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Record W4281613358 · doi:10.1038/s42003-022-03507-5

Three dimensional reconstruction of the mouse cerebellum in Hedgehog-driven medulloblastoma models to identify Norrin-dependent effects on preneoplasia

2022· article· en· W4281613358 on OpenAlexafffund
Nenad T. Pokrajac, Akshay Gurdita, Nobuhiko Tachibana, Nicholas Tokarew, Valerie A. Wallace

Bibliographic record

VenueCommunications Biology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersGovernment of CanadaCanadian Institutes of Health ResearchCancer Research Society
KeywordsMedulloblastomaHedgehogCerebellumNeurosciencePsychologyBiologyCancer researchCell biology

Abstract

fetched live from OpenAlex

Abstract Spontaneous mouse models of medulloblastoma (MB) offer a tractable system to study malignant progression in the brain. Mouse Sonic Hedgehog (Shh)-MB tumours first appear at postnatal stages as preneoplastic changes on the surface of the cerebellum, the external granule layer (EGL). Here we compared traditional histology and 3DISCO tissue clearing in combination with light sheet fluorescence microscopy (LSFM) to identify and quantify preneoplastic changes induced by disrupting stromal Norrin/Frizzled 4 (Fzd4) signalling, a potent tumour inhibitory signal in two mouse models of spontaneous Shh-MB. We show that 3DISCO-LSFM is as accurate as traditional histology for detecting Norrin/Fzd4-associated changes in PNL formation in Ptch +/− mice and EGL hyperplasia in Neurod2-SmoA1 +/− mice. Moreover, we show that the anti-tumour effect of Norrin/Fzd4 signalling is restricted to the posterior region of the cerebellum and is characterized by defective neural progenitor migration away from the EGL. In conclusion, 3DISCO-LSFM is a valid way to monitor tumour initiation events in mouse MB models and reveals an unanticipated regional restriction of stromal signalling in constraining tumour initiation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.501

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 science0.0010.002
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 head0.031
GPT teacher head0.287
Teacher spread0.255 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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