Journal of Chromatography A最新文献

Optimization algorithms play an important role in method development workflows for gradient elution liquid chromatography. Their effectiveness has not been evaluated for chromatographic method development using standardized comparisons across factors such as sample complexity, chromatographic response functions (CRFs), gradient complexity, and application type. This study compares six optimization algorithms - Bayesian optimization (BO), differential evolution (DE), a genetic algorithm (GA), covariance-matrix adaptation evolution strategy (CMA-ES), random search, and grid search - for the development of gradient elution LC methods. Utilizing a multi-linear retention modeling framework, these algorithms were assessed across diverse samples, CRFs, and gradient segments, considering two observation modes: dry (in silico, deconvoluted), and wet (search-based, requiring peak detection). The optimization algorithms were evaluated based on their data (i.e. number of iterations) and time efficiency. Of the algorithms compared in this study, DE proved to be a highly competitive method for dry optimization purposes in terms of both data and time efficiency. BO outperformed all other algorithms in terms of data efficiency and was found to be most effective for search-based optimization, which requires a low number of iterations (<200). However, BO was found to be impractical for dry optimization requiring a large iteration budget due to its unfavorable computational scaling. It was observed that both the CRF and the sample have a strong influence on the efficiency of the algorithms, emphasizing the need for better benchmark samples and highlighting the importance of assessing CRF-induced complexity in the optimization landscape.

Polysorbates (PS), as non-ionic surfactants, contribute significantly to the stability of proteins in formulations. However, their lack of chromophore groups makes them difficult to detect with high sensitivity and simplicity. The charged aerosol detector (CAD) is an emerging and universal detector that can provide highly sensitive response signals to non-volatile or semi-volatile substances, such as esters, acids, oxidized aldehydes, and contaminant ions in PS. This article provides a comprehensive review of the qualitative and quantitative analysis of PS, profiling its composition, investigating the reasons for its degradation, and discussing its reaction mechanisms. This review aims to promote the quality control of PS production for the development of stable and safe protein formulations.

Steroid hormones constitute a group of hormones with molecular weights ranging from 200 to 400 daltons, characterized by their highly similar chemical structures. Each hormone within this group holds significant value for the diagnosis of various diseases. Accurate clinical measurement of the levels of each hormone is crucial for the diagnosis in clinical settings. Due to the wide variety and different properties of steroid hormones in organisms, sample pretreatment is the rate-limiting step for analysis and detection. In this paper, magnetic molecule-imprinting polymers (MMIPs) were prepared by surface imprinting on silicon coated magnetic spheres, and a detection method of MMIPs-combined with liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for 19 steroid hormones in plasma was developed and verified. Fourier transform infrared spectroscopy, field emission scanning electron microscopy and transmission electron microscopy were used to confirm the formation of MMIPs materials, and the conditions of material synthesis and pretreatment of steroid hormones from plasma were optimized. The detection method was evaluated by using linearity, LOD and LOQ, precision, accuracy and matrix effect. The linearity of 19 steroid hormones was good, and the linear correlation coefficient was greater than 0.995. The coefficients of variation were 2.1-9.8 % and 1.1-9.7 % for intra-day and inter-day, respectively, and the recoveries were 83.6 %-118.2 % at low concentration, and the recoveries of medium and high concentrations were 94.6 %-113.8 % and 89.5 %-113.6 %, respectively. The coefficient of variation of Relative matrix effect of 19 steroid hormones measured in different batches of plasma was 2.1-5.4 % after isotope internal standard correction, which eliminated the influence of matrix effect.

A flat membrane-based liquid-phase microextraction (FM-LPME) method was developed for the first time to simultaneously separate and extract basic and acidic pesticide analytes from the same sample. Using carbendazim and pirimicarb as representative basic pesticides, along with bromacil, diflubenzuron and 1,2-dibenzoyl-1‑tert-butylhydrazine (RH-5849) as representative acidic pesticides, the performance of FM-LPME for the extraction of these model pesticides has been optimised individually. Under optimal extraction conditions, the developed FM-LPME-LC-MS/MS method exhibited excellent linearity, with R² values exceeding 0.9903 in concentration ranges of 0.1-1400 ng mL^-1 for carbendazim and pirimicarb, and 1-1400 ng mL^-1 for bromacil, diflubenzuron and RH-5849. The limits of detection ranged from 0.01 to 0.09 ng mL^-1. The recoveries and relative standard deviations of all the tested pesticides at three spiked concentrations (100, 500 and 1200 ng mL^-1) were in the ranges of 80.0 %-125.0 % and 0.3 %-9.3 %, respectively. The FM-LPME-LC-MS/MS method demonstrated advantages in terms of being environmentally friendly, possessing a wide linear range, high sensitivity, high precision and satisfactory recoveries, thus highlighting its notable potential for the separation and extraction of basic and acidic pesticide residues in water samples.

Skin aging, characterized by reduced elasticity, wrinkles, and changes in pigmentation, presents significant challenges in the cosmetics industry. Identifying compounds that can help mitigate these effects is crucial to developing effective anti-aging treatments and improving skin health. An advanced analytical approach for identifying skin anti-aging compounds within complex natural mixtures must be developed to achieve this. This study introduces a state-of-the-art methodology that combines High-Performance Thin-Layer Chromatography (HPTLC) and in vitro skin anti-aging spectrophotometry bioassays with regression multivariate analysis and molecular docking. The proposed methodology integrates spectrophotometric assays for tyrosinase inhibition (anti-pigmentation), elastase inhibition (anti-wrinkle), and radical scavenging capacity (DPPH^•/ ABTS^• assays) with analytical signals obtained from HPTLC chromatograms using Partial Least Squares models (PLS). The PLS models for predicting elastase inhibition and antioxidative capacity showed high accuracy with minimal errors. This study introduces an innovative approach combining HPTLC profiling and PLS regression to identify single phenolic compounds/bands responsible for anti-aging effects. In addition, identified bioactives were submitted to molecular docking studies to elucidate the enzyme inhibition mechanisms of elastase and confirm our approach. This integrated, simple, cost-effective, and high-throughput approach represents a significant advancement in the discovery of anti-aging compounds, with promising implications for future skincare and therapeutic applications.

Molecularly imprinted nanocomposite membranes (MINMs) have shown great superiority in selective separation of acteoside (ACT) from phenylethanoid glycosides in Cistanche tubulosa. Herein, ACT-based MINMs (A-MINMs) with coral reef-like imprinted structure were proposed and developed for specifically separating ACT molecules. The nanospheres with hydrophilic multicores (NHMs) were introduced into polyvinylidene fluoride (PVDF) powders to obtain NHMs@PVDF membranes by a phase inversion method. Subsequently, the designed coral reef-like imprinted structure was constructed on NHMs@PVDF membrane-based surface. The A-MINMs with coral reef-like imprinted structure had dendritic and porous properties, which helped to form abundant ACT-imprinted cavities and sites of A-MINMs. In addition, the hydrophilic multicores and void space of NHMs together formed the affinity capture cages for hydrophilic ACT, enhancing rebinding capacity and permselectivity of A-MINMs. Therefore, A-MINMs with coral reef-like imprinted structure exhibited the high rebinding capacity (110.95 mg/g), rebinding selectivity of 5.15 and outstanding permselectivity of 10.04 toward ACT molecules. Moreover, the designed strategy of A-MHIMs with coral reef-like imprinted structure provides a new feasible method for permselectivity separation of other bioactive components.

In this study, a novel imidazolium-based ionic liquid (IL) coating was developed for stir bar sorptive extraction (SBSE) using a sol-gel method. The effects of different counterions, conditioning temperatures and polymer compositions were investigated. The stir bar with bis((trifluoromethyl)sulfonyl) amide 1-butyl-3-(3-(triethoxysilyl)propyl)-1H-imidazol-3-ium showed good mechanical and thermal stability with high resistance to water solubilization. The extraction efficiency of the IL-coated stir bar was evaluated on a mixture of 11 compounds presenting a wide range of polarities (log K_o/w values between 0.65 and 7.21) using thermodesorption gas chromatography coupled with Orbitrap high-resolution mass spectrometry (TD-GC-Orbitrap-HRMS). The results showed that extraction yields were increased for the IL-stir bar. In contrast, the commercial polydimethylsiloxane (PDMS) stir bar resulted in decreased yields with salt addition, particularly for compounds with log K_o/w > 4. SBSE of contaminants was performed on natural waters collected from France, followed by nontargeted analysis using TD-GC-Orbitrap-HRMS. The results revealed the detection of over 1,000 compounds, with 334 compounds annotated after deconvolution. The IL-stir bar with the addition of NaCl specifically extracted five times more compounds (167 compounds) than did the commercial PDMS stir bar (29 compounds) and more than 10 times more with the addition of NaCl with the PDMS stir bar (15 compounds). Various pollutants, including pesticides, personal care products, polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs), were identified. The annotations of the identified compounds were classified according to a level of confidence based on comparisons of retention indices, match library spectra and high-resolution mass filters.

Protein A (ProA) affinity chromatography plays an essential role in purifying monoclonal antibodies (mAbs) and their analogues by reducing impurities like residual host cell proteins (HCPs), residual DNA, process additives, and potential viral contaminants. Decades of mAb process development and commercialization efforts have built extensive prior knowledge in the Protein A process. The prior knowledge facilities streamlined process development and minimized the need for extensive process characterization studies to inform manufacturing control strategies. This manuscript presents a comprehensive prior knowledge package, consolidating process parameter characterization data from ten molecules developed by Eli Lilly and Company using the Protein A chromatography process. Results from multiple Design of Experiment (DOE) studies on these molecules demonstrated that no process parameters significantly impacted critical quality attributes when operated within platform ranges. Additionally, a Bayesian hierarchical model was applied to analyze historical data and predict the effects of process parameters, further confirming that parameter effects were insignificant across the platform ranges for the Protein A process. By leveraging this historical data package, we directly supported the classification of ProA process parameters for new therapeutic antibodies, effectively replacing the need for product-specific process characterization evaluations. This approach has been positively received by global regulatory agencies during the market authorization filings for two Lilly's products.

Multicomponent quantitative analysis (MCQA) is necessary for comprehensively characterizing the quality of complex samples, including medicines, foods. However, the limited supply of reference substances and the high costs associated with testing hinder the application of the MCQA using the external standard (ES) method. Here we propose a Molar Mass Coefficient (MMC) method for the quantification of multiple compounds with identical chromophore utilizing a single reference compound (SRC) by a UV detector. This method involves establishment of a linear equation of SRC (y_r=ax_r+b) with a standard compound r, followed by the derivation of quantitative equations for other components i using the deduced formula (y_i=(M_r/M_i)ax_i+b). The MMC method introduces only two known physical parameters, specifically the molar mass of compounds r and i, which ensures both the accuracy and practicality of this method. The feasibility of the MMC method was demonstrated with a set of simulated samples containing 17 flavonoids standard compounds, and further validated with samples of Scutellariae Radix and Ginkgo dry extract. The newly established method could accurately quantify flavonoids, yielding results and robustness consistent with the traditional ES method. Notably, for the contents of baicalin and kaempferol, when compared to the results obtained by ES method, the relative standard deviations (RSD%) for the commonly used method were 5.72 % and 4.96 %, respectively, while these values fall down to 0.73 % and 1.02 % when employing the MMC method. The MMC method exhibited significant advantages over existing methods, including high accuracy, robustness and low cost, implying its broad application in different fields.

Ion exchange chromatography (IEX) is an important analytical technique for the characterization of biotechnology-derived products, such as monoclonal antibodies (mAbs) and more recently, cell and gene therapy products such as messenger ribonucleic acid (mRNA) and adeno-associated viruses (AAVs). This review paper first outlines the basic principles and separation mechanisms of IEX for charge variant separation of biotherapeutics, and examines the different elution modes based on salt or pH gradients. It then highlights several recent trends when applying IEX for the characterization of biotechnology-derived products, including: i) the effective use of pH gradients, ii) the improvement of selectivity by using organic solvents in the mobile phase, multi-step gradients, or by combining ion pairing and ion exchange, and iii) the increase in analytical throughput using ultra-short columns or automated screening of conditions. The review also discusses the incorporation of IEX into multidimensional liquid chromatography setups, integrating it with other chromatographic dimensions for the analysis of complex biotherapeutic products. It also covers the coupling of IEX with mass spectrometry (MS), ion mobility spectrometry (IMS), and multi-angle light scattering (MALS) to identify the various species contained in complex biotherapeutic samples. In conclusion, IEX is considered today as an essential technique in the analytical toolbox for the characterization and quality control of biotechnology-derived products. It offers a unique separation mechanism and can be coupled with highly informative detectors, such as MS and MALS.