Respiratory syncytial virus (RSV) imposes a substantial health burden, particularly among pediatric and elderly populations. The RSV fusion (F) protein, a critical mediator of viral entry and syncytium formation, represents a promising and rational target for antiviral drug development. Forsythia suspensa (Lianqiao in Chinese), a traditional Chinese medicinal herb, has been empirically employed for decades in the prevention of viral infections; however, its pharmacologically active constituents remain poorly characterized. The present investigation developed a high-expression F protein cell membrane chromatography system, and integrated with UHPLC-MS, to screen pharmacological substances from FS and verified the anti-viral potential against RSV in vivo. Our study pinpointed Forsythoside A, Forsythoside B, Phillygenin, and Phillyrin as potential anti-RSV compounds in FS. The research findings suggest that Forsythoside A, Forsythoside B, and Phillygenin exhibit considerable suppressive effects on cell fusion induced by RSV, concurrently effectively diminishing the expression level of the F protein gene. In contrast, the inhibitory impact of Phillyrin seems relatively less potent. In conclusion, our findings provide a convenient, fast, and accurate method to screen potential anti-RSV ingredients in natural herbal medicines. These results may facilitate the development of RSV treatment.
Fluorinated liquid crystal monomers, owing to persistent, bioaccumulative, and toxic properties, have been detected in environmental and biological samples, posing potential hazards to the environment and humans. However, current pretreatment methods predominantly rely on volatile organic solvents, necessitating cumbersome purification and prolonged nitrogen evaporation time. Moreover, the trace distribution characteristics of fluorinated liquid crystal monomers in the environment demand pretreatment methods that combine highly selective extraction capabilities with significant enrichment efficiency. Consequently, developing efficient extraction methods is crucial for enhancing the detection of fluorinated liquid crystal monomers in the environment. Temperature-responsive deep eutectic solvents represent a novel class of designable extraction solvents developed in recent years. Under temperature induction, temperature-responsive deep eutectic solvents reversibly switch between polar and non-polar states, achieving separation and enrichment effects. According to the biphenyl structure of fluorinated liquid crystal monomers, phenolic compounds were selected as precursors to prepare a series of temperature-responsive deep eutectic solvents for extracting 15 fluorinated liquid crystal monomers from water samples. During the transition from polar to hydrophobic non-polar states, temperature-responsive deep eutectic solvents extract fluorinated liquid crystal monomers from water via π-π interactions and intermolecular hydrogen bonding. Single-factor screening identified temperature-responsive deep eutectic solvents (M4-chlorophenol:M4-ethylphenol = 1:2) as the optimal extractant, with extraction conditions optimized using response surface methodology. Method's LOD and LOQ ranged from 0.08 to 0.30 µg/L and 0.26 to 0.98 µg/L, respectively. In analysis of surface water samples and wastewater treatment inlet/outlet samples, the spiked recovery rates of fluorinated liquid crystal monomers ranged from 70.5% ± 3.5% to 125.8% ± 1.6%, with detection concentrations spanning 0.44-2.67 µg/L. Compared to conventional methods, this approach achieves one-step extraction without requiring purification or additional dispersing solvents. It reduces extractant consumption and shortens extraction time while maintaining high extraction efficiency, offering a novel approach for detecting fluorinated liquid crystal monomers in environmental water.
1-(9H-Fluoren-9-ylidene)-2,3-dihydro-2-methyl-1H-benz[e]indene (short as FMB) as one of second-generation light-driven molecular motors contains a chiral carbon atom, and has attracted considerable attentions due to macroscopic chiral structures and light-driven behaviors through supramolecular assembly and cooperative effects. Herein, chiral analysis and semi-preparative separation of FMB enantiomers have been studied by high-performance liquid chromatography (HPLC) on polysaccharide-derived chiral stationary phases (CSPs). Effects of factors on chiral separation of FMB enantiomers, including type of CSP, composition and ratio of mobile phase, temperature, and flow rate, have been discussed in detail. Best separation of racemic FMB was achieved on cellulose tri(3,5-dimethylphenylcarbamate)-coated CSP with the resolution of 2.50 using the hexane-ethanol mixture (99:1, v/v). Then, each FMB enantiomer was obtained through semi-preparative separation with enantiomeric purity over 99%, and their absolute configurations as well as elution order were determined by electronic circular dichroism spectroscopy. Surprisingly, elution reversal phenomenon of FMB enantiomers was observed on cellulose- and amylose- tri(3,5-dimethylphenyl carbamate)-coated CSPs, in which (S)-FMB was eluted first on cellulose tri(3,5-dimethylphenylcarbamate)-coated CSP, and (R)-enantiomer was eluted first on the other. Moreover, molecular docking simulation has been employed to explain the recognition mechanism and elution reversal of FMB enantiomers on these two CSPs. The docking results revealed that π-π stacks, π-lone pair interactions, π- σ, and π-alkyl interactions between FMB and CSPs were the primary forces driving chiral separation, and the differences between them led to the enantiomer elution reversal on these two CSPs. Briefly, this work would provide valuable information for the separation and elution mechanisms of chiral molecular motors on polysaccharide-based CSPs.
In a context where environmental concerns and circular economy drive innovation, co-products from the flax industry emerge as valuable lignocellulosic feedstocks. Pyrolysis of these biomasses generates bio-oils with complex and highly oxygenated composition, which requires in-depth molecular characterization to optimize valorization processes. This study focuses on the molecular-level characterization of bio-oil derived from flax shives, a local co-product in Normandy. Size-exclusion chromatography (SEC) was used to fractionate the bio-oil into five distinct fractions based on apparent molecular size. The complete bio-oil and each SEC fraction were then analyzed by high-resolution mass spectrometry (Fourier-transform ion cyclotron resonance [FT-ICR MS] and Orbitrap MS) to identify and compare thousands of molecular formulae. A custom Python-based workflow was developed to align and annotate Orbitrap MS data using the FT-ICR MS dataset as a reference, allowing for rapid molecular formula assignment. Chemical class distribution, oxygen content, and Van Krevelen analysis revealed specific trends across fractions, indicating that SEC separation was influenced not only by molecular size but also by polarity and structural interactions. This approach offers a refined strategy for exploring the chemical complexity of lignocellulosic bio-oils and supports future efforts in their upgrading and application.
In this study, a novel effervescent-assisted magnetic micro solid-phase extraction (EA-MSPE) method was developed for the detection of four organochlorine pesticides (OCPs) in water samples. The adsorbent for this method consisted of magnetic biochar particles, which were created by loading Fe 3 O 4 onto pomelo peel biochar. It combined effervescent compression technology to complete the automatic extraction process and utilized an applied magnetic field to achieve solid-liquid separation, thereby establishing the EA-MSPE method. Several experimental parameters that affect the extraction efficiency, including biochar dosage, acid-base conditions, pH, eluting solvent, and salt content, were investigated. The results indicated that the optimal conditions were as follows: a biochar dosage of 0.06 g, a ratio of sodium dihydrogen phosphate to sodium bicarbonate of 1:3, a pH of 10, an elution solvent composed of ethyl acetate and n -hexane (2:1), and 10% NaCl. The recoveries of the four OCPs ranged from 63.56% to 87.52%. The limits of detection varied between 0.17 and 0.95 µg/L. The relative standard deviations ranged from 6.0% to 9.2%. This method was based on effervescent technology and magnetic particles to achieve an automatic extraction and separation process, saving time, energy, and being environmentally friendly. The produced magnetic effervescent tablet was easy to carry, more suitable for field sampling and extraction, and has strong practicability.
Continuous counter-current microfluidic liquid-liquid extraction performs separations by flowing immiscible liquids in opposing directions within a single flow channel. In principle, this flow arrangement enables a large number of theoretical separation units in a small footprint, without using interstage valving, pumping, and phase separation. Despite its potential for excellent separation performance, this microfluidic scheme rarely appears in literature due to the requirement for capillary forces to be greater than hydrodynamic forces for stable flow. We present a novel microfluidic device and flow approaches that overcome this force-balance challenge, enabling stable, long-duration continuous counter-current flow. Additionally, we cover a suite of methodologies for quantifying the performance of the microfluidic device, revealing the number of theoretical equilibrium stages achieved. The enabling technologies include a woven mesh screen-based microfluidic device architecture that is easily fabricated outside of a clean room, surface functionalization strategies to promote conjugate (organic/aqueous) wettability, flow approaches to eliminate bubbles and carryover, and computer-aided flow automation with optical measurement of extraction performance. The reported experiments lasted for over 36 h, terminated only at experiment conclusion, where the device still exhibited good performance. Automated Raman spectroscopy was used for solute quantitation of the ternary system tert-butanol in a toluene/water matrix, a ternary system that was specifically chosen to analyze the device's performance with a small solute partition ratio and to enable in-line Raman measurements of solute concentrations in both phases. The microfluidic device possessed a 55 mm contact length and a 38.5 µL internal volume. During counter-current flow, we observed approximately 37 equilibrium stages (37 ± 13) based on a best-fit of the solute fraction remaining in the aqueous phase using a Kremser Group Method analysis.
This study proposed a general strategy of "pre-column derivatization-chiral selector synergy" and achieved preparation-level separation in the gossypol derivative system for the first time. In this study, gossypol acetate was derived by chloramphenicol base (d-(-)-threo-1-(p-nitrophenyl)-2-amino-1,3-propanediol), and the derivatives were separated by high-speed countercurrent chromatography using HP-β-CD (Hydroxypropyl-β-cyclodextrin) as chiral selector. According to the test results, a two-phase solvent system with a volume ratio of 7:13:8:12 water: methanol: ethyl acetate: cyclohexane was selected. The factors influencing the separation process were investigated. The final conditions are 65% methanol content in aqueous phase, 60% ethyl acetate content in organic phase, HP-β-CD concentration was 0.05 mol/L, pH value was 2.37, and temperature was 20°C. The purity of the enantiomers of gossypol acetate is more than 95% (it was calculated by the area normalization method), and the recoveries of gossypol derivatives are between 80% and 90%.
High-performance affinity microcolumns with entrapped humic acid were utilized to investigate interactions between this natural carrier agent and several classes of antibiotics that are common emerging environmental contaminants, or micropollutants. Aldrich humic acid was used as a general model for this type of binding agent. Chromatographic studies under various temperature and mobile phase conditions were used to characterize interactions of the humic acid with the antibiotics sulfadiazine and sulfamethoxazole (sulfonamides), clarithromycin (a macrolide), and lincomycin (a lincosamide). It was determined by this approach that sulfadiazine and sulfamethoxazole had moderate affinities for the humic acid at pH 7.0 and 25°C, with distribution equilibrium constants (KD) of ∼2-3 × 101 L/kg and global affinities (nK'a) of ∼0.8-1.0 × 103 M-1. Lincomycin and clarithromycin had stronger binding, with KD and nK'a values of 3.8-7.5 × 102 L/kg and 1.3-2.6 × 104 M-1. All the antibiotics had a negative Δ G 0 $\Delta {{G}^0}$ for this binding, representing spontaneous reactions, and a negative change in enthalpy; however, the change in free energy due to entropy was positive in some cases but negative in others. The binding strength decreased in each case as the ionic strength increased. A change in pH also affected binding, as was consistent with the presence of significant electrostatic interactions from some of the antibiotics. These experiments demonstrated how affinity microcolumns could be employed to study such interactions quickly and with only small amounts of binding agent. The fundamental information obtained through this analytical technique should be valuable in characterizing the transport and activity of these antibiotics in the environment and in adapting this approach to the study of other binding agents and micropollutants that may be found in water.
Endogenous glycopeptides in human serum are valuable candidates for disease biomarker discovery, but their low abundance and structural complexity pose significant analytical challenges. In this study, we developed and optimized a robust workflow for enriching and in-depth characterizing the endogenous glycopeptidome using a novel hydrophilic interaction liquid chromatography (HILIC) sorbent. The HILIC-based strategy effectively enriched glycopeptides from mono-glycosylated IgG and avidin digests, as well as multi-glycosylated horseradish peroxidase (HRP), demonstrating high selectivity, femtomolar-level sensitivity (down to 1 fmol), reproducibility (RSD > 1), and reusability for up to four cycles. Comprehensive analysis by mass spectrometry (MS) identified 334 endogenous intact N-linked glycopeptides, including 318 N-glycosites from 289 glycoproteins. In addition, 242 endogenous intact O-linked glycopeptides from 38 glycoproteins are identified. These represent one of the most extensive endogenous glycopeptide datasets to date. N-glycans were primarily complex biantennary types, while Core 1 structures dominated O-glycans. Motif analysis revealed a strong preference for canonical N-glycosylation motifs (NXT/NXS) and a nearly equal distribution of O-glycosylation on serine and threonine residues. Gene Ontology analysis indicated functional enrichment in membrane-associated, catalytic, and immune-related processes. This optimized HILIC-MS platform enables sensitive and reproducible glycoproteomic profiling, providing a valuable tool for biomarker discovery.
Casein-based ingredients are widely used and labeled in cosmetic products, especially facial masks. However, a reliable determination method has not been established, and label authenticity cannot be readily verified. Therefore, in the present study, we selected four previously verified marker peptides corresponding to the four milk casein subtypes (αs1, αs2, β, and κ) and developed a quantitative UHPLC-ESI-QqQ-MS method for determining caseins in facial mask samples. Compared with organic-solvent precipitation and isoelectric precipitation, an optimized in-gel enzymatic digestion using 8% polyacrylamide, followed by three cycles of ultrasound-assisted extraction with 0.1% formic acid-acetonitrile, afforded the highest recovery. αs1-, αs2-, and κ-casein showed good linearity from 0.1 to 4 µmol/L, while β-casein was linear from 0.2 to 8 µmol/L (all R2 > 0.990). For β-casein, the detection limit and quantitation limit were 10 and 30 nmol/L, respectively. Matrix effects (ME) were calculated as (response in matrix/response in neat solution) - 1. The ME values were 0.5, 0.4, 0.3, and 0.4 for the selected peptides of αs1-, αs2-, β-, and κ-casein, respectively, indicating that the corresponding peak areas in the milk matrix were 50%, 40%, 30%, and 40% higher than those obtained in neat solution. Therefore, all four peptides exhibited moderate-to-strong signal enhancement rather than ion suppression. Method accuracy and precision were satisfactory, with recoveries of 87.0%-108.0% and relative standard deviations of 2.8%-8.2%. Applied to 20 batches of facial masks labeled as containing milk protein extract, casein was detected in 11 batches. In conclusion, the method is suitable for authenticity verification of casein in cosmetic products.
The objective was to achieve accurate origins discriminations of flos of Lonicerae japonicae, especially those from the genuine and non-genuine producing areas. An integration strategy was proposed based on machine learning, combining ultra-high performance liquid chromatography-time-of-flight mass spectrometry and gas chromatography-ion mobility chromatography data fusion for geographical origins discrimination of flos of Lonicerae japonicae. Sixty-one batches of flos of Lonicerae japonicae samples from different origins were determined by ultra-high performance liquid chromatography-time-of-flight mass spectrometry and gas chromatography-ion mobility chromatography. Multivariate statistical analysis, including principal component analysis and partial least-squares discriminant analysis were performed for the classification with an accuracy of 80.33% and 96.72%, respectively. Variable importance in projection (VIP>1) screened 9 nonvolatile differential constituents and 32 volatile differential constituents, respectively. The results of machine learning models combined with ultra-high performance liquid chromatography-time-of-flight mass spectrometry and gas chromatography-ion mobility chromatography data fusion indicated that the multilayer perceptron, logistic, gradient boosting decision tree, and Decision Tree (CART)) combined with a middle-level data fusion approach, achieve 100% classification accuracy with the training set. Among them, the multilayer perceptron algorithm achieved 100% accuracy for both the training and testing sets. These findings provide methodology support for tracing the origin of flos of Lonicerae japonicae.
Comprehensive two-dimensional gas chromatography (GC×GC) offers exceptional separation performance, but method development remains time-consuming and sensitive to numerous system parameters. In this study, we present a modular simulation framework for GC×GC systems with thermal modulation, implemented in the open-source Julia package GasChromatographySystems.jl. The simulation is based on a graph-based abstraction of the GC system and models solute migration through column and modulator modules using previously established retention models. A simplified but effective model for thermal modulation enables the generation of realistic two-dimensional retention times and peak widths. Simulation results were validated against experimental measurements from a GC×GC-ToF-MS system using different modulation periods and temperature programs. Systematic deviations between simulated and measured retention times could be explained and corrected by adjusting parameters such as the actual modulation period and modulator shift. The final model achieved root mean squared error ( rmse ${\mathrm{rmse}}$ ) of below 15 s (less than 1%) for first-dimension retention times and 55 ms (8%) for the second dimension. Peak width predictions were less accurate, with deviations of up to 3 s (40%) in the first dimension and up to 40 ms (60%) in the second. This modular and adaptable simulation framework provides a robust foundation for future applications in automated method development and system diagnostics in multidimensional gas chromatography.
A wet oxidation method was developed to remove the bonded phase from silica-based packing materials in spent chromatographic columns, thereby regenerating sub-3 µm monodisperse superficially porous particles (SPPs). The (2-hydroxyethyl)-β-cyclodextrin was grafted onto the surface of the regenerated particles, creating a chiral stationary phase (CSP). For comparison, CSPs were also prepared based on commercially available fully porous particles (3 µm, FPPs) and commercially available SPPs (2.7 µm). The chiral separation performance of these CSPs was evaluated using nine racemic compounds in reversed-phase liquid chromatography (RPLC) and supercritical fluid chromatography (SFC). The results showed that the regeneration method effectively removed the bonded phase from the spent column packing materials while maintaining the structural integrity of the SPP. Under the same chromatographic conditions, the SPP-CSP achieved a comparable enantioselectivity relative to the FPP-CSP while demonstrating superior column efficiency. The SPP-CSP displayed higher enantioselectivity when chromatographic conditions were altered to yield equivalent analysis times. SFC and RPLC demonstrated complementary chiral recognition ranges. SFC achieved higher enantioselectivity and better chromatographic performance within their jointly effective separation ranges. Compared to commercially available (2-hydroxypropyl)-β-cyclodextrin column of identical structure and specifications, the (2-hydroxyethyl)-β-cyclodextrin SPP-CSP exhibits different enantioselectivity. CSPs prepared from regenerated SPPs exhibit no significant differences in chiral separation performance compared to commercially available SPPs of the same brand, structure, and specifications. The (2-hydroxyethyl)-β-cyclodextrin SPP-CSP, synthesized via a straightforward and uncomplicated method, demonstrates favorable stability and chiral resolution capabilities.
A chromatography/mass spectrometry method is presented for the determination of the weight percent of aromatic compounds in a heavy marine fuel oil. This information facilitates the estimation of the stability, engine performance, and environmental as well as health-related consequences related to heavy fuel oils. These fuel oils are complex mixtures of many different compound types. Thus, a previously reported method was used to first separate the oil sample via distillation, precipitation, and fractionation into asphaltenes, heavy saturated hydrocarbons, alkylaromatic hydrocarbons, aromatic and heteroaromatic, as well as polar compounds. For the fractionation, both flash column chromatography and solid-phase extraction techniques were utilized to ensure proper separation of the compound classes in the maltenes fraction of the sample. High-temperature two-dimensional gas chromatography coupled with high-resolution electron ionization time-of-flight mass spectrometry was used to determine the overall compound compositions of the obtained fractions (other than the asphaltenes) and to classify the detected compounds. The results indicate that the saturated compound fraction contained only alkanes, while all the other fractions contained aromatic compounds. Combining the weight percent of these fractions was used to determine the weight percent of the aromatic compounds in the oil sample.
Nano liquid chromatography-mass spectrometry has come to be a key enabling technology in shotgun proteomics due to the combination of exceptional separation power, sensitivity, and comprehensiveness. However, the know-how of setting up proteomics methods to deliver robust, reliable, and meaningful results to large-scale life science experiments has remained somewhat ambiguous. This protocol outlines guidance for establishing nano-LC-MS/MS workflows focusing on comprehensive and untargeted deep proteome profiling, using state-of-the-art column technology and mass spectrometry. Employing a second-generation micropillar-array column, a trade-off is demonstrated between analysis time and chromatographic resolving power, which in turn impacts peptide and protein identification scores from a commercial HeLa reference standard. Furthermore, a straightforward workflow to develop a data-independent acquisition (DIA)-parallel accumulation-serial fragmentation (PASEF) analytical method is proposed, with a special focus on the optimization of the ESI source settings. Besides the method development, the study discusses the use of segmented gradients, and an MS-compatible surfactant in the sample diluent is also explored. Finally, the robustness of the developed method is demonstrated through consistently identifying 7558 protein groups (CV = 0.3%) as maintaining high repeatability peptide retention times (mean CV = 0.2%) and system pressure (CV = 0.4%) over 21 consecutive analyses.
This study introduces an innovative method for continuous multistage liquid-liquid extraction. Addressing challenges like coalescence and settling times that limit efficiency makes centrifugal partition extraction a promising technique for continuous product separation. It combines the benefits of a mixer-settler cascade with centrifugal extractors in one compact apparatus. The working principle is based on centrifugal partition chromatography, where two immiscible liquid phases are contacted inside a rotor, one serving as the mobile phase and the other as the stationary phase. In centrifugal partition extraction, both phases are mobile. The rotating apparatus allows dispersion and reduces settling time compared with static settlers, with its 300 times higher acceleration. To overcome constructional challenges, a novel concept, termed counter-current centrifugal extraction, is introduced in this work. Thereby, the primary objective is to validate the hypothesis that the process is feasible with a modified rotor design consisting of 10 chambers connected by individual ducts. Combined with alternating pump directions, this enables a pseudo-continuous counter-current flow. A proof of concept is investigated using computational fluid dynamics. The methodologies employed yield valuable insights into hydrodynamic performance. Based on these simulations, an optimized geometry for the flow area is developed, where 100% of the total chamber height is utilized as a dispersion zone compared with the previous 45%. The improvements result in elliptical chambers inclined at 35° to the radial direction, with a height of 6 mm and a volume of 1.43 mL. Additionally, baffles are placed inside the chambers opposite to the two inlets, enhancing dispersion of the inflowing phases. Finally, during alternating operation mode, it is demonstrated that ducts with a volume of 0.17 mL lead to an alternating phase ratio between 0.48 and 0.57 inside the chambers, which was repeatable over five simulated switches. This confirms the feasibility of the concept proposed based on hydrodynamics.
This study examined an improved and simplified method for solid-phase extraction that provides rapid and accurate determination and identification of 116 pharmaceutical and personal care products (PPCPs) in an aqueous environment using ultra-high performance liquid chromatography-tandem mass spectrometry. The common active compounds include 22 sulfonamides, 18 quinolones, 8 macrolides, 18 β-agonists, 6 sedative-hypnotics, 3 antipyretic-analgesics, 3 antihypertensives, 2 antidiabetic drugs, 3 antihistamines, 8 sex hormones, 2 antivirals, 6 nitroimidazoles, 8 glucocorticoids, and 3 amphenicols, lincomycin, pimaricin, levothyroxine sodium, bisphenol A, aldosterone, and melamine in water samples. Key parameters of tandem mass spectrometry, ultra-high performance liquid chromatography, and solid-phase extraction were optimized to enhance the analytical performance. The calibration curves were accomplished at seven concentration levels, and a satisfactory linear relationship (R > 0.99) was observed within the range of 5-800 ng/mL. Results showed varying limits of detection (0.0136-13.3 ng/L for different analytes based on signal-to-noise (S/N) = 3) and limits of quantitation (0.0452-44.4 ng/L). Recoveries of the spiked samples ranged from 53.1% to 116.5% with relative standard deviation lower than 9.9%. This approach effectively minimized matrix interference, improved extraction efficiency, and enhanced detection sensitivity, enabling more accurate PPCP residue analysis in water. The validated method was applied to raw water, treated water, and river water samples from Hangzhou, detecting 47 compounds at concentrations ranging from nondetected to 359 ng/L. Our findings provided critical technical support for the preliminary establishment of an environmental monitoring system targeting emerging pollutants. Notably, to the best of our knowledge, this study represented the first reported detection of melamine, loratadine, aldosterone, and levothyroxine sodium in aquatic environments. In particular, melamine was detected in aquatic environment for the first time, thus expanding the understanding of PPCPs' pollution status.
Erdong-Yangxin oral liquid (EYOL) is a traditional Chinese medicine (TCM) prescription that demonstrates clinical efficacy in treating depression, yet its comprehensive chemical profile and quality-control markers remain insufficiently studied. This study aimed to systematically characterize its chemical composition and establish a robust method for quality assessment. First, ultrahigh-performance liquid chromatography (UHPLC)-linear ion trap quadrupole-Orbitrap mass spectrometry enabled the tentative identification of 149 compounds, primarily iridoid glycosides, flavonoids, and saponins. Subsequently, network pharmacology analysis predicted several components, such as dioscin, calycosin, and ruscogenin, as potential bioactive candidates based on their target network associations. To quantitatively assess key constituents, a novel method based on UHPLC-tandem mass spectrometry was established and fully validated for 15 components selected by integrating network pharmacology predictions, phytochemical characteristics, and pharmacopoeia references. Quantitative results revealed catalpol as the predominant component, followed by rehmannioside D, lobetyolin, dioscin, and calycosin-7-O-β-d-glucoside. The study establishes a comprehensive chemical basis for EYOL and a reliable quantitative approach for its quality control, facilitating further research into its pharmacodynamic material basis.
Wastewater-based epidemiology (WBE) concerns the analysis of human biomarkers in untreated sewage samples as indicators of diseases, exposure to pollutants, and population lifestyle. Smoking, in various forms, and its prevalence in society are essential aspects of such studies. Anatabine, anabasine, cotinine, and hydroxycotinine are the most well-known nicotine biomarkers, and the relation of their concentrations with the smoking prevalence has been used in WBE studies. Analysis of these compounds has been based on LC-MS following classical solid or liquid extractions. Regarding the complexity of the sewage samples, the final chromatograms are still plagued by a large number of contaminants, despite the use of tandem or high-resolution MS detectors. In this work, a novel headspace SPME-Arrow extraction method has been developed, optimized, and validated for determining four nicotine metabolites in raw sewage medium. A Box-Behnken design was used to assess the significance of temperature, pH and ionic strength as three factors influencing the extraction efficiency and also to optimize the experimental conditions. The effect of extraction time and its optimum value were determined individually. The optimized sample preparation method followed by GC-MS (SIM) was shown to be sensitive enough to analyze the analytes at their actual concentration levels (ng-µg L-1), thanks to ng L-1 LOQs and linear calibration up to 40 µg L-1. A raw sewage sample was also used to evaluate the accuracy and validate the method, with relative recoveries ranging from 87% to 103% for the spiked real sample at 400 ng L-1. The entire analytical procedure and the sample preparation step were assessed for their greenness, based on AGREE and AGREEprep models, respectively. Results showed that not only can this method be considered an alternative to SPE-LC-MS methods, but it is also more environmentally friendly due to its automation and solventless nature.
The technical progress of metabolomics-the analysis of metabolite composition of cells, tissues, and biofluids-and its ability to unravel phenotypical responses of organisms to their environment was accompanied by the democratization of their use in a wide range of scientific fields. While the reliability of analytical procedures was thoroughly assessed, the effects of preanalytical processing on sample metabolic profiles (i.e., conditioning, storage, transportation, etc.) remain quite unclear. This uncertainty is especially notable for samples collected in the frame of ecological studies, which often involve field sampling and remote sample production, leading to extended transportation durations and suboptimal storage conditions. In this study, we evaluated the impact of storage duration and temperature, along with the effects of freeze-drying (or lyophilization; the process of stabilization through dehydration by sublimation), on the metabolic profiles of samples relevant to ecological studies. Specifically, we focused on the lesser mealworm (Alphitobius diaperinus), the fruit fly (Drosophila melanogaster), and the perennial ryegrass (Lolium perenne). The levels of 60 different metabolites were quantitatively analyzed using targeted metabolomics through gas chromatography-mass spectrometry (GC-MS). We report significant metabolic shifts associated with freeze-drying, resulting in both increases and decreases in the contents of more than half of the quantified metabolites across all assessed chemical families. Several amino acids exhibited more than a fourfold increase in all investigated matrices. Furthermore, while samples stored at -80°C exhibited profiles most similar to those of samples analyzed right after collection, the metabolic profiles of these samples gradually changed over the 6 months of storage. Interestingly, metabolic shifts related to sample preanalytical processing and storage were relatively consistent across the biological matrices studied, particularly between the two insect species. Based on these observations, we propose several recommendations for reliable preanalytical sample processing in ecological studies, considering logistical and economic constraints.
