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Record W2525035101 · doi:10.1016/j.jacbts.2016.06.002

Adenosine Receptor Activation in the “Trigger” Limb of Remote Pre-Conditioning Mediates Human Endothelial Conditioning and Release of Circulating Cardioprotective Factor(s)

2016· article· en· W2525035101 on OpenAlexaff
Hussain Contractor, R. H. LIE, Colin Cunnington, Jing Li, Nicolaj B. Støttrup, Cedric Manlhiot, Hans Erik Bøtker, Michael Rahbek Schmidt, J C Forfar, Houman Ashrafian, Andrew N. Redington, Rajesh Kharbanda

Bibliographic record

VenueJACC Basic to Translational Science · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersFondation Leducq
KeywordsAdenosineMedicineConditioningIschemic preconditioningBlockadeAdenosine receptorIschemiaReceptorPharmacologyNeuroscienceInternal medicineBiology

Abstract

fetched live from OpenAlex

Remote ischemic pre-conditioning (rIPC) has emerged as a potential mechanism to reduce ischemia-reperfusion injury. Clinical data, however, have been mixed, and its physiological basis remains unclear, although it appears to involve release of circulating factor(s) and/or neural pathways. Here, the authors demonstrate that adenosine receptor activation is an important step in initiating human pre-conditioning; that pre-conditioning liberates circulating cardioprotective factor(s); and that exogenous adenosine infusion is able to recapitulate release of this factor. However, blockade of adenosine receptors in ischemic tissue does not block the protection afforded by pre-conditioning. These data have important implications for defining the physiology of human pre-conditioning and its translation to future clinical trials.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.279
Teacher spread0.264 · 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 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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJACC Basic to Translational ScienceSame topicCardiac Ischemia and ReperfusionFrench-language works237,207