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Record W2598773960 · doi:10.1177/1010428317692248

Proteasome expression and activity in cancer and cancer stem cells

2017· review· en· W2598773960 on OpenAlexaff
Ioannis A. Voutsadakis

Bibliographic record

VenueTumor Biology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsNOSM UniversitySault Area Hospital
Fundersnot available
KeywordsProteasomeCancer stem cellCancerCancer cellBiologyProteostasisCell biologyStem cellCarcinogenesisCancer researchRegulatorBiochemistryGenetics

Abstract

fetched live from OpenAlex

Proteasome is a multi-protein organelle that participates in cellular proteostasis by destroying damaged or short-lived proteins in an organized manner guided by the ubiquitination signal. By being in a central place in the cellular protein complement homeostasis, proteasome is involved in virtually all cell processes including decisions on cell survival or death, cell cycle, and differentiation. These processes are important also in cancer, and thus, the proteasome is an important regulator of carcinogenesis. Cancers include a variety of cells which, according to the cancer stem cell theory, descend from a small percentage of cancer stem cells, alternatively termed tumor-initiating cells. These cells constitute the subsets that have the ability to propagate the whole variety of cancer and repopulate tumors after cytostatic therapies. Proteasome plays a role in cellular processes in cancer stem cells, but it has been found to have a decreased function in them compared to the rest of cancer cells. This article will discuss the transcriptional regulation of proteasome sub-unit proteins in cancer and in particular cancer stem cells and the relationship of the proteasome with the pluripotency that is the defining characteristic of stem cells. Therapeutic opportunities that present from the understanding of the proteasome role will also be discussed.

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 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 score0.959
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 science0.0000.000
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 head0.078
GPT teacher head0.367
Teacher spread0.289 · 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.

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

Citations77
Published2017
Admission routes1
Has abstractyes

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