Determination of DPPH free radical scavenging activity: application of artificial neural networks

Emodin in-situ delivery with Pluronic F-127 hydrogel for myocardial infarction treatment: Enhancing efficacy and reducing hepatotoxicity

AIMS

This study evaluates the therapeutic potential of emodin in enhancing the anti-inflammatory phenotype of macrophages, proposing a novel treatment strategy for myocardial infarction (MI). Our objective is to overcome the challenge of myocardial repair post-MI by developing an innovative in-situ myocardial drug delivery system that reduces associated hepatotoxicity.

MATERIALS AND METHODS

Through network pharmacology, it was identified that emodin primarily treats MI through anti-inflammatory actions. We investigated the influence of emodin on macrophage polarization using cellular assays and examined its therapeutic impacts and hepatotoxicity in animal models across various doses. A novel in-situ drug delivery system was devised using Pluronic F-127, a thermosensitive hydrogel, to enhance solubility and enable localized delivery to the myocardium.

KEY FINDINGS

In vitro studies confirmed that emodin effectively induces macrophage polarization toward an anti-inflammatory phenotype. In vivo analyses demonstrated a dose-dependent therapeutic effect on the myocardium, although higher doses led to significant hepatotoxicity. The innovative drug delivery system increased emodin's solubility, facilitated precise myocardial targeting, and markedly reduced systemic exposure and liver toxicity.

SIGNIFICANCE

This study introduces an advanced approach to treating MI by leveraging the natural anti-inflammatory properties of emodin combined with drug delivery technology. This strategy not only enhances the clinical feasibility of emodin for MI treatment but also represents a significant advancement in therapeutic methods. It focuses on increasing the drug concentration in the myocardium while minimizing the systemic side effects of the drug.

Novel assaying method for the accurate and rapid analysis of antioxidant total capacity based on hexachloroiridate(IV)

We introduce a novel method, namely IrRAC, for assessing total antioxidant capacity utilizing the single electron oxidant hexachloroiridate(IV). This method leverages the 488 nm absorption band of [IrCl6]2- largely reducing interferences from antioxidants and their oxidation products. [IrCl6]2- is stable 6 h in phosphate-buffered saline (PBS) ensuring consistent and reproducible absorbance readings and rendering spectrophotometric determinations under physiological neutrality. Individual assessments of 23 antioxidants reveal a linear correlation between decreasing absorbance and increasing antioxidant concentration. When the IrRAC assay was compared with several established water-based methods, strong correlations were found. Importantly, [IrCl6]2- shows a minimal oxidation of non-antioxidative substances. Moreover, IrRAC performs well with synthetic antioxidant mixtures and real samples, highlighting that the nature of antioxidants dominates the assay without much disturbance. Commercial availability of K2[IrCl6] eliminates the need of pretreatment of the oxidant. Undoubtedly, the new method confers a compelling and cost-effective alternative to the existing electron transfer-based methodologies.

Rahman N, Hashim H. Determining food safety in canned food using fuzzy logic based on sulphur dioxide, benzoic acid and sorbic acid concentration

Canned food market demand has arisen due to the higher need for instant and ready-to-eat food. Food preservatives are often added to canned and processed foods to prolong their shelf life and help to sustain the quality, taste, color, and food texture. However, excessive usage of such food preservatives can lead to various diseases and health issues including palpitations, allergies, and cancer. Therefore, food preservative detection in food samples is essential for safe consumption and health well-being. This paper proposed a fuzzy logic framework to determine the safety of food products based on the concentration of sulphur dioxide (SD), benzoic acid (BA), and sorbic acid (SA) in five different food categories as referred to the Food Acts 1983 and Food Regulations 1985 in Malaysia. The fuzzy logic framework comprises of Mamdani inference system design with 90 fuzzy rules, 15 and 5 membership functions for both the input and output parameters respectively. 50 random values and 10 lab analysis results based on the industrial samples were used to validate the developed algorithms in ensuring the safety of the food products. The membership functions generated for the three inputs (SD, BA, and SA) during the fuzzification steps are based on the maximum allowable limit from the food acts. The defuzzification of fuzzy logic gave an average output value of 0.1565, 0.1350, 0.1150, 0.1100, and 0.1550 for chicken curry with potatoes, satay sauce, sardine in tomato sauce, anchovies paste, and sardine spread accordingly. Results obtained from the fuzzy logic framework concluded that all the industrial samples are safe to be eaten and comply with the Sixth Schedule, Regulation 20 in both Acts.

Bioinspired multiscale cellulose/lignin-silver composite films with robust mechanical, antioxidant and antibacterial properties for ultraviolet shielding

Constructing a high-performance ultraviolet shielding film is an effective way for addressing the growing problem of ultraviolet radiation. However, it is still a great challenge to achieve a combination of multifunctional, excellent mechanical properties and low cost. Here, inspired by the multiscale structure of biomaterials and features of lignin, a multifunctional composite film (CNF/CMF/Lig-Ag) is constructed via a facile vacuum-filtration method by introducing micron-sized cellulose fibers (CMF) and lignin-silver nanoparticles (Lig-Ag NPs) into the cellulose nanofibers (CNF) film network. In this composite film, the microfibers interweave with nanofibers to form a multiscale three-dimensional network, which ensures satisfactory mechanical properties of the composite film. Meanwhile, the Lig-Ag NPs are employed as a multifunctional filler to enhance the composite film's antioxidant, antibacterial and ultraviolet shielding abilities. As a result, the prepared CNF/CMF/Lig-Ag composite film demonstrates excellent mechanical properties (with tensile strength of 133.8 MPa and fracture strain of 7.4 %), good biocompatibility, high thermal stability, potent antioxidant and antibacterial properties. More importantly, such composite film achieves a high ultraviolet shielding rate of 98.2 % for ultraviolet radiation A (UVA) and 99.4 % for ultraviolet radiation B (UVB), respectively. Therefore, the prepared CNF/CMF/Lig-Ag composite film shows great potential in application of ultraviolet protection.

Optimization of ultrasound-aided extraction of bioactive ingredients from Vitis vinifera seeds using RSM and ANFIS modeling with machine learning algorithm

Plant materials are a rich source of polyphenolic compounds with interesting health-beneficial effects. The present study aimed to determine the optimized condition for maximum extraction of polyphenols from grape seeds through RSM (response surface methodology), ANFIS (adaptive neuro-fuzzy inference system), and machine learning (ML) algorithm models. Effect of five independent variables and their ranges, particle size (X1: 0.5-1 mm), methanol concentration (X2: 60-70% in distilled water), ultrasound exposure time (X3: 18-28 min), temperature (X4: 35-45 °C), and ultrasound intensity (X5: 65-75 W cm-2) at five levels (- 2, - 1, 0, + 1, and + 2) concerning dependent variables, total phenolic content (y1; TPC), total flavonoid content (y2; TFC), 2, 2-diphenyl-1-picrylhydrazyl free radicals scavenging (y3; %DPPH*sc), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) free radicals scavenging (y4; %ABTS*sc) and Ferric ion reducing antioxidant potential (y5; FRAP) were selected. The optimized condition was observed at X1 = 0.155 mm, X2 = 65% methanol in water, X3 = 23 min ultrasound exposure time, X4 = 40 °C, and X5 = 70 W cm-2 ultrasound intensity. Under this situation, the optimal yields of TPC, TFC, and antioxidant scavenging potential were achieved to be 670.32 mg GAE/g, 451.45 mg RE/g, 81.23% DPPH*sc, 77.39% ABTS*sc and 71.55 μg mol (Fe(II))/g FRAP. This optimal condition yielded equal experimental and expected values. A well-fitted quadratic model was recommended. Furthermore, the validated extraction parameters were optimized and compared using the ANFIS and random forest regressor-ML algorithm. Gas chromatography-mass spectroscopy (GC-MS) and liquid chromatography-mass spectroscopy (LC-MS) analyses were performed to find the existence of the bioactive compounds in the optimized extract.

The effect of theabrownins on the amino acid composition and antioxidant properties of hen eggs

Pu-erh tea theabrownins (TBs) exert beneficial effect on egg quality and antioxidant properties of eggs, but the underlying mechanisms behind this response are unclear. In this study, we investigate the effect of TBs on egg antioxidative activity, amino acid and fatty acid profiles, and the underlying relationship between the TBs and oxidant-sensitive Nrf2 signaling pathway in laying hens. Eighty layers were fed a basal diet (control) and 400 mg/kg of TBs supplemented diet for 12 wk. TBs led to an increase in albumen height and Haugh unit (P < 0.05). The albumen lysine, valine, and tryptophan were higher in layers fed TBs, whereas yolk tryptophan, methionine, vitamin A, and α-tocopherol content were enhanced by TBs (P < 0.05). Eggs albumen and yolk showed higher total antioxidant capacity (T-AOC), reducing power (RP), and the scavenging rate of 2,2-diphenyl-1-picrylhydrazyl hydrate (DPPH), and lower MDA content than those of eggs from the control group (P < 0.05). Also, magnum Nrf2, hemeoxygenase 1 (HO-1), NAD(P)H quinone dehydrogenase 1 (NQO1), and Bcl2 expression were up-regulated by TBs, whereas magnum proapoptotic gene (Bax, caspase 3, Cyt C) were down-regulated by TBs (P < 0.05). Our findings suggest that TBs improved egg albumen quality and antioxidant activity, and the Nrf2-ARE pathway were found to be involved in this process.

Natural deep eutectic ready to use extract of astilbin: Super high in vitro bioaccessibility, α-amylase and α-glucosidase enzyme inhibition kinetics

Astilbin, a natural flavonoid, possesses multiple functionalities, while the poor bioavailability seriously restricts its application in functional food and medicine. Therefore, in this study, a natural deep eutectic solvent (NaDES) with choline chloride: lactic acid (CHCL-LAC) is selected to deliver astilbin by evaluating the bioaccessibility and antioxidant capacity during in vitro gastrointestinal digestion, and the inhibitory effect with underlying mechanism of astilbin-CHCL-LAC against α-amylase/α-glucosidase were investigated. The CHCL-LAC showed significant high astilbin bioaccessibility (84.1% bioaccessible) and DPPH and ORAC antioxidant capacity with 75.7% and 57.7% respectively after 3 h in vitro digestion, which may be attributed by hydrogen bond based supramolecule formed between astilbin and CHCL-LAC. Moreover, significant inhibitions of astilbin-CHCL-LAC on α-amylase (IC50 of 0.67 g/L) and α-glucosidase (IC50 of 0.64 g/L) were observed in mixed competitive and non-competitive manners. The dominant binding force between enzymes and astilbin were the hydrogen and hydrophobic interaction. This is the first time that the underlying mechanisms for astilbin delivered by NaDESs were revealed, suggesting that CHCL-LAC-based NaDESs are promising ready-to-use vehicles of natural inhibitors for carbohydrate-hydrolyzing enzymes.

Development of gelatin-coated nanoliposomes loaded with β-cyclodextrin/vitamin D3 inclusion complex for nutritional therapy

The aim of this study was to synthesize of β-cyclodextrin/Vitamin D₃ (βCD/VitD₃) inclusion complex and encapsulation of this complex with gelatin-coated nanoliposomes (NLPs). Fourier transform infrared spectroscopy confirmed the formation of βCD/VitD₃ inclusion complex. In the next step, different gelatin concentrations (1, 2, and 4 mg/mL) were used to surface coat the blank NLPs. The concentration of 2 mg/mL of gelatin was chosen as the optimal concentration for coating the complex-loaded NLPs by considering particle size, morphology, and zeta potential. The particle size and zeta potential of the coated complex-loaded NLPs were 117 ± 2.55 nm and 19.8 ± 1.25 mV, respectively. The images taken by transmission electron microscopy confirmed the formation of a biopolymer layer of gelatin around the NLPs' vesicles. The complex encapsulation efficiency inside the NLPs was 81.09%. The βCD/VitD₃ complex loaded NLPs and its coated form exhibited a controlled release profile in simulated gastrointestinal condition.

Apple polyphenol biotransformation using probiotics in vitro and dynamic simulated digestion by bionic rats

BACKGROUND

The present study investigated the effects of fermentation by Lactobacillus rhamnosus zrx01 (LR-zrx01), Lactobacillus acidophilus zrx02 (LA-zrx02), and Lactobacillus plantarum zrx03 (LP-zrx03), as well as dynamic simulated digestion by bionic rats, on the biotransformation and antioxidant potential of apple polyphenols. Polyphenols were determined by ultra-high-performance liquid chromatography-mass spectrometry, the dynamic simulated digestion of fermented apple pulp was determined by bionic rats, and the antibacterial and antioxidant activities were analyzed.

RESULTS

The polyphenol content of apple pulp fermented using the three strains was respectively 1.41, 1.38, and 1.36 times that of non-fermented pulp. The antibacterial activity of apple pulp improved dramatically after fermentation. Moreover, the antioxidant potential of apple pulp increased after fermentation and digestion. After dynamic simulated digestion by bionic rats, the polyphenol content in unfermented and the three fermented groups increased significantly by 1.19, 1.23, 1.20, and 1.19 times compared to that before digestion, respectively. The major polyphenols in each group with obvious changes were epicatechin, rutin, kaempferol, quercetin-3 galactoside, p-coumaric acid, and two unknown substances, 1 and 2.

CONCLUSION

Fermented and digested apple polyphenols showed better biotransformation effects and mostly existed in the form of small molecules, which was conducive to the improvement of polyphenol bioavailability and beneficial to the absorption of active substances by the human body. These findings build a foundation for the development of functional food beverages. © 2023 Society of Chemical Industry.

The Effects of the Mixed Fermentation of Honeysuckle Cereal Mixed Flour on the Dough Characteristics and Bread Quality

This study investigated the effects of the mixed solid fermentation of honeysuckle cereal mixed flour with lactic acid bacteria and yeast on dough characteristics and bread quality. Honeysuckle powder and whole wheat flour were mixed to make reconstituted cereal flour, and yeast and Lactobacillus plantarum were implanted and mixed to make dough for fermentation. The dynamic rheological properties of the dough were determined, and the properties of the reconstituted cereal flour bread were determined, including the texture characteristics and color; then, the sensory evaluation and antioxidant capacity of the bread were determined. The storage modulus (G′) and loss modulus (G″) of the dough increased gradually with the increase in the honeysuckle powder content, and the loss tangent value, tanδ (G″/G′), was less than 1.0. The loss tangent value of the dough had no significant change (p > 0.05) with the increase in honeysuckle powder content; the L* value of the bread decreased from 88.50 to 76.00, the a* value increased from −1.87 to 0.79, and the b* value decreased from 21.04 to 13.68 with the increase in the amount of honeysuckle powder. When the honeysuckle powder addition was 4%, the reconstituted cereal bread was bright yellow and gave off a hint of bean and wheat flavor and had the best taste and quality. The hardness, chewiness, and the recovery of the bread decreased when the content of the honeysuckle powder was in the range of 0~4%, but the elasticity and the antioxidant and antiaging activity of the bread increased significantly (p > 0.05). It was determined that the best content of honeysuckle powder was 4%. The mixed microbial fermentation of honeysuckle cereal mixed flour can improve the quality and enhance the nutritional value of bread.

Optimization of the processing technology of schizonepetae herba carbonisata using response surface methodology and artificial neural network and comparing the chemical profiles between raw and charred schizonepetae herba by UPLC-Q-TOF-MS

In this study, response surface methodology (RSM) and artificial neural network (ANN) were used to predict and validate the optimal processing method of Schizonepetae Herba Carbonisata (SHC). The highest overall desirability (OD) value of the total flavonoids content (TFC), total tannin content (TTC), and adsorption capacity (AC) were used as response values. The optimal processing technology processing time lasted 10 min at a processing temperature of 178 °C and the herbs/machine had a volume of 77 g/5 L. The Ultra Performance Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-TOF-MS), combined with chemometrics, was used to investigate the changes of compounds in Schizonepetae Herba (SH) before and after being charred. A total of 104 compounds were tentatively identified in SH and 83 in SHC. Fifteen differential compounds were found between by chemometrics SH and SHC. Altogether, our findings can provide a practical approach to the processing technology of carbonizing by stir-frying SH.

Comparative study on the extraction efficiency, characterization, and bioactivities of Bletilla striata polysaccharides using response surface methodology (RSM) and genetic algorithm-artificial neural network (GA-ANN)

This research established the optimal conditions for alkali-assisted extraction (AAE) of bioactive polysaccharides from Bletilla striata integrated with response surface methodology (RSM) and the genetic algorithm-artificial neural networks (GA-ANN). In comparison with RSM, the ANN model showed a relatively higher determination coefficient in the global output values (RSM: ANN = 0.9270: 0.9742) performing more satisfactorily in the validation. Under the optimum conditions (52 °C; 167 min, and 0.01 mol/L NaOH), the extraction yields, IC₅₀ of ABTS, and FRAP value were 29.53 ± 0.97 %, 3.41 mg/mL, and 39.11 μmol Fe²⁺/g, respectively. The results indicated that BSPs-A was mainly composed of glucose and mannose with small amounts of arabinose, galactose, and galacturonic acid, while possessed a molecular weight of about 305.94 kDa (Mw). The structural characterization of BSPs-A was initially characterized by FT-IR, SEM, and Congo red tests, which indicated that BSPs-A possessed a triple helix conformation of typical Bletilla striata polysaccharides. In addition, BSPs-A exhibited excellent antioxidant activity, which was further confirmed by a series of in vitro antioxidant activity assays including DPPH, ABTS, FRAP, and ORAC. After incubation in the BSA-glucose system for 15 days, BSPs-A showed inhibition of the advanced glycation end products (AGEs) formation for the first time.

Extraction of Ursolic Acid from Apple Peel with Hydrophobic Deep Eutectic Solvents: Comparison between Response Surface Methodology and Artificial Neural Networks

Extracting ursolic acid (UA) from plant resources using organic solvents is incompatible with food applications. To address this, in this study, 15 edible hydrophobic deep eutectic solvents (HDESs) were prepared to extract UA from apple peel, the extraction conditions were optimized, and the optimization strategies were compared. It was found that the solubility of UA in the HDESs can be 9 times higher than the traditional solvent such as ethanol. The response surface optimization concluded that temperature had the greatest effect on the extraction and the optimized test conditions obtained as follows: temperature of 49 °C, time of 32 min, solid-liquid ratio of 1:16.5 g/mL, respectively. Comparing the response surface methodology (RSM) and artificial neural networks (ANN), it was concluded that ANN has more accurate prediction ability than RSM. Overall, the HDESs are more effective and environmentally friendly than conventional organic solvents to extract UA. The results of this study will facilitate the further exploration of HDES in various food and pharmaceutical applications.

Metabolite Profiling of Microwave-Assisted Sargassum fusiforme Extracts with Improved Antioxidant Activity Using Hybrid Response Surface Methodology and Artificial Neural Networking-Genetic Algorithm

Sargassum fusiforme (SF) is a popular edible brown macroalga found in Korea, Japan, and China and is known for its health-promoting properties. In this study, we used two sophisticated models to obtain optimized conditions for high antioxidant activity and metabolite profiling using high-resolution mass spectrometry. A four-factor central composite design was used to optimize the microwave-assisted extraction and achieve the maximum antioxidant activities of DPPH (Y1: 28.01 % inhibition), ABTS (Y2: 36.07 % inhibition), TPC (Y3: 43.65 mg GAE/g), and TFC (Y4: 17.67 mg CAE/g), which were achieved under the optimized extraction conditions of X1: 47.67 %, X2: 2.96 min, X3: 139.54 °C, and X4: 600.00 W. Moreover, over 79 secondary metabolites were tentatively identified, of which 12 compounds were reported for the first time in SF, including five phenolic (isopropyl 3-(3,4-dihydroxyphenyl)-2-hydroxypropanoate, 3,4-dihydroxyphenylglycol, scopoletin, caffeic acid 4-sulfate, and cinnamoyl glucose), two flavonoids (4',7-dihydroxyisoflavone and naringenin), three phlorotannins (diphlorethohydroxycarmalol, dibenzodioxin-1,3,6,8-tetraol, and fucophlorethol), and two other compounds (dihydroxyphenylalanine and 5-hydroxybenzofuran-2(3H)-one) being identified for the first time in optimized SF extract. These compounds may also be involved in improving the antioxidant potential of the extract. Therefore, optimized models can provide better estimates and predictive capabilities that would assist in finding new bioactive compounds with improved biological activities that can be further applied at a commercial level.

The Impact of Atmospheric Plasma/UV Laser Treatment on the Chemical and Physical Properties of Cotton and Polyester Fabrics

Atmospheric plasma treatment can modify fabric surfaces without affecting their bulk properties. One recently developed, novel variant combines both plasma and UV laser energy sources as a means of energising fibre surfaces. Using this system, the two most commonly used fibres, cotton and polyester, have been studied to assess how respective fabric surfaces were influenced by plasma power dosage, atmosphere composition and the effects of the presence or absence of UV laser (308 nm XeCl) energy. Plasma/UV exposures caused physical and chemical changes on both fabric surfaces, which were characterised using a number of techniques including scanning electron microscopy (SEM), radical scavenging (using 2,2-diphenyl-1-picrylhydrazyl (DPPH)), thermal analysis (TGA/DTG, DSC and DMA), electron paramagnetic resonance (EPR) and X-ray photoelectron spectroscopy (XPS). Other properties studied included wettability and dye uptake. Intermediate radical formation, influenced by plasma power and presence or absence of UV, was key in determining surface changes, especially in the presence of low concentrations of oxygen or carbon dioxide (20%) mixed with either nitrogen or argon. Increased dyeability with methylene blue indicated the formation of carboxyl groups in both exposed cotton and polyester fabrics. In the case of polyester, thermal analysis suggested increased cross-linking had occurred under all conditions.

Isolation and Characterization of Flavonoids from Fermented Dandelion (Taraxacum mongolicum Hand.-Mazz.), and Assessment of Its Antioxidant Actions In Vitro and In Vivo

Flavonoids are famous for their diverse sources, strong biological activity, and low toxicity and could be used as a natural antioxidant in animal husbandry. In this study, the purification process and antioxidant activity of flavonoids from fermented dandelion were investigated. The adsorption and desorption characterizations of AB-8 macroporous resin for flavonoids from fermented dandelion (FD) were determined and purification parameters were optimized. Qualitative analysis using UPLC-MS/MS analysis was explored to identify the components of the purified flavonoids of FD (PFDF). The antioxidant activity of PFDF in vitro and in vivo was analyzed. The optimum purification parameters were as follows: a sample concentration of 2 mg/mL, 120 mL of the sample volume, a pH of 2.0, and eluted with 90 mL of 70% ethanol (pH 5). After purification, the concentration of the flavonoids in PFDF was 356.08 mg/mL. By comparison with reference standards or the literature data, 135 kinds of flavonoids in PFDF were identified. Furthermore, PFDF had a strong reducing power and scavenging ability against 8-hydroxy radical and DPPH radical. PFDF can effectively reduce the oxidative stress of zebrafish embryos and IPCE-J2 cells by modulating antioxidant enzyme activities. In summary, the purified flavonoids from fermented dandelion have good antioxidant activity and display superior potential as a natural antioxidant in animal husbandry.

Artificial Neural Networks for Predicting Food Antiradical Potential

Using an artificial neural network (ANN), the values of the antiradical potential of 1315 items of food and agricultural raw materials were calculated. We used an ANN with the structure of a “multilayer perceptron” (MLP) and with the hyberbolic tangent (Tanh) as an activation function. Values reported in the United States Food and Nutrient Database for Dietary Studies (FNDDS) were taken as input to the analysis. When training the ANN, 60 parameters were used, such as the content of plastic substances, food calories, the amount of mineral components, vitamins, the composition of fatty acids and additional substances presented in this database. The analysis revealed correlations, namely, a direct relationship between the value of the antiradical potential (ARP) of food and the concentration of dietary fiber (r = 0.539) and a negative correlation between the value of ARP and the total calorie content of food (r = −0.432) at a significance level of p < 0.001 for both values. The average ARP value for 10 product groups within the 95% CI (confidence interval) was ≈23–28 equivalents (in terms of ascorbic acid) per 1 g of dry matter. The study also evaluated the range of average values of the daily recommended intake of food components (according to Food and Agriculture Organization—FAO, World Health Organization—WHO, Russia and the USA), which within the 95% CI, amounted to 23.41–28.98 equivalents per 1 g of dry weight. Based on the results of the study, it was found that the predicted ARP values depend not only on the type of raw materials and the method of their processing, but also on a number of other environmental and technological factors that make it difficult to obtain accurate values.

Optimization of the extraction conditions of Nypa fruticans Wurmb. using response surface methodology and artificial neural network

In this study, we conducted response surface methodology (RSM) and artificial neural network (ANN) to predict and estimate the optimized extraction condition of Nypa fruticans Wurmb. (NF). The effect of ethanol concentration (X₁; 0-100%), extraction time (X₂; 6-24 h), and extraction temperature (X₃; 40-60 °C) on the antioxidant potential was confirmed. The optimal conditions (57.6% ethanol, 19.0 h extraction time, and 51.3 °C extraction temperature) of 2,2-diphenyl-1-1picrylhydrazyl (DPPH) scavenging activity, cupric reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP), total phenolic content (TPC), and total flavonoid contents (TFC) resulted in a maximum value of 62.5%, 41.95 and 48.39 µM, 143.6 mg GAE/g, and 166.8 CAE/g, respectively. High-resolution mass spectroscopic technique was performed to profile phenolic and flavonoid compounds. Upon analyzing, total 48 compounds were identified in NF. Altogether, our findings can provide a practical approach for utilizing NF in various bioindustries.

DES Based Efficient Extraction Method for Bioactive Coumarins from Angelica dahurica (Hoffm.) Benth. & Hook.f. ex Franch. & Sav

In this study, a simple and environmentally friendly method was developed for the extraction of seven active coumarins from Angelica dahurica (Hoffm.) Benth. & Hook.f. ex Franch. & Sav.(A. dahurica) based on deep eutectic solvents (DESs). Among the 16 kinds of DES based on choline chloride, the DES system with the molar ratio of choline chloride, citric acid, and water as 1:1:2 had the best extraction effect. Ultrasonic-assisted response surface methodology (RSM) was used to investigate the optimal extraction scheme. The results showed that the optimal extraction conditions were a liquid–solid ratio of 10:1 (mL/g), an extraction time of 50 min, an extraction temperature of 59.85 °C, and a moisture content of 49.28%. Under these conditions, the extraction yield reached 1.18%. In addition, scanning electron microscopy (SEM) was used to observe the degree of powder fragmentation before and after extraction with different solvents. The cells of A. dahurica medicinal materials obtained by DES ultrasonic-assisted treatment were the most seriously broken, indicating that DES had the highest efficiency in the treatment of A. dahurica. The 1,1-diphenyl-2-picrylhydrazyl (DPPH) DPPH radical scavenging model was used to evaluate the biological activity of DES extract. The results showed that DES extract had better scavenging ability of DPPH free radical. Therefore, DES is a green solvent suitable for extracting coumarin compounds of A. dahurica, with great potential to replace organic solvents.

Physicochemical parameters combined flash GC e-nose and artificial neural network for quality and volatile characterization of vinegar with different brewing techniques

Vinegar is a kind of traditional fermented food, there are significant variances in quality and flavor due to differences in raw ingredients and processes. The quality assessment and flavor characteristics of 69 vinegar samples with 5 brewing processes were analyzed by physicochemical parameters combined with flash gas chromatography (GC) e-nose. The evaluation system of quality and the detection method of flavor profile were established. 17 volatile flavor compounds and potential flavor differential compounds of each brewing process were identified. The artificial neural network (ANN) analysis model was established based on the physicochemical parameters and the analysis of flash GC e-nose. Although the physicochemical parameters were more intuitive in quality evaluating, the flash GC e-nose could better reflect the flavor characteristics of vinegar samples and had better fitting, prediction and discrimination ability, the correct rates of training and prediction of flash GC e-nose trained ANN model were 98.6% and 96.7%, respectively.

Sweet-flavored peptides with biological activities from mulberry seed protein treated by multifrequency countercurrent ultrasonic technology

To increase the reuse of food residues, multifrequency countercurrent ultrasonic treatment was used to enhance the extraction yield of defatted mulberry seed protein (DMSP), and sweet-flavored peptides from DMSP hydrolysates (DMSPHs) were obtained for the first time. Here, the DMSP yield was increased by 16.2% (p < 0.05) while the power density was halved compared with single-frequency ultrasonic treatment. According to Fick's second law, a molecular diffusion dynamics model was developed to be suitable for predicting the pretreatment conditions (R² = 0.9785). After that, the sweet-flavored peptides were purified and the main amino acid sequences were identified, i.e., FEGGSIE, KDFPEAHSQAT, and GSQPAEGAK. Moreover, the antioxidant activities of DMSPHs prepared with tri-frequency treatment was higher than 60%. The DMSPHs retarded the growth of HepG2 cells in vitro, increased the necrotic quadrant (Q1-UL), and extended the S phase. Therefore, the sweet-flavored peptides prepared from DMSPHs using the multifrequency-ultrasonic treatment have significant biological activities.

Potential antiviral agents of Rosmarinus officinalis extract against herpes viruses 1 and 2

Herpes simplex viruses 1 and 2 (HSV-1 and HSV-2) belong to the herpesviridae family and cause neurological disorders by infecting the nervous system. The present study aimed to investigate the effects of Rosmarinus officinalis L. (rosemary) extract against HSV-1 and HSV-2 in vitro. The antioxidant activity of this extract was investigated by superoxide anion and 2,2-diphenyl-1-picrylhydrazyl (DPPH) free-radical assays. Rosemary extract was evaluated by an HSV-1 antiviral assay, in which viral replication in Vero cells was determined and quantified using a cytopathic effect assay. The present study showed that rosemary extract at 30 µg/ml caused 55% inhibition of HSV-1 plaques, whereas 40 µg/ml rosemary extract caused 65% inhibition of HSV-2 plaques. The extracts completely inhibited HSV-1 and HSV-2 plaque formation at 50 µg/ml. Scavenging activity of the superoxide anion radical was observed at 65.74 mg/ml, whereas 50% scavenging activity of the DPPH radical was observed at 67.34 mg/ml. These data suggest that rosemary extract may be suitable as a topical prophylactic or therapeutic agent for herpes viral infections. However, further research is required to elucidate the plant’s active constituents, which may be useful in drug development.

Common Trends and Differences in Antioxidant Activity Analysis of Phenolic Substances Using Single Electron Transfer Based Assays

Numerous assays were developed to measure the antioxidant activity, but each has limitations and the results obtained by different methods are not always comparable. Popular examples are the DPPH and ABTS assay. Our aim was to study similarities and differences of these two assay regarding the measured antioxidant potentials of 24 phenolic compounds using the same measurement and evaluation methods. This should allow conclusions to be drawn as to whether one of the assays is more suitable for measuring specific subgroups like phenolic acids, flavonols, flavanones, dihydrochalcones or flavanols. The assays showed common trends for the mean values of most of the subgroups. Some dihydrochalcones and flavanones did not react with the DPPH radical in contrast to the ABTS radical, leading to significant differences. Therefore, to determine the antioxidant potential of dihydrochalcone or flavanone-rich extracts, the ABTS assay should be preferred. We found that the results of the flavonoids in the DPPH assay were dependent on the Bors criteria, whereas the structure–activity relationship in the ABTS assay was not clear. For the phenolic acids, the results in the ABTS assay were only high for pyrogallol structures, while the DPPH assay was mainly determined by the number of OH groups.

Free radical scavenging activity of newly designed sesamol derivatives

Recently proposed derivatives of sesamol as better oxidants than the parent molecule are predicted to react faster, with several orders larger rate constants than sesamol itself.

Comprehensive study on applications of artificial neural network in food process modeling

Artificial neural network (ANN) is a simplified model of the biological nervous system consisting of nerve cells or neurons. The application of ANN to food process engineering is relatively novel. ANN had been employed in diverse applications like food safety and quality analyses, food image analysis, and modeling of various thermal and non-thermal food-processing operations. ANN has the ability to map nonlinear relationships without any prior knowledge and predicts responses even with incomplete information. Every neural network possesses data in the form of connection weights interconnecting lines between the input to hidden layer neurons and weights of hidden to output layer neurons, which has a significant role in predicting the output data. The applications of ANN in different unit operations in food processing were described that includes theoretical developments using intelligent characteristics for adaptability, automatic learning, classification, and prediction. The parallel architecture of ANN resulted in a fast response and low computational time making it suitable for application in real-time systems of different food process operations. The predicted responses obtained by the ANN model exhibited high accuracy due to lower relative deviation and root mean squared error and higher correlation coefficient. This paper presented the various applications of ANN for modeling nonlinear food engineering problems. The application of ANN in the modeling of the processes such as extraction, extrusion, drying, filtration, canning, fermentation, baking, dairy processing, and quality evaluation was reviewed.HIGHLIGHTS1. This paper discusses application of ANN in different emerging trends in food process.2. Application of ANN to develop non-linear multivariate modeling is illustrated.3. ANNs have been shown to be useful tool for prediction of outcomes with high accuracy.4. ANN resulted in fast response making it suitable for application in real time systems.

Polysaccharides of Scrophularia ningpoensis Hemsl.: Extraction, Antioxidant, and Anti-Inflammatory Evaluation

The roots of Scrophularia ningpoensis Hemsl. are a famous traditional Chinese medicinal herb and are also used as health food. However, information about polysaccharides from S. ningpoensis (SNPS) is very limited. We applied the ultrasonic-assisted extraction (UAE) process to extract SNPS. The UAE conditions were optimized using single-factor experiments and response surface analysis. Under the optimized conditions of ultrasonic power of 550 W, extraction time of 26 min, and extraction temperature at 50°C, the highest yield of 13.47% ± 1.63% was obtained, which was in accordance with the predicted value of 13.71%. In comparison with traditional hot water extraction, the optimized UAE method significantly increased the extraction yield with lower extraction temperature and shorter extraction time. Furthermore, the in vitro antioxidant evaluation showed that EC50 values of SNPS were 2.43 ± 0.21, 4.40 ± 0.35, and 0.56 ± 0.062 mg/mL for 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) radical, hydroxyl free radical, and 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging assay, respectively. The anti-inflammatory potential of SNPS was detected in lipopolysaccharide (LPS) induced ICR mice. Real-time reverse transcription-polymerase chain reaction and enzyme-linked immunosorbent assay showed that SNPS significantly improved LPS-stimulated inflammatory response by decreasing mRNA and protein expression of interleukin (IL)-6 and tumour necrosis factor (TNF)-α in a dose-dependent manner. In conclusion, the extraction process of SNPS established in this study is reliable, and SNPS possesses potential antioxidant and anti-inflammatory activities, which will provide a theoretical basis for guiding the clinical application of S. ningpoensis.

Ultrasound-assisted extraction of phytocompounds from dragon fruit peel: Optimization, kinetics and thermodynamic studies

Ultrasound-assisted extraction method (UAE) was applied to recover phytocompounds from dragon fruit peel and the process was modelled and optimized using the combination of artificial neural network (ANN) and genetic algorithm (GA). The influence of ultrasonic temperature (30-70 °C), solvent to solid ratio (10:1-30:1 mL/g), solvent concentration (30-60%), and ultrasonic treatment time (5-25 min) on total polyphenolic content (Z_T), antioxidant activity (Z_D) and betacyanin content (Z_B) was investigated. The ANN model successfully fitted to the experimental data and the output of ANN model was applied for genetic algorithm optimization. The optimal UAE conditions were obtained at ultrasonic temperature of 60 °C, solvent to solid ratio 25:1 mL/g, solvent concentration 60%, and ultrasonic treatment time of 20 min. The extraction kinetics and thermodynamic study for phytochemical compounds extracted from dragon fruit peel using UAE process was carried out at different combinations of temperature and time of extraction. The effective diffusion coefficient for total polyphenol content, antioxidant activity and betacyanin content were ranged from 2.99×10^-11to4.84×10^-11m²/s, 1.89×10^-11to4.51×10^-11m²/s and 2.55×10^-11to5.40×10^-11m²/s respectively and the corresponding mass transfer coefficient were varied between 2.00×10^-06-2.81×10^-06m/s, 1.53×10^-06-2.66×10^-06m/s and 1.81×10^-06-3.05×10^-06m/s respectively. The obtained information on effective diffusivity and mass transfer coefficient during extraction would allow the prediction of extraction rate and for estimation of operation conditions for industrial implementation.

Effect of inlet temperature on the physicochemical properties of spray-dried seed-watermelon seed protein powder

Here, we studied the effects of inlet temperature on the physicochemical properties of the hydrolyzed protein (seed-watermelon seed hydrolyzed protein [SWSP]) powder in seed-watermelon seeds. The inlet temperature of the study was in the range of 150 to 180 °C, and the remaining experimental parameters remained constant, that is, the feed flow rate was 0.2 L/hr, the concentration of maltodextrin was 30%, and the outlet temperature was 80 °C. We studied the water activity and moisture content, bulk density, flowability (Carr index and Hausner ratio), angle of repose, solubility, color, hygroscopicity, powder morphology, particle size, crystallinity, and odor of the sample. Inlet temperature of 170 to 180 °C reduced the moisture content and increased the particle size. It was found that the value of measured water activity was less than 0.5, which helped in maintaining stability of the sample. Powders produced at the temperatures showed smoother particle surfaces, whereas higher inlet temperature showed spherical particles with some shrinkage as analyzed by scanning electron microscope. The inlet temperature affected the color of the sample, thus at high temperature, the sample had a brighter color. The sample was approximately 18% crystalline. At a preparation temperature of 160 °C, the sample showed significant antioxidant activity (P < 0.05).

Optimized parameters for the preparation of silk fibroin drug-loaded microspheres based on the response surface method and a genetic algorithm-backpropagation neural network model

Using silk fibroin as the base material, the drug-loaded microspheres are prepared by an emulsification method. In order to determine the drug-loading and drug-release performance parameters of the microspheres, the central composite design method is used to design and investigate the effects of the parameters of the microsphere preparation process, such as the oil-water ratio, stirring temperature, and stirring rate, on the microsphere particle size, drug-loading rate, and drug release rate. The "overall desirability" is taken as a comprehensive evaluation index, and the response surface method (RSM) and genetic algorithm-backpropagation (GA-BP) neural network GA-BP model are used to predict and evaluate the parameters of the drug-loaded microsphere preparation process. The root-mean-square error values obtained from the RSM and BP-GA model experiments are 0.000325 and 0.00022, respectively. The results show that the BP-GA model has better prediction accuracy and optimization ability than the RSM. The optimal microsphere preparation process conditions were determined to be as follows: a water-oil ratio of 10:1, at a temperature of 45°C with stirring at a speed of 400 rpm, the particle size of the microspheres is 1.392 μm, the drug-loading rate is 3.218%, and the drug release rate is 51.991%. The results of this study indicate that this approach is an effective method for the optimization of the parameters of the drug-loaded microsphere preparation process.

Structural characterization and antioxidant potential of a novel exopolysaccharide produced by Bacillus velezensis SN-1 from spontaneously fermented Da-Jiang

The aim of this study was to characterize the exopolysaccharide (EPS) produced by Bacillus velezensis SN-1 (B. velezensis SN-1) (EPS-SN-1), which was isolated from the fermented Da jiang. The microbe made crude exopolysaccharides EPS-SN-1 was produced throughout the bacterial growth period, and the highest yield (2.7 g/L) was obtained with sucrose as the carbon source. As per high performance liquid chromatography (HPLC), EPS-SN-1 is a heteropolysaccharide consisting of glucose, mannose and fructose, with a high molecular weight of 2.21 × 10⁵ Da. FTIR spectra further indicated the presence of hydroxyl and carbonyl groups, and NMR analysis confirmed both α- and β-glycosidic bonds. Furthermore, differential scanning calorimetry (DSC) showed that EPS-SN-1 has high thermal stability with fusion point of 270.7 °C. Finally, EPS-SN-1 demonstrated strong antioxidant capacity via its ability to scavenge hydroxyl radical (^•OH), 1,1-diphenyl-2-picrylhydrazyl (DPPH^•) radical, ABTS radical (ABTS^•+) and oxygen radical (O₂^-•). Taken together, EPS-SN-1 is a promising natural antioxidant and probiotic with potential applications in the food industry.

Seasonal and Diurnal Variation in Leaf Phenolics of Three Medicinal Mediterranean Wild Species: What Is the Best Harvesting Moment to Obtain the Richest and the Most Antioxidant Extracts?

Mediterranean plants biosynthesize high amounts of polyphenols, which are important health-promoting compounds. Leaf polyphenolic composition changes according to environmental conditions. Therefore, it is crucial to know the temporal variation in their production. This study aimed to: i) evaluate the monthly and daily changes in polyphenols of Phyllirea latifolia, Cistus incanus, and Pistacia lentiscus to identify their best harvesting moment, ii) verify the possible correlations between phenolic production and temperature and irradiation, iii) evaluate their antioxidant capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and hydroxyl radical (OH)scavenging assays. The extracts of leaves harvested at 8:00, 13:00 and 18:00, in May, July, and October for two years were analysed by HPLC-DAD. Both "month" and "time of the day" affected the polyphenolic content in all species. July at 13:00 was the best harvesting moment for all polyphenolic classes of P. latifolia and only for some classes of C. incanus and P. lentiscus. Environmental parameters positively correlated with the polyphenols of C. incanus and P. latifolia, while the antioxidant capacity only varied in this last species, reaching the highest value in July. Results of the study allow to determine the balsamic time for each species. Moreover, the relationship between polyphenols and environmental data can be useful for the cultivation of these plants under controlled conditions.

An aqueous miscible organic (AMO) process for layered double hydroxides (LDHs) for the enhanced properties of polypropylene/LDH composites

AMO D-LDH (h) antioxidants are fabricated using an acetone solvent, and the modified time is optimized based on the anti-aging performance of PP/D-LDH (h).

Response surface methodology and artificial neural network approach for the optimization of ultrasound-assisted extraction of polyphenols from garlic

This paper aimed to establish the optimal conditions for ultrasound-assisted extraction of polyphenols from domestic garlic (Allium sativum L.) using response surface methodology (RSM) and artificial neural network (ANN) approach. A 4-factor-3-level central composite design was used to optimize ultrasound-assisted extraction (UAE) to obtain a maximum yield of target responses. Maximum values of the two output parameters: 19.498 mg GAE/g fresh weight of sample total phenolic content and 1.422 mg RUT/g fresh weight of sample total flavonoid content were obtained under optimum extraction conditions: 13.50 min X₁, 59.00 °C X₂, 71.00% X₃ and 20.00 mL/g X₄. Root mean square error for training, validation, and testing were 0.0209, 3.6819 and 1.8341, respectively. The correlation coefficient between experimentally obtained total phenolic content and total flavonoid content and values predicted by ANN were 0.9998 for training, 0.9733 for validation, and 0.9821 for testing, indicating the good predictive ability of the model. The ANN model had a higher prediction efficiency than the RSM model. Hence, RSM can demonstrate the interaction effects of basic inherent UAE parameters on target responses, whereas ANN can reliably model the UAE process with better predictive and estimation capabilities.

Leonurine ameliorates D-galactose-induced aging in mice through activation of the Nrf2 signalling pathway

Aging is a complex physiological phenomenon associated with oxidative stress damage. The objective of this study was to investigate the potential effects of leonurine on D-galactose-induced aging in mice and its possible mechanisms. In this study, we first tested the antioxidant activity of leonurine in vitro. A subcutaneous injection of D-galactose in mice for 8 weeks was used to establish the aging model to evaluate the protective effects of leonurine. The results showed that treatment with 150 mg·kg^-1 leonurine could improve the mental condition, organic index, and behavioural impairment; significantly increase the activities of antioxidative enzymes including SOD, CAT, and T-AOC; and ameliorate the advanced glycation end product (AGE) level and histopathological injury. Furthermore, the Western blotting data revealed that leonurine supplementation noticeably modulated the suppression of the Nrf2 pathway and upregulated the downstream expression of HO-1 and NOQ1 in aging mice. Additionally, leonurine treatment activated Nrf2 nuclear translocation in both aging mice and normal young mice, and the expression levels of Nrf2 in normal young mice was higher than those in naturally aging mice. In conclusion, our findings suggest that leonurine is a promising agent for attenuating the aging process, and the underlying molecular mechanisms depend on activating the Nrf2 pathway.

Quantitative fingerprint and quality control analysis of Compound Liquorice Tablet combined with antioxidant activities and chemometrics methods

BACKGROUND

Herbal medicine (HM), as a complex system, is difficult to investigate their quality consistency effectively by chromatographic fingerprinting obtained in a single detection method. Moreover, active compound discovery affords no information about pharmacological activity until late in the discovery process, and the interaction between HMs in vitro is not yet clear, which requires sufficient practice to prove their effectiveness.

PURPOSE

Therefore, the purpose of this study was to improve the quality control methods of Compound Liquorice Tablet (CLT) using multi-wavelength fusion fingerprinting, explore the possible antioxidant components and assess the interaction between herbs combined with bioactivity evaluation.

METHODS AND DESIGN

Once the theoretical standard preparation obtained in combination of multi-wavelength fusion fingerprinting and hierarchical clustering analysis, averagely linear quantified fingerprint method could rapidly calculate the composition similarities and efficiently quantify the multiple components of CLTs without any chemical standard. Furthermore, the fingerprint-efficacy relationship was investigated by integrating high performance liquid chromatography fingerprints with antioxidant activity assessment using the partial least squares model, which was capable of directly discovering the bioactive ingredients. Hereafter, combination index value was introduced to evaluate the correlation between the two antioxidant herbs in CLT formula.

RESULTS

The results showed that CLT samples were effectively identified and quantified, and their quality was accurately distinguished. By analyzing the antioxidant evaluation results, it was found that CLT had strong antioxidant activity, and through the study on PLS model and antioxidant activity assay of individual compounds, it was found that the order of chemical constituents responsible for antioxidant activity in CLT was as follows: flavonoids > saponins > alkaloids. Finally, it was determined that the CI value of GE-PPCE was in the range of 1.20-1.61, indicating that the interaction of the GE-PPCE pair was a slight antagonism.

CONCLUSION

Thus, this study provided a preferred way for monitoring the quality consistency of HM, exploring possible bioactive components of HMs and assessing the interaction between herbs.

Comparative study on the physicochemical properties and bioactivities of polysaccharide fractions extracted from Fructus Mori at different temperatures

This study examined the effects of different extraction temperatures (30 °C and 90 °C) on the physicochemical properties and bioactivities of polysaccharides (MFPs-30-60, MFPs-30-80, MFPs-90-40, MFPs-90-60 and MFPs-90-80) extracted at same ethanol gradation (40, 60 and 80%).

QSAR Study on Antioxidant Tripeptides and the Antioxidant Activity of the Designed Tripeptides in Free Radical Systems

In this study, quantitative structure-activity relationship (QSAR) models were determined based on 91 antioxidant tripeptides. We firstly adopted the stepwise regression (SWR) method for selecting key variables without autocorrelation and then utilized multiple linear regression (MLR), support vector machine (SVM), random forest (RF), and partial least square regression (PLS) to develop predictive QSAR models based on the screened variables. The results demonstrated that all the established models have good reliability (R²_train > 0.86, Q²_train > 0.70) and relatively good predictability (R²_test > 0.88). The contribution of amino acid residues was calculated from the stepwise regression combined with multiple linear regression (SWR-MLR) method model that shows Trp, Tyr, or Cys at C-terminus is favorable for antioxidant activity of tripeptides. Nineteen antioxidant tripeptides were designed based on SWR-MLR models, and the antioxidant activity of these tripeptides were evaluated using three antioxidant assays in free radical systems (1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging capacity, trolox equivalent antioxidant capacity assay, and the ferric reducing antioxidant power assay). The experimental antioxidant activities of these tripeptides were higher than the calculated/predicted activity values of the QSAR models. The QSAR models established can be used to identify and screen novel antioxidant tripeptides with high activity.