Evaluation of Essential Oil From Different <i>Artemisia fragrans</i> Willd. Populations: Chemical Composition, Antioxidant, and Antibacterial Activity

Younessi-Hamzekhanlu, Mehdi; Sanjari, Sepideh; Dejahang, Ata; Karkaj, Esmaeil Sheidai; Nojadeh, Mohsen Sabzi; Gönenç, Tuba Mert; Öztürk, Münir

doi:10.1080/0972060x.2020.1854129

Cited by 21 publications

(13 citation statements)

References 42 publications

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“…Medicinal plants have a special place in traditional medicine folk and are used as treatment for many diseases [5,6]. Essential oils are naturally occurring in medicinal and aromatic plants which are rich in valuable biochemical compounds with high bioactivities such as antibacterial, antioxidant and phytotoxic activity [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Essential Oil and Trans-Anethole Yield of Fennel (Foeniculum vulgare Mill. var. vulgare) by Application Artificial Neural Network and Multiple Linear Regression Methods

et al. 2021

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Foeniculum vulgare Mill. (commonly known as fennel) is used in the pharmaceutical, cosmetic, and food industries. Fennel widely used as a digestive, carminative, galactagogue and diuretic and in treating gastrointestinal and respiratory disorders. Improving low heritability traits such as essential oil yield (EOY%) and trans-anethole yield (TAY%) of fennel by direct selection does not result in rapid gains of EOY% and TAY%. Identification of high-heritable traits and using efficient modeling methods can be a beneficial approach to overcome this limitation and help breeders select the most advantageous traits in medicinal plant breeding programs. The present study aims to compare the performance of the artificial neural network (ANN) and multilinear regression (MLR) to predict the EOY% and TAY% of fennel populations. Stepwise regression (SWR) was used to assess the effect of various input variables. Based on SWR, nine traits—number of days to 50% flowering (NDF50%), number of days to maturity (NDM), final plant height (FPH), number of internodes (NI), number of umbels (NU), seed yield per square meter (SY/m2), number of seeds per plant (NS/P), number of seeds per umbel (NS/U) and 1000-seed weight (TSW)—were chosen as input variables. The network with Sigmoid Axon transfer function and two hidden layers was selected as the final ANN model for the prediction of EOY%, and the TanhAxon function with one hidden layer was used for the prediction of TAY%. The results revealed that the ANN method could predict the EOY% and TAY% with more accuracy and efficiency (R2 of EOY% = 0.929, R2 of TAY% = 0.777, RMSE of EOY% = 0.544, RMSE of TAY% = 0.264, MAE of EOY% = 0.385 and MAE of TAY% = 0.352) compared with the MLR model (R2 of EOY% = 0.553, R2 of TAY% = 0.467, RMSE of EOY% = 0.819, RMSE of TAY% = 0.448, MAE of EOY% = 0.624 and MAE of TAY% = 0.452). Based on the sensitivity analysis, SY/m2, NDF50% and NS/P were the most important traits to predict EOY% as well as SY/m2, NS/U and NDM to predict of TAY%. The results demonstrate the potential of ANNs as a promising tool to predict the EOY% and TAY% of fennel, and they can be used in future fennel breeding programs.

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Section: Introductionmentioning

confidence: 99%

Modeling the Essential Oil and Trans-Anethole Yield of Fennel (Foeniculum vulgare Mill. var. vulgare) by Application Artificial Neural Network and Multiple Linear Regression Methods

et al. 2021

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“…[20] The bactericidal properties of other species of Artemisia were earlier reported. [21,22] In the present study, SCF nanocarriers were used to transfer and evaluate the toxicity of AVEO on different bacterial strains. Chitosan-coated SLN-NPs are able to fuse with lipid membranes due to positive surface charge.…”

Section: Discussionmentioning

confidence: 99%

Folic Acid‐Conjugated Chitosan‐Coated Solid Lipid Nanoparticles: Precision Targeting of Artemisia vulgaris Essential Oils for Anticancer Therapy

Aghabagherzadeh,

Karimi,

Zareian

2024

Chemistry & Biodiversity

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In this study, we developed Solid Lipid Nanoparticles (SLN‐NPs) loaded with Artemisia vulgaris essential oil and coated with folic acid‐chitosan (AVEO‐SCF‐NPs) to enhance drug delivery in biotechnology and pharmaceutical sectors. AVEO‐SCF‐NPs were synthesized using homogenization and ultra‐sonication methods and comprehensively characterized. These nanoparticles exhibited a particle size of 253.67 nm, Polydispersity Index (PDI) of 0.26, zeta potential (ζ‐p) of +39.96 mV, encapsulation efficiency (%EE) of 99.0 %, and folic acid binding efficiency (% FB) of 46.25 %. They effectively inhibited MCF‐7, HT‐29, and PC‐3 cancer cells with IC50 values of 48.87 μg/mL, 88.48 μg/mL, and 121.34 μg/mL, respectively, and demonstrated antibacterial properties against Gram‐positive strains. AVEO‐SCF‐NPs also exhibited scavenging effects on ABTS (IC50: 203.83 μg/mL) and DPPH (IC50: 680.86 μg/mL) free radicals and inhibited angiogenesis, as confirmed through CAM and qPCR assays. Furthermore, these nanoparticles induced apoptosis, evidenced by up‐regulation of caspase 3 and 9, down‐regulation of TNF‐α genes, and an increase in SubG1 phase cells. The high loading capacity of SCF‐NPs for AVEO, coupled with their multifaceted biological properties, highlights AVEO‐SCF‐NPs as promising candidates for cancer therapy in the biotechnology and pharmaceutical industries.

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“…Our results showed that the expression level of the recombinant protein was relatively low, which was in agreement with earlier studies (Razmi et al, 2019 ; Schindel et al 2018 ; Shen et al, 2010 ). Many studies have indicated that the low expression level of recombinant proteins in chloroplasts could be attributed to codon usage, translation efficiency, promoter, and protein stability in chloroplasts (Ahmad et al, 2020 ; Apel et al, 2010 ; De Marchis et al, 2012 ; Rowland et al, 2015 ; Soria-Guerra et al, 2009 ; Younessi-Hamzekhanlu et al, 2020 ). Huy Kim ( 2019 ) reported a low expression level (0.07% of TSP) of the porcine epidemic diarrhea antigen in tobacco, whereas fusion with a stable B subunit of the cholera toxin protein increased the expression level by up to 1.4% TSP.…”

Section: Discussionmentioning

confidence: 99%

Overexpression of the recombinant human interferon-beta (rhIFN-β) gene in tobacco chloroplasts

Feizi¹,

BaghbanKohnehrouz²

2021

bta

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Chloroplast genetic engineering is a convenient method for the production of recombinant proteins by increasing the expression level of transgenes. Interferon-beta (IFN- β ) is a member of type I interferons that possess some pharmaceutical properties. The present study aimed to investigate the overexpression and production of the recombinant human IFN- β gene ( rhIFN-β ) in the tobacco chloroplast genome. For this purpose, a codon-optimized rhIFN-β was transferred to the pVSR326 plastid vector containing the aadA gene as a selectable marker. The rhIFN-β gene was then successfully introduced into the tobacco chloroplast genome by using a gene gun. The integration of the rhIFN-β gene into the chloroplast genome and the homoplasmy of the T1 progeny were confirmed by PCR and Southern blot analysis, respectively. RT-PCR and western blot analyses confirmed the transcription and translation of the rhIFN - β gene, respectively. An enzyme-linked immunosorbent assay (ELISA) showed that the rhIFN-β protein in transplastomic plants comprised approximately 2.4% of total soluble protein (TSPs). The bioassay confirmed that the rhIFN-β protein expressed in the tobacco chloroplast had a relatively high biological activity (2.9 × 10 4 IU/ml) and protected human amnionic cells against the vesicular stomatitis virus (VSV). On the basis of these findings, it can be concluded that plastid transformation can serve as an operative method for the production of pharmaceutical recombinant proteins.

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Evaluation of Essential Oil From Different Artemisia fragrans Willd. Populations: Chemical Composition, Antioxidant, and Antibacterial Activity

Cited by 21 publications

References 42 publications

Modeling the Essential Oil and Trans-Anethole Yield of Fennel (Foeniculum vulgare Mill. var. vulgare) by Application Artificial Neural Network and Multiple Linear Regression Methods

Modeling the Essential Oil and Trans-Anethole Yield of Fennel (Foeniculum vulgare Mill. var. vulgare) by Application Artificial Neural Network and Multiple Linear Regression Methods

Folic Acid‐Conjugated Chitosan‐Coated Solid Lipid Nanoparticles: Precision Targeting of Artemisia vulgaris Essential Oils for Anticancer Therapy

Overexpression of the recombinant human interferon-beta (rhIFN-β) gene in tobacco chloroplasts

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