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Record W2161251010 · doi:10.1101/gad.1254305

Visualization of looping involving the immunoglobulin heavy-chain locus in developing B cells

2005· article· en· W2161251010 on OpenAlexfundno aff
Camil E. Sayegh, Suchit Jhunjhunwala, Roy Riblet, Cornelis Murre

Bibliographic record

VenueGenes & Development · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyLocus (genetics)Immunoglobulin heavy chainCD8AntibodyB cellMolecular biologyGeneticsGeneImmune system

Abstract

fetched live from OpenAlex

The immunoglobulin heavy-chain (IgH) locus undergoes large-scale contraction in B cells poised to undergo IgH V(D)J recombination. We considered the possibility that looping of distinct IgH V regions plays a role in promoting long-range interactions. Here, we simultaneously visualize three subregions of the IgH locus, using three-dimensional fluorescence in situ hybridization. Looping within the IgH locus was observed in both B- and T-lineage cells. However, monoallelic looping of IgH V regions into close proximity of the IgH DJ cluster was detected in developing B cells with significantly higher frequency when compared with hematopoietic progenitor or CD8+ T-lineage cells. Looping of a subset of IgH V regions, albeit at lower frequency, was also observed in RAG-deficient pro-B cells. Based on these observations, we propose that Ig loci are repositioned by a looping mechanism prior to IgH V(D)J rearrangement to facilitate the joining of Ig variable, diversity, and joining segments.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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 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

Citations190
Published2005
Admission routes1
Has abstractyes

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