scholarly journals A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents

2021 ◽  
Author(s):  
Thomas Pircher ◽  
Bianca Pircher ◽  
Andreas Feigenspan
Keyword(s):  
Machine Learning ◽  
Neurotransmitter Release ◽  
Automated Analysis ◽  
Cell Types ◽  
Synaptic Activity ◽  
Mouse Retina ◽  
Synaptic Current ◽  
Algorithm Comparison ◽  
Depth Analysis ◽  
The Central Nervous System

Spontaneous synaptic activity is a hallmark of neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity of synaptic current trajectories has either precluded an in-depth analysis or it has forced human observers to resort to manual or semi-automated approaches based on subjective amplitude and area threshold settings. Both procedures are time-consuming, error-prone and likely affected by human bias. Here, we present three complimentary methods for a fully automated analysis of spontaneous excitatory postsynaptic currents measured in major cell types of the mouse retina and in a primary culture of mouse auditory cortex. Two approaches rely on classical threshold methods, while the third represents a novel machine learning-based algorithm. Comparison with frequently used existing methods demonstrates the suitability of our algorithms for an unbiased and efficient analysis of synaptic signals in the central nervous system.

scholarly journals A Novel Machine Learning-based Approach for the Detection and Analysis of Spontaneous Synaptic Currents

2021 ◽  
Author(s):  
Thomas Pircher ◽  
Bianca Pircher ◽  
Andreas Feigenspan
Keyword(s):  
Machine Learning ◽  
Neurotransmitter Release ◽  
Automated Analysis ◽  
Cell Types ◽  
Synaptic Activity ◽  
Mouse Retina ◽  
Synaptic Current ◽  
Algorithm Comparison ◽  
Depth Analysis ◽  
The Central Nervous System

Abstract Spontaneous synaptic activity is a hallmark of neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity of synaptic current trajectories has either precluded an in-depth analysis or it has forced human observers to resort to manual or semi-automated approaches based on subjective amplitude and area threshold settings. Both procedures are time-consuming, error-prone and likely affected by human bias. Here, we present three complimentary methods for a fully automated analysis of spontaneous excitatory postsynaptic currents measured in major cell types of the mouse retina and in a primary culture of mouse auditory cortex. Two approaches rely on classical threshold methods, while the third represents a novel machine learning-based algorithm. Comparison with frequently used existing methods demonstrates the suitability of our algorithms for an unbiased and efficient analysis of synaptic signals in the central nervous system.

Advances in the Prediction of Protein Subcellular Locations with Machine Learning

2019 ◽  
Vol 14 (5) ◽  
pp. 406-421 ◽  
Author(s):  
Ting-He Zhang ◽  
Shao-Wu Zhang
Keyword(s):  
Machine Learning ◽  
Feature Fusion ◽  
Protein Sequences ◽  
Subcellular Location ◽  
Automated Analysis ◽  
Cellular Level ◽  
Machine Learning Algorithms ◽  
Feature Representation ◽  
Protein Subcellular Location ◽  
Protein Subcellular Locations

Background: Revealing the subcellular location of a newly discovered protein can bring insight into their function and guide research at the cellular level. The experimental methods currently used to identify the protein subcellular locations are both time-consuming and expensive. Thus, it is highly desired to develop computational methods for efficiently and effectively identifying the protein subcellular locations. Especially, the rapidly increasing number of protein sequences entering the genome databases has called for the development of automated analysis methods. Methods: In this review, we will describe the recent advances in predicting the protein subcellular locations with machine learning from the following aspects: i) Protein subcellular location benchmark dataset construction, ii) Protein feature representation and feature descriptors, iii) Common machine learning algorithms, iv) Cross-validation test methods and assessment metrics, v) Web servers. Result & Conclusion: Concomitant with a large number of protein sequences generated by highthroughput technologies, four future directions for predicting protein subcellular locations with machine learning should be paid attention. One direction is the selection of novel and effective features (e.g., statistics, physical-chemical, evolutional) from the sequences and structures of proteins. Another is the feature fusion strategy. The third is the design of a powerful predictor and the fourth one is the protein multiple location sites prediction.

scholarly journals Neural Stem Cells: What Happens When They Go Viral?

Viruses ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1468
Author(s):  
Yashika S. Kamte ◽  
Manisha N. Chandwani ◽  
Alexa C. Michaels ◽  
Lauren A. O’Donnell
Keyword(s):  
Stem Cells ◽  
Neural Stem Cells ◽  
Viral Infections ◽  
Wide Spectrum ◽  
Cell Types ◽  
Developmental Abnormalities ◽  
Multipotent Progenitor Cells ◽  
The Central Nervous System ◽  
Simplex Virus ◽  
The Brain

Viruses that infect the central nervous system (CNS) are associated with developmental abnormalities as well as neuropsychiatric and degenerative conditions. Many of these viruses such as Zika virus (ZIKV), cytomegalovirus (CMV), and herpes simplex virus (HSV) demonstrate tropism for neural stem cells (NSCs). NSCs are the multipotent progenitor cells of the brain that have the ability to form neurons, astrocytes, and oligodendrocytes. Viral infections often alter the function of NSCs, with profound impacts on the growth and repair of the brain. There are a wide spectrum of effects on NSCs, which differ by the type of virus, the model system, the cell types studied, and the age of the host. Thus, it is a challenge to predict and define the consequences of interactions between viruses and NSCs. The purpose of this review is to dissect the mechanisms by which viruses can affect survival, proliferation, and differentiation of NSCs. This review also sheds light on the contribution of key antiviral cytokines in the impairment of NSC activity during a viral infection, revealing a complex interplay between NSCs, viruses, and the immune system.

scholarly journals The Microbiota–Gut–Brain Axis and Alzheimer Disease. From Dysbiosis to Neurodegeneration: Focus on the Central Nervous System Glial Cells

2021 ◽  
Vol 10 (11) ◽  
pp. 2358
Author(s):  
Maria Grazia Giovannini ◽  
Daniele Lana ◽  
Chiara Traini ◽  
Maria Giuliana Vannucchi
Keyword(s):  
Alzheimer Disease ◽  
Glial Cells ◽  
Cell Types ◽  
The Past ◽  
The Central Nervous System ◽  
Diseased State ◽  
The Brain ◽  
Alzheimer Disease Pathogenesis ◽  
Brain Homeostasis

The microbiota–gut system can be thought of as a single unit that interacts with the brain via the “two-way” microbiota–gut–brain axis. Through this axis, a constant interplay mediated by the several products originating from the microbiota guarantees the physiological development and shaping of the gut and the brain. In the present review will be described the modalities through which the microbiota and gut control each other, and the main microbiota products conditioning both local and brain homeostasis. Much evidence has accumulated over the past decade in favor of a significant association between dysbiosis, neuroinflammation and neurodegeneration. Presently, the pathogenetic mechanisms triggered by molecules produced by the altered microbiota, also responsible for the onset and evolution of Alzheimer disease, will be described. Our attention will be focused on the role of astrocytes and microglia. Numerous studies have progressively demonstrated how these glial cells are important to ensure an adequate environment for neuronal activity in healthy conditions. Furthermore, it is becoming evident how both cell types can mediate the onset of neuroinflammation and lead to neurodegeneration when subjected to pathological stimuli. Based on this information, the role of the major microbiota products in shifting the activation profiles of astrocytes and microglia from a healthy to a diseased state will be discussed, focusing on Alzheimer disease pathogenesis.

scholarly journals Made to Measure: Patient-Tailored Treatment of Multiple Sclerosis Using Cell-Based Therapies

2021 ◽  
Vol 22 (14) ◽  
pp. 7536
Author(s):  
Inez Wens ◽  
Ibo Janssens ◽  
Judith Derdelinckx ◽  
Megha Meena ◽  
Barbara Willekens ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Autoimmune Diseases ◽  
Stromal Cells ◽  
Mononuclear Cells ◽  
Treatment Options ◽  
Cell Types ◽  
Peripheral Blood Mononuclear ◽  
Tailored Treatment ◽  
Key Issues ◽  
The Central Nervous System

Currently, there is still no cure for multiple sclerosis (MS), which is an autoimmune and neurodegenerative disease of the central nervous system. Treatment options predominantly consist of drugs that affect adaptive immunity and lead to a reduction of the inflammatory disease activity. A broad range of possible cell-based therapeutic options are being explored in the treatment of autoimmune diseases, including MS. This review aims to provide an overview of recent and future advances in the development of cell-based treatment options for the induction of tolerance in MS. Here, we will focus on haematopoietic stem cells, mesenchymal stromal cells, regulatory T cells and dendritic cells. We will also focus on less familiar cell types that are used in cell therapy, including B cells, natural killer cells and peripheral blood mononuclear cells. We will address key issues regarding the depicted therapies and highlight the major challenges that lie ahead to successfully reverse autoimmune diseases, such as MS, while minimising the side effects. Although cell-based therapies are well known and used in the treatment of several cancers, cell-based treatment options hold promise for the future treatment of autoimmune diseases in general, and MS in particular.

scholarly journals Mitochondrial DNA Heteroplasmy as an Informational Reservoir Dynamically Linked to Metabolic and Immunological Processes Associated with COVID-19 Neurological Disorders

2021 ◽  
Author(s):  
George B. Stefano ◽  
Richard M. Kream
Keyword(s):  
Mitochondrial Dna ◽  
Mitochondrial Function ◽  
Neurological Disorders ◽  
Nuclear Dna ◽  
Mitochondrial Dynamics ◽  
Cell Types ◽  
Tissue Specific ◽  
Copy Numbers ◽  
The Central Nervous System ◽  
Mitochondrial Dna Heteroplasmy

AbstractMitochondrial DNA (mtDNA) heteroplasmy is the dynamically determined co-expression of wild type (WT) inherited polymorphisms and collective time-dependent somatic mutations within individual mtDNA genomes. The temporal expression and distribution of cell-specific and tissue-specific mtDNA heteroplasmy in healthy individuals may be functionally associated with intracellular mitochondrial signaling pathways and nuclear DNA gene expression. The maintenance of endogenously regulated tissue-specific copy numbers of heteroplasmic mtDNA may represent a sensitive biomarker of homeostasis of mitochondrial dynamics, metabolic integrity, and immune competence. Myeloid cells, monocytes, macrophages, and antigen-presenting dendritic cells undergo programmed changes in mitochondrial metabolism according to innate and adaptive immunological processes. In the central nervous system (CNS), the polarization of activated microglial cells is dependent on strategically programmed changes in mitochondrial function. Therefore, variations in heteroplasmic mtDNA copy numbers may have functional consequences in metabolically competent mitochondria in innate and adaptive immune processes involving the CNS. Recently, altered mitochondrial function has been demonstrated in the progression of coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Accordingly, our review is organized to present convergent lines of empirical evidence that potentially link expression of mtDNA heteroplasmy by functionally interactive CNS cell types to the extent and severity of acute and chronic post-COVID-19 neurological disorders.

scholarly journals Inhibition of Vesicular Secretion in Both Neuronal and Nonneuronal Cells by a Retargeted Endopeptidase Derivative ofClostridium botulinum Neurotoxin Type A

2000 ◽  
Vol 68 (5) ◽  
pp. 2587-2593 ◽  
Author(s):  
John A. Chaddock ◽  
John R. Purkiss ◽  
Lorna M. Friis ◽  
Janice D. Broadbridge ◽  
Michael J. Duggan ◽  
...  
Keyword(s):  
Neurotransmitter Release ◽  
Botulinum Neurotoxin ◽  
Type A ◽  
Cell Types ◽  
Snare Complex ◽  
Cell Binding ◽  
Vesicle Docking ◽  
Botulinum Neurotoxin Type A ◽  
Clostridial Neurotoxins ◽  
Dose Dependent

ABSTRACT Clostridial neurotoxins potently and specifically inhibit neurotransmitter release in defined cell types by a mechanism that involves cleavage of specific components of the vesicle docking/fusion complex, the SNARE complex. A derivative of the type A neurotoxin fromClostridium botulinum (termed LHN/A) that retains catalytic activity can be prepared by proteolysis. The LHN/A, however, lacks the putative native binding domain (HC) of the neurotoxin and is thus unable to bind to neurons and effect inhibition of neurotransmitter release. Here we report the chemical conjugation of LHN/A to an alternative cell-binding ligand, wheat germ agglutinin (WGA). When applied to a variety of cell lines, including those that are ordinarily resistant to the effects of neurotoxin, WGA-LHN/A conjugate potently inhibits secretory responses in those cells. Inhibition of release is demonstrated to be ligand mediated and dose dependent and to occur via a mechanism involving endopeptidase-dependent cleavage of the natural botulinum neurotoxin type A substrate. These data confirm that the function of the HC domain of C. botulinumneurotoxin type A is limited to binding to cell surface moieties. The data also demonstrate that the endopeptidase and translocation functions of the neurotoxin are effective in a range of cell types, including those of nonneuronal origin. These observations lead to the conclusion that a clostridial endopeptidase conjugate that can be used to investigate SNARE-mediated processes in a variety of cells has been successfully generated.

scholarly journals Comparisons of neuroinflammation, microglial activation, and degeneration of the locus coeruleus-norepinephrine system in APP/PS1 and aging mice

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Song Cao ◽  
Daniel W. Fisher ◽  
Guadalupe Rodriguez ◽  
Tian Yu ◽  
Hongxin Dong
Keyword(s):  
Spinal Cord ◽  
Locus Coeruleus ◽  
Microglial Activation ◽  
Healthy Aging ◽  
Cell Types ◽  
Norepinephrine System ◽  
Protective Processes ◽  
The Central Nervous System ◽  
Brain And Spinal Cord ◽  
The Brain

Abstract Background The role of microglia in Alzheimer’s disease (AD) pathogenesis is becoming increasingly important, as activation of these cell types likely contributes to both pathological and protective processes associated with all phases of the disease. During early AD pathogenesis, one of the first areas of degeneration is the locus coeruleus (LC), which provides broad innervation of the central nervous system and facilitates norepinephrine (NE) transmission. Though the LC-NE is likely to influence microglial dynamics, it is unclear how these systems change with AD compared to otherwise healthy aging. Methods In this study, we evaluated the dynamic changes of neuroinflammation and neurodegeneration in the LC-NE system in the brain and spinal cord of APP/PS1 mice and aged WT mice using immunofluorescence and ELISA. Results Our results demonstrated increased expression of inflammatory cytokines and microglial activation observed in the cortex, hippocampus, and spinal cord of APP/PS1 compared to WT mice. LC-NE neuron and fiber loss as well as reduced norepinephrine transporter (NET) expression was more evident in APP/PS1 mice, although NE levels were similar between 12-month-old APP/PS1 and WT mice. Notably, the degree of microglial activation, LC-NE nerve fiber loss, and NET reduction in the brain and spinal cord were more severe in 12-month-old APP/PS1 compared to 12- and 24-month-old WT mice. Conclusion These results suggest that elevated neuroinflammation and microglial activation in the brain and spinal cord of APP/PS1 mice correlate with significant degeneration of the LC-NE system.

scholarly journals Automated analysis of filopodial length and spatially resolved protein concentration via adaptive shape tracking

2016 ◽  
Vol 27 (22) ◽  
pp. 3616-3626 ◽  
Author(s):  
Tanumoy Saha ◽  
Isabel Rathmann ◽  
Abhiyan Viplav ◽  
Sadhana Panzade ◽  
Isabell Begemann ◽  
...  
Keyword(s):  
Protein Concentration ◽  
Growth Dynamics ◽  
Automated Analysis ◽  
Cell Types ◽  
Control Mechanisms ◽  
Spatially Resolved ◽  
Novel Approach ◽  
Associated Proteins

Filopodia are dynamic, actin-rich structures that transiently form on a variety of cell types. To understand the underlying control mechanisms requires precise monitoring of localization and concentration of individual regulatory and structural proteins as filopodia elongate and subsequently retract. Although several methods exist that analyze changes in filopodial shape, a software solution to reliably correlate growth dynamics with spatially resolved protein concentration along the filopodium independent of bending, lateral shift, or tilting is missing. Here we introduce a novel approach based on the convex-hull algorithm for parallel analysis of growth dynamics and relative spatiotemporal protein concentration along flexible filopodial protrusions. Detailed in silico tests using various geometries confirm that our technique accurately tracks growth dynamics and relative protein concentration along the filopodial length for a broad range of signal distributions. To validate our technique in living cells, we measure filopodial dynamics and quantify spatiotemporal localization of filopodia-associated proteins during the filopodial extension–retraction cycle in a variety of cell types in vitro and in vivo. Together these results show that the technique is suitable for simultaneous analysis of growth dynamics and spatiotemporal protein enrichment along filopodia. To allow readily application by other laboratories, we share source code and instructions for software handling.

scholarly journals Planet of the AAVs: The Spinal Cord Injury Episode

Biomedicines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 613
Author(s):  
Katerina Stepankova ◽  
Pavla Jendelova ◽  
Lucia Machova Urdzikova
Keyword(s):  
Spinal Cord ◽  
Gene Therapy ◽  
Spinal Cord Injury ◽  
Cell Types ◽  
Specific Cell ◽  
Adeno Associated Virus ◽  
Adequate Treatment ◽  
Cord Injury ◽  
The Central Nervous System ◽  
Transgene Delivery

The spinal cord injury (SCI) is a medical and life-disrupting condition with devastating consequences for the physical, social, and professional welfare of patients, and there is no adequate treatment for it. At the same time, gene therapy has been studied as a promising approach for the treatment of neurological and neurodegenerative disorders by delivering remedial genes to the central nervous system (CNS), of which the spinal cord is a part. For gene therapy, multiple vectors have been introduced, including integrating lentiviral vectors and non-integrating adeno-associated virus (AAV) vectors. AAV vectors are a promising system for transgene delivery into the CNS due to their safety profile as well as long-term gene expression. Gene therapy mediated by AAV vectors shows potential for treating SCI by delivering certain genetic information to specific cell types. This review has focused on a potential treatment of SCI by gene therapy using AAV vectors.

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