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Record W2083300502 · doi:10.3171/jns.2003.99.3.0534

Transcriptional profiling of medulloblastoma in children

2003· article· en· W2083300502 on OpenAlexaff
Paul C. Park, Michael D. Taylor, Todd G. Mainprize, Laurence E. Becker, Michael Ho, Wiesław T. Dura, Jeremy A. Squire, James T. Rutka

Bibliographic record

VenueJournal of neurosurgery · 2003
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsMedicineMedulloblastomaProfiling (computer programming)Computational biologyBioinformaticsPathology

Abstract

fetched live from OpenAlex

OBJECT: Although medulloblastoma is the most common malignant brain tumor found in children, little is known about its molecular pathogenesis. The authors have attempted to compare patterns of gene expression in medulloblastoma samples with those in the healthy cerebellum. METHODS: The authors used complementary (c)DNA microarray analysis to compare the expression of genes in samples of medulloblastoma and normal cerebellum. The expression levels of a subset of genes were then verified by immunohistochemical analysis. Six genes were identified that were expressed at a much higher level in at least five of six medulloblastomas: ezrin, cyclin D2, high mobility group protein 2, MAPRE1, histone deacetylase 2, and ornithine decarboxylase 1. A number of potentially important genes whose expression was much lower in medulloblastomas than in control cerebellum were also identified: tenascin R, TRK-B, FGF receptor, and death receptor 3. The expression levels of a subset of the identified genes were confirmed by immunohistochemical analysis, which was performed on fetal cerebellum and medulloblastoma samples. CONCLUSIONS: The authors demonstrate that cDNA microarray analysis is an effective method of increasing understanding of the molecular biology of medulloblastomas found in children. A comparison between gene expression patterns in medulloblastoma and those observed in healthy cerebellum may provide clues as to the origin of these tumors and may lead to the identification of new genes or pathways to be targeted for future therapies.

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 score0.003
Threshold uncertainty score0.241

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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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

Citations41
Published2003
Admission routes1
Has abstractyes

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