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Trigger-dependent Gene Expression Profiles in Cardiac Preconditioning

2004· article· en· W2134604138 on OpenAlexaff
П. В. Сергеев, Rafaela da Silva, Eliana Lucchinetti, Kathrin Zaugg, Thomas Pasch, Marcus Schaub, Michael Zaugg

Bibliographic record

VenueAnesthesiology · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsGene expressionIschemic preconditioningTranscriptomeGeneMolecular biologyMicroarrayMessenger RNAMicroarray analysis techniquesMedicineReal-time polymerase chain reactionRegulation of gene expressionHeat shock proteinIschemiaBiologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: DNA chips facilitate genomic-wide exploration of gene expression. The authors hypothesized that ischemic (IPC) and anesthetic preconditioning (APC) would differentially modulate gene expression in hearts. METHODS: Affymetrix rat U34A gene chips were used to explore the transcriptional response to IPC and APC, sustained ischemia (110 min) without reperfusion, and time-matched perfusion in isolated rat hearts. IPC was induced by three cycles of 5 min of ischemia, and APC was induced by 1.5 minimum alveolar concentration isoflurane (110 min). For each heart, a separate chip was used for hybridization. Data were analyzed for significant > or = 2.0-fold changes in gene expression. Microarray results were confirmed by quantitative real-time reverse-transcription polymerase chain reaction. RESULTS: Of the 8,799 genes represented on U34A, 217 transcripts in the APC group, 234 in the IPC group, and 29 in the ischemia group displayed significant > or = 2.0-fold up-regulation in messenger RNA levels, and 185 transcripts in the APC group, 55 in the IPC group, and 49 in the ischemia group displayed significant > or = 2.0-fold down-regulation. Many of these transcripts were unknown genes. A high number of commonly regulated genes were found in IPC and APC (39 up-regulated, 17 down-regulated). Genes commonly regulated included those associated with cell defense (heat shock protein 10, aldose reductase, Bcl-xS). Conversely, a pool of protective and antiprotective genes was differentially regulated in APC versus IPC (heat shock protein 27/70, programmed cell death 8), suggesting trigger-dependent transcriptome variability. CONCLUSIONS: The novel microarray technology provides evidence for distinct cardioprotective phenotypes in IPC and APC. The observed transcriptional changes raise the possibility of a second window of protection by volatile anesthetics. The authors' molecular portraits are the first global genomic comparison between IPC and APC.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.254
Teacher spread0.242 · 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

Citations94
Published2004
Admission routes1
Has abstractyes

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