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Metabolic adjustments in the common carp during prolonged hypoxia

2000· article· en· W2083494620 on OpenAlexaff
B. S. Zhou, Rongben Wu, David Randall, Paul K.S. Lam, Yuen K. Ip, Shit F. Chew

Bibliographic record

VenueJournal of Fish Biology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiologyCarpPhosphofructokinaseInternal medicineGlycogenHypoxia (environmental)EndocrinologyCytochrome c oxidaseCyprinusCitrate synthaseLactate dehydrogenaseGlycolysisCommon carpPyruvate kinaseOxygenBiochemistryMetabolismEnzymeFish <Actinopterygii>FisheryChemistry

Abstract

fetched live from OpenAlex

Biochemical and respiratory changes in the common carp Cyprinus carpio , were studied 6, 24, 96 and 168 h upon exposure to hypoxia (0·5 mgO 2 l −1 ). Modification of kinetic properties of phosphofructokinase (PFK‐1), coupled with a decreased in PFK‐1 activities, were evident in muscle. No changes in kinetics and activities could be observed in muscle pyruvate kinase (PK) and lactate dehydrogenase (LDH). A decrease in muscle citrate synthase (CS) and an increase in muscle cytochrome c oxidase (CCO) were found. The common carp was able to maintain a constant level of muscle glycogen, muscle ATP, and liver CS throughout the 168‐h experimental period. Changes in activities of liver LDH and muscle CCO were observed only at 168 h, which indicates that common carp may switch to alternative metabolic pathway to deal with prolonged hypoxia. A severe decrease in liver glycogen was accompanied by increases in lactate levels in both the muscle and liver. Oxygen consumption rate was reduced under hypoxia, but resumed to normoxic levels within 2 h upon return to normoxic condition. Overall, these results indicate that carp adopt different strategies in an attempt to deal with short term and long term hypoxia in the natural environment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score1.000

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)0.0010.000

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 head0.016
GPT teacher head0.239
Teacher spread0.224 · 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.

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

Citations87
Published2000
Admission routes1
Has abstractyes

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