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A novel cell culture model for studying ischemia-reperfusion injury in lung transplantation

2000· article· en· W159099134 on OpenAlexaff
Jonathan Cardella, Shaf Keshavjee, E. Mourgeon, Stephen D. Cassivi, Stefan Fischer, Noritaka Isowa, Arthur S. Slutsky, Mingyao Liu

Bibliographic record

VenueJournal of Applied Physiology · 2000
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsLung transplantationTransplantationReperfusion injuryIschemiaLungMedicineCell injuryCardiologyInternal medicineChemistryApoptosis

Abstract

fetched live from OpenAlex

Many cell culture models have been developed to study ischemia-reperfusion injury; however, none is specific to the conditions of lung preservation and transplantation. The objective of this study was to design a cell culture model that mimics clinical lung transplantation, in which preservation is aerobic and hypothermic. A549 cells, a human pulmonary epithelial cell line, were preserved in 100% O(2) at 4 degrees C for varying periods in low-potassium dextran glucose solution, simulating ischemia, followed by the introduction of warm (37 degrees C) DMEM plus 10% fetal bovine serum to simulate reperfusion. Cultures were assayed for cell attachment and viability. Sequential extension of ischemic times to 24 h showed a time-dependent loss of cells. There was a further decrease in cell number after simulated reperfusion. Cell detachment was due mainly to cell death, as determined by cell viability. The effects of chemical components such as dextran 40 and calcium in the preservation solution and various preservation gas mixtures were examined by use of this model system. With its design and validation, this model could be used to study mechanisms related to ischemia-reperfusion injury at the cellular and molecular level.

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 score0.107
Threshold uncertainty score0.376

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 head0.021
GPT teacher head0.314
Teacher spread0.293 · 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

Citations47
Published2000
Admission routes1
Has abstractyes

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