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Record W3038278697 · doi:10.1038/s41375-020-0958-y

Targeting nuclear import and export in hematological malignancies

2020· review· en· W3038278697 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLeukemia · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNuclear Structure and Function
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsKaryopherinImportinNuclear transportBiologyCarcinogenesisCancer researchNuclear localization sequenceCancerCell nucleusGeneGenetics

Abstract

fetched live from OpenAlex

The transport of proteins across the nuclear membrane is a highly regulated process, essential for the cell function. This transport is actively mediated by members of the karyopherin family, termed importins, or exportins, depending on the direction of transport. These proteins play an active part in tumorigenesis, through aberrant localization of their cargoes, which include oncogenes, tumor-suppressor genes and mediators of key signal transduction pathways. Overexpression of importins and exportins is reported in many malignancies, with implications in cell growth and viability, differentiation, drug resistance, and tumor microenvironment. Given their broad significance across tumors and pathways, much effort is being put to develop specific inhibitors as a novel anticancer therapeutics. Already, selinexor, a specific inhibitor of exportin-1 (XPO1), is approved for clinical use. This review will focus on the role of importins and exportins in hematological malignancies. We will discuss current preclinical and clinical data on importins and exportins, and demonstrate how our growing understanding of their functions has identified new therapeutic targets.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.257
Teacher spread0.241 · 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