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Record W4386318986 · doi:10.1080/09603123.2023.2249424

Phytochemical investigation, antioxidant, anti-inflammatory and cytotoxic activities of Tunisian medicinal <i>Tamarix africana Poir</i>

2023· article· en· W4386318986 on OpenAlexaff
Manel Karker, Samia Oueslati, Hanen Falleh, Kamel Msaâda, Jean Legault, Chédly Abdelly, André Pichette, Riadh Ksouri

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsPhytochemicalTraditional medicineAntioxidantAnti-inflammatoryChemistryIC50Secondary metaboliteBiologyPharmacologyIn vitroBiochemistryMedicine

Abstract

fetched live from OpenAlex

The current study aimed to evaluate Tunisian Tamarix africana Poir biological activities. In this study, novel biological activities of the shoot extracts related to their phenolics investigated. Secondary metabolite contents, antioxidant, anti-inflammatory and cytotoxic activities of four extracts (hexane, dichloromethane, methanol and water) were investigated. Antioxidant activities were assessed via in vitro and ex vivo assays. Besides, anticancer activity was investigated against human lung carcinoma (A-549) and colon adenocarcinoma (DLD-1) cells. The anti-inflammatory ability was evaluated via inhibition of LPS-induced NO production in RAW 264.7 macrophage cell lines. Methanol and water extracts displayed the highest antioxidant (IC50 = 3.3 and 4.3 µg/mL respectively), which are correlated activities correlated with phenolic contents. Hexane extract exhibited an important anti-inflammatory effect inhibiting NO ability by 100% at 80 µg/mL. Besides, T. africana extracts were found to be active against A-549 lung carcinoma cells with IC50 values ranging from 20 to 34 µg/mL. These results suggested that T. africana is considered as a potential source of readily accessible natural molecules with a promising effect on human health and 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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.189

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 integrity0.0000.000
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 head0.052
GPT teacher head0.326
Teacher spread0.274 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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