Electrochemical degradation of diclofenac generates unexpected thyroidogenic transformation products: Implications for environmental risk assessment

Diclofenac (DCF) is an environmentally persistent, nonsteroidal anti-inflammatory drug (NSAID) with thyroid disrupting properties. Electrochemical advanced oxidation processes (eAOPs) can efficiently remove NSAIDs from wastewater. However, eAOPs can generate transformation products (TPs) with unknown chemical and biological characteristics. In this study, DCF was electrochemically degraded using a boron-doped diamond anode. Ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry was used to analyze the TPs of DCF and elucidate its potential degradation pathways. The biological impact of DCF and its TPs was evaluated using the Xenopus Eleutheroembryo Thyroid Assay, employing a transgenic amphibian model to assess thyroid axis activity. As DCF degradation progressed, in vivo thyroid activity transitioned from anti-thyroid in non-treated samples to pro-thyroid in intermediately treated samples, implying the emergence of thyroid-active TPs with distinct modes of action compared to DCF. Molecular docking analysis revealed that certain TPs bind to the thyroid receptor, potentially triggering thyroid hormone-like responses. Moreover, acute toxicity occurred in intermediately degraded samples, indicating the generation of TPs exhibiting higher toxicity than DCF. Both acute toxicity and thyroid effects were mitigated with a prolonged degradation time. This study highlights the importance of integrating in vivo bioassays in the environmental risk assessment of novel degradation processes.

Deep reinforcement learning for the direct optimization of gradient separations in liquid chromatography

While Reinforcement Learning (RL) has already proven successful in performing complex tasks, such as controlling large-scale epidemics, mitigating influenza and playing computer games beyond expert level, it is currently largely unexplored in the field of separation sciences. This paper therefore aims to introduce RL, specifically proximal policy optimization (PPO), in liquid chromatography, and evaluate whether it can be trained to optimize separations directly, based solely on the outcome of a single generic separation as input, and a reward signal based on the resolution between peak pairs (taking a value between [-1,1]). More specifically, PPO algorithms or agents were trained to select linear (1-segment) or multi-segment (2-, 3-, or 16-segment) gradients in 1 experiment, based on the outcome of an initial, generic linear gradient (ϕstart=0.3, ϕend=1.0, and tg=20min), to improve separations. The size of the mixtures to be separated varied between 10 and 20 components. Furthermore, two agents, selecting 16-segment gradients, were trained to perform this optimization using either 2 or 3 experiments, in sequence, to investigate whether the agents could improve separations further, based on previous outcomes. Results showed that the PPO agent can improve separations given the outcome of one generic scouting run as input, by selecting ϕ-programs tailored to the mixture under consideration. Allowing agents more freedom in selecting multi-segment gradients increased the reward from 0.891 to 0.908 on average; and allowing the agents to perform an additional experiment increased the reward from 0.908 to 0.918 on average. Finally, the agent outperformed random experiments as well as standard experiments (ϕstart=0.0, ϕend=1.0, and tg=20min) significantly; as random experiments resulted in average rewards between 0.220 and 0.283, and standard experiments resulted in average rewards of 0.840. In conclusion, while there is room for improvement, the results demonstrate the potential of RL in chromatography and present an interesting future direction for the automated optimization of separations.

Comprehensive two-dimensional liquid chromatography with high resolution mass spectrometry to investigate the photoelectrochemical degradation of environmentally relevant pharmaceuticals and their degradation products in water

The widespread presence of organic micropollutants in the environment reflects the inability of traditional wastewater treatment plants to remove them. In this context, advanced oxidation processes (AOPs) have emerged as promising quaternary wastewater treatment technologies since they efficiently degrade recalcitrant components by generating highly reactive free radicals. Nonetheless, the chemical characterization of potentially harmful byproducts is essential to avoid the contamination of natural water bodies with hazardous substances. Given the complexity of wastewater matrices, the implementation of comprehensive analytical methodologies is required. In this work, the simultaneous photoelectrochemical degradation of seven environmentally relevant pharmaceuticals and one metabolite from the EU Watch List 2020/1161 was examined in ultrapure water and simulated wastewater, achieving excellent removal efficiencies (overall >95%) after 180 min treatment. The reactor unit was linked to an online LC sample manager, allowing for automated sampling every 15 min and near real-time process monitoring. Online comprehensive two-dimensional liquid chromatography (LC × LC) coupled with high resolution mass spectrometry (HRMS) was subsequently used to tentatively identify degradation products after photoelectrochemical degradation. Two reversed-phase liquid chromatography (RPLC) columns were used: an SB-C18 column operated with 5 mM ammonium formate at pH 5.8 (1A) and methanol (1B) as the mobile phases in the first dimension and an SB-Aq column using acidified water at pH 3.1 (2A) and acetonitrile (2B) as the mobile phases in the second dimension. This resulted in a five-fold increase in peak capacity compared to one-dimensional LC while maintaining the same total analysis time of 50 min. The LC x LC method allowed the tentative identification of 12 venlafaxine, 7 trimethoprim and 10 ciprofloxacin intermediates. Subsequent toxicity predictions suggested that some of these byproducts were potentially harmful. This study presents an effective hybrid technology for the simultaneous removal of pharmaceuticals from contaminated wastewater matrices and demonstrates how multidimensional liquid chromatography techniques can be applied to better understand the degradation mechanisms after the treatment of micropollutants with AOPs.

Automated method development in high-pressure liquid chromatography

Method development in liquid chromatography is a crucial step in the optimization of analytical separations for various applications. However, it is often a challenging endeavour due to its time-consuming, resource intensive and costly nature, which is further hampered by its complexity requiring highly skilled and experienced scientists. This review presents an examination of the methods that are required for a completely automated method development procedure in liquid chromatography, aimed at taking the human out of the decision loop. Some of the presented approaches have recently witnessed an important increase in interest as they offer the promise to facilitate, streamline and speed up the method development process. The review first discusses the mathematical description of the separation problem by means of multi-criteria optimization functions. Two different strategies to resolve this optimization are then presented; an experimental and a model-based approach. Additionally, methods for automated peak detection and peak tracking are reviewed, which, upon integration in an instrument, allow for a completely closed-loop method development process. For each of these approaches, various currently applied methods are presented, recent trends and approaches discussed, short-comings pointed out, and future prospects highlighted.

Comprehensive analysis of the effective and intra-particle diffusion of weakly retained compounds in silica hydrophilic interaction liquid chromatography columns

A detailed analysis of intra-particle volumes and layer thicknesses and their effect on the diffusion of solutes in hydrophilic interaction liquid chromatography (HILIC) was made. Pycnometric measurements and the retention volume of deuterated mobile phase constituents (water and acetonitrile) were used to estimate the void volume inside the column, including not only the volume of the mobile phase but also part of the enriched water solvent acting as the stationary phase in HILIC. The mobile phase (hold-up) volume accessible to non-retained components was estimated using a homologous series approach. The joint analysis of the different approaches indicated the formation of enriched water layers on the hydrophobic silica mesopore walls with a thickness varying significantly with mobile phase composition. The maximal thickness of the enriched water layers, which corresponded to the minimum void volume accessible to unretained solutes, marked a transition in the retention behavior of the studied analytes. Discrepancies between deuterated solvent measurements and pycnometry were explained by the existence of an irreplaceable water layer adsorbed on the silica surface. Regarding the diffusion behavior in HILIC, peak parking experiments were used to interpret the influence of the acetonitrile content on the effective diffusion coefficient Deff. A systematic decrease in Deff and molecular diffusion Dm was observed with decreasing acetonitrile concentration, primarily attributed to variations in mobile phase viscosity. Notably, Deff/Dm remained nearly unaffected by variations in mobile phase composition. Finally, the effective medium theory was used to make a comprehensive analysis of Dpart/Dm to study the contribution to band broadening when the solute resides in the mesopores. The obtained data unveiled a curvature with a minimum corresponding to conditions of maximum water-layer thickness and retention. For the weakly retained compounds (k' < 0.5) the Dpart/Dm-values were found to be relatively high (order of 0.35-0.5), which directly reflects the high γsDs/Dm-values that were observed (order 0.35-7).

Detailed comparison of in-house developed and commercially available heart-cutting and selective comprehensive two-dimensional liquid chromatography systems

Recently, two-dimensional liquid chromatography (2D-LC) has become a popular approach to analyze complex samples. This is partly due to the introduction of commercial 2D-LC systems. In the past, 2D-LC was carried out on in-house developed setups, typically consisting of several switching valves and sample loops as the interface between the two dimensions. Commercial systems usually offer different 2D-LC modes in combination with specialized software to operate the instrument and analyze the data. This makes them highly user-friendly, however, at an increased cost compared to in-house developed setups. This study aims to make a comparison between an in-house developed 2D-LC setup and a commercially available 2D-LC instrument. The comparison is made based on experimental differences, in addition to more general differences, including cost price, flexibility, and ease of operation. Special attention is also paid to the different strategies to deal with the mobile phase incompatibility between the highly orthogonal separation mechanisms considered in this work: hydrophilic interaction liquid chromatography (HILIC) and reversed-phase LC (RPLC). For the commercial 2D-LC instrument, this is done using active solvent modulation (ASM), a valve-based approach allowing the on-line dilution of the effluent eluting from the first dimension column before transfer to the second dimension (2D) column. For the in-house developed setup, a combination of restriction capillaries and a trap column is used. Using a sample of 28 compounds with a large polarity range, peak shapes and recoveries of the 2D-chromatograms are compared for both setups. For early eluting compounds, the selective comprehensive approach, currently only possible on the commercial 2D-LC instrument, results in the best peak shapes and recoveries, however, at the cost of an increased analysis time. In general, depending on the analytical goal (single heart-cut versus full-comprehensive 2D-LC), an in-house developed system can be satisfactory for the analysis of specific target compounds/samples. For more complex problems, it can be interesting to use a more specialized commercial 2D-LC instrument. Overall, this comparison study provides advice for analytical scientists, who are considering to use 2D-LC, on the type of equipment to consider, depending on the needs of their particular applications.

A perspective on the use of deep deterministic policy gradient reinforcement learning for retention time modeling in reversed-phase liquid chromatography

Artificial intelligence and machine learning techniques are increasingly used for different tasks related to method development in liquid chromatography. In this study, the possibilities of a reinforcement learning algorithm, more specifically a deep deterministic policy gradient algorithm, are evaluated for the selection of scouting runs for retention time modeling. As a theoretical exercise, it is investigated whether such an algorithm can be trained to select scouting runs for any compound of interest allowing to retrieve its correct retention parameters for the three-parameter Neue-Kuss retention model. It is observed that three scouting runs are generally sufficient to retrieve the retention parameters with an accuracy (mean relative percentage error MRPE) of 1 % or less. When given the opportunity to select additional scouting runs, this does not lead to a significantly improved accuracy. It is also observed that the agent tends to give preference to isocratic scouting runs for retention time modeling, and is only motivated towards selecting gradient scouting runs when penalized (strongly) for large analysis/gradient times. This seems to reinforce the general power and usefulness of isocratic scouting runs for retention time modeling. Finally, the best results (lowest MRPE) are obtained when the agent manages to retrieve retention time data for % ACN at elution of the compound under consideration that spread the entire relevant range of ACN (5 % ACN to 95 % ACN) as well as possible, i.e., resulting in retention data at a low, intermediate and high % ACN. Based on the obtained results, we believe reinforcement learning holds great potential to automate and rationalize method development in liquid chromatography in the future.

Detailed analysis of the effective and intra-particle diffusion coefficient of proteins at elevated pressure in columns packed with wide-pore core-shell particles

To determine the efficiency that can be obtained in a packed-bed liquid-chromatography column for a particular analyte, a correct determination of the molecular and effective diffusion coefficients (Dm and Deff) of the analyte is required. The latter is usually obtained via peak parking experiments wherein the flow is stopped. As a result, the column pressure rapidly dissipates and the measurement is essentially conducted at ambient pressure. This is problematic for analytes whose retention depends on pressure, such as proteins and potentially other large (dipolar) molecules. In that case, a conventional peak parking experiment is expected to lead to large errors in Deff. To obtain a better estimate ofDeff, the present study reports on the use of a set-up enabling peak parking measurements under pressurized conditions. This approach allowed us to report, for the first time, Deff for proteins at elevated pressure under retained conditions. First, Deff was determined at a (average) pressure of about 105 bar for a set of proteins with varying size, namely: bradykinin, insulin, lysozyme, β-lactoglobulin, and carbonic anhydrase in a column packed with 400 Å core-shell particles. The obtained data were then compared to those of several small analytes: acetophenone, propiophenone, benzophenone, valerophenone, and hexanophenone. A clear trend between Deff and analyte size was observed. The set-up was then used to determine Deff of bradykinin and lysozyme at variable (average) pressures ranging from 28 bar to 430 bar. These experiments showed a decrease in intra-particle and surface diffusion with pressure, which was larger for lysozyme than bradykinin. The data show that pressurized peak parking experiments are vital to correctly determine Deff when the analyte retention varies significantly with pressure.

Automated tuning of denoising algorithms for noise removal in chromatograms

Different algorithms, such as the Savitzky-Golay filter and Whittaker smoother, have been proposed to improve the quality of experimental chromatograms. These approaches avoid excessive noise from hampering data analysis and as such allow an accurate detection and quantification of analytes. These algorithms require fine-tuning of their hyperparameters to regulate their roughness and flexibility. Traditionally, this fine-tuning is done manually until a signal is obtained that removes the noise while conserving valuable peak information. More objective and automated approaches are available, but these are usually method specific and/or require previous knowledge. In this work, the L-and V-curve, k-fold cross-validation, autocorrelation function and residual variance estimation approach are introduced as alternative automated and generally applicable parameter tuning methods. These methods do not require any previous information and are compatible with a multitude of denoising methods. Additionally, for k-fold cross-validation, autocorrelation function and residual variance estimation, a novel implementation based on median estimators is proposed to handle the specific shape of chromatograms, typically composed of alternating flat baselines and sharp peaks. These tuning methods are investigated in combination with four denoising methods; the Savitsky-Golay filter, Whittaker smoother, sparsity assisted signal smoother and baseline estimation and denoising using sparsity approach. It is demonstrated that the median estimators approach significantly improves the denoising and information conservation performance of relevant smoother-tuner combinations up to a factor 4 for simulated datasets and even up to a factor 10 for an experimental chromatogram. Moreover, the parameter tuning methods relying on residual variance estimation, k-fold cross-validation and autocorrelation function lead to similar small root-mean squared errors on the different simulated datasets and experimental chromatograms. The sparsity assisted signal smoother and baseline estimation and denoising using sparsity approach, which both rely on the use of sparsity, systematically outperform the two other methods and are hence most appropriate for chromatograms.

Treatment of antimicrobial azole compounds via photolysis, electrochemical and photoelectrochemical oxidation: Degradation kinetics and transformation products

The degradation kinetics and transformation products of pharmaceutical azole drugs from Watch List 2020/1161 (fluconazole, FCZ; miconazole, MCZ; clotrimazole, CTZ; and sulfamethoxazole, SMX) are examined individually and as a mixture in Milli-Q water and simulated wastewater (SWW) upon treatment with three different advanced oxidation processes: (i) photolysis (UV), (ii) electrochemical (eAOP), and (iii) photoelectrochemical (eAOP/UV). For individual pollutant degradation, UV was found to be significantly more effective for SMX and CTZ compared to MCZ and FCZ. Whereas when treating the azole drugs mixture, eAOP/UV was determined to be the most effective treatment method. The degradation efficiency was higher in Milli-Q than in SWW because the treatment efficiency depended on the matrix compositions. The degradation products formed under different processes were identified, and the routes of transformation were proposed. The results of this study can assist in the selection of the most suitable treatment technology depending upon the pollutant or matrix.

Electrochemical degradation of 17α-ethinylestradiol: Transformation products, degradation pathways and in vivo assessment of estrogenic activity

Conventional water treatment methods are not efficient in eliminating endocrine disrupting compounds (EDCs) in wastewater. Electrochemical Advanced Oxidation Processes (eAOPs) offer a promising alternative, as they electro-generate highly reactive species that oxidize EDCs. However, these processes produce a wide spectrum of transformation products (TPs) with unknown chemical and biological properties. Therefore, a comprehensive chemical and biological evaluation of these remediation technologies is necessary before they can be safely applied in real-life situations. In this study, 17α-ethinylestradiol (EE2), a persistent estrogen, was electrochemically degraded using a boron doped diamond anode with sodium sulfate (Na₂SO₄) and sodium chloride (NaCl) as supporting electrolytes. Ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry was used for the quantification of EE2 and the identification of TPs. Estrogenic activity was assessed using a transgenic medaka fish line. At optimal operating conditions, EE2 removal reached over 99.9% after 120 min and 2 min, using Na₂SO₄ and NaCl, respectively. The combined EE2 quantification and in vivo estrogenic assessment demonstrated the overall estrogenic activity was consistently reduced with the degradation of EE2, but not completely eradicated. The identification and time monitoring of TPs showed that the radical agents readily oxidized the phenolic A-ring of EE2, leading to the generation of hydroxylated and/or halogenated TPs and ring-opening products. eAOP revealed to be a promising technique for the removal of EE2 from water. However, caution should be exercised with respect to the generation of potentially toxic TPs.

In-Depth Performance Analysis and Comparison of Monolithic and Particulate Zwitterionic Hydrophilic Interaction Liquid Chromatography Polymer Columns

The kinetic performance of different zwitterionic hydrophilic interaction liquid chromatography polymer columns is evaluated and compared in-depth. For this purpose, two lab-made monolithic columns, synthesized with different crosslinkers, and a commercial particle packed column are considered. It is found that performance evaluation techniques, such as comparing plate height curves or fitted A-, B- and C-terms, obtained by fitting experimental plate height data to a plate height model, are complicated by the determination of a reliable characteristic length. This is due to the very different morphology of these column types, and the heterogeneity of the monolithic columns. The occurrence of a convective flow through the packed particle column further complicates the interpretation of the obtained fitting parameters, as part of the C-term is wrongfully attributed to the A-term. Therefore, the use of the kinetic plot method is suggested for the comparative evaluation of these columns, as kinetic plots do not require the determination of a characteristic length, nor rely on any fitting parameters. With the kinetic plot method, it is demonstrated that the lab-made monolithic columns outperform the packed particle column for plate counts between 10,000 and 800,000. This is attributed to the higher column efficiency of these columns, due to their small domain and skeleton sizes, and their high permeability, resulting from their high external porosity and the occasional occurrence of preferential flow paths.

Sterilisation of biopharmaceuticals: Effect of gamma irradiation, e-beam irradiation and nitrogen dioxide on human insulin

Biopharmaceuticals are administered parenterally and therefore sterility is required. Sterility can be obtained via different processes including exposure to steam or dry heat. Sterilisation studies on biopharmaceuticals, which are highly sensitive medicinal products, are scarce. This study investigates the effect of different sterilisation processes on recombinant human insulin in solid state (gamma and e-beam irradiation (w/wo dry ice), nitrogen dioxide (NO₂)) and in aqueous solution (gamma irradiation (w/wo dry ice, w/wo glycerin)) using ultra-high performance liquid chromatography-diode array detection-mass spectrometry. It is observed that NO₂ substantially degrades the solid samples, while gamma and e-beam irradiation result in lower levels of degradation (mean normalized peak areas of 95.2-96.2 % with respect to the non-sterilised samples). Gamma irradiation of insulin solutions with and without dry ice at 2.5 kGy results in mean normalised peak areas of 85 % and <40 % with respect to the non-sterilised samples, respectively. It is concluded that sterilisation using ionising radiation of liquid biopharmaceuticals with insulin and sterilisation of insulin dry powder using NO₂ is less suitable with the set-ups used here because of substantial degradation. In contrast, evidence is presented in favour of sterilisation of insulin dry powder using ionising radiation.

Application of partial ozonation on tank truck cleaning concentrate and the influence on biodegradability and ecotoxicity: a pilot-scale study

This study investigates the pilot-scale ozone treatment of reverse osmosis concentrate (ROC), originating from variable tank truck cleaning wastewater. The influence of ozonation on short- and long-term biodegradation potential was examined through respirometry and Zahn-Wellens, respectively. Ecotoxicity was also examined for several concentrate batches and ozonation steps. Chemical oxidation through ozone had a beneficial effect on chemical oxygen demand removal, with a removal efficiency up to 56%. Formation of short-term biochemical oxygen demand (BOD_st) was induced for several, but not all batches, showing the potential of subsequent biological treatment of ozonated ROC. An increase in the inherent biodegradability through Zahn-Wellens was observed for all tested samples after ozonation, rising to a maximum of 68% after 3 hours of ozonation, highlighting the importance of sludge adaptation. Ecotoxicity, tested with Artemia franciscana and the saltwater algae P. tricornutum, showed initial decreases in algae inhibition after short ozonation periods. An increase in algae inhibition was, however, seen after prolonged ozonation for all tested ROC samples, pointing to the formation of ecotoxic by-products. Artemia showed no significant toxicity effects. When applying biological treatment through Zahn-Wellens, a decrease in ecotoxicity was observed for several samples, likely through biological oxidation of the produced degradation products.

Graph Neural Networks for Improved Retention Time Predictions

In this extended special feature to celebrate the 35th anniversary edition of LCGC Europe, leading figures from the separation science community explore contemporary trends in separation science and identify possible future developments.

Kinetics and mechanisms of the carbamazepine degradation in aqueous media using novel iodate-assisted photochemical and photocatalytic systems

The present study investigates the kinetics and mechanisms of carbamazepine (CBZ) degradation using a novel UV/iodate (IO₃^-) system for the first time and explores the influence of process conditions on its degradation. UV/IO₃^- showed high degradation efficiencies in a wide range of pHs, especially under neutral and acidic conditions, indicating that the system can be considered as a promising method to deal with effluents under various pH conditions. Radical scavenging experiments show that both iodine radicals (IO, IO₂ and IO₃) and hydroxyl radicals play an important role in CBZ degradation. Furthermore, the combination of UV/IO₃^- with TiO₂ was studied to explore the potential of the addition of IO₃^- to improve the efficiency of the conventional TiO₂ photocatalytic system. Scavenging experiments indicated that iodine radicals (IO, IO₂ and IO₃) were mainly involved in the degradation of CBZ in the UV/IO₃^-/TiO₂ system, and the reaction mechanism equations were proposed for the first time for the studied UV/IO₃^-/TiO₂ system. Several degradation products and four possible pathways of CBZ degradation were also elucidated using ultra-high-performance liquid chromatography in combination with a quadrupole time-of-flight mass spectrometer (Q-TOF MS). Respirometric tests indicated that the treatment has a positive impact on biomass behavior during subsequent biological purification, highlighting that the developed IO₃^--assisted AOPs are eco-friendly.

Taylor-Aris methodology for the experimental determination of molecular diffusion coefficients: Tutorial with focus on large biomolecules

High-Performance Liquid Chromatography (HPLC) is a key technique in the evaluation of biopharmaceuticals. To improve the separation of biopharmaceuticals, it is crucial to improve the fundamental understanding of the parameters governing their band broadening behavior. This can be obtained by a detailed assessment of the individual contributions to their mass transfer. For this purpose, a precise knowledge of the molecular diffusion coefficient (D_m) of biopharmaceuticals is required. Only little experimental data is available for the D_m-values of biopharmaceuticals under HPLC relevant conditions. Furthermore, none of the available equations that can be used to calculate D_m-values, allows to account for any conformational changes that might occur. The Taylor-Aris method is a very simple and absolute method that is often employed to determine D_m-coefficients. The Taylor-Aris method measures the band broadening of an analyte in an open tube under laminar conditions, wherein (1) longitudinal diffusion can be ignored, (2) the sample is fully radially equilibrated and (3) the contribution of the extra-column variance to the total variance is negligible. Moreover, since the open tubes are typically coiled for practical reasons, (4) the influence of secondary flows on the band broadening should be insignificant. In this tutorial paper, the impact of the four conditions mentioned above on the accuracy of the obtained D_m values is revisited. For this purpose, D_m values are measured for two representative compounds (Bovine Serum Albumin and Thiourea), and the obtained values are compared with literature data and theoretical recommendations. Based on these observations, a set of 'rules' for accurate and fast D_m measurements is put forward. Finally, an Interactive Tool (IT), combining these rules in a comprehensive way, is introduced and can be used to set up TA experiments.

Removal of sulfamethoxazole by ferrous iron activation of persulfate: Optimization of dosing strategy and degradation mechanism

In this paper, the degradation of sulfamethoxazole (SMX) was investigated using the ferrous iron (Fe²⁺) activation of persulfate (PS) (the Fe²⁺/PS process). The influence of the initial concentration of both PS and Fe²⁺ was investigated. It was found that increasing the PS concentration resulted in a higher SMX degradation efficiency. The influence of inhibiting reactions was found to increase with increasing Fe²⁺ concentration. In order to minimize these inhibiting reactions, different dosing strategies were applied. It was found that the SMX degradation efficiency could be enhanced significantly when changing from direct dosing (total amount of Fe²⁺ dosed at the start) to sequential dosing (dosing that same total amount but divided over specific time intervals) and even more when using continuous dosing (dosing the same total amount but continuously over 30 min reaction time). The contribution of different reactive species in this process was also investigated. It was found that hydroxyl radicals (•OH) were mainly responsible for the degradation of SMX during direct dosing, while using continuous dosing of Fe²⁺, the contribution of Fe(IV) and sulfate radicals (•SO₄^-) became more important (reduction of •OH contribution from 89 to 71%). Some degradation products formed during the SMX degradation process were identified and the difference in reaction mechanism between •OH on the one hand and Fe(IV) and •SO₄^- on the other hand was elucidated. At last, a comparison of different sulfate radical based advanced oxidation processes (SR-AOP) is performed by comparing the difference in SMX degradation efficiency, reactive species contribution and the formed degradation products. In most investigated processes, similar degradation products have been found, however, the large •OH contribution in the Fe²⁺/PS process resulted in distinct degradation products.

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data

Machine learning is a popular technique to predict the retention times of molecules based on descriptors. Descriptors and associated labels (e.g., retention times) of a set of molecules can be used to train a machine learning algorithm. However, descriptors are fixed molecular features which are not necessarily optimized for the given machine learning problem (e.g., to predict retention times). Recent advances in molecular machine learning make use of so-called graph convolutional networks (GCNs) to learn molecular representations from atoms and their bonds to adjacent atoms to optimize the molecular representation for the given problem. In this study, two GCNs were implemented to predict the retention times of molecules for three different chromatographic data sets and compared to seven benchmarks (including two state-of-the art machine learning models). Additionally, saliency maps were computed from trained GCNs to better interpret the importance of certain molecular sub-structures in the data sets. Based on the overall observations of this study, the GCNs performed better than all benchmarks, either significantly outperforming them (5-25% lower mean absolute error) or performing similar to them (<5% difference). Saliency maps revealed a significant difference in molecular sub-structures that are important for predictions of different chromatographic data sets (reversed-phase liquid chromatography vs hydrophilic interaction liquid chromatography).

Detailed numerical analysis of the effect of radial column heterogeneities on peak parking experiments with slowly diffusing analytes

The origin of the peak skewness that can be observed when applying the deconvolution method to isolate the diffusion process from the flow processes for peak parking experiments conducted under conditions of slow radial equilibration and strong trans-column velocity gradients was investigated. Numerical simulations were carried out for a variety of trans-column velocity profiles and a broad range of experimental conditions and system parameters were investigated. Results show that, under the aforementioned conditions, the traditionally employed variance subtraction method displays a consistent error which follows the dynamics of the diffusive relaxation during both the peak parking and the flow steps. It is also found that, under the same conditions, the peak deconvolution method is bound to produce deconvoluted "parking-only" peaks that are strongly asymmetric, despite the perfectly symmetric nature of the pure diffusion process marking this parking step. It is shown that this asymmetry is acquired during the flow step following the parking stop. During this step, parked and non-parked peaks are deformed in different ways, despite being subjected to the same trans-column velocity profile. This different deformation cannot be filtered away with the deconvolution or the variance subtraction method, hence introducing an error. Solutions to alleviate the peak skewness and the variance error consist of parking the peak close to the inlet or the outlet or exiting the parked peak through the column inlet (flow reversal method). Under the considered conditions, these approaches could reduce the error on the measured effective diffusion coefficient up to 87%. Carrying out the variance subtraction or the deconvolution process with a peak that has also been parked for a substantially long parking time instead of using a "no-parking" peak as is customary done, is another option to counter the effect.

A systematic investigation of the effect of sample solvent on peak shape in nano- and microflow hydrophilic interaction liquid chromatography columns

A frequently encountered problem in the practical application of nano- and microflow hydrophilic interaction chromatography (HILIC) columns is the distortion of peak shapes arising from a mismatch between the sample solvent and the mobile phase. An unmatched or improperly matched sample solvent can distort the peak shape of analytes and influence their retention times, thereby affecting the quality of the resulting chromatogram. In this work, the effect of sample solvent composition (mixtures of acetonitrile, water, methanol and isopropanol in different ratios) and injection volume (20-100 nL) was systematically investigated using a selection of neutral and charged compounds on a series of zwitterionic and charged small I.D. (0.1-0.3 mm) HILIC columns. For retained compounds, pure ACN was demonstrated to be the best sample solvent to obtain narrow peaks, while for compounds that eluted very close to the solvent peak, the peak shape was distorted when the sample solvent consisted of pure ACN. A highly aqueous sample solvent, which interferes with the partitioning of polar analytes into the stationary phase, was demonstrated to be detrimental for the peak shape of retained neutral compounds, while for unretained compounds that do not or hardly interact with the stationary phase, a high amount of water in the sample solvent was not problematic. For charged compounds, water in the sample solvent favored the electrostatic attraction with the stationary phase. Therefore, the retention time of charged analytes was shown to increase with increasing water content in the sample solvent. Even when a large amount of water was present in the sample solvent, the peak shapes of these compounds were still acceptable. For highly polar compounds with a limited solubility in aqueous sample solvents, it was found that a mixture of ACN and MeOH or IPA is a good alternative.

Efficiency and mechanism of 2,4-dichlorophenol degradation by the UV/IO4- process

This study explores the efficiency and kinetics of the photoactivated periodate process for the degradation of 2,4-dichlorophenol (2,4-DCP) in water. The obtained results show that the degradation rate was considerably higher for UV/IO₄^- compared to UV irradiation alone. Pseudo first-order reaction rate kinetics were obtained for all process conditions. The pH did not have a significant impact on the decomposition of 2,4-DCP using photoactivated periodate. Therefore, the applied method can be used to treat (waste)water at various pH. By raising the initial concentration of periodate to 5 mM, the degradation rate increased, while it decreased again at a concentration of 8 mM. As the 2,4-DCP concentration increased, the removal rate decreased. The extent of degradation was observed to be proportional with the UV intensity. A mechanistic study revealed that iodine radicals dominated the degradation of 2,4-DCP by photoactivated periodate, whereas OH and O(³P) only played a minor role. At pH 5.0, all chlorine atoms in 2,4-DCP were released as chloride ions in the UV/IO₄^- process, hence reaching a total dechlorination. Finally, the presence of inorganic salts, even at high levels, did not significantly impact the degradation. According to the results achieved in this study, the UV/IO₄^- system can be considered as a valuable alternative to treat effluents containing chlorinated organic compounds such as pulp and paper mill effluents and brine (waste)water.

Pilot-scale evaluation of ozone as a polishing step for the removal of nonylphenol from tank truck cleaning wastewater

The presence of nonylphenol (NP) in the wastewater of the tank truck cleaning industry is a major concern because of its endocrine disruptive properties. In this paper, the use of ozone for degrading NP from tank truck cleaning wastewater was investigated by operating a pilot-scale biological wastewater treatment in combination with an ozonation unit. The impact of the added ozonation step on the removal of NP, soluble chemical oxygen demand (sCOD) and total organic carbon (TOC) was monitored over one year. sCOD and TOC removal were not significantly enhanced, but the NP peak concentrations in the effluent were significantly lower than those obtained after biological treatment only: a relatively low NP concentration was observed, even when peak loads were present in the influent of the pilot-scale biological wastewater treatment plant (influent_bio). Contrariwise, the effluent of the sole biological treatment follows the peak load trends of the influent_bio. During the ozonation period, the average NP concentration in the combined biological-ozone unit was 0.29 μg/L, compared to 1.89 μg/L for the effluent obtained after a sole biological treatment, resulting in an improved average removal efficiency of 32%.

Spatiotemporal imaging and pharmacokinetics of fluorescent compounds in zebrafish eleuthero-embryos after different routes of administration

Zebrafish (Danio rerio) is increasingly used to assess the pharmacological activity and toxicity of compounds. The spatiotemporal distribution of seven fluorescent alkyne compounds was examined during 48 h after immersion (10 µM) or microinjection (2 mg/kg) in the pericardial cavity (PC), intraperitoneally (IP) and yolk sac (IY) of 3 dpf zebrafish eleuthero-embryos. By modelling the fluorescence of whole-body contours present in fluorescence images, the main pharmacokinetic (PK) parameter values of the compounds were determined. It was demonstrated that especially in case of short incubations (1-3 h) immersion can result in limited intrabody exposure to compounds. In this case, PC and IP microinjections represent excellent alternatives. Significantly, IY microinjections did not result in a suitable intrabody distribution of the compounds. Performing a QSPkR (quantitative structure-pharmacokinetic relationship) analysis, LogD was identified as the only molecular descriptor that explains the final uptake of the selected compounds. It was also shown that combined administration of compounds (immersion and microinjection) provides a more stable intrabody exposure, at least in case of a prolonged immersion and compounds with LogD value > 1. These results will help reduce the risk of false negative results and can offer an invaluable input for future translational research and safety assessment applications.

Degradation of ciprofloxacin using UV-based advanced removal processes: Comparison of persulfate-based advanced oxidation and sulfite-based advanced reduction processes

In this study, the degradation of ciprofloxacin (CIP) in wastewater was investigated using UV-based sulfate radical advanced oxidation processes (SR-AOP) and UV-based advanced reduction processes (ARP). More specifically, a comparison of the UV-based persulfate advanced oxidation process (the UV/PS process) and the UV-based sulfite advanced reduction process (the UV/sulfite process) was made. Considering the UV-based SR-AOPs, the UV/PS process was much more efficient than the UV-based peroxymonosulfate advanced oxidation process (the UV/PMS process), with pseudo first order reaction rate constants (k_obs) of 0.752 and 0.145 min^-1, respectively. For the UV-based ARPs, the UV/sulfite process was the most efficient, compared to the UV/sulfide and the UV/dithionite process (k_obs of 0.269, 0.0157 and 0.0329 min^-1, respectively). The optimal process parameters for both the UV/PS and the UV/sulfite process were determined and the contribution of the produced reactive species were identified. For the UV/PS process, maximal CIP degradation was found at pH 8, and both OH and SO₄^- were responsible for CIP degradation. For the UV/sulfite process, H and e_aq^- were responsible for CIP degradation, with e_aq^- being the predominant radical at pH 8.5. Although CIP degradation was much faster for the UV/PS process, the UV/sulfite process was determined to be much more efficient in the defluorination of CIP.

Deep convolutional autoencoder for the simultaneous removal of baseline noise and baseline drift in chromatograms

Enhancement of chromatograms, such as the reduction of baseline noise and baseline drift, is often essential to accurately detect and quantify analytes in a mixture. Current methods have been well studied and adopted for decades and have assisted researchers in obtaining reliable results. However, these methods rely on relatively simple statistics of the data (chromatograms) which in some cases result in significant information loss and inaccuracies. In this study, a deep one-dimensional convolutional autoencoder was developed that simultaneously removes baseline noise and baseline drift with minimal information loss, for a large number and great variety of chromatograms. To enable the autoencoder to denoise a chromatogram to be almost, or completely, noise-free, it was trained on data obtained from an implemented chromatogram simulator that generated 190.000 representative simulated chromatograms. The trained autoencoder was then tested and compared to some of the most widely used and well-established denoising methods on testing datasets of tens of thousands of simulated chromatograms; and then further tested and verified on real chromatograms. The results show that the developed autoencoder can successfully remove baseline noise and baseline drift simultaneously with minimal information loss; outperforming methods like Savitzky-Golay smoothing, Gaussian smoothing and wavelet smoothing for baseline noise reduction (root mean squared error of 1.094 mAU compared to 2.074 mAU, 2.394 mAU and 2.199 mAU) and Savitkzy-Golay smoothing combined with asymmetric least-squares or polynomial fitting for baseline noise and baseline drift reduction (root mean absolute error of 1.171 mAU compared to 3.397 mAU and 4.923 mAU). Evidence is presented that autoencoders can be utilized to enhance and correct chromatograms and consequently improve and alleviate downstream data analysis, with the drawback of needing a carefully implemented simulator, that generates realistic chromatograms, to train the autoencoder.

Deep Q-learning for the selection of optimal isocratic scouting runs in liquid chromatography

An important challenge in chromatography is the development of adequate separation methods. Accurate retention models can significantly simplify and expedite the development of adequate separation methods for complex mixtures. The purpose of this study was to introduce reinforcement learning to chromatographic method development, by training a double deep Q-learning algorithm to select optimal isocratic scouting runs to generate accurate retention models. These scouting runs were fit to the Neue-Kuss retention model, which was then used to predict retention factors both under isocratic and gradient conditions. The quality of these predictions was compared to experimental data points, by computing a mean relative percentage error (MRPE) between the predicted and actual retention factors. By providing the reinforcement learning algorithm with a reward whenever the scouting runs led to accurate retention models and a penalty when the analysis time of a selected scouting run was too high (> 1h); it was hypothesized that the reinforcement learning algorithm should by time learn to select good scouting runs for compounds displaying a variety of characteristics. The reinforcement learning algorithm developed in this work was first trained on simulated data, and then evaluated on experimental data for 57 small molecules - each run at 10 different fractions of organic modifier (0.05 to 0.90) and four different linear gradients. The results showed that the MRPE of these retention models (3.77% for isocratic runs and 1.93% for gradient runs), mostly obtained via 3 isocratic scouting runs for each compound, were comparable in performance to retention models obtained by fitting the Neue-Kuss model to all (10) available isocratic datapoints (3.26% for isocratic runs and 4.97% for gradient runs) and retention models obtained via a "chromatographer's selection" of three scouting runs (3.86% for isocratic runs and 6.66% for gradient runs). It was therefore concluded that the reinforcement learning algorithm learned to select optimal scouting runs for retention modeling, by selecting 3 (out of 10) isocratic scouting runs per compound, that were informative enough to successfully capture the retention behavior of each compound.

Local immune response to food antigens drives meal-induced abdominal pain

Up to 20% of people worldwide develop gastrointestinal symptoms following a meal¹, leading to decreased quality of life, substantial morbidity and high medical costs. Although the interest of both the scientific and lay communities in this issue has increased markedly in recent years, with the worldwide introduction of gluten-free and other diets, the underlying mechanisms of food-induced abdominal complaints remain largely unknown. Here we show that a bacterial infection and bacterial toxins can trigger an immune response that leads to the production of dietary-antigen-specific IgE antibodies in mice, which are limited to the intestine. Following subsequent oral ingestion of the respective dietary antigen, an IgE- and mast-cell-dependent mechanism induced increased visceral pain. This aberrant pain signalling resulted from histamine receptor H₁-mediated sensitization of visceral afferents. Moreover, injection of food antigens (gluten, wheat, soy and milk) into the rectosigmoid mucosa of patients with irritable bowel syndrome induced local oedema and mast cell activation. Our results identify and characterize a peripheral mechanism that underlies food-induced abdominal pain, thereby creating new possibilities for the treatment of irritable bowel syndrome and related abdominal pain disorders.

Measurement and modelling of the intra-particle diffusion and b-term in reversed-phase liquid chromatography

In an ongoing effort to better understand the underlying mechanisms of band broadening in particle-packed reversed-phase liquid chromatography columns, new models for intra-particle diffusion, representing an adsorption- and partition-type retention behavior, are proposed. These models assume the mesoporous zone inside the particles is subdivided in four distinct regions: a fraction f₁ filled with bulk mobile phase, a fraction f₂ enriched in pure organic modifier extending outside the stationary phase layer, a fraction f₃ comprising the liquid surrounding the alkyl chains and a fraction f₄ consisting of the stationary phase alkyl chains. Intra-particle diffusion is calculated as a residence time weighted average of the diffusion in these different regions. Experimental procedures and models are proposed to determine the volumes of these four regions and applied to three reversed-phase liquid chromatography columns with different pore sizes (80 Å versus 300 Å) and different stationary phase types (C₁₈ versus C₈). The newly proposed models are then applied to predict the intra-particle diffusion of butyrophenone across a wide range of retention factors (1 ≤ k" ≤ 40) in each of these columns. These predictions are compared to experimental data that are extracted from the effective diffusion coefficients of butyrophenone obtained via peak parking experiments. It is demonstrated that both adsorption- and partition-type models for intra-particle diffusion model the actual behavior of the test compound well, and require the determination of only one (partition) or two (adsorption) fitting factors: the obstruction to free movement the analytes experience from the alkyl chains in the retained state (partition and adsorption) and in the unretained state (adsorption). Finally, it is demonstrated that the major contributor to the intra-particle diffusion of retained compounds (k" > 2) is the diffusion these analytes undergo when retained in the organic-modifier enriched zone surrounding the alkyl chains (partition model) or when adsorbed onto the alkyl chains (adsorption model), confirming that surface diffusion plays an important role in the mass transfer of retained compounds in reversed-phase liquid chromatography columns.

Development of a HILIC-MS/MS method for the quantification of histamine and its main metabolites in human urine samples

An LC-MS/MS method was developed enabling the separation and quantification of histamine and its main metabolites (imidazole acetaldehyde, imidazole acetic acid, methyl imidazole acetic acid, methyl histamine, acetyl histamine) in urine samples. A fast separation was achieved in 10 min on two HILIC columns connected in series by adopting a linear gradient followed by an isocratic hold. The sample preparation consisted of a simple dilution step wherein 10 μL of urine was diluted with acetonitrile (ACN) to a final volume comprising 95% ACN. For methyl imidazole acetic acid, an additional dilution step was incorporated due to its high natural levels. Hereafter, the samples were stored at -20 °C and centrifuged prior to injection. Matrix matched calibrators were unavailable due to the endogenous occurrence of the compounds of interest. The occurrence of matrix effects and the lack of labeled internal standards prompted the use of the standard addition method as a viable alternative to solvent calibration. The validation of the method entailed matrix effects, accuracy and precision and was performed in compliance with the recent guidelines on endogenous compounds issued by the International Conference of Harmonization (ICH). The method was then adopted for the quantification of histamine and its metabolites in human urine samples collected from healthy volunteers and patients suffering from gastrointestinal discomfort.

Current developments in LC-MS for pharmaceutical analysis

Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades.

Efficiency and mechanism of diclofenac degradation by sulfite/UV advanced reduction processes (ARPs)

Diclofenac (DCF) is a non-steroidal anti-inflammatory drug which is frequently detected in the aqueous environment. The synergistic treatment using sulfite and UV irradiation is proposed to be one of the most effective advanced reduction processes (ARPs) to degrade refractory contaminants. This paper systematically investigated the performance and mechanism of DCF degradation by sulfite/UV ARP under various conditions. A significant enhancement in degradation efficiency of DCF was exhibited via sulfite/UV ARP compared with direct UV photolysis, which is primarily due to the generation of reductive radicals (e_aq^- and H). This process was well described by a pseudo first-order kinetic model with a rate constant of 0.154 min^-1. The influence of solution pH, sulfite dosage, initial DCF concentration and UV intensity were evaluated. Results revealed that DCF more favorably reacted with H in an acidic environment than with e_aq^- under alkaline conditions. A positive impact on the DCF decomposition was observed with increasing sulfite dosage, but with an inhibiting trend at high sulfite concentrations. The degradation rate constant was accelerated by increasing the UV intensity, while decreased by promoting the initial DCF concentration. Degradation mechanisms at different pH levels revealed that the reduction reactions were induced by e_aq^- at pH 9.2, and dominated by H at pH 6.0. Complete dechlorination was readily achieved with all chlorine atoms in DCF released as chloride ions under sulfite/UV ARP, which may lead to a decreased toxicity of the degradation products. This observation emphasized the advantages of sulfite/UV ARP on DCF degradation, in comparison with that under direct UV photolysis.

Safety Assessment of Compounds after In Vitro Metabolic Conversion Using Zebrafish Eleuthero Embryos

Zebrafish-based platforms have recently emerged as a useful tool for toxicity testing as they combine the advantages of in vitro and in vivo methodologies. Nevertheless, the capacity to metabolically convert xenobiotics by zebrafish eleuthero embryos is supposedly low. To circumvent this concern, a comprehensive methodology was developed wherein test compounds (i.e., parathion, malathion and chloramphenicol) were first exposed in vitro to rat liver microsomes (RLM) for 1 h at 37 °C. After adding methanol, the mixture was ultrasonicated, placed for 2 h at −20 °C, centrifuged and the supernatant evaporated. The pellet was resuspended in water for the quantification of the metabolic conversion and the detection of the presence of metabolites using ultra high performance liquid chromatography-Ultraviolet-Mass (UHPLC-UV-MS). Next, three days post fertilization (dpf) zebrafish eleuthero embryos were exposed to the metabolic mix diluted in Danieau’s medium for 48 h at 28 °C, followed by a stereomicroscopic examination of the adverse effects induced, if any. The novelty of our method relies in the possibility to quantify the rate of the in vitro metabolism of the parent compound and to co-incubate three dpf larvae and the diluted metabolic mix for 48 h without inducing major toxic effects. The results for parathion show an improved predictivity of the toxic potential of the compound.

Elongator subunit 3 (ELP3) modifies ALS through tRNA modification

Amyotrophic lateral sclerosis (ALS) is a fatal degenerative motor neuron disorder of which the progression is influenced by several disease-modifying factors. Here, we investigated ELP3, a subunit of the elongator complex that modifies tRNA wobble uridines, as one of such ALS disease modifiers. ELP3 attenuated the axonopathy of a mutant SOD1, as well as of a mutant C9orf72 ALS zebrafish model. Furthermore, the expression of ELP3 in the SOD1^G93A mouse extended the survival and attenuated the denervation in this model. Depletion of ELP3 in vitro reduced the modified tRNA wobble uridine mcm⁵s²U and increased abundance of insoluble mutant SOD1, which was reverted by exogenous ELP3 expression. Interestingly, the expression of ELP3 in the motor cortex of ALS patients was reduced and correlated with mcm⁵s²U levels. Our results demonstrate that ELP3 is a modifier of ALS and suggest a link between tRNA modification and neurodegeneration.

Effects of process variables and kinetics on the degradation of 2,4-dichlorophenol using advanced reduction processes (ARP)

This study aims at investigating the efficiency and kinetics of 2,4-DCP degradation via advanced reduction processes (ARP). Using UV light as activation method, the highest degradation efficiency of 2,4-DCP was obtained when using sulphite as a reducing agent. The highest degradation efficiency was observed under alkaline conditions (pH = 10.0), for high sulphite dosage and UV intensity, and low 2,4-DCP concentration. For all process conditions, first-order reaction rate kinetics were applicable. A quadratic polynomial equation fitted by a Box-Behnken Design was used as a statistical model and proved to be precise and reliable in describing the significance of the different process variables. The analysis of variance demonstrated that the experimental results were in good agreement with the predicted model (R² = 0.9343), and solution pH, sulphite dose and UV intensity were found to be key process variables in the sulphite/UV ARP. Consequently, the present study provides a promising approach for the efficient degradation of 2,4-DCP with fast degradation kinetics.

Development of a sensitive and quantitative capillary LC-UV method to study the uptake of pharmaceuticals in zebrafish brain

The present study explores the potential of 10-day-old zebrafish (Danio rerio) as a predictive blood-brain-barrier model using a set of 7 pharmaceutical agents. For this purpose, zebrafish were incubated with each of these 7 drugs separately via the route of immersion and the concentration reaching the brain was determined by applying a brain extraction procedure allowing isolation of the intact brain from the head of the zebrafish larvae. Sample analysis was performed utilizing capillary ultra-high performance liquid chromatography (cap-UHPLC) on a Pepmap RSLC C18 capillary column (150 mm × 300 μm, d_p = 2 μm) coupled to a variable wavelength UV detector. Gradient separation was performed in 28 min at a flow rate of 5 μL/min and the optimal injection volume was determined to be 1 μL. The brain extraction procedure was established for the zebrafish strain TG898 exhibiting red fluorescence of the brain, allowing control of the integrity of the extracted parts. Quantitative experiments carried out on pooled samples of six zebrafish (n = 6) demonstrated the selective semipermeable nature of the blood-brain barrier after incubating the zebrafish at the maximum tolerated concentration for the investigated pharmaceuticals. The obtained brain-to-trunk ratios ranged between 0.3 for the most excluded compound and 1.2 for the pharmaceutical agent being most accumulated in the brain of the fish. Graphical abstract Workflow of brain extraction to study the uptake of pharmaceuticals in the brain of zebrafish larvae.

Flexible nano- and microliter injections on a single liquid chromatography-mass spectrometry system: Minimizing sample preparation and maximizing linear dynamic range

Lack of knowledge on the expected concentration range or insufficient linear dynamic range of the analytical method applied are common challenges for the analytical scientist. Samples that are above the upper limit of quantification are typically diluted and reanalyzed. The analysis of undiluted highly concentrated samples can cause contamination of the system, while the dilution step is time consuming and as the case for any sample preparation step, also potentially leads to precipitation, adsorption or degradation of the analytes.

Development of a sensitive and quantitative UHPLC-MS/MS method to study the whole-body uptake of pharmaceuticals in zebrafish

An analytical procedure to measure the whole-body uptake of pharmaceuticals in zebrafish has been developed using state-of-the-art methodologies. A sample preparation procedure for 9 pharmaceuticals displaying a variety in physicochemical properties was developed using 10-day old zebrafish (TG898). For an efficient homogenization of the samples and subsequent recovery of the compounds of interest, different amounts of organic solvents in combination with acidic modifiers were added to zebrafish samples. Samples were subsequently processed using a powerful bath sonicator and centrifuged. Supernatant was then removed and evaporated in a vacuum oven before being reconstituted in a mobile phase-like solvent. Samples were analyzed using ultra-high performance liquid chromatography (UHPLC) on an Acquity BEH C₁₈ column (100 × 2.1mm, d_p=1.7µm) coupled to a Waters Xevo TQ-S mass spectrometer. For this purpose, a generic gradient was run, wherein the percentage of acetonitrile was varied from 3% to 82% in 10.5min at a flow rate of 0.41mL/min. Linearity of the method was demonstrated for all compounds (R² > 0.997) in a practically relevant concentration range. Matrix effects were between 81% and 106%, except for amitriptyline (51%). Using this method, it was demonstrated that a sample pretreatment using 1:2 (v/v) water:methanol in combination with 0.1% formic acid resulted in acceptable recoveries between 74% and 100% for all compounds. Together with the obtained lower limits of quantification of the analytical method (between 0.005 and 1.5ng/mL), this allowed the use of a single zebrafish to study the whole-body uptake of a particular drug, after incubating zebrafish at the maximum tolerated concentration for this drug.

Cell Imaging Counting as a Novel Ex Vivo Approach for Investigating Drug-Induced Hepatotoxicity in Zebrafish Larvae

Drug-induced liver injury (DILI) is the most common reason for failures during the drug development process and for safety-related withdrawal of drugs from the pharmaceutical market. Therefore, having tools and techniques that can detect hepatotoxic properties in drug candidates at an early discovery stage is highly desirable. In this study, cell imaging counting was used to measure in a fast, straightforward, and unbiased way the effect of paracetamol and tetracycline, (compounds known to cause hepatotoxicity in humans) on the amount of DsRed-labeled hepatocytes recovered by protease digestion from Tg(fabp10a:DsRed) transgenic zebrafish. The outcome was in general comparable with the results obtained using two reference methods, i.e., visual analysis of liver morphology by fluorescence microscopy and size analysis of fluorescent 2D liver images. In addition, our study shows that administering compounds into the yolk is relevant in the framework of hepatotoxicity testing. Taken together, cell imaging counting provides a novel and rapid tool for screening hepatotoxicants in early stages of drug development. This method is also suitable for testing of other organ-related toxicities subject to the organs and tissues expressing fluorescent proteins in transgenic zebrafish lines.

Atmospheric Pressure Ionization Using a High Voltage Target Compared to Electrospray Ionization

A new atmospheric pressure ionization (API) source, viz. UniSpray, was evaluated for mass spectrometry (MS) analysis of pharmaceutical compounds by head-to-head comparison with electrospray ionization (ESI) on the same high-resolution MS system. The atmospheric pressure ionization source is composed of a grounded nebulizer spraying onto a high voltage, cylindrical stainless steel target. Molecules are ionized in a similar fashion to electrospray ionization, predominantly producing protonated or deprotonated species. Adduct formation (e.g., proton and sodium adducts) and in-source fragmentation is shown to be almost identical between the two sources. The performance of the new API source was compared with electrospray by infusion of a mix of 22 pharmaceutical compounds with a wide variety of functional groups and physico-chemical properties (molecular weight, logP, and pKa) in more than 100 different conditions (mobile phase strength, solvents, pH, and flow rate). The new API source shows an intensity gain of a factor 2.2 compared with ESI considering all conditions on all compounds tested. Finally, some hypotheses on the ionization mechanism, similarities, and differences with ESI, are discussed. Graphical Abstract ᅟ.