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Record W3163084951

Metabolomic Profiling and Biological Investigation of Tabebuia aurea (Silva Manso) Leaves, Family Bignoniaceae

2021· article· en· W3163084951 on OpenAlexaff
Basma Khalaf Mahmoud, Ashraf Hamed, Mamdouh Nabil Samy, Usama Ramadan Abdelmohsen, Eman Zekry Attia, Michael Atef Fawzy, Rana H. Refaey, Mohammad Alaraby Salem, Sheila Marie Pimentel‐Elardo, Justin R. Nodwell, Samar Yehia Desoukey, Mohamed Kamel

Bibliographic record

VenueSSRN Electronic Journal · 2021
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicBioactive Compounds and Antitumor Agents
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBignoniaceaeEthyl acetateChemical constituentsTraditional medicineChemistryKaempferolRutinBiologyAntioxidantBotanyBiochemistryChromatographyFlavonoid
DOInot available

Abstract

fetched live from OpenAlex

Both ethyl acetate and aqueous fractions of Tabebuia aurea leaves exhibited noteworthy antioxidant and nephroprotective activities against carbon tetrachloride (CCl4)-induced nephrotoxicity in rats, as evidenced by the remarkable improvements of renal serum biomarkers and histopathological features. Additionally, the ethyl acetate fraction displayed a prominent in vitro antitrypanosomal activity against Trypanosoma brucei; consequently, the leaves were subjected to LC-HR-ESI-MS metabolomic profiling to discover the constituents that possibly underlie their bioactivities. Therefore, ten metabolites were characterized, mostly dominated by flavonoids. Interestingly, two identified constituents viz., 3,9,12,15-octadecatetraenoic acid (9) and 9,11,13-octadecatrienoic acid (10) are reported firstly herein from the genus Tabebuia. Furthermore, among the dereplicated constituents, rutin (5) and kaempferol 3-O-rutinoside (6) exhibited the highest docking scores as effective antitrypanosomal compounds.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.002
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 head0.106
GPT teacher head0.379
Teacher spread0.273 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

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