Analytical Instrument Documents

Fentanyl and fentanyl analogues represent a current and emerging threat in the United States as pure illicit narcotics and in mixtures with heroin. Because of their extreme potency, methods to safely and rapidly detect these compounds are of high interest. This work investigates the use of thermal desorption direct analysis in real time mass spectrometry (TD-DART-MS) and ion mobility spectrometry (IMS) as tools for the rapid and sensitive (nanogram to picograms) detection of fentanyl, 16 fentanyl analogues, and five additional opioids. Competitive ionization studies highlight that detection of these compounds in the presence of heroin is readily achievable, down to 0.1% fentanyl by mass with TD-DART-MS. With IMS, detection of nanogram levels of fentanyl in a binary fentanyl and heroin mixture is possible but can be complicated by decreased resolution in certain commercial instrument models. Modifications to the alarm windows can be used to ensure detection of fentanyl in binary mixtures. Additionally, three complex background matrices (fingerprint residue, dirt, and plasticizers) are shown to have a minimal effect of the detection of these compounds. Wipe sampling of the exterior of bags of questioned powders is shown to be a safe alternative method for field screening and identification, removing the need to handle potentially lethal amounts of material.

The roots of the shy plant Mimosa pudica emit a cocktail of small organic and inorganic sulfur compounds and reactive intermediates into the environment, including SO2, methanesulfinic acid, pyruvic acid, lactic acid, ethanesulfinic acid, propanesulfenic acid, 2-aminothiophenol, S-propyl propane 1-thiosulfinate, phenothiazine, and thioformaldehyde, an elusive and highly unstable compound that, to our knowledge, has never before been reported to be emitted by a plant. When soil around the roots is dislodged or when seedling roots are touched, an odor is detected. The perceived odor corresponds to the emission of higher amounts of propanesulfenic acid, 2-aminothiophenol, S-propyl propane 1-thiosulfinate, and phenothiazine. The mechanosensitivity response is selective. Whereas touching the roots with soil or human skin resulted in odor detection, agitating the roots with other materials such as glass did not induce a similar response. Light and electron microscopy studies of the roots revealed the presence of microscopic sac-like root protuberances. Elemental analysis of these projections by energy-dispersive x-ray spectroscopy revealed them to contain higher levels of K+ and Cl− compared with the surrounding tissue. Exposing the protuberances to stimuli that caused odor emission resulted in reductions in the levels of K+ and Cl− in the touched area. The mechanistic implications of the variety of sulfur compounds observed vis-à-vis the pathways for their formation are discussed.

Determining the species source of logs and planks suspected of being Araucaria araucana (Molina) K.Koch (CITES Appendix I) using traditional wood anatomy has been difficult, because its anatomical features are not diagnostic. Additionally, anatomical studies of Araucaria angustifolia (Bertol.) Kuntze, Araucaria heterophylla (Salisb.) Franco, Agathis australis (D.Don) Lindl., and Wollemia nobilis W.G.Jones, K.D.Hill & J.M.Allen have reported that these taxa have similar and indistinguishable anatomical characters from A. araucana. Transnational shipments of illegal timber obscure their geographic provenance, and therefore identification using wood anatomy alone is insufficient in a criminal proceeding. In this study we examine the macroscopic appearance of selected members of the Araucariaceae and investigate whether analysis of heartwood chemotypes using Direct Analysis in Real Time (DART) Time-of-Flight Mass Spectrometry (TOFMS) is useful for making species determinations. DART TOFMS data were collected from 5 species (n =75 spectra). The spectra were analyzsed statistically using supervised and unsupervised classification algorithms. Results indicate that A. araucana can be distinguished from the look-alike taxa. Another statistical inference of the data suggests that Wollemia nobilis is more similar and within the same clade as Agathis australis. We conclude that DART TOFMS spectra can help in making species determination of the Araucariaceae even when the geographic provenance is unknown.

A ionization technique in mass spectrometry called Direct Analysis in Real Time Mass Spectrometry (DART TOF-MS) coupled with a Direct Binding Assay was used to identify and characterize anti-viral components of an elderberry fruit (Sambucus nigra L.) extract without either derivatization or separation by standard chromatographic techniques. The elderberry extract inhibited Human Influenza A (H1N1) infection in vitro with an IC(50) value of 252+/-34 microg/mL. The Direct Binding Assay established that flavonoids from the elderberry extract bind to H1N1 virions and, when bound, block the ability of the viruses to infect host cells. Two compounds were identified, 5,7,3',4'-tetra-O-methylquercetin (1) and 5,7-dihydroxy-4-oxo-2-(3,4,5-trihydroxyphenyl)chroman-3-yl-3,4,5-trihydroxycyclohexanecarboxylate (2), as H1N1-bound chemical species. Compound 1 and dihydromyricetin (3), the corresponding 3-hydroxyflavonone of 2, were synthesized and shown to inhibit H1N1 infection in vitro by binding to H1N1 virions, blocking host cell entry and/or recognition. Compound 1 gave an IC(50) of 0.13 microg/mL (0.36 microM) for H1N1 infection inhibition, while dihydromyricetin (3) achieved an IC(50) of 2.8 microg/mL (8.7 microM). The H1N1 inhibition activities of the elderberry flavonoids compare favorably to the known anti-influenza activities of Oseltamivir (Tamiflu; 0.32 microM) and Amantadine (27 microM).

Elemental compositions are commonly determined from the exact m/z of the monoisotopic peak, which is often the lightest isotope. However, the lightest isotope peak is often weak or absent and the monoisotopic peak can be difficult to identify for organometallics, polyhalogenated compounds, or large molecules. An alternative approach using the abundant isotope for elemental composition determinations is presented here.

To ensure food safety, rapid detection of adulterated and counterfeit food products is critical. One such method, Direct Analysis in Real Time-Mass Spectrometry (DART-MS) (IonSense, Saugus, Mass.), quickly screens and analyzes a wide array of samples for mass spectral information and does not require sample preparation. As an example, several recent studies detail the analysis of cinnamon, mostly using chromatographic methods. High concentrations of coumarin in cinnamon have prompted numerous investigations as well, as its presence is suspected of being harmful. All of these studies require sample derivatization and long analysis times. In the current study, DART-MS was used to analyze cinnamon and detect the presence of coumarin.

DART-MS spectra were acquired under CID conditions to rapidly differentiate among  five synthetic cannabinoids contained within  ’herbal’ products purchased locally in New York State (USA). The spectra exhibited [M+H]+ ions and product ions unique to each cannabinoid that corresponded to major structural features. Five different cannabinoid analogs, alone and as mixtures of at least two cannabinoids, were identified in six herbal products and differentiated by their CID product ion patterns.

The blue lotus flower (Nymphea caerulea) is an Egyptian water lily containing apomorphine and nuciferine. Apomorphine has been described as a psychoactive alkaloid and is a non-selective dopamine agonist primarily used to treat Parkinson’s disease as it stimulates dopamine receptors and improves motor function. Nuciferine is an alkaloid associated with dopamine receptor blockade. Today, blue lotus flower is used as a sleep aid and anxiety reliever. The rebuildable dripping atomizer (RDA) is an electronic cigarette that allows direct application of an e-liquid onto the coil in the atomizer for aerosolization, compared to a typical electronic cigarette where the e-liquid is wicked from a storage vessel to the coil. Our laboratory received a dark-brown resin material from a concerned parent. The resin had been confiscated from an adolescent who had a reported history of marijuana use. The resin was later identified as blue lotus flower (N. caerulea). This resin, together with four commercially available blue lotus products, was analyzed for content. Apomorphine was detected in two samples, and nuciferine was detected in all five samples. The confiscated resin was determined to contain no apomorphine and 4300 ng/g of nuciferine. The nuciferine resin was shown to aerosolize using aRDA electric cigarette.

Using chemical fingerprints for timber species identification is a relatively new, but promising technique. However, little is known about the effect of pre-processing spectral data parameter settings on the timber species classification accuracy. Therefore, this study presents an extensive and automated analysis method using the random forest machine learning algorithm on a set of highly valuable timber species from the Meliaceae family. Metabolome profiles were collected using direct analysis in real-time (DART™) ionisation coupled with time-of-flight mass spectrometry (TOFMS) analysis of heartwood specimens for 175 individuals (representing 10 species). In order to analyse variability in classification accuracy, 110 sets of data pre-processing parameter combinations consisting of mass tolerance for binning and relative abundance cut-off thresholds were tested. Furthermore, for each set of parameters (designated “binning/threshold setting”), a random search for one hyperparameter of interest was performed, i.e. the number of variables (in this case ions) drawn randomly for each random forest analysis. The best classification accuracy (82.2%) was achieved with 47 variables and a binning and threshold combination of 40 mDa and 4%, respectively. Entandrophragma angolense is mostly confused with Entandrophragma candollei and Khaya anthotheca, and several Swietenia species are confused with each other due to the high similarity of their chemical fingerprints. Entandrophragma cylindricum, Entandrophragma utile, Khaya ivorensis, Lovoa trichilioides and Swietenia macrophylla are easy to discriminate and show less misclassifications. The choice of parameter settings, whether it is in the data pre-processing (binning and threshold) or classification algorithm (hyperparameters), results in variability in classification accuracy. Therefore, a preliminary parameter screening is proposed before constructing the final model when using the random forest algorithm for classification. Overall, DART-TOFMS in combination with random forest is a powerful tool for species identification.

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. A range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. Here, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.

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