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IntroductionImpact of processing on product characteristics, sustainability, traceability, authenticity, and public health along the food chain becomes more and more important not only to the producer but also to the customer and the trust of a consumer toward a brand. In recent years, the number of juices and smoothies containing so called super foods or fruits, which have been “gently pasteurized,” has increased significantly. However, the term “gentle pasteurization” related to the application of emerging preservation technologies such as pulsed electric fields (PEF), high pressure processing (HPP) or ohmic heating (OH) is not clearly defined.MethodsTherefore, the presented study investigated the influence of PEF, HPP, OH, and thermal treatment on quality characteristics and microbial safety of sea buckthorn syrup. Syrups from two different varieties were investigated under the following conditions HPP (600 MPa 4–8 min), OH (83°C and 90°C), PEF (29.5 kV/cm, 6 μs, 100 Hz), and thermal (88°C, hot filling). Analyses to test the influence on quality parameters like ascorbic acid (AA), flavonoids, carotenoids, tocopherols, antioxidant activity; metabolomical/chemical profiling (fingerprinting) via U-HPLC-HRMS/MS (here especially flavonoids and fatty acids); sensory evaluation, as well as microbial stability including storage, were conducted.Results and discussionIndependent from the treatment, the samples were stable over 8 weeks of storage at 4°C. The influence on the nutrient content [Ascorbic acid (AA), total antioxidant activity (TAA), total phenolic compounds (TPC), tocopherols (Vit E)] was similar for all tested technologies. Employing statistical evaluation Principal Component Analysis (PCA) a clear clustering based on the processing technologies was observed. Flavonoids as well as fatty acids were significantly impacted by the type of used preservation technology. This was obvious during the storage time of PEF and HPP syrups, where enzyme activity was still active. The color as well as taste of the syrups were found to be more fresh-like for the HPP treated samples.

Optimization of experimental conditions in chromatography is recognized as a wear-and-tear process involving hundreds of experiments in order to maximize the number of separated compounds for each sample. The critical thinking skills and practices entailed cannot be achieved with students in a conventional lecture class. This report provides a Microsoft Excel-based spreadsheet allowing the fast simulation of fingerprinting results and the number of separated peaks for a given sample analyzed using gas chromatography–mass spectrometry. The applications were demonstrated for the simulation of extracted ion chromatograms in order to find a peak for the target compound in a model kerosene sample containing 254 volatile compounds with the optimization of the separation of fatty acid methyl esters. Using the simulation applications, students are able to perform experimental design in a lecture class. Test score results reveal the selectivity of the approach toward students with laboratory practical experience and experimental skills. This approach is expected to be useful to all higher education students in chemistry.

Poisonous plants are widely distributed and may have risk of phytotoxicity upon mixing with medicinal plants. Several species of Cestrum genus are poisonous and linked with many serious health issues. In the present study, cross-mixing of a toxic plant, Cestrum diurnum with morphologically resembling medicinal plant, Adhatoda vasica was studied using chemical fingerprinting approach. LC-ESI-MS/MS tool was used to develop the chemical fingerprints of three toxic species of Cestrum, including, C. diurnum, C. nocturnum and C. parqui. Total forty-three compounds were identified using high-resolution LC-ESI-MS/MS data comparison. Chemometric analyses were done to compare the distribution of identified compounds present in these Cestrum species. One of the identified compounds, nornicotine (a toxic compound) was also quantified using LC-IT-MS/MS. Adulteration study was conducted by mixing toxic C. diurnum in A. vasica with various ratios (w/w) and five differentiable compounds were identified to detect the adulteration. The method was able to detect up to the limit of 5% mixing of toxic C. diurnum. Moreover, cytotoxicity of the methanolic extracts of these three species were also studied on normal human PBMC (peripheral blood mononuclear cells) and all found to be toxic, while the C. nocturnum showed the highest level of toxicity with the IC50 12.5 μg/mL.

The resistance of wood against fungal decay, in short the natural durability, is one of the main criteria for defining the potential use of a wood species. Wood collections, or xylaria, offer the unique opportunity to screen many specimens and species for the latter purpose yet sample size is often limited and standardized tests are often not possible neither desired given the historical and cultural value of these specimens. Two different methods to determine the natural durability are tested and presented here, more specifically the mini-block test and chemical fingerprinting by Direct Analysis in Real-Time Time-Of-Flight Mass Spectrometry (DART TOFMS). Fungal decay by Trametes versicolor was determined for 577 mini-blocks collected from xylarium specimens and 602 mini-blocks from commercial species, not belonging to the xylarium collection, were included as a benchmark. Mass loss percentages of the different species are similar to reported values, supporting the use of the mini-block test when standardized testing is hardly feasible. Furthermore, as expected there is also a significantly negative relationship between density and the mass loss percentages from the mini-block test (r-Spearman = − 0.65***). Finally, partial least square-based prediction of recorded mass loss by using the DART TOFMS chemical fingerprints is promising (R2-adjusted = 0.40***), yet the accuracy differs between species.

Two-dimensional gas chromatography is a mature, yet underutilised, separation technique able to provide the high resolution and peak capacity required for the study of complex samples such as oils. This paper presents the development of a comprehensive two-dimensional gas chromatography method with flame ionisation detection to profile easily available ignitable liquids commonly found in arson cases. The use of 2D chromatograms to profile different potential ignitable liquids was also explored for classification purposes. The chemical fingerprints produced were visually different and allowed the distinction of all the petroleum products tested. How the chemical fingerprints of each fuel changed over time was also assessed. Each sample was subjected to weathering with aliquots (1 mL) being collected every half hour for a five-hour period. Principal component analysis of the resulting data was able to demonstrate the effect of weathering for all fuels tested and established that it was still possible to differentiate between the various petrochemicals even after weathering. The work demonstrates an optimised analytical method for petrochemical product analysis that provides forensic scientists with a robust, fast and sensitive technique that can be used to determine not only which ignitable liquid was used in a fire (even after the fact) but also provide information on the specific fuel used.

Aim: Earlier studies have established the antidiabetic activity of Nauclea latifolia. The aim of this study was to obtain chemical fingerprints of the ethanolic extracts of Nauclea latifolia leaf using Gas chromatography-Mass spectrometry (GC-MS), in order to assure proper identification of the plant and to evaluate its phytochemical composition using GC-MS. It was also aimed at unravelling the phytochemical constituents responsible for its antidiabetic activities. Methodology: The phytochemicals in the plant leaves were extracted by cold maceration in ethanol and subjected to GC-MS analysis. Results: Chromatograms showed 51 peaks of identified phytochemical compounds. The GC-MS analysis also revealed sixteen (16) active antidiabetic phytochemicals namely: Pentanoic acid 4-oxo- ethyl ester, 2-Methoxy-4-vinylphenol, Triethyl citrate, Quinic acid, 3-O-Methyl-d-glucose, 3,7,11,15-tetramethyl-2-hexadecen-1-ol, Phytol, Hexadecanoic acid, 9,12-octadecadienoic acid, 9,12,15-octadecatrienoic acid, Octadecanoic acid, Hexadecanoic acid 2-hydroxy-1-(hydroxymethyl) ethyl ester, Vitamin E, Campesterol, Stigmasterol, Gamma-sitosterol. Conclusion: The GC-MS profile provides a suitable chemical fingerprint to assure proper identification of the Nauclea latifolia plant. Sixteen (16) active phytochemicals of the plant leaf are known to have antidiabetic activities; these could be used as a basis for standardization of the plant preparations for diabetes therapy.

Recently, the olive oil industry has been the subject of harsh criticism for false labeling and even adulterating olive oils. This situation in which both the industry and the population are affected leads to an urgent need to increase controls to avoid fraudulent activities around this precious product. The aim of this work is to propose a new analytical platform by coupling electrospray ionization (ESI), differential mobility analysis (DMA), and mass spectrometry (MS) for the analysis of olive oils based on the information obtained from the chemical fingerprint (nontargeted analyses). Regarding the sample preparation, two approaches were proposed: (i) sample dilution and (ii) liquid-liquid extraction (LLE). To demonstrate the feasibility of the method, 30 olive oil samples in 3 different categories were analyzed, using 21 of them to elaborate the classification model and the remaining 9 to test it (blind samples). To develop the prediction model, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used. The overall success rate of the classification to differentiate among extra virgin olive oil (EVOO), virgin olive oil (VOO), and lampante olive oil (LOO) was 89% for the LLE samples and 67% for the diluted samples. However, combining both methods, the ability to differentiate EVOO from lower-quality oils (VOO and LOO) and the edible oils (EVOO and VOO) from nonedible oil (LOO) was 100%. The results show that ESI-DMA-MS can become an effective tool for the olive oil sector.

Gas chromatography system equipped with a mass selective detector was employed for chemical fingerprinting of two Niger Delta crude oils (samples A-001 and F-100) and their mixtures (samples B-208, C-406, D-604 and E-802) at different proportion. Total and individual abundances of C19 to C29 tricyclic terpanes, including C24 tetracyclic terpane, detected in the six oil samples followed similar patterns, A-001 < E-802 < F-100 < B-208 < C-406 < D-604, indicating the abundances did not mix correspondingly with the proportion of the two Niger Delta crude oils. Pearson correlation suggested sample A-001 was genetically related to sample F-100 (76.03%), and the four mixtures were significantly similar to each other (99.00% - 99.90%) and sample F-100 (99.00% - 99.81%), and similar to sample A-001 (76.02% - 81.60%). Hierarchical cluster analysis (HCA) separated the tricyclic and tetracyclic terpanes detected into 2 main groups, which distinctly differed (strong negative correlation) in the variations of their compositions in the six crude oil samples. Plots show the compositions of HCA group-A and -B tricyclic terpanes decrease as the proportion of sample A-001 decrease, and increase as the proportion of sample F-100 increase in the six crude oil samples, respectively. Values of the coefficient of determination (R²) for the tricyclic terpane plots, range from 0.1406 to 0.9113 for group-A and 0.1226 to 0.6081 for group-B, with the compositions of C21 tricyclic terpane(d) being most suitable for use to estimate (91.13%) the proportion(s) of the two Niger Delta crude oils in their mixtures. Keywords: Abundance, Correlation, Crude oil mixtures, Distribution, Niger Delta, Tricyclic terpane. Title: Chemical Fingerprinting of Tricyclic Terpanes in Two Niger Delta Crude Oils and their Mixtures Author: Mark O. Onyema International Journal of Novel Research in Civil Structural and Earth Sciences ISSN 2394-7357 Vol. 10, Issue 1, January 2023 - April 2023 Page No: 8-15 Novelty Journals Website: www.noveltyjournals.com Published Date: 25-April-2023 DOI: https://doi.org/10.5281/zenodo.7862509 Paper Download Link (Source) https://www.noveltyjournals.com/upload/paper/Chemical%20Fingerprinting%20of%20Tricyclic-25042023-3.pdf, International Journal of Novel Research in Civil Structural and Earth Sciences, ISSN 2394-7357, Novelty Journals, Website: www.noveltyjournals.com

A combinative method using high-performance liquid chromatography-electrochemical detection for fingerprinting and quantitative analysis was developed and successfully applied for the quality evaluation of Lophatherum gracile Brongn leaves collected from 21 geographical locations in China. In the fingerprint analysis, 18 common peaks were observed among the 21 samples, and 10 peaks were identified. Simultaneous quantification of the 10 components was conducted to interpret the variations in these compounds among the L. gracile Brongn leaves originating from different geographical locations. The correlation between the chromatograms and the antioxidant activities of the samples was further studied. The results indicated a linear correlation between the antioxidant activity and the total common peak areas of the fingerprints obtained by high-performance liquid chromatography-electrochemical detection. Importantly, it was found that high-performance liquid chromatography-electrochemical detection fingerprinting can not only determine the quantities of individual components present in such samples but also evaluate the antioxidant activities of the samples. The developed method is a valuable reference for the further study and development of L. gracile Brongn.

Drimys winteri J.R. Forst. & G. Forst (D.C) G. Gray, var. chilensis (canelo) is an endemic tree from Chile. Since pre-Columbian times, it has produced a fruit known as the canelo pepper, (pimienta de canelo) or Foye pepper, which can be used as a spice. The chemical and biological analysis of canelo fruits is reported for the first time in this study, that is, its phenolic fingerprinting by UHPLC-PDA- Q-orbitrap MS, the antioxidant activity, the enzymatic inhibitory activity, and its relaxation effects on rat aorta. The proximal composition and the mineral content (Ca: 1.45 ± 0.03 mg/100 g; Mg: 7.72 ± 0.03 mg/100 g; Fe: 4.54 ± 0.21 mg/100 g; Zn: 2.99 ± 0.02 mg/100 g; Mn: 1.08 ± 0.03 mg/100 g; Cu: 0.82 ± 0.02 mg/100 g; K: 53.03 ± 0.20 mg/100 g; Na: 0.087 ± 0.00 mg/100 g) are also reported. The canelo fruits showed a total phenolic content of 57.33 ± 0.82 mg GAE/g dry weight. In addition, the total flavonoid content was 38.42 ± 1.32 mg equivalent of QE/g dry weight. The antioxidant activity was evaluated by employing DPPH and ABTS methods (IC50 of 6.65 ± 0.5 and 9.5 ± 0.05 μg/mL, respectively), ORAC (25.33 ± 1.2 μmol Trolox/g dry plant) and FRAP (45.56 ± 1.32 μmol Trolox/g dry plant). The enzymatic inhibition of acetylcholinesterase, butyrylcholinesterase, and tyrosinase (IC50: 1.94 ± 0.07, 2.73 ± 0.05, and 9.92 ± 0.05 µg extract/mL, respectively) is also reported. Canelo extract led to an 89% relaxation of rat aorta. Our results confirm that D. winteri fruits are a rich source of secondary metabolites and can inhibit enzymes associated with neurodegenerative diseases; the results also suggest that canelo may induce a potentially hypotensive effect in rat aorta. The study demonstrates the medicinal properties of canelo fruit and spice.

Accurate characterization of technologically relevant materials, particularly through spectroscopic techniques, necessitates the availability of reference information. However for electron energy-loss spectroscopy (EELS), reference spectra in the form of chemical fingerprints of even common polymers are not readily available. Here, the chemical fingerprints of polymers, which have been generated through EELS, can be used for the identification and compositional analysis of polymeric materials by chemical bond mapping with nanoscale spatial resolution. Electron energy-loss spectra of polyvinyl acetate (PVAc) and polycarbonate (PC), including the low-loss region and core-loss edges of carbon and oxygen, are reported. Additionally, decomposition of the carbon K-edge fine-structure of both polymers was performed and the observed peaks were assigned to bonding transitions. The carbon K-edge from low energy resolution spectra was also analyzed to address the challenges associated with the processing of easily available low energy resolution EELS data. This work demonstrates the high sensitivity of EELS towards identification of changes in the chemical structure of polymeric materials, which highlights its potential for wider applicability in polymer science.

The use of performance-enhancing drugs is prohibited in sports competitions according to the World Anti-Doping Agency (WADA) regulations. Here, ATR-FTIR spectroscopy coupled with a partial least squares regression (PLSR) chemometric tool was used for the detection of the misuse of such substances. Bambuterol and its metabolite terbutaline have been included in the list of prohibited doping agents. Therefore, we used bambuterol and terbutaline as models for the accurate and simultaneous qualitative and quantitative analysis of bambuterol and terbutaline in human urine samples. The method was straightforward and once the urine samples were collected, they could be directly applied to the surface of the ZnSe prism (ATR unit) to get the results within one minute. A calibration set with a partial factorial design was used to develop the PLSR model that could be used to predict the concentration of unknown samples containing the two drugs. The developed method was carefully validated and successfully applied to the urine sample analysis of human volunteers. The drugs were quantified at nanogram level concentrations. A side-by-side comparison of the proposed method with the routine GC-MS method was performed to demonstrate the challenges and opportunities of each method.

Introduction Polygoni Orientalis Fructus (POF) is a clinically effective Chinese medicine. Raw POF (RPOF) and POF Tostus (POFT) are used separately in clinics. However, incomplete progress has been made on quality control. Objective To establish a comprehensive method for quality assessment of RPOF and POFT and to discriminate these two varieties. Methodology High-performance liquid chromatography combined with the diode array detector (HPLC-DAD) methods were developed for fingerprinting and quantitative analysis of seven major compounds in RPOF and POFT, and the main components were determined by HPLC-DAD coupled with Fourier-transform ion cyclotron resonance-mass spectrometry. Chemometric approaches were performed to discriminate RPOF and POFT and to screen discriminatory components. Results Fingerprints were established and 12 common peaks were identified, cannabisin G and cannabisin E were firstly identified from POF. In quantitative analysis, all analytes showed good regression (R > 0.9996) within test ranges and the recovery of the method was in the range 96.6-104.3%. Fingerprints in conjunction with similarity analysis and hierarchical clustering analysis (HCA) demonstrated the consistent quality of RPOF and showed a clear discrimination between RPOF and POFT. Principal component analysis, partial least-squares discriminant analysis, and heatmap-HCA on quantitative data not only gave a clear differentiation between RPOF and POFT, but they also suggested that quercetin, 3,5,7-trihydroxychromone, and N-trans-feruloyltyramine acted as the main factors responsible for the sample differences. Conclusions Chromatographic analysis in combination with chemometric analysis provides a simple and reliable method of comparing and evaluating the qualities of RPOF and POFT.

Many phytochemicals have medicinal properties including anti-inflammatory, antioxidant and cytotoxic activities. The current study aims to estimate and identify the chemical composition of Calamintha fenzlii Vis. leaves volatile oil and to evaluate its cytotoxic, anti-inflammatory and antioxidant properties. The volatile oil (VO) of C. fenzlii leaves was separated using microwave ultrasonic method and the chemical composition was characterized using Gas Chromatography–Mass Spectroscopy method. The anti-inflammatory, antioxidant and cytotoxic activities were determined using a COX inhibitor screening, the DPPH-free radical scavenging and MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-cyrboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt) cell viability colorimetric assays, respectively. The chemical constituents of C. fenzlii VO were dominated by oxygenated monoterpenoid (96.91%). The major chemical components of C. fenzlii VO were represented by menthone 68.93% and pulegone 23.1%. The cytotoxicity test results revealed that the 23.22, 11.6, 5.8 and 2.9 mg/ml of C. fenzlii VO treatments induced cell death significantly (p ≤ 0.0001) by 70%, while 1.4 and 0.7 mg/ml induced cell cytotoxicity significantly (p ≤ 0.0001) by approximately 50% and 40%, respectively. The VO showed moderate antioxidant activity with an IC50 value of 15.38 ± 0.81 µg/ml. The COX-1 IC50 value was 0.215 µg/ml, while COX-2 IC50 was 0.241 µg/ml. Our data demonstrate for the first time that the VO of the Palestinian C. fenzlii plant possesses cytotoxic, anti-inflammatory and antioxidants effects. It is a good source of therapeutic active compounds that could have potential applications in the nutraceutical and pharmaceutical industries.

Demantoid garnets are among the most valuable gemstones in the world and their prices vary depending on the location they are found. Thus, a reference set of stones with known origins was assembled and their chemical composition analyzed with laser ablation—inductively coupled plasma mass spectrometry. It was shown that the three major sources, Russia, Namibia, and Madagascar, could be distinguished by using a plot of the manganese/titanium ratio versus the sum of chromium and vanadium in combination with the aluminum content. Even within Russia it was possible to separate some deposits using elemental composition despite some stones having color zones and therefore a varying concentration of some elements.

A frequent goal of chemical forensic analyses is to select a panel of diagnostic chemical features─colloquially termed a chemical fingerprint─that can predict the presence of a source in a novel sample. However, most of the developed chemical fingerprinting workflows are qualitative in nature. Herein, we report on a quantitative machine learning workflow. Grab samples (

Background Serious infections caused by bacteria and their resistance to antibiotics are one of the biggest healthcare threats to mankind. Therefore, the present study aimed to isolate endophytes from medicinal plant Ampelopsis grossedentata, an endemic species of Western Hubei, China and to investigate its antibacterial efficacy and chemical diversity of the secondary metabolites. Methods The antibacterial potential of the endophytes was evaluated by disc diffusion method against a panel of eleven type strains and some multidrug resistant pathogenic bacteria. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were estimated by broth microdilution using iodonitrotetrazolium chloride assay. Further, the chemical diversity of the metabolites was estimated using LC-Q-TOF-MS/MS and GC–MS fingerprinting. Results Four endophytic fungi were isolated from the tender shoot of A. grossedentata; they were identified as Fusarium graminearum TC-1, Phomopsis mali TC-3, Pestalotiopsis maculans TC-5 and Alternaria alternata TC-11. Among the endophytes screened, A. alternata TC-11 exhibited significant antibacterial activity with the zones of inhibition ranging from 13.72 ± 0.30 to 21.76 ± 0.53 mm against all the tested type strains and multidrug resistant bacterial pathogens. Further, it showed significant antibacterial activity with MIC values ranging from 0.37 to 3.00 μg/mL. The combined LC-Q-TOF-MS/MS and GC–MS analyses of active extract revealed that alternarian acid, altertenuol, dimethyl sulfone, docosane, dodecane, duclauxin, ergosta-4,6,8(14),22-tetraen-3-one, ethyl 6-cyano-5-oxo-1-phenyl-7-thiophen-2-yl-[1,2,4]triazolo[4,3-a]pyrimidine-3-carboxylate, heptacosane, linoleic acid, neodecanoic acid, oxiranylmethyl ester, pentadecane, verrulactone E, 2,6,11-Trimethyldodecane and 4-[(E,4R,6R)-11-(furan-3-yl)-6-hydroxy-4,8-dimethylundec-8-enyl]-2-hydroxy-2H-furan-5-one were the most abundant compounds present which were responsible for the significant antibacterial activity. Conclusions To our knowledge, this is the first report of fungal endophytes isolated from the tender shoot of A. grossedentata with bacteriostatic and bactericidal activities. Our finding provides a new insight into the antibacterial potential of endophytes and envisages the possibility of using them for drug discovery.

The adulteration of plant raw materials used for the preparation of herbal drugs with foreign plant material is one of the important issues in the quality control of herbal products. Chemical fingerprinting is a well-known approach for the characterization of secondary metabolites associated with the plant species and can be used for quality control of plant material. The current study centred on the development of chemical fingerprinting of three medicinal plants of genus Anemone including A. obtusiloba, A. falconeri and A tetrasepala through identification of their metabolites using LC-ESI-QTOF-MS/MS analysis. Thirty compounds were identified by using high-resolution positive and negative electrospray- ionization (ESI) modes and MS/MS analysis. The identified compounds belong to diterpenoids, alkaloids, phenols, flavonoids and other classes and their distribution among the analysed species was studied using different statistical tools. Moreover, an LC-HR-ESI-MS/MS method was developed to detect the cross mixing of A. obtusiloba with Ziziphus jujuba. Seven chromatographically differentiative peaks confined to A. obtusiloba were selected to detect its contamination in adulterated samples. The method was able to detect as low as 20% mixing of A. obtusiloba in Z. jujuba. This study can play a significant role to manage the quality control of herbal medicines and to identify lead natural products of these plants.

Wildfires are an increasing problem worldwide, with their number and intensity predicted to rise due to climate change. When fires occur close to vineyards, this can result in grapevine smoke contamination and, subsequently, the development of smoke taint in wine. Currently, there are no in-field detection systems that growers can use to assess whether their grapevines have been contaminated by smoke. This study evaluated the use of near-infrared (NIR) spectroscopy as a chemical fingerprinting tool, coupled with machine learning, to create a rapid, non-destructive in-field detection system for assessing grapevine smoke contamination. Two artificial neural network models were developed using grapevine leaf spectra (Model 1) and grape spectra (Model 2) as inputs, and smoke treatments as targets. Both models displayed high overall accuracies in classifying the spectral readings according to the smoking treatments (Model 1: 98.00%, Model 2: 97.40%). Ultraviolet to visible spectroscopy was also used to assess the physiological performance and senescence of leaves, and the degree of ripening and anthocyanin content of grapes. The results showed that chemical fingerprinting and machine learning might offer a rapid, in-field detection system for grapevine smoke contamination that will enable growers to make timely decisions following a bushfire event, e.g., avoiding harvest of heavily contaminated grapes for winemaking or assisting with a sample collection of grapes for chemical analysis of smoke taint markers.

Jojoba (Simmondsia chinensis) is an important commercial shrub. Concerns have been raised about the availability of the good raw material for various industries to lower down the costs of products. Seed planted populations are highly variable in yields and growth habits. For this reason, there is need to develop a selection programs that improves the crop productivity of good quality seed plants. Jojoba industry, mainly depends on its oil, but the remaining seed meal is also useful for various industries like cosmetics, animal fodder, bio fuel etc. In the present study 14 different accessions of jojoba are used for the chemical and molecular fingerprinting. Chemical fingerprinting of jojoba includes both nutritional (Carbohydrate, protein, polyphenol, aminoacids, antioxidants) as well as antinutritional factor (Simmondsin). Simmondsin content was analyzed by using HPLC (High Performance Liquid Chromatography) technique. Molecular fingerprinting was done by using ISSR (Inter Simple Sequence Repeat) molecular markers. Finally the correlation of molecular and chemical fingerpring data showed that accession Clone-64 having highest nutritional value and formed a separate OTU (Operational Taxonomic Unit) in dendrogram. Thus, this accession could be good candidates for different commercial applications. Our data strongly suggest that cumulative approach (molecular and chemical fingerprinting) proved to be best for accessing, the relationship between different accessions of jojoba in future breeding programs.

Identification of humic-like substances (HULIS) structures and components is still a major challenge owing to their chemical complexity. This study first employed a complementary method with the combination of two-dimensional gas chromatography-time-of-flight mass spectrometry and liquid chromatography-quadrupole-time-of-flight mass spectrometry to address low-polarity and polar components of HULIS in PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm), respectively. The combination method showed a significant correlation in identifying overlapping species and performed well in uncovering the chemical complexity of HULIS. A total of 1246 compound species in HULIS (65.6-81.0% for each sample), approximately 1 order of magnitude more compounds than that reported in previous studies, were addressed in PM2.5 collected in real-world household biomass and coal combustion. Aromatics were the most abundant compounds (37.4-64.1% in biomass and 34.5-70.0% in coal samples) of the total mass in all HULIS samples according to carbon skeleton determination, while the major components included phenols (2.6-21.1%), ketones (6.0-17.1%), aldehydes (1.1-6.8%), esters (2.9-20.0%), amines/amides (3.2-8.5%), alcohols (3.8-17.0%), and acids (4.7-15.1%). Among the identified HULIS species, 11-36% mass in biomass and 11-41% in coal were chromophores, while another 22-35 and 23-29% mass were chromophore precursors, respectively. The combination method shows promise for uncovering HULIS fingerprinting.

Dental diseases are one of the significant public health problems globally. Herbal medicines for managing oral diseases are considered an effective alternative to synthetic compounds due to their lower side effect. Acacia catechu, Piper nigrum, Piper longum, and Piper cubeba are vital components of Dasanakanthi Churnam used to control and prevent oral inflammations in dentistry. Tannic acid and Piperine are major markers for the chemical fingerprinting of Dasanakanthi Churnam. They serve as quality indicating parameters for Dasanakanthi Churnam because of their pharmacological action. Development and validation of a stability-indicating assay method using RP-HPLC become an integral part of simultaneous estimation of Tannic acid and Piperine in Dasanakanthi Churnam. Stability indicating the method is established by exposing markers to various stress conditions such as alkaline hydrolysis, photolytic, oxidative and thermal conditions. Stress testing of the markers can help identify the likely degradation products and validate the stability indicating the power of the analytical procedures used. Tannic acid and Piperine were effectively separated at 5.2 and 22.5 minutes respectively using a PDA detector without interference from any degradant and impurities. This research gives a scope to further carry out the stability studies such as accelerated, intermediate, and long-term studies for Dasanakanthi Churnam.

With the large-scale development of drugs, understanding the drug phase behaviors in complex systems become increasingly important. Among them, the solubility of drugs in biorelevant media needs to be urgently understood. To address this challenge, new strategies based on machine learning models are proposed. First, the strategy trains five machine learning models based on fifteen molecular descriptors of the drug molecular properties. The XGboost model was identified as the best predictive model for predicting drug solubility performance in various solvents. Next, the input feature vectors were expanded for machine learning using the MACCS chemical fingerprint coupled with the XGboost model. The MACCS chemical fingerprint coupled with the XGboost model has significantly improved the prediction accuracy of drug solubility. This finding demonstrates that the proposed strategy has solubility prediction capability, which is expected to provide valid information for drug development and drug solvent screening.

Important wine quality traits such as sensory profile and color are the product of complex interactions between the soil, grapevine, the environment, management, and winemaking practices. Artificial intelligence (AI) and specifically machine learning (ML) could offer powerful tools to assess these complex interactions and their patterns through seasons to predict quality traits to winegrowers close to harvest and before winemaking. This study considered nine vintages (2008&ndash, 2016) using near-infrared spectroscopy (NIR) of wines and corresponding weather and management information as inputs for artificial neural network (ANN) modeling of sensory profiles (Models 1 and 2 respectively). Furthermore, weather and management data were used as inputs to predict the color of wines (Model 3). Results showed high accuracy in the prediction of sensory profiles of vertical wine vintages using NIR (Model 1, R = 0.92, slope = 0.85), while better models were obtained using weather/management data for the prediction of sensory profiles (Model 2, R = 0.98, slope = 0.93) and wine color (Model 3, R = 0.99, slope = 0.98). For all models, there was no indication of overfitting as per ANN specific tests. These models may be used as powerful tools to winegrowers and winemakers close to harvest and before the winemaking process to maintain a determined wine style with high quality and acceptability by consumers.

Telomere maintenance by telomerase activity supports the infinite growth of cancer cells. MST-312, a synthetic telomerase inhibitor, gradually shortens telomeres at non-acute lethal doses and eventually induces senescence and apoptosis of telomerase-positive cancer cells. Here we report that MST-312 at higher doses works as a dual inhibitor of telomerase and DNA topoisomerase II and exhibits acute anti-proliferative effects on cancer cells and xenografted tumours in vivo. Our cell-based chemical fingerprinting approach revealed that cancer cells with shorter telomeres and lower expression of lamin A, a nuclear architectural protein, exhibited higher sensitivity to the acute deleterious effects of MST-312, accompanied by formation of telomere dysfunction-induced foci and DNA double-strand breaks. Telomere elongation and lamin A overexpression attenuated telomeric and non-telomeric DNA damage, respectively, and both conferred resistance to apoptosis induced by MST-312 and other DNA damaging anticancer agents. These observations suggest that sufficient pools of telomeres and a nuclear lamina component contribute to the cellular robustness against DNA damage induced by therapeutic treatment in human cancer cells.

Safflower Injection is one kind of injections derived from traditional Chinese medicine. It is widely applied to treat cerebrovascular diseases such as acute cerebral infarction, stroke, coronary heart disease, and angiitis. However, most adverse reactions of Safflower Injection in clinic are caused by its quality problems. In this study, 10 batches of normal and 42 batches of abnormal Safflower Injections were obtained from the clinical practice. Their quality fluctuations were detected by chemical fingerprinting (CF, ultra-performance liquid chromatography tandem mass spectrometry) and bioassays including cell-based biological profile (CBP) assay and enzymatic assay. CF identified 33 compounds in the Safflower Injections, and scutellarin and kaempferol-3-O-rutinoside were identified to be the possible components responsible for clinical adverse reaction. In addition, 59.5% (25/42), 85.7% (36/42) and 38.1% (16/42) of abnormal samples could be identified by CF, CBP assay and enzymatic assay, respectively. Interestingly, further integration of the three methods could entirely identify all the abnormal samples. It indicated that it is advisable to integrate CF, CBP assay and enzymatic assay for developing quality standard of Safflower Injections.

Aneura pinguis (L.) Dumort. is a representative of the simple thalloid liverworts, one of the three main types of liverwort gametophytes. According to classical taxonomy, A. pinguis represents one morphologically variable species, however, genetic data reveal that this species is a complex consisting of 10 cryptic species (named by letters from A to J), of which four are further subdivided into two or three evolutionary lineages. The objective of this work was to develop an efficient method for the characterisation of plant material using marker compounds. The volatile chemical constituents of cryptic species within the liverwort A. pinguis were analysed by GC-MS. The compounds were isolated from plant material using the HS-SPME technique. Of the 66 compounds examined, 40 were identified. Of these 40 compounds, nine were selected for use as marker compounds of individual cryptic species of A. pinguis. A guide was then developed that clarified how these markers could be used for the rapid identification of the genetic lineages of A. pinguis. Multivariate statistical analyses (principal component and cluster analysis) revealed that the chemical compounds in A. pinguis made it possible to distinguish individual cryptic species (including genetic lineages), with the exception of cryptic species G and H. The classification of samples based on the volatile compounds by cluster analysis reflected phylogenetic relationships between cryptic species and genetic lineages of A. pinguis revealed based on molecular data.

The genus Coccoloba (Polygonaceae) comprises approximately 150 species of flowering plants. It is native to the tropical and subtropical regions of America, in South America, the Caribbean and Central America. A wide variety of biological activities has been studied for Coccoloba species due to great diversity of metabolites (mainly flavonoids, tannins, terpenoids and volatile oils) and popular uses reported for different ailments like fever, diarrhea, menstrual disturbance, uterine hemorrhages, hemorrhoids and gonorrhea. The methanolic extract of the leaves of C. cowellii, endemic of the Camaguey province of Cuba and critically endangered, was subjected to structural analysis. The obtained HPLC-DAD-QTOF-ESI-MS data were analyzed employing the MS-DIAL software. A dereplication of the ESI-MS data was realized using the feature-based molecular networking (FBMN) analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure, leading to 12 compound hits against the GNPS database. A total of 13 compounds were tentatively identified by means of MS data, together with the interpretation of the observed MS/MS spectra in comparison with those found in the literature. The major compounds were myricetin and quercetin glucuronides and glycosides and epichatechin-3-O-gallate. The total extract presented an antifungal effect against Candida albicans ATCC B59630 (azole-resistant) (IC50 = 2.13 µg/mL) and was not cytotoxic (IC50 > 64.00 µg/mL) in the resazurin MRC-5 SV2 cell viability assay employed. This is the first report related to chemical composition of C. cowellii plant. The research is now focused on determining the secondary metabolites responsible for the antifungal activity of the total extract.

Sarsaparilla is a popular natural health product (NHP) that has been reported to be one of the most adulterated botanicals in the marketplace. Several plausible explanations are documented including economically motivated product substitution, unintentional errors due to ambiguous trade name associated with several different taxa, and wild harvesting of incorrect non-commercial plants. Unfortunately, this includes the case of an adulterant species Decalepis hamiltonii, a Red listed medicinal plant species by the International Union for Conservation of Nature (IUCN) and declared as a species with high conservation concern by the National Biodiversity Authority of India (NBA). This study provides validated genomic (genome skimming & DNA probes) and metabolomic (NMR chemical fingerprints) biotechnology solutions to prevent adulteration on both raw materials and finished products. This is also the first use of Oxford Nanopore on herbal products enabling the use of genome skimming as a tool for quality assurance within the supply chain of botanical ingredients. The validation of both genomics and metabolomics approach provided quality assurance perspective for both product identity and purity. This research enables manufactures and retailers to verify their supply chain is authentic and that consumers can enjoy safe, healthy products.

Heliotropium taltalense is an endemic species of the northern coast of Chile and is used as folk medicine. The polyphenolic composition of the methanolic and aqueous extract of the endemic Chilean species was investigated using Ultrahigh-Performance Liquid Chromatography, Heated Electrospray Ionization and Mass Spectrometry (UHPLC-Orbitrap-HESI-MS). Fifty-three compounds were detected, mainly derivatives of benzoic acid, flavonoids, and some phenolic acids. Furthermore, five major compounds were isolated by column chromatography from the extract, including four flavonoids and one geranyl benzoic acid derivative, which showed vascular relaxation and were in part responsible for the activity of the extracts. Since aqueous extract of H. taltalense (83% &plusmn, 9%, 100 &mu, g/mL) produced vascular relaxation through an endothelium-dependent mechanism in rat aorta, and the compounds rhamnocitrin (89% &plusmn, 7%, 10&minus, 4 M) and sakuranetin (80% &plusmn, 6%, 4 M) also caused vascular relaxation similar to the extracts of H. taltalense, these pure compounds are, to some extent, responsible for the vascular relaxation.

The development of digital tools based on artificial intelligence can produce affordable and accurate methodologies to assess quality traits and sensory analysis of beers. These new and emerging technologies can also assess new products in a near real-time fashion through virtual simulations before the brewing process. This research was based on the development of specific digital tools (four models) to assess quality traits and sensory profiles of beers produced using sonication and traditional brewing techniques. Results showed that models developed using supervised machine learning (ML) regression algorithms based on near-infrared spectroscopy (NIR) were highly accurate in the estimation of physicochemical parameters (Model 1; R = 0.94; b = 0.91). Outputs from Model 1 were then used as inputs to obtain estimations of the intensity of sensory descriptors (Model 2; R = 0.99; b = 0.98), liking of sensory attributes (Model 3; R = 0.97; b = 0.99), and the classification of fermentation treatments using supervised classification ML algorithms (Model 4; 96% accuracy). These new digital tools can aid craft brewing companies for product development at lower costs and maintain specific quality traits and sensory profiles, creating original styles of beers to get positioned in the market.

Consumables-from food to pharmaceuticals and supplements-are becoming increasingly vulnerable to various modes of counterfeiting due to the growing complexity of their supply chain. Mislabeling, re-branding, and false advertising are prevalent in this sector. Existing physical authentication techniques fail to adequately verify integrity of these products and protect the end-users. In this paper, we aim at addressing this critical problem through the development of a novel authentication solution. It builds on the chemical analysis properties of a powerful spectroscopy technique, namely, nuclear quadrupole resonance (NQR) that is quantitative, non-invasive, low-cost, and amenable for miniaturization (to hand-held form factors). The method is sensitive to small variations in the solid-state chemical structure of a sample, which change the NQR signal properties. These attributes can be unique for various manufacturers, enabling their use as manufacturer-specific watermarks. However, NQR spectroscopy only works reliably (i.e., provides good sensitivity) on compounds that contain certain nuclear isotopes. We take advantage of the intrinsic properties of NQR-sensitive isotopes to use them as extrinsic tags in NQR-insensitive products. The NQR spectra of these extrinsic tags act as unique watermarks that can be analyzed using machine learning methods to authenticate any consumable with high confidence. In particular, we use support vector machines to classify the measured spectra and confirm the identity of items under test. We have assessed this approach on a variety of consumables utilizing semi-custom equipment and verified that it results in high (>95%) classification accuracy. In order to prove the unclonability of such extrinsic tags, we have also performed a mathematical analysis that proves the randomness of the extrinsic tag and confirms its robustness to brute-force attacks.

The 20.000 km2 swamp of the Delta is organized into islands, flood plains and permanent and seasonal channels. Most of these islands display a surprising vegetation distribution composed of tree rings surrounding the islands and limiting an inner domain with scarce vegetation. Whereas the hydrology of the Okanvango wetlands is governed by a series of drivers such as, sedimentation, climate, tectonic and biological processes, the potential of the use of multi-chemical tracing has not been so far much investigated. The conducted study as part of a multidisciplinary project dedicated to the understanding of the functioning of the Delta, involved water samples collected both upstream and downsream the river, close to one of these islands and also recovered within the island as well. The main objective of this geochemical investigation was to better constrain the interactions prevailing in between these islands and the water chemical record. pH, conductivity (C), dissolved organic and inorganic carbon (DOC & DIC) concentrations were measured as well as those of major anion and cation and trace cation concentrations as well. Whichever the tracers are considered, two contrasted groups of samples were evidenced depending on their sampling positioning regarding the island. The samples recovered only within the island displayed pH around and over 9 and higher conductivities, whereas the other showed lower circumneutral pH values and conductivities as well. The high conductivities of the water samples fom the island also correspond to the highest DOC and DIC concentrations. The strong relationship linking the high DIC values and the high pH in the island samples records probably alkaline CO32- et HCO3- -rich waters resulting from water-rock interactions with carbonates. The marked DOC enrichment has mostly to be related to microbial or photo-degradation of plant-derived organic matter and/or hydrological condition variations promoting DOC release. Significant, Cl-, SO42-, NO2-enrichments as well as major cation ones were also evidenced in the same group of samples within the island. However, the most surprising results are sourced in the trace element fingerprinting. This latter includes huge enrichment in heavy, critical metals and metalloids as well (e.g. Cr, Pb, V, REE, U, Th or As). Beyond the only marked REE-spike, Upper Continental Crust-normalized REE patterns displayed markedly contrasted shapes exhibiting two types of waters with circumneutral pH ones with MREE-enrichment, whereas the alkaline waters evidenced a classical continuous enrichment throughout the whole series from LREE to HREE and a positive Ce anomaly. The use of such multi-tracing allowed an efficient fingerprinting of two distint types of waters to get clues to further constrain both the dynamics of such islands and the functioning of the water system. Still in progress, the study will be completed by (i) the stable isotope analysis, (ii) the modeling of the minerals possibly at equilibrium with the waters and of the organic matter-trace element interactions, (iii) the speciation analysis of some enriched elements, (iv) the comparison between water and solid samples analyses and (v) the understanding of the relations in between the concentrations and locations in the hydrological system.

Emerging evidence has revealed the functional characteristics of black pepper extracts for both nutritional and medicinal purposes. The medicinal properties of this important commodity crop are due to the presence of active piperine which it a viable drug potential in ethnomedicine for the treatment of many degenerative free-radical related diseases. In this study, the microwave-enhanced technique was employed in the extraction of alkaloid oleoresins at optimum condition. The metabolomics-based approach was employed to determine the alkaloid profiles using LC-MS-Quadrupled time of flight mass spectrometer. At optimum microwave condition, a total of 21 bioactive alkaloids were identified with piperine being the most abundant with a mass to charge ratio of 286.1442 m/z. The result from the SEM-monograph and BET-surface characterization showed a remarkable transformation in the micro-cellular matrix as a result of the applied microwave electromagnetic heating.

The viability of cells for drug screening purposes is usually tested with a variety of colorimetric/fluorescent methods In this work, two alternative ways of assessing toxic effect in cell cultures: sequential injection analysis (SIA) electronic tongue and soft-sensor based on 2D fluorescence have been evaluated and compared as novel, rapid techniques for cell culture monitoring. It is shown, that the proposed non-selective methods, which are based on sample fingerprinting, are capable of cytotoxic effect detection and incubation time estimation in a model experiment considering the treatment of various cell lines with a model drug − diclofenac. It affected the metabolic activity of the cells in a concentration- and time-dependent manner resulting in varying amounts of necrotic, early apoptotic and late apoptotic cells. These phenomena could have been revealed with the use of both non-selective analytical systems based on the extraction of useful information from sample fingerprints by multivariate data analysis procedures. This proves that the proposed methods can be used for fast and reliable cell culture monitoring which potentially can be also non-invasive.

The lichen species Cladonia chlorophaea and C. gracilis (Cladoniaceae) are widely distributed in the island archipelago of maritime Antarctica and represent a natural resource of scientific interest. In this work, the metabolomic characterization of the ethanolic extracts of these species and the determination of the antioxidant activity, enzymatic inhibition and anti-inflammatory potential of selected compounds on the 5-lipoxygenase enzyme by molecular docking and cytoprotective activity in the SH-SY5Y cell line were carried out. Nineteen compounds were identified by liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS) in each of the species. The contents of phenolic compounds, antioxidant activity, the inhibition of cholinesterases (acetylcholinesterase and butyrylcholinesterase) and digestive enzymes (α-glucosidase and pancreatic lipase) were variable among species, with better results in C. chlorophaea. Molecular docking evidenced significant binding affinities of some compounds for the 5-lipoxygenase enzyme, together with outstanding pharmacokinetic properties. Both extracts were shown to promote cell viability and a reduction in reactive oxygen species production in an H2O2-induced oxidative stress model. This study contributes to the chemical knowledge of the Cladonia species and demonstrates the biological potential for the prevention and promising treatment of central nervous system pathologies, inflammatory disorders and metabolic alterations.

Calea pinnatifida (R. Br.) Less. is a plant of Brazilian folk medicine. We evaluated the influence of environmental factors on the chemical profile of C. pinnatifida collected during the winter season. C. pinnatifida leaves, alongside soil samples, were collected from two sites of different altitude. Plant samples were sequentially extracted, while soil samples were subject to compositional analysis. Plant extracts were compared using HPTLC-UV, using chemometric analyses to compare samplings harvested at both altitudes. Two marker metabolites, calein A (1) and acetylportentol (2), were isolated from samples collected at the respective altitudes. The differing metabolic profiles observed may be a result of the influence of environmental factors.

We present machine learning models trained on experimental data to predict room-temperature solubility for any polymer-solvent pair. The new models are a significant advancement over past data-driven work, in terms of protocol, validity, and versatility. A generalizable fingerprinting method is used for the polymers and solvents, making it possible, in principle, to handle any polymer-solvent combination. Our data-driven approach achieves high accuracy when either both the polymer and solvent or just the polymer has been seen during the training phase. Model performance is modest though when a solvent (in a newly queried polymer-solvent pair) is not part of the training set. This is likely because the number of unique solvents in our data set is small (much smaller than the number of polymers). Nevertheless, as the data set increases in size, especially as the solvent set becomes more diverse, the overall predictive performance is expected to improve.

Berry cell death assessment can become one of the most objective parameters to assess important berry quality traits, such as aroma profiles that can be passed to the wine in the winemaking process. At the moment, the only practical tool to assess berry cell death in the field is using portable near-infrared spectroscopy (NIR) and machine learning (ML) models. This research tested the NIR and ML approach and developed supervised regression ML models using Shiraz and Chardonnay berries and wines from a vineyard located in Yarra Valley, Victoria, Australia. An ML model was developed using NIR measurements from intact berries as inputs to estimate berry cell death (BCD), living tissue (LT) (Model 1). Furthermore, canopy architecture parameters obtained from cover photography of grapevine canopies and computer vision analysis were also tested as inputs to develop ML models to assess BCD and LT (Model 2) and the intensity of sensory descriptors based on visual and aroma profiles of wines for Chardonnay (Model 3) and Shiraz (Model 4). The results showed high accuracy and performance of models developed based on correlation coefficient (R) and slope (b) (M1: R = 0.87, b = 0.82, M2: R = 0.98, b = 0.93, M3: R = 0.99, b = 0.99, M4: R = 0.99, b = 1.00). Models developed based on canopy architecture, and computer vision can be used to automatically estimate the vigor and berry and wine quality traits using proximal remote sensing and with visible cameras as the payload of unmanned aerial vehicles (UAV).

Gaultheria pumila (Ericaceae) (known as Chaura or Mutilla) is a Chilean native small shrub that produces berry fruits consumed by local Mapuche people. In this study, the chemical fingerprinting and antioxidant, enzyme inhibition, and antiproliferative activities of the berries were investigated for the first time. Thirty-six metabolites were identified in the fruits by ultra-high performance liquid chromatography-photodiode array detection, hyphenated with Orbitrap mass spectrometry analysis (UHPLC-DAD-Orbitrap-MS). Metabolites, included anthocyanins, phenolic acids, flavonoids, iridoids, diterpenes, and fatty acids. Moderate inhibitory activities against acetylcholinesterase (7.7 ± 0.3 µg/mL), butyrylcholinesterase (34.5 ± 0.5 µg/mL), and tyrosinase (3.3 ± 0.2 µg/mL) enzymes were found. Moreover, selected major compounds were subjected to docking assays in light of their experimental inhibition. Results indicated that hydrogen bonding, π–π interaction, and a salt bridge interaction contributed significantly. Gaultheria pumila berries showed a total phenolic content of 189.2 ± 0.2 mg of gallic acid equivalents/g, total flavonoid content of 51.8 ± 0.1 mg quercetin equivalents/g, and total anthocyanin content of 47.3 ± 0.2 mg of cianydin-3-glucoside equivalents/g. Antioxidant activity was assessed using DPPH (92.8 ± 0.1 µg/mL), FRAP (134.1 ± 0.1 μmol Trolox equivalents/g), and ORAC (4251.6 ± 16.9 μmol Trolox equivalents/g) assays. Conversely, Gaultheria pumila showed a scarce antiproliferative potential against several solid human cancer cells. Our findings suggest that Gaultheria pumila berries have several bioactive metabolites with inhibitory effects against acetylcholinesterase, butyrylcholinesterase, and tyrosinase, and have the potential for use in food supplements.