MétaCan
Menu
Back to cohort
Record W2284553164 · doi:10.1186/s12885-016-2170-z

MB3W1 is an orthotopic xenograft model for anaplastic medulloblastoma displaying cancer stem cell- and Group 3-properties

2016· article· en· W2284553164 on OpenAlexaff
Sebastian Dietl, Stefanie Schwinn, Susanne Dietl, Simone S. Riedel, Frank Deinlein, Stefan Rutkowski, André O. von Bueren, Jürgen Krauß, Tilmann Schweitzer, Giles H. Vince, Daniel Picard, Matthias Eyrich, Andreas Rosenwald, Vijay Ramaswamy, Michael D. Taylor, Marc Remke, Camelia Maria Monoranu, Andreas Beilhack, Paul G. Schlegel, Matthias Wölfl

Bibliographic record

VenueBMC Cancer · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick Children
FundersJulius-Maximilians-Universität WürzburgDeutsche Forschungsgemeinschaft
KeywordsMedulloblastomaSurgical oncologyMedicineStem cellOncologyCancer stem cellCancerInternal medicineCancer researchBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Medulloblastoma is the most common malignant brain tumor in children and can be divided in different molecular subgroups. Patients whose tumor is classified as a Group 3 tumor have a dismal prognosis. However only very few tumor models are available for this subgroup. METHODS: We established a robust orthotopic xenograft model with a cell line derived from the malignant pleural effusions of a child suffering from a Group 3 medulloblastoma. RESULTS: Besides classical characteristics of this tumor subgroup, the cells display cancer stem cell characteristics including neurosphere formation, multilineage differentiation, CD133/CD15 expression, high ALDH-activity and high tumorigenicity in immunocompromised mice with xenografts exactly recapitulating the original tumor architecture. CONCLUSIONS: This model using unmanipulated, human medulloblastoma cells will enable translational research, specifically focused on Group 3 medulloblastoma.

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 score0.433
Threshold uncertainty score0.509

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 head0.058
GPT teacher head0.292
Teacher spread0.234 · 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

Citations23
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueBMC CancerSame topicGlioma Diagnosis and TreatmentFrench-language works237,207