MétaCan
Menu
Back to cohort
Record W2045970616 · doi:10.1182/blood.v97.11.3552

p53 abnormalities in splenic lymphoma with villous lymphocytes

2001· article· en· W2045970616 on OpenAlexaff
Alicja Gruszka, Rifat Hamoudi, Estella Matutes, Esperanza Tuset, Daniel Catovsky

Bibliographic record

VenueBlood · 2001
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsInstitute of Cancer Research
Fundersnot available
KeywordsPathologyLymphomaImmunocytochemistrySplenic marginal zone lymphomaBiologyBCL10Chromosome abnormalityMedicineSpleenImmunologySplenectomyChromosomeKaryotypeGene

Abstract

fetched live from OpenAlex

The incidence and role of p53 abnormalities have not been reported in splenic lymphoma with villous lymphocytes (SLVL), the leukemic counterpart of splenic marginal zone lymphoma. Because p53 abnormalities correlate with progressive and refractory disease in cancer and isochromosome 17q has been described in SLVL, a low-grade lymphoma that behaves aggressively in a minority of patients, this study investigated p53 changes by molecular and immunophenotypic methods in samples from 59 patients. The p53 deletion was analyzed by fluorescence in situ hybridization, and p53 protein expression was assessed by immunocytochemistry in 35 of 59 cases and by flow cytometry in 20 of 35 patients. Ten patients (17%) had a monoallelic p53 loss, 3 (9%) of 35 nuclear protein expression by immunocytochemistry, and 2 (10%) of 20 by flow cytometry. Two patients had both deletion and protein expression. Direct sequencing of all p53 exons was used to delineate mutations in 9 of 11 patients with an identified abnormality. Mutations, both compromising p53 DNA binding, were identified in the 2 patients with deletion and protein accumulation. Kaplan-Meier analysis revealed a significantly worse survival for patients with p53 abnormalities. Although p53 abnormalities are infrequent in SLVL, they underlie a more aggressive disease course and poor prognosis. (Blood. 2001;97:3552-3558)

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.541

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 head0.009
GPT teacher head0.224
Teacher spread0.214 · 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

Citations98
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicLymphoma Diagnosis and TreatmentFrench-language works237,207