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Record W2004921719 · doi:10.1002/stem.1001

Aldehyde Dehydrogenase Activity Is a Biomarker of Primitive Normal Human Mammary Luminal Cells

2011· article· en· W2004921719 on OpenAlexafffund
Peter Eirew, Nagarajan Kannan, David J. H. F. Knapp, François Vaillant, Joanne T. Emerman, Geoffrey J. Lindeman, Jane E. Visvader, Connie J. Eaves

Bibliographic record

VenueStem Cells · 2011
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersAustralian Cancer Research FoundationCanadian Breast Cancer Research Alliance
KeywordsBiologyAldehyde dehydrogenaseBiomarkerDehydrogenaseMammary glandEnzymeCell biologyBiochemistryGeneticsCancer

Abstract

fetched live from OpenAlex

Elevated aldehyde dehydrogenase (ALDH) expression/activity has been identified as an important biomarker of primitive cells in various normal and malignant human tissues. Here we examined the level and type of ALDH expression and activity in different subsets of phenotypically and functionally defined normal human mammary cells. We find that the most primitive human mammary stem and progenitor cell types with bilineage differentiation potential show low ALDH activity but undergo a marked, selective, and transient upregulation of ALDH activity at the point of commitment to the luminal lineage. This mirrors a corresponding change in transcripts and protein levels of ALDH1A3, an enzyme involved in retinoic acid synthesis and the most highly expressed ALDH gene in normal human mammary tissue. In contrast, ALDH1A1 is expressed at low levels in all mammary epithelial cells. These findings raise interesting questions about the reported association of ALDH activity with breast cancer stem cells and breast cancer prognosis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.272
Teacher spread0.219 · 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 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

Citations87
Published2011
Admission routes2
Has abstractyes

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