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Record W2891164425 · doi:10.1002/jcp.27372

Melatonin and pancreatic cancer: Current knowledge and future perspectives

2018· review· en· W2891164425 on OpenAlexaff
Omid Reza Tamtaji, Naghmeh Mirhosseini, Rüssel J. Reiter, Morteza Behnamfar, Zatollah Asemi

Bibliographic record

VenueJournal of Cellular Physiology · 2018
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsPure North
Fundersnot available
KeywordsMelatoninPancreatic cancerCancerPancreasPineal glandInternal medicineCancer researchOxidative stressMedicineEndocrinologyAngiogenesisMelatonin receptorInflammationBiology

Abstract

fetched live from OpenAlex

Pancreatic cancer has a high mortality rate due to the absence of early symptoms and subsequent late diagnosis; additionally, pancreatic cancer has a high resistance to radio- and chemotherapy. Multiple inflammatory pathways are involved in the pathophysiology of pancreatic cancer. Melatonin an indoleamine produced in the pineal gland mediated and receptor-independent action is the pancreas and other where has both receptors. Melatonin is a potent antioxidant and tissue protector against inflammation and oxidative stress. In vivo and in vitro studies have shown that melatonin supplementation is an appropriate therapeutic approach for pancreatic cancer. Melatonin may be an effective apoptosis inducer in cancer cells through regulation of a large number of molecular pathways including oxidative stress, heat shock proteins, and vascular endothelial growth factor. Limited clinical studies, however, have evaluated the role of melatonin in pancreatic cancer. This review summarizes what is known regarding the effects of melatonin on pancreatic cancer and the mechanisms involved.

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)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.037
GPT teacher head0.331
Teacher spread0.294 · 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

Citations49
Published2018
Admission routes1
Has abstractyes

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