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Record W4229014721 · doi:10.1007/s11302-022-09862-6

Ectonucleotidases as bridge between the ATP and adenosine world: reflections on Geoffrey Burnstock

2022· review· en· W4229014721 on OpenAlexfundno aff
Jürgen Schrader

Bibliographic record

VenuePurinergic Signalling · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsnot available
FundersHeinrich-Heine-Universität DüsseldorfInstitut de Cardiologie de MontréalDeutsche Forschungsgemeinschaft
KeywordsAdenosineExtracellularPurineAdenosine receptorPurinergic signallingReceptorAdenosine triphosphateAdenosine diphosphateAdenine nucleotideBiochemistryMedicineBiologyInternal medicineNucleotideEnzyme

Abstract

fetched live from OpenAlex

Historically, mainly by the work of Robert Berne, extracellular adenosine was the first purine compound recognized as an important signaling molecule linking energy metabolism to function by acting on membrane bound receptors. Geoffrey Burnstock by his vision and endurance pioneered the idea that cells release ATP that also acts as an extracellular signaling molecule under many physiological and pathophysiological circumstances. Only later, it was appreciated that extracellular ATP and adenosine are metabolically linked by the activity of several ectoenzymes which critically determine the concentrations of these purines at their respective receptors. In this brief review, I will report some personal recollections on Geoffrey Burnstock and his impressive personality. In addition, I will give a brief overview on our present knowledge of extracellular purine metabolism and its control and will address some still open issues.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.002

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 head0.098
GPT teacher head0.365
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2022
Admission routes1
Has abstractyes

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