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Record W2608952477 · doi:10.1093/gerona/glx058

Digital PCR Quantitation of Muscle Mitochondrial DNA: Age, Fiber Type, and Mutation-Induced Changes

2017· article· en· W2608952477 on OpenAlexaff
Allen Herbst, Kevin Widjaja, Beatrice Nguy, Entela B. Lushaj, Timothy M. Moore, Andrea L. Hevener, Debbie McKenzie, Judd M. Aiken, Jonathan Wanagat

Bibliographic record

VenueThe Journals of Gerontology Series A · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingNational Institutes of HealthAmerican Federation for Aging ResearchNational Institute of General Medical SciencesEllison Medical Foundation
KeywordsMitochondrial DNAPolymerase chain reactionDigital polymerase chain reactionBiologyMutationMolecular biologyDNAFiberReal-time polymerase chain reactionGeneticsChemistryGene

Abstract

fetched live from OpenAlex

Definitive quantitation of mitochondrial DNA (mtDNA) and mtDNA deletion mutation abundances would help clarify the role of mtDNA instability in aging. To more accurately quantify mtDNA, we applied the emerging technique of digital polymerase chain reaction to individual muscle fibers and muscle homogenates from aged rodents. Individual fiber mtDNA content correlated with fiber type and decreased with age. We adapted a digital polymerase chain reaction deletion assay that was accurate in mixing experiments to a mutation frequency of 0.03% and quantitated an age-induced increase in deletion frequency from rat muscle homogenates. Importantly, the deletion frequency measured in muscle homogenates strongly correlated with electron transport chain-deficient fiber abundance determined by histochemical analyses. These data clarify the temporal accumulation of mtDNA deletions that lead to electron chain-deficient fibers, a process culminating in muscle fiber loss.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.057
GPT teacher head0.317
Teacher spread0.260 · 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

Citations34
Published2017
Admission routes1
Has abstractyes

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Same venueThe Journals of Gerontology Series ASame topicMitochondrial Function and PathologyFrench-language works237,207