Real-time High-resolution Mass Spectrometry Research Articles

Chemical characterization of polymer and chloride content in waste plastic materials using pyrolysis - direct analysis in real time - high-resolution mass spectrometry.

The increasing global demand for plastic has raised the need for effective waste plastic management due to its long lifetime and resistance to environmental degradation. There is a need for rapid plastic identification to improve the mechanical waste plastic sorting process. This study presents a novel application of Temperature-Programmed Desorption-Direct Analysis in Real Time-High Resolution Mass Spectrometry (TPD-DART-HRMS) that enables rapid characterization of various plastics. This technique was applied on four commercially available reference polymers (polyethylene, polypropylene, polystyrene, polyvinyl chloride) as well as three "waste" plastic samples of mixed origin. These waste plastic samples were obtained as discards from various industrial processes with limited analytical characterization data. Through the application of CH2 Kendrick mass defect (KMD) grouping, characteristic trends in the mass spectra of each sample were identified, allowing for a simplified numerical comparison. This approach utilized a robust statistical approach using the Tanimoto coefficient, allowing for the quantitative measures of similarity between standards and unknown samples. The application of this mathematical evaluation methodology was used to identify plastic types and to distinguish structurally similar polymers. Additionally, we report that a chloride ion clustering effect with copper substrate can identify chlorinated polymer PVC (polyvinyl chloride) utilizing pyro-(-)DART-HRMS mode. PVC polymer is of particular interest in recycling due to its high chloride content, which can present technical challenges for some types of recycling. We found that chloride ion clusters are a good screening marker for the presence of chlorinated polymers in mixed waste plastic samples. This study can possibly help advance rapid and accurate analytical techniques for identifying the composition of waste plastics to advance the effectiveness of the waste plastic sorting process.

Volatility Basis Set Distributions and Viscosity of Organic Aerosol Mixtures: Insights from Chemical Characterization Using Temperature-Programmed Desorption-Direct Analysis in Real-Time High-Resolution Mass Spectrometry.

Quantitative assessment of gas-particle partitioning of individual components within complex atmospheric organic aerosol (OA) mixtures is critical for predicting and comprehending the formation and evolution of OA particles in the atmosphere. This investigation leverages previously documented data obtained through a temperature-programmed desorption-direct analysis in real-time, high-resolution mass spectrometry (TPD-DART-HRMS) platform. This methodology facilitates the bottom-up construction of volatility basis set (VBS) distributions for constituents found in three biogenic secondary organic aerosol (SOA) mixtures produced through the ozonolysis of α-pinene, limonene, and ocimene. The apparent enthalpies (ΔH*, kJ mol-1) and saturation mass concentrations (CT*, μg·m-3) of individual SOA components, determined as a function of temperature (T, K), facilitated an assessment of changes in VBS distributions and gas-particle partitioning with respect to T and atmospheric total organic mass loadings (tOM, μg·m-3). The VBS distributions reveal distinct differences in volatilities among monomers, dimers, and trimers, categorized into separate volatility bins. At the ambient temperature of T = 298 K, only monomers efficiently partition between gas and particle phases across a broad range of atmospherically relevant tOM values of 1-100 μg·m-3. Partitioning of dimers and trimers becomes notable only at T > 360 K and T > 420 K, respectively. The viscosity of SOA mixtures is assessed using a bottom-up calculation approach, incorporating the input of elemental formulas, ΔH*, CT*, and particle-phase mass fractions of the SOA components. Through this approach, we are able to accurately estimate the variations in SOA viscosity that result from the evaporation of its components. These variations are, in turn, influenced by atmospherically relevant changes in tOM and T. Comparison of the calculated SOA viscosity and diffusivity values with literature reported experimental results shows close agreement, thereby validating the employed calculation approach. These findings underscore the significant potential for TPD-DART-HRMS measurements in enabling the untargeted analysis of organic molecules within OA mixtures. This approach facilitates quantitative assessment of their gas-particle partitioning and allows for the estimation of their viscosity and condensed-phase diffusion, thereby contributing valuable insights to atmospheric models.

Ambient mass spectrometry imaging of food natural products by angled direct analysis in real time high-resolution mass spectrometry

Direct surface analysis in ambient conditions provides information on the position and chemical composition of an object at the time of investigation. An angled sampling probe is developed in this work for direct analysis in real time (DART) ionization high-resolution mass spectrometry. The DART ion source and the interface were modified for improved surface resolution, increased ion transfer efficiency, as well as enabling two-dimensional surface scanning. The angled probe DART-MS system was used for investigating a variety of food samples including fruit peels, ginseng root, plant leaves and sections of radish. Abundant signals and distinct chemical profiles are obtained in seconds, and spatial distribution of different molecules across the sample surfaces can be observed. In addition, the developed system can quickly identify the chemical changes when the surfaces were treated. The method is capable of directly evaluating food sample surfaces with different shapes, hardness, and conditions, without any sample pretreatments.

Thermal desorption direct analysis in real-time high-resolution mass spectrometry and machine learning allow the rapid authentication of ground black pepper and dried oregano: A proof-of-concept study.

Thermal desorption direct analysis in real-time high-resolution mass spectrometry (TD-DART-HRMS) approaches have gained popularity for fast screening of a variety of samples. With rapid volatilization of the sample at increasing temperatures outside the mass spectrometer, this technique can provide a direct readout of the sample content with no sample preparation. In this study, TD-DART-HRMS's utility for establishing spice authenticity was examined. To this aim, we directly analyzed authentic (typical) and adulterated (atypical) samples of ground black pepper and dried oregano in positive and negative ion modes. We analyzed a set of authentic ground black pepper samples (n = 14) originating from Brazil, Sri Lanka, Madagascar, Ecuador, Vietnam, Costa Rica, Indonesia, Cambodia, and adulterated samples (n = 25) consisting of mixtures of ground black pepper with this spice's nonfunctional by-products (pinheads or spent) or with different exogenous materials (olive kernel, green lentils, black mustard seeds, red beans, gypsum plaster, garlic, papaya seeds, chili, green aniseed, or coriander seeds). TD-DART-HRMS facilitated the capture of informative fingerprinting of authentic dried oregano (n = 12) originating from Albania, Turkey, and Italy and those spiked (n = 12) with increasing percentages of olive leaves, sumac, strawberry tree leaves, myrtle, and rock rose. A predictive LASSO classifier was built, after merging by low-level data fusion, the positive and negative datasets for ground black pepper. Fusing multimodal data allowed retrieval of more comprehensive information from both datasets. The resultant classifier achieved on the withheld test set accuracy, sensitivity, and specificity of 100%, 75%, and 90%, respectively. On the contrary, the sole TD-(+)DART-HRMS spectra of the oregano samples allowed construction of a LASSO classifier that predicted the adulteration of the oregano with excellent statistical indicators. This classifier achieved, on the withheld test set, 100% each for accuracy, sensitivity, and specificity.

Volatility Measurements of Individual Components in Organic Aerosol Mixtures Using Temperature-Programmed Desorption-Direct Analysis in Real Time-High Resolution Mass Spectrometry.

Atmospheric organic aerosols (OA) have profound effects on air quality, visibility, and radiative forcing of climate. Quantitative assessment of gas-particle equilibrium of OA components is critical to understand formation, growth, distribution, and evolution of OA in the atmosphere. This study presents a novel ambient pressure measurement approach developed and tested for untargeted screening of individual components in complex OA mixtures, followed by targeted chemical speciation of identified species and assessment of their physicochemical properties such as saturation vapor pressure and enthalpies of sublimation/evaporation. The method employs temperature-programmed desorption (TPD) experiments coupled to "direct analysis in real time" (DART) ionization source and high resolution mass spectrometry (HRMS) detection. Progression of the mass spectra is acquired in the TPD experiments over a T = 25-350 °C temperature range, and extracted ion chromatograms (EIC) of individual species are used to infer their apparent enthalpies of sublimation/evaporation (ΔHsub*) and saturation vapor pressure (pT*, Pa, or CT*, μg m-3) as a function of T. We validate application of this method for analysis of selected organic compounds with known ΔHsub and CT values, which showed excellent agreement between our results and the existing data. We then extend these experiments to interrogate individual components in complex OA samples generated in the laboratory-controlled ozonolysis of α-pinene, limonene, and β-ocimene monoterpenes. The abundant OA species of interest are distinguished based on their accurate mass measurements, followed by quantitation of their apparent ΔHsub* and CT* values from the corresponding EIC records. Comparison of C298K* values derived from our experiments for the individual OA components with the corresponding estimates based on their elemental composition using a "molecular corridors" (MC) parametrization suggests that the MC calculations tend to overestimate the saturation vapor pressures of OA components. Presented results indicate very promising applicability of the TPD-DART-HRMS method for the untargeted analysis of organic molecules in OA and other environmental mixtures, enabling rapid detection and quantification of organic pollutants in the real-world condensed-phase samples at atmospheric pressure and without sample preparation.

Combined ambient ionization mass spectrometric and chemometric approach for the differentiation of hemp and marijuana varieties of Cannabis sativa

BackgroundHemp and marijuana are the two major varieties of Cannabis sativa. While both contain Δ9-tetrahydrocannabinol (THC), the primary psychoactive component of C. sativa, they differ in the amount of THC that they contain. Presently, U.S. federal laws stipulate that C. sativa containing greater than 0.3% THC is classified as marijuana, while plant material that contains less than or equal to 0.3% THC is hemp. Current methods to determine THC content are chromatography-based, which requires extensive sample preparation to render the materials into extracts suitable for sample injection, for complete separation and differentiation of THC from all other analytes present. This can create problems for forensic laboratories due to the increased workload associated with the need to analyze and quantify THC in all C. sativa materials.MethodThe work presented herein combines direct analysis in real time—high-resolution mass spectrometry (DART-HRMS) and advanced chemometrics to differentiate hemp and marijuana plant materials. Samples were obtained from several sources (e.g., commercial vendors, DEA-registered suppliers, and the recreational Cannabis market). DART-HRMS enabled the interrogation of plant materials with no sample pretreatment. Advanced multivariate data analysis approaches, including random forest and principal component analysis (PCA), were used to optimally differentiate these two varieties with a high level of accuracy.ResultsWhen PCA was applied to the hemp and marijuana data, distinct clustering that enabled their differentiation was observed. Furthermore, within the marijuana class, subclusters between recreational and DEA-supplied marijuana samples were observed. A separate investigation using the silhouette width index to determine the optimal number of clusters for the marijuana and hemp data revealed this number to be two. Internal validation of the model using random forest demonstrated an accuracy of 98%, while external validation samples were classified with 100% accuracy.DiscussionThe results show that the developed approach would significantly aid in the analysis and differentiation of C. sativa plant materials prior to launching painstaking confirmatory testing using chromatography. However, to maintain and/or enhance the accuracy of the prediction model and keep it from becoming outdated, it will be necessary to continue to expand it to include mass spectral data representative of emerging hemp and marijuana strains/cultivars.

Chemical characterization of microplastic particles formed in airborne waste discharged from sewer pipe repairs.

Microplastic particles are of increasing environmental concern due to the widespread uncontrolled degradation of various commercial products made of plastic and their associated waste disposal. Recently, common technology used to repair sewer pipes was reported as one of the emission sources of airborne microplastics in urban areas. This research presents results of the multi-modal comprehensive chemical characterization of the microplastic particles related to waste discharged in the pipe repair process and compares particle composition with the components of uncured resin and cured plastic composite used in the process. Analysis of these materials employs complementary use of surface-enhanced Raman spectroscopy, scanning transmission X-ray spectro-microscopy, single particle mass spectrometry, and direct analysis in real-time high-resolution mass spectrometry. It is shown that the composition of the relatively large (100 μm) microplastic particles resembles components of plastic material used in the process. In contrast, the composition of the smaller (micrometer and sub-micrometer) particles is significantly different, suggesting their formation from unintended polymerization of water-soluble components occurring in drying droplets of the air-discharged waste. In addition, resin material type influences the composition of released microplastic particles. Results are further discussed to guide the detection and advanced characterization of airborne microplastics in future field and laboratory studies pertaining to sewer pipe repair technology.

Optimized Solid-Phase Mesh-Enhanced Sorption from Headspace (SPMESH) for Rapid Sub-ng/kg Measurements of 3-Isobutyl-2-methoxypyrazine (IBMP) in Grapes.

Parallel extraction of headspace volatiles from multiwell plates using sorbent sheets (HS-SPMESH) followed by direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) can be used as a rapid alternative to solid-phase micro-extraction (SPME) gas-chromatography mass-spectrometry (GC-MS) for trace level volatile analyses. However, an earlier validation study of SPMESH-DART-MS using 3-isobutyl-2-methoxypyrazine (IBMP) in grape juice showed poor correlation between SPMESH-DART-MS and a gold standard SPME-GC-MS around the compound’s odor detection threshold (<10 ng/kg) in grape juice, and lacked sufficient sensitivity to detect IBMP at this concentration in grape homogenate. In this work, we report on the development and validation of an improved SPMESH extraction approach that lowers the limit of detection (LOD < 0.5 ng/kg), and regulates crosstalk between wells (<0.5%) over a calibration range of 0.5–100 ng/kg. The optimized SPMESH-DART-MS method was validated using Cabernet Sauvignon and Merlot grape samples harvested from commercial vineyards in the central valley of California (n = 302) and achieved good correlation and agreement with SPME-GC-MS (R2 = 0.84) over the native range of IBMP (<0.5–20 ng/kg). Coupling of SPMESH to a lower resolution triple quadrupole (QqQ)-MS via a new JumpShot-HTS DART source also achieved low ng/kg detection limits, and throughput was improved through positioning stage optimizations which reduced time spent on intra-well SPMESH areas.

Rapid, novel screening of toxicants in poison baits, and autopsy specimens by ambient mass spectrometry.

Animal poisoning and dissemination of baits in the environment have public health and ethological implications, which can be followed by criminal sanctions for those responsible. The reference methods for the analysis of suspect baits and autopsy specimens are founded on chromatographic-based techniques. They are extremely robust and sensitive, but also very expensive and laborious. For this reason, we developed an ambient mass spectrometry (AMS) method able to screen for 40 toxicants including carbamates, organophosphate and chlorinated pesticides, coumarins, metaldehyde, and strychnine. Spiked samples were firstly purified and extracted by dispersive solid phase extraction (QuEChERS) and then analyzed by direct analysis in real time high-resolution mass spectrometry (DART-HRMS). To verify the performance of this new approach, 115 authentic baits (n = 59) and necropsy specimens (gastrointestinal content and liver, n = 56) were assessed by the official reference methods and combined QuEChERS-DART-HRMS. The agreement between the results allowed evaluation of the performances of the new screening method for a variety of analytes and calculation of the resultant statistical indicators (the new method had overall accuracy 89.57%, sensitivity of 88.24%, and a specificity of 91.49%). Taking into account only the baits, 96.61% of overall accuracy was achieved with 57/59 samples correctly identified (statistical sensitivity 97.50%, statistical specificity 94.74%). Successful identification of the bitter compound, denatonium benzoate, in all the samples that contained rodenticides (28/28) was also achieved. We believe initial screening of suspect poison baits could guide the choice of reference confirmatory methods, reduce the load in official laboratories, and help the early stages of investigations into cases of animal poisoning.

Authentication of Edible Insects' Powders by the Combination of DART-HRMS Signatures: The First Application of Ambient Mass Spectrometry to Screening of Novel Food.

This feasibility study reports the use of direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) in profiling the powders from edible insects, as well as the potential for the identification of different insect species by classification modeling. The basis of this study is the revolution that has occurred in the field of analytical chemistry, with the improved capability of ambient mass spectrometry to authenticate food matrices. In this study, we applied DART-HRMS, coupled with mid-level data fusion and a learning method, to discriminate between Acheta domesticus (house cricket), Tenebrio molitor (yellow mealworm), Locusta migratoria (migratory locust), and Bombyx mori (silk moth). A distinct metabolic fingerprint was observed for each edible insect species, while the Bombyx mori fingerprint was characterized by highly abundant linolenic acid and quinic acid; palmitic and oleic acids are the statistically predominant fatty acids in black soldier fly (Hermetia illucens). Our chemometrics also revealed that the amino acid proline is a discriminant molecule in Tenebrio molitor, whereas palmitic and linoleic acids are the most informative molecular features of the house cricket (Acheta domesticus). Good separation between the four different insect species was achieved, and cross-validation gave 100% correct identification for all training samples. The performance of the random forest classifier was examined on a test set and produced excellent results, in terms of overall accuracy, sensitivity, and specificity. These results demonstrate the reliability of the DART-HRMS as a screening method in a future quality control scenario to detect complete substitution of insect powders.

Composition of Nonextractable Polyphenols from Sweet Cherry Pomace Determined by DART-Orbitrap-HRMS and Their In Vitro and In Vivo Potential Antioxidant, Antiaging, and Neuroprotective Activities

Sweet cherry pomace is an important source of phenolic compounds with beneficial health properties. As after the extraction of phenolic compounds, a phenolic fraction called nonextractable polyphenols (NEPs) remains usually retained in the extraction residue, alkaline and acid hydrolyses and enzymatic-assisted extraction (EAE) were carried out in this work to recover NEPs from the residue of conventional extraction from sweet cherry pomace. In vitro and in vivo evaluation of the antioxidant, antihypertensive, antiaging, and neuroprotective capacities employing Caenorhabditis elegans was achieved for the first time. Extractable phenolic compounds and NEPs were separated and identified by families by high-performance thin-layer chromatography (HPTLC) with UV/Vis detection. A total of 39 phenolic compounds were tentatively identified in all extracts by direct analysis in real-time high-resolution mass spectrometry (DART-Orbitrap-HRMS). EAE extracts presented the highest in vitro and in vivo antioxidant capacity as well as the highest in vivo antiaging and neuroprotective capacities. These results showed that NEPs with interesting biological properties are retained in the extraction residue, being usually underestimated and discarded.

Direct analysis in real time high-resolution mass spectrometry for authenticity assessment of lamb

In comparison to more traditional methods of determining food authenticity, such as gas chromatography analysis, the primary advantages of DART-HRMS include its high speed and throughput of analysis. This study used a non-targeted metabolomics method based on real-time high-resolution mass spectrometry combined with chemometric analysis to distinguish lamb samples from four regions. Orthogonal least squares-discriminant analysis revealed a distinct difference between these four lamb regions. The potential markers were chosen based on the variable's importance in projection values, variance, and fold change. A total of 79 markers were identified using the matching chemistry database. These markers differed significantly between lambs in four regions according to heatmap analysis. The linear discriminatory analysis model had an initial classification rate of 100.0% and a cross-validation accuracy of 82.50% on the identified markers. The research demonstrates that DART-HRMS can perform a rapid authentication evaluation of lamb samples.

Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage.

Metabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.

New strategies for the differentiation of fresh and frozen/thawed fish: A rapid and accurate non-targeted method by ambient mass spectrometry and data fusion (part A)

Ambient mass spectrometry (AMS) was applied for the first time to differentiate fresh and frozen/thawed Dicentrarchus labrax (European sea bass). One hundred and twenty samples were submitted to two extraction procedures and analyzed in positive and negative ion modes by direct analysis in real time-high resolution mass spectrometry (DART-HRMS). The four DART-HRMS datasets were concatenated with a low-level data fusion approach, and the resultant unique block of data was submitted to multivariate statistical analysis to tease out the most informative m/z values capable of codifying fresh and defrosted D. labrax . The statistical significance (p-value) and fold change (FC) of these informative signals were then evaluated with univariate analyses and tentatively assigned. The 25 features were then used to build a support vector machine (SVM) model capable of classifying D. labrax samples according to whether they were fresh or previously frozen. The SVM model has accuracy, sensitivity and specificity of 100%, both in training and test set. The SVM model was used to successfully classify an independent set of twenty fresh and frozen/thawed Salmo salar (Atlantic salmon). The concentrations of the most significant molecular features were quantified by gas-chromatography-mass spectrometry. • (+/−)DART-HRMS of polar and non-polar extracts of sea bass was performed. • The four DART-HRMS datasets were concatenated by low-level data fusion. • PLS-DA was performed on the training set to extrapolate the informative signals. • SVM classification model was constructed with the selected signals. • The built-in SVM model was validated with on hold-out subset with high accuracy.

Coral Genus Differentiation Based on Direct Analysis in Real Time-High Resolution Mass Spectrometry-Derived Chemical Fingerprints.

Coral reefs are one of the most biologically diverse ecosystems, and the accurate identification of the species is essential for diversity assessment and conservation. Current genus determination approaches are time-consuming and resource-intensive and can be highly subjective. To explore the hypothesis that the small-molecule profiles of coral are genus-specific and can be used as a rapid tool to catalogue and distinguish between coral genera, the small-molecule chemical fingerprints of the species Acanthastrea echinata, Catalaphyllia jardinei, Duncanopsammia axifuga, Echinopora lamellosa, Euphyllia divisa, Euphyllia paraancora, Euphyllia paradivisa, Galaxea fascicularis, Herpolitha limax, Montipora confusa, Monitpora digitata, Montipora setosa, Pachyseris rugosa, Pavona cactus, Plerogyra sinuosa, Pocillopora acuta, Seriatopora hystrix, Sinularia dura, Turbinaria peltata, Turbinaria reniformis, Xenia elongata, and Xenia umbellata were generated using direct analysis in real time-high resolution mass spectrometry (DART-HRMS). It is demonstrated here that the mass spectrum-derived small-molecule profiles for coral of different genera are distinct. Multivariate statistical analysis processing of the DART-HRMS data enabled rapid genus-level differentiation based on the chemical composition of the coral. Coral samples were analyzed with no sample preparation required, making the approach rapid and efficient. The resulting spectra were subjected to kernel discriminant analysis (KDA), which furnished accurate genus differentiation of the coral. Leave-one-out cross-validation (LOOCV) was carried out to determine the classification accuracy of each model and confirm that this approach can be used for coral genus attribution with prediction accuracies ranging from 86.67 to 97.33%. The advantages and application of the statistical analysis to DART-HRMS-derived coral chemical signatures for genus-level differentiation are discussed.

A longevity study to determine appropriate storage conditions for sexual lubricants using spectroscopic and spectrometric techniques

There has been an increase in the number of reported cases in which assailants have used a condom or sexual lubricant. Sexual predators understand that DNA from seminal fluid is one of the main forms of evidence used to connect a suspect to a victim or crime scene; therefore, the use of condoms in sexual assault cases has increased. This dilemma has led to research into other types of trace evidence (e.g., sexual lubricants). The study presented herein was performed to determine the optimal storage time length and conditions appropriate for storing trace lubricant residue. This research project used Fourier transform infrared spectroscopy (FTIR), direct analysis in real time-high resolution mass spectrometry (DART-HRMS), and gas chromatography-mass spectrometry (GC-MS) techniques to analyze the stored swabs containing sexual lubricants at 8 timepoints over 18 months. Blank, personal lubricant, and condom swabs were stored under several environmental conditions. Swab storage allowed for the determination of whether lubricants degraded, thus adversely affecting the ability to recognize the classification patterns. Resulting spectra from each instrument can be used to identify environmental degradation of lubricant samples and generate investigative leads. Pearson Correlation Coefficients and time plots of the chemical components were used to determine if chemical breakdown occurred for each lubricant and if the pattern changed significantly. Results showed that the strongest correlations occur between the initial timepoint (T 0) and one month (T1m), with correlations decreasing consistently up to eighteen months (T18m). The best storage conditions were determined to be 22 °C at both 16% and 50% humidity. The ability to understand the effects of environment and time to the analysis of sexual lubricants may offer helpful information when analyzing sexual assault kits.

High-performance thin-layer chromatography and direct analysis in real time-high resolution mass spectrometry of non-extractable polyphenols from tropical fruit peels

Passiflora species, mangosteen, and cherimoya peels are a source of bioactive phenolic compounds. Nevertheless, a significant fraction of polyphenols, called non-extractable polyphenols (NEPs), are retained in the extraction residue after a conventional extraction. Thus, alkaline, acid, and enzymatic-assisted extractions to recover high contents of antioxidant NEPs from the extraction residue of fruit peels, were compared in this work. A high-performance thin-layer chromatography method with UV/Vis detection was developed in order to obtain the phenolic profile for the extracts. The most intense bands were further analyzed by direct analysis in real-time-high-resolution mass spectrometry to tentatively identified NEPs in fruit peel extracts. Total phenolic and proanthocyanidin contents and antioxidant capacity of the extracts were measured to carry out a multivariate statistical analysis. Alkaline hydrolysis was the most efficient treatment to recover NEPs from fruit peels as well as a promising treatment to obtain antioxidant extracts along with EAE. Cherimoya peel extracts were the richest in antioxidant NEPs. This work highlights that many NEPs remain on the extraction residue of fruit peels after conventional extraction and are not usually taken into account.

Oregano authentication by mid-level data fusion of chemical fingerprint signatures acquired by ambient mass spectrometry

Economically motivated adulteration (EMA) of herbs and spices is very frequent and a major cause of concern to consumers, manufacturers and legislators. Rapid, non-targeted methods capable of distinguishing authentic herbs from those mixed with low cost materials are desirable. To this aim, ambient mass spectrometry (AMS) was applied to authenticate dried oregano leaves. Authentic and adulterated oregano samples were submitted to two extraction procedures and analysed in positive and negative ion modes by direct analysis in real time-high resolution mass spectrometry (DART-HRMS). Mid-level data fusion of the four blocks of DART-HRMS data was performed, and the resultant unique dataset was submitted to supervised statistical analysis to ascertain the signals that discriminate authentic from adulterated oregano. The fourteen most informative signals of authenticity were tentatively assigned and validated by support vector machine (SVM). In the final model, accuracy, sensitivity and specificity of >90% were obtained. Independent authentic and adulterated oregano samples were used to validate the discriminative m/z values and evaluate the classification capability of the model. To the best of our knowledge this is the first application of AMS coupled to mid-level data fusion for oregano authentication.

In vivo monitoring of volatile metabolic trajectories enables rapid diagnosis of influenza A infection.

We report that influenza A virus infection induces changes in odor traits that could be captured by real-time high-resolution mass spectrometry in a living mouse model. The most striking changes in the volatile metabolites may be associated mostly to glyoxylate/dicarboxylate metabolism.

MALDI-mass spectrometry imaging for touch chemistry biometric analysis: Establishment of exposure to nitroaromatic explosives through chemical imaging of latent fingermarks

Fingerprint ridge patterns continue to be tremendously important in forensic science because of their power to identify individuals. However, the current emphasis on the patterns fails to take advantage of additional chemical information they contain that may have a bearing on an investigation. One way this information can be useful is through correlating the fingerprint pattern with the presence of compounds that suggest exposure to compounds of interest, such as energetic materials that can be used to create explosive devices. We report here how interrogation of fingermarks by MALDI-mass spectrometry imaging (MSI) can be used to expose the presence of the explosive compounds trinitrotoluene (TNT), tetryl and picric acid, while yielding the fingerprint pattern that is traditionally collected in crime scene investigation. Ion images derived from diagnostic [M−H]− ions at nominal m/z 226 and 228 for TNT and picric acid respectively, and the [M-NO2-H]− ion at m/z 241 for tetryl were generated and revealed the fingerprint pattern. Direct analysis in real-time high-resolution mass spectrometry (DART-HRMS) analysis of fingerprints was found to be useful in enabling rapid detection of diagnostic ions, so that their presence could inform whether subsequent MALDI-MSI experiments should be performed. The approach illustrates how DART-HRMS and MALDI-MSI in tandem can be employed in touch chemistry biometrics for revealing a direct connection between an individual and materials of forensic interest to which they have been exposed, such as explosives.