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Record W4388632881 · doi:10.1080/14786419.2023.2278756

Antibacterial stigmastane-type steroids and other constituents from the leaves of <i>Vernonia glabra</i> (Steetz) Vatke (Asteraceae)

2023· article· en· W4388632881 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNatural Product Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNatural product bioactivities and synthesis
Canadian institutionsCarleton University
Fundersnot available
KeywordsBroth microdilutionStaphylococcus aureusAntibacterial activityBacteriaKlebsiella pneumoniaeAsteraceaeChemistryEscherichia coliTraditional medicineMicrobiologyBiologyAntimicrobialMinimum inhibitory concentrationBiochemistryBotanyMedicine

Abstract

fetched live from OpenAlex

Two new stigmastane steroids (1 and 2) were isolated from the methanol extract of the leaves of Vernonia glabra, together with seventeen known compounds (3–19) including one fatty acid, four triterpenoids, four steroids, one trinitropropanoyl glucoside, and seven flavonoids. The structures of compounds 1 and 2 were assigned based on their IR, NMR and MS data, and by comparison with literature values. The MeOH extract, its fractions and isolated compounds were subjected to in vitro antibacterial assay against two Gram-positive (Staphylococcus aureus ATCC25923 and Streptococcus pneumoniae ATCC49619) and two Gram-negative (Escherichia coli ATCC8739 and Klebsiella pneumoniae ATCC10031) bacteria, using broth microdilution method. The extract and fractions exhibited (16 ≤ MIC ≤ 512 μg/mL) antibacterial activities. The isolated and tested compounds were also active (16 ≤ MIC ≤ 128 μg/mL) against the four pathogenic bacteria, with compound 2 being the most active and E. coli, the most sensitive microorganism.

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.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.048
GPT teacher head0.340
Teacher spread0.292 · 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