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Record W4319302880 · doi:10.1139/bcb-2022-0332

Emerging roles for heterogeneous ribonuclear proteins in normal and malignant B cells

2023· review· en· W4319302880 on OpenAlexafffundvenue
Qurat Ul Ain Qureshi, Timothy E. Audas, Ryan D. Morin, Krysta M. Coyle

Bibliographic record

VenueBiochemistry and Cell Biology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsCanada's Michael Smith Genome Sciences CentreSimon Fraser University
FundersCanadian Institutes of Health ResearchCancer Research SocietyAmerican Society of Hematology
KeywordsBiologyMalignant cellsCancerGenetics

Abstract

fetched live from OpenAlex

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are among the most abundantly expressed RNA binding proteins in the cell and play major roles in all facets of RNA metabolism. hnRNPs are increasingly appreciated as essential for mammalian B cell development by regulating the carefully ordered expression of specific genes. Due to this tight regulation of the hnRNP-RNA network, it is no surprise that a growing number of genes encoding hnRNPs have been causally associated with the onset or progression of many cancers, including B cell neoplasms. Here we discuss our current understanding of hnRNP-driven regulation in normal, perturbed, and malignant B cells, and the most recent and emerging therapeutic innovations aimed at targeting the hnRNP-RNA network in lymphoma.

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)0.000
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
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 head0.020
GPT teacher head0.284
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

Citations3
Published2023
Admission routes3
Has abstractyes

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