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Record W1790387644

Internalizing antibodies are necessary for improved therapeutic efficacy of antibody-targeted liposomal drugs.

2002· article· en· W1790387644 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

VenuePubMed · 2002
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLiposomeEpitopePharmacologyDoxorubicinAntibodyMedicineCytotoxicityCD20Targeted therapyTherapeutic indexImmunologyCancer researchIn vitroChemotherapyChemistryDrugCancerInternal medicineBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

Direct experimental proof has been sought for the hypothesis that liposomal drugs targeted against internalizing epitopes (e.g., CD19) will have higher therapeutic efficacies than those targeted against noninternalizing epitopes (e.g., CD20). Anti-CD19-targeted liposomes were rapidly internalized into human B-lymphoma (Namalwa) cells, whereas those targeted with anti-CD20 were not internalized. Similar in vitro binding and cytotoxicity were observed for anti-CD19-targeted and anti-CD20-targeted liposomal formulations of doxorubicin (DXR). Therapeutic experiments were performed in severe combined immunodeficient mice inoculated i.v. with Namalwa cells. Administration of single i.v. doses of DXR-loaded anti-CD19-targeted liposomes resulted in significantly greater survival times than either DXR-loaded anti-CD20-targeted liposomes or nontargeted liposomes. The therapeutic advantage of targeting internalizing versus noninternalizing epitopes has been directly demonstrated.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.051
GPT teacher head0.308
Teacher spread0.257 · 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