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Record W2511703858 · doi:10.14740/jocmr2672w

Astaxanthin as a Potential Protector of Liver Function: A Review

2016· review· en· W2511703858 on OpenAlexvenueno aff
Jui‐Tung Chen, Kazuhiko Kotani

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typereview
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsnot available
Fundersnot available
KeywordsAstaxanthinCarotenoidMedicineFatty liverOxidative stressLiver injuryXanthophyllLiver functionHyperlipidemiaLiver diseasePharmacologyBiochemistryDiseaseEndocrinologyInternal medicineBiologyDiabetes mellitus

Abstract

fetched live from OpenAlex

Protecting against liver damage, such as non-alcoholic fatty liver disease, is currently considered to be important for the prevention of adverse conditions, such as cardiovascular and cancerous diseases. Liver damage often occurs in relation to oxidative stress with metabolic disorders, including cellular lipid accumulation. Astaxanthin (3,3'-dihydroxy-β,β-carotene-4,4'dione), a xanthophyll carotenoid, is a candidate for liver protection. Here, we briefly review astaxanthin as a potential protector against liver damage. In particular, studies have reported antioxidative effects of astaxanthin in liver tissues. Astaxanthin treatment is also reported to improve hyperlipidemia, which indirectly induces the antioxidative effects of astaxanthin on liver pathologies. Furthermore, astaxanthin may alleviate liver damage independent of its antioxidative effects. Of note, there are still insufficient human data to observe the effect of astaxanthin treatment on liver function in clinical conditions. More studies investigating the relevance of astaxanthin on liver protection are necessary.

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)0.023
metaresearch head score (Gemma)0.040
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.489
GPT teacher head0.630
Teacher spread0.141 · 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 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

Citations58
Published2016
Admission routes1
Has abstractyes

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