Mixtures Of Analytes Research Articles

MXene-montmorillonite nanocomposites-based scaffold sensors for early pancreatic cancer diagnosis

Pancreatic cancer is increasingly prevalent and characterized by a high mortality rate. Due to the limitations of current diagnostic methods, early-stage detection remains elusive, contributing to persistently low survival rates among affected individuals. Nanomaterials have garnered significant attention in cancer research for their potential diagnostic applications. Among these, MXenes – a novel family of two-dimensional nanomaterials composed of transition metal carbides, nitrides, and carbonitrides – are of particular interest due to their unique properties. These include high electrical conductivity, hydrophilicity, thermal stability, large interlayer spacing, tunable structure, and high surface area. These characteristics make MXenes highly effective for detecting trace amounts of various analytes. In addition, their tunable structure enables precise manipulation of their properties, allowing for optimized sensing responses. Montmorillonite nanoclay (MMT), a member of the smectite group of natural clay minerals, is known for its ability to promote bone development and influence cell behavior. When combined with MXenes, MMT forms promising nanocomposites for early pancreatic cancer detection through sensing applications. The Ti3C2 MXene-MMT nanocomposites exhibit potential as scaffold sensors capable of distinguishing cancerous from non-cancerous samples by observing the distinctive patterns in resistance changes. In addition, MXenes possess excellent selectivity, allowing for the reliable identification of targeted analytes from a complex mixture of chemical and biological analytes. Due to the advanced sensing capabilities of MXene-MMT composite scaffold sensors, they hold great promise for early cancer diagnosis and tissue regeneration, providing a novel therapeutic approach to improving patient outcomes.

Polyelectrolyte modified Ag-nanosphere: A Practical Approach for Sensitive and Selective SERS-based Detection of Organic Dye Pollutants

This study presents a cost-effective method for fabricating surface-enhanced Raman spectroscopy (SERS) substrates using Ag-nanospheres (AgNS) capped with Poly(diallyldimethylammonium chloride) (PDADMAC) and poly(styrene sulfonate) (PSS). AgNS synthesis involves immersing Ag-nanocrystals in a nonaqueous solution, mixed with PEs in an aqueous solution via ultrasonic disturbance. Resulting aggregates form stable spherical assemblies with diameters ranging from 150 nm to 450 nm, and various characterization techniques, including scanning electron microscopy with energy-dispersive X-ray, UV-visible spectrophotometry, dynamic light scattering, and zeta potential analysis, were employed to analyze their fundamental chemical and physical properties. These qualified AgNSs serve as SERS substrates for sensitive and selective identification of charged organic dye contaminants, such as rhodamine 6G (R6G) and rose bengal (RB). Sensitivity assessments with the optimized quantities of either PDADMAC or PSS-capped AgNSs demonstrate successful detection down to concentrations of 10-14 M for RB and 4 x 10-13 M for R6G. The same SERS substrates also enable electrostatically driven selective detection even in analyte mixtures, and an additional variation of the SERS substrate comprising a complex of PDADMAC-capped and PSS-capped AgNSs exhibited distinct SERS spectra influenced by both positively and negatively charged analytes. Finally, successful detection of two oppositely charged pesticides was achieved through electrostatic attraction, so theses polyelectrolytes capped AgNS-based SERS substrate presents a promising avenue for efficiently and selectively detecting charged organic contaminants.

SWIEET-a salt-free alternative to QuEChERS.

The efficient extraction of various analytes from a wide spectrum of matrices with organic solvents is still a great challenge in analytical chemistry. Especially polar and charged compounds are hard to extract in combination with neutral analytes of intermediate to low polarity. The QuEChERS method is often chosen and has been adapted not only to the analysis of food samples, but also to environmental matrices (soil, wastewater) or biota. In this study, we overcome major drawbacks of QuEChERS such as low recoveries of charged analytes and impairment of downstream analysis by high salt loads. The new extraction method, applicable to liquid and solid samples, is called SWIEET (sugar water isopropanol ethyl nitrile extraction technique). Phase separation of the otherwise miscible extraction solvents water and acetonitrile is achieved by sugaring-out instead of salting-out. Extraction efficiencies were greatly improved by adding isopropanol to the acetonitrile phase. The concentrations of the additives glucose and isopropanol, as well as temperature, were optimized by a design of experiment. Further improvement was achieved through electro- or double-extractions. For all sample types tested (surface water, wastewater treatment plant effluent, tomato, soil, and oats), recoveries and precision were higher with SWIEET than with the established QuEChERS method. From wastewater treatment plant effluent, 75% recovery on average were achieved with our SWIEET method compared to 37% with QuEChERS for a model analyte mixture with polarities of logDpH7 = - 5.7 - 3.5. Higher recoveries and lower standard deviations compared to QuEChERS were achieved especially for polar and charged analytes such as metformin. Handling proved to be easy, since there was no additional solid phase and no tedious weighing of salts.

Digital Ion Trap Isolation and Mass Analysis of Macromolecular Analytes with Multiply Charged Ion Attachment.

Multiply charged ions produced by electrospray ionization (ESI) of heterogeneous mixtures of macromolecular analytes under native conditions are typically confined to relatively narrow ranges of mass-to-charge (m/z) ratio, often with extensive overlap. This scenario makes charge and mass assignments extremely challenging, particularly when individual charge states are unresolved. An ion/ion reaction strategy involving multiply charged ion attachment (MIA) to the mixture components in a narrow range of m/z can facilitate charge and mass assignment. In MIA operation, multiply charged reagent ions are attached to the analyte ions of opposite polarity to provide large m/z displacements resulting from both large changes in mass and charge. However, charge reduction of the high m/z ions initially generated under native ESI conditions requires the ability to isolate high m/z ions and to analyze even higher m/z product ions. Digital ion trap (DIT) operation offers means for both high m/z ion isolation and high m/z mass analysis, in addition to providing conditions for the reaction of oppositely charged ions. The feasibility of conducting MIA experiments in a DIT that takes advantage of high m/z ion operation is demonstrated here using a tandem 2D-3D DIT instrument. Proof-of-concept MIA experiments with cations derived from β-galactosidase using the 20- charge state of human serum immunoglobulin G (IgG, ∼149 kDa) as the reagent anion are described. MIA experiments involving mixtures of ions derived from the E. coli. ribosome are also described. For example, three components in a mixture of 70S particles (>2.2 MDa) were resolved and assigned with masses and charges following an MIA experiment involving the 20- charge state of human serum IgG.

Coaxial-Tube Quantitative Nuclear Magnetic Resonance for Various Solutions Using SI-Traceable Concentration References.

Quantitative nuclear magnetic resonance (qNMR) is an accepted method for determining analyte concentrations using quantitative substances in one spectrum. Conventional qNMR is performed using a mixture of analytes and reference substances. In coaxial-tube NMR, two tubes are used as different solutions, similar to normal NMR spectra. Currently, coaxial tubes with various diameters are available; however, coaxial-tube qNMR is limited, and a general analytical protocol is yet to be proposed. In this study, we established an effective volume ratio (EVR) measurement method using the weight density and qNMR methods. Various analyte concentrations were determined using coaxial-tube qNMR and an SI-traceable reagent. The EVR required for the qNMR concentration calculation was determined using a coefficient of variation (CV) of <1% for an inner tube of ϕ 3 mm or less. The peak integral of each substance was correlated with the effective volume, depending on the abundance of the tube and matched 1H in the solution. The T1 relaxation times differed depending on the substructure, and the T1 values of the formate and OH groups varied for each tube set. Thus, each partial structural characteristic of the peak must be understood before qNMR is performed. The concentrations of various substances, including hygroscopic substances, were determined using coaxial-tube qNMR. Coaxial tubes eliminate the need to mix the analyte with the reference substance; thus, we can quantify the analyte without causing pH and structural changes caused by other mixtures and reuse the analyte for other test systems.

Conducting Nickel Hydroxide Thin Film on Molybdenum Disulfide – Reduced Graphene Oxide Composite Electrode for Simultaneous Detection of Uric Acid, Dopamine and Ascorbic Acid

AbstractHerein we report the fabrication of a simple electrochemical sensor based on an electrode containing reduced graphene oxide and molybdenum disulphide (RGO/MoS2) as a conducting film onto the glassy carbon electrode (GCE) via a drop dry method to form GCE‐RGO/MoS2. The surface (GCE‐RGO/MoS2) was further modified with nickel hydroxide thin film using electrodeposition method to form GCE‐RGO/MoS2/Ni(OH)2. The materials and modification steps were thoroughly characterized using microscopy and spectroscopy methods. The composite electrode, GCE‐RGO/MoS2/Ni(OH)2, showed excellent electrocatalytic potential separation for the detection of dopamine, uric acid, and ascorbic acid. The electrocatalytic oxidation peak potentials were at 3 mV, 157 mV and 303 mV for AA, DA and UA, respectively. The composite electrode was also selective towards the determination of ascorbic acid (AA), dopamine (DA), uric acid (UA), and simultaneously in mixture of analytes. The low detection limits for AA, DA and UA were 1.17 μM, 0.15 μM and 1.15 μM, respectively. The composite electrode was applied for the detection of AA, DA and UA in spiked newborn calf serum samples with high percentage recoveries ranging from 96.6–100.8 % for AA, 92.8–104.2 % for DA and 99.4–102.3 % for UA.

Plasmonic Cross-Reactive Sensing Noses and Tongues.

The advancements in the capabilities of artificial sensory technologies, such as electronic/optical noses and tongues, have significantly enhanced their ability to identify complex mixtures of analytes. These improvements are rooted in the evolving manufacturing processes of cross-reactive sensor arrays (CRSAs) and the development of innovative computational methods. The potential applications in early diagnosis, food quality control, environmental monitoring, and more, position CRSAs as an exciting area of research for scientists from diverse backgrounds. Among these, plasmonic CRSAs are particularly noteworthy because they offer enhanced capabilities for remote, fast, and even real-time monitoring, in addition to better portability of instrumentation. Specifically, the synergy between the localized surface plasmon resonance (LSPR) of metallic nanoparticles (NPs) and CRSAs introduces advanced techniques such as LSPR, metal-enhanced fluorescence (MEF), surface-enhanced infrared absorption (SEIRA), surface-enhanced Raman scattering (SERS), and surface-enhanced resonance Raman scattering (SERRS) spectroscopies. This review delves into the importance and versatility of optical-CRSAs, especially those based on plasmonic materials, discussing recent applications and potential new research directions.

“PAW” a smart analytical process assessing lipophilicity of solutes in mixtures

BackgroundThe analysis of mixtures of contaminants remains a challenging task in many fields, including water quality and waste management. For example, the degradation of industrial waste such as plastics, leads to complex mixtures with hundreds of organic contaminants and often non-referenced analytes. In such cases, non-targeted or effects-based analyses provide complementary information to classical targeted-analyses, regarding contaminants nature or properties (molecular mass, lability, toxicity). In this study, a novel analytical method is proposed to characterise mixtures of unknown organic contaminants, with a focus on the lipophilicity of solutes. ResultsThe proposed process, named “PAW“ (Partition of Aqueous Waste), aims at the quantification of octanol-water partition coefficients (POW) of mixed organic analytes. The process is based on sequential liquid-liquid partition equilibria. The output result is a lipophilicity histogram of the solutes, screened according to the chosen detection method. The process quantifies the distribution of analytes as a function of their octanol-water partition coefficients, without requiring any identification or prior knowledge. The PAW process is applicable with various detectors (UV–Visible, total carbon, liquid scintillation, etc.) allowing to focus on specific families of contaminants (e.g. organic solutes, colloids, 14C-bearing, etc.). Experimental proofs of concept are proposed, illustrating process implementation and possible fields of application. The first example deals with purity analysis of synthetic radiolabeled compounds. The second example aims the monitoring of cellulose degradation and quantification of the lipophilicity of degradation products. SignificanceThe PAW analytical process seems especially useful for characterisation of mixtures containing both hydrophilic and lipophilic compounds, e.g. neutral and ionizable organic contaminants, hardly characterisable simultaneously by chromatographic methods. It could be complementary to more detailed targeted or screening analysis of samples and effluents. For example it may help assessing the composition and environmental fate of mixtures of unknown analytes, thus facilitating waste management or mitigation strategies.

Quick Response Auto‐Coding and Recognition of Mixed Vapors Via Microlaser Array Sensor

AbstractThe superior stimuli‐responsiveness, narrow linewidth, and high spectral multiplexing capacity of microlasers have led to their use as photonic tags for molecular labeling, encryption, and anticounterfeiting. However, the requirement of consistent lasing features for repeated measurements and the need for lasing features to change regularly with varying analytes pose a challenge to the efficient and convenient authentication of laser‐encoded photonic tags for practical applications. To address this challenge, an optical microsphere array is proposed that provides a set of real‐time typical lasing spectra collected from microspheres coated with specific recognition surface films of different sizes capable of recognizing one analyte or a mixture of analytes. These lasing spectra were transformed into 2D grayscale barcodes. Additionally, a gray value‐quick response code (GV‐QR code) is developed using deep learning methods, which enables the real‐time monitoring and identification of molecular concentration changes through GV‐QR autocoding, resulting in more precise, wide‐ranging, and reliable molecular detection.

Effect of Mobile Phase pH and Counterion Concentration on Retention and Selectivity for a Diol Column in Hydrophilic Interaction Liquid Chromatography

This work focuses on the effects of the mobile phase pH and the counterion concentration in buffer solution on retention in hydrophilic interaction liquid chromatography (HILIC) mode. Analytes with various acid-base properties and a silica-based Diol stationary phase were used. Retention and separation selectivity changes with ionization of the analytes and the adsorbent’s groups were discussed. It was demonstrated that the Diol phase behaved as a cation exchanger at pH 5.76 because of its residual dissociated silanols, while the phase provided almost no charge at lower pH (2.85). Separation efficiency and asymmetry factors for ionized compounds were also affected by the changes of mobile phase pH and counterion concentration. Separation conditions for the mixture of analytes of various acid-base properties were established.

A Terahertz Metasurface Sensor Based on Quasi-BIC for Detection of Additives in Infant Formula

Prohibited additives in infant formula severely affect the health of infants. Terahertz (THz) spectroscopy has enormous application potential in analyte detection due to its rich fingerprint information content. However, there is limited research on the mixtures of multiple analytes. In this study, we propose a split ring metasurface that supports magnetic dipole bound states in the continuum (BIC). By breaking the symmetry, quasi-BIC with a high quality (Q) factor can be generated. Utilizing an angle-scanning strategy, the frequency of the resonance dip can be shifted, resulting in the plotting of an envelope curve which can reflect the molecular fingerprint of the analytes. Two prohibited additives found in infant formula, melamine and vanillin, can be identified in different proportions. Furthermore, a metric similar to the resolution in chromatographic analysis is introduced and calculated to be 0.61, indicating that these two additives can be detected simultaneously. Our research provides a new solution for detecting additives in infant formula.

Detection of metallic pollutants in waste water using bio sensors and its remediation

AbstractWater pollution has emerged as the biggest threat to the sustenance of human civilization and the environment. With the increase in rapid industrialization and urbanization, there is a considerable increase in the influx of complex and diverse pollutants in water bodies. Hence continuous and efficient monitoring is required to detect the pollutants in the aquatic environment. Either preventing or detecting and subsequent elimination of these pollutants is of utmost importance for the health of the aquatic ecosystem. Biosensors have proved to be efficient in detecting these pollutants in a better way as compared to other conventional methods. Sensors are devices that have the ability to detect changes in the physical, chemical, or biological domains and produce a signal that can be measured. The distinguisher element in it minimizes noise caused by other components in the analyte mixture by being able to detect a specific analyte or set of analytes. This current review is focused on the role of biosensors in detecting metallic pollutants in water bodies. It also discusses the process of remediation of metallic pollutants in the aquatic environment.

A pyrene-based chromo-fluorogenic probe for specific detection of sarin gas mimic, diethylchlorophosphate.

Nerve agents are becoming serious issues for the healthy and sustainable environment of modern civilization. Therefore, its detection and degradation are of paramount importance to the scientific community. In the present contribution, we have introduced a chromo-fluorogenic pyrene-based probe, (E)-2-methoxy-3-(pyren-1-ylimino)-3,8a-dihydro-2H-chromen-4-ol (PMCO)to detect sarin stimulant diethylchlorophosphate (DCP) in solution and gaseous phases. On inserting DCP in PMCO solution, a visual colorimetric change from yellow to clear colourless in daylight and highly intensified blue fluorescence was observed instantly under a 365 nm portable UV lamp light. PMCO has outstanding selectivity and high sensitivity with a limit of detection of 1.32 μM in dimethyl sulfoxide (DMSO) medium and 77.5nM in 20% H2O-DMSO. A handy strained paper strip-based experiment was demonstrated to recognize DCP in a mixture of similar toxic analytes. A dip-stick experiment was performed to identify DCP vapour, and may be used as an effective photonic tool. We also demonstrated real sample analysis utilizing different DCP-spiked water samples and validating DCP detection even in various types of soils such as sand, field, and mud. Therefore, this present study provides an effective chemosensor for instant and on-site detection of toxic nerve agents in dangerous circumstances.

Smart 3D Ag-decorated TiO2 Nanostructure: An advanced synergistic SERS substrate for trace detection of analytes with diverse natures

Designing surface-enhanced Raman scattering (SERS) substrates that combine multiple advanced features in synergy is highly desirable for the SERS technique, however, it has been a long-standing challenge due to inherent trade-offs in feature selection. For instance, while nanoplasmonic surface functionalization bolsters attraction to target analytes, it simultaneously introduces barriers to direct contact. Similarly, the intrinsic hydrophilic or hydrophobic nature of substrates often limits their sensing effectiveness across a wide range of analyte types. Here, we demonstrate a smart 3D Ag-decorated TiO2 nanostructure, an advanced synergistic SERS substrate, created by controlling the formation of Ag nanoparticles on functionalized TiO2 nanomaterials, which integrates four unique features: uniform hotspot distribution, efficient analyte trapping, accessible plasmonic surfaces, and dual-phase detection. This design brings unachieved sensor efficiency across a diverse array of analytes with varying sizes and hydrophobicity. Moreover, our design exhibits a novel dual-phase detection capability within mixtures of hydrophilic and hydrophobic analytes. As a proof-of-concept, our results highlight the potential of designing SERS substrates with multiple advanced features that work synergistically, enabling trace detection of a broader range of analyte types in various environments. More broadly, we anticipate that this work paves the way for the development of other nanomaterials that are capable of attracting diverse molecules while retaining key features such as accessible plasmonic surfaces and wide-area ordered hotspot distribution. Such nanomaterials could be powerful for advanced applications in hotspot engineering, surface analysis, catalysis, and plasmon-mediated reactions.

A facile paper-based chromatography coupled Au nanodendrite on nickel foam for application in separation and SERS measurement

A simple paper-based chromatography coupling with nickel foam decorated Au nanodendrite (PP-AuND/NiF) was fabricated for simultaneous separation and surface-enhanced Raman scattering (SERS) detection of Rhodamine-6G (R6G) from a mixture of analytes. The three-dimensional porous nickel foam (NiF) was employed as a sampling diffusion platform, and AuND with a high surface active area beneficial for SERS efficiency was electro-deposited directly onto the NiF frame. The structure of AuND/NiF was characterized by X-ray diffraction and scanning electron microscopy. The AuND/NiF could detect R6G at 0.1 nM, and the enhancement factor was 1.84 x 106. The AuND/NiF was durable, with a slight signal decrease after 6 m of drop-testing. Also, upon three days of exposure to ambient air, the signal droped only 3.35 %. Subsequently, the PP-AuND/NiF was constructed by directly situating AuND/NiF on a paper strip, serving as a sample in and out to AuND/NiF. A mixture of two SERS active compounds, namely 2-Naphthalenethiol (2-NpSH) and Rhodamine 6G (R6G), was prepared in ethanol: water (1:1) solution to evaluate PP-AuND/NiF separation capability. Raman measurements along different distances of AuND/NiF were performed, and the signal of 2-NpSH was dismissed after 3.0 mm, while R6G’s signals were observed throughout AuND/NiF. In general, the PP-AuND/NiF demonstrated effective separation and SERS measurement of analytes in a mixture, which could be applicable for more complex samples in the future, especially in clinical analysis.

Revisiting column selectivity choices in ultra-high performance liquid chromatography–Using multidimensional analytical Design Spaces to identify column equivalency

Current guides and column selection system (CSS) platforms can provide some helpful insights with regard to the selection of alternative phases. Their practical reliability however, can also turn out to be questionable, especially considering the lack of detailed specifics, such as a clear definition of points of equivalence—appropriate running conditions under which the given analytical mixture can be satisfactorily resolved on various stationary phases. In this context, the use of multivariate modeling tools can be highly beneficial. These tools, when applied systematically, are ideal for uniquely characterizing complex LC-separation systems, a fact supported by numerous peer-reviewed papers.Revisiting our earlier work [1] and the applied systematic workflow [2], we used a Design Space modeling software (DryLab), with the main focus on building and comparing 3-dimensional separation models of amlodipine and its related impurities to identify shared method conditions under which columns are conveniently interchangeable. Our study comprised 5, C18-modified ultra-high performance liquid chromatography (UHPLC) columns in total, in some cases with surprising results. We identified several equivalences between the Design Spaces (DSs) of markedly different columns. Conversely, there were cases where, despite the predicted similarities in column data, the modeled DSs demonstrated clear differences between the selected stationary phases.

Multi-reflection Astral mass spectrometer with isochronous drift in elongated ion mirrors

Multi-reflection time-of-flight (MR ToF) mass spectrometers are promising tools for accurate mass analysis, which combine a high resolving power with a short duty cycle. Though MR ToFs have been used for long in nuclear physics to explore short-lived isotopes, a restricted mass range of closed ion traps did not allow their use in chemical and bio-chemical applications, in which an analyte mixture contains a wide range of ionic species. This paper describes development of an open-path multi-reflection analyzer in which ion trajectories stay separated in the phase space on the oscillations to achieve an unlimited mass range. The design employs a controlled adiabatic ion drift along electrostatic mirrors. Ion focusing and time-of-flight aberration are corrected via reflection in slightly converging mirrors and refraction on optimally shaped electrostatic prisms.

Spright: a probabilistic mass–density–radius relation for small planets

ABSTRACT We present spright, a python package that implements a fast and lightweight mass–density–radius relation for small planets. The relation represents the joint planetary radius and bulk density probability distribution as a mean posterior predictive distribution of an analytical three-component mixture model. The analytical model, in turn, represents the probability for the planetary bulk density as three generalized Student’s t-distributions with radius-dependent weights and means based on theoretical composition models. The approach is based on Bayesian inference and aims to overcome the rigidity of simple parametric mass–radius relations and the danger of overfitting of non-parametric mass–radius relations. The package includes a set of pre-trained and ready-to-use relations based on two M-dwarf catalogues, one catalogue containing stars of spectral types F, G, and K (FGK stars), and two theoretical composition models for water-rich planets. The inference of new models is easy and fast, and the package includes a command line tool that allows for coding-free use of the relation, including the creation of publication-quality plots. Additionally, we study whether the current mass and radius observations of small exoplanets support the presence of a population of water-rich planets positioned between rocky planets and sub-Neptunes. The study is based on Bayesian model comparison and shows somewhat strong support against the existence of a water-world population around M dwarfs. However, the results of the study depend on the chosen theoretical water-world density model. A more conclusive result requires a larger sample of precisely characterized planets and community consensus on a realistic water-world interior structure and atmospheric composition model.

A single recognition unit-based virtual sensor Array: Applying 3D fluorescence spectroscopy to inner filter effect-based sensing

A convenient, fast, low-cost detection and discrimination method is demanded for environmental monitoring but still it remains more technological challenges. Herein, we demonstrate that the inner filter effect (IFE), in combination with three-dimensional fluorescence spectroscopy, can offer a virtual sensor array (VSA) as apropersolution. And with the aid of pattern recognition techniques, it is feasible to recognize compounds with structural similarities economically and effectively. In this study, with the help of visual clustering plots of principal component analysis (PCA), a prediction model based on hierarchical strategy was made using support vector machine (SVM) method for the qualitative profiling of aromatic pollutants. The VSA was constructed by a single metal–organic framework (MOF) recognition unit (MOF-74 (Zn)) with the excitation wavelength as external regulatory factors. Pattern characteristics of four aromatics with very similar structures (phenylamine, chlorobenzene, nitrobenzene, and phenol), both single analyte and binary mixtures, were acquired. The primary constituents of multi-dimensional spectral signals were subsequently extracted and fed into a vector machine to construct a prediction model through 10-fold cross-validation optimization, resulting in a classification accuracy of 100% for single analytes and 96% for mixtures. Quantitative research has shown that, except for chlorobenzene, all three other analytes can be predicted in concentration within an acceptable error range, and the mixture can be predicted proportionally. Moreover, the VSA can be used to distinguish these pollutants in tap and river water also. We propose for the first time a new tack for the construction of VSA in a general manner, namely using three-dimensional full range fluorescence scanning for IFE based sensing to get multiple times of information resulting from different weak interaction between analyte and sensor for decision-making.

Prevalence of Δ8-tetrahydrocannabinol carboxylic acid in workplace drug testing.

Δ8-Tetrahydrocannabinol (Δ8-THC) recently became widely available as an alternative to cannabis. Δ8-THC is likely impairing and poses a threat to workplace and traffic safety. In the present study the prevalence of Δ8-THC in workplace drug testing was investigated by analyzing 1,504 urine specimens with a positive immunoassay cannabinoid initial test using an LC-MS-MS method quantifying 15 cannabinoid analytes after hydrolysis. Δ8-tetrahydrocannabinol-9-carboxylic acid (Δ8-THC-COOH) was detected in 378 urine specimens (15 ng/mL cutoff), compared to 1,144 specimens containing Δ9-THC-COOH. The data could be divided into three general groups. There were 964 (76%) Δ9-THC-COOH dominant (<10% Δ8-THC-COOH) and 139 (11%) Δ8-THC-COOH dominant (>90% Δ8-THC-COOH) specimens, with the remaining 164 (13%) specimens showing a mixture of both analytes (>90% Δ8-THC-COOH). Similar concentrations of Δ9-THC-COOH (median 187 ng/mL) and Δ8-THC-COOH (150 ng/mL) as the dominant species support the use of similar cutoffs and decision rules for both analytes. Apart from the carboxylic acid metabolites, 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-Δ9-THC, n = 1,282), Δ9-tetrahydrocannabivarin-9-carboxylic acid (Δ9-THCV-COOH, n = 1,058), Δ9-THC (n = 746) and 7-hydroxy-cannabidiol (7-OH-CBD, n = 506) were the most prevalent analytes. Two specimens (0.13%) contained ≥140 ng/mL Δ9-THC without Δ9-THC-COOH, which could be due to genetic variability in the drug metabolizing enzyme CYP2C9 or an adulterant targeting Δ9-THC-COOH. The cannabinoid immunoassay was repeated, and five specimens (0.33%) generated negative initial tests despite Δ9-THC-COOH concentrations of 54-1,000 ng/mL, potentially indicative of adulteration. The use of Δ8-THC is widespread in the US populations, and all forensic laboratories should consider adding Δ8-THC and/or Δ8-THC-COOH to their scope of testing. Similar urinary concentrations were observed for both analytes indicating that the decision rules used for Δ9-THC-COOH are appropriate also for Δ8-THC-COOH.