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Record W2995728042 · doi:10.1021/acs.jnatprod.9b00849

Phloroglucinol Benzophenones and Xanthones from the Leaves of <i>Garcinia cowa</i> and Their Nitric Oxide Production and α-Glucosidase Inhibitory Activities

2019· article· en· W2995728042 on OpenAlexaff
Achara Raksat, Piyaporn Phukhatmuen, Yang Jian-xiong, Wisanu Maneerat, Rawiwan Charoensup, Raymond J. Andersen, Y. Wang, Stephen G. Pyne, Surat Laphookhieo

Bibliographic record

VenueJournal of Natural Products · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsUniversity of British Columbia
FundersAgricultural Research Development Agency
KeywordsPhloroglucinolChemistryAcarboseStereochemistryXanthoneClusiaceaeLignanNitric oxideGarcinia mangostanaIC50Organic chemistryBiochemistryTraditional medicineIn vitroBotanyBiologyEnzyme

Abstract

fetched live from OpenAlex

Five new compounds—two phloroglucinol benzophenones, garciniacowones F ( 1 ) and G ( 2 ), and three xanthones, garciniacowones H ( 3 ), I ( 4 ), and J ( 5 )—together with seven known xanthones ( 6 – 12 ) were isolated from the fresh leaves of Garcinia cowa . Their structures were elucidated by detailed analysis of NMR and MS data. Compounds 1 and 2 are phloroglucinol benzophenones containing a polyprenylated bicyclo[3.3.1]nonane ring system, while compounds 3 – 5 are rare xanthones having farnesyl ( 3 and 5 ) and geranylgeranyl ( 5 ) units at C-8. Compounds 1, 3, 4, 7, 8, and 10 exhibited inhibitory effects on NO production in LPS-induced RAW264.7 macrophage cells with IC 50 values ranging from 5.4 to 18.6 μM. Compounds 4 and 8 had α-glucosidase inhibitory activities with IC 50 values of 15.4 and 11.4 μM, respectively, which were more potent than that of the acarbose control.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.011
GPT teacher head0.201
Teacher spread0.190 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations34
Published2019
Admission routes1
Has abstractyes

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