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Modulations of anti‐D affinity following promiscuous binding of the heavy chain with naïve light chains

2003· article· en· W2000203015 on OpenAlexaff
Isabelle St‐Amour, Chantal Proulx, Réal Lemieux, Renée Bazin

Bibliographic record

VenueTransfusion · 2003
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversité LavalHéma-Québec
Fundersnot available
KeywordsImmunoglobulin light chainChemistryComplementarity determining regionAntigenStereochemistryMolecular biologySingle chainAntibodyBiologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: It is generally accepted that the antibody heavy (H) chain is more important than the light (L) chain for determining antigen specificity. In the case of anti-D, the predominant role of H chains in antigen binding is well recognized, but much less is known about the function of L chains. In this work, the contribution of L chains from non-D-immunized donors to the specificity and reactivity of anti-Ds was studied with L-chain shuffling. STUDY DESIGN AND METHODS: A kappa L chain library was recombined with the H chain of the 43F10 anti-D in a phagemid vector system (pComb3H, Scripps Institute). D-specific F(ab) phages were selected by panning on RBCs. Soluble F(ab)s were prepared, and their reactivity was assessed by RBC agglutination. The nucleotide and amino acid sequences of the variable region of the L chains were analyzed. RESULTS: The L chains of the six D-specific 43F10 F(ab) clones studied used five different germline genes from three Vkappa families and three different Jkappa segments. The L chains were all cationic with isoelectric points ranging from 8.1 to 10.2. CONCLUSION: The 43F10 anti-D H chain could bind promiscuously to a diversity of L chains from non-D-immunized donors without losing the D-antigen specificity. Relationships between the anti-D affinity and the cationic charge of the L chain as well as with the presence of an arginine residue in the L-chain complementarity-determining region 1 were observed.

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 score0.006
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.276
Teacher spread0.254 · 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

Citations6
Published2003
Admission routes1
Has abstractyes

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