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Record W4281401473 · doi:10.1002/cbf.3710

One‐step purification and regulation of fructose 1,6‐bisphosphatase from the liver of the freeze‐tolerant wood frog, <i>Rana sylvatica</i>

2022· article· en· W4281401473 on OpenAlexafffund
Anchal Varma, Kenneth B. Storey

Bibliographic record

VenueCell Biochemistry and Function · 2022
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-bisphosphataseGluconeogenesisFructoseGlycogenBiologyBiochemistryAllosteric regulationEnzyme

Abstract

fetched live from OpenAlex

The wood frog (Rana sylvatica) undergoes numerous changes to its physiology and metabolic processes to survive the winter months, including adaptations that let them endure whole-body freezing. The regulation of key enzymes of central carbohydrate metabolism in the liver plays a crucial role in mediating the synthesis and maintenance of high concentrations of glucose as a cryoprotectant during freezing as well as glucose reconversion to glycogen after thawing. The present study characterized the regulation of fructose-1,6-bisphosphatase (FBPase; EC 3.1.3.11) from wood frog liver during freezing, FBPase being a crucial enzyme regulating gluconeogenesis. Liver FBPase was purified to homogeneity from control and frozen wood frogs by a one-step chromatographic process. Kinetic and regulatory parameters of the enzyme were investigated and demonstrated a significant decrease in sensitivity to its substrate fructose-1,6-bisphosphate in the liver of frozen frogs, as compared with controls. Immunoblotting also revealed freeze-responsive changes in posttranslational modifications with a significant decrease in serine phosphorylation (by 53%) for FBPase from frozen frogs. Taken together, these results suggest that FBPase is suppressed, and gluconeogenesis is inhibited during freezing. This response acts as an important component of the metabolic survival strategy of the wood frog.

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 score0.037
Threshold uncertainty score0.347

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 head0.006
GPT teacher head0.174
Teacher spread0.168 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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