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Record W4323538062 · doi:10.14785/lymphosign-2023-0001

Identification of a novel <i>NFKB2</i> mutation in a patient presenting with autoimmune cytopenia and generalized granulomatous lymphadenopathy

2023· article· en· W4323538062 on OpenAlexaffvenue
Abdulrahman Al Ghamdi, Marina Sham, Laura Abrego Fuentes, Linda Vong

Bibliographic record

VenueLymphoSign Journal · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsCytopeniaPrimary immunodeficiencyImmunologyMedicineImmunodeficiencyExome sequencingImmune systemBiologyMutationGeneGeneticsBone marrow

Abstract

fetched live from OpenAlex

Introduction: NF-κB proteins are transcription factors that modulate various functions of the immune system. NF-κB2 (or p100/p52) has particularly important roles in B cell development and function. Primary immunodeficiency due to mutations in the NFKB2 gene, encoding NF-κB2, range from combined immunodeficiency with susceptibility to viral or opportunistic infections to primarily antibody deficiency. Methods: A comprehensive chart review of our patient was performed. Results: Our patient, currently a 19-year-old male, presented with multiple autoimmune cytopenia resistant to treatment and generalized granulomatous lymphadenopathy. Whole exome sequencing identified a novel pathogenic variant in NFKB2 (c.1700C>T; p.A567V) that is the cause of our patient’s presentation. Conclusion: We present a novel pathogenic variant in NFKB2 with an unusual presentation. Statement of novelty: Here, we report a novel mutation in NFKB2 and the clinical presentation of the affected patient, which helps in further understanding the NF-κB2 pathway and its associated disease.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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 designCase report
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

Citations1
Published2023
Admission routes2
Has abstractyes

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