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Record W2116852571 · doi:10.3233/hab-2002-11302

Isolation of human single chain antibodies (scFv) against human TNF-α from human peripheral blood lymphocyte-SCID mice

2002· article· en· W2116852571 on OpenAlexaff
Hai V. Nguyen, John B. Hay, Steven Gallinger, Jagdeep Singh Sandhu, Nobumichi Hozumi

Bibliographic record

VenueHuman Antibodies · 2002
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsVirologyAntibodyMonoclonal antibodyAntigenKeyhole limpet hemocyaninBiologyMolecular biologyImmunizationPhage displayImmunology

Abstract

fetched live from OpenAlex

By developing an appropriate immunization protocol for SCID (hu-PBL-SCID) mice engrafted with human peripheral blood lymphocytes in combination with scFv phage display library, we were able to establish an efficient strategy to obtain human scFv clones against a human self-antigen, TNF-alpha. The mice pretreated with gamma-radiation (3Gy) and anti-asialo GM1 antibody were immunized with a mixture of human TNF-alpha-keyhole limpet hemocyanin and Freund's adjuvant. Human antibody maturation was suggested to be induced in the mice with the immunization protocol. The scFv clones obtained from the mice were shown to exhibit binding affinities in the range of 10(7)-10(8) M(-1). Together with our previously published work on the isolation of respiratory syncytial virus neutralizing scFvs, the results of this study have implicated that this combined approach is one of the effective alternatives for the cloning of human monoclonal antibodies specific for a wide range of antigens of interest.

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), Science and technology studies, Insufficient payload (model declined to judge)
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 score0.346
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.311
Teacher spread0.255 · 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 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
Published2002
Admission routes1
Has abstractyes

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