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Immunoglobulin and T‐cell receptor gene rearrangement in Castleman's disease: molecular genetic analysis

2005· article· en· W2160342137 on OpenAlexaff
Jaudah Al‐Maghrabi, Suzanne Kamel‐Reid, Denis Bailey

Bibliographic record

VenueHistopathology · 2005
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGene rearrangementBiologyAntibodyT-cell receptorMonoclonalPolyclonal antibodiesImmunohistochemistryImmunoglobulin heavy chainPathologyLymphocytePopulationImmunoglobulin light chainMolecular biologyImmunologyMonoclonal antibodyGeneT cellMedicineGenetics

Abstract

fetched live from OpenAlex

AIMS: Castleman's disease (CD) is a rare heterogeneous disorder that is associated with an increased risk of developing lymphoma. Whether CD is primarily hyperplastic or neoplastic in origin is not yet clear. The aim of this study was to investigate CD further by determining the clonality status of its lymphocyte populations. METHODS AND RESULTS: We reviewed 20 patients with CD, 15 with the hyaline-vascular type and five with the plasma cell type. Immunoglobulin (JH) and T-cell receptor (TCR) gene rearrangements were examined using polymerase chain reaction and Southern blotting techniques. B-lymphocyte clonality was also assessed by flow cytometry (FC) and by immunohistochemistry (IHC). The age range of the patients was 15-66 years: nine female and 11 male. Monoclonal rearrangement of the immunoglobulin (JH) gene was detected in only one case. No cases were positive for monoclonal rearrangement of the TCR gene. All of the cases except one were negative for immunoglobulin light chain restriction by both FC and IHC. CONCLUSIONS: The lymphoid cells in CD are most commonly polyclonal in origin, which supports a non-neoplastic origin. However, rare cases may show lymphocyte monoclonality, which could represent the development of a neoplastic population. The latter cases should be followed closely.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.553

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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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 designObservational
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

Citations27
Published2005
Admission routes1
Has abstractyes

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