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Temperature and phosphate effects on allosteric phenomena of phosphofructokinase from a hibernating ground squirrel (Spermophilus lateralis)

2004· article· en· W2150123796 on OpenAlexaff
Justin A. MacDonald, Kenneth B. Storey

Bibliographic record

VenueFEBS Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCarleton UniversityUniversity of Calgary
FundersFordham University
KeywordsGround squirrelPhosphofructokinaseAllosteric regulationHibernation (computing)ChemistryPhosphateZoologyBiologyEcologyEnzymeBiochemistryGlycolysisThermoregulationMathematics

Abstract

fetched live from OpenAlex

Temperature effects on the kinetic properties of phosphofructokinase (PFK) purified from skeletal muscle of the golden-mantled ground squirrel, Spermophilus lateralis, were examined at 37 degrees C and 5 degrees C, values characteristic of body temperatures in euthermia vs. hibernation. The enzyme showed reduced sensitivity to all activators at 5 degrees C, the K(a) values for AMP, ADP, NH(4) (+) and F2,6P(2) were 3-11-fold higher at 5 degrees C than at 37 degrees C. Inhibition by citrate was not affected whereas phosphoenolpyruvate, ATP and urea became more potent inhibitors at low temperature. While typically considered an activator of PFK activity, inorganic phosphate performed as an inhibitor at 5 degrees C. Decreasing temperature alone causes the actions of inorganic phosphate to change from activation to inhibition. We found that K(m) values for ATP remained constant while V(max) dropped significantly upon the addition of phosphate. Phosphate inhibition at 5 degrees C was noncompetitive with respect to ATP and the K(i) was 0.15 +/- 0.01 mm (n = 4). The results indicate that PFK is less likely to be activated in cold torpid muscle; PFK is less sensitive to changing adenylate levels at the low temperatures characteristic of torpor, and PFK is clearly much less sensitive to biosynthetic signals. All of these characteristics of hibernator PFK would serve to reduce glycolytic rate and help to preserve carbohydrate reserves during torpor.

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 score0.394
Threshold uncertainty score0.776

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 integrity0.0000.001
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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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

Citations20
Published2004
Admission routes1
Has abstractyes

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