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Record W2748693600 · doi:10.1002/9781119166191.ch8

Biochemistry and Molecular Mechanisms of<i>Monascus</i>Pigments

2017· other· en· W2748693600 on OpenAlexaff
Changlu Wang, Di Chen, Jiancheng Qi

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolism and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMonascusPigmentYeastRed yeast riceBiologyBiochemistryAdipogenesisFermentationGeneFood scienceChemistry

Abstract

fetched live from OpenAlex

A Monascus pigment is produced by either traditional extraction processing from red yeast rice or modern submerged fermentation and extraction technology. Some reports indicate that Monascus pigments and red yeast rice extracts possess potential anti-obesity activities, through inhibition of the activities of lipases and of the proliferation and adipogenesis of adipocyte cells. Monascin and ankaflavin may reduce the accumulation of triglycerides in fat cells and inhibit the expression of a specific transcription factor in order to reduce cell proliferation. There is a large literature to suggest that Monascus pigments and red yeast rice extracts have antimutagenic and anticancer activities. Continuous improvement of molecular biology makes it possible to reveal the metabolic mechanism of Monascus pigments on the molecular level. At present, molecular investigation of the genus Monascus has revealed the taxonomic identity of the species, the gene cluster of secondary metabolites, and the G-protein signal transduction pathways of related genes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.005
GPT teacher head0.232
Teacher spread0.228 · 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 designBench or experimental
Domainnot available
GenreOther

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

Citations3
Published2017
Admission routes1
Has abstractyes

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