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Record W2622964295 · doi:10.3390/biomedicines5020029

NF-κB Signalling in Glioblastoma

2017· review· en· W2622964295 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomedicines · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health Research
KeywordsCancer researchTranscription factorNF-κBBiologyGlioblastomaGliomaStem cellMotilityCancerRadiation therapySignal transductionMedicineGeneCell biologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Nuclear factor-κB (NF-κB) is a transcription factor regulating a wide array of genes mediating numerous cellular processes such as proliferation, differentiation, motility and survival, to name a few. Aberrant activation of NF-κB is a frequent event in numerous cancers, including glioblastoma, the most common and lethal form of brain tumours of glial cell origin (collectively termed gliomas). Glioblastoma is characterized by high cellular heterogeneity, resistance to therapy and almost inevitable recurrence after surgery and treatment. NF-κB is aberrantly activated in response to a variety of stimuli in glioblastoma, where its activity has been implicated in processes ranging from maintenance of cancer stem-like cells, stimulation of cancer cell invasion, promotion of mesenchymal identity, and resistance to radiotherapy. This review examines the mechanisms of NF-κB activation in glioblastoma, the involvement of NF-κB in several mechanisms underlying glioblastoma propagation, and discusses some of the important questions of future research into the roles of NF-κB in glioblastoma.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.089
GPT teacher head0.379
Teacher spread0.290 · 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