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Record W2802078370 · doi:10.3340/jkns.2018.0008

Diffuse Intrinsic Pontine Glioma : Clinical Features, Molecular Genetics, and Novel Targeted Therapeutics

2018· review· en· W2802078370 on OpenAlexafffund
Ryan Mathew, James T. Rutka

Bibliographic record

VenueJournal of Korean Neurosurgical Society · 2018
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institute for Advanced Research
KeywordsMedicineGliomaCarcinogenesisCancer researchEpigeneticsDrug developmentHistoneBioinformaticsCancerDrugComputational biologyNeuroscienceGenePharmacologyBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Diffuse intrinsic pontine glioma (DIPG) is a deadly paediatric brain cancer.Transient response to radiation, ineffective chemotherapeutic agents and aggressive biology result in rapid progression of symptoms and a dismal prognosis.Increased availability of tumour tissue has enabled the identification of histone gene aberrations, genetic driver mutations and methylation changes, which have resulted in molecular and phenotypic subgrouping.However, many of the underlying mechanisms of DIPG oncogenesis remain unexplained.It is hoped that more representative in vitro and preclinical models-using both xenografted material and genetically engineered mice-will enable the development of novel chemotherapeutic agents and strategies for targeted drug delivery.This review provides a clinical overview of DIPG, the barriers to progress in developing effective treatment, updates on drug development and preclinical models, and an introduction to new technologies aimed at enhancing drug delivery.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.361
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations68
Published2018
Admission routes2
Has abstractyes

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