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Adding New Scientific Evidences on the Pharmaceutical Properties of Pelargonium quercetorum Agnew Extracts by Using In Vitro and In Silico Approaches.

ABSTRACT: Pelargonium quercetorum is a medicinal plant traditionally used for treating intestinal worms. In the present study, the chemical composition and bio-pharmacological properties of P. quercetorum extracts were investigated. Enzyme inhibition and scavenging/reducing properties of water, methanol, and ethyl acetate extracts were assayed. The extracts were also studied in an ex vivo experimental model of colon inflammation, and in this context the gene expression of cyclooxygenase-2 (COX-2) and tumor necrosis factor α (TNFα) were assayed. Additionally, in colon cancer HCT116 cells, the gene expression of transient receptor potential cation channel subfamily M (melastatin) member 8 (TRPM8), possibly involved in colon carcinogenesis, was conducted as well. The extracts showed a different qualitative and quantitative content of phytochemicals, with water and methanol extracts being richer in total phenols and flavonoids, among which are flavonol glycosides and hydroxycinnamic acids. This could explain, at least in part, the higher antioxidant effects shown by methanol and water extracts, compared with ethyl acetate extract. By contrast, the ethyl acetate was more effective as cytotoxic agent against colon cancer cells, and this could be related, albeit partially, to the content of thymol and to its putative ability to downregulate TRPM8 gene expression. Additionally, the ethyl acetate extract was effective in inhibiting the gene expression of COX-2 and TNFα in isolated colon tissue exposed to LPS. Overall, the present results support future studies for investigating protective effects against gut inflammatory diseases.

SUBMITTER: Chiavaroli A

PROVIDER: S-EPMC10005478 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Adding New Scientific Evidences on the Pharmaceutical Properties of Pelargonium quercetorum Agnew Extracts by Using In Vitro and In Silico Approaches.

Chiavaroli Annalisa A Libero Maria Loreta ML Di Simone Simonetta Cristina SC Acquaviva Alessandra A Nilofar Recinella Lucia L Leone Sheila S Brunetti Luigi L Cicia Donatella D Izzo Angelo Antonio AA Orlando Giustino G Zengin Gokhan G Uba Abdullahi Ibrahim AI Cakilcioğlu Ugur U Mukemre Muzaffer M Elkiran Omer O Menghini Luigi L Ferrante Claudio C

Plants (Basel, Switzerland) 20230302 5

Pelargonium quercetorum is a medicinal plant traditionally used for treating intestinal worms. In the present study, the chemical composition and bio-pharmacological properties of P. quercetorum extracts were investigated. Enzyme inhibition and scavenging/reducing properties of water, methanol, and ethyl acetate extracts were assayed. The extracts were also studied in an ex vivo experimental model of colon inflammation, and in this context the gene expression of cyclooxygenase-2 (C ...[more]

PMID: 36903991

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Project description:The mastic tree, scientifically known as Pistacia lentiscus, which belongs to the Anacardiaceae family, was used in this study. The aim of this research was to analyze the chemical composition of this plant and assess its antioxidant and antibacterial properties using both laboratory experiments and computer simulations through molecular docking, a method that predicts the binding strength of a small molecule to a protein. The soxhlet method (SE) was employed to extract substances from the leaves of P. lentiscus found in the eastern region of Morocco. Hexane and methanol were the solvents used for the extraction process. The n-hexane extract was subjected to gas chromatography-mass spectrometry (GC/MS) to identify its fatty acid content. The methanolic extract underwent high-performance liquid chromatography with a diode-array detector (HPLC-DAD) to determine the presence of phenolic compounds. Antioxidant activity was assessed using the DPPH spectrophotometric test. The findings revealed that the main components in the n-hexane extract were linoleic acid (40.97 ± 0.33%), oleic acid (23.69 ± 0.12%), and palmitic acid (22.83 ± 0.10%). Catechin (37.05 ± 0.15%) was identified as the predominant compound in the methanolic extract through HPLC analysis. The methanolic extract exhibited significant DPPH radical scavenging, with an IC50 value of 0.26 ± 0.14 mg/mL. The antibacterial activity was tested against Staphylococcus aureus, Listeria innocua, and Escherichia coli, while the antifungal activity was evaluated against Geotrichum candidum and Rhodotorula glutinis. The P. lentiscus extract demonstrated notable antimicrobial effects. Additionally, apart from molecular docking, other important factors, such as drug similarity, drug metabolism and distribution within the body, potential adverse effects, and impact on bodily systems, were considered for the substances derived from P. lentiscus. Scientific algorithms, such as Prediction of Activity Spectra for Substances (PASS), Absorption, Distribution, Metabolism, Excretion (ADME), and Pro-Tox II, were utilized for this assessment. The results obtained from this research support the traditional medicinal usage of P. lentiscus and suggest its potential for drug development.

Project description:BackgroundSharing anonymized/de-identified clinical trial data and publishing research outcomes in scientific journals, or presenting them at conferences, is key to data-driven scientific exchange. However, when data from scientific publications are linked to other publicly available personal information, the risk of reidentification of trial participants increases, raising privacy concerns. Therefore, we defined a set of criteria allowing us to determine and minimize the risk of data reidentification. We also implemented a review process at Takeda for clinical publications prior to submission for publication in journals or presentation at medical conferences.MethodsAbstracts, manuscripts, posters, and oral presentations containing study participant information were reviewed and the potential impact on study participant privacy was assessed. Our focus was on direct (participant ID, initials) and indirect identifiers, such as sex, age or geographical indicators in rare disease studies or studies with small sample size treatment groups. Risk minimization was sought using a generalized presentation of identifier-relevant information and decision-making on data sharing for further research. Additional risk identification was performed based on study participant/personnel parameters present in materials destined for the public domain. The potential for participant/personnel identification was then calculated to facilitate presentation of meaningful but de-identified information.ResultsThe potential for reidentification was calculated using a risk ratio of the exposed versus available individuals, with a value above the threshold of 0.09 deemed an unacceptable level of reidentification risk. We found that in 13% of Takeda clinical trial publications reviewed, either individuals could potentially be reidentified (despite the use of anonymized data sets) or inappropriate data sharing plans could pose a data privacy risk to study participants. In 1/110 abstracts, 58/275 manuscripts, 5/87 posters and 3/58 presentations, changes were necessary due to data privacy concerns/rules. Despite the implementation of risk-minimization measures prior to release, direct and indirect identifiers were found in 11% and 34% of the analysed documents, respectively.ConclusionsRisk minimization using de-identification of clinical trial data presented in scientific publications and controlled data sharing conditions improved privacy protection for study participants. Our results also suggest that additional safeguards should be implemented to ensure that higher data privacy standards are met.

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Adding New Scientific Evidences on the Pharmaceutical Properties of Pelargonium quercetorum Agnew Extracts by Using In Vitro and In Silico Approaches.

Publications

Adding New Scientific Evidences on the Pharmaceutical Properties of <i>Pelargonium quercetorum</i> Agnew Extracts by Using In Vitro and In Silico Approaches.

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