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Record W2914913137 · doi:10.1097/tp.0000000000002594

Memory B Cells and Long-lived Plasma Cells

2019· review· en· W2914913137 on OpenAlexaff
Lavinia Ionescu, Simon Urschel

Bibliographic record

VenueTransplantation · 2019
Typereview
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAntibodyImmunologyABO blood group systemBiologyB cellImmune systemTransplantationMedicineInternal medicine

Abstract

fetched live from OpenAlex

The importance of B cell and antibody-mediated immune response in the acute and long-term persistence of transplanted solid organs has become increasingly evident in recent years. A variety of therapeutic innovations target antibodies directed toward HLA or blood groups (ABO) to allow better allocation and posttransplant longevity of organs. Antibodies originate from plasma cells (PCs), which are terminally differentiated B cells. Long-term production and persistence of these antibodies is partly due to fast reactivation of previously generated memory B cells; however, there is increasing evidence that some differentiated PCs can persist independently in the bone marrow for years or even decades, producing specific antibodies or even experiencing regeneration without proliferation without need to be replaced by newly differentiating B cells. This review outlines the currently presumed pathways of differentiation, antibody, and memory generation on both B-cell and PC levels. On this background, current therapeutic concepts for antibody reduction before and after solid organ transplantation are considered, to better understand their mechanisms, possible synergisms, and specific risks. Specific differences in regards to ABO versus HLA antibodies as well as practical relevance for generation of desensitization and posttransplant antibody-directed therapy protocols are discussed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.684
Threshold uncertainty score1.000

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)0.0000.001

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 head0.063
GPT teacher head0.339
Teacher spread0.276 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations47
Published2019
Admission routes1
Has abstractyes

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