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Childhood radiation‐associated atypical meningioma with novel complex rearrangements involving chromosomes 1 and 12

2008· article· en· W1970349058 on OpenAlexaff
María Sol Brassesco, Elvis Terci Valera, Luciano Neder, Angel Maurício Castro‐Gamero, Fábio Morato de Oliveira, Antônio Carlos Santos, Carlos Alberto Scrideli, Ricardo Santos de Oliveira, Hélio Rubens Machado, Luíz Gonzaga Tone

Bibliographic record

VenueNeuropathology · 2008
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsMeningiomaFluorescence in situ hybridizationCytogeneticsChromosomeMolecular cytogeneticsBiologyComparative genomic hybridizationFish <Actinopterygii>GeneticsPathologyMedicineGene

Abstract

fetched live from OpenAlex

Meningiomas are recognized as the most common late complication following radiotherapy. However, cytogenetic studies in childhood atypical radiation-induced meningioma are sporadic, mainly because this condition generally occurs after a long latent period. In the present study we show the results of conventional and molecular cytogenetics in a 14-year-old boy with a secondary atypical meningioma. Apart from numerical changes, we found complex aberrations with the participation of chromosomes 1, 6 and 12. The invariable presence of loss of 1p was demonstrated by fluorescent in situ hybridization (FISH) analysis with probes directed to telomeric regions and by comparative genome hybridization (CGH). Previous cytogenetic studies on adult spontaneous and radiation-associated meningiomas showed loss of chromosome 22 as the most frequent change, followed by loss of the short arm of chromosome 1. To the best of our knowledge this is the first report of highly complex chromosome aberrations in the pediatric setting of meningioma.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.245
Teacher spread0.205 · 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

Citations14
Published2008
Admission routes1
Has abstractyes

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