MicrogliaST: a web server for microglia spatiotemportal pattern analysis in normal and disordered brains

2022 ◽  
Author(s):  
Zhong Xiaoling ◽  
Li Feng ◽  
Tan Guiyuan ◽  
Yi Li ◽  
Zhao Jiaxin ◽  
...  
Keyword(s):  
Single Cell ◽  
Neural Development ◽  
Brain Regions ◽  
Disease Treatment ◽  
Sequencing Technologies ◽  
The Central Nervous System ◽  
Living Organisms ◽  
Analytical Tools ◽  
The Brain

Brain is the most complex organ of living organisms, as the celebrated cells in the brain, microglia play an indispensable role in the brain's immune microenvironment. Microglia have critical roles not only in neural development and homeostasis, but also in neurodegenerative diseases and malignant of the central nervous system. However, little is known about the dynamic characteristics of microglia during development or disease conditions. Recently, the single-cell RNA sequencing technologies have become possible to characterize the heterogeneity of immune system in brain. But it posed computational challenges on integrating and utilizing the massive published datasets to dissect the spatiotemporal characterization of microglia. Here, we present microgliaST (bio-bigdata.hrbmu.edu.cn/MST), a database consisting of single-cell microglia transcriptomes across multiple brain regions and developmental periods. Based on high-quality microglia markers collected from published papers, we annotated and constructed human and mouse transcriptomic profiles of 273,374 microglias, comprising 12 regions, 12 periods and 3 conditions (normal, disease, treatment). In addition, MicrogliaST provides multiple analytical tools to elucidate the landscape of microglia under disorder conditions, conduct personalized difference analysis and spatiotemporal dynamic analysis. More importantly, microgliaST paves an ingenious way to the study of brain environment, and also provides insights into clinical therapy assessments.

scholarly journals Characterization of the brain functional architecture of psychostimulant withdrawal using single-cell whole brain imaging

2019 ◽  
Author(s):  
Adam Kimbrough ◽  
Lauren C. Smith ◽  
Marsida Kallupi ◽  
Sierra Simpson ◽  
Andres Collazo ◽  
...  
Keyword(s):  
Single Cell ◽  
Brain Imaging ◽  
Drugs Of Abuse ◽  
Brain Regions ◽  
Functional Architecture ◽  
Whole Brain ◽  
Similarities And Differences ◽  
Drug Dependent ◽  
The Brain

AbstractNumerous brain regions have been identified as contributing to addiction-like behaviors, but unclear is the way in which these brain regions as a whole lead to addiction. The search for a final common brain pathway that is involved in addiction remains elusive. To address this question, we used male C57BL/6J mice and performed single-cell whole-brain imaging of neural activity during withdrawal from cocaine, methamphetamine, and nicotine. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical- to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway that leads to addiction.Significance StatementA key aspect of treating drug abuse is understanding similarities and differences of how drugs of abuse affect the brain. In the present study we examined how the brain is altered during withdrawal from psychostimulants. We found that each drug produced a unique pattern of activity in the brain, but that brains in withdrawal from cocaine and methamphetamine shared similar features. Interestingly, we found the major common link between withdrawal from all psychostimulants, when compared to controls, was a shift in the broad organization of the brain in the form of reduced modularity. Reduced modularity has been shown in several brain disorders, including traumatic brain injury, and dementia, and may be the common link between drugs of abuse.

scholarly journals Intracranial And Intraorbital Rosai Dorfman Disease

2020 ◽  
Vol 11 (4) ◽  
pp. 5187-5191
Author(s):  
Sivapriya G Nair ◽  
Jina Raj ◽  
Sajesh K Menon ◽  
Suhas Udayakumaran ◽  
Roshni P R
Keyword(s):  
Histopathological Study ◽  
Disease Treatment ◽  
Mri Scan ◽  
Massive Lymphadenopathy ◽  
Rosai Dorfman Disease ◽  
History Of ◽  
The Central Nervous System ◽  
The Right ◽  
The Brain ◽  
Suprasellar Extension

Rosai Dorfman disease is a rare histiocytic disorder. It is also known as Sinus Histiocytosis. It is with massive lymphadenopathy involves an overproduction of a type of white blood cell. The disease is rarely associated with intracranial and intraorbital involvement. Intracranial Rosai-Dorfman can mimic meningioma. Other pathologies also underline its pathologies. Here, we report a nine-year-old boy with a history of proptosis of the right eye and presenting with multiple skull lesions. Histopathological study revealed Sphenopetroclival lesion, which features that of Rosai Dorfman Disease. His MRI scan of the brain was taken, which showed evidence of right optic nerve meningioma with sella and suprasellar extension, causing severe proptosis. The child underwent right frontotemporal craniotomy with petrosectomy and Transylvanian, subtemporal approach to multicompartmental Rosai-Dorfmans lesion. After four months, the patient had a recurrence of the disease on which chemotherapy and steroids were started, which also did not show much response while taking an MRI scan. A corticosteroid is a useful option in the Central Nervous System Rosai Dorfman disease treatment. But this patient showed a negative outcome to the treatment.

scholarly journals A Graphlet-Based Topological Characterization of the Resting-State Network in Healthy People

2021 ◽  
Vol 15 ◽  
Author(s):  
Paolo Finotelli ◽  
Carlo Piccardi ◽  
Edie Miglio ◽  
Paolo Dulio
Keyword(s):  
Resting State ◽  
Brain Regions ◽  
Brain Network ◽  
Induced Subgraphs ◽  
Topological Characterization ◽  
Network Information ◽  
The Subject ◽  
Euclidean Distances ◽  
The Brain

In this paper, we propose a graphlet-based topological algorithm for the investigation of the brain network at resting state (RS). To this aim, we model the brain as a graph, where (labeled) nodes correspond to specific cerebral areas and links are weighted connections determined by the intensity of the functional magnetic resonance imaging (fMRI). Then, we select a number of working graphlets, namely, connected and non-isomorphic induced subgraphs. We compute, for each labeled node, its Graphlet Degree Vector (GDV), which allows us to associate a GDV matrix to each one of the 133 subjects of the considered sample, reporting how many times each node of the atlas “touches” the independent orbits defined by the graphlet set. We focus on the 56 independent columns (i.e., non-redundant orbits) of the GDV matrices. By aggregating their count all over the 133 subjects and then by sorting each column independently, we obtain a sorted node table, whose top-level entries highlight the nodes (i.e., brain regions) most frequently touching each of the 56 independent graphlet orbits. Then, by pairwise comparing the columns of the sorted node table in the top-k entries for various values of k, we identify sets of nodes that are consistently involved with high frequency in the 56 independent graphlet orbits all over the 133 subjects. It turns out that these sets consist of labeled nodes directly belonging to the default mode network (DMN) or strongly interacting with it at the RS, indicating that graphlet analysis provides a viable tool for the topological characterization of such brain regions. We finally provide a validation of the graphlet approach by testing its power in catching network differences. To this aim, we encode in a Graphlet Correlation Matrix (GCM) the network information associated with each subject then construct a subject-to-subject Graphlet Correlation Distance (GCD) matrix based on the Euclidean distances between all possible pairs of GCM. The analysis of the clusters induced by the GCD matrix shows a clear separation of the subjects in two groups, whose relationship with the subject characteristics is investigated.

CNS myeloid cell heterogeneity at the single-cell level

Neuroforum ◽  
2019 ◽  
Vol 25 (3) ◽  
pp. 195-204
Author(s):  
Chotima Böttcher ◽  
Roman Sankowski ◽  
Josef Priller ◽  
Marco Prinz
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Myeloid Cell ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Mass Cytometry ◽  
Dynamic Regulation ◽  
The Central Nervous System ◽  
Disease Profiling ◽  
The Brain

Abstract The cellular composition of the central nervous system (CNS) is highly complex and dynamic. Regulation of this complexity is increasingly recognized to be spatially and temporally dependent during development, homeostasis and disease. Context-dependent cellular heterogeneity was shown for neuroectodermal cells as well as the myeloid compartment of the CNS. The brain myeloid compartment comprises microglia and other CNS-associated macrophages. These are brain-resident cells with critical roles in brain development, maintenance, and immune responses during states of disease. Profiling of CNS myeloid cell heterogeneity has been greatly facilitated in the past years by development of high-throughput technologies for single-cell analysis. This review summarizes current insights into heterogeneity of the CNS myeloid cell population determined by single-cell RNA sequencing and mass cytometry. The results offer invaluable insights into CNS biology and will facilitate the development of therapies for neurodegenerative and neuroinflammatory pathologies.

scholarly journals STAB: a spatio-temporal cell atlas of the human brain

2020 ◽  
Vol 49 (D1) ◽  
pp. D1029-D1037
Author(s):  
Liting Song ◽  
Shaojun Pan ◽  
Zichao Zhang ◽  
Longhao Jia ◽  
Wei-Hua Chen ◽  
...  
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Temporal Dynamics ◽  
Cell Types ◽  
Brain Regions ◽  
Molecular Characteristics ◽  
Great Effort ◽  
Brain Functions ◽  
Spatio Temporal ◽  
The Brain

Abstract The human brain is the most complex organ consisting of billions of neuronal and non-neuronal cells that are organized into distinct anatomical and functional regions. Elucidating the cellular and transcriptome architecture underlying the brain is crucial for understanding brain functions and brain disorders. Thanks to the single-cell RNA sequencing technologies, it is becoming possible to dissect the cellular compositions of the brain. Although great effort has been made to explore the transcriptome architecture of the human brain, a comprehensive database with dynamic cellular compositions and molecular characteristics of the human brain during the lifespan is still not available. Here, we present STAB (a Spatio-Temporal cell Atlas of the human Brain), a database consists of single-cell transcriptomes across multiple brain regions and developmental periods. Right now, STAB contains single-cell gene expression profiling of 42 cell subtypes across 20 brain regions and 11 developmental periods. With STAB, the landscape of cell types and their regional heterogeneity and temporal dynamics across the human brain can be clearly seen, which can help to understand both the development of the normal human brain and the etiology of neuropsychiatric disorders. STAB is available at http://stab.comp-sysbio.org.

scholarly journals Tissue-Specificity of Antibodies Raised Against TrkB and p75NTR Receptors; Implications for Platelets as Models of Neurodegenerative Diseases

2021 ◽  
Vol 12 ◽  
Author(s):  
Samuel Fleury ◽  
Imane Boukhatem ◽  
Jessica Le Blanc ◽  
Mélanie Welman ◽  
Marie Lordkipanidzé
Keyword(s):  
Central Nervous System ◽  
Neurological Disorders ◽  
Blood Circulation ◽  
Tissue Specificity ◽  
Receptor Kinase ◽  
Calcium Dependent ◽  
Neuronal Growth Factor ◽  
The Central Nervous System ◽  
The Brain

Platelets and neurons share many similarities including comparable secretory granule types with homologous calcium-dependent secretory mechanisms as well as internalization, sequestration and secretion of many neurotransmitters. Thus, platelets present a high potential to be used as peripheral biomarkers to reflect neuronal pathologies. The brain-derived neurotrophic factor (BDNF) acts as a neuronal growth factor involved in learning and memory through the binding of two receptors, the tropomyosin receptor kinase B (TrkB) and the 75 kDa pan-neurotrophic receptor (p75NTR). In addition to its expression in the central nervous system, BDNF is found in much greater quantities in blood circulation, where it is largely stored within platelets. Levels 100- to 1,000-fold those of neurons make platelets the most important peripheral reservoir of BDNF. This led us to hypothesize that platelets would express canonical BDNF receptors, i.e., TrkB and p75NTR, and that the receptors on platelets would bear significant resemblance to the ones found in the brain. However, herein we report discrepancies regarding detection of these receptors using antibody-based assays, with antibodies displaying important tissue-specificity. The currently available antibodies raised against TrkB and p75NTR should therefore be used with caution to study platelets as models for neurological disorders. Rigorous characterization of antibodies and bioassays appears critical to understand the interplay between platelet and neuronal biology of BDNF.

scholarly journals Effects of tiletamine-xylazine-tramadol combination and its specific antagonist on AMPK in the brain of rats

2019 ◽  
Vol 63 (2) ◽  
pp. 285-292
Author(s):  
Ning Ma ◽  
Xin Li ◽  
Hong-bin Wang ◽  
Li Gao ◽  
Jian-hua Xiao
Keyword(s):  
Mrna Expression ◽  
Opposite Effect ◽  
Brain Regions ◽  
Control Group ◽  
Sprague Dawley ◽  
Sd Rats ◽  
The Central Nervous System ◽  
Specific Antagonist ◽  
Sedation And Analgesia ◽  
The Brain

AbstractIntroduction:Tiletamine-xylazine-tramadol (XFM) has few side effects and can provide good sedation and analgesia. Adenosine 5’-monophosphate-activated protein kinase (AMPK) can attenuate trigeminal neuralgia. The study aimed to investigate the effects of XFM and its specific antagonist on AMPK in different regions of the brain.Material and Methods:A model of XFM in the rat was established. A total of 72 Sprague Dawley (SD) rats were randomly divided into three equally sized groups: XFM anaesthesia (M group), antagonist (W group), and XFM with antagonist interactive groups (MW group). Eighteen SD rats were in the control group and were injected intraperitoneally with saline (C group). The rats were sacrificed and the cerebral cortex, cerebellum, hippocampus, thalamus, and brain stem were immediately separated, in order to detect AMPKα mRNA expression by quantitative PCR.Results:XFM was able to increase the mRNA expression of AMPKα1 and AMPKα2 in all brain regions, and the antagonist caused the opposite effect, although the effects of XFM could not be completely reversed in some areas.Conclusion:XFM can influence the expression of AMPK in the central nervous system of the rat, which can provide a reference for the future development of anaesthetics for animals.

scholarly journals Astrocytes, Noradrenaline, α1-Adrenoreceptors, and Neuromodulation: Evidence and Unanswered Questions

2021 ◽  
Vol 15 ◽  
Author(s):  
Jérôme Wahis ◽  
Matthew G. Holt
Keyword(s):  
Critical Appraisal ◽  
Brain Regions ◽  
Synaptic Activity ◽  
Physiological Effects ◽  
Astrocyte Heterogeneity ◽  
Main Effect ◽  
The Central Nervous System ◽  
Noradrenergic Modulation ◽  
The Brain ◽  
Experimental Strategies

Noradrenaline is a major neuromodulator in the central nervous system (CNS). It is released from varicosities on neuronal efferents, which originate principally from the main noradrenergic nuclei of the brain – the locus coeruleus – and spread throughout the parenchyma. Noradrenaline is released in response to various stimuli and has complex physiological effects, in large part due to the wide diversity of noradrenergic receptors expressed in the brain, which trigger diverse signaling pathways. In general, however, its main effect on CNS function appears to be to increase arousal state. Although the effects of noradrenaline have been researched extensively, the majority of studies have assumed that noradrenaline exerts its effects by acting directly on neurons. However, neurons are not the only cells in the CNS expressing noradrenaline receptors. Astrocytes are responsive to a range of neuromodulators – including noradrenaline. In fact, noradrenaline evokes robust calcium transients in astrocytes across brain regions, through activation of α1-adrenoreceptors. Crucially, astrocytes ensheath neurons at synapses and are known to modulate synaptic activity. Hence, astrocytes are in a key position to relay, or amplify, the effects of noradrenaline on neurons, most notably by modulating inhibitory transmission. Based on a critical appraisal of the current literature, we use this review to argue that a better understanding of astrocyte-mediated noradrenaline signaling is therefore essential, if we are ever to fully understand CNS function. We discuss the emerging concept of astrocyte heterogeneity and speculate on how this might impact the noradrenergic modulation of neuronal circuits. Finally, we outline possible experimental strategies to clearly delineate the role(s) of astrocytes in noradrenergic signaling, and neuromodulation in general, highlighting the urgent need for more specific and flexible experimental tools.

scholarly journals Brain composition in Heliconius butterflies, post-eclosion growth and experience dependent neuropil plasticity

2015 ◽  
Author(s):  
Stephen H Montgomery ◽  
Richard M Merrill ◽  
Swidbert R Ott
Keyword(s):  
Behavioral Ecology ◽  
Neural Development ◽  
Mushroom Body ◽  
Brain Regions ◽  
Mushroom Bodies ◽  
Heliconius Butterflies ◽  
Sensory Adaptations ◽  
Differential Expansion ◽  
The Brain

Behavioral and sensory adaptations are often based in the differential expansion of brain components. These volumetric differences represent changes in investment, processing capacity and/or connectivity, and can be used to investigate functional and evolutionary relationships between different brain regions, and between brain composition and behavioral ecology. Here, we describe the brain composition of two species of Heliconius butterflies, a long-standing study system for investigating ecological adaptation and speciation. We confirm a previous report of striking mushroom body expansion, and explore patterns of post-eclosion growth and experience-dependent plasticity in neural development. This analysis uncovers age- and experience-dependent post-emergence mushroom body growth comparable to that in foraging hymenoptera, but also identifies plasticity in several other neuropil. An interspecific analysis indicates that Heliconius display remarkable levels of investment in mushroom bodies for a lepidopteran, and indeed rank highly compared to other insects. Our analyses lay the foundation for future comparative and experimental analyses that will establish Heliconius as a useful case study in evolutionary neurobiology.

The somatic error hypothesis of anxiety

2018 ◽  
Author(s):  
Sahib S. Khalsa ◽  
Justin S. Feinstein
Keyword(s):  
Central Nervous System ◽  
Physiological State ◽  
Brain Regions ◽  
Novel Therapies ◽  
Body State ◽  
Long Term Changes ◽  
The Central Nervous System ◽  
And Behavior ◽  
The Brain

A regulatory battle for control ensues in the central nervous system following a mismatch between the current physiological state of an organism as mapped in viscerosensory brain regions and the predicted body state as computed in visceromotor control regions. The discrepancy between the predicted and current body state (i.e. the “somatic error”) signals a need for corrective action, motivating changes in both cognition and behavior. This chapter argues that anxiety disorders are fundamentally driven by somatic errors that fail to be adaptively regulated, leaving the organism in a state of dissonance where the predicted body state is perpetually out of line with the current body state. Repeated failures to quell somatic error can result in long-term changes to interoceptive circuitry within the brain. This chapter explores the neuropsychiatric sequelae that can emerge following chronic allostatic dysregulation of somatic errors and discusses novel therapies that might help to correct this dysregulation.

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