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Record W4380683267 · doi:10.1515/chem-2022-0338

Mineral composition, principal polyphenolic components, and evaluation of the anti-inflammatory, analgesic, and antioxidant properties of <i>Cytisus villosus</i> Pourr leaf extracts

2023· article· en· W4380683267 on OpenAlexaff
Aziz Zouhri, Naoual El Menyiy, Yahya El-Mernissi, Toufik Bouddine, Rafik El-Mernissi, Hassan Amhamdi, Abdelhay Elharrak, Ahmad Mohammad Salamatullah, Hiba‐Allah Nafidi, Farid Khallouki, Mohammed Bourhia, Lhoussain Hajji

Bibliographic record

VenueOpen Chemistry · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversité Laval
FundersKing Saud University
KeywordsABTSChemistryDPPHPolyphenolGallic acidQuinic acidAntioxidantPhytochemicalTraditional medicineFood scienceBiochemistryMedicine

Abstract

fetched live from OpenAlex

Abstract Cytisus villosus Pourr. (C. villosus) is a medicinal plant belonging to the Fabaceae family, which grows in the Mediterranean area. It is used in traditional medicine against diseases related to inflammation. The objective of the present study was to identify the mineral and polyphenolic composition as well as to evaluate some biological properties including antioxidant, anti-inflammatory, and analgesic activities of C. villosus leaf aqueous extract. The chemical constituents were identified and quantified using ultra performance liquid chromatography-electrospray ionization tandem mass spectrometry (UPLC-ESI-MS/MS) methods. The antioxidant properties of C. villosus leaves were tested using reducing power (RP), 2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS), and 2,2′-diphenyl-1-picrylhydrazyl (DPPH) assays. The anti-inflammatory potency was evaluated in vitro and in vivo using the albumin denaturation test and the carrageenan test, respectively. Furthermore, the analgesic effect was performed in vivo using tail flick, acetic acid-induced contortion, and plantar tests. Mineralogical analysis revealed that potassium and calcium were the most abundant minerals. The analysis and quantification of the phytochemical composition using UPLC-ESI-MS/MS showed that quinic acid (57.478 ± 1.72 mg/kg) was the major compound of the aqueous extract, followed by salicylic acid (17.38 ± 0.2 mg/kg), isoquercetin (16.895 ± 1.01 mg/kg), and gallic acid (15.914 ± 1.51 mg/kg). The extracts showed potent antioxidant activity for all tests used. The highest antioxidant activity was recorded for the DPPH, ABTS and RP methods, with an IC50 of 3.94 ± 0.09, 2.88 ± 0.07, and 1.94 ± 0.10 μg/mL, respectively. Additionally, using the most frequent analgesic assays, the aqueous extract at a dose of 500 mg/kg exhibited a potent analgesic activity. Notably, an interesting inhibition of albumin denaturation was recorded with an IC50 of 383.94 μg/mL, corroborating the in vivo test. Overall, the results presented here may represent a scientific basis for the traditional use of C. villosus in the treatment of inflammation-related diseases.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.244
Teacher spread0.207 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

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