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Record W2555548581 · doi:10.1111/voxs.12320

A role for red cell clearance in antibody‐mediated inhibition of erythrocyte alloimmunization?

2016· article· en· W2555548581 on OpenAlexafffund
Danielle Marjoram, Yoelys Cruz‐Leal, L. Bernardo, Alan H. Lazarus

Bibliographic record

VenueISBT Science Series · 2016
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsCanadian Blood ServicesUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchHealth CanadaGovernment of CanadaAustralian Government
KeywordsMonoclonal antibodyRed blood cellAntibodyRed CellImmunologyMonoclonalImmune systemBiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Antibodies targeting erythrocytes can induce antibody‐mediated inhibition of erythrocyte alloimmunization, and anti‐D has been extremely successful in preventing haemolytic disease of the foetus and newborn ( HDFN ). It is desirable to replace the current donor‐derived anti‐D with a monoclonal antibody; however, the exact mechanism of IgG‐mediated suppression of red blood cell immune responses remains unclear. It has been proposed that the ability of anti‐D to prevent HDFN is due to IgG interactions with Fc receptors on phagocytic cells leading to rapid clearance of RhD+ red cells. Several monoclonal anti‐D alternatives have been developed with an emphasis on their ability to rapidly clear red blood cells from the circulation. None of the monoclonal antibodies have been as effective as donor‐derived anti‐D with some antibodies inadvertently leading to immune enhancement instead of inhibition. A better understanding of the mechanisms of IgG‐mediated inhibition of red cell alloimmunization is necessary. In this brief review, we highlight selected evidence for and against the requirement for rapid red cell clearance in the ability of IgG to prevent red cell alloimmunization. We also discuss potential alternative mechanisms which could be important for informing the future development of monoclonal antibody alternatives.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.252
Teacher spread0.245 · 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 teacher head, 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

Citations4
Published2016
Admission routes2
Has abstractyes

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