Protein NMR assignment by isotope pattern recognition.

The current standard method for amino acid signal identification in protein NMR spectra is sequential assignment using triple-resonance experiments. Good software and elaborate heuristics exist, but the process remains laboriously manual. Machine learning does help, but its training databases need millions of samples that cover all relevant physics and every kind of instrumental artifact. In this communication, we offer a solution to this problem. We propose polyadic decompositions to store millions of simulated three-dimensional NMR spectra, on-the-fly generation of artifacts during training, a probabilistic way to incorporate prior and posterior information, and integration with the industry standard CcpNmr software framework. The resulting neural nets take [1H,13C] slices of mixed pyruvate-labeled HNCA spectra (different CA signal shapes for different residue types) and return an amino acid probability table. In combination with primary sequence information, backbones of common proteins (GB1, MBP, and INMT) are rapidly assigned from just the HNCA spectrum.

Fabrication of Isotope-Enriched Nanostructures Using Ultrafast Laser Pulses under Ambient Conditions for Biomolecular Sensing.

Recent advances in the use of stable isotopes necessitate novel synthesis techniques for isotope separation and enrichment that are scalable and offer high throughput. Stable-isotope-enriched nanostructures can offer unique advantages as nanomedicines, safe tracers, and labels and are critical for applications in various industrial processes, metabolic research, and medicine. So far, there exists no method to synthesize miniature isotope-enriched materials at the nanoscale. In this study, an ultrafast Laser-induced isotope enrichment at nanoscale (LIIEN) is put forward to synthesize isotope-enriched nanostructures, eliminating the need for large equipment and expenses, thereby demonstrating a lab-scale isotope enrichment process. A significant isotope enrichment for Carbon nanostructures is observed. The isotope enrichment can be attributed to the redistribution of isotope ions in the plasma plume explained by the plasma centrifuge model. The LIIEN synthesized structures exhibit excellent Surface-Enhanced Raman Scattering (SERS) signal enhancement and reproducibility, making them potential candidates for SERS-based biomolecule sensing. This technique is an efficient method to fabricate nanosized isotope-enriched structures of characteristic properties by carefully tuning laser parameters at ambient conditions.

A guide to precise measurements of isotope abundance by ESI-Orbitrap MS.

Stable isotopes of carbon, hydrogen, nitrogen, oxygen and sulfur are widespread in nature. Nevertheless, their relative abundance is not the same everywhere. This is due to kinetic isotope effects in enzymes and other physical principles such as equilibrium thermodynamics. Variations in isotope ratios offer unique insights into environmental pollution, trophic relationships in ecology, metabolic disorders and Earth history including climate history. Although classical isotope ratio mass spectrometry (IRMS) techniques still struggle to access intramolecular information like site-specific isotope abundance, electrospray ionization-Orbitrap mass spectrometry can be used to achieve precise and accurate intramolecular quantification of isotopically substituted molecules ('isotopocules'). This protocol describes two procedures. In the first one, we provide a step-by-step beginner's guide for performing multi-elemental, intramolecular and site-specific stable isotope analysis in unlabeled polar solutes by direct infusion. Using a widely available calibration solution, isotopocules of trifluoroacetic acid and immonium ions from the model peptide MRFA are quantified. In the second approach, nitrate is used as a simple model for a flow injection routine that enables access to a diverse range of naturally occurring isotopic signatures in inorganic oxyanions. Each procedure takes 2-3 h to complete and requires expertise only in general mass spectrometry. The workflows use optimized Orbitrap IRMS data-extraction and -processing software and are transferable to various analytes amenable to soft ionization, including metabolites, peptides, drugs and environmental pollutants. Optimized mass spectrometry systems will enable intramolecular isotope research in many areas of biology.

Applicability of self-consistent reaction field (SCRF) method to DFT estimation of hydrogen isotope separation factors in reversible processes.

In earlier quantum chemical calculations of isotope effects, chemical species in the liquid phase were generally treated as existing in the gas phase. In recent years, however, advances in computational programs have made it easier for the self-consistent reaction field (SCRF) method to handle chemical species in the liquid phase, and as a result, it has become easier to apply the SCRF method to isotope effect calculations. This paper concerns the scope of application of the DFT-SCRF method to reversible processes for hydrogen isotope enrichment. It is found that the applicability of the method depends on the type of the intermolecular interaction in the liquid phase and the degree of hydrogen isotope effect (separation factor) on which the process is based. When the magnitude of the isotope effect of the separation system is greater than 10-1, the simple SCRF method is fully applicable; when the magnitude is around 10-2, SCRF with a dimer model, in which the monomer is replaced by a dimer, is applicable for the analysis of the liquid phase with relatively strong intermolecular interactions. Anharmonic correction to the separation factor calculated based on harmonic frequencies may be effective to systems with the liquid phase with weak intermolecular interactions.

Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling.

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.

Copper Isotope Compositions Measured Using a Sapphire Dual Path MC-ICPMS with a Collision/Reaction Cell.

We present a new approach to Cu isotopic measurements using a state-of-the-art Nu Sapphire multicollector inductively coupled plasma source mass spectrometer equipped with a collision/reaction cell (CRC-MC-ICPMS). We investigate the effects of Na doping and Cu concentration mismatch between bracketing standard and unknown samples and demonstrate the efficacy of introducing a He-H2 gas mix into the CRC to efficiently eliminate the sample matrix-based 40Ar23Na+ isobaric interference on 63Cu+. This capability is crucial when measuring samples with high Na/Cu ratios, such as some biological samples, which have significantly different chemical compositions compared to most geological samples. Moreover, considering the necessity of obtaining large data sets for biological samples to ensure reliable interpretations, the implementation of a CRC for mitigating the 40Ar23Na+ interference offers the advantage of minimizing the requirement for extensive Cu chemical separation procedure prior to Cu isotopic measurements. Our results demonstrate that the accurate determination of the δ65Cu values is achievable for samples with Na/Cu concentration ratios of up to ∼65, even when measuring 100 ppb Cu solutions (equivalent to a signal of ∼3.5-4 V total Cu). Furthermore, our results showcase a good short-term repeatability on δ65Cu for pure Cu standard solutions (NIST SRM 976 and Cu-IPGP), typically of 0.05‰ (2 SD) when measuring >50 ppb Cu solutions. Our long-term external reproducibility stands at approximately 0.07‰ (2 SD). This value accounts for the variable Cu concentrations analyzed across the different analytical sequences (from 10 to 100 ppb Cu solutions). To validate the robustness of our analytical method, we first conduct a comparison between data sets from mice brains processed twice through column chemistry using a Thermo Finnigan Neptune MC-ICPMS and a Nu Sapphire CRC-MC-ICPMS in CRC mode. This comparison serves to verify the reliability of our method for measuring Cu isotopic composition using the CRC on samples with a low Na/Cu ratio after traditional chemical processing. Then, we compare the data sets obtained for biological standards (tuna fish ERM-CE 464 (IRMM) and human serum Seronorm Trace Elements Serum L-1) processed either once, or twice, through column chemistry and demonstrate that the CRC allows accurate Cu isotopic measurements of the samples processed only once and therefore with a higher Na/Cu ratio.

In Situ Discrimination and Cultivation of Active Degraders in Soils by Genome-Directed Cultivation Assisted by SIP-Raman-Activated Cell Sorting.

The identification and in situ cultivation of functional yet uncultivable microorganisms are important to confirm inferences regarding their ecological functions. Here, we developed a new method that couples Raman-activated cell sorting (RACS), stable-isotope probing (SIP), and genome-directed cultivation (GDC)─namely, RACS-SIP-GDC─to identify, sort, and cultivate the active toluene degraders from a complex microbial community in petroleum-contaminated soil. Using SIP, we successfully identified the active toluene degrader Pigmentiphaga, the single cells of which were subsequently sorted and isolated by RACS. We further successfully assembled the genome of Pigmentiphaga based on the metagenomic sequencing of 13C-DNA and genomic sequencing of sorted cells, which was confirmed by gyrB gene comparison and average nucleotide identity determination. Additionally, the genotypes and phenotypes of this degrader were directly linked at the single-cell level, and its complete toluene metabolic pathways in petroleum-contaminated soil were reconstructed. Based on its unique metabolic properties uncovered by genome sequencing, we modified the traditional cultivation medium with antibiotics, amino acids, carbon sources, and growth factors (e.g., vitamins and metals), achieving the successful cultivation of RACS-sorted active degrader Pigmentiphaga sp. Our results implied that RACS-SIP-GDC is a state-of-the-art approach for the precise identification, targeted isolation, and cultivation of functional microbes from complex communities in natural habitats. RACS-SIP-GDC can be used to explore specific and targeted organic-pollution-degrading microorganisms at the single-cell level and provide new insights into their biodegradation mechanisms.

The Historic Built Environment As a Long-Term Geochemical Archive: Telling the Time on the Urban "Pollution Clock".

This study introduces a novel methodology for utilizing historic built environments as reliable long-term geochemical archives, addressing a gap in the reconstruction of past anthropogenic pollution levels in urban settings. For the first time, we employ high-resolution laser ablation mass spectrometry for lead isotope (206Pb/207Pb and 208Pb/206Pb) analysis on 350-year-old black crust stratigraphies found on historic built structures, providing insights into past air pollution signatures. Our findings reveal a gradual shift in the crust stratigraphy toward lower 206Pb/207Pb and higher 208Pb/206Pb isotope ratios from the older to the younger layers, indicating changes in lead sources over time. Mass balance analysis of the isotope data shows black crust layers formed since 1669 primarily contain over 90% Pb from coal burning, while other lead sources from a set of modern pollution including but not limited to leaded gasoline (introduced after 1920) become dominant (up to 60%) from 1875 onward. In contrast to global archives such as ice cores that provide integrated signals of long-distance pollution, our study contributes to a deeper understanding of localized pollution levels, specifically in urban settings. Our approach complements multiple sources of evidence, enhancing our understanding of air pollution dynamics and trends, and the impact of human activities on urban environments.

Authenticating teas using multielement signatures, strontium isotope ratios, and volatile compound profiling.

High value food products are subject to adulterations and frauds. This study aimed to combine, in our knowledge for the first time, inorganic chemical tracers (multi-elements and Sr isotopy) with volatile organic compound (VOCs) to discriminate the geographic origin, the varieties and transformation processes to authenticate 26 tea samples. By measuring Sr isotope ratio using the multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), 6 out of 11 regions were successfully discriminated. The combination with the ICP-MS inorganic pattern allowed to discriminate 4 more regions with a significance level of 0.05. VOCs fingerprints, obtained with selected ion flow tube mass spectrometer (SIFT-MS), were not correlated with origin but with the cultivar and transformation processes. Green, oolong, and dark teas were clearly differentiated, with hexanal and hexanol contributing to the discrimination of oxidation levels. With this multi-instrumental approach, it is possible to certify the geographical origin and the tea conformity.

Stable isotope and trace element analyses with non-linear machine-learning data analysis improved coffee origin classification and marker selection.

BACKGROUND: This study investigated the geographical origin classification of green coffee beans from continental to country and regional levels. An innovative approach combined stable isotope and trace element analyses with non-linear machine learning data analysis to improve coffee origin classification and marker selection. Specialty green coffee beans sourced from three continents, eight countries, and 22 regions were analyzed by measuring five isotope ratios (δ13 C, δ15 N, δ18 O, δ2 H, and δ34 S) and 41 trace elements. Partial least squares discriminant analysis (PLS-DA) was applied to the integrated dataset for origin classification. RESULTS: Origins were predicted well at the country level and showed promise at the regional level, with discriminating marker selection at all levels. However, PLS-DA predicted origin poorly at the continental and Central American regional levels. Non-linear machine learning techniques improved predictions and enabled the identification of a higher number of origin markers, and those that were identified were more relevant. The best predictive accuracy was found using ensemble decision trees, random forest and extreme gradient boost, with accuracies of up to 0.94 and 0.89 for continental and Central American regional models, respectively. CONCLUSION: The potential for advanced machine learning models to improve origin classification and the identification of relevant origin markers was demonstrated. The decision-tree-based models were superior with their embedded variable identification features and visual interpretation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Machine learning approach for the prediction of the number of sulphur atoms in peptides using the theoretical aggregated isotope distribution.

RATIONALE: The observed isotope distribution is an important attribute for the identification of peptides and proteins in mass spectrometry-based proteomics. Sulphur atoms have a very distinctive elemental isotope definition, and therefore, the presence of sulphur atoms has a substantial effect on the isotope distribution of biomolecules. Hence, knowledge of the number of sulphur atoms can improve the identification of peptides and proteins. METHODS: In this paper, we conducted a theoretical investigation on the isotope properties of sulphur-containing peptides. We proposed a gradient boosting approach to predict the number of sulphur atoms based on the aggregated isotope distribution. We compared prediction accuracy and assessed the predictive power of the features using the mass and isotope abundance information from the first three, five and eight aggregated isotope peaks. RESULTS: Mass features alone are not sufficient to accurately predict the number of sulphur atoms. However, we reach near-perfect prediction when we include isotope abundance features. The abundance ratios of the eighth and the seventh, the fifth and the fourth, and the third and the second aggregated isotope peaks are the most important abundance features. The mass difference between the eighth, the fifth or the third aggregated isotope peaks and the monoisotopic peak are the most predictive mass features. CONCLUSIONS: Based on the validation analysis it can be concluded that the prediction of the number of sulphur atoms based on the isotope profile fails, because the isotope ratios are not measured accurately. These results indicate that it is valuable for future instrument developments to focus more on improving spectral accuracy to measure peak intensities of higher-order isotope peaks more accurately.

Wheat authentication：An overview on different techniques and chemometric methods.

Wheat (Triticum aestivum L.) is one of the most important cereal crops and is consumed as a staple food around the globe. Wheat authentication has become a crucial issue over the last decades. Recently, many techniques have been applied in wheat authentication including the authentication of wheat geographical origin, wheat variety, organic wheat, and wheat flour from other cereals. This paper collected related literature in the last ten years, and attempted to highlight the recent studies on the discrimination and authentication of wheat using different determination techniques and chemometric methods. The stable isotope analysis and elemental profile of wheat are promising tools to obtain information regarding the origin, and variety, and to differentiate organic from conventional farming of wheat. Image analysis, genetic parameters, and omics analysis can provide solutions for wheat variety, organic wheat, and wheat adulteration. Vibrational spectroscopy analyses, such as NIR, FTIR, and HIS, in combination with multivariate data analysis methods, such as PCA, LDA, and PLS-DA, show great potential in wheat authenticity and offer many advantages such as user-friendly, cost-effective, time-saving, and environment friendly. In conclusion, analytical techniques combining with appropriate multivariate analysis are very effective to discriminate geographical origin, cultivar classification, and adulterant detection of wheat.

Rapid discrimination of the authenticity and geographical origin of bear bile powder using stable isotope ratio and elemental analysis.

Bear bile powder (BBP) is one of the most famous traditional Chinese medicines derived from animals. It has a long history of medicinal use and is widely used in the treatment of hepatobiliary and ophthalmic diseases. Due to its similar morphological characterizations and chemical composition compared with other bile powders, it is difficult to accurately identify its authenticity. In addition, there are very few methods that could analyze the geographical origins of BBP. In this study, elemental analysis isotope ratio mass spectrometry (EA-IRMS) and inductively coupled plasma mass spectrometry (ICP-MS) were used to determine stable isotope ratios and elemental contents, respectively. Combined these variables with chemometrics, the discrimination models were established successfully for identifying the authenticity and geographical origins of BBP. Meanwhile, the discrimination markers were identified by calculating the variable importance for the projection (VIP) value of each variable. A total of 13 discrimination markers (δ13C, δ15N, C, Li, Mg, K, Ca, Cr, Ni, Zn, As, Se, and Sr) were used to further establish the fingerprint of BBP. According to similarity analysis, the authenticity and geographical origins of BBP could be identified without chemometrics. In conclusion, the present study established a reliable method for authenticity identification and origin traceability of BBP, which will provide references for the quality control of bile medicines.

Solvent Effects on the Temperature Dependence of Hydride Kinetic Isotope Effects: Correlation to the Donor-Acceptor Distances.

Protein structural effects on the temperature (T) dependence of kinetic isotope effects (KIEs) in H-tunneling reactions have recently been used to discuss about the role of enzyme thermal motions in catalysis. Frequently observed nearly T-independent KIEs in the wild-type enzymes and T-dependent KIEs in variants suggest that H-tunneling in the former is assisted by the naturally evolved protein constructive vibrations that help sample short donor-acceptor distances (DADs) needed. This explanation that correlates the T-dependence of KIEs with DAD sampling has been highly debated as simulations following other H-tunneling models sometimes gave alternative explanations. In this paper, solvent effects on the T-dependence of KIEs of two hydride tunneling reactions of NADH/NAD+ analogues (represented by ΔEa = EaD - EaH) were determined in attempts to replicate the observations in enzymes and test the protein vibration-assisted DAD sampling concept. Effects of selected aprotic solvents on the DADPRC's of the productive reactant complexes (PRCs) and the DADTRS's of the activated tunneling ready states (TRSs) were obtained through computations and analyses of the kinetic data, including 2° KIEs, respectively. A weaker T-dependence of KIEs (i.e., smaller ΔEa) was found in a more polar aprotic solvent in which the system has a shorter average DADPRC and DADTRS. Further results show that a charge-transfer (CT) complexation made of a stronger donor/acceptor gives rise to a smaller ΔEa. Overall, the shorter and less broadly distributed DADs resulting from the stronger CT complexation vibrations give rise to a smaller ΔEa. Our results appear to support the explanation that links the T-dependence of KIEs to the donor-acceptor rigidity in enzymes.

Mechanisms of Ni removal from contaminated groundwater by calcite using X-ray absorption spectroscopy and Ni isotope measurements.

A flow-through cell (FTC) experiment was conducted to identify mechanisms of Ni removal by calcite through study of changes in Ni speciation and Ni isotope signature during the treatment of simulated Ni-contaminated groundwater. Synthetic Ni-contaminated groundwater was pumped through a FTC packed with crushed natural calcite. Effluent samples were collected to determine concentrations of anions, cations, and for Ni isotope-ratio measurement. X-ray absorption spectroscopy (XAS) was performed on chosen spots of the solid phase along the FTC length. Isotope data indicated multiple mechanisms affected Ni removal in the FTC system. Ni adsorption to and coprecipitation with calcite dominated the early part of the experiment yielding a fractionation factor of ε = -0.5 ‰. Subsequently, Ni precipitation as a Ni-hydroxide phase became the major process controlling Ni removal, resulting in a fractionation factor ε = -0.4 ‰. XAS analysis confirmed the presence of both Ni(OH)2 and (Ni, Ca)CO3 types of Ni local structural environments. Results from this study highlight the potential of Ni isotopes as auxiliary tools to determine the processes involved in Ni attenuation from the environment. The characterization of mechanisms involved in Ni removal from solution is necessary to evaluate potential impacts to the environment and to develop effective remediation strategies.

Chemometric origin classification of Chinese garlic using sulfur-containing compounds, assisted by stable isotopes and bioelements.

Geographical origin discrimination of agro-products is essential to guarantee food safety and fair trade. Garlic samples cultivated in six provinces or major production regions in China were characterized for stable isotopes (δ13C, δ2H, δ18O, δ15N, and δ34S), bioelemental contents (% C, % N and % S), and sulfur-containing compounds (8 organosulfur components and 2 amino acids). Results showed that many of the 18 analyzed garlic variables had significant differences among production regions. Some sulfur-containing compounds found in garlic from different provinces had a strong correlation with sulfur isotopes, suggesting garlic sulfur isotopes were also affected by geographical origin. Two supervised pattern recognition models (PLS-DA and k-NN) were developed using stable isotopes, elemental contents, and sulfur-containing compounds, and had a discrimination accuracy of 93.4 % and 87.8 %, respectively. Chemometric classification models using multi-isotopes, elements and sulfur-containing compounds provides a useful method to authenticate Chinese garlic origins.

Perceptions on the treatment of apparent isotope effects during the analyses of reaction rate and mechanism.

Isotope substitution, a fascinating tool of physical chemistry, has been broadly applied in the research field of heterogeneous catalysis. In general, due to the differences in the mass-related atomic vibrational frequencies and zero-point energy of isotopic molecules, the apparent isotope effect (AIE) or observed kinetic isotope effect (observed KIE) from isotope substitution examination could provide unique knowledge regarding the reaction rate and mechanism of a catalytic reaction, such as the rate-determining step, key reaction intermediate, or catalyst design and synthesis. However, the treatment of the AIE is not as straightforward as the isotopic switch experiment, and needs sufficient care and comprehensive identification to deal with the influences from the equilibrium isotope effects (EIEs) of quasi-equilibrium elementary steps, kinetic isotope effect (KIE) of the pseudo rate-determining step, transition states, intrinsic reaction barriers, etc. Fundamentally, the key factors affecting the AIE could be the partition function part and the zero-point energy part of each single elementary step. Theoretically, the classification of the KIE could be based on the quantity of KIE (including normal KIE and inverse KIE) or the molecular transformation (including primary KIE, secondary KIE, tunneling KIE, and solvent KIE) involved. This article presents a recap of the fundamental concepts and relations of KIE, EIE and AIE, and a concise review on the selected applications of isotope effects throughout heterogeneous catalysis. Lastly, the meaningful perspectives regarding the critical factors that impact the AIE and the appropriate treatment of the AIE are discussed meticulously.

Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions.

We present a fast, accurate, and robust approach for determination of free energy profiles and kinetic isotope effects for RNA 2'-O-transphosphorylation reactions with inclusion of nuclear quantum effects. We apply a deep potential range correction (DPRc) for combined quantum mechanical/molecular mechanical (QM/MM) simulations of reactions in the condensed phase. The method uses the second-order density-functional tight-binding method (DFTB2) as a fast, approximate base QM model. The DPRc model modifies the DFTB2 QM interactions and applies short-range corrections to the QM/MM interactions to reproduce ab initio DFT (PBE0/6-31G*) QM/MM energies and forces. The DPRc thus enables both QM and QM/MM interactions to be tuned to high accuracy, and the QM/MM corrections are designed to smoothly vanish at a specified cutoff boundary (6 Å in the present work). The computational speed-up afforded by the QM/MM+DPRc model enables free energy profiles to be calculated that include rigorous long-range QM/MM interactions under periodic boundary conditions and nuclear quantum effects through a path integral approach using a new interface between the AMBER and i-PI software. The approach is demonstrated through the calculation of free energy profiles of a native RNA cleavage model reaction and reactions involving thio-substitutions, which are important experimental probes of the mechanism. The DFTB2+DPRc QM/MM free energy surfaces agree very closely with the PBE0/6-31G* QM/MM results, and it is vastly superior to the DFTB2 QM/MM surfaces with and without weighted thermodynamic perturbation corrections. 18O and 34S primary kinetic isotope effects are compared, and the influence of nuclear quantum effects on the free energy profiles is examined.

Bifunctionalized isotopologs as calibrants for standard-free quantitation of drug metabolites in plasma by liquid chromatography coupled with radiometry and mass spectrometry.

The reported method involves a novel workflow that eliminates the need for authentic reference standards for the quantitation of drug metabolites in biological samples using a single multi-isotopically labeled compound bearing both radio and stable isotopes. The resulting radio and stable bifunctionalized isotopolog (RADSTIL) of the parent drug is employed as a substrate for in vitro biotransformation to targeted RADSTILs of metabolites as calibrants. Inclusion of a radio label enables both radiometric and mass spectrometric detection. The addition of stable labels ensures the subsequent isotopic interference-free quantitation of unlabeled metabolites in preclinical and clinical samples. This affords a more accurate quantitation workflow compared with the current semi-quantitation method, which utilizes isotopic interfering radio isotopologs of metabolites alone as calibrants. The proof-of-concept is illustrated with (14 C,13 C2 )-acetaminophen where in vitro biotransformation produced (14 C,13 C2 )-sulfate and (14 C,13 C2 )-glucuronide calibrants. Absolute quantitation of the acetaminophen metabolites was then achieved by liquid chromatography coupled with radiometry and mass spectrometry. Quantitative data obtained by this method fell within 82-86% of the values from conventional LC-MS/MS method.

Determining the geographical origin of flaxseed based on stable isotopes, fatty acids and antioxidant capacity.

BACKGROUND: Flaxseed is an economically important oilseed crop whose geographic origin is of significant interest to producers and consumers because every region may exhibit particular quality characteristics. The lipid/fatty acid method of determining the geographic origin of flaxseed has not been found to be adequate. RESULTS: To improve the discrimination rate and the geographical traceability of this crop, the chemical profiles of the flaxseed samples were characterized via lipids/fatty acids, stable isotopes, and antioxidant capacity. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were also performed. A satisfactory discrimination rate of 98.6% was obtained after combining fatty acids, stable isotopes, and antioxidant capacity to trace the origin of flaxseed from five regions in northern China. CONCLUSION: This study provides an effective method for distinguishing the geographic origin of flaxseed. © 2021 Society of Chemical Industry.