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Record W1982396632 · doi:10.1196/annals.1349.001

Acute Myeloid Leukemia Stem Cells

2005· review· en· W1982396632 on OpenAlexafffund
John E. Dick

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2005
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersNational Cancer InstituteCanadian Institutes of Health ResearchChina Scholarship CouncilStem Cell Network
Keywordsclone (Java method)Stem cellMyeloid leukemiaCancer stem cellCancer researchLeukemiaBiologyNeoplasmCancerMyeloidImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

A fundamental problem in cancer research is identification of the cells within a tumor that sustain the growth of the neoplastic clone. The concept that only a subpopulation of rare cancer stem cells (CSCs) is responsible for maintenance of the neoplasm emerged nearly 50 years ago; however, conclusive proof for the existence of a CSC was obtained only relatively recently. The evidence for the existence of CSCs was first derived from the study of human acute myeloid leukemia (AML), largely because of the availability of quantitative stem cell assays for the leukemic stem cell (LSC). These studies showed that only rare cells within the leukemic clone had the capacity to initiate AML growth after transplant into NOD/SCID mice, establishing the hierarchical organization of AML. Recent clonal-tracking studies showed that the LSC compartment is composed of different classes of LSCs, which can be distinguished on the basis of self-renewal potential. These findings have important implications for our understanding of the leukemogenic process as well as the design of more effective therapies to eliminate AML based on eradication of the LSCs. These studies are briefly reviewed here.

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.006

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 head0.176
GPT teacher head0.417
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

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

Citations194
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicAcute Myeloid Leukemia ResearchFrench-language works237,207