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Record W2097314357 · doi:10.1152/physiol.00036.2007

Physiology of Nucleoside Transporters: Back to the Future. . . .

2008· review· en· W2097314357 on OpenAlexaff
Jennifer B. Rose, Imogen R. Coe

Bibliographic record

VenuePhysiology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsYork University
Fundersnot available
KeywordsNucleosideTransporterBiologyFunction (biology)Nucleoside transporterCell physiologyNucleoside analogueCell biologyComputational biologyPhysiologyBiochemistryGeneCell

Abstract

fetched live from OpenAlex

Nucleoside transporters (NTs) are integral membrane proteins responsible for mediating and facilitating the flux of nucleosides and nucleobases across cellular membranes. NTs are also responsible for the uptake of nucleoside analog drugs used in the treatment of cancer and viral infections, and they are the target of certain compounds used in the treatment of some types of cardiovascular disease. The important role of NTs as drug transporters and therapeutic targets has necessarily led to intense interest into their structure and function and the relationship between these proteins and drug efficacy. In contrast, we still know relatively little about the fundamental physiology of NTs. In this review, we discuss various aspects of the physiology of NTs in mammalian systems, particularly noting tissues and cells where there has been little recent research. Our central thesis is reference back to some of the older literature, combined with current findings, will provide direction for future research into NT physiology that will lead to a fuller understanding of the role of these intriguing proteins in the everyday lives of cells, tissues, organs, and whole animals.

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
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0020.002
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 head0.022
GPT teacher head0.287
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 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

Citations48
Published2008
Admission routes1
Has abstractyes

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