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Record W2073984498 · doi:10.1089/hyb.2006.0051

B7 and 34B7 Monoclonal Antibodies: A Theoretical Approach to the Molecular Basis of Immunoglobulin Cross-Reactive Antibodies

2007· article· en· W2073984498 on OpenAlexfundno aff
Tays Hernández, Alejandro López‐Requena, Cristina Mateo de Acosta, Geraudis Mustelier, Lourdes Roque-Navarro, Rolando Pérez

Bibliographic record

VenueHybridoma · 2007
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsnot available
FundersCanadian Institute for Advanced Research
KeywordsAntibodyIdiotypeMonoclonal antibodyBiologyImmunoglobulin IdiotypesCross-reactivityImmunoglobulin light chainEpitopeMonoclonalVirologyImmunologyGeneticsCross reactions

Abstract

fetched live from OpenAlex

Neonatal natural antibodies (NAbs) are characterized by their high degree of idiotypic cross reactivity, together with some restrictions in the genetic mechanisms of variable region diversity. We report here the immunogenetic analysis of two anti-idiotype antibodies (B7 and 34B7 monoclonal antibodies [MAbs]), which are also polyreactive as NAbs. Evidence of a process of somatic mutations were found for heavy and light chain variable regions of both antibodies. A phylogenetic analysis of the V(H)J558 family showed that the immunoglobulin cross-reactivity displayed by B7 and 34B7 MAbs is not restricted to a particular subgroup of this family. Moreover, we identified amino acid motifs in the CDR H1 and H2 of B7 and 34B7 MAbs that are also present in high proportion in immunoglobulin cross-reactive antibodies (ICRA) reported in the Kabat database. We propose that these regions are involved in ICRA activity.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.324
Teacher spread0.308 · 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 designTheoretical or conceptual
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

Citations3
Published2007
Admission routes1
Has abstractyes

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