Chemical Variability and In Vitro Anti-Inflammatory Activity of Leaf Essential Oil from Ivorian Isolona dewevrei (De Wild. & T. Durand) Engl. & Diels.

The chemical variability and the in vitro anti-inflammatory activity of the leaf essential oil from Ivorian Isolona dewevrei were investigated for the first time. Forty-seven oil samples were analyzed using a combination of CC, GC(RI), GC-MS and 13C-NMR, thus leading to the identification of 113 constituents (90.8-98.9%). As the main components varied drastically from sample to sample, the 47 oil compositions were submitted to hierarchical cluster and principal components analyses. Three distinct groups, each divided into two subgroups, were evidenced. Subgroup I-A was dominated by (Z)-ß-ocimene, ß-eudesmol, germacrene D and (E)-ß-ocimene, while (10ßH)-1ß,8ß-oxido-cadina-4-ene, santalenone, trans-α-bergamotene and trans-ß-bergamotene were the main compounds of Subgroup I-B. The prevalent constituents of Subgroup II-A were germacrene B, (E)-ß-caryophyllene, (5αH,10ßMe)-6,12-oxido-elema-1,3,6,11(12)-tetraene and γ-elemene. Subgroup II-B displayed germacrene B, germacrene D and (Z)-ß-ocimene as the majority compounds. Germacrene D was the most abundant constituent of Group III, followed in Subgroup III-A by (E)-ß-caryophyllene, (10ßH)-1ß,8ß-oxido-cadina-4-ene, germacrene D-8-one, and then in Subgroup III-B by (Z)-ß-ocimene and (E)-ß-ocimene. The observed qualitative and quantitative chemical variability was probably due to combined factors, mostly phenology and season, then harvest site to a lesser extent. The lipoxygenase inhibition by a leaf oil sample was also evaluated. The oil IC50 (0.020 ± 0.005 mg/mL) was slightly higher than the non-competitive lipoxygenase inhibitor NDGA IC50 (0.013 ± 0.003 mg/mL), suggesting a significant in vitro anti-inflammatory potential.

Utilizing AgNPt-SALDI to Classify Edible Oils by Multivariate Statistics of Triacylglycerol Profile.

Edible oils are valuable sources of nutrients, and their classification is necessary to ensure high quality, which is essential to food safety. This study reports the establishment of a rapid and straightforward SALDI-TOF MS platform used to detect triacylglycerol (TAG) in various edible oils. Silver nanoplates (AgNPts) were used to optimize the SALDI samples for high sensitivity and reproducibility of TAG signals. TAG fingerprints were combined with multivariate statistics to identify the critical features of edible oil discrimination. Eleven various edible oils were discriminated using principal component analysis (PCA). The results suggested the creation of a robust platform that can examine food adulteration and food fraud, potentially ensuring high-quality foods and agricultural products.

Headspace gas chromatography-mass spectrometry in the analysis of lavender's essential oil: Optimization by response surface methodology.

A static headspace gas chromatography - mass spectrometry (HS-GC/MS) method was developed and optimized with the aim to be applied in the analysis of lavender essential oil. To obtain a comprehensive profile of the essential oil, the optimum HS-GC/MS method parameters were selected based on a Design of Experiments (DοE) process. Plackett-Burman experimental design was applied by utilizing seven parameters of the HS injection system. Incubation equilibration temperature and time, agitator's vortex speed, post injection dwell time, inlet temperature, split ratio and injection flow rate were screened to select the optimum conditions on the basis of the number and the intensity of the identified compounds. Other parameters, such as sample volume and dilution solvent ratio, were also examined to achieve a comprehensive profile in a chromatographic run of 55 min. With the obtained optimum method, more than 40 volatile compounds were identified in lavender's essential oils from different geographical regions in Greece. The method can be utilized for the quality assessment of lavender's essential oil and provide information on its characteristic aroma and discrimination among species based on the acquired GC-MS profiles.

Essential oils and their components in combating fungal pathogens of animal and human skin.

OBJECTIVE: The most common problems of modern medicine include fungal infections of the skin and its appendages caused by dermatomycetes, yeast-like fungi and moulds. Due to toxicity of pharmacological fungicides and promotion of ecology, natural substances with high antifungal properties are sought. Essential oils and their components show potential in this regard. MATERIAL AND METHOD: Fourteen commercial essential oils were tested for antifungal activity. The study were carried out by agar dilution method against the following fungal species: Microsporum gypseum, Microsporum canis, Trichophyton mentagrophytes, Trichophyton violaceum, Aspergillus niger, Scopulariopsis brevicaulis and (IZ 1) dog skin isolate. The minimum inhibitory concentration (MIC) and the minimum fungicidal concentration (MFC) values were determined for all tested oils and individual components of oils with the highest activity against the tested fungi. GC-MS analysis was performed for the most active oils. RESULTS: Cinnamon, thyme, clove, geranium and manuka oils were most active against the test fungi. The MIC values in the tested oils were in the range of 0.5->10µg/µl and the MFC amounted to 1.25->10µg/µl. Activity of individual components against the tested fungi strains was selective and clearly higher against dermatomycetes fungi and IZ 1 isolate. The strongest effect on dermatomycetes fungi was of cinnamaldehyde, thymol and carvacrol-with the values of 0.039-1.25µg/µl (MIC) and 0.078-1.25µg/µl (MFC). In turn, the highest activity against IZ 1 isolate was of cinnamaldehyde, eugenol, carvacrol, geraniol and thymol. Their MIC and MFC was 0.313-1.25µg/µl. CONCLUSION: The results prove the applicability of selected oils and their components as alternatives to synthetic agents in combating fungal dermatoses in animals and humans.

Natural volatile oils derived from herbal medicines: A promising therapy way for treating depressive disorder.

Depression is a common global mental disorder that seriously harms human physical and mental health. With the development of society, the increase of pressure and the role of various other factors make the incidence of depression increase year by year. However, there is a lack of drugs that have a fast onset, significant effects, and few side effects. Some volatile oils from traditional natural herbal medicines are usually used to relieve depression and calm emotions, such as Lavender essential oil and Acorus tatarinowii essential oil. It was reported that these volatile oils, are easy to enter the brain through the blood-brain barrier and have good antidepressant effects with little toxicity and side effects. In this review, we summarized the classification of depression, and listed the history of using volatile oils to fight depression in some countries. Importantly, we summarized the anti-depressant natural volatile oils and their monomers from herbal medicine, discussed the anti-depressive mechanisms of the volatile oils from natural medicine. The volatile oils of natural medicine and antidepressant drugs were compared and analyzed, and the application of volatile oils was explained from the clinical use and administration routes. This review would be helpful for the development of potential anti-depressant medicine and provide new alternative treatments for depressive disorders.

Pattern recognition based on machine learning identifies oil adulteration and edible oil mixtures.

Previous studies have shown that each edible oil type has its own characteristic fatty acid profile; however, no method has yet been described allowing the identification of oil types simply based on this characteristic. Moreover, the fatty acid profile of a specific oil type can be mimicked by a mixture of 2 or more oil types. This has led to fraudulent oil adulteration and intentional mislabeling of edible oils threatening food safety and endangering public health. Here, we present a machine learning method to uncover fatty acid patterns discriminative for ten different plant oil types and their intra-variability. We also describe a supervised end-to-end learning method that can be generalized to oil composition of any given mixtures. Trained on a large number of simulated oil mixtures, independent test dataset validation demonstrates that the model has a 50th percentile absolute error between 1.4-1.8% and a 90th percentile error of 4-5.4% for any 3-way mixtures of the ten oil types. The deep learning model can also be further refined with on-line training. Because oil-producing plants have diverse geographical origins and hence slightly varying fatty acid profiles, an online-training method provides also a way to capture useful knowledge presently unavailable. Our method allows the ability to control product quality, determining the fair price of purchased oils and in-turn allowing health-conscious consumers the future of accurate labeling.

Effect of vegetable oils on the experimental infection of mice with Trypanosoma congolense.

Vegetable oils are frequently used as solvents for lipophilic materials; accordingly, the effects of their components should be considered in animal experiments. In this study, the effects of various vegetable oils on the course of Trypanosoma congolense infection were examined in mice. C57BL/6J mice were orally administered four kinds of oils (i.e., coconut oil, olive oil, high oleic safflower oil, and high linoleic safflower oil) with different fatty acid compositions and infected with T. congolense IL-3000. Oil-treated mice infected with T. congolense showed significantly higher survival rates and lower parasitemia than those of control mice. Notably, coconut oil, which mainly consists of saturated fatty acids, delayed the development of parasitemia at the early stage of infection. These results indicated that vegetable oil intake could affect T. congolense infection in mice. These findings have important practical implications; for example, they suggest the potential effectiveness of vegetable oils as a part of the regular animal diet for controlling tropical diseases and indicate that vegetable oils are not suitable solvents for studies of the efficacy of lipophilic agents against T. congolense.

Phytosterols Content in Vegetable Oils of Brazil: Coconut, Safflower, Linseed and Evening Primrose

Abstract In the last years phytosterols, natural components of plants, have received more attention due to association of their consumption with reducing risk of cardiovascular diseases and cancer. There are several scientific studies about phytosterols in vegetable oils, but they are scarce in unconventional oils. The objective of this research was evaluating the content of phytosterols (β-sitosterol, stigmasterol and campesterol) in vegetable oils sold in São Paulo city, in Brazil. The analysis included cold alkaline saponification, derivatization with hexamethyldisilazane and trimethylchlorosilane reagents, and quantification by gas chromatography using flame ionization detection and internal standardization. The quality control parameters indicated that the method was suitable for analysis. Total sterols were between 272.3 mg kg-1 (coconut oil) to 6169.7 mg kg-1 (evening primrose oil). β-sitosterol was the component found in higher concentrations and evening primrose oil was the most representative in quantity of phytosterols.

Oxidomics on the omega-3 volatile degradation pattern to determine differences between vegetable and marine oils.

In this work, oxidation assessment of vegetable and marine oils was performed based on their quantitative volatile profile and data analysis by 3-way partial least square chemometrics. Classification models were obtained using broad-spectrum isotopically labelled standards on the analysis of 25 volatile compounds from omega-3 fatty acid (FA) degradation by headspace solid phase microextraction gas chromatography time-of-flight mass spectrometry. Our oxidomic approach was performed on edible oils that differed in their origin (marine or vegetable) and in their omega-3 FA profile. In order to achieve a 3D matrix, every oil was oxidized at 6 different time-points. The obtained models classified edible oils according to their volatile degradation pattern. Oxidation of eicosapentaenoic/docosahexaenoic FA was mainly related to 2-propenal, butanal and 2-ethylfuran while α-linolenic acid oxidation was linked to 1-hydroxy-2-butanone and 5-ethyl-2(5H)-furanone. The present research provides valuable information on the degradation differences of omega-3 oils and proposes specific oxidation markers that could be used to ensure their quality assurance and avoid intentional adulterations.

Different susceptibilities of Aedes aegypti and Aedes albopictus larvae to plant-derived products.

INTRODUCTION: Aedes aegypti and Aedes albopictus are important vectors that transmit arboviruses to human populations. METHODS: Natural products were obtained and tested against larvae collected from the field in Fortaleza, capital of Ceará state. RESULTS: The essential oils of Syzygium aromaticum (Ae. aegypti LC50 = 32.7 ppm and Ae. albopictus LC50 = 138.1 ppm) and Croton nepetaefolius (Ae. aegypti LC50 = 81.7 ppm and Ae. albopictus LC50 = 76.1 ppm) showed the most intense larvicidal activity. CONCLUSIONS: The essential oils and methyl esters showed greater larvicidal activity than did the ethanol extracts.

Combined fluorescence-transmittance imaging system for geographical authentication of patchouli oil.

Recently, demand for authentication technology is growing rapidly in an attempt to overcome counterfeiting of high-value agricultural products, such as patchouli oil. Fingerprinting methods based on spectroscopy are one such technology being used for authentication. However, the spectral datasets obtained are multivariate in nature; containing thousands of data points for a single sample, making data acquisition and processing time-consuming. Therefore, reduction and simplification in the number of variables used required is needed to provide a more rapid and applicable method. Color cameras, which can capture image in the visible region light, could be such an alternative spectral data acquisition approach. In this research, a simplified spectroscopy method was developed for origin authentication of patchouli oil. The system consists of front ultraviolet light induced (365 nm) fluorescence and a white LED-based backlighting imaging system that consecutively captures the fluorescence and transmittance characteristics of the oil in the visible region. From the captured images, features were extracted and analyzed using Principle Component Analysis (PCA) to identify important image features for discrimination of origin. From the samples measured, the samples clustered around three islands of origin in the PCA space. A classification model based on fluorescence and transmittance image features (color values) could discriminate origin classes with a total accuracy of 88.46%. A lower accuracy was found for the Java class due to low sample numbers. This result demonstrates that the proposed system has the potential to be a rapid authentication tool for determining the geographical origin of patchouli oils.

Toxic aldehyde generation in and food uptake from culinary oils during frying practices: peroxidative resistance of a monounsaturate-rich algae oil.

Human ingestion of cytotoxic and genotoxic aldehydes potentially induces deleterious health effects, and high concentrations of these secondary lipid oxidation products (LOPs) are generated in polyunsaturated fatty acid (PUFA)-rich culinary oils during high temperature frying practices. Here, we explored the peroxidative resistance of a novel monounsaturate-rich algae frying oil (MRAFO) during laboratory-simulated shallow- and domestically-based repetitive deep-frying episodes (LSSFEs and DBRDFEs respectively), the latter featuring potato chip fryings. Culinary frying oils underwent LSSFEs at 180 °C, and DBRDFEs at 170 °C: aldehydes were determined by 1H NMR analysis in samples collected at increasing heating/frying time-points. Fast food restaurant-fried potato chip serving (FFRPCS) aldehyde contents were also monitored. Substantially lower levels of aldehydes were generated in the MRAFO product than those observed in PUFA-richer oils during LSSFEs. Toxicologically-significant concentrations of aldehydes were detected in FFRPCSs, and potato chips exposed to DBRDFEs when using a PUFA-laden sunflower oil frying medium: these contents increased with augmented deep-frying episode repetition. FFRPCS aldehyde contents were 10-25 ppm for each class monitored. In conclusion, the MRAFO product generated markedly lower levels of food-penetrative, toxic aldehydes than PUFA-rich ones during LSSFEs. Since FFRPCS and DBRDFE potato chip aldehydes are predominantly frying oil-derived, PUFA-deplete MRAFOs potentially offer health-friendly advantages.

A comprehensive classification of edible oils according to their radical scavenging spectral profile evaluated by advanced chemometrics.

A comprehensive study concerning the characterization and classification of 30 cold-pressed edible oils according to their UV-Vis spectra and radical scavenging profiles using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay is presented. Considering the principal component analysis (PCA) and fuzzy-principal component analysis (FPCA) loadings profiles, the characteristic spectral regions with a significant influence in oil samples classification were identified and associated with characteristic factors in each group. Much more, the oils with high antiradical capacity were revealed. The scores corresponding to the first principal component and the canonical scores corresponding to the first discriminant function derived from radical scavenging spectral profiles allowed a relevant classification of oils in well-defined groups associated with their high, medium and low radical scavenging capacity. The FPCA-LDA method applied on DPPH radical scavenging spectral profiles of edible oils appeared to be the most efficient method with a correct classification rate of 96.7%.

Rapid identification of edible oil species using supervised support vector machine based on low-field nuclear magnetic resonance relaxation features.

Aimed to rapidly identify the edible oils according to their botanical origin, a novel method was proposed using supervised support vector machine based on low-field nuclear magnetic resonance and relaxation features. The low-field (LF) nuclear magnetic resonance (NMR) signals of 11 types of edible oils were acquired, and 5 features were extracted from the transverse relaxation decay curves and modeled using support vector machines (SVM) for the identification of edible oils. Two SVM classification strategies have been applied and discussed. Good performance can be achieved when the relative position of each edible oil has been determined by PCA before the designing of binary tree structure of SVM model, and the classification accuracy is 99.04%. The good robustness of this method has been verify at different data sets. It is almost a real time method, and the entire process takes only 144 s.

Discrimination and classification of extra virgin olive oil using a chemometric approach based on TMS-4,4'-desmetylsterols GC(FID) fingerprints of edible vegetable oils.

A single out-line HPLC-GC (FID) analytical method is applied to acquire the chromatographic fingerprint characteristic of the TMS-4,4'-desmetylsterol derivative fraction of several marketed edible vegetable oils in order to identify and discriminate the most valuable extra-virgin olive oils from the other vegetal oils (canola, corn, grape seed, linseed, olive pomace, peanut, rapeseed, soybean, sesame, seeds (non-specified composition but usually a blend of corn and sunflower) and sunflower). The natural structure of the preprocessed data undergoes a preliminary exploration using principal component analysis and heat map-based cluster analysis. A partial least squares-discriminant model is first trained from 53 oil samples (only 3 latent variables) and externally validated from 18 test oil samples. No classification errors are found and all the test samples are correctly classified. Additional classification models are also built in order to discriminate among vegetables-oil families and excellent results have been also achieved.

Different susceptibilities of Aedes aegypti and Aedes albopictus larvae to plant-derived products

Abstract INTRODUCTION: Aedes aegypti and Aedes albopictus are important vectors that transmit arboviruses to human populations. METHODS: Natural products were obtained and tested against larvae collected from the field in Fortaleza, capital of Ceará state. RESULTS: The essential oils of Syzygium aromaticum (Ae. aegypti LC50 = 32.7 ppm and Ae. albopictus LC50 = 138.1 ppm) and Croton nepetaefolius (Ae. aegypti LC50 = 81.7 ppm and Ae. albopictus LC50 = 76.1 ppm) showed the most intense larvicidal activity. CONCLUSIONS: The essential oils and methyl esters showed greater larvicidal activity than did the ethanol extracts.

Fingerprint profile and efficacy-associated markers of Nigella sativa oil for geographical origin determination using targeted and untargeted HPTLC-multivariate analysis.

Efficacy directed-fingerprint analysis of high-performance thin layer chromatography is proposed to set up fingerprint activity relationship modeling for precise discrimination of chemical and effective consistency of Nigella sativa oils from different geographical origins. A whole of 27 samples of N. sativa oils from three geographical area (Egypt, Ethiopia and Syria) were collected and their antimicrobial, cytotoxic, anti-inflammatory and analgesic activities were measured. The results revealed that there was significant difference in the biological activities of the oils collected. The fingerprints of the samples had been established by high performance thin layer chromatography, subsequently the data had been utilized for the discrimination of the samples geographical origin. The loading plots of HPTLC-Principal Component Analysis (PCA) had been used to discover the crucial marker ingredients for classification. Furthermore, targeted chemical fingerprints had been established by HPTLC, and discriminant analyses were calculated depending on five common characteristic peaks. The chosen markers were quantified by validated HPTLC methods, and then the quantitative data as well as the oils bioactive properties were subjected to partial least squares regression (PLSR) analyses. Thymoquinone and free fatty acids (FFA) were revealed as potential markers to distinguish the chemical consistency and efficacy of the oils from the three different geographical origins. The suggested technique provides an applicable integrated strategy to screen for efficacy-associated markers for discrimination of N. sativa oils from distinctive geographical origins exploiting HPTLC fingerprint activity relationship modeling.

High-throughput authentication of edible oils with benchtop Ultrafast 2D NMR.

We report the use of an Ultrafast 2D NMR approach applied on a benchtop NMR system (43 MHz) for the authentication of edible oils. Our results demonstrate that a profiling strategy based on fast 2D NMR spectra recorded in 2.4 min is more efficient than the standard 1D experiments to classify oils from different botanical origins, since 1D spectra on the same samples suffer from strong peak overlaps. Six edible oils with different botanical origins (olive, hazelnut, sesame, rapeseed, corn and sunflower) have been clearly discriminated by PCA analysis. Furthermore, we show how this approach combined with a PLS model can detect adulteration processes such as the addition of hazelnut oil into olive oil, a common fraud in food industry.

Investigating Chemical Composition and Indications of Hydrosol Soft Drinks (Aromatic Waters) Used in Persian Folk Medicine for Women's Hormonal and Reproductive Health Conditions.

Hydrosol soft drinks in Persian nutrition culture are produced as side products of the essential oil industry to be used as safe remedies for treatment of some ailments. This study investigated hydrosols for women's hormonal health conditions. Detailed information was gathered by questionnaires. Chemical constituents of these mono- or poly-herbal hydrosols were identified after liquid/liquid extraction and gas chromatography-mass spectrometry. Hierarchical cluster and K-means analysis (SPSS software) were used to find their relevance. A literature survey was also performed. In most cases, thymol, carvacrol, and carvone were the major constituents except for dill, white horehound, willow, Moderr, and yarrow hydrosols, whose their major components were dill ether, menthol, phenethyl alcohol, linalool, or camphor. Based on clustering methods, some similarities could be found in their constituents with some exceptions. None of them have been studied scientifically before. These investigations may lead to the development of some functional drinks or even new lead components.

A Survey on Chemical Constituents and Indications of Aromatic Waters Soft Drinks (Hydrosols) Used in Persian Nutrition Culture and Folk Medicine for Neurological Disorders and Mental Health.

In Persian nutrition culture, drinking aromatic waters (hydrosols, distillate) has a long history as functional beverages or therapeutic remedies. The co-distilled water with essential oils, which contains partial amounts of more water-soluble volatile compounds are diluted and used as beverages. Since the solubility of volatile components is different in water, the overall composition, and thus the biological activities of aromatic waters seem to be different from the essential oils they were co-distilled with. Despite the essential oils, chemical constituents of many aromatic waters have not been evaluated scientifically. This research investigated hydrosols used for mental and neurological health maintenance in Persian nutrition culture and their chemical constituents. Constitutions of these hydrosols were extracted by liquid/liquid extraction method and identified by gas chromatography-mass spectrometry. Furthermore, cluster analysis was used to evaluate the relevance of these hydrosols chemical constituents. About 93 compounds were identified from 20 aromatic waters. the major or second major constituents were thymol (azarol howthorn, frankincense, lemon balm, valerian, shadab), phenethyl alcohol (damask rose, dog-rose, starflower), carvacrol (basil, creeping buttercup, lemon balm); eugenol (shadab, dog-rose, starflower, basil), camphor (yarrow and wormwood), carvone (oriental plane), caryophyllene (cuminum), cinnamaldehyde (Chinese cinnamon), p-cymen-7-ol (musk willow), limonene (lemon verbena), linalool and α-terpineol (bitter orange), menthol (date palm) and methyl 5-vinylnicotinate (olive). Although, these hydrosols prepared from plants belong to different genus and families, but cluster analysis showed obvious similarities between their chemical constituents. Results of this investigation showed in many cases that the constituents of aromatic waters are different from the pure essential oil.