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Novel Mouse Anti-Mouse β3 Integrin Monoclonal Antibodies: Development and Characterization of New Reagents for Research in Thrombosis and Thrombocytopenia.

2007· article· en· W2558961081 on OpenAlexaff
Guangheng Zhu, Michelle Webster, Reheman Adili, Pingguo Chen, Ebrahim Sayeh, Ming Wang, John Freedman, Heyu Ni

Bibliographic record

VenueBlood · 2007
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of TorontoCanadian Blood ServicesSt. Michael's Hospital
Fundersnot available
KeywordsMonoclonal antibodyEpitopeIntegrinMolecular biologyPlateletAntibodyAntigenicityAntigenBiologyPlatelet activationRecombinant DNAWestern blotImmunologyChemistryBiochemistryGeneReceptor

Abstract

fetched live from OpenAlex

Abstract Background: Platelets are critical for maintaining hemostasis, but inappropriate platelet activation can lead to pathogenic thrombosis. It has been demonstrated that the platelet integrin αIIbβ3 is essential for platelet aggregation and is also a major target antigen in immune thrombocytopenias (e.g. ITP). Current monoclonal antibodies (mAbs) against this protein complex have been generated using traditional methods involving cross-species immunization (e.g. mouse proteins into rat hosts). These approaches may generate a limited repertoire of anti-β3 mAbs since the antigenicity of the protein and the variety of epitopes targeted are based on amino acid sequence differences between the two species and integrin family members are highly conserved. Additionally, studies in murine models of ITP are hampered by the use of xenogeneic antibodies rather than syngeneic antibodies. Methods: We developed a method to generate mouse anti-mouse β3 integrin mAbs utilising β3 gene deficient mice (β3−/−) immunized with wild-type platelets. To generate antibodies specific to the PSI domain (HPA-1 region) of β3 integrin, β3−/− mice were immunized with the recombinant murine PSI domain of β3 integrin. Platelet binding and specificity were determined by flow cytometry and western blot. In vitro effects on platelet function were measured using aggregometry. Different doses of mAbs (5, 10, and 15 μg/mouse) were injected intravenously to induce thrombocytopenia in vivo. Results: A total of twelve mAbs were generated against native β3 integrin (JAN A1, B1, C1, D1 and DEC A1 and B1, 9D2, M1) or recombinant PSI domain (PSI A1, B1, C1, E1). The mAbs were specific for β3 integrin; no binding was observed using β3−/− platelets. Isotyping showed that DEC A1 and DEC B1 are IgG3, PSI E1 is IgG2b, and all other mAbs are IgG1. The anti-PSI domain mAbs recognized linear epitopes and the anti-native β3 mAbs recognized conformational epitopes. All mAbs, with the exception of JAN A1 and B1, cross-reacted with human platelets. JAN C1, JAN D1, DEC A1, 9D2, M1, and all anti-PSI antibodies inhibited mouse platelet aggregation. These antibodies, except DEC A1, 9D2 and M1, also inhibited human platelet aggregation. One anti-PSI domain antibody (PSI B1), however, directly induced human platelet aggregation in the absence of agonist in platelet rich plasma but not in PIPES buffer. This suggests that PSI B1 may initiate conformational changes in β3 integrin and promote fibrinogen binding. Six anti-β3 mAbs (JAN A1, B1, C1 and D1, 9D2 and M1) induced severe dose-dependent thrombocytopenia in mice, while the anti-PSI domain mAbs induced only a mild decrease in platelet count. Interestingly, the two IgG3 mAbs (DEC A1 and B1) did not induce thrombocytopenia. Conclusion: This approach to generating mouse anti-mouse β3 integrin mAbs using β3−/− mice was successful. Different anti-β3 mAbs had different effects on platelet aggregation, and on the induction of thrombocytopenia. These mAbs may be useful reagents for research in thrombosis and immune thrombocytopenia and as novel anti-thrombotic therapeutics.

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)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.126
GPT teacher head0.378
Teacher spread0.252 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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