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Record W4205560219 · doi:10.1016/j.xcrm.2021.100470

Targeted blockade of immune mechanisms inhibit B precursor acute lymphoblastic leukemia cell invasion of the central nervous system

2021· article· en· W4205560219 on OpenAlexafffund
Sujeetha A. Rajakumar, Ildiko Grandal, Mark D. Minden, Johann Hitzler, Cynthia J. Guidos, Jayne S. Danska

Bibliographic record

VenueCell Reports Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreHospital for Sick ChildrenUniversity of Toronto
FundersOntario Institute for Cancer ResearchUniversity of TorontoLeukemia and Lymphoma Society of Canada
KeywordsRANKLBone marrowCentral nervous systemCancer researchMedicineLeukemiaImmunologyCXCR4Blood–brain barrierReceptorBiologyImmune systemChemokineActivator (genetics)Internal medicine

Abstract

fetched live from OpenAlex

Acute lymphoblastic leukemia (ALL) dissemination to the central nervous system (CNS) is a challenging clinical problem whose underlying mechanisms are poorly understood. Here, we show that primary human ALL samples injected into the femora of immunodeficient mice migrate to the skull and vertebral bone marrow and provoke bone lesions that enable passage into the subarachnoid space. Treatment of leukemia xenografted mice with a biologic antagonist of receptor activator of nuclear factor κB ligand (RANKL) blocks this entry route. In addition to erosion of cranial and vertebral bone, samples from individuals with B-ALL also penetrate the blood-cerebrospinal fluid barrier of recipient mice. Co-administration of C-X-C chemokine receptor 4 (CXCR4) and RANKL antagonists attenuate both identified routes of entry. Our findings suggest that targeted RANKL and CXCR4 pathway inhibitors could attenuate routes of leukemia blast CNS invasion and provide benefit for B-ALL-affected individuals.

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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.227
Teacher spread0.218 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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