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Record W2061307034 · doi:10.1158/0008-5472.can-11-1874

The <i>Pax-5</i> Gene: A Pluripotent Regulator of B-cell Differentiation and Cancer Disease

2011· review· en· W2061307034 on OpenAlexafffund
Pierre O'Brien, Pier Morin, Rodney J. Ouellette, Gilles A. Robichaud

Bibliographic record

VenueCancer Research · 2011
Typereview
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsAtlantic Cancer Research InstituteUniversité de Moncton
FundersCanadian Institutes of Health Research
KeywordsBiologyTranscription factorPAX5Cancer researchOncogeneB cellCarcinogenesisCancerGeneCell growthRegulation of gene expressionLymphopoiesisGeneticsCell cycleHaematopoiesisStem cellAntibody

Abstract

fetched live from OpenAlex

The Pax-5 oncogene encodes a potent transcription factor that plays a key role in B-cell development and cancerous processes. In normal B-lymphopoiesis, Pax-5 accomplishes a dual function by activating B-cell commitment genes while concomitantly repressing non-B-lineage genes. Given the pivotal importance of Pax-5-mediated processes in B-cell development, an aberrant regulation of Pax5 expression has consistently been associated with B-cell cancers, namely, lymphoma and lymphocytic leukemias. More recently, Pax-5 gene expression has been proposed to influence carcinogenic events in tissues of nonlymphoid origin by promoting cell growth and survival. However, in other cases, Pax-5 products have opposing effects on proliferative activity, thus redefining its generally accepted role as an oncogene in cancer. In this review, we attempt to summarize recent findings about the function and regulation of Pax-5 gene products in B-cell development and related cancers. In addition, we present new findings that highlight the pleiotropic effects of Pax-5 activity in a number of other cancer types.

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)0.000
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.093
GPT teacher head0.406
Teacher spread0.313 · 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

Citations80
Published2011
Admission routes2
Has abstractyes

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