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Record W2790004023 · doi:10.1073/pnas.1717815115

Lateral cerebellum is preferentially sensitive to high sonic hedgehog signaling and medulloblastoma formation

2018· article· en· W2790004023 on OpenAlexaff
I‐Li Tan, Alexandre Wojcinski, Harikrishna Rallapalli, Zhimin Lao, Reeti Sanghrajka, Daniel Stephen, Eugenia Volkova, Andrey Korshunov, Marc Remke, Michael D. Taylor, Daniel H. Turnbull, Alexandra L. Joyner

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersNational Cancer InstituteGeoffrey Beene Cancer Research CenterMemorial Sloan-Kettering Cancer CenterNational Institute of Mental HealthNational Brain Tumor Society
KeywordsMedulloblastomaSonic hedgehogCerebellumHedgehog signaling pathwayBiologyNeuroscienceCell biologySignal transductionCancer research

Abstract

fetched live from OpenAlex

Significance Cerebellar tumor medulloblastoma (MB) is no longer considered a single disease as it has been separated into four subgroups with further subdivisions based on genomic and clinical data. Mechanistic understandings of the stratification within subgroups should allow for better-targeted treatments. We redefined the main cell of origin by showing that granule cell precursors (GCPs) are heterogeneous with molecularly distinct populations based on their location. As a consequence, GCPs respond differentially to two driver mutations, and a subset of GCPs is more susceptible to Sonic hedgehog (SHH) pathway elevation and forms tumors more readily. These results provide insights into the preferential location of human SHH-MBs in the lateral cerebellum and the cellular and genetic factors influencing SHH-MB progression.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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 designBench or experimental
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

Citations48
Published2018
Admission routes1
Has abstractyes

Explore more

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