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Record W2319980961 · doi:10.1515/hmbci-2012-0009

Progress towards direct inhibitors of Stat5 protein

2012· article· en· W2319980961 on OpenAlexaff
Abbarna A. Cumaraswamy, Patrick T. Gunning

Bibliographic record

VenueHormone Molecular Biology and Clinical Investigation · 2012
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSTAT5ImatinibEffectorCancer researchPharmacologySignal transductionChemistryMedicineBiologyCell biology

Abstract

fetched live from OpenAlex

Abstract Molecular approaches to inhibit STAT5 signaling have been hailed as a viable targeted anticancer therapy. In particular, many drugs and drug candidates have been developed to successfully inhibit upstream effectors of STAT5 by indirectly targeting cell surface receptors and protein kinases (FLT-3, JAK2, and BCR-ABL). Indirect strategies have yielded potent agents, such as imatinib, AC2207, and EXEL823 which effectively silence STAT5 activity but which suffer from off-target effects and toxicity. This article will focus on reviewing the current literature pertaining to direct inhibitors of STAT5 protein and assess the prospects for a future STAT5-targeting therapeutic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.079
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.377
Teacher spread0.336 · 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 teacher head, 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

Citations7
Published2012
Admission routes1
Has abstractyes

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