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Record W2023728706 · doi:10.1126/science.1139851

Modeling the Initiation and Progression of Human Acute Leukemia in Mice

2007· article· en· W2023728706 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience · 2007
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversité LavalCentre hospitalier de l'Université LavalCentre hospitalier universitaire de QuébecHôpital de l'Enfant-JésusUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsBiologyHaematopoiesisLeukemiaMyeloidMyeloid leukemiaCancer researchLineage (genetic)TransplantationImmunoglobulin heavy chainFusion geneImmunologyGermlineGeneStem cellAntibodyGeneticsMedicine

Abstract

fetched live from OpenAlex

Our understanding of leukemia development and progression has been hampered by the lack of in vivo models in which disease is initiated from primary human hematopoietic cells. We showed that upon transplantation into immunodeficient mice, primitive human hematopoietic cells expressing a mixed-lineage leukemia (MLL) fusion gene generated myeloid or lymphoid acute leukemias, with features that recapitulated human diseases. Analysis of serially transplanted mice revealed that the disease is sustained by leukemia-initiating cells (L-ICs) that have evolved over time from a primitive cell type with a germline immunoglobulin heavy chain (IgH) gene configuration to a cell type containing rearranged IgH genes. The L-ICs retained both myeloid and lymphoid lineage potential and remained responsive to microenvironmental cues. The properties of these cells provide a biological basis for several clinical hallmarks of MLL leukemias.

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.

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)0.002
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 score0.530
Threshold uncertainty score0.154

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.037
GPT teacher head0.387
Teacher spread0.351 · 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