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Record W2748755751 · doi:10.3390/pharmaceutics9030028

Theophylline-7β-d-Ribofuranoside (Theonosine), a New Theophylline Metabolite Generated in Human and Animal Lung Tissue

2017· article· en· W2748755751 on OpenAlexafffund
Daniel Sitar, James M. Bowen, Juan He, Angelo Tesoro, Michael Spino

Bibliographic record

VenuePharmaceutics · 2017
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPlant-based Medicinal Research
Canadian institutionsUniversity of TorontoUniversity of Manitoba
FundersMedical Research CouncilMedical Research Council CanadaUniversity of Toronto
KeywordsMetaboliteTheophyllineMicrosomeChemistryPharmacologyBiochemistryBiologyEnzyme

Abstract

fetched live from OpenAlex

While assessing the ability of mammalian lung tissue to metabolize theophylline, a new metabolite was isolated and characterized. The metabolite was produced by the microsomal fraction of lungs from several species, including rat, rabbit, dog, pig, sheep and human tissue. Metabolite production was blocked by boiling the microsomal tissue. This new metabolite, theophylline-7β-d-ribofuranoside (theonosine), was confirmed by several spectral methods and by comparison to an authentic synthetic compound. Tissue studies from rats, rabbits, dogs, and humans for cofactor involvement demonstrated an absolute requirement for NADP and enhanced metabolite production in the presence of magnesium ion. It remains to be demonstrated whether theonosine may contribute to the known pharmacological effects of theophylline.

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 score0.003

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 head0.197
GPT teacher head0.524
Teacher spread0.327 · 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
Published2017
Admission routes2
Has abstractyes

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