Phytochemical compounds with promising biological activities from Ascophyllum nodosum extracts using microwave-assisted extraction.

Phytochemical-rich antioxidant extracts were obtained from Ascophyllum nodosum (AN) using microwave-assisted extraction (MAE). Critical extraction factors such as time, pressure, and ethanol concentration were optimized by response surface methodology with a circumscribed central composite design. Under the optimal MAE conditions (3 min, 10.4 bar, 46.8 % ethanol), the maximum recovery of phytochemical compounds (polyphenols and fucoxanthin) with improved antioxidant activity from AN was obtained. In addition, the optimized AN extract showed significant biological activities as it was able to scavenge reactive oxygen and nitrogen species, inhibit central nervous system-related enzymes, and exhibit cytotoxic activity against different cancer cell lines. In addition, the optimized AN extract showed antimicrobial, and anti-quorum sensing activities, indicating that this extract could offer direct and indirect protection against infection by pathogenic microorganisms. This work demonstrated that the sustainably obtained AN extract could be an emerging, non-toxic, and natural ingredient with potential to be included in different applications.

Algal nutraceuticals: A perspective on metabolic diversity, current food applications, and prospects in the field of metabolomics.

The current consumers' demand for food naturalness is urging the search for new functional foods of natural origin with enhanced health-promoting properties. In this sense, algae constitute an underexplored biological source of nutraceuticals that can be used to fortify food products. Both marine macroalgae (or seaweeds) and microalgae exhibit a myriad of chemical constituents with associated features as a result of their primary and secondary metabolism. Thus, primary metabolites, especially polysaccharides and phycobiliproteins, present interesting properties to improve the rheological and nutritional properties of food matrices, whereas secondary metabolites, such as polyphenols and xanthophylls, may provide interesting bioactivities, including antioxidant or cytotoxic effects. Due to the interest in algae as a source of nutraceuticals by the food and related industries, novel strategies should be undertaken to add value to their derived functional components. As a result, metabolomics is considered a high throughput technology to get insight into the full metabolic profile of biological samples, and it opens a wide perspective in the study of algae metabolism, whose knowledge is still little explored. This review focuses on algae metabolism and its applications in the food industry, paying attention to the promising metabolomic approaches to be developed aiming at the functional characterization of these organisms.

Phenolic acids, lignans, and low-molecular-weight phenolics exhibit the highest in vitro cellular bioavailability in different digested and faecal-fermented phenolics-rich plant extracts.

Polyphenols are multifaceted bioactive compounds, but little is known about their real impact on human health after consumption. In this work, the phenolic profiling of quebracho, yellow maize, and violet rice extracts was comprehensively investigated, together with the impact of in vitro digestion and colonic fermentation on the bioaccessibility and bioavailability of these phytochemicals. The different matrices showed distinct profiles, potentially influencing in vitro starch digestion under cooking conditions. Furthermore, after the extracts underwent in vitro gastrointestinal digestion and faecal fermentation, phenolics exhibited a differential bioaccessibility trend at every digestion level, with matrix-dependent behaviour. The bioavailability results suggest that polyphenols are metabolised during colonic fermentation, mainly into tyrosols, phenolic acids, and lignans, which are partially absorbed by Caco-2 cells. By combining metabolomics with in vitro cellular methods, this research provides new insights into the fate of these phytochemicals in the gut, yielding comprehensive data on their consumption in food matrices.

Bioactive compounds, health benefits, and industrial applications of Tartary buckwheat (Fagopyrum tataricum).

Tartary buckwheat belongs to the family Polygonaceae, which is a traditionally edible and medicinal plant. Due to its various bioactive compounds, the consumption of Tartary buckwheat is correlated to a wide range of health benefits, and increasing attention has been paid to its potential as a functional food. This review summarizes the main bioactive compounds and important bioactivities and health benefits of Tartary buckwheat, emphasizing its protective effects on metabolic diseases and relevant molecular mechanisms. Tartary buckwheat contains a wide range of bioactive compounds, such as flavonoids, phenolic acids, triterpenoids, phenylpropanoid glycosides, bioactive polysaccharides, and bioactive proteins and peptides, as well as D-chiro-inositol and its derivatives. Consumption of Tartary buckwheat and Tartary buckwheat-enriched products is linked to multiple health benefits, e.g., antioxidant, anti-inflammatory, antihyperlipidemic, anticancer, antidiabetic, antiobesity, antihypertensive, and hepatoprotective activities. Especially, clinical studies indicate that Tartary buckwheat exhibits remarkable antidiabetic activities. Various tartary buckwheat -based foods presenting major health benefits as fat and blood glucose-lowering agents have been commercialized. Additionally, to address the safety concerns, i.e., allergic reactions, heavy metal and mycotoxin contaminations, the quality control standards for Tartary buckwheat and its products should be drafted and completed in the future.

Neurofuzzy logic predicts a fine-tuning metabolic reprogramming on elicited Bryophyllum PCSCs guided by salicylic acid.

Novel approaches to the characterization of medicinal plants as biofactories have lately increased in the field of biotechnology. In this work, a multifaceted approach based on plant tissue culture, metabolomics, and machine learning was applied to decipher and further characterize the biosynthesis of phenolic compounds by eliciting cell suspension cultures from medicinal plants belonging to the Bryophyllum subgenus. The application of untargeted metabolomics provided a total of 460 phenolic compounds. The biosynthesis of 164 of them was significantly modulated by elicitation. The application of neurofuzzy logic as a machine learning tool allowed for deciphering the critical factors involved in the response to elicitation, predicting their influence and interactions on plant cell growth and the biosynthesis of several polyphenols subfamilies. The results indicate that salicylic acid plays a definitive genotype-dependent role in the elicitation of Bryophyllum cell cultures, while methyl jasmonate was revealed as a secondary factor. The knowledge provided by this approach opens a wide perspective on the research of medicinal plants and facilitates their biotechnological exploitation as biofactories in the food, cosmetic and pharmaceutical fields.

Camellia japonica: A phytochemical perspective and current applications facing its industrial exploitation.

In response to the increased popularity of medicinal plants, a number of conservation groups are recommending the investigation on poorly characterized and widely distributed species, as it is the case of camellias. In particular, Camellia japonica L. is a widespread species found in Galicia (NW Spain), where it has been largely exploited with ornamental purposes. Recent findings on its phytochemical characterization showed thousands of bioactive ingredients, mostly represented by phenolic compounds, together with terpenoids, and fatty acids. These molecules present associated biological activities, acting as antioxidant, antimicrobial, anti-inflammatory, and anticancer agents. This review is aimed at describing the main bioactive compounds of C. japonica, as well as the health-enhancing properties attributed to this medicinal plant. Novel strategies are needed to implement an efficient industrialization process for C. japonica, ranging from small-scale approaches to the establishment of large plantations, thus involving important sectors, such as the food, pharmaceutical and cosmetic industries.

The Combination of Untargeted Metabolomics and Machine Learning Predicts the Biosynthesis of Phenolic Compounds in Bryophyllum Medicinal Plants (Genus Kalanchoe).

Phenolic compounds constitute an important family of natural bioactive compounds responsible for the medicinal properties attributed to Bryophyllum plants (genus Kalanchoe, Crassulaceae), but their production by these medicinal plants has not been characterized to date. In this work, a combinatorial approach including plant tissue culture, untargeted metabolomics, and machine learning is proposed to unravel the critical factors behind the biosynthesis of phenolic compounds in these species. The untargeted metabolomics revealed 485 annotated compounds that were produced by three Bryophyllum species cultured in vitro in a genotype and organ-dependent manner. Neurofuzzy logic (NFL) predictive models assessed the significant influence of genotypes and organs and identified the key nutrients from culture media formulations involved in phenolic compound biosynthesis. Sulfate played a critical role in tyrosol and lignan biosynthesis, copper in phenolic acid biosynthesis, calcium in stilbene biosynthesis, and magnesium in flavanol biosynthesis. Flavonol and anthocyanin biosynthesis was not significantly affected by mineral components. As a result, a predictive biosynthetic model for all the Bryophyllum genotypes was proposed. The combination of untargeted metabolomics with machine learning provided a robust approach to achieve the phytochemical characterization of the previously unexplored species belonging to the Bryophyllum subgenus, facilitating their biotechnological exploitation as a promising source of bioactive compounds.

From Ethnomedicine to Plant Biotechnology and Machine Learning: The Valorization of the Medicinal Plant Bryophyllum sp.

The subgenus Bryophyllum includes about 25 plant species native to Madagascar, and is widely used in traditional medicine worldwide. Different formulations from Bryophyllum have been employed for the treatment of several ailments, including infections, gynecological disorders, and chronic diseases, such as diabetes, neurological and neoplastic diseases. Two major families of secondary metabolites have been reported as responsible for these bioactivities: phenolic compounds and bufadienolides. These compounds are found in limited amounts in plants because they are biosynthesized in response to different biotic and abiotic stresses. Therefore, novel approaches should be undertaken with the aim of achieving the phytochemical valorization of Bryophyllum sp., allowing a sustainable production that prevents from a massive exploitation of wild plant resources. This review focuses on the study of phytoconstituents reported on Bryophyllum sp.; the application of plant tissue culture methodology as a reliable tool for the valorization of bioactive compounds; and the application of machine learning technology to model and optimize the full phytochemical potential of Bryophyllum sp. As a result, Bryophyllum species can be considered as a promising source of plant bioactive compounds, with enormous antioxidant and anticancer potential, which could be used for their large-scale biotechnological exploitation in cosmetic, food, and pharmaceutical industries.

Machine Learning Unmasked Nutritional Imbalances on the Medicinal Plant Bryophyllum sp. Cultured in vitro.

Plant nutrition is a crucial factor that is usually underestimated when designing plant in vitro culture protocols of unexploited plants. As a complex multifactorial process, the study of nutritional imbalances requires the use of time-consuming experimental designs and appropriate statistical and multiple regression analysis for the determination of critical parameters, whose results may be difficult to interpret when the number of variables is large. The use of machine learning (ML) supposes a cutting-edge approach to investigate multifactorial processes, with the aim of detecting non-linear relationships and critical factors affecting a determined response and their concealed interactions. Thus, in this work we applied artificial neural networks coupled to fuzzy logic, known as neurofuzzy logic, to determine the critical factors affecting the mineral nutrition of medicinal plants belonging to Bryophyllum subgenus cultured in vitro. The application of neurofuzzy logic algorithms facilitate the interpretation of the results, as the technology is able to generate useful and understandable "IF-THEN" rules, that provide information about the factor(s) involved in a certain response. In this sense, ammonium, sulfate, molybdenum, copper and sodium were the most important nutrients that explain the variation in the in vitro culture establishment of the medicinal plants in a species-dependent manner. Thus, our results indicate that Bryophyllum spp. display a fine-tuning regulation of mineral nutrition, that was reported for the first time under in vitro conditions. Overall, neurofuzzy model was able to predict and identify masked interactions among such factors, providing a source of knowledge (helpful information) from the experimental data (non-informative per se), in order to make the exploitation and valorization of medicinal plants with high phytochemical potential easier.

Exploring the Use of Bryophyllum as Natural Source of Bioactive Compounds with Antioxidant Activity to Prevent Lipid Oxidation of Fish Oil-In-Water Emulsions.

The current industrial requirements for food naturalness are forcing the development of new strategies to achieve the production of healthier foods by replacing the use of synthetic additives with bioactive compounds from natural sources. Here, we investigate the use of plant tissue culture as a biotechnological solution to produce plant-derived bioactive compounds with antioxidant activity and their application to protect fish oil-in-water emulsions against lipid peroxidation. The total phenolic content of Bryophyllum plant extracts ranges from 3.4 to 5.9 mM, expressed as gallic acid equivalents (GAE). The addition of Bryophyllum extracts to 4:6 fish oil-in-water emulsions results in a sharp (eight-fold) increase in the antioxidant efficiency due to the incorporation of polyphenols to the interfacial region. In the emulsions, the antioxidant efficiency of extracts increased linearly with concentration and levelled off at 500 µM GAE, reaching a plateau region. The antioxidant efficiency increases modestly (12%) upon increasing the pH from 3.0 to 5.0, while an increase in temperature from 10 to 30 °C causes a six-fold decrease in the antioxidant efficiency. Overall, results show that Bryophyllum plant-derived extracts are promising sources of bioactive compounds with antioxidant activity that can be eventually be used to control lipid oxidation in food emulsions containing (poly)unsaturated fatty acids.

Machine Learning Technology Reveals the Concealed Interactions of Phytohormones on Medicinal Plant In Vitro Organogenesis.

Organogenesis constitutes the biological feature driving plant in vitro regeneration, in which the role of plant hormones is crucial. The use of machine learning (ML) technology stands out as a novel approach to characterize the combined role of two phytohormones, the auxin indoleacetic acid (IAA) and the cytokinin 6-benzylaminopurine (BAP), on the in vitro organogenesis of unexploited medicinal plants from the Bryophyllum subgenus. The predictive model generated by neurofuzzy logic, a combination of artificial neural networks (ANNs) and fuzzy logic algorithms, was able to reveal the critical factors affecting such multifactorial process over the experimental dataset collected. The rules obtained along with the model allowed to decipher that BAP had a pleiotropic effect on the Bryophyllum spp., as it caused different organogenetic responses depending on its concentration and the genotype, including direct and indirect shoot organogenesis and callus formation. On the contrary, IAA showed an inhibiting role, restricted to indirect shoot regeneration. In this work, neurofuzzy logic emerged as a cutting-edge method to characterize the mechanism of action of two phytohormones, leading to the optimization of plant tissue culture protocols with high large-scale biotechnological applicability.

Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds.

We combined machine learning and plant in vitro culture methodologies as a novel approach for unraveling the phytochemical potential of unexploited medicinal plants. In order to induce phenolic compound biosynthesis, the in vitro culture of three different species of Bryophyllum under nutritional stress was established. To optimize phenolic extraction, four solvents with different MeOH proportions were used, and total phenolic content (TPC), flavonoid content (FC) and radical-scavenging activity (RSA) were determined. All results were subjected to data modeling with the application of artificial neural networks to provide insight into the significant factors that influence such multifactorial processes. Our findings suggest that aerial parts accumulate a higher proportion of phenolic compounds and flavonoids in comparison to roots. TPC was increased under ammonium concentrations below 15 mM, and their extraction was maximum when using solvents with intermediate methanol proportions (55-85%). The same behavior was reported for RSA, and, conversely, FC was independent of culture media composition, and their extraction was enhanced using solvents with high methanol proportions (>85%). These findings confer a wide perspective about the relationship between abiotic stress and secondary metabolism and could serve as the starting point for the optimization of bioactive compound production at a biotechnological scale.

Adsorption of gallic acid, propyl gallate and polyphenols from Bryophyllum extracts on activated carbon.

The adsorption of gallic acid (GA) and propyl gallate (PG) on activated carbon (AC) was studied as a function of the AC mass and temperature. Clean first order behavior was obtained for at least three half-lives and the equilibrium was reached after ∼4 h contact time. An increase in the temperature (T = 20-40 °C) increases their adsorption rate constant values (k1) by 2.5 fold but has a negligible effect on the amount of antioxidant adsorbed per mass of AC at equilibrium. We also analyzed the adsorption process of polyphenols from Bryophyllum extracts and ca 100% of the total amount of the polyphenols in the extract were adsorbed when using 7 mg of AC. Results can be explained on the basis of the Freundlich isotherm but do not fit the Langmuir model. Results suggest that the combination of emerging in vitro plant culture technologies with adsorption on activated carbon can be successfully employed to remove important amounts of bioactive compounds from plant extracts by employing effective, sustainable and environmental friendly procedures.