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Record W3207761744 · doi:10.3390/biom11101548

New Insights to Regulation of Fructose-1,6-bisphosphatase during Anoxia in Red-Eared Slider, Trachemys scripta elegans

2021· article· en· W3207761744 on OpenAlexafffund
Aakriti Gupta, Anchal Varma, Kenneth B. Storey

Bibliographic record

VenueBiomolecules · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFructose 1,6-bisphosphataseBiologyGluconeogenesisFructoseAnoxic watersBiochemistryPhosphorylationEnzymeEcology

Abstract

fetched live from OpenAlex

) undergoes numerous changes to its physiological and metabolic processes to survive without oxygen. During anoxic conditions, its metabolic rate drops drastically to minimize energy requirements. The alterations in the central metabolic pathways are often accomplished by the regulation of key enzymes. The regulation of one such enzyme, fructose-1,6-bisphosphatase (FBPase; EC 3.1.3.11), was characterized in the present study during anoxia in liver. FBPase is a crucial enzyme of gluconeogenesis. The FBPase was purified from liver tissue in both control and anoxic conditions and subsequently assayed to determine the kinetic parameters of the enzyme. The study revealed the relative degree of post-translational modifications in the FBPase from control and anoxic turtles. Further, this study demonstrated a significant decrease in the maximal activity in anoxic FBPase and decreased sensitivity to its substrate Fructose-1,6-bisphosphate (FBP) when compared to the control. Immunoblotting demonstrated increased threonine phosphorylation (~1.4-fold) in the anoxic FBPase. Taken together, these results suggest that the phosphorylation of liver FBPase is an important step in suppressing FBPase activity, ultimately leading to the inhibition of gluconeogenesis in the liver of the red-eared slider during anaerobic conditions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.819

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.235
Teacher spread0.226 · 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 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

Citations10
Published2021
Admission routes2
Has abstractyes

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