Journal of Chromatography A最新文献

Taylor Dispersion Analysis (TDA) allows diffusion coefficient (D) or hydrodynamic radius (R_h) determination on a wide range of size between angstroms and about 300 nm. However, solute adsorption phenomena can affect the repeatability and reproducibility of TDA. Several numerical studies addressed the theoretical impact of solute adsorption in TDA, but very few experimental studies focus on this topic and no experimental methodologies were proposed so far to reduce the impact of adsorption in TDA. In this work, an experimental protocol, called plug-in-front TDA, consisting of adding the solute in the eluent at a lower concentration compared to the injected sample, was proposed to strongly limit the impact of adsorption on the R_h determination. This protocol was suggested based on the evidence that adsorption / desorption phenomena impacting narrow bore fused silica TDA in aqueous conditions are typically slow processes that can be counteracted by saturating the interaction sites during the experiments. Successful applications to proteins and mRNA lipid nanoparticles (LNP) in vaccine against Covid 19 and protein analysis were reported. TDA of proteins in conditions of strong interactions with the capillary surface was possible using the plug-in-front methodology. We anticipate that such experimental methodology will greatly help the experimentalist for implementing TDA in various applications.

Proanthocyanidins (OPACs) are the second largest class of plant metabolites after lignans. Although knowledge of their 3D conformations would add greatly to our understanding of their biological properties, very little has been published on the conformations of OPACs with a degree of polymerization (DP) above 4. We investigated the conformations of the linear epicatechin oligomers, prominent representatives of OPACs prevalent in apples and cocoa, where the epicatechin units are interconnected through the 4β-8 bonds. For DP-2 to DP-10 oligomers, conformational preferences reflected in the arrangement of consecutive flavan-3-ol units, are characterized by the φ torsion. For dimers, there are two energy wells corresponding to two preferred φ torsions, designated as compact and extended form. This behaviour is preserved in OPACs with higher DPs, but the most energetically favoured conformations are a combination of both, with compact-only or extended-only conformations being very unlikely. Thus, oligomers with DP ≥ 7 tend to assume an overall conformation approximating a spherical shape. This shape has a significant influence on the polarity of the OPAC oligomers expressed as 3D polar surface area, calculated using Spartan software for geometry-optimized 3D models, and possibly on other physicochemical properties. The results of polarity calculations provide a molecular-level rationale for the polarity-based chromatographic separation of the cocoa B-type procyanidins with DP range 4 to 10. In our experiments, using centrifugal partition chromatography (CPC) (a solvent system consisting of EtOAc-EtOH-water (6:1:5) v/v/v with aqueous phase stationary and upper phase mobile) we found that an enriched mixture of proanthocyanidins eluted first DP-1 (epicatechin) followed by consecutive elution of the DP-2 to DP-10 in the linear 4β-8 form. We demonstrated that such separation would not be possible if compact-only or extended-only conformations were present in solution. However, for the energy-favoured, spherically shaped conformations, the observed CPC elution order is fully justified.

Oligonucleotides (ONs) are acquiring clinical relevance and their demand is expected to grow. However, the ON production capacity is currently limited by high manufacturing costs. Since the purification of the target ON sequence from molecularly similar variants represents a major bottleneck, this work presents a resource-effective strategy for the optimization of their preparative reversed-phase chromatographic purification. First, a model based on the equilibrium-dispersive theory was introduced to describe the chromatographic operation. Considering a deoxyribose nucleic acid with 20 nucleobases as case study, a genetic algorithm was developed to efficiently determine the adsorption isotherm and mass transfer parameters for the target ON and impurities. After the estimation of these parameters, a strategy for the in-silico optimization of the operation was established. The product collection window, gradient duration, and resin loading were considered as process variables and their influence on yield and productivity was investigated after setting a purity specification of 99.0%. The optimal process parameters identified through this analysis were experimentally verified, confirming the reliability of the model, calibrated with only 5 experimental runs. In addition, this optimal setpoint was exploited to design the multicolumn countercurrent solvent gradient purification (MCSGP) of this ON mixture, which allowed to boost the yield of the process and to work at cyclic steady state, while respecting the purity constraint. This study confirmed the potential of this in-silico optimization strategy in both improving the performance of the traditional single-column operations and in the rapid development of multicolumn processes.

The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection and monitoring technologies. The precise identification of coal trace evidence presents a challenge with current methods, owing to its minute quantity, fine texture, and intricate composition. In this study, we integrated machine learning with the identification of volatiles to accurately differentiate coal geographical origins through the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The topographic distribution of volatiles in coals was visually depicted to elucidate the subtle distinctions through spectra and fingerprint analysis. Additionally, four supervised machine learning algorithms were developed to quantitatively predict the geographical origins of natural coals utilizing the HS-GC-IMS dataset, and these were subsequently compared with unsupervised models. Remarkable volatile compounds were identified through the quantitative analysis and optimal Random Forest model, which offered a rapid readout and achieved an average accuracy of 100 % in coal identification. Our findings indicate that the integration of HS-GC-IMS and machine learning is anticipated to enhance the efficiency and accuracy of coal geographical traceability, thereby providing a foundation for litigation and trials.

Per- and Polyfluoroalkyl Substances (PFAS) are a group of persistent organic pollutants that have received considerable attention from public and regulatory groups. Due to regulations of long-chain PFAS, the use of short-chain and ultrashort-chain PFAS is rapidly growing. Thus, there is an urgent need to develop quantitative methods for determining PFAS with different chain lengths in various environmental matrices. This study introduces an innovative liquid chromatography-mass spectrometry (LC-MS) system combining large volume injection (LVI) and online solid phase extraction (SPE). This system incorporates three columns: a reverse-phase (RP) column, a weak anion exchange (WAX) trap column, and a hybrid HILIC/ion-exchange (HILIC/IE) column, controlled by two valves. With valve switching, ultrashort-chain PFAS that are not retained by the RP column are enriched by the trap column, while other PFAS are separated by the RP column. The trapped ultrashort PFAS are then transferred to the HILIC/IE column for further separation. The LVI significantly enhances the method's sensitivity, allowing for rapid and simultaneous determination of ultrashort-, short- and long- chain PFAS in aqueous samples. The matrix effects from various environmental samples were evaluated, and the results indicate that this unique LC-MS method is suitable for analyzing all chain-length PFAS in various matrices, including surface water, sewage effluent, and seawater. Finally, this novel LC-MS method was applied to quantify PFAS in various water samples.

Plastic additives are introduced in plastic material formulations, along with organic polymers, to offer different properties such as stability, plasticity or color. However, plastic additives may migrate from the plastic material to the content (in case of plastic containers) or to the material in contact with the plastic, like human skin. In the case of plastic medical devices, this migration is of particular interest, as plastic additives may be deleterious to health. In the present paper, we examined the interest of combining supercritical fluid extraction (SFE) to supercritical fluid chromatography (SFC) hyphenated to mass spectrometry (MS) in an online system to characterize plastic additives in laboratory gloves, taken as samples of medical devices. A set of target compounds comprising 18 plasticizers, 4 antioxidants and 2 lubricants was defined and their detectability with MS was examined, where it appeared that electrospray ionization (ESI) provided better detectability than atmospheric pressure chemical ionization (APCI). After examining possible stationary phases with the help of Derringer desirability function, an isocratic chromatographic method (CO₂:methanol 95:5) was developed on Shim-pack UC Phenyl column. The extraction method was examined with a 3-level full factorial design of experiments to optimize the extraction temperature (40 °C) and pressure (200 bar). The online SFE-SFC-MS method was compared to offline methods where the samples were extracted with liquid solvents at atmospheric pressure or high pressure then analysed with SFC-MS. In all cases, offline methods showed significant contaminants (like the oleamide lubricant) issuing from laboratory plastic materials as nitrogen drying station, syringes and filters, while the online method allowed a complete elimination of laboratory contaminations. Furthermore, the online method saved time, solvents and laboratory consumables. It will also show that transferring a compressible fluid from a loading loop is favourable to high efficiency, as the resulting chromatographic peaks are much thinner than when transferring a liquid. Compared to injecting liquid heptane, the efficiency increase was 3.4-fold, while compared to injecting liquid methanol (a common practice in SFC), the efficiency increase was 13-fold. Finally, the additive composition of different laboratory gloves was compared.

Because of their major role in indoor and outdoor air pollution, even at trace levels, VOCs are of great interest, and their monitoring requires sensitive analytical instruments. Several techniques are commonly used, such as portable sensors, Proton Transfer Reaction Mass Spectrometry (PTR-MS) and Thermal Desorption Gas Chromatography (TD-GC). The latter is widely used off- and on-line with Flame Ionization Detectors (FID) or Mass Spectrometers (MS). Given the large number of molecules detected per chromatogram, the data generated by these monitoring techniques are usually checked and reprocessed manually. This process is extremely time consuming and could result in human error. The challenge is to provide reliable results as quickly as possible.

In this study, the performances of an on-line TD-GC system with dual detection FID and MS were tested. The Method Detection Limits (MDL), linearities and accuracies of 60 VOCs (alkanes, aromatics, oxygenated and halogenated) were calculated both for FID and MS detectors. The MDLs and accuracies ranged from 0.006 to 0.618 ppbv and from 77 % to 100 % for FID, and from 0.018 to 0.760 ppbv and from 80 % to 100 % for MS. Both detectors showed good complementarity and allowed the development of two programs to facilitate data analysis. These algorithms were designed to autonomously select optimal results between FID and MS detectors, and were evaluated for outdoor and indoor measurement conditions. Measuring VOCs in field campaigns is challenging, and it is anticipated that these programs could be extended to other types of dual-detector systems or for the comparison of data from different calibrated instruments.

The inorganic matrices such as metal concentrates, steel, cement, glass, clay, coal, graphite, rocks and sediments, ores etc. play a pivotal role in infrastructure development, transportation, and energy. The presence of non-metallic elements particularly halogens influence their quality, processing cost, and environment dynamics. The analysis of non-metals in such matrices is critically challenging due to their hardness, rigidity, and non-digestibility. This comprehensive review provides a critical comparison of various sample preparation methods in conjunction with pros and cons of advanced techniques for the detection of non-metals in complex matrices, particularly focusing on ion chromatography. Moreover, the review also addresses the challenges related to the enrichment and automation of non-metals analysis. In addition, the previous literature on non-metals determination in diverse range of inorganic matrices has been tabulated for the first time. These insights are intended to guide researchers, quality control analysts, environmental scientists, and policymakers in enhancing pollution monitoring and control strategies.

Excellent pretreatments before instrumental analysis are critical for separation and determination of target compounds for discovery of new drugs from herb medicines. We developed a rapid and highly-selective method to separate the bioactive compounds from herbal extract using protein affinity-selection spin column, which was packed with the new sorbent materials from integrating the recombinant β₂-adrenoceptor (β₂-AR) directly out of cell lysates onto the surface of microspheres. Protein affinity-selection spin column was placed in a centrifugal tube, where after the non-specific binders were released to the filtrate under the operational centrifugation, the specific binders on the spin column were cleaned with a washing solvent for LC-MS analysis. The known agonists of β₂-AR were retained/released on protein affinity-selection spin column but not on control column, demonstrating the method with good recovery (79.4∼95.7 %) and high repeatability (RSD < 3.5 %). The adsorption features of three ligands on the spin column were described best by Prism saturation binding model, and the high-affinity binding and the large binding capacity of the spin column make it feasible to trap the trace analytes effectively. It was applied in separating bioactive compounds from Alstoniae Scholaris extract, two of which were identified as picrinine and oleanolic acid in combination with LC-MS and verified as the potential agonists towards β₂-AR though molecular docking and cell experiments. Our study demonstrated that, the spin column with the immobilized protein sorbents in the centrifugal filter device represents a promising tool, enabling rapid and target-specific affinity separation of the bioactive compounds from herbal extract.