scholarly journals Gap Junction Channels of Innexins and Connexins: Relations and Computational Perspectives

2019 ◽  
Vol 20 (10) ◽  
pp. 2476 ◽  
Author(s):  
Alejandro Sánchez ◽  
Carlos Castro ◽  
Dora-Luz Flores ◽  
Everardo Gutiérrez ◽  
Pierre Baldi
Keyword(s):  
Gap Junction ◽  
Cell Communication ◽  
Machine Learning Techniques ◽  
Computational Techniques ◽  
Tissue Formation ◽  
Clinical Tool ◽  
Mediated Communication ◽  
Gap Junction Channels ◽  
Learning Techniques ◽  
Cell Propagation

Gap junction (GJ) channels in invertebrates have been used to understand cell-to-cell communication in vertebrates. GJs are a common form of intercellular communication channels which connect the cytoplasm of adjacent cells. Dysregulation and structural alteration of the gap junction-mediated communication have been proven to be associated with a myriad of symptoms and tissue-specific pathologies. Animal models relying on the invertebrate nervous system have exposed a relationship between GJs and the formation of electrical synapses during embryogenesis and adulthood. The modulation of GJs as a therapeutic and clinical tool may eventually provide an alternative for treating tissue formation-related diseases and cell propagation. This review concerns the similarities between Hirudo medicinalis innexins and human connexins from nucleotide and protein sequence level perspectives. It also sets forth evidence of computational techniques applied to the study of proteins, sequences, and molecular dynamics. Furthermore, we propose machine learning techniques as a method that could be used to study protein structure, gap junction inhibition, metabolism, and drug development.

Potassium transfer assay for cell communication: effects of phorbol esters, retinoic acid, and furosemide

1991 ◽  
Vol 261 (6) ◽  
pp. C1115-C1122 ◽  
Author(s):  
M. L. Ledbetter ◽  
P. L. Medrek ◽  
B. M. Spinney
Keyword(s):  
Retinoic Acid ◽  
Gap Junction ◽  
Mass Culture ◽  
Phorbol Esters ◽  
Cell Communication ◽  
Ion Transfer ◽  
Mediated Communication ◽  
Human Diploid Fibroblasts ◽  
Communication Effects ◽  
State Content

Using a mass culture assay for the contact-dependent transfer of potassium among cells with intrinsic differences in ability to concentrate it, we have investigated the ability of several drugs to influence this form of cell communication. We concentrated on 12-O-tetradecanoylphorbol-13-acetate (TPA), which is known to interfere with gap junction-mediated communication and ion transport in several other systems, and compared its effects with those of its inactive derivative, 4-O-methyl-TPA. We found that the communication between mouse BALB/c 3T3 cells and human diploid fibroblasts was reduced in the presence of TPA but not O-methyl-TPA and that this inhibition was not obscured by small but measurable influences of TPA on steady-state content and transport of 86Rb+. We confirmed these findings using an autoradiographic assay for transfer of uridine derivatives among cells in contact. We also showed that retinoic acid had no effect on communication in the ion transfer assay but that furosemide, an inhibitor of Na(+)-K(+)-2Cl- cotransport, stimulated ion transfer dramatically both in the presence and absence of TPA. These results indicate both the promise and the limitations of the potassium transfer assay for identifying potential modulators of gap junction-mediated cell communication.

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

2019 ◽  
Vol 26 (8) ◽  
pp. 601-619 ◽  
Author(s):  
Amit Sagar ◽  
Bin Xue
Keyword(s):  
Machine Learning ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Experimental Methods ◽  
Machine Learning Techniques ◽  
Computational Techniques ◽  
Biological Processes ◽  
Complete Spectrum ◽  
Future Developments ◽  
Learning Techniques

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

scholarly journals Connexin and pannexin mediated cell–cell communication

2007 ◽  
Vol 3 (3) ◽  
pp. 199-208 ◽  
Author(s):  
Eliana Scemes ◽  
Sylvia O. Suadicani ◽  
Gerhard Dahl ◽  
David C. Spray
Keyword(s):  
Gap Junction ◽  
Cell Communication ◽  
Structural Features ◽  
Paracrine Signaling ◽  
Gap Junction Channels ◽  
Metabolic Coupling ◽  
Junctional Coupling ◽  
Intercellular Channels ◽  
Gap Junction Proteins ◽  
Junction Proteins

AbstractIn this review, we briefly summarize what is known about the properties of the three families of gap junction proteins, connexins, innexins and pannexins, emphasizing their importance as intercellular channels that provide ionic and metabolic coupling and as non-junctional channels that can function as a paracrine signaling pathway. We discuss that two distinct groups of proteins form gap junctions in deuterostomes (connexins) and protostomes (innexins), and that channels formed of the deuterostome homologues of innexins (pannexins) differ from connexin channels in terms of important structural features and activation properties. These differences indicate that the two families of gap junction proteins serve distinct, complementary functions in deuterostomes. In several tissues, including the CNS, both connexins and pannexins are involved in intercellular communication, but have different roles. Connexins mainly contribute by forming the intercellular gap junction channels, which provide for junctional coupling and define the communication compartments in the CNS. We also provide new data supporting the concept that pannexins form the non-junctional channels that play paracrine roles by releasing ATP and, thus, modulating the range of the intercellular Ca2+-wave transmission between astrocytes in culture.

scholarly journals Connexin Gap Junctions and Hemichannels in Modulating Lens Redox Homeostasis and Oxidative Stress in Cataractogenesis

Antioxidants ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1374
Author(s):  
Yumeng Quan ◽  
Yu Du ◽  
Yuxin Tong ◽  
Sumin Gu ◽  
Jean X. Jiang
Keyword(s):  
Oxidative Stress ◽  
Gap Junction ◽  
Redox Homeostasis ◽  
Cell Communication ◽  
Underlying Mechanism ◽  
Post Translational Modifications ◽  
Gap Junction Channels ◽  
Mediate Cell ◽  
The Impact

The lens is continuously exposed to oxidative stress insults, such as ultraviolet radiation and other oxidative factors, during the aging process. The lens possesses powerful oxidative stress defense systems to maintain its redox homeostasis, one of which employs connexin channels. Connexins are a family of proteins that form: (1) Hemichannels that mediate the communication between the intracellular and extracellular environments, and (2) gap junction channels that mediate cell-cell communication between adjacent cells. The avascular lens transports nutrition and metabolites through an extensive network of connexin channels, which allows the passage of small molecules, including antioxidants and oxidized wastes. Oxidative stress-induced post-translational modifications of connexins, in turn, regulates gap junction and hemichannel permeability. Recent evidence suggests that dysfunction of connexins gap junction channels and hemichannels may induce cataract formation through impaired redox homeostasis. Here, we review the recent advances in the knowledge of connexin channels in lens redox homeostasis and their response to cataract-related oxidative stress by discussing two major aspects: (1) The role of lens connexins and channels in oxidative stress and cataractogenesis, and (2) the impact and underlying mechanism of oxidative stress in regulating connexin channels.

Mechanical stimulation initiates cell-to-cell calcium signaling in ovine lens epithelial cells

1996 ◽  
Vol 109 (2) ◽  
pp. 355-365 ◽  
Author(s):  
G.C. Churchill ◽  
M.M. Atkinson ◽  
C.F. Louis
Keyword(s):  
Plasma Membrane ◽  
Epithelial Cells ◽  
Gap Junction ◽  
Mechanical Stimulation ◽  
Primary Cultures ◽  
Channel Blockers ◽  
Extracellular Medium ◽  
Gap Junction Channels ◽  
Cell Propagation ◽  
Cytosolic Factor

Although abnormalities in calcium regulation have been implicated in the development of most forms of cataract, the mechanisms by which Ca2+ is regulated in the cells of the ocular lens remain poorly defined. Cell-to-cell Ca2+ signaling was investigated in primary cultures of ovine epithelial cells using the Ca(2+)-reporter dye fura-2 and fluorescence microscopy. Mechanical stimulation of a single cell with a micropipette initiated a propagated increase in cytosolic free Ca2+ that spread from the stimulated cell through 2–8 tiers of surrounding cells. During this intercellular Ca2+ wave, cytosolic Ca2+ increased 2- to 12-fold from resting levels of approximately 100 nM. Nanomolar extracellular Ca2+ did not affect the cell-to-cell propagation of the Ca2+ wave, but reduced the magnitude of the cytosolic Ca2+ increases, which was most evident in the mechanically-stimulated cell. Depletion of intracellular Ca2+ stores with thapsigargin eliminated the propagated intercellular Ca2+ wave, but did not prevent the cytosolic Ca2+ increase in the mechanically-stimulated cell, which required extracellular Ca2+ and was attenuated by the addition of the Ca2+ channel blockers Ni2+, Gd3+ and La3+ to the medium. These results are most easily explained by a mechanically-activated channel in the plasma membrane of the stimulated cell. The propagated increase in cytosolic Ca2+ appeared to be communicated to adjacent cells by the passage of an intracellular messenger other than Ca2+ through gap junction channels. However, if the plasma membrane of the mechanically-stimulated cell was ruptured such that there was loss of cytosolic contents, the increase in cytosolic Ca2+ in the surrounding cells was elicited by both a messenger passing through gap junction channels and by a cytosolic factor(s) diffusing through the extracellular medium. These results demonstrate the existence of intercellular Ca2+ signaling in lens cells, which may play a role in regulating cytosolic Ca2+ in the intact lens.

scholarly journals Differential regulation of distinct types of gap junction channels by similar phosphorylating conditions.

1995 ◽  
Vol 6 (12) ◽  
pp. 1707-1719 ◽  
Author(s):  
B R Kwak ◽  
M M Hermans ◽  
H R De Jonge ◽  
S M Lohmann ◽  
H J Jongsma ◽  
...  
Keyword(s):  
Gap Junction ◽  
Single Channel ◽  
Cell Communication ◽  
Differential Regulation ◽  
Cell Coupling ◽  
Gap Junction Channels ◽  
Physiological Importance ◽  
Gap Junction Channel ◽  
Conductance States ◽  
Channel Properties

Studies on physiological modulation of intercellular communication mediated by protein kinases are often complicated by the fact that cells express multiple gap junction proteins (connexins; Cx). Changes in cell coupling can be masked by simultaneous opposite regulation of the gap junction channel types expressed. We have examined the effects of activators and inhibitors of protein kinase A (PKA), PKC, and PKG on permeability and single channel conductance of gap junction channels composed of Cx45, Cx43, or Cx26 subunits. To allow direct comparison between these Cx, SKHep1 cells, which endogenously express Cx45, were stably transfected with cDNAs coding for Cx43 or Cx26. Under control conditions, the distinct types of gap junction channels could be distinguished on the basis of their permeability and single channel properties. Under various phosphorylating conditions, these channels behaved differently. Whereas agonists/antagonist of PKA did not affect permeability and conductance of all gap junction channels, variable changes were observed under PKC stimulation. Cx45 channels exhibited an additional conductance state, the detection of the smaller conductance states of Cx43 channels was favored, and Cx26 channels were less often observed. In contrast to the other kinases, agonists/antagonist of PKG affected permeability and conductance of Cx43 gap junction channels only. Taken together, these results show that distinct types of gap junction channels are differentially regulated by similar phosphorylating conditions. This differential regulation may be of physiological importance during modulation of cell-to-cell communication of more complex cell systems.

scholarly journals Big data and democratic speech: Predicting deliberative quality using machine learning techniques

2021 ◽  
Vol 14 (2) ◽  
pp. 205979912110104
Author(s):  
Eleonore Fournier-Tombs ◽  
Michael K. MacKenzie
Keyword(s):  
Machine Learning ◽  
Speech Acts ◽  
Large Scale ◽  
Large Datasets ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Computational Techniques ◽  
Learning Techniques ◽  
Campaign Speeches ◽  
Northern Territories

This article explores techniques for using supervised machine learning to study discourse quality in large datasets. We explain and illustrate the computational techniques that we have developed to facilitate a large-scale study of deliberative quality in Canada’s three northern territories: Yukon, Northwest Territories, and Nunavut. This larger study involves conducting comparative analyses of hundreds of thousands of parliamentary speech acts since the creation of Nunavut 20 years ago. Without computational techniques, we would be unable to conduct such an ambitious and comprehensive analysis of deliberative quality. The purpose of this article is to demonstrate the machine learning techniques that we have developed with the hope that they might be used and improved by other communications scholars who are interested in conducting textual analyses using large datasets. Other possible applications of these techniques might include analyses of campaign speeches, party platforms, legislation, judicial rulings, online comments, newspaper articles, and television or radio commentaries.

scholarly journals Heteromerization of Innexin Gap Junction Proteins Regulates Epithelial Tissue Organization in Drosophila

2006 ◽  
Vol 17 (4) ◽  
pp. 1676-1685 ◽  
Author(s):  
Corinna Lehmann ◽  
Hildegard Lechner ◽  
Birgit Löer ◽  
Martin Knieps ◽  
Sonja Herrmann ◽  
...  
Keyword(s):  
Gap Junctions ◽  
Gap Junction ◽  
Ectopic Expression ◽  
Cell Communication ◽  
Epithelial Tissue ◽  
Surface Plasmon Resonance Analysis ◽  
Gap Junction Channels ◽  
Tissue Organization ◽  
Biochemical Fractionation

Gap junctions consist of clusters of intercellular channels, which enable direct cell-to-cell communication and adhesion in animals. Whereas deuterostomes, including all vertebrates, use members of the connexin and pannexin multiprotein families to assemble gap junction channels, protostomes such as Drosophila and Caenorhabditis elegans use members of the innexin protein family. The molecular composition of innexin-containing gap junctions and the functional significance of innexin oligomerization for development are largely unknown. Here, we report that heteromerization of Drosophila innexins 2 and 3 is crucial for epithelial organization and polarity of the embryonic epidermis. Both innexins colocalize in epithelial cell membranes. Innexin3 is mislocalized to the cytoplasm in innexin2 mutants and is recruited into ectopic expression domains defined by innexin2 misexpression. Conversely, RNA interference (RNAi) knockdown of innexin3 causes mislocalization of innexin2 and of DE-cadherin, causing cell polarity defects in the epidermis. Biochemical interaction studies, surface plasmon resonance analysis, transgenesis, and biochemical fractionation experiments demonstrate that both innexins interact via their C-terminal cytoplasmic domains during the assembly of heteromeric channels. Our data provide the first molecular and functional demonstration that innexin heteromerization occurs in vivo and reveal insight into a molecular mechanism by which innexins may oligomerize into heteromeric gap junction channels.

scholarly journals MACHINE LEARNING PER CARATTERIZZARE GLI ATTACCHI TERRORISTICI

2020 ◽  
Author(s):  
Silvia Figini
Keyword(s):  
Machine Learning ◽  
Domain Knowledge ◽  
Machine Learning Techniques ◽  
Terrorist Attacks ◽  
Strategy Development ◽  
Computational Techniques ◽  
Law Enforcement Agencies ◽  
Policy Makers ◽  
Learning Techniques ◽  
Recurrent Patterns

For security departments understanding the dynamics of terrorist events finding significant and recurrent patterns can have an important impact in the counter-terrorism strategy development. Machine learning techniques coupled with domain knowledge are useful to understand terrorist behaviours with high accuracy, thus helping policy makers for time-sensitive understanding of terrorist activity, which can enable precautions to avoid against future attacks. In this paper different computational techniques, able to derive relationships among terrorist attacks and detect terrorist behaviours, are used on the Global Terrorism Database. The analysis proposed in this paper could help security and government departments to prevent terrorist attacks and to reduce financial, human and political losses. Furthermore, this information can be useful for law enforcement agencies to propose reactive strategies.

A critical review on predicting drug-drug reactions using machine learning techniques

2021 ◽  
Vol 16 (10) ◽  
pp. 186-188
Author(s):  
A. Saran Kumar ◽  
R. Rekha
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Computational Techniques ◽  
Learning Approaches ◽  
Drug Reactions ◽  
Advantages And Disadvantages ◽  
Learning Techniques ◽  
Comprehensive Survey

Drug-Drug interaction (DDI) refers to change in the reaction of a drug when the person consumes other drug. It is the main cause of avertable bad drug reactions causing major issues on the patient’s health and the information systems. Many computational techniques have been used to predict the adverse effects of drug-drug interactions. However, these methods do not provide adequate information required for the prediction of DDI. Machine learning algorithms provide a set of methods which can increase the accuracy and success rate for well-defined issues with abundant data. This study provides a comprehensive survey on most popular machine learning and deep learning algorithms used by the researchers to predict DDI. In addition, the advantages and disadvantages of various machine learning approaches have also been discussed here.

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