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Record W2991814262 · doi:10.1002/jbio.201960085

Detecting metabolic differences in fetal and adult sheep adipose and skeletal muscle tissues

2019· article· en· W2991814262 on OpenAlexaff
Jack R. T. Darby, Alexandra Sorvina, Christie A. Bader, Mitchell C. Lock, Jia Yin Soo, Stacey L. Holman, Mike Seed, Tim Kuchel, Doug A. Brooks, Sally E. Plush, Janna L. Morrison

Bibliographic record

VenueJournal of Biophotonics · 2019
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersNational Health and Medical Research CouncilAustralian Research Council
KeywordsSkeletal muscleAdipose tissueGlycolysisOxidative phosphorylationFetusBiologyMetabolismRedoxBiochemistryEndocrinologyChemistryInternal medicineMedicine

Abstract

fetched live from OpenAlex

The primary metabolic pathway required to produce ATP differs as a result of tissue type, developmental stage and substrate availability. We utilized molecular and histological techniques to define the metabolic status in foetal and adult, adipose and skeletal muscle tissues. Redox ratios of these tissues were also determined optically by two-photon microscopy. Adult perirenal adipose tissue had a higher optical redox ratio than fetal perirenal adipose tissue, which aligned with glycolysis being used for ATP production; whereas adult skeletal muscle had a lower optical redox ratio than fetal skeletal muscle, which aligned with oxygen demanding oxidative phosphorylation activity being utilized for ATP production. We have compared traditional molecular and microscopy techniques of metabolic tissue characterization with optical redox ratios to provide a more comprehensive report on the dynamics of tissue metabolism.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.695
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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 teacher head, 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

Citations17
Published2019
Admission routes1
Has abstractyes

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