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Record W2072559448 · doi:10.1182/blood-2008-10-184077

Differentiation stage–specific expression of microRNAs in B lymphocytes and diffuse large B-cell lymphomas

2008· article· en· W2072559448 on OpenAlexaff
Raquel Malumbres, Kristopher A. Sarosiek, Elena Cubedo, Jose W. Ruiz, Xiaoyu Jiang, Randy D. Gascoyne, Robert Tibshirani, Izidore S. Lossos

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsBC Cancer Agency
FundersNational Cancer Institute
KeywordsBiologyGerminal centermicroRNADiffuse large B-cell lymphomaIRF4BCL6Cellular differentiationB cellCellCancer researchCell biologyLymphomaGeneticsTranscription factorGeneImmunologyAntibody

Abstract

fetched live from OpenAlex

miRNAs are small RNA molecules binding to partially complementary sites in the 3'-UTR of target transcripts and repressing their expression. miRNAs orchestrate multiple cellular functions and play critical roles in cell differentiation and cancer development. We analyzed miRNA profiles in B-cell subsets during peripheral B-cell differentiation as well as in diffuse large B-cell lymphoma (DLBCL) cells. Our results show temporal changes in the miRNA expression during B-cell differentiation with a highly unique miRNA profile in germinal center (GC) lymphocytes. We provide experimental evidence that these changes may be physiologically relevant by demonstrating that GC-enriched hsa-miR-125b down-regulates the expression of IRF4 and PRDM1/BLIMP1, and memory B cell-enriched hsa-miR-223 down-regulates the expression of LMO2. We further demonstrate that although an important component of the biology of a malignant cell is inherited from its nontransformed cellular progenitor-GC centroblasts-aberrant miRNA expression is acquired upon cell transformation. A 9-miRNA signature was identified that could precisely differentiate the 2 major subtypes of DLBCL. Finally, expression of some of the miRNAs in this signature is correlated with clinical outcome of uniformly treated DLBCL patients.

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 score0.083
Threshold uncertainty score0.432

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 studies0.0000.000
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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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

Citations249
Published2008
Admission routes1
Has abstractyes

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