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The genus Coffea is known for the two species C. arabica (CA) and C. canephora (CC), which are used to prepare the beverage coffee. Proper identification of green beans of coffee varieties is based on phenotypic and phytochemical/molecular characteristics. In this work, a combination of chemical (UV/Vis, HPLC-DAD–MS/MS, GC–MS, and GC-FID) and molecular (PCR-RFLP) fingerprinting was used to discriminate commercial green coffee accessions from different geographical origin. The highest content of polyphenols and flavonoids was always found in CC accessions, whereas CA showed lower values. ABTS and FRAP assays showed a significant correlation between phenolic content and antioxidant activity in most CC accessions. We identified 32 different compounds, including 28 flavonoids and four N-containing compounds. The highest contents of caffeine and melatonin were detected in CC accessions, whereas the highest levels of quercetin and kaempferol derivatives were found in CA accessions. Fatty acids of CC accessions were characterized by low levels of linoleic and cis octadecenoic acid and high amounts of elaidic acid and myristic acid. Discrimination of species according to their geographical origin was achieved using high-throughput data analysis, combining all measured parameters. Lastly, PCR-RFLP analysis was instrumental for the identification of recognition markers for the majority of accessions. Using the restriction enzyme AluI on the trnL-trnF region, we clearly discriminated C. canephora from C. arabica, whereas the cleavage performed by the restriction enzymes MseI and XholI on the 5S-rRNA-NTS region produced specific discrimination patterns useful for the correct identification of the different coffee accessions. This work extends our previous studies and provides new information on the complete flavonoid profile, combining high-throughput data with DNA fingerprinting to assess the geographical discrimination of green coffee.

The surge in electronic cigarette (e-cig) use in recent years has raised questions on chemical exposures that may result from vaping. Previous studies have focused on measuring known toxicants, particularly those present in traditional cigarettes, while fewer have investigated unknown compounds and transformation products formed during the vaping process in these diverse and constantly evolving products. The primary aim of this work was to apply liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemical fingerprinting techniques for the characterization of e-liquids and aerosols from a selection of popular e-cig products. We conducted nontarget and quantitative analyses of tobacco-flavored e-liquids and aerosols generated using four popular e-cig products: one disposable, two pod, and one tank/mod. Aerosols were collected using a condensation device and analyzed in solution alongside e-liquids by LC-HRMS. The number of compounds detected increased from e-liquids to aerosols in three of four commercial products, as did the proportion of condensed-hydrocarbon-like compounds, associated with combustion. Kendrick mass defect analysis suggested that some of the additional compounds detected in aerosols belonged to homologous series resulting from decomposition of high-molecular-weight compounds during vaping. Lipids in inhalable aerosols have been associated with severe respiratory effects, and lipid-like compounds were observed in aerosols as well as e-liquids analyzed. Six potentially hazardous additives and contaminants, including the industrial chemical tributylphosphine oxide and the stimulant caffeine, were identified and quantified in the e-cig liquids and aerosols analyzed. The obtained findings demonstrate the potential of nontarget LC-HRMS to identify previously unknown compounds and compound classes in e-cig liquids and aerosols, which is critical for the assessment of chemical exposures resulting from vaping.

Invasive alien species are non-native plant species that displace native species and pose adverse effects to en¬vironment, ecosystem, economy, and human health by diminishing the growth of native plants and by exhibiting higher stress tolerance. In our present study, four invasive alien species, namely Lantana camara, Parthenium hysterophorous, Ricinus communis, and Ageratum conyzoides, were studied from different locations. Plants growing under natural environmental conditions were sampled at random in the vicinity of Jalandhar. To gain insights into the biochemical basis of invasiveness of these plants, the samples were subjected to chemical finger¬printing by using UV-Vis, fluorescent, and Fourier transform-infrared (FT-IR) techniques under natural abiotic stress conditions (moderate and hot conditions). Indices of oxidative stress, such as malondialdehyde (MDA), were also studied. MDA levels were enhanced under hot conditions. Elevated peaks (major and minor) were ob¬served in UV fingerprinting during adverse abiotic conditions. Fluorescent spectroscopy also validated the en¬hanced levels of secondary metabolites. FT-IR spectroscopy confirmed the presence of alkaloids and phenolics during stress conditions. Peaks were identified as rutin, vanillic acid, ascorbic acid, and glutathione reduced. The obtained results showed that under stressful conditions, the studied plants may produce an increased level of metabolites that might play a role in minimizing the oxidative stress faced by these plants. It was concluded that the studied plants, namely P. hysterophorus, L. camara, R. communis, and A. conyzoides, have the potential to cope with abiotic stress such as high temperature, which could be the reason for their invasiveness and vast adaptability.

The population needs reliable information on the chemical composition of plants and products made from them in order to preserve the environment and its safety. With the increase in cross-border trade, there is a growing demand for traceable results of determining the content of chemical elements in plants and not only proteins, fats, carbohydrates, pesticides, moisture, vitamins, etc., which can affect the quality of human life. An urgent but difficult analytical task is to obtain reliable measurements of the elemental composition of agricultural and wild plants and various products made from them. Reference materials (RMs) are a widely recognized tool for ensuring the uniformity of chemical measurements. They are designed for certification (validation) of existing and new methods (techniques) of chemical analysis, certification studies in the development of reference materials, and professional testing of laboratories. The article lists the reputable manufacturers of plant RMs in which the content of chemical elements is certified. The ratio of certified, reference, and quality control samples of plant-matrix has been assessed. The classification of certified reference materials according to the type of plant material used for their food application is provided. The contribution of different countries to the development of plant CRMs is hown. The selection of plants for the development of new RMs is discussed from two points of view, namely food composition databases (AOAC INTERNATIONAL) and the ‘Reference Plant’ chemical fingerprinting (B. Markert). Based on the consolidation of studies devoted to the development and appliance of plant-matrix reference materials, a list of the most important requirements has been compiled for reference materials that ensure the reliability and comparability of the results of chemical analysis in the fields of biology, geochemistry, ecology, agriculture, medicine, and interdisciplinary research.

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.

This study is the first to provide a comprehensive characterization of the liquid and volatile fractions of whole goat milk powder (GMP). Robust nuclear magnetic resonance (NMR)- and gas chromatography-mass spectrometry (GC-MS)-based chemical fingerprinting methods were optimized and implemented. The untargeted 1H-NMR analysis resolved 44 metabolites in the liquid fractions of GMP. The NMR fingerprinting technique effectively identified metabolites coming from the aliphatic, sugar, and aromatic regions that can be important in defining the technological properties and quality of the GMP. The untargeted headspace gas chromatography-mass spectrometry fingerprinting was able to detect a total of 50 volatiles including alkanes, ketones, alcohols, aromatics, alkenes, aldehydes, esters, acid, and sulfur compounds. The GMP was dominated by volatiles in the alkane group, while only a few esters were detected. Goat milk is a premium product and vulnerable to fraudulent activities such as adulteration or counterfeit. Therefore, proper characterization and identification is a crucial first step to verify its authenticity and quality.

Untargeted metabolomics is a powerful tool in chemical fingerprinting. It can be applied in phytochemistry to aid species identification, systematic studies and quality control of bioproducts. This approach aims to produce as much chemical information as possible, without focusing on any specific chemical class, thus, requiring extensive chemometric effort. This study aimed to evaluate the feasibly of an untargeted metabolomics method in phytochemistry by a study case of the Copaifera genus (Fabaceae). This genus contains significant medicinal species used worldwidely. Copaifera exploitation issues include a lack of chemical data, ambiguous species identification methods and absence of quality control for its bioproducts. Different organs of five Copaifera species were analysed by UHPLC-HRMS/MS, GNPS platform and chemometric tools. Untargeted metabolomics enabled the identification of 19 chemical markers and 29 metabolites, distinguishing each sample by species, plant organs, and biome type. Chemical markers were classified as flavonoids, terpenoids and condensed tannins. The applied method provided reliable information about species chemodiversity using fast workflow with little sampling size. The untargeted approach by UHPLC-HRMS/MS proved to be a promising tool for species identification, pharmacological prospecting and in the future for the quality control of extracts used in the manufacture of bioproducts.

The transformative potential of pattern-based sensing techniques is often hampered by their difficulty in dealing with mixtures of analytes, a drawback that severely limits the applications of this sensing approach (the "problem of mixtures"). We show here that this is not an intrinsic limitation of the pattern sensing method. Indeed, we developed general guidelines for the design of the sensing, signal detection, and data interpretation methods to avoid this constraint, which resulted in chemical fingerprinting systems capable of recognizing unknown mixtures of analytes in a single experiment, without separation or pre-treatment before data acquisition. In support of these design principles, we report their successful application to an important analytical problem, metal ion discrimination and quantitation, by constructing a sensor array that provided a linear colorimetric response over a wide range of analyte concentrations. The resulting data set was interpreted using common multivariate data processing algorithms to achieve quantitative identification and concentration determination for pure and mixture samples, with excellent predictive ability on unknowns. Separation and detection methods for analyte mixtures, normally envisioned as independent processes, were successfully integrated in a single system.

The spectroscopy of surface-enhanced Raman scattering (SERS), with its high sensitivity and specific chemical fingerprinting, has received increasing attention. A stable substrate is extraordinaril...

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 detailed chemical composition of crude oil in subsurface reservoirs provides important information about reservoir connectivity and can potentially play a very important role for the understanding of recovery processes. Relying on studying produced oil samples alone to understand the rock-fluid and fluid-fluid interactions is insufficient as the heavier polar components may be retained by tight reservoirs and not produced. These heavy and polar compounds that constitute the resin and asphaltene fractions of crude oil are typically present in low concentrations and yet are determining for the physical-chemical properties of the oil because of their polarity. In order to obtain a fingerprint analysis of oils including polar compounds from different wells, the oil content of drill cores has been extracted and analyzed. Infrared spectroscopy has been used to perform chemical fingerprinting of the oil extracted from drill cores sampled in different geographical locations of the Danish North Sea. Statistical analysis has been employed to identify the chemical differences within the sample set and explore the link between chemical composition and geographic location of the sample. A principal component analysis, based on spectral peak fitting in the 1800-1400 cm-1 range, has allowed for statistical grouping of the samples and identified the primary chemical feature characteristic of these groups. Statistically significant differences in the quantities of polar oxygen- and nitrogen-containing compounds were found between the oil wells. The results of this analysis have been used as guidelines and reference to establish an express statistical approach based on the full-range infrared spectra for a further expansion of the sample set. The chemical information presented in this work is discussed in relation to oil fingerprinting and geochemical analysis.

In complex atmospheric emission environments such as urban agglomerates, multiple sources control the ambient chemical composition driving air quality and regional climate. In contrast to pristine sites, where reliance on single or a few chemical tracers is often adequate for resolving pollution plumes and source influences, the comprehensive chemical fingerprinting of sources using non-methane hydrocarbons (NMHCs) and the identification of suitable tracer molecules and emission ratios becomes necessary. Here, we characterise and present chemical fingerprints of some major urban and agricultural emission sources active in South Asia, such as paddy stubble burning, garbage burning, idling vehicular exhaust and evaporative fuel emissions. A total of 121 whole air samples were actively collected from the different emission sources in passivated air sampling steel canisters and then analysed for 49 NMHCs (22 alkanes, 16 aromatics, 10 alkenes and one alkyne) using thermal desorption gas chromatography flame ionisation detection. Several new insights were obtained. Propane was found to be present in paddy stubble fire emissions (8 %), and therefore, for an environment impacted by crop residue fires, the use of propane as a fugitive liquefied petroleum gas (LPG) emission tracer must be done with caution. Propene was found to be ∼ 1.6 times greater (by weight) than ethene in smouldering paddy fires. Compositional differences were observed between evaporative emissions of domestic LPG and commercial LPG, which are used in South Asia. While the domestic LPG vapours had more propane (40 ± 6 %) than n-butane (19 ± 2 %), the converse was true for commercial LPG vapours (7 ± 6 % and 37 ± 4 %, respectively). Isoprene was identified as a new tracer for distinguishing paddy stubble and garbage burning in the absence of isoprene emissions at night from biogenic sources. Analyses of source-specific inter-NMHC molar ratios revealed that toluene/benzene ratios can be used to distinguish among paddy stubble fire emissions in the flaming (0.38 ± 0.11) and smouldering stages (1.40 ± 0.10), garbage burning flaming (0.26 ± 0.07) and smouldering emissions (0.59 ± 0.16), and traffic emissions (3.54 ± 0.21), whereas i-pentane ∕ n-pentane can be used to distinguish biomass burning emissions (0.06–1.46) from the petrol-dominated traffic and fossil fuel emissions (2.83–4.13). i-butane ∕ n-butane ratios were similar (0.20–0.30) for many sources and could be used as a tracer for photochemical ageing. In agreement with previous studies, i-pentane, propane and acetylene were identified as suitable chemical tracers for petrol vehicular and evaporative emissions, LPG evaporative and vehicular emissions and flaming-stage biomass fires, respectively. The secondary pollutant formation potential and human health impact of the sources was also assessed in terms of their hydroxyl radical (OH) reactivity (s−1), ozone formation potential (OFP; gO3/gNMHC) and fractional benzene, toluene, ethylbenzene and xylenes (BTEX) content. Petrol vehicular emissions, paddy stubble fires and garbage fires were found to have a higher pollution potential (at ≥95 % confidence interval) relative to the other sources studied in this work. Thus, many results of this study provide a new foundational framework for quantitative source apportionment studies in complex emission environments.

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.

Sidr honey from Ziziphus species is gaining importance after Manuka honey due to its health benefits, therefore chemical fingerprinting of the Sidr honey from different regions of Pakistan was performed in comparison with other unifloral (Elettaria cardamomum, Citrus reticulata and Grewia asiatica) and polyfloral honey. Front face, synchronous fluorescence spectroscopy (SFS) was recorded at an excitation wavelength range from 250–450 nm with offset of 60 nm. All honey samples have fluorescent emission peaks at 342 and 349 nm attributed to amino acid (Tryptophan). The emission spectra of raw Sidr honey showed clear discrimination from uni/polyfloral and commercial samples owing to its phenolic profile with peaks at 396 and major distinctive peak at 451 nm that corresponds to caffeic acid, chlorogenic acid and ferulic acid. Whereas a year old Sidr honey showed decreased and shifted fluorescence emission from amino acid and phenolic compounds respectively. Variation in fluorescent intensity of phenolic compounds in Sidr honey from different regions of Pakistan may be attributed to diverse species of Ziziphus in these geographical areas. A broad band from 395 to 459 nm in commercial honey samples are due to fluorescence of Maillard reaction products that could be generated during thermal processing of honey. Natural variability exists among honey samples owing to different floral origin as authenticated by Principal Component and Heirarchial Cluster Analysis techniques applied in this study. The unique fluorescence emission spectra of raw Sidr honey samples proposed front face SFS as a simple technique for the quick identification of its monofloral origin. Therefore, fluorescent inherent markers are helpful in identifying botanical and geographical origin and may also be standardized to authenticate the purity of honey.

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.

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.

Background: Ultra-performance LC (UPLC)–tandem MS (MS/MS) and high-performance TLC (HPTLC) assay methods were developed for chemical fingerprinting and quantitative analysis of bioactive constituents of a certain “Itrifal formulation,” a traditional kind of Unani medicine. Objective: In the present investigation, HPTLC and UPLC-MS/MS methods were developed and validated for the detection and quantification of major metabolites present in itrifal formulation. Methods: The metabolites present in the formulation were separated using modern chromatographic techniques, and a quantitative analysis was performed. Analytical performance of the proposed HPTLC and UPLC-MS/MS methods was validated as per the defined guidelines with respect to linearity, accuracy, precision, robustness, and specificity. Results: The developed UPLC-MS/MS and HPTLC methods were used for quantification of gallic acid, tannic acid, catechin, and quercetin. All four constituents were quantified by UPLC-MS/MS, while two constituents were quantified by HPTLC in the commercial itrifal formulation. The calibration plot was found to be linear, accurate, precise, robust, and specific for both HPTLC and UPLC-MS/MS. Conclusions: The present methods were successfully applied for analysis of the given markers in itrifal formulations. The same can be used for QC and stability testing of itrifal formulations.

Background Propolis is a resinous substance produced by bees. Propolis extracts have been used for anti-inflammatory and antimicrobial activities. The use of propolis dietary supplements has been increasing in the United States and the rest of the world. Objective A simple, economic, and valid analytical method is needed for quality assessment of dietary supplements and extracts claiming to contain propolis. Methods A ultra-high performance liquid chromatography (UHPLC) quadropole time-of-flight-MS method was used to characterize the chemical composition of northern Indian propolis. Fourteen major phenolic compounds were quantified using a UHPLC-DAD method. An HPTLC method was used to develop chemical fingerprinting profiles for propolis extracts and dietary supplements. The seven propolis extracts and 14 dietary supplements purchased in the U.S. were analyzed using the UHPLC-DAD-QToF method. Results Fifty-seven compounds belonging to phenolic, coumarin, fatty acid, and terpene classes were identified in propolis extracts. Based on quantification results, the content of 14 phenolic compounds in propolis extracts varied from 19–32% in dietary supplements, a significant variation to the recommended daily intake (0.2–94 mg/day). Conclusions/Highlights The developed analytical methods can be used for quality assessment of propolis extracts and dietary supplements.

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.

In 2019, an oil spill of unprecedented dimensions and unknown source reached the Brazilian coast. Such incident, which occurred somewhere in the ocean and was detected only when the first oil patches reached the beaches in the northeastern region, is recognized as one of the most serious oil spills in the country. From the chromatographic analysis of the oily residues using n-alkanes, polycyclic aromatic hydrocarbons (PAH), and oil biomarkers, it was possible to characterize their coverage. The results confirmed that an oil of the same specification reached a length of coastline higher than 3,000 kilometers. However, were also found oily residues that did not match with the product involved in that incident, evidencing the occurrence of different discharges. This study documents the extension of the affected coastline during the incident and assesses the possible origin of such different oils from their geochemical characteristics by selecting 21 samples from more than 300 samples previously collected and analyzed during the response actions. The unexpected occurrence of these residues suggest chronic events. The results highlighted that unrelated oily residues were found even in a region far from the coast, indicating that discharges of oil in the open sea occur more regularly than initially expected.

A multi-parametric experimental campaign was performed in Agri Valley (Basilicata, southern Italy) from July 2017 to January 2018. The investigated area, though basically rural and devoted to agricultural activities, hosts a huge onshore oil reservoir, i.e. Centro Olio Val d'Agri (COVA), bringing substantial environmental modifications and impacts to the district landscape. Daily concentrations of PM1 aerosol samples, Equivalent Black Carbon and number size distributions were evaluated. Chemical aerosol speciation based on elemental and ion analyses were carried out and source apportionment by Positive Matrix Factorization (PMF) was applied to reconstruct PM1 source profile. The most significant emission sources found are torches from the oil treatment facility (37 % w/w), an unresolved factor constituted by soil resuspension, Saharan dust, and biomass burning (24 % w/w), ammonium sulphate (23 % w/w), emissions from the oil desulfurization (Claus process) (13 % w/w), and traffic +road dust (3 % w/w). SEM analysis on PM1 single particles allowed to confirm the finding from PMF including the occurrence of elemental sulfur associated with the Claus process. The novelty of the present study consists in the identification of this latter fingerprint.

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.

Thermal radiation is nominally broadband, incoherent, and isotropic, so controlling the spectral, temporal, and directional characteristics of thermal emission is an important frontier in imaging and chemical fingerprinting. The use of thermal metasurfaces, whose emission properties can be finely tailored, has recently become of great interest. Here we theoretically demonstrate the thermal emission of a metasurface arising from the coupled emission from a plasmonic mode in graphene nanoribbons and the guided mode resonance of a 1D photonic crystal. We also discuss the utility of a computationally cheap approach based on coupled-mode theory to model the device scattering characteristics.

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.

Background: Invasive alien species (IAS) are broadly distributed all over the world by disturbing or reducing the growth and development of native vegetation. Lantana camara is basically a noxious weed and have a potential to invade a region's indigenous vegetation. Even after knowing all its harmful effects, there has been a little research on various mechanisms followed by this plant to harm the plant species. Results: Random sampling was performed to take plant samples without any bias, to study various mechanisms carried out in plant species. Chemical fingerprinting of samples were then performed in various abiotic stress conditions (cold and hot) to study changes in L. camara under these stressful conditions in order to find the reason behind the invasiveness of this plant species. Stress indicator like malondialdehyde (MDA)/lipid peroxidation was also performed and increased lipid peroxidation during both extremities showed that plant is experiencing oxidative stress. ROS imaging was performed on the leaves of L. camara, which also showed rise in ROS staining during extreme conditions. Elevated peaks (major and minor) and detection of secondary metabolites like glycine betaine in chemical fingerprinting observed under stressful conditions showed that plant may produce some increased level of metabolites in stress conditions that might play a role in minimizing the oxidative stress that plant is facing. Conclusions: On the behalf of obtained results, it can be assumed that Lantana camara has the capability to survive in or tolerate extreme environmental abiotic stress conditions by producing or agglomerating various stress-reducing metabolites.

In recent years, the chemical fingerprinting of traditional Chinese medicines and the metabolites in these compounds has been a hot topic. In the present study, the chemical fingerprint of Tianshu tablets (TST) and the metabolic characteristics of compounds in rats after intragastric administration were studied by ultra-high performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry (UPLC/Q-TOF MS). In a preliminary study, 77 chemical components in TST were determined by comparison with retention times, accurate molecular mass, and characteristic fragment ions of the known compounds in the literature and some well-known compounds were analyzed in detail, and the fragmentation pathways for parishins B, gastrodin A, and cnidilide or neocnilide were specifically analyzed. After intragastric administration of TST (4 g/kg) to rats, a total of 61 compounds were detected in plasma samples, including 7 prototypes and 54 metabolites. After further analysis, it was found that these metabolites were subjected to glucuronidation, sulfation, methylation, hydroxylation, dehydrogenation, or mixed metabolic processes. Hydroxylation and glucuronidation were finally confirmed as the main metabolic pathways. This is the first research on the chemical fingerprint and metabolites of TST, which lays a foundation for further investigation of TST.

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.

Chemical fingerprinting has been widely used for the quality control of complex natural products including traditional Chinese medicines and botanical drugs. However, there is still lack of appropriate method to monitor the batch-to-batch consistency of hydrophilic constituents, such as saccharides and oligosaccharides. In the present study, we developed a novel approach based on high performance liquid chromatography with evaporative light scattering detector(HPLC-ELSD) for establishing saccharide fingerprinting of Danhong Injection(DHI), which is a widely used botanical drug for treating cardiovascular diseases. Major saccharides in DHI were isolated and four compounds including fructose, glucose and two oligosaccharides were identified. The structures of two novel saccharides named glycerol-1-O-galactfpyranosyl-(1→4)-O-arabinofuranoside, and glycerol-1-O-galactpyranosyl-(1→4) [O-arabinfuranosyl-(1→3)]-O-arabinofuranoside were confirmed by NMR, HR-ESI-MS and GC-MS for the first time. The establishment approach was successfully applied to distinguishing 12 batches of DHI from other botanical drugs with the aid of principle component analysis as well as to evaluating batch-to-batch consistency with the help of calculating similarity of fingerprints. Our findings indicate that the chemical fingerprint of saccharides can be a useful tool for the quality control of complex natural products.

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.

Global population forecasts dictate a rapid adoption of multifaceted approaches to fulfill increasing food requirements, ameliorate food dietary value and security using sustainable and economically feasible agricultural processes. Plant pathogens induce up to 25% losses in vegetable crops and their early detection would contribute to limit their spread and economic impact. As an alternative to time-consuming, destructive, and expensive diagnostic procedures, such as immunological assays and nucleic acid-based techniques, Raman spectroscopy (RS) is a nondestructive rapid technique that generates a chemical fingerprinting of a sample, at low operating costs. Here, we assessed the suitability of RS combined to chemometric analysis to monitor the infection of an important vegetable crop plant, tomato, by two dangerous and peculiarly different viral pathogens, Tomato yellow leaf curl Sardinia virus (TYLCSV) and Tomato spotted wilt virus (TSWV). Experimentally inoculated plants were monitored over 28 days for symptom occurrence and subjected to RS analysis, alongside with measuring the virus amount by quantitative real-time PCR. RS allowed to discriminate mock inoculated (healthy) from virus-infected specimens, reaching an accuracy of >70% after only 14 days after inoculation for TYLCSV and >85% only after 8 days for TSWV, demonstrating its suitability for early detection of virus infection. Importantly, RS also highlighted spectral differences induced by the two viruses, providing specific information on the infecting agent.

Propolis is a mixture of resin collected by the bees to build their hive. These mixtures contain natural remedy and used to treat variety of health-related problems. Unlike honeybee propolis, the study of stingless bee propolis still lacking. The important part of propolis study is the optimization of extraction procedures. The aim for this study is to employ chemometrics on FTIR data in order to discriminate the chemical fingerprinting of Malaysian stingless bee, Heterotrigona itama propolis yielded from different extraction methods, which were maceration, sonication and soxhlet. The chemical fingerprinting was obtained through Fourier Transform Infrared (FTIR). Principle component analysis (PCA) and hierarchical cluster analysis (HCA) were applied as pattern recognition methods for FTIR spectra. PCA of FTIR data for different extraction methods of stingless bee’s propolis revealed that variability of PC1 and PC2 is 84.76%. PCA’s variation in propolis by different extraction methods was classified based on specific functional groups arisen from the peaks. The FTIR fingerprinting of HCA of stingless bee’s propolis were distributed into three clusters based on percentages of ethanol, intensity of peaks and different fingerprint region. FTIR coupled with chemometric analysis showed classification of different extraction methods of propolis from PCA and HCA based on vibration of functional groups presence in the samples. Taken together, these results showed that different extraction methods play important role in detaining of chemical in propolis of stingless bee.

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.

Carbohydrate and saccharide sensing in water remains very challenging. Using the covalent reversible interaction between boronic acids and the diol groups in carbohydrates is still one of the most ...

Tephra layers are of importance for the construction of reliable age control in late Quaternary paleoenvironmental and volcanic hazard studies, especially in volcanically-active settings such as the North Island of New Zealand. However, their identification involves time-consuming and destructive processing steps, making the application of non-destructive μ-XRF core scanners potentially advantageous for tephra identification. Here, we investigate the potential of the Itrax μ-XRF core scanner to differentiate between rhyolitic tephra layers sourced from various northern New Zealand rhyolitic volcanic centres deposited in maar lakes of the Auckland Volcanic Field. In their macroscopic form these tephra layers are usually visibly distinct when surrounded by a dark, organic-rich sediment matrix, although their attribution to source volcanic centre and eruption typically requires examination of their mineral assemblages, combined with chemical fingerprinting of the rhyolite glass shards. We demonstrate that μ-XRF core scanning of rhyolitic tephra layers from the Taupo Volcanic Zone and Tuhua Volcanic Centre can also allow identification, and sometimes differentiation, of the tephra using μ-XRF-derived elemental counts, especially high Si, K, Ca and very low Br and Ti. Different rhyolite tephra layers vary in their relative abundances of major, minor and trace elements as is evident from electron microprobe and LA-ICP-MS analyses of their glass shards. Mo-tube based μ-XRF cannot detect Na nor Mg and is of lower reliability for the lighter elements (Ca, Al) which play an important role in traditional tephra fingerprinting. Nevertheless, we are able to demonstrate that μ-XRF core scanning data can distinguish between previously identified tephra layers using multivariate statistics. Furthermore, the study emphasises the need for a standard protocol for μ-XRF core scanning of tephra layers for this approach to be more widely applicable, especially to aid or be a substitute for conventional geochemical approaches used for tephra fingerprinting.

Detection and identification of the in vivo metabolites of traditional Chinese medicine by untargeted profiling strategies are often confronted with severe interference from complex endogenous substances. Here we developed an integral approach, by combining untargeted data-dependent MS2 (dd-MS2) of Q-Orbitrap mass spectrometry and predictive multiple reaction monitoring-information dependent acquisition-enhanced product ion scan (pMRM-IDA-EPI) of triple quadrupole-linear ion trap (QTRAP) mass spectrometry, aiming to detect and identify more extensive metabolites in bio-samples. Ecliptae Herba (EH) is a widely consumed medicinal herb with the effects of nourishing liver/kidney, but its metabolites in vivo have not been fully elucidated. Firstly, after UHPLC separation on an HSS T3 column, chemical fingerprinting of 70% ethanolic extract of EH was performed by untargeted dd-MS2 in negative ion mode. We could characterize 41 compounds from EH, and 24 were detectable in the plasma of rats (prototypes) after oral administration of EH extract (1 g/kg). Secondly, using echinocystic acid (triterpene), wedelolactone (coumarin), and apigenin (flavonoid) as the different parent templates, an MRM list containing 150 predicted ion-pairs was established to enhance MS2 scan by pMRM-IDA-EPI, which enabled the primary identification of up to 200 metabolites. The biotransformations mainly involve oxidation, hydrogenation, methylation, glucuronidation, sulfonation etc. Thirdly, the rat plasma samples obtained after oral administration of three pure compounds (echinocystic acid, wedelolactone and apigenin) were analyzed to verify the reliability of metabolites identification, and 11, 4, and 10 metabolites were found individually. This is the first comprehensive research on the metabolism of EH in vivo.

Purpose: Are rare earth element (REE) patterns employable as tracers in human interventions of bulk soil disturbances, when high concentrations of metals are involved in the in situ soil disturbance? In terms of bulk soil disturbance, it is difficult to distinguish between bulk soil disturbances and emplacement of new earthen material. Chemical fingerprinting, in particular REE plus yttrium, is applied across many fields, but predominantlyin tracking the sources of potential environmental contaminants. Materials and methods: The REE normalised patterns (HNO 3 :HF:HCl 3:1:1 digestion, ICP-MS) of two Calcaric Cambisols were compared with those of a Geric Ferralsol (Novic, Technic) originated from selective overburden of nickel mining (20°40′ N, 75°35′ W). Results and discussion: The sum of REE, including Y and Sc, ranged between 48 and 101mgkg −1 . Principal component analysis (PCA) shows a discriminant role of REE. REE signature normalised to the upper continental crust shows slight positive Eu and negative Ce anomalies in the case of both Calcaric Cambisols, while the Geric Ferralsol shows anomalous patterns with the same anomalies plus a slight positive anomaly of Y, as a consequence of the addition of mining by-products. Conclusions: Here, we show that REE patterns of the individual horizons of a soil have characteristics that allow us to distinguish undisturbed from soils mixed with other soil materials, including those with different pH values and high metal contents (e.g. Cr, Mn, and Ni ≥ 0.5%, Fe ≫ 5wt%). Our results demonstrate, by using soils with contrasting characteristics, that their origins can be traced via the patterns of their REEs, even in the presence of high concentrations of other metals. In perspective, when background maps of all REE elements in soils are available worldwide on an appropriate scale, this enables us to obtain a level of discriminatory detail on a local scale.

Clinical and laboratory studies have implicated black raspberries (BRBs) and their associated phytochemicals in the modulation of several chronic diseases. Most research on the health benefits of BRBs is conducted using freeze-dried or otherwise minimally processed products, yet BRBs are typically consumed as thermally processed goods like jams and syrups. The objective of this work was to profile the chemical changes that result from thermal processing of BRB powder into a nectar beverage. Using an untargeted UHPLC-QTOF-MS metabolomics approach, key degradation products of anthocyanins were identified along with several other proposed phenolic degradants. The effects of processing on other key BRB compound groups, including ellagitannins, are also discussed. This work demonstrates the utility of an untargeted metabolomics approach in describing the chemistry of complex food systems and provides a foundation for future research on the impact of processing on BRB product bioactivity.

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.

We combine nanoindentation, herein achieved using atomic force microscopy-based pulsed-force lithography, with tip-enhanced Raman spectroscopy (TERS) and imaging. Our approach entails indentation and multimodal characterization of otherwise flat Au substrates, followed by chemical functionalization and TERS spectral imaging of the indented nanostructures. We find that the resulting structures, which vary in shape and size depending on the tip used to produce them, may sustain nano-confined and significantly enhanced local fields. We take advantage of the latter and illustrate TERS-based ultrasensitive detection/chemical fingerprinting as well as chemical reaction imaging-all using a single platform for nano-lithography, topographic imaging, hyperspectral dark field optical microscopy, and TERS.

Ephedra herb extracts are being extensively investigated in terms of their antioxidative, antimicrobial and antiproliferative properties, with phenolic components being the general carriers of these bioactivities. Here we describe a comprehensive set of analytical methods employed to determine and characterize both the antioxidative activity and the qualitative profile of phenolic acids and flavonoids present in several Ephedra species of different geographical origin. Spectrophotometric methods were used to determine the total phenolic content, total flavonoid content and antioxidative activity. Multi-development HPTLC enabled chemical fingerprinting which can be used for species differentiation. Individual spots of the thin-layer chromatogram were subjected to GC-MS with injection port derivatization for identification, which was based on both the detected mass spectra and recorded retention indices. The results were compared and complemented with GC-MS using offline derivatization.

The complex chemical composition of crude oils presents many challenges for rapid chemical characterization in the case of a spill. A number of approaches are currently used to "fingerprint" petroleum-derived samples. Gas chromatography coupled with mass spectrometry (GC-MS) is the most common, albeit not very rapid, technique; however, with GC-MS alone, it is difficult to resolve the complex substances in crude oils. The present study examined the potential application of ion mobility spectrometry-mass spectrometry (IMS-MS) coupled with chem-informatic analyses as an alternative high-throughput method for the chemical characterization of crude oils. We analyzed 19 crude oil samples from on- and offshore locations in the Gulf of Mexico region in the United States using both GC-MS (biomarkers, gasoline range hydrocarbons, and n-alkanes) and IMS-MS (untargeted analysis). Hierarchical clustering, principal component analysis, and nearest neighbor-based classification were used to examine sample similarity and geographical groupings. We found that direct-injection IMS-MS performed either equally or better than GC-MS in the classification of the origins of crude oils. In addition, IMS-MS greatly increased the sample analysis throughput (minutes vs hours per sample). Finally, a tabletop science-to-practice exercise, utilizing both the GC-MS and IMS-MS data, was conducted with emergency response experts from regulatory agencies and the oil industry. This activity showed that the stakeholders found the IMS-MS data to be highly informative for rapid chemical fingerprinting of complex substances in general and specifically advantageous for accurate and confident source-grouping of crude oils. Collectively, the present study shows the utility of IMS-MS as a technique for rapid fingerprinting of complex samples and demonstrates its advantages over traditional GC-MS-based analyses when used for decision-making in emergency situations. Environ Toxicol Chem 2021;40:1034-1049. © 2020 SETAC.

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.

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.

Alpinia galanga (L.) Willd. (Zingiberaceae), or galangal, has been previously reported as active against Mycobacterium tuberculosis (TB) in vitro. The present study assessed a novel antitubercular mechanism of of galangal through M. tuberculosis shikimate kinase (MtSK) inhibitory assays. Sequential extractions of nonpolar solvents hexane and dichloromethane (DCM) were performed on galangal and screened in MtSK inhibitory assays to identify potential activity. Samples were then subjected to high resolution (HR) LC–MS chemical fingerprinting and analysis. Additionally, a novel approach was undertaken for galangal using methods such as mass professional profiler (MPP) and global natural products social (GNPS) molecular networking for structure elucidation.

Mid-infrared photothermal (MIP) microscopy has been a promising label-free chemical imaging technique for functional characterization of specimens owing to its enhanced spatial resolution and high specificity. Recently developed wide-field MIP imaging modalities have drastically improved speed and enabled high-throughput imaging of micron-scale subjects. However, the weakly scattered signal from sub-wavelength particles becomes indistinguishable from the shot-noise as a consequence of the strong background light, leading to limited sensitivity. Here, we demonstrate background-suppressed chemical fingerprinting at a single nanoparticle level by selectively attenuating the reflected light through pupil engineering in the collection path. Our technique provides over three orders of magnitude background suppression by quasi-darkfield illumination in epi-configuration without sacrificing lateral resolution. We demonstrate 6-fold signal-to-background noise ratio improvement, allowing for simultaneous detection and discrimination of hundreds of nanoparticles across a field of view of 70 um x 70 um. A comprehensive theoretical framework for photothermal image formation is provided and experimentally validated with 300 and 500~nm PMMA beads. The versatility and utility of our technique are demonstrated via hyperspectral dark-field MIP imaging of S. aureus and E. coli bacteria., Comment: 33 pages, 7 figures, journal article

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.

A variational autoencoder (VAE) is a generational deep learning model based on encoding a particular observation into a latent space and then decoding it while incorporating some random noise with the intuition of being able to generate slightly different forms of the input observation. Here, I propose a VAE that is able to generate denovo drug compounds by feeding in a known set of drug compounds against a particular biological target. To demonstrate the ability of the proposed VAE as a generative model, known drug molecules belonging to the class of Neuraminidase (NA) inhibitors were taken from the ZINC database and fed into the VAE model as one-hot encoded SMILES strings. Similarly, active NA inhibitors and decoy molecules together were also fed to compare efficiency. The generated molecules were then screened to remove impractical structures. Next, a drug-likeness (QED) score was computed for each candidate molecule and a cutoff of 0.5 was used to extract viable candidates. To ensure that the generated drug compounds were active NA inhibitors, a series of Artificial Neural Networks (ANNs) classifiers based on three different characterization techniques, namely chemical fingerprinting, molecular descriptions and graph convolutions, were developed to identify active NA inhibitors from decoy molecules. The feature candidate data were then fed into the three designed ANNs to obtain the final set of novel, viable and active NA inhibitors. Seventy-one new NA inhibitors were obtained after three runs of the VAE model under different parameterizations. The proposed VAE can hence be used to generate de-novo drug compounds for a wide variety of biological targets.