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Record W2079406524 · doi:10.1182/blood-2010-05-280115

Amelioration of murine immune thrombocytopenia by CD44 antibodies: a potential therapy for ITP?

2010· article· en· W2079406524 on OpenAlexafffund
Andrew R. Crow, Seng Song, Sara J. Suppa, Shuhua Ma, Michael P. Reilly, Pierrette André, Steven E. McKenzie, Alan H. Lazarus

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of TorontoCanadian Blood ServicesSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchCanadian Blood Services
KeywordsMonoclonal antibodyAntibodyImmunologyImmune systemMedicineCD44BiologyIn vitro

Abstract

fetched live from OpenAlex

To explore the potential for monoclonal antibodies as a treatment for immune thrombocytopenia (ITP) and to further explore their mechanisms of action, we tested 8 monoclonal CD44 antibodies in murine ITP and found 4 antibodies that could successfully ameliorate ITP; 2 of these antibodies function at a full 3-log fold lower dosage compared with IVIg. Further characterization of the 2 most successful antibodies (5035-41.1D and KM114) demonstrated that, similar to IVIg: (1) the presence of the inhibitory IgG receptor FcγRIIB was required for their ameliorative function, (2) complement-deficient mice responded to anti-CD44 treatment, and (3) human transgenic FcγRIIA-expressing mice also responded to the CD44 therapeutic modality. Dissimilar to IVIg, the Fc portion of the CD44 antibody was not required. These data demonstrate that CD44 antibodies can function therapeutically in murine ITP and that they could potentially provide a very-low-dose recombinant therapy for the amelioration of human ITP.

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 integrity0.0000.001
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 head0.268
Teacher spread0.259 · 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

Citations23
Published2010
Admission routes2
Has abstractyes

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