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Record W2310360756 · doi:10.1530/erc-15-0042

Autophagy in endocrine tumors

2015· review· en· W2310360756 on OpenAlexaff
Andrea M. Weckman, Fabio Rotondo, Antonio Di Ieva, Luis V. Syro, Henriett Butz, Michael D. Cusimano, Kálmán Kovács

Bibliographic record

VenueEndocrine Related Cancer · 2015
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsAutophagyEndocrine systemBiologyContext (archaeology)Cancer researchCancerPancreasCell biologyEndocrinologyHormoneApoptosisBiochemistryGenetics

Abstract

fetched live from OpenAlex

Autophagy is an important intracellular process involving the degradation of cytoplasmic components. It is involved in both physiological and pathological conditions, including cancer. The role of autophagy in cancer is described as a 'double-edged sword,' a term that reflects its known participation in tumor suppression, tumor survival and tumor cell proliferation. Available research regarding autophagy in endocrine cancer supports this concept. Autophagy shows promise as a novel therapeutic target in different types of endocrine cancer, inhibiting or increasing treatment efficacy in a context- and cell-type-dependent manner. At present, however, there is very little research concerning autophagy in endocrine tumors. No research was reported connecting autophagy to some of the tumors of the endocrine glands such as the pancreas and ovary. This review aims to elucidate the roles of autophagy in different types of endocrine cancer and highlight the need for increased research in the field.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.059
GPT teacher head0.428
Teacher spread0.368 · 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

Citations33
Published2015
Admission routes1
Has abstractyes

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