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Record W2024678881 · doi:10.1089/jmf.2006.9.451

Green Tea Extract Thermogenesis-Induced Weight Loss by Epigallocatechin Gallate Inhibition of Catechol- <i>O</i> -Methyltransferase

2006· review· en· W2024678881 on OpenAlexaff
Q. Shixian, B. VanCrey, John Shi, Yukio Kakuda, Yongwen Jiang

Bibliographic record

VenueJournal of Medicinal Food · 2006
Typereview
Languageen
FieldMedicine
TopicTea Polyphenols and Effects
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
Fundersnot available
KeywordsThermogenesisEpigallocatechin gallateCatechinCatechol-O-methyl transferaseChemistryWeight lossPharmacologyGreen tea extractBiochemistryPolyphenolGreen teaFood scienceEndocrinologyMedicineAntioxidantAdipose tissue

Abstract

fetched live from OpenAlex

Epidemiological studies have shown that intake of tea catechins is associated with a lower risk of cardiovascular disease. The antioxidative activity of tea-derived catechins has been extensively studied. Reports have shown that green tea extract intake is associated with increased weight loss due to diet-induced thermogenesis, which is generally attributed to the catechin epigallocatechin gallate. That catechin-polyphenols are known to be capable of inhibiting catechol-O-methyltransferase (the enzyme that degrades norepinephrine) is a possible explanation for why the green tea extract is effective in stimulating thermogenesis by epigallocatechin gallate to augment and prolong sympathetic stimulation of thermogenesis. Knowledge about thermogenesis-induced weight loss produced by green tea's epigallocatechin gallate and its ability to inhibit catechol-O-methyltransferase is important for health benefits and for prolonging the action of norepinephrine in the synaptic cleft.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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

Citations113
Published2006
Admission routes1
Has abstractyes

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