspective. Some advances in potential therapeutic interventions are highlighted, from current antiepileptic and neuroprotective drugs to cutting edge modulation of parvalbumin subpopulations using optogenetics, designer receptors exclusively activated by designer drugs (DREADD) techniques, transcranial magnetic stimulation, genome engineering, and cell grafting. Creating new perspectives on mechanisms and therapeutic strategies is valuable for understanding the pathophysiology of epilepsy and its psychiatric comorbidities and improving efficiency in clinical intervention.
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Affiliation(s)
- Lívea Dornela Godoy
- Department of Psychology, Faculty of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Tamiris Prizon
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - Matheus Teixeira Rossignoli
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - João Pereira Leite
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- João Pereira Leite,
| | - José Luiz Liberato
- Department of Neuroscience and Behavioral Sciences, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
- *Correspondence: José Luiz Liberato,
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Lu Z, Xu X, Li D, Sun N, Lin S. Sea Cucumber Peptides Attenuated the Scopolamine-Induced Memory Impairment in Mice and Rats and the Underlying Mechanism. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:157-170. [PMID: 34932331 DOI: 10.1021/acs.jafc.1c06475] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Social stress and unhealthy diets lead to memory impairment, triggering health problems. This study aimed to determine the mitigating effect and regulation mechanism of sea cucumber peptides (SCP) against memory impairment. Here, scopolamine-induced memory impairment in mouse and rat models was used based on behavioral tests, a histological staining technique, Fourier transform infrared microscopy, and gas-chromatographic analysis as well as a Western blotting method. SCP improved the behavioral performance and regulated the disorder of the cholinergic system in mouse models in a dose-dependent manner. Therefore, the underlying mechanism was explored in high-dose SCP using mouse and rat models. SCP repaired damaged neuronal cells, enhanced the Nissl body number, increased the unsaturated lipid level, and activated the long-term potentiation (LTP) pathway (p-CaMKII, p-CREB, and BDNF), both in the mouse and rat hippocampus. The results indicated that SCP upregulated the LTP pathway and unsaturated lipid level to combat scopolamine-induced memory impairment, suggesting that SCP was a potential candidate for neurological recovery.
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Affiliation(s)
- Zhiqiang Lu
- National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, P.R. China
| | - Xiaomeng Xu
- National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, P.R. China
| | - Dongmei Li
- National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, P.R. China
| | - Na Sun
- National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, P.R. China
| | - Songyi Lin
- National Engineering Research Center of Seafood, School of Food Science and Technology, Dalian Polytechnic University, Dalian 116034, P.R. China
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