Extraction Method Research Articles

Evaluation of the time, labor, and money required for manual and automated nucleic acid (RNA) isolation for the detection of SARS-COV-2 by QRT-PCR using the qiamp viral RNA mini kit and kingfisher flex

We undertook this cross-sectional investigation to assess the time, manpower, and average run cost per sample using manual Qiamp Viral RNA micro kit (Qiagen) and automated kingfisher flex instrument extraction methods for SARS-Cov-2 identification.The study used 120 Viral Transport Media-collected nasopharyngeal/ oropharyngeal swabs.Magnetic bead-based RNA extraction was performed using the Thermo Fisher Scientific kingfisher flex instrument and manual Extraction was Silica membrane-based Qiagen spin column kits. The TaqPath™ COVID-19 Combo Kit from Thermo Fisher Scientific was used for detecting SARS-CoV-2 target genes.Human technique took 40 minutes longer than automation. It cost more to automate than to manually labor. These disparities in time, effort, and cost affect laboratory operations, offering pros and cons for each method. This suggests that positive or negative was consistent regardless of viral load or RNA concentration.The study found that automated RNA extraction yielded better results compared to manual extraction. The automated sample processing system saved time, people, and money. In resource-limited or low-throughput labs, manual extraction may be preferable. Manual methods are laborious, require more hands-on time, and risk cross-contamination and technical blunders.

Assessment of ethanol leaf extract from urtica dioica for in vitro Anti-Helminthic properties

Helminthic infections continue to be a significant public health concern worldwide, particularly in regions with poor sanitation and limited access to healthcare. With the increasing prevalence of drug resistance among helminths, there is a pressing need for alternative treatments derived from natural sources. Urtica dioica, commonly known as stinging nettle, has been traditionally used for various medicinal purposes, including its purported anthelmintic properties. This study aimed to evaluate the in vitro anti-helminthic activity of ethanol leaf extract of Urtica dioica against helminth parasites. Fresh leaves of Urtica dioica were collected, dried, and powdered. The ethanol leaf extract was prepared using standard extraction methods. Various concentrations of the extract were tested against helminth parasites using established in vitro assays. The efficacy of the extract was determined by assessing parameters such as paralysis and mortality of the parasites. Preliminary findings indicate that the ethanol leaf extract of urtica dioica possesses significant anti-helminthic activity against the tested parasites. The extract exhibited dose-dependent paralysis and mortality of the helminths, with higher concentrations demonstrating greater efficacy. These results suggest the potential of Urtica dioica as a natural source of anthelmintic agents. Further studies are warranted to elucidate the specific bioactive compounds responsible for the observed anti-helminthic activity and to evaluate the safety and efficacy of Urtica dioica extract in vivo. Additionally, investigations into the underlying mechanisms of action and potential synergistic effects with conventional anthelmintic drugs may provide valuable insights for the development of novel therapeutic interventions against helminthic infections. The study results when compared to standard drug of fenbendazole, ethanolic extract of Urtica dioica possess a good significant anti-helmentic activity compared to standard drug of fenbendazole.

AlphaFind: discover structure similarity across the proteome in AlphaFold DB.

AlphaFind is a web-based search engine that provides fast structure-based retrieval in the entire set of AlphaFold DB structures. Unlike other protein processing tools, AlphaFind is focused entirely on tertiary structure, automatically extracting the main 3D features of each protein chain and using a machine learning model to find the most similar structures. This indexing approach and the 3D feature extraction method used by AlphaFind have both demonstrated remarkable scalability to large datasets as well as to large protein structures. The web application itself has been designed with a focus on clarity and ease of use. The searcher accepts any valid UniProt ID, Protein Data Bank ID or gene symbol as input, and returns a set of similar protein chains from AlphaFold DB, including various similarity metrics between the query and each of the retrieved results. In addition to the main search functionality, the application provides 3D visualizations of protein structure superpositions in order to allow researchers to instantly analyze the structural similarity of the retrieved results. The AlphaFind web application is available online for free and without any registration at https://alphafind.fi.muni.cz.

Extraction of Heracleum dissectum soluble dietary fiber by different methods: Structure and antioxidant properties.

Heracleum dissectum is rich in nutrients, but there is little research on its soluble dietary fiber (SDF). In this study, SDF from H. dissectum was extracted by enzyme extraction (E-SDF), enzyme chemical extraction (EC-SDF), and fermentation extraction (F-SDF). The composition, molecular weight (Mw), structural characterization, and antioxidant activity of SDF extracted by the three methods were compared. This study showed that different extraction methods lead to differences in their structure. The Mw results showed that F-SDF had the largest Mw, the structure of SDF could be destroyed by enzymatic hydrolysis, and large molecules could be converted into small molecules. The monosaccharide composition analysis showed that the main sugars of E-SDF, EC-SDF, and F-SDF were galacturonic acid and galactose, and the main components of the three SDF samples were hemicellulose hydrolyzed pectin and soluble polysaccharide. Notably, E-SDF had the greatest antioxidant effect at the same concentration. In summary, different extraction methods can affect the structure and antioxidant capacity of H. dissectum SDF, among which E-SDF has potential as a functional food ingredient.

Valorization of rice straw and vascular aquatic weeds for sustainable prebiotic hemicellulosic autohydrolysate production: Extraction, characterization and fermentability.

This study describes the extraction and characterization of the hemicellulosic autohydrolysates (HAHs) derived from rice straw (RS) and vascular aquatic weeds like Typha angustifolia (TA) and Ceretophyllum demersum (CD). It further explores their capacity to sustain the proliferation of selected lactic acid bacteria (i.e., prebiotic activity) isolated from milk samples. To fractionate HAH from RS, TA and CD hot water extraction (HWE) method was used and RS, TA, and CD biomasses yielded 6.8, 4.99 and 2.98% of HAH corresponding to the hemicellulose extraction efficiencies of 26.15 ± 0.8%, 23.76 ± 0.6%, and 18.62 ± 0.4% respectively. The chemical characterization of HAH concentrates through HPLC showed that they comprised galactose, arabinose, xylose and glucose. The total phenol content of the RS, TA and CD-derived HAH concentrates were 37.53, 56.78 and 48.08mg GAE/g. The five lactic acid bacteria (LAB) isolates Q1B, Q2A, Q3B, G1C and G2B selected for prebiotic activity assays generated mixed responses with the highest growth in RS-HAH for Q2A and the least in TA-HAH for Q3B. Further, the isolates Q2A, Q3B, G1C, and G2B, which showed the highest growth performance, were identified through MALDI-TOF and 16S rRNA sequencing as Lactobacillus brevis. All the tested LAB isolates showed diauxic growth in crude HAH preparations to maximize the utilization of carbon resources for their proliferation. This suggests that the selected LAB isolates are efficient degraders of hemicellulosic sugars. This paves the way for the valorization of lignocellulosic biomass to produce prebiotic hemicellulosic autohydrolysate and consequently enhances environmental sustainability by improving resource efficiency.

Spectrum feature extraction method combining Allan variance, VMD, and PSD

Spectrum feature extraction plays a crucial role in identifying seismic events and calculating structural response parameters. However, the criteria for identifying effective modal components in Variational Mode Decomposition (VMD) are not well-defined, resulting in inaccurate spectrum feature extraction. To address this issue, we propose a novel spectrum feature extraction method that combines Allan variance, VMD, and power spectral density (PSD). Firstly, VMD is applied to filter noise components from triaxial accelerometer observations and add effective signals. Secondly, PSD is utilized to extract three groups of seismic frequencies (tri-axial accelerometers). Finally, the Allan method is introduced to identify the group of accelerometer observations with the highest reliability as the vibration frequency caused by the seismic excitation. We validate the effectiveness of our method by analyzing a Mw 2.6 micro-seismic event that occurred in Huairou, Beijing in 2022. The result shows that our proposed method accurately extracts spectrum features of the Great Wall. Specifically, the seismic excitation vibration frequencies at four monitoring stations were found to be 26.95 Hz, 12.89 Hz, 12.89 Hz, and 12.5 Hz. These findings underscore our method's utility in evaluating the Great Wall's structural response to seismic loading, which has significant implications for the conservation and protection of heritage structures.

Non-Contact Blood Pressure Estimation from Radar Signals by a Stacked Deformable Convolution Network.

This study introduces a contactless blood pressure monitoring approach that combines conventional radar signal processing with novel deep learning architectures. During the preprocessing phase, datasets suitable for synchronization are created by integrating Kalman filtering, multiscale bandpass filters, and a periodic extraction method in the time domain. These data comprise data on chest micro variations, encapsulating a complex array of physiological and biomedical information reflective of cardiac micromotions. The Radar-based Stacked Deformable convolution Network (RSD-Net) integrates channel and spatial self attention mechanisms within a deformable convolutional framework to enhance feature extraction from radar signals. The network architecture systematically employs deformable convolutions for initial deep feature extraction from individual signals. Subsequently, continuous blood pressure estimation is conducted using self attention mechanisms on feature map from single source coupled with multi-feature map channel attention. The performance of model is corroborated via the open-source dataset procured using a non-invasive 24GHz six-port continuous wave radar system. The dataset, encompassing readings from 30 healthy individuals subjected to diverse conditions including rest, the Valsalva maneuver, apnea, and tilt-table examinations. It serves to substantiate the validity and resilience of the proposed method in the non-contact assessment of continuous blood pressure. Evaluation metrics reveal Pearson correlation coefficients of 0.838 for systolic and 0.797 for diastolic blood pressure predictions. The Mean Error (ME) and Standard Deviation (SD) for systolic and diastolic blood pressure measurements are -0.32 ±6.14mmHg and -0.20 ±5.50mmHg, respectively. The ablation study assesses the contribution of different structural components of the RSD-Net, validating their significance in the overall of model performance.

One-Year Longitudinal Assessment of Patients With CMT1A Using Quantitative MRI.

Intramuscular fat fraction (FF) assessed using quantitative MRI (qMRI) has emerged as one of the few responsive outcome measures in CMT1A suitable for future clinical trials. This study aimed to identify the relevance of multiple qMRI biomarkers for tracking longitudinal changes in CMT1A and to assess correlations between MRI metrics and clinical parameters. qMRI was performed in CMT1A patients at 2 time points, a year apart, and various metrics were extracted from 3-dimensional volumes of interest at thigh and leg levels. A semiautomated segmentation technique was used, enabling the analysis of central slices and a larger 3D muscle volume. Metrics included proton density (PD), magnetization transfer ratio (MTR), and intramuscular FF. The sciatic and tibial nerves were also assessed. Disease severity was gauged using Charcot Marie Tooth Neurologic Score (CMTNSv2), Charcot Marie Tooth Examination Score, Overall Neuropathy Limitation Scale scores, and Medical Research Council (MRC) muscle strength. Twenty-four patients were included. FF significantly rose in the 3D volume at both thigh (+1.04% ± 2.19%, p = 0.041) and leg (+1.36% ± 1.87%, p = 0.045) levels. The 3D analyses unveiled a length-dependent gradient in FF, ranging from 22.61% ± 10.17% to 26.17% ± 10.79% at the leg level. There was noticeable variance in longitudinal changes between muscles: +3.17% ± 6.86% (p = 0.028) in the tibialis anterior compared with 0.37% ± 4.97% (p = 0.893) in the gastrocnemius medialis. MTR across the entire thigh volume showed a significant decline between the 2 time points -2.75 ± 6.58 (p = 0.049), whereas no significant differences were noted for the 3D muscle volume and PD. No longitudinal changes were observed in any nerve metric. Potent correlations were identified between FF and primary clinical measures: CMTNSv2 (ρ = 0.656; p = 0.001) and MRC in the lower limbs (ρ = -0.877; p < 0.001). Our results further support that qMRI is a promising tool for following up longitudinal changes in CMT1A patients, FF being the paramount MRI metric for both thigh and leg regions. It is crucial to scrutinize the postimaging data extraction methods considering that annual changes are minimal (around +1.5%). Given the varied FF distribution, the existence of a length-dependent gradient, and the differential fatty involution across muscles, 3D volume analysis appeared more suitable than single slice analysis.

Evaluation of pretreatment methods for filamentous fungal detection

In order to obtain the best mass spectrometry identification results for using the most appropriate methods in clinical practice, we explore the optimal pretreatment methods for different species and morphologies of filamentous fungi. 98 fungal strains were treated with formic acid sandwich method, dispersion method, extraction method, and other methods using a medium element mass spectrometer (EXS3000) as a platform. Each strain had three targets, and the identification rates and confidence differences under different pre-treatment methods were compared to evaluate the identification effects of these methods. The mass spectrometry identification rates of 98 filamentous fungi obtained after pre-treatment with formic acid sandwich method, dispersion method, and extraction method were 85.71%, 82.65%, and 75.51%, respectively. The identification rate of the formic acid sandwich method was significantly higher than the other two methods (P < 0 005) has the best identification ability and the obtained confidence is also higher than the other two methods. The use of formic acid sandwich method for mass spectrometry identification of filamentous fungi can achieve ideal identification results, which is suitable for mass spectrometry identification of filamentous fungi in conventional laboratories.

IDENTIFICATION OF POTATO LEAF DISEASES USING ARTIFICIAL NEURAL NETWORKS WITH EXTREME LEARNING MACHINE ALGORITHM

Potato plants have an important role in providing a source of carbohydrates for society. However, potato production is often threatened by various plant diseases, such as leaf disease, which can cause a decrease in yields. Identification of diseases on potato leaves is currently mostly done by farmers manually, so it is not always efficient and accurate. So the aim of this research is to identify diseases on potato leaves with artificial neural networks using the ELM (Extreme Learning Machine) approach and the GLCM (Gray Level Co-Occurrence Matrix) method for feature extraction. The GLCM approach functions to obtain texture features on objects by measuring how often certain pairs of pixel intensities appear together at various distances and directions in the image. Meanwhile, the ELM algorithm is used for image identification by adopting a one-time training method without iteration, which involves randomly determining weights and biases in hidden layers, thus allowing training to be carried out quickly and efficiently. Evaluation of the model by looking for the level of accuracy produces a value of 84.667%. The results show that the model developed is capable of accurate identification.

Use of diffusive gradients in thin-film technique to predict the mobility and transfer of nutrients and toxic elements from agricultural soil to crops-an overview of recent studies.

The purpose of this review was to survey the recent applications of the diffusive gradients in thin films (DGT) technique in the assessment of mobility and bioavailability of nutrients and potentially toxic elements (PTEs) in agricultural soil. Many studies compared the capabilities of the DGT technique with those of classical soil chemical extractants used in single or sequential procedures to predict nutrients and PTE bioavailability to crops. In most of the published works, the DGT technique was reported to be superior to the conventional chemical extraction and fractionation methods in obtaining significant correlations with the metals and metalloids accumulated in crops. In the domain of nutrient bioavailability assessment, DGT-based studies focused mainly on phosphorous and selenium labile fraction measurement, but potassium, manganese, and nitrogen were also studied using the DGT tool. Different DGT configurations are reported, using binding and diffusive layers specific for certain analytes (Hg, P, and Se) or gels with wider applicability, such as Chelex-based binding gels for metal cations and ferrihydrite-based hydrogels for oxyanions. Overall, the literature demonstrates that the DGT technique is relevant for the evaluation of metal and nutrient bioavailability to crops, due to its capacity to mimic the plant root uptake process, which justifies future improvement efforts.

Research Progress on Taxus Extraction and Formulation Preparation Technologies

Taxus, as a globally prevalent evergreen tree, contains a wealth of bioactive components that play a crucial role in the pharmaceutical field. Taxus extracts, defined as a collection of one or more bioactive compounds extracted from the genus Taxus spp., have become a significant focus of modern cancer treatment research. This review article aims to delve into the scientific background of Taxus extracts and their considerable value in pharmaceutical research. It meticulously sifts through and compares various advanced extraction techniques such as supercritical extraction, ultrasound extraction, microwave-assisted extraction, solid-phase extraction, high-pressure pulsed electric field extraction, and enzymatic extraction, assessing each technology’s advantages and limitations across dimensions such as extraction efficiency, extraction purity, economic cost, operational time, and environmental impact, with comprehensive analysis results presented in table form. In the area of drug formulation design, this paper systematically discusses the development strategies for solid, liquid, and semi-solid dosage forms based on the unique physicochemical properties of Taxus extracts, their intended medical uses, and specific release characteristics, delving deeply into the selection of excipients and the critical technical issues in the drug preparation process. Moreover, the article looks forward to the potential directions of Taxus extracts in future research and medical applications, emphasizing the urgency and importance of continuously optimizing extraction methods and formulation design to enhance treatment efficacy, reduce production costs, and decrease environmental burdens. It provides a comprehensive set of preparation techniques and formulation optimization schemes for researchers in cancer treatment and other medical fields, promoting the application and development of Taxus extracts in pharmaceutical sciences.

The double-feature extraction method based on slope entropy and symbolic dynamic entropy for the fault diagnosis of rolling bearing

The double-feature extraction method based on slope entropy and symbolic dynamic entropy for the fault diagnosis of rolling bearing

Enhancing phycocyanin yield from Spirulina sp. under salt stress using various extraction methods.

Phycocyanin, a blue-coloured pigment, predominantly found and derived from Spirulina sp., has gained researchers' interest due to its vibrant hues and other attractive properties like antioxidant and anti-microbial. However, the lack of reliable and sustainable phycocyanin extraction strategies without compromising the quality has hindered the scaling up of its production processes for commercial purposes. Here in this study, phycocyanin was extracted from wet and dry biomass Spirulina sp., using three different physical cell disruption methods (ultrasonication, homogenization, and freeze-thaw cycles) combined with two different buffers (phosphate buffer and acetate buffer) and water (as control). The result showed that the freeze-thaw method combined with acetate buffer produced the highest yield (25.013 ± 2.572mg/100mg) with a purity ratio of 0.806 ± 0.079. Furthermore, when subjected to 30% w/v salt stress, 1.9 times higher phycocyanin yield with a purity ratio of 1.402 ± 0.609 was achieved using the previously optimized extraction method.

Quantitative analysis of organosulphur compounds in crude oil samples using magnetic solid phase extraction based on Au-Fe3O4 adsorbent and gas chromatography with time-of-flight mass spectrometry

AbstractThis study focused on the development of a magnetic solid phase extraction (m-SPE) method using Au-Fe3O4 as an adsorbent followed by GC-ToFMS analysis for the determination of organosulphur compounds (OSCs) in fuel samples. The m-SPE using Au-Fe3O4 NPs was preferred because of the low toxicity of the adsorbent1, high separation efficiency using external magnet2 and greater extraction selectivity between sulphur and Au atom3. The Au-Fe3O4 NPs were characterized using XRD, UV–Vis, TEM, SEM and FTIR. This method was optimized using multivariate analysis based on a two-level full factorial and central composite designs. The conditions which produced optimum efficiency were found to be 150 mg mass of sorbent, 100 µL eluent volume, 50 min extraction time and 6,5 pH of the sample. These optimum conditions showed a relatively low limit of detection in the range of 0.02–0.199nµg/g and limit of quantification of 0.08–0.602 µg/g. Furthermore, a relative standard deviation of triplicates analysis was between 0.8 and 2.3% with good linearity of 0.9816–0.9961. The percentage recovery for thiophene, 3-methylthiophene, benzothiophene and dibenzothiophene ranged from 76 to 95% for the spiked samples. The optimized m-SPE method was then applied in real fuel oil samples. The concentration of thiophene, 3-methylthiophene, benzothiophene and dibenzothiophene in crude oil, gasoline, diesel and kerosene ranged from 0.43–1.94 µg/g, 0.78–1.63 µg/g, 0.95–4.31 µg/g to 1.55–2.09 µg/g, respectively. The m-SPE, followed by GC-ToFMS method, proved to be efficient, inexpensive and an alternative method for OSCs analysis in fuel oils.

Structural Characteristic, Strong Antioxidant, and Anti-Gastric Cancer Investigations on an Oleoresin from Ginger (Zingiber officinale var. roscoe)

It is known that ginger oleoresin contains various active components and possesses bioactivities. In this study, ginger oleoresin from Chinese ginger (Zingiber officinale var. roscoe) was extracted using a CO2 supercritical fluid extraction method with a 0.52% yield (g/g), based on dry weights. Zingiberene with a content of 51.6 mg/g was the main volatile in the ginger oleoresin. In total, 17 phenolic compounds were identified, and their contents were calculated as 587.54 mg/g. Among them, a new gingertriol was detected in the Z. officinale. Antioxidant activity tests showed that the ginger oleoresin and six gingerols exhibited strong scavenging free radical activities, and the zingerone exhibited the strongest antioxidant activity, with IC50 values of 11.3 µg/mL for the 2, 2′-diphenyl-1-picrylhydrazyl radical and 19.0 µg/mL for the 2, 2′-amino-di (2-ethyl-benzothiazoline sulphonic acid-6) ammonium salt radical cation, comparable to vitamin C. Ginger oleoresin inhibits HGC-27 human gastric cancer cell proliferation at a rate of 4.05~41.69% and induces cell apoptosis at a rate of 10.4~20.9%. The Western blot result demonstrated that the AKT signaling pathway has the potential mechanism of ginger oleoresin acting on HGC-27 cells. The anticancer potential of the gingerol standards on HGC-27 cells followed the order of 8-gingerol &gt; 6-gingerol &gt; 10-gingerol &gt; zingerone. The different antioxidant and anticancer potentials of the ginger phenolic compounds could be attributed to the presence of hydroxyl groups in the unbranched 1-alkyl chain and the length of carbon side chain. Consequently, ginger oleoresin shows substantial antioxidant and anticancer therapeutic potential and can be used for novel food–drug development.

Sustainable dye extraction: Annatto powder production in a fountain confined spouted bed

AbstractThis study proposes an efficient and sustainable process for annatto powder production using a fountain confined spouted bed. With widespread applications in industries such as food, pharmaceuticals, and cosmetics, conventional extraction methods face environmental and economic challenges. Our study explores a solvent‐free and eco‐friendly approach using mechanical attrition within a fountain confined spouted bed, offering a cost‐effective solution for annatto cultivation. We systematically investigated the impact of four parameters—fountain confiner position and length, draft tube diameter, and airflow velocity—employing experimental design, multiple regression analysis, particle swarm optimization, and computational fluid dynamics–discrete element method (CFD‐DEM) simulations. The proposed optimization condition shows significantly higher collision intensity, improving annatto powder production compared to other central composite design tests. This study contributes to developing of a sustainable and economically viable method for dye production, with potential implications for annatto‐producing regions globally.

Applying the Hypothetical Extraction Method to Investigate Intersectoral Carbon Emission Linkages of China’s Transportation Sector

Applying the Hypothetical Extraction Method to Investigate Intersectoral Carbon Emission Linkages of China’s Transportation Sector

Research Progress on Active Ingredients and Product Development of Lycium ruthenicum Murray

Lycium ruthenicum Murray possesses significant applications in both food and medicine, including antioxidative, anti-tumor, anti-fatigue, anti-inflammatory, and various other effects. Consequently, there has been a surge in research endeavors dedicated to exploring its potential benefits, necessitating the organization and synthesis of these findings. This article systematically reviews the extraction and content determination methods of active substances such as polysaccharides, anthocyanins, flavonoids, and polyphenols in LRM in the past five years, as well as some active ingredient composition determination methods, biological activities, and product development. This review is divided into three main parts: extraction and determination methods, their bioactivity, and product development. Building upon prior research, we also delve into the economic and medicinal value of Lycium ruthenicum Murray, thereby contributing significantly to its further exploration and development. It is anticipated that this comprehensive review will serve as a valuable resource for advancing research on Lycium ruthenicum Murray.

Extraction of Antioxidants from Brown Macroalgae Fucus spiralis

In this study, different extraction methods and conditions were used for the extraction of antioxidants from brown macroalgae Fucus spiralis. The extraction methodologies used were ultrasound-assisted extraction (ultrasonic bath and ultrasonic probe), extraction with a vortex, extraction with an Ultra-Turrax® homogenizer, and high-pressure-assisted extraction. The extracts were analyzed for their total phenolic content (TPC) and their antioxidant activity, and evaluated through the 2,2-difenil-1-picrilhidrazil (DPPH) free radical scavenging method and ferric reducing antioxidant power (FRAP) assay. Ultrasonic probe-assisted extraction yielded the highest values of TPC (94.78–474.16 mg gallic acid equivalents/g extract). Regarding the antioxidant activity, vortex-assisted extraction gave the best DPPH results (IC50 1.89–16 µg/mL), while the highest FRAP results were obtained using the Ultra-Turrax® homogenizer (502.16–1188.81 μmol ascorbic acid equivalents/g extract). For each extraction method, response surface methodology was used to analyze the influence of the experimental conditions “extraction time” (t), “biomass/solvent ratio” (R), “solvent” (S, water % in water/ethanol mixture), and “pressure” (P) on TPC, DPPH, and FRAP of the F. spiralis extracts. In general, higher TPC content and higher antioxidant capacity (lower IC50 and higher FRAP) were obtained with higher R, t, and P, and lower S (higher ethanol %). The model regarding the combined effects of independent variables t, R, and S on the FRAP response values for vortex-assisted extractions best fitted the experimental data (R2 0.957), with optimal extraction conditions of t = 300 s, R = 50 g, and S = 25%.