MétaCan
Menu
Back to cohort
Record W2590621618 · doi:10.1080/15548627.2017.1290751

New frontiers in the treatment of colorectal cancer: Autophagy and the unfolded protein response as promising targets

2017· review· en· W2590621618 on OpenAlexafffund
Pooneh Mokarram, Mohammed Albokashy, Maryam Zarghooni, Mohammad Amin Moosavi, Zahra Sepehri, Qi Min Chen, Andrzej Hudecki, Aliyeh Sargazi, Javad Alizadeh, Adel Rezaei Moghadam, Mohammad Hashemi, Hesam Movassagh, Thomas Klonisch, Ali Akbar Owji, Marek Łoś, Saeid Ghavami

Bibliographic record

VenueAutophagy · 2017
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of TorontoUniversity of Manitoba
FundersNational Institute for Genetic Engineering and BiotechnologyNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsAutophagyUnfolded protein responseBiologyColorectal cancerCancerMalignancyCancer researchDiseaseBioinformaticsGeneGeneticsApoptosisMedicineInternal medicine

Abstract

fetched live from OpenAlex

Colorectal cancer (CRC), despite numerous therapeutic and screening attempts, still remains a major life-threatening malignancy. CRC etiology entails both genetic and environmental factors. Macroautophagy/autophagy and the unfolded protein response (UPR) are fundamental mechanisms involved in the regulation of cellular responses to environmental and genetic stresses. Both pathways are interconnected and regulate cellular responses to apoptotic stimuli. In this review, we address the epidemiology and risk factors of CRC, including genetic mutations leading to the occurrence of the disease. Next, we discuss mutations of genes related to autophagy and the UPR in CRC. Then, we discuss how autophagy and the UPR are involved in the regulation of CRC and how they associate with obesity and inflammatory responses in CRC. Finally, we provide perspectives for the modulation of autophagy and the UPR as new therapeutic options for CRC treatment.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.042
GPT teacher head0.375
Teacher spread0.333 · 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

Citations155
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueAutophagySame topicAutophagy in Disease and TherapyFrench-language works237,207