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Record W2526886998 · doi:10.1002/1873-3468.12435

Torpor‐responsive expression of novel microRNA regulating metabolism and other cellular pathways in the thirteen‐lined ground squirrel, <i>Ictidomys tridecemlineatus</i>

2016· letter· en· W2526886998 on OpenAlexafffund
Bryan E. Luu, Kyle K. Biggar, Cheng‐Wei Wu, Kenneth B. Storey

Bibliographic record

VenueFEBS Letters · 2016
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTorporHibernation (computing)microRNABiologyGround squirrelCell biologyMessenger RNAGene expressionGeneGeneticsEndocrinology

Abstract

fetched live from OpenAlex

Research has demonstrated the importance of microRNA in cold-tolerant animals, including their dynamic regulation throughout mammalian hibernation. In this study, we used small RNA sequencing and bioinformatic methods to identify novel microRNA regulating gene expression during hibernation in thirteen-lined ground squirrels, Ictidomys tridecemlineatus. A group of 17 novel microRNA was identified, and their relative expression was quantitated using real-time quantitative polymerase chain reaction in liver, skeletal muscle, and heart tissues over four experimental conditions that represent the torpor-arousal cycle. Predicted mRNA targets of these novel microRNA were found to be enriched in biological processes known to be regulated during hibernation, such as lipid metabolism, ion-transport ATPases, and various cellular signaling cascades. This study provides an analysis of several novel microRNA that may be crucial to adaptation during hibernation.

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: Observational · Consensus signal: none
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 head0.030
GPT teacher head0.210
Teacher spread0.180 · 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 designObservational
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

Citations26
Published2016
Admission routes2
Has abstractyes

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