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Record W4205468833 · doi:10.22215/etd/2021-14738

MicroRNA regulation and expression in the anoxia-tolerant red-eared slider turtle, Trachemys scripta elegans

2021· dissertation· en· W4205468833 on OpenAlexaff
Sarah A. Breedon

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsCarleton UniversityWestern University
Fundersnot available
KeywordsBiologymicroRNAMessenger RNAGene silencingCell biologyGene expressionRegulation of gene expressionTurtle (robot)GeneGeneticsEcology

Abstract

fetched live from OpenAlex

The red-eared slide turtle (Trachemys scripta elegans) is able to survive prolonged episodes of anoxia without suffering any apparent damage.This feat is underscored by a complex set of regulatory mechanisms to achieve metabolic rate depression (MRD) including microRNA (miRNA)-mediated gene silencing.Immunoblotting of relative protein abundance was used to analyze miRNA biogenesis under anoxic and reoxygenated conditions in liver and muscle, finding tissue-specific regulation of miRNA production.Cytoplasmic granule proteins were also assessed to inspect mRNA fate, the results of which indicated that mRNA sequestration to stress granules or processing bodies was also tissue specific.Next, the miRNAome was analyzed using RNA sequencing and bioinformatic analyses, revealing anoxia-induced suppression of processes associated with cell cycle progression and protein turnover.Altogether, these results indicate that miRNA targeting of mRNA transcripts occurs in a tissue specific manner with a particular focus on the suppression of energetically expensive processes.

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 score0.001
Threshold uncertainty score0.002

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.225
Teacher spread0.212 · 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
Published2021
Admission routes1
Has abstractyes

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