[Development of a widely-targeted metabolomics method based on gas chromatography-mass spectrometry]

Gas chromatography-mass spectrometry (GC-MS) detectors are widely used detection instruments owing to their distinct advantages over other analytical techniques, including lower sample consumption, higher sensitivity, faster analysis speed, and simultaneous separation and analysis. Metabolomics is an important component of system physiology that concerns systematic studies of the metabolite spectrum in one or more biological systems, such as cells, tissues, organs, body fluids, and organisms. Unfortunately, conventional GC-MS detectors also feature low scan rates, high ion loss rates, and a narrow concentration detection range, which limit their applications in the field of metabolomics. Therefore, establishing a GC-MS-based metabolomic analysis method with wide coverage is of great importance. In this research, a widely-targeted metabolomics method based on GC-MS is proposed. This method combines the universality of untargeted metabolomics with the accuracy of targeted metabolomics to realize the qualitative and semi-quantitative detection of numerous metabolites. It does not require a self-built database and exhibits high sensitivity, good repeatability, and strong support for a wide range of metabolic substances. The proposed method was used to establish the relationship between the retention time of straight-chain fatty acid methyl esters (FAMEs) and their retention index (RI) in the FiehnLib database based on the metabolite information stored in this database. We obtained a linear relationship that could be described by the equation y=40878x-47530, r²=0.9999. We then calculated the retention times of metabolites in the FiehnLib database under the experimental conditions based on their RI. In this way, the effects of significant variations in peak retention times owing to differences in the chromatographic column, temperature, carrier gas flow rate, and so on can be avoided. The retention time of a substance fluctuates within a certain threshold because of variations in instrument performance, matrix interference, and other factors. As such, the retention time threshold of the substance must be determined. In this paper, the retention time threshold was set to 0.15 min to avoid instrument fluctuations. The optimal scan interval was optimized to 0.20 s (possible values=0.10, 0.15, 0.20, 0.25, and 0.30 s) because longer sampling periods can lead to spectral data loss and reductions in the resolution of adjacent chromatographic peaks, whereas shorter sampling periods can result in deterioration of the signal-to-noise ratio of the collected signals. The metabolite quantification ions were optimized to avoid the interference of quantification ion peak accumulation in the case of similar peak times, and a selected ion monitoring (SIM) method table was constructed for 611 metabolites, covering 65% of the metabolic pathways in the KEGG (Kyoto Encyclopedia of Genes and Genomes). The developed method covered 39 pathways, including glycolysis, the tricarboxylic acid cycle, purine metabolism, pyrimidine metabolism, amino acid metabolism, and biosynthesis. Compared with the full-scan untargeted GC-MS method, the widely-targeted GC-MS method demonstrated a 20%-30% increase in the number of metabolites detected, as well as a 15%-20% increase in signal-to-noise ratio. The results of stability tests showed that 84% of the intraday relative standard deviations (RSDs) of metabolite retention times were less than 2% and 91% of that were less than 3%; moreover, 54% of the interday RSDs of metabolite retention times were less than 2% and 76% of that were less than 3%. The detection and analysis results of common biological samples confirmed that the proposed method greatly improved the quantity and signal-to-noise ratio of the detected metabolites and is applicable to substances that are thermally stable, volatile, or volatile after derivation and have relative molecular masses lower than 600. Thus, the widely-targeted GC-MS method can expand the application scope of GC-MS in metabolomics.

Progress in high-resolution isotope-ratio analysis of tree rings using laser ablation

Stable isotope ratio analysis of tree rings has been widely and successfully applied in recent decades for climatic and environmental reconstructions. These studies were mostly conducted at an annual resolution, considering one measurement per tree ring, often focusing on latewood. However, much more information could be retrieved with high-resolution intra-annual isotope studies, based on the fact that the wood cells and the corresponding organic matter are continuously laid down during the growing season. Such studies are still relatively rare, but have a unique potential for reconstructing seasonal climate variations or short-term changes in physiological plant properties, like water-use efficiency. The reason for this research gap is mostly technical, as on the one hand sub-annual, manual splitting of rings is very tedious, while on the other hand automated laser ablation for high-resolution analyses is not yet well established and available. Here, we give an update on the current status of laser ablation research for analysis of the carbon isotope ratio (δ13C) of wood, describe an easy-to-use laser ablation system, its operation and discuss practical issues related to tree core preparation, including cellulose extraction. The results show that routine analysis with up to 100 laser shot-derived δ13C-values daily and good precision and accuracy (ca. 0.1‰) comparable to conventional combustion in an elemental analyzer are possible. Measurements on resin-extracted wood is recommended as most efficient, but laser ablation is also possible on cellulose extracted wood pieces. Considering the straightforward sample preparation, the technique is therefore ripe for wide-spread application. With this work, we hope to stimulate future progress in the promising field of high-resolution environmental reconstruction using laser ablation.

Validation of a Novel RP-HPLC Technique for Simultaneous Estimation of Lignocaine Hydrochloride and Tibezonium Iodide: Greenness Estimation Using AGREE Penalties

Herein, we reported an HPLC method for the simultaneous determination of tibezonium iodide (TBN) and lignocaine hydrochloride (LGN). The method was developed according to the International Conference for Harmonization guidelines (ICH) Q2R1 using Agilent^® 1260 with a mobile phase consisting of acetonitrile and phosphate buffer (pH 4.5) in a volumetric ratio of 70:30 and flowing through a C₈ Agilent^® column at 1 mL/min. The results revealed that TBN and LGN peaks were isolated at 4.20 and 2.33 min, respectively, with a resolution of 2.59. The accuracy of TBN and LGN was calculated to be 100.01 ± 1.72% and 99.05 ± 0.65% at 100% concentration, respectively. Similarly, the respective precision was 100.03 ± 1.61% and 99.05 ± 0.48%. The repeatability for TBN and LGN was found to be 99.05 ± 0.48% and 99.19 ± 1.72%, respectively, indicating that the method was precise. The respective regression co-efficient (r²) for TBN and LGN was found to be 0.9995 and 0.9992. Moreover, the LOD and LOQ values for TBN were 0.012 and 0.037 µg/mL, respectively, while for LGN, they were 0.115 and 0.384 µg/mL, respectively. The calculated greenness of the method for ecological safety was found to be 0.83, depicting a green contour on the AGREE scale. No interfering peaks were found when the analyte was estimated in dosage form and in volunteers' saliva, depicting the specificity of the method. Conclusively, a robust, fast, accurate, precise and specific method was successfully validated to estimate TBN and LGN.

Target occupancy biomarker assay development using a conformation-selective antibody against small-molecule-bound TNF

Background: An antibody specific to small-molecule inhibitor-bound TNF has enabled the development of target occupancy biomarker assays to support the development of novel treatments for autoimmune disorders. Materials & methods: ELISAs were developed for inhibitor-bound and total TNF to determine the percentage of TNF occupancy in samples from stimulated blood. Inhibitor-saturated samples allowed measurement of total and inhibitor-bound TNF in a single electrochemiluminescence immunoassay. Results: TNF occupancy was proportional to inhibitor concentration in plasma samples. An electrochemiluminescence method for inhibitor-bound TNF was validated for use as a potential clinical occupancy biomarker assay. Conclusion: Development of these assays has allowed measurement of a target occupancy biomarker, which has supported progression of the first small-molecule inhibitors of TNF.

Simultaneous analysis of antihyperglycemic small molecule drugs and peptide drugs by means of dual liquid chromatography high-resolution mass spectrometry

OBJECTIVES

The study aimed to evaluate dual liquid chromatography (LC) coupled to high-resolution mass spectrometry (HRMS) for the simultaneous analysis of small and large molecule drugs by development and application of a validated bioanalytical method.

METHODS

The oral antihyperglycemic drugs (OAD) dapagliflozin, empagliflozin, glibenclamide, glimepiride, metformin, pioglitazone, repaglinide, saxagliptin, sitagliptin, and vildagliptin, as well as the antihyperglycemic peptides exenatide, human insulin, insulin aspart, insulin degludec, insulin detemir, insulin glargine, insulin glulisine, insulin lispro, and semaglutide were included in the analytical procedure. Analytes were extracted using a combination of protein precipitation and solid-phase extraction. Two identical reversed-phase columns were used for separation followed by Orbitrap high-resolution mass spectrometry. The whole procedure was validated according to international recommendations.

RESULTS

Different MS parameters had to be used for the two analyte groups, but dual LC separation allowed elution of all analytes within 12 min using the same column type. The analytical procedure was accurate and precise for most of the compounds except for exenatide, semaglutide, and insulin glargine, which were included qualitatively in the method. Analysis of proof-of-concept samples revealed OAD concentrations mostly within their therapeutic range, insulins could be detected in five cases but at concentrations below the lower limit of quantification except for one case.

CONCLUSIONS

Dual LC in combination with HRMS was shown to be a suitable platform to analyze small and large molecules in parallel and the current method allowed the determination of a total of 19 antihyperglycemic drugs in blood plasma within 12 min.

Prediction of transition state structures of gas-phase chemical reactions via machine learning

The elucidation of transition state (TS) structures is essential for understanding the mechanisms of chemical reactions and exploring reaction networks. Despite significant advances in computational approaches, TS searching remains a challenging problem owing to the difficulty of constructing an initial structure and heavy computational costs. In this paper, a machine learning (ML) model for predicting the TS structures of general organic reactions is proposed. The proposed model derives the interatomic distances of a TS structure from atomic pair features reflecting reactant, product, and linearly interpolated structures. The model exhibits excellent accuracy, particularly for atomic pairs in which bond formation or breakage occurs. The predicted TS structures yield a high success ratio (93.8%) for quantum chemical saddle point optimizations, and 88.8% of the optimization results have energy errors of less than 0.1 kcal mol^-1. Additionally, as a proof of concept, the exploration of multiple reaction paths of an organic reaction is demonstrated based on ML inferences. I envision that the proposed approach will aid in the construction of initial geometries for TS optimization and reaction path exploration.

Quantitative Analysis of Lysergic Acid Diethylamide (LSD) and 2-oxo-3-hydroxy-LSD in Urine by Automated Extraction and Liquid Chromatography-Tandem Mass Spectrometry

Recently, lysergic acid diethylamide (LSD) has become a resurgent drug of abuse. The detection of LSD is problematic because of the low dosage taken by users, light and heat sensitivity of the analyte, and the lack of efficient analytical methods. Presented here is the validation of an automated sample preparation method for the analysis of LSD and its primary urinary metabolite, 2-oxo-3-hydroxy-LSD (OHLSD), in urine samples by liquid chromatography-tandem mass spectrometry (LC-MS-MS). Analytes were extracted from urine using an automated Dispersive Pipette XTRaction (DPX) method on Hamilton STAR and STARlet liquid handling systems. The limit of detection for both analytes was administratively defined at the lowest calibrator used in the experiments, and the limit of quantitation was 0.05 ng/mL for both analytes. All validation criteria were acceptable per Department of Defense Instruction 1010.16 requirements. This method offers an efficient, sensitive analytical solution to routinely evaluate large numbers of urine specimens for LSD in workplace drug-deterrence programs.

Fanpy: A python library for prototyping multideterminant methods in ab initio quantum chemistry

Fanpy is a free and open-source Python library for developing and testing multideterminant wavefunctions and related ab initio methods in electronic structure theory. The main use of Fanpy is to quickly prototype new methods by making it easier to convert the mathematical formulation of a new wavefunction ansätze to a working implementation. Fanpy is designed based on our recently introduced Flexible Ansatz for N-electron Configuration Interaction (FANCI) framework, where multideterminant wavefunctions are represented by their overlaps with Slater determinants of orthonormal spin-orbitals. In the simplest case, a new wavefunction ansatz can be implemented by simply writing a function for evaluating its overlap with an arbitrary Slater determinant. Fanpy is modular in both implementation and theory: the wavefunction model, the system's Hamiltonian, and the choice of objective function are all independent modules. This modular structure makes it easy for users to mix and match different methods and for developers to quickly explore new ideas. Fanpy is written purely in Python with standard dependencies, making it accessible for various operating systems. In addition, it adheres to principles of modern software development, including comprehensive documentation, extensive testing, quality assurance, and continuous integration and delivery protocols. This article is considered to be the official release notes for the Fanpy library.

Single step method for high yield human platelet lysate production

BACKGROUND

We aimed to develop a single step method for the production of human platelet lysate (hPL). The method must result in high hPL yields, be closed system and avoid heparin use.

STUDY DESIGN AND METHODS

The method aimed at using glass beads and calcium. An optimal concentration of calcium and glass beads was determined by serial dilution. This was translated to a novel method and compared to known methods: freeze-thawing and high calcium. Quality outcome measures were transmittance, fibrinogen and growth factor content, and cell doubling time.

RESULTS

An optimal concentration of 5 mM Ca²⁺ and 0.2 g/ml glass beads resulted in hPL with yields of 92% ± 1% (n = 50) independent of source material (apheresis or buffy coat-derived). The transmittance was highest (56% ± 9%) compared to known methods (<39%). The fibrinogen concentration (7.0 ± 1.1 μg/ml) was well below the threshold, avoiding the need for heparin. Growth factor content was similar across hPL production methods. The cell doubling time of adipose derived stem cells was 25 ± 1 h and not different across methods. Batch consistency was determined across six batches of hPL (each n = 25 constituting concentrates) and was <11% for all parameters including cell doubling time. Calcium precipitation formed after 4 days of culturing stem cells in media with hPL prepared by the high (15 mM) Ca²⁺ method, but not with hPL prepared by glass bead method.

DISCUSSION

The novel method transforms platelet concentrates to hPL with little hands-on time. The method results in high yield, is closed system, without heparin and non-inferior to published methods.

Electronic excited states in deep variational Monte Carlo

Obtaining accurate ground and low-lying excited states of electronic systems is crucial in a multitude of important applications. One ab initio method for solving the Schrödinger equation that scales favorably for large systems is variational quantum Monte Carlo (QMC). The recently introduced deep QMC approach uses ansatzes represented by deep neural networks and generates nearly exact ground-state solutions for molecules containing up to a few dozen electrons, with the potential to scale to much larger systems where other highly accurate methods are not feasible. In this paper, we extend one such ansatz (PauliNet) to compute electronic excited states. We demonstrate our method on various small atoms and molecules and consistently achieve high accuracy for low-lying states. To highlight the method's potential, we compute the first excited state of the much larger benzene molecule, as well as the conical intersection of ethylene, with PauliNet matching results of more expensive high-level methods.

Response Surface Methodology Optimization for Analytical Microwave-Assisted Extraction of Resveratrol from Functional Marmalade and Cookies

A novel analytical method based on microwave-assisted extraction has been successfully optimized and validated to determine resveratrol from functional marmalade and cookies. The optimization was performed using a Box−Behnken design with three factors: solvent composition (60−100% and 10−70% methanol in water for marmalade and cookies, respectively), microwave power (250−750 W), and solvent-to-solid ratio (20:5−60:5). The main and quadratic effects of solvent composition significantly contributed to the recovery values (p < 0.005) for both kinds of samples. Additionally, the solvent-to-solid ratio and the quadratic effect of microwave power also influenced the resveratrol recovery from functional marmalade. Hence, the optimum condition for resveratrol extraction from marmalade (80% methanol, 500 W, solvent-to-solid ratio 40:5) and cookies (80% methanol, 250 W, solvent-to-solid ratio 20:5) was proposed. The extraction kinetics (5−30 min) was then studied to clarify the complete recovery of resveratrol from the food matrices resulting in 15 min as the optimum extraction time. The developed method showed a satisfactory precision indicated by the coefficient of variation (CV) lower than 5.70% for both repeatability and intermediate precision. To check the matrix effects, the developed MAE procedures were applied to a number of commercial marmalade and cookies. The high-fat and fiber cookies resulted in overestimated values due to the interfering ingredients. As a final point, the methods successfully measured the stability of naturally present resveratrol in grape-derived products while preparing functional marmalade and cookies.

Development of a single-run liquid chromatography-mass spectrometry analysis for the detection of 11 multiclass contaminants of emerging concern using a direct filtration method

In toxicological analysis, the analytical validation method is important to assess the exact risk of contaminants of emerging concern in the environment. Syringe filters are mainly used to remove impurities from sample solutions. However, the loss of analyte to the syringe filter could be considerable, causing an underestimate of the analyte concentrations. The current study develops and validates simultaneous liquid chromatography-mass spectrometry analysis using a direct filtration method to detect four groups of contaminants of emerging concern. The adsorption of the analyte onto three different matrices and six types of syringe filters is reported. The lowest adsorption of analytes was observed in methanol (16.72%), followed by deionized water (48.19%) and filtered surface lake water (48.94%). Irrespective of the type of the matrices, the lowest average adsorption by the syringe filter was observed in the 0.45 μm polypropylene membrane (15.15%), followed by the 0.20 μm polypropylene membrane (16.10%), the 0.20 μm regenerated cellulose (16.15%), the 0.20 μm polytetrafluoroethylene membrane (47.38%), the 0.45 μm nylon membrane (64.87%) and the 0.20 μm nylon membrane (71.30%). In conclusion, the recommended syringe filter membranes for contaminants of emerging concern analysis are polypropylene membranes and regenerated cellulose, regardless of the matrix used.

Identification and quantification of cyclitols and sugars isolated from different morphological parts of Raphanus sativus L

Through this study, we aimed to develop a new analytical method for identification and quantification of sugars and cyclitols isolated from different morphological parts of Raphanus sativus L (R. sativus). Accelerated solvent extraction with water was involved for targets extraction. Solid phase extraction was used for purification and preconcentration, while high performance liquid chromatography with evaporative light scattering detector (HPLC-ELSD) was used for chromatographic analyses. A short method of only 30 min for a single analysis was developed finally. The obtained results, allowed for quantification of eight targets, i.e., three cyclitols (D-pinitol, allo-inositol and scyllo-inositol) and five sugars (xylose, D-mannose, D-fructose, D-glucose and sucrose) that were determined simultaneously using a single analysis. The developed method can be applied in industry as a routine method for analysis of sugars and cyclitols from different sources.

A Novel Spectrophotometric Method Development for Quantification of Desidustat in Bulk and Pharmaceutical Dosage Form

BACKGROUND

Desidustat (DES) belongs to a new category of drugs, i.e., Hypoxia-Inducible Factor (HIF) propyl hydroxylase inhibitor, and is used for the treatment of anemia in chronic kidney disease. However, no method has yet been reported in the literature for the estimation of drugs.

OBJECTIVE

The objective of the study is to develop a simple, precise, and accurate method for determining DES in bulk and pharmaceutical dose form.

METHODS

The physicochemical characterization of the drug was performed using methanol as a solvent to establish the identity. According to ICH Q2 criteria, validation characteristics, such as specificity, linearity, accuracy, precision, limits of detection and quantification, and robustness, were assessed.

RESULTS

Maximum absorbance wavelength was observed at 229 nm. The sample solution remained stable for up to 12 hours. The linear response from 2 to 12 μg/ml of DES was y = 0.1087x + 0.0962 and r2 = 0.9963. The accuracy was between 100 to 101%. Precision was recorded under three criteria: repeatability, intraday and interday, for which results fell within the acceptable ranges (<2%). The limit of detection (LOD) and limit of quantification (LOQ) of the technique were 0.434 μg/ml and 1.316 μg/ml, respectively.

CONCLUSION

The proposed method was found to be beneficial for drug monitoring and the ongoing analysis of DES in research and quality control laboratories. This approach is simple, precise, rapid, economical, and sensitive.

New Analytical Methods for the Determination of New Anti-Viral Drug Favipiravir: A Potential Therapeutic Drug Against Covid-19 Virus, in Bulk and Dosage Forms

Simple, accurate and robust analytical methods have been developed and validated for the determination of favipiravir (FVPR) by RP-HPLC and UV spectroscopy techniques as per the ICH guidelines. In the RP-HPLC method for FVPR determination, the mobile phase was ammonium acetate buffer pH 6.5 in pump Aand methanol in pump B. The C18 (Sunfire) 5 μm, 4.6 × 250 mm column was used as a stationary phase, and the detection wavelength was at 323 nm. Under these conditions, FVPR was eluted as a sharp peak at 2.65 min and the overall time taken for each injection was 10 min. In case of the UV spectroscopy method, standard FVPR solutions were prepared with pure ethanol and scanned from 250 to 400 nm and a flourishing spectrum was obtained at 323 nm. Hence, the wavelength of 323 nm was fixed for the whole process of validation in both techniques. The limit of detection (LOD) and limit of quantification (LOQ) in the RP-HPLC method were 1.0 and 3.5 μg/mL, respectively, and the linearity was established in the 10 to 50 μg/mL range. In the UV spectroscopy method, the LOD and LOQ values were found to be 3.5 and 12 μg/mL, respectively, and the linearity was established within 20 to 60 μg/mL range. The regression coefficient was found to exceed 0.999 in both methods. The proposed RP-HPLC and UV spectroscopy techniques are simple, accurate, rugged and robust.

Developing the multi-dimensional mobility divide index (MDI) as a methodology to assess the accessibility level of public transport systems

Background: This paper presents the development of a multi-dimensional mobility divide index (MDI) for assessing the accessibility of public transport developed using a co-design approach, directly involving end-users in the index design process. The index measures the gap that persons with disabilities feel they need to over-come to use public transport in the same way non-disabled citizens do. The MDI covers six accessibility-related dimensions: 1) safety, 2) convenience, 3) comfort, 4) affordability, 5) travel time, and 6) autonomy. Methods: The method paper describes the step-by-step approach to create the MDI as a set of indicators to be rated by people with different access needs to 1) provide evidence of the main criticalities to be addressed through the design and implementation of new inclusive mobility solutions, 2) guide the design of new inclusive mobility solutions and measure their impacts, and 3) inform the transport sector encouraging positive changes in transport by providing recommendations for policy-making, new directions for service innovation, improvements and practical advice or highlighting investment priorities to pave the way for a more inclusive mobility. Results: We present our findings in ways that can inform universal design and provide actionable information to researchers, policymakers, transport and urban planners, operators, and stakeholders' representatives to promote inclusive and equitable mobility solutions for all. Conclusions: Finally, we suggest follow up research and innovation, as well as recommendations for its uptake and utilisation in the pursuit of European accessibility standards and requirements for products and services in the mobility sector.

The dominant nature of Herzberg-Teller terms in the photophysical description of naphthalene compared to anthracene and tetracene

The first order and second order corrected photoluminescence quantum yields are computed and compared to experiment for naphthalene in this manuscript discussing negative results. Results for anthracene and tetracene are recalled from previous work (Manian et al. in J Chem Phys 155:054108, 2021), and the results for all three polyacenes are juxtaposed to each other. While at the Franck-Condon point, each of the three noted polyacenes were found to possess a quantum yield near unity. Following the consideration of Herzberg-Teller effects, quantum yields stabilised for anthracene and tetracene to 0.19 and 0.08, respectively. Conversely, the second order corrected quantum yield for naphthalene was found to be 0.91. Analysis of this result showed that while the predicted non-radiative pathways correlate well with what should be expected, the approximation used to calculate second order corrected fluorescence, which yielded very positive results for many other molecular systems, here is unable to account for strong second order contributions, resulting in a grossly overestimated rate of fluorescence. However, substitution of an experimental radiative rate results in a quantum yield of 0.33. This work extols the importance of Herzberg-Teller terms in photophysical descriptions of chromophores, and highlights those cases in which a treatment beyond the above approximation is required.

HPLC with Fluorescence and Photodiode Array Detection for Quantifying Capmatinib in Biological Samples: Application to In Vivo and In Vitro Studies

Capmatinib, a recently approved tyrosine kinase inhibitor, is used for the treatment of non-small cell lung cancer. We describe two new HPLC methods for capmatinib quantification in vivo and in vitro. HPLC with a fluorescence detection method was used to quantify capmatinib in plasma for the first time. The method was successfully applied in a pharmacokinetic study following a 10 mg/kg oral dose of capmatinib given to rats. The chromatographic separation was performed using a Eurospher II 100-3 C18H (50 × 4 mm, 3 µm) column and a mobile phase containing 10 mM of ammonium acetate buffer (pH 5.5): acetonitrile (70:30, v/v), at a flow rate of 2.0 mL min^-1. The study also describes the use of HPLC-PDA for the first time for the determination of capmatinib in human liver microsomes and describes its application to study its metabolic stability in vitro. Our results were in agreement with those reported using LC-MS/MS, demonstrating the reliability of the method. The study utilized a Gemini-NX C18 column and a mobile phase containing methanol: 20 mM ammonium formate buffer pH 3.5 (53:47, v/v), delivered at a flow rate of 1.1 mL min^-1. These methods are suitable for supporting pharmacokinetic studies, particularly in bioanalytical labs lacking LC-MS/MS capabilities.

Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial

The performance of the current bottom-up liquid chromatography hyphenated with mass spectrometry (LC-MS) analyses has undoubtedly been fueled by spectacular progress in mass spectrometry. It is thus not surprising that the MS instrument attracts the most attention during LC-MS method development, whereas optimizing conditions for peptide separation using reversed-phase liquid chromatography (RPLC) remains somewhat in its shadow. Consequently, the wisdom of the fundaments of chromatography is slowly vanishing from some laboratories. However, the full potential of advanced MS instruments cannot be achieved without highly efficient RPLC. This is impossible to attain without understanding fundamental processes in the chromatographic system and the properties of peptides important for their chromatographic behavior. We wrote this tutorial intending to give practitioners an overview of critical aspects of peptide separation using RPLC to facilitate setting the LC parameters so that they can leverage the full capabilities of their MS instruments. After briefly introducing the gradient separation of peptides, we discuss their properties that affect the quality of LC-MS chromatograms the most. Next, we address the in-column and extra-column broadening. The last section is devoted to key parameters of LC-MS methods. We also extracted trends in practice from recent bottom-up proteomics studies and correlated them with the current knowledge on peptide RPLC separation.

Automation of tacrolimus measurement on volumetric absorptive microsampling devices by tandem mass spectrometry

Aims: An automated method for the measurement of blood tacrolimus on volumetric absorptive microsampling (VAMS) devices was developed. Materials & methods: VAMS devices prepared by the automated method were compared with those prepared by the existing manual method (n = 284; mean concentration: 8.0 μg/l; range: 0.6-18.1). Results: The performance of both methods was comparable. Passing-Bablok regression demonstrated an acceptable correlation (y = -0.449 + 1.06x). Bland-Altman analysis demonstrated acceptable agreement (mean bias: -0.007 μg/l; standard deviation: 1.536). Automation reduced operator touch time by 40 min (48-sample batch). Conclusion: Automated preparation of VAMS devices reduced touch time and improved process consistency, facilitating high-throughput testing and transformation of existing laboratory workflows. Automation did not improve precision for VAMS devices but did so for liquid blood samples.

User-Driven Strategy for In Silico Screening of Reversed-Phase Liquid Chromatography Conditions for Known Pharmaceutical-Related Small Molecules

In the pharmaceutical field, and more precisely in quality control laboratories, robust liquid chromatographic methods are needed to separate and analyze mixtures of compounds. The development of such chromatographic methods for new mixtures can result in a long and tedious process even while using the design of experiments methodology. However, developments could be accelerated with the help of in silico screening. In this work, the usefulness of a strategy combining response surface methodology (RSM) followed by multicriteria decision analysis (MCDA) applied to predictions from a quantitative structure-retention relationship (QSRR) model is demonstrated. The developed strategy shows that selecting equations for the retention time prediction models based on the pKa of the compound allows flexibility in the models. The MCDA developed is shown to help to make decisions on different criteria while being robust to the user's decision on the weights for each criterion. This strategy is proposed for the screening phase of the method lifecycle. The strategy offers the possibility to the user to select chromatographic conditions based on multiple criteria without being too sensitive to the importance given to them. The conditions with the highest desirability are defined as the starting point for further optimization steps.

An integral method for determining the molecular composition of lignin and its application

Lignin is a natural and renewable aromatic polymer, but only about 2% of lignin is utilized with high added value. Polydispersity and heterogeneity are the key reasons for the difficulty in separation, fractionation, characterization, purification and utilization of lignin. However, the molecular weight of lignin is still described from the overall perspective of number-/weight-average molecular weight (Mn and Mw), which if far from enough to understand the heterogeneous and dispersed lignin. To provide a tool for understanding the molecular weight of lignin from a molecular perspective, an integral method for quantifying the molecular characteristics of lignin molecules at arbitrary molecular intervals on the molecular weight distribution curve of lignin was established. The molecular contents of wheat straw lignin as well as its soluble and insoluble fractions at different intervals were calculated. The ease of fractionation of small molecules with weights lower than 8000 g/mol into soluble fractions, and that of large molecules with weights higher than 10,000 g/mol into insoluble fractions were quantitatively analyzed. The established integral method will significantly help in the understanding the properties of lignin at the molecular-level, as well as the fractionation and utilization of lignin.

Method Development for Separation and Analysis of Tire and Road Wear Particles from Roadside Soil Samples

A comprehensive understanding of tire and road wear particles (TRWPs) and their detection and quantification in soils is still challenged by the lack of well-set standardized methods, inherent technological inconsistencies, and generalized protocols. Our protocol includes soil sampling, size separation, and organic matter removal by using hydrogen peroxide followed by density separation and analysis. In this context, roadside soil samples from different sites in Kansas and Ohio, USA, were collected and analyzed. Tire cryogrinds analogous to TRWPs were used to evaluate various density separation media, and collected particles more than 1 mm in size were then subjected to infrared spectroscopy (IR), thermogravimetric analysis (TGA), and scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX) to confirm TRWP presence. Particles smaller than 1 mm were Soxhlet extracted, followed by gas chromatography-mass spectrometry (GC-MS) to validate the presence of tire-related intermediates. SEM-EDX validated the presence of elemental combinations (S + Zn/Na) ± (Al, Ca, Mg, K, Si) attributed to tires. Ketones, carboxylic acids, epoxies, cyclohexane, and benzothiazole sulfenamide (BTS) intermediates were the most probable tire-related intermediates observed in the roadside soil samples. Thus, this simple, widely applicable, cost-effective sample preparation protocol for TRWP analysis can assist TRWP research advancement in terrestrial environments.