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Record W3165797423 · doi:10.3390/cancers13112628

Current Evidence of the Role of the Myokine Irisin in Cancer

2021· review· en· W3165797423 on OpenAlexaff
Evangelia Tsiani, Nicole Tsakiridis, Rozalia Kouvelioti, Alina Jaglanian, Panagiota Klentrou

Bibliographic record

VenueCancers · 2021
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsBrock University
Fundersnot available
KeywordsMyokineCancerCancer cellReceptorApoptosisDiseaseCancer researchMedicineBioinformaticsBiologyEndocrinologyInternal medicineSkeletal muscleBiochemistry

Abstract

fetched live from OpenAlex

Cancer is a disease associated with extreme human suffering, a huge economic cost to health systems, and is the second leading cause of death worldwide. Regular physical activity is associated with many health benefits, including reduced cancer risk. In the past two decades, exercising/contracting skeletal muscles have been found to secrete a wide range of biologically active proteins, named myokines. Myokines are delivered, via the circulation, to different cells/tissues, bind to their specific receptors and initiate signaling cascades mediating the health benefits of exercise. The present review summarizes the existing evidence of the role of the myokine irisin in cancer. In vitro studies have shown that the treatment of various cancer cells with irisin resulted in the inhibition of cell proliferation, survival, migration/ invasion and induced apoptosis by affecting key proliferative and antiapoptotic signaling pathways. However, the effects of irisin in humans remains unclear. Although the majority of the existing studies have found reduced serum irisin levels in cancer patients, a few studies have shown the opposite. Similarly, the majority of studies have found increased levels of irisin in cancer tissues, with a few studies showing the opposite trend. Clearly, further investigations are required to determine the exact role of irisin in cancer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.087
GPT teacher head0.415
Teacher spread0.328 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations47
Published2021
Admission routes1
Has abstractyes

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