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A Metabolic Mechanism for the Detrimental Effect of Exogenous Glucose During Cardiac Storage

2003· article· en· W2139381533 on OpenAlexafffund
Randy P. Pulis, Beatrice M. Wu, Jay Zhu, E. Castillo, Norman M. Kneteman, Thomas A. Churchill

Bibliographic record

VenueAmerican Journal of Transplantation · 2003
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsUniversity of Alberta
FundersEdmonton Civic Employees Charitable Assistance Fund
KeywordsGlycogenolysisHistidineViaspanGlycolysisMedicineGlycogenInternal medicinePhosphofructokinaseEndocrinologyBiochemistryEnzymeChemistryMetabolismTransplantation

Abstract

fetched live from OpenAlex

The purpose of this study was to clarify the metabolic events that explain why supplemental glucose is detrimental during cardiac storage. Four solutions were used to flush and store porcine hearts: St. Thomas Hospital Solution (STHS), University of Wisconsin (UW) solution, and UW + 90 mM histidine, and UW + 90 mM histidine + 11 mM glucose. Despite equivalent increases in lactate in the two histidine-buffered groups throughout 10 h of storage, glycogen utilization was evident in the group without supplemental glucose. The presence of glucose resulted in a reduction in energy production, presumably mediated by direct inhibition of glycogenolysis. Furthermore, UW + histidine was the only group to show consistent improvements in ATP and total adenylates. It was concluded that inclusion of the buffering agent, histidine, to UW solution promotes anaerobic energy production as a result, in part, of preserved high levels of the regulatory control enzyme, phosphofructokinase.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.258
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2003
Admission routes2
Has abstractno

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