Correlation analysis and modeling application from objective indicators to subjective evaluation of scented tea: A case study of rose tea.

Different scented teas provide various choices for consumers from appearance, aroma, flavor and others. Aiming to define advantages and market positions of different scented teas and promote optimization of market structure, characteristics for scented tea favored by consumers and outstanding attributes of different scented teas should be clarified. Rose tea was taken as study object. Sensory evaluation and consumer acceptance were investigated. GC-MS and HPLC fingerprints were established. Physicochemical characteristics were determined. RGB integration analysis was inventively proposed for correlation analysis. The volatile compounds with spicy, green or herbal odor as camphene, ß-phenethyl acetate, eugenol, and physicochemical parameters as antioxidant capacity, reducing sugar content, pH showed positive correlation with popular sensory properties. Six models for consumer preference by objective description were built through GA-SVR (accuracy = 1), and APP was developed. The research mode of scented tea has been successfully established to study multiple subjective characteristics with measurable objective parameters.

Insights into the flavor endowment of aroma-active compounds in cloves (Syzygium aromaticum) to stewed beef.

Clove (Syzygium aromaticum) is one of the most commonly used spices in stewed beef to enrich and improve its aroma during the stewing process. Gas chromatography ion mobility spectroscopy (GC-IMS), Q Exactive GC-Orbitrap-MS-O (QE-GC-MS/O), combined with sensory evaluation were employed to analyze the flavor endowment of aroma-active compounds in cloves to stewed beef. A total of 173 volatiles were identified in the clove powder (CP), stewed beef with clove (SBC), and stewed beef with salt (SBS), of which 21 volatiles were considered as aroma-active compounds. The concept of flavor endowment of aroma-active compounds in cloves was defined innovatively, and the endowment rate values (ERVs) of stewed beef were calculated. Nine aroma-active compounds in cloves were found to have a flavor endowment effect on stewed beef, while the terpenoids exhibited high ERVs. Despite the low ERV of eugenol, it still significantly impacted the aroma profile of SBC due to its high odor activity value (OAV) and flavor dilution (FD) factor. These volatiles offered mainly the clove, herbal, anise, and floral odor to stewed beef, which was also confirmed by sensory evaluation. These findings indicated that the terpenoids, phenolics and ethers in cloves had a significant influence on the overall aroma of stewed beef through the flavor endowment, which contributed to the precise use of cloves and improved the aroma of stewed beef.

Identifying Putative Biomarkers of Foodborne Pathogens Using a Metabolomic Approach.

Metabolomics is the study of low molecular weight biochemical molecules (typically <1500 Da) in a defined biological organism or system. In case of food systems, the term "food metabolomics" is often used. Food metabolomics has been widely explored and applied in various fields including food analysis, food intake, food traceability, and food safety. Food safety applications focusing on the identification of pathogen-specific biomarkers have been promising. This chapter describes a nontargeted metabolite profiling workflow using gas chromatography coupled with mass spectrometry (GC-MS) for characterizing three globally important foodborne pathogens, Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella enterica, from selective enrichment liquid culture media. The workflow involves a detailed description of food spiking experiments followed by procedures for the extraction of polar metabolites from media, the analysis of the extracts using GC-MS, and finally chemometric data analysis using univariate and multivariate statistical tools to identify potential pathogen-specific biomarkers.

How storage post sampling influences the stability of sebum when used for mass spectrometry metabolomics analysis?

Sebum is a biofluid excreted by sebaceous glands in the skin. In recent years sebum has been shown to contain endogenous metabolites diagnostic of disease, with remarkable results for Parkinson's Disease. Given that sebum sampling is facile and non-invasive, its potential for use in clinical biochemistry diagnostic assays should be explored including the parameters for standard operating procedures around collection, transport, and storage. To this aim we have here investigated the reproducibility of mass spectrometry data from sebum in relation to both storage temperature and length of storage. Sebum samples were collected from volunteers and stored for up to four weeks at a range of temperatures: ambient (circa 17 °C), -20 °C and -80 °C. Established extraction protocols were employed and samples were analysed by two chromatographic mass spectrometry techniques and data investigated using PCA, PLS-DA and ANOVA. We cannot discriminate samples as a function of storage temperature or time stored in unsupervised analysis using data acquired via TD-GC-MS and LC-IM-MS, although the sampling of volatiles was susceptible to batch effects. This study indicates that the requirements for storage and transport of sebum samples that may be used in clinical assays are less stringent than for liquid samples and indicate that sebum is suitable for remote and at home sampling prior to analysis.

Generating pooled quality control samples of volatile organic compounds.

Untargeted analysis of volatile organic compounds (VOCs) from exhaled breath and culture headspace are influenced by several confounding factors not represented in reference standards. In this study, we propose a method of generating pooled quality control (QC) samples for untargeted VOC studies using a split-recollection workflow with thermal desorption tubes. Sample tubes were desorbed and split from each sample and recollected onto a single tube, generating a pooled QC sample. This QC sample was then repeatedly desorbed and recollected with a sequentially lower split ratio allowing injection of multiple QC samples. We found pooled QC samples to be representative of complex mixtures using principal component analysis and may be useful in future longitudinal, multi-centre, and validation studies to assess data quality and adjust for batch effects.

Characterization and Profiling of Key Odorants in Roasted Hybrid American-European Hazelnuts.

American-European hybrid hazelnuts (Corylus americana × Corylus avellana) are an emerging crop in the Upper Midwest of the United States that have been reported to have unique sensory characteristics compared to traditionally grown European hazelnuts. In this study, key odor-active compounds in a roasted hybrid hazelnut variety (C. americana × C. avellana) were identified and profiled across different hybrid hazelnut varietals to understand sensory differences. Gas chromatography/mass spectrometry/olfactometry analysis identified 33 odorants with high flavor dilution factors (FD ≥ 16) in the roasted hybrid hazelnut, including 2-acetylpyrazine and 2-aminoacetophenone as first reported hazelnut odorants. Descriptive sensory analysis profiles of the roasted hazelnut and an aroma recombination model consisting of 27 odorants quantified above their odor detection thresholds were not significantly different for the six evaluated attributes, confirming the aroma contribution of the identified odorants. Variation in all 33 aroma-active compounds across 12 hybrid and two European hazelnut varieties was visualized through principal component analysis and related to aroma profiles previously characterized by consumers.

Identification of Compounds That Contribute to Consumer Aroma Liking of Roasted American-European Hybrid Hazelnuts.

New interspecific hybrid hazelnut crosses between American (Corylus americana) and European (Corylus avellana) hazelnuts are being developed to support a commercial industry in the Midwest region of the United States. In this study, volatile compounds that impact consumer aroma liking of roasted hybrid hazelnuts (C. americana × C. avellana) were investigated by targeted and nontargeted GC/MS flavoromics. Chemical profiles from 10 roasted hybrid hazelnut samples were modeled with consumer aroma liking scores by orthogonal partial least-squares with good fit and predictive performance (R2 ≥ 0.92, Q2 ≥ 0.82, RMSECV = 0.2). Top ranked predictors positively correlated with liking included 12 aroma compounds and 4 profiled volatiles for the targeted and nontargeted methods, respectively. Sensory recombination testing of hazelnut samples with addition of the 12 predictive odorants was preferred by consumers (p < 0.001, Δ aroma liking = 2.2 on 9-point scale) and perceived as more roasty, nutty, and sweet compared to the control (p < 0.05). Addition of the 4 predictive volatiles at subthreshold levels also was preferred (p = 0.02) and perceived as less earthy and mushroom like than the control (p < 0.05).

In Vitro α-Amylase and α-Glucosidase Inhibitory Potential of Green Banana Powder Extracts.

This study investigated the proximate composition and inhibitory potential of hot water and ethanolic extracts of the pulp, peel and whole fruit of green banana (Musa sapientum) on α-amylase and α-glucosidase. Bioactive compounds were identified using GC-MS analysis. In addition, the cytotoxic effect on human gingival fibroblast (hGF) was evaluated using the sulphorhodamine B (SRB) assay. The results showed that the peel of green banana had the highest amount of ash (10.05%), fat (2.83%), protein (3.64%) and total dietary fibre (36.62%). The carbohydrate content of the whole fruit (81.79%) and pulp (81.50%) was higher than that of the peel (71.90%). The moisture content of the pulp (13.08%) was higher than that of the peel (11.58%) and whole fruit (11.30%). The ethanolic green banana peel extract showed a good inhibitory effect of α-amylase and α-glucosidase with the concentration necessary for 50% inhibition (IC50) of 0.512 and 0.100 mg·mL-1, respectively. The α-glucosidase inhibitory effect of the ethanolic green banana peel extract and the hot water green banana peel extract was not significantly different from that of acarbose (IC50 0.108 mg·mL-1). GC-MS analysis of the ethanolic green banana peel extract revealed fatty acids and fatty acid ester (9-octadecenamide (Z), octadecanamide and other compounds). The ethanolic peel extract exhibits a significant noncytotoxicity effect on hGF cells at concentrations ranging from 0.0001 to 1.0 mg·mL-1.

Discrimination of coal geographical origins through HS-GC-IMS assisted with machine learning algorithms in larceny case.

The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection and monitoring technologies. The precise identification of coal trace evidence presents a challenge with current methods, owing to its minute quantity, fine texture, and intricate composition. In this study, we integrated machine learning with the identification of volatiles to accurately differentiate coal geographical origins through the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The topographic distribution of volatiles in coals was visually depicted to elucidate the subtle distinctions through spectra and fingerprint analysis. Additionally, four supervised machine learning algorithms were developed to quantitatively predict the geographical origins of natural coals utilizing the HS-GC-IMS dataset, and these were subsequently compared with unsupervised models. Remarkable volatile compounds were identified through the quantitative analysis and optimal Random Forest model, which offered a rapid readout and achieved an average accuracy of 100 % in coal identification. Our findings indicate that the integration of HS-GC-IMS and machine learning is anticipated to enhance the efficiency and accuracy of coal geographical traceability, thereby providing a foundation for litigation and trials.

Development, optimization and validation of automated volatile organic compound data analysis using an on-line thermal desorption gas chromatograph with dual detection and application to measurements in ambient air.

Because of their major role in indoor and outdoor air pollution, even at trace levels, VOCs are of great interest, and their monitoring requires sensitive analytical instruments. Several techniques are commonly used, such as portable sensors, Proton Transfer Reaction Mass Spectrometry (PTR-MS) and Thermal Desorption Gas Chromatography (TD-GC). The latter is widely used off- and on-line with Flame Ionization Detectors (FID) or Mass Spectrometers (MS). Given the large number of molecules detected per chromatogram, the data generated by these monitoring techniques are usually checked and reprocessed manually. This process is extremely time consuming and could result in human error. The challenge is to provide reliable results as quickly as possible. In this study, the performances of an on-line TD-GC system with dual detection FID and MS were tested. The Method Detection Limits (MDL), linearities and accuracies of 60 VOCs (alkanes, aromatics, oxygenated and halogenated) were calculated both for FID and MS detectors. The MDLs and accuracies ranged from 0.006 to 0.618 ppbv and from 77 % to 100 % for FID, and from 0.018 to 0.760 ppbv and from 80 % to 100 % for MS. Both detectors showed good complementarity and allowed the development of two programs to facilitate data analysis. These algorithms were designed to autonomously select optimal results between FID and MS detectors, and were evaluated for outdoor and indoor measurement conditions. Measuring VOCs in field campaigns is challenging, and it is anticipated that these programs could be extended to other types of dual-detector systems or for the comparison of data from different calibrated instruments.

Extraction of pesticides from soil using direct-immersion SPME LC-Tips followed by GC-MS/MS: Evaluation and proof-of-concept.

A new method was evaluated and developed for the analysis of pesticides in sandy-loam soil by direct-immersion solid phase microextraction (DI-SPME) followed by gas chromatography tandem-mass spectrometry (GC-MS/MS) determination. Ten pesticides were selected based on a literature survey of the compounds reported to be present in EU soils. The extraction was performed using SPME LC-Tips, a new SPME configuration with the coated fibers attached to a disposable and easy-to-handle micropipette tip, which was immersed into a soil slurry made by the addition of an aqueous solution to the soil sample. Ten experimental parameters were evaluated with a Plackett-Burman design, after which the extraction time and percentage of organic solvent in the aqueous extraction were optimized separately. The two fiber chemistries available (PDMS/DVB and C18) were evaluated in parallel for the entire work. In the final method, slurry samples were made by adding an aqueous solution (6 % methanol v/v) to 2 g of soil. The fiber was conditioned and then inserted, for extraction, into the samples, stirred by a magnetic bar. Afterwards, the analytes were desorbed onto 100 µL of methanol. After the addition of analyte protectants (ethylglycerol, gulonolactone, and sorbitol) the extract was injected into the GC-MS/MS system. Isotopically labelled penconazole was used as internal standard. A calibration was performed by extracting spiked soil with analyte concentrations of 0.1-50 µg/kg. Coefficients of determination of the linear calibration were between 0.94-0.98 for the PDMS/DVB and 0.92-0.99 for the C18. Limits of detection range between 0.01-10 µg/kg for the PDMS/DVB and 0.1-10 µg/kg for the C18. Overall, the C18 analytically outperformed the PDMS/DVB but required a longer extraction time (120 min vs 75 min for the PDMS/DVB). This method allows automation and generates low residual toxic waste, having the potential to be introduced as a greener and simpler alternative to currently used sample preparation methodologies.

Evaluation of lavender essential oils and by-products using microwave hydrodistillation and conventional hydrodistillation.

This study investigated the impact of two extraction methods, traditional hydrodistillation (TDH) and microwave-assisted hydrodistillation (MAH), on the essential oil yield and chemical profile of Lavandula angustifolia L., as well as the bioactive potential of the resulting wastewater. Essential oil composition was analyzed via GC-MS, revealing similar qualitative and quantitative profiles for both methods, with α-terpinolene and (-)borneol as major constituents. Wastewater analysis via LC-MS/MS and spectrophotometric assays demonstrated the presence of significant total phenolic content (3.29-1.78 mg GAE/g) and 32 individual phenolics (463.1 µg/kg for TDH; 479.33 µg/kg for MAH). These findings suggest that both essential oil and wastewater obtained by either method possess considerable bioactive potential, with the MAH method potentially offering advantages over TDH for essential oil extraction. Further exploration of wastewater applications in various industrial sectors is warranted.

Toward the apoplast metabolome: Establishing a leaf apoplast collection approach suitable for metabolomics analysis.

The leaf apoplast contains several compounds that play important roles in the regulation of different physiological processes in plants. However, this compartment has been neglected in several experimental and modelling studies, which is mostly associated to the difficulty to collect apoplast washing fluid (AWF) in sufficient amount for metabolomics analysis and as free as possible from symplastic contamination. Here, we established an approach based in an infiltration-centrifugation technique that use little leaf material but allows sufficient AWF collection for gas chromatography mass spectrometry (GC-MS)-based metabolomics analysis in both tobacco and Arabidopsis. Up to 54 metabolites were annotated in leaf and apoplast samples from both species using either 20% (v/v) methanol (20% MeOH) or distilled deionized water (ddH2O) as infiltration fluids. The use of 20% MeOH increased the yield of the AWF collected but also the level of symplastic contamination, especially in Arabidopsis. We propose a correction factor and recommend the use of multiple markers such as MDH activity, protein content and conductivity measurements to verify the level of symplastic contamination in MeOH-based protocols. Neither the concentration of sugars nor the level of primary metabolites differed between apoplast samples extracted with ddH2O or 20% MeOH. This indicates that ddH2O can be preferentially used, given that it is a non-toxic and highly accessible infiltration fluid. The infiltration-centrifugation-based approach established here uses little leaf material and ddH2O as infiltration fluid, being suitable for GC-MS-based metabolomics analysis in tobacco and Arabidopsis, with great possibility to be extended for other plant species and tissues.

A vortex-assisted MSPD method for the extraction of Polycyclic Aromatic Hydrocarbons from shrimp with determination by GC-MS/MS.

Polycyclic Aromatic Hydrocarbons (PAHs) are organic compounds with two or more condensed aromatic rings, formed from incomplete organic matter combustion. PAHs pose potential health risks due to their carcinogenic and mutagenic properties, accumulating in edible tissues of aquatic organisms, such as shrimp, which is extensively produced in the southern region of Rio Grande do Sul state (Brazil) and it is the most consumed seafood globally. Therefore, this study aimed to optimize and validate an analytical method for extracting 16 priority PAHs from shrimp samples using Vortex-Assisted Matrix Solid-Phase Dispersion (VA-MSPD) with determination by Gas Chromatography Tandem Mass Spectrometry (GC-MS/MS). The optimized method, which uses a reused solid support, was validated according to INMETRO and SANTE guidelines. PAHs demonstrated adequate linearity with correlation coefficients > 0.99. The matrix effect was assessed, and 12 out of the 16 PAHs showed a matrix effect of less than ±20%. The method's quantification limits ranged from 6.67 to 33.35 ng g-1. Accuracy and precision showed recovery values ranging from 55 to 115% with relative standard deviation (RSD) lower than 17% for all PAHs. In the applicability, 11 PAHs were detected, such as benzo[a]pyrene and benzo[b]fluoranthene, and the ∑PAHs ranged from 25.14 to 79.52 ng g-1, confirming the environmental contamination in the region and the need for monitoring these contaminants in shrimp destined for human consumption.

Alcohol-based hydrophobic deep eutectic solvents and ultrasound-assisted liquid phase microextraction followed by GC-MS for the extraction and analysis of organophosphorus pesticides in the blood of farmers.

Organophosphorus pesticides (OPPs) are a group of pesticides that are most widely used in the agricultural sector, and farmers are exposed to these chemicals more than other members of society. In this work, an environmentally friendly, simple, and safe ultrasound-assisted dispersive liquid-liquid microextraction (USA-DLLME) method using alcohol-based hydrophobic deep eutectic solvents (HDESs) followed by gas chromatography-mass spectroscopy (GC-MS) was developed for the extraction and determination of OPPs in the blood of farmers studied in Ravansar cohort. DESs synthesized from thymol as hydrogen bond donor (HBD) and aliphatic alcohols as hydrogen bond acceptor (HBA) have been used as extractants. Under optimal experimental conditions, the reproducibility of the method based on 7 replicate measurements of 10 µg L-1 of OPPs in blood samples was in the range of 1.4-3.8%. The method showed a linearity in the range of 0.01-150 µg L-1. The limits of detection and limits of quantification were between 0.003 and 0.02 µg L-1 and 0.01-0.05 µg L-1, respectively. The matrix effect and accuracy of the method were confirmed by spiking different amounts of OPPs in real blood samples and obtaining relative recoveries in the range of 91-112%. The results showed that the concentration of OPPs in the case group was significantly higher than in the control group, which is because the case group was exposed to OPPs during the spraying of agricultural products.

Mentha arvensis oil exhibits repellent acute toxic and antioxidant activities in Nauphoeta cinerea.

Mentha arvensis is an herbaceous plant commonly known as peppermint or Japanese mint. This study investigated the toxic potential and repellent efficacy of M. arvensis essential oil (MaEO) at varying concentrations (15.625-250 mg/mL) in Nauphoeta cinerea, along with its impact on biochemical parameters in N. cinerea. The potential of the major compounds as a new analgesic target was investigated using molecular docking. The essential oil was analyzed by gas Chromatography-mass spectrometry (GC-MS) and the toxic potential, repellent property, and changes in lipid peroxidation (LPO) levels were evaluated as markers of oxidative stress. GC-MS results revealed that the main components were oxygenated monoterpenes such as menthol (71.31%), mentone (13.34%) and isomentone (5.35%). MaEO significantly reduced lipid peroxidation (LPO), the levels of non-protein thiols and iron(II) at the concentration of 125 mg/mL in N. cinerea. Furthermore, the major components, L-(-)-Menthol and menthone demonstrated high gastrointestinal absorption and high affinity with the target protein, suggesting possible links that contribute to the analgesic effect of MaEO.

Two-Dimensional Liquid Chromatography Purified GC/C/IRMS Doping Control Method: Analysis of Endogenous and Exogenous Sources in Urine Samples from Asian Subjects Administered a Low Dose of AICAR.

AICAR (5-amino-4-imidazolecarboxyamide ribonucleoside), as a metabolic modulator, is classified in the S4 category by the World Anti-Doping Agency (WADA). Carbon Isotope Ratio Mass Spectrometry (CIR) is the mainstream method for distinguishing the endogenous and exogenous sources of AICAR in urine due to the significant individual difference in the concentration. The purpose of this study is to establish a gas chromatography combustion Isotope Ratio Mass Spectrometry (GC/C/IRMS) method for AICAR based on efficient two-dimensional liquid chromatography (2D-HPLC) separation. METHOD: In this study, an automated 2D-HPLC separation technique was used to separate and purify AICAR and endogenous reference substances in urine samples. Then, AICAR was derivatized with 3-TMS as the main derivative product, while the endogenous reference compounds remained in their original form. Subsequently, the developed GC/C/IRMS method was utilized for the detection of the target and reference substances. Followed, we evaluated the applicability of this method using urine samples from two Asian males administered a low dose of AICAR (3 grams). RESULTS: The advantages of this study include: 1) reduced sample pretreatment time: the established 2D-HPLC separation method can separate the target and endogenous reference substances in one step; 2) low interference: the isotope chromatograms have low background interference, and the separation of endogenous reference substances is purer; 3) more accurate result calculations: this method only requires derivatization and result correction for AICAR, with the endogenous reference substances measured in their original form, reducing biases from corrections of multiple substances. The detection method performed well, with a concentriton limit of 2500 ng/mL, meeting the needs of routine detection concentrations. The CIR results from volunteer samples indicated that samples collected within 16 hours post-administration exceeded the threshold set in the literature. CONCLUSION: This study successfully established a 2D-HPLC-GC/IRMS method that integrates CIR as the most stable indicator for distinguishing the internal and external sources of AICAR. After administering a low dose of AICAR to the Asian population, exogenous drug characteristics were manifested within 16 hours. This observation, when compared to the 40-hour detection window cited in the literature, suggests that the length of the detection window is positively correlated with the dosage of the test drug.

The dominant white color trait of the melon fruit rind is associated with epicuticular wax accumulation.

MAIN CONCLUSION: Microscopic analyses and chemical profiling demonstrate that the white rind phenotype in melon fruit is associated with the accumulation of n-alkanes, fatty alcohols, aldehydes and wax esters. Serving as an indicator of quality, the rind (or external) color of fruit directly affects consumer choice. A fruit's color is influenced by factors such as the levels of pigments and deposited epicuticular waxes. The latter produces a white-grayish coating often referred to as "wax bloom". Previous reports have suggested that some melon (Cucumis melo L.) accessions may produce wax blooms, where a dominant white rind color trait was genetically mapped to a major locus on chromosome 7 and suggested to be inherited as a single gene named Wi. We here provide the first direct evidence of the contribution of epicuticular waxes to the dominant white rind trait in melon fruit. Our light and electron microscopy and gas chromatography-mass spectrometry (GC-MS) comparative analysis of melon accessions with white or green rinds reveals that the rind of melon fruit is rich in epicuticular waxes. These waxes are composed of various biochemical classes, including fatty acids, fatty alcohols, aldehydes, fatty amides, n-alkanes, tocopherols, triterpenoids, and wax esters. We show that the dominant white rind phenotype in melon fruit is associated with increased accumulation of n-alkanes, fatty alcohols, aldehydes and wax esters, which are linked with the deposition of crystal-like wax platelets on their surfaces. Together, this study broadens the understanding of natural variation in an important quality trait of melon fruit and promotes the future identification of the causative gene for the dominant white rind trait.

Uncovering anti-inflammatory potential of Lantana camara Linn: Network pharmacology and in vitro studies.

Lantana camara Linn contains a diverse array of metabolites that exhibit therapeutic potential. The aim of this study was to evaluate the potential of L. camara leaves, which were collected at the Ie-Seu'um geothermal area in Aceh, Indonesia, as an anti-inflammatory through network pharmacology and in vitro analysis. The ethanolic extract derived from L. camara underwent identification utilizing gas chromatography-mass spectrometry (GC-MS) to verify chemical constituents for drug-likeness properties. The evaluation of anti-inflammatory activity included network pharmacology and a series of in vitro investigations using two methods: protein inhibition and albumin denaturation assays. The findings revealed that the extract contained a domination of terpenoids and fatty acids class, which met the evaluation criteria of drug-likeness. Network pharmacology analysis identified the top five key proteins (peroxisome proliferator-activated receptor gamma, prostaglandin G/H synthase 2, epidermal growth factor receptor, hypoxia-inducible factor 1-alpha, and tyrosine protein kinase-Janus kinase 2) involved in inflammation-related protein-protein interactions. Gene ontology enrichment highlighted the predominance of inflammatory responses in biological processes (BP), cytoplasm in cellular components (CC), and oxidoreductase activity in molecular functions (MF). In vitro analysis showed that the extract inhibited protein activity and protein denaturation with inhibitory concentration (IC50) values of 202.27 and 223.85 ppm, respectively. Additionally, the extract had antioxidant activity with DPPH- and ABTS-scavenging IC50 values of 140 ppm and 163 ppm, respectively. Toxicological assessment by brine shrimp lethality assay (BSLA), yielding a lethal concentration (LC50) value of 574 ppm (essentially non-toxic) and its prediction via ProTox 3.0 that indicated non-active in hepatotoxicity, carcinogenicity, immunotoxicity, mutagenicity, and cytotoxicity. These results suggested that L. camara holds noteworthy effectiveness as a potential candidate for complementary medicine in the realm of inflammatory agents, warranting further investigation in clinical settings.

GC-MS metabolomics of French lettuce (Lactuca Sativa L. var capitata) leaves exposed to bisphenol A via the hydroponic media.

INTRODUCTION: Bisphenol A (BPA), an organic compound used to produce polycarbonate plastics and epoxy resins, has become a ubiquitous contaminant due to its high-volume production and constant release to the environment. Plant metabolomics can trace the stress effects induced by environmental contaminants to the variation of specific metabolites, making it an alternative way to study pollutants toxicity to plants. Nevertheless, there is an important knowledge gap in metabolomics applications in this area. OBJECTIVE: Evaluate the influence of BPA in French lettuce (Lactuca Sativa L. var capitata) leaves metabolic profile by gas chromatography coupled to mass spectrometry (GC-MS) using a hydroponic system. METHODS: Lettuces were cultivated in the laboratory to minimize biological variation and were analyzed 55 days after sowing (considered the plant's adult stage). Hexanoic and methanolic extracts with and without derivatization were prepared for each sample and analyzed by GC-MS. RESULTS: The highest number of metabolites was obtained from the hexanoic extract, followed by the derivatized methanolic extract. Although no physical differences were observed between control and contaminated lettuce leaves, the multivariate analysis determined a statistically significant difference between their metabolic profiles. Pathway analysis of the most affected metabolites showed that galactose metabolism, starch and fructose metabolism and steroid biosynthesis were significantly affected by BPA exposure. CONCLUSIONS: The preparation of different extracts from the same sample permitted the determination of metabolites with different physicochemical properties. BPA alters the leaves energy and membrane metabolism, plant growth could be affected at higher concentrations and exposition times.