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Record W7043287653

The Role of Cytoplasmic Poly(A)-Binding Protein in Modulating the Mammalian Transcriptome

2025· dissertation· en· W7043287653 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2025
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersMcGill University
KeywordsTranscriptomeCytoplasmGene expressionGeneRegulation of gene expression
DOInot available

Abstract

fetched live from OpenAlex

Gene expression is a tightly regulated process fundamental to cellular function, identity, and adaptation.Among the key regulators of post-transcriptional gene expression, cytoplasmic poly(A)-binding proteins (PABPCs) play a crucial role in controlling mRNA stability, translation efficiency, and decay.This thesis investigates the context-dependent functions of PABPCs in mammalian cells, with a particular focus on their interactions with translation factors, mRNA decay machinery, and stress response pathways.I examine how PABPCs influence translation efficiency under different cellular conditions, challenging the conventional closed-loop model of translation, which posits that PABPC bridges the 5' cap and 3' poly(A) tail to enhance translation initiation.Recent findings indicate that not all mRNAs adopt a closed-loop conformation, suggesting alternative mechanisms for ribosome recruitment.Additionally, this work explores the role of PABPCs in stress granule dynamics, particularly in relation to neurodegenerative diseases.Furthermore, this thesis highlights the interplay between PABPCs and viral infections, where certain viruses manipulate PABPC interactions to hijack host translation machinery.By integrating insights from molecular biology, structural biochemistry, and cellular imaging studies, this research provides a comprehensive overview of PABPC function and its broader implications for gene expression regulation, disease mechanisms, and potential therapeutic interventions.These findings emphasize that PABPC activity is highly adaptable, influenced by cell type, environmental stress, and pathological conditions.Understanding the diverse roles of PABPCs opens new avenues for targeted therapies in cancer, viral infections, and neurodegenerative disorders.Résumé (French) L'expression génique est un processus finement régulé, fondamental pour la fonction, l'identité et l'adaptation cellulaires.Parmi les régulateurs clés de l'expression génique posttranscriptionnelle, les protéines de liaison à la queue poly(A) cytoplasmiques (PABPCs) jouent un rôle essentiel dans le contrôle de la stabilité des ARNm, de l'efficacité de la traduction et de leur dégradation.Cette thèse explore les fonctions contextuelles des PABPCs dans les cellules de mammifères, en mettant l'accent sur leurs interactions avec les facteurs de traduction, les voies de dégradation des ARNm et les réponses au stress cellulaire.J'analyse comment les PABPCs influencent l'efficacité de la traduction selon les conditions cellulaires, en remettant en question le modèle de boucle fermée qui propose que les PABPCs

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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
Published2025
Admission routes1
Has abstractyes

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