19 research outputs found
Context Map Analysis of Fake News in Social Media: A Contextualized Visualization Approach
Visualization tools in text analytics are typically based on content analysis, using -gram frequencies or topic models which output commonly used words, phrases, or topics in a text corpus. However, the interpretation of these visual output and summary labels can be incomplete or misleading when words or phrases are taken out of context. We use a novel Context Map approach to create a connected network of -grams by considering the frequency in which they are used together in the same context. We combine network optimization techniques with embedded representation models to generate an visualization interface with clearer and more accurate interpretation potential. In this paper, we apply our Context Map method to analyze fake news in social media. We compare news article veracity (true versus false news) with orientation (left, mainstream, or right). Our approach provides a rich context analysis of the language used in true versus fake news
Quantum Informational Dark Energy: Dark energy from forgetting
We suggest that dark energy has a quantum informational origin. Landauer's
principle associated with the erasure of quantum information at a cosmic
horizon implies the non-zero vacuum energy having effective negative pressure.
Assuming the holographic principle, the minimum free energy condition, and the
Gibbons-Hawking temperature for the cosmic event horizon we obtain the
holographic dark energy with the parameter , which is consistent
with the current observational data. It is also shown that both the
entanglement energy and the horizon energy can be related to Landauer's
principle.Comment: revtex,8 pages, 2 figures more detailed arguments adde
Generation and characterization of human induced pluripotent stem cell line METUi001-A from a 25-year-old male patient with relapsing-remitting multiple sclerosis
© 2021Multiple sclerosis is a chronic disease characterized by inflammation, demyelination, and axonal damage in the central nervous system. Here, we established an induced pluripotent stem cell (iPSC) line METUi001-A from the peripheral blood mononuclear cells of a 25-year-old male individual with clinically diagnosed Relapsing-Remitting Multiple Sclerosis (RRMS) using the integration-free Sendai reprogramming method. We demonstrated that the iPSCs are free of exogenous Sendai reprogramming vectors, have a normal male karyotype, express pluripotency markers, and differentiate into the three germ layers. The iPSC line can serve as a valuable resource to generate cellular model systems to investigate molecular mechanisms underlying RRMS
Rhetoric Mining for Fake News: Identifying Moves of Persuasion and Disinformation
We propose a novel Rhetoric Mining methodology to identify moves of persuasion used in disinformation of social media news posts. Rhetoric Mining combines qualitative methodologies and rhetorical theory analysis with machine learning techniques to automatically identify rhetorical moves. Rhetorical moves are instances of discourse intentionally used to persuade an audience. Rhetoric Mining converts the qualitative detection of persuasive moves into quantified rhetoric instance vectors which can be used to characterize rhetorical styles of a text. We identify rhetorical styles of persuasion (news posts with high positive responses, likes, shares, or re-posts) as well as disinformation (news posts that are persuasive but false)
Changing Views: Pre-suasion in a Reddit Discussion Community
Social media allows people to connect and disconnect easily, which leads to more polarization over time. Polarization and the emergence of echo chambers pose a threat to humanity, implying a need to design a healthy social ecosystem in the digital space. Online platforms fostering an environment for good faith discussions and diverse opinions could serve this need. ChangeMyView community of Reddit can be a good example for such an environment because of community-specific characteristics. In this study, utilizing elaboration likelihood model and Cialdiniâs pre-suasion, we study the effect of the reward system on individualsâ persuasion mechanisms. Our research design employs a mixed-methods approach in which we investigate (1) the persuasion strategies used in the community and (2) the information processing mechanisms of the community members. We believe that this study will provide insights into potential features of a healthier social ecosystem in digital spaces
Phase-rotated MR spectroscopy using dual-PRESS: theory and application in human brain
Phaseârotation spectroscopic acquisition is inherently different from the popular signalâaveraging method. Phaseârotation will be described theoretically and experimentally in this article. Traditionally, a single echo is acquired in a PRESS or STEAM sequence at a particular TE. If a longâTE spectrum is desired, then another echo is usually acquired at a longer echo time. We here propose a method by which a pair echoes, at shortâTE and a longâTE, are acquired in one experiment, thus saving 50% of total acquisition time without significant sacrifice spectral quality. The phaseârotation approach has been implemented with the proposed method. An additional benefit the proposed DualâPRESS method, is that it gives an insight into the transverse relaxation time constant, T2, for the various metabolites. The DualâPRESS method is applied in phantom and inâvivo
In silico identification of widely used and well-tolerated drugs as potential SARS-CoV-2 3C-like protease and viral RNA-dependent RNA polymerase inhibitors for direct use in clinical trials
Despite strict measures taken by
many countries, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
continues to be an issue of global concern. Currently, there are no clinically
proven pharmacotherapies for coronavirus disease 2019, despite promising
initial results obtained from drugs such as azithromycin and hydroxyquinoline.
Therefore, the repurposing of clinically approved drugs for use against
SARS-CoV-2 has become a viable strategy. Here, we searched for drugs that
target SARS-CoV-2 3C-like protease (3CLpro) and viral RNA-dependent
RNA polymerase (RdRp) by in silico
screening of the U.S. Food and Drug Administration approved drug library.
Well-tolerated and widely used drugs were selected for molecular dynamics (MD)
simulations to evaluate drug-protein interactions and their persistence under
physiological conditions. Tetracycline, dihydroergotamine, ergotamine,
dutasteride, nelfinavir, and paliperidone formed stable interactions with 3CLpro
based on MD simulation results. Similar analysis with RdRp showed that
eltrombopag, tipranavir, ergotamine, and conivaptan bound to the enzyme with
high binding free energies. Docking results suggest that ergotamine,
dihydroergotamine, bromocriptine, dutasteride, conivaptan, paliperidone, and
tipranavir can bind to both enzymes with high affinity. As these drugs are well
tolerated, cost-effective, and widely used, our study suggests that they could
potentially to be used in clinical trials for the treatment of
SARS-CoV-2-infected patients.</p
In silico identification of widely used and well-tolerated drugs as potential SARS-CoV-2 3C-like protease and viral RNA-dependent RNA polymerase inhibitors for direct use in clinical trials
Despite strict measures taken by many countries, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to be an issue of global concern. Currently, there are no clinically proven pharmacotherapies for coronavirus disease 2019, despite promising initial results obtained from drugs such as azithromycin and hydroxychloroquine. Therefore, the repurposing of clinically approved drugs for use against SARS-CoV-2 has become a viable strategy. Here, we searched for drugs that target SARS-CoV-2 3C-like protease (3CL(pro)) and viral RNA-dependent RNA polymerase (RdRp) by in silico screening of the U.S. Food and Drug Administration approved drug library. Well-tolerated and widely used drugs were selected for molecular dynamics (MD) simulations to evaluate drug-protein interactions and their persistence under physiological conditions. Tetracycline, dihydroergotamine, ergotamine, dutasteride, nelfinavir, and paliperidone formed stable interactions with 3CL(pro)based on MD simulation results. Similar analysis with RdRp showed that eltrombopag, tipranavir, ergotamine, and conivaptan bound to the enzyme with high binding free energies. Docking results suggest that ergotamine, dihydroergotamine, bromocriptine, dutasteride, conivaptan, paliperidone, and tipranavir can bind to both enzymes with high affinity. As these drugs are well tolerated, cost-effective, and widely used, our study suggests that they could potentially to be used in clinical trials for the treatment of SARS-CoV-2-infected patients. Communicated by Ramaswamy H. Sarm