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Record W2092189360 · doi:10.6000/1927-5129.2015.11.23

Phytochemical Studies and Antimicrobial Screening of Non/Less-Polar Fraction of Psoralea corylifolia by Using GC-MS

2015· article· en· W2092189360 on OpenAlexvenueno aff
Syed Tariq Ali, Hina Anwar, Syed Kashif Ali, Sobiya Perwaiz, Talat Yasmeen Mujahid, Abdul Wahab, Syed Abdus Subhan

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioactive natural compounds
Canadian institutionsnot available
Fundersnot available
KeywordsPsoralea corylifoliaPhytochemicalAntimicrobialPsoralenChemistryFurocoumarinsGas chromatography–mass spectrometryTraditional medicineChromatographyMass spectrometryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Psoralea corylifolia is a well-known medicinal plant, traditionally used against several diseased conditions. The present study was conducted to investigate the phytochemical composition and antimicrobial activity of P. corylifolia seeds. Non/less-polar fraction of methanolic seed extract was subjected to gas chromatography-mass spectrometry (GC-MS) for phytochemical analysis. A total of fourteen compounds were identified which include aromatic, sesquiterpenes, furocoumarins, sterols, fatty acid and their methyl esters. The predominant compounds were epoxycaryophyllene (3), isopsoralen (6), psoralen (7) and bakuchiol (9). Identification of these compounds was also strongly supported by Kovat’s Retention Indices. Furthermore, the n-hexane soluble fraction showed significant antimicrobial activity against several bacterial strains. P. corylifolia seeds represented a unique chemical composition with considerable antimicrobial activity which not only validates their traditional medicinal uses but also indicates their potential as a source of natural antimicrobial 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 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.323
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 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
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

Citations3
Published2015
Admission routes1
Has abstractyes

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