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Record W2283495265 · doi:10.20381/ruor-4753

Development of Biomolecular Tools for Studying Host-Virus Interactions of the Hepatitis C Virus

2015· dissertation· en· W2283495265 on OpenAlexaboutno aff
Neda Nasheri Ardekan

Bibliographic record

VenueuO Research (University of Ottawa) · 2015
Typedissertation
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsHost (biology)VirologyHepatitis a virusVirusBiologyComputer scienceComputational biologyGenetics

Abstract

fetched live from OpenAlex

Hepatitis C virus (HCV) is a growing health concern in Canada and around the world, as it currently infects 3% of the global population. While there is no vaccine available against this virus, novel and effective treatment regimens have improved prospects for the cure of HCV. Complications caused by HCV can lead to severe liver disease and even death. The limited viral proteome forces HCV to rely heavily on various host factors for its replication. Additionally HCV modulates the host physiology to facilitate its pathogenesis; consequently, the in dept study of essential host-virus interactions expands our understandingof how the virus and related species commandere host cell machinery. This understanding can help create new therapeutic strategies, which may have applications towards HCV and other related RNA viruses. While numerous studies have demonstrated that HCV modulates the abundance of various host proteins, the systematic study of the virus’s effect on the enzymatic activity has been relatively unexplored. For this reason, activity-based protein profiling (ABPP) was applied to study the changes in the activity of host enzymes during HCV replication. ABPP is a functional proteomics technique that employs active site-directed probe (ABP) to report on the activity of enzymes within complex proteomes, such as living cells. Herein, directed and non-directed ABPs were employed for specific as well as global profiling of the alterations in the activity of cellular enzymes during HCV replication. As a result, essential host enzymes that are differentially active during HCV infection were identified. Furthermore, I have developed a quantitative ABPP method for relative quantification of the cellular enzymes activity during HCV infection. These results contribute to the discovery of disease-associated biomarkers, with diagnostic significance, and aid in the identification of potential targets for therapeutic interventions. In addition to developing protein-based tools to study host-virus interactions, I employed a novel technique to investigate the interactions of micro-RNA 122 (miR-122), an essential HCV host factor, with the viral RNA genome. This in vitro screening approach, interrogates the folding of HCV RNA using viral RNA-coated magnetic bead (VRB) to determine target site accessibility for RNA silencing. This method predicts the relative affinity of small RNAs towards HCV genomic RNA that are not easily predicted by informatic means, and led to discovery of potent miR-122 interaction site within the large, highly-structured HCV RNA genome. For that reason, VRB assay may represent an attractive tool for the examination of target site accessibility for RNA silencing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.164
GPT teacher head0.411
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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