Analytical and Bioanalytical Chemistry最新文献

Thiamethoxam is one of the top three neonicotinoids found in the environment and in food. The widespread use of thiamethoxam in medicinal and edible herbs threatens their safe use. Therefore, it is particularly important to develop a rapid and simple approach to detect thiamethoxam residues in herbal medicines. In this study, colloidal carbon-based immunochromatographic strip (CNP-ICS) and colloidal gold-based immunochromatographic test strip (GNP-ICS) methods were respectively developed for the determination of thiamethoxam. The cutoff value of CNP-ICS was 0.1 ng mL^-1, which is six times more sensitive than that of the GNP-ICS method (0.6 ng mL^-1). The CNP-ICS method was applied to detect thiamethoxam in medicinal and edible Lonicerae Japonicae Flos (LJF) for the first time, with a limit of detection of 10 ng g^-1. The detection results of thiamethoxam in 26 batches of LJF samples by the CNP-ICS were consistent with those of the LC-MS/MS method. High residue levels (10.16-530.40 ng g^-1) and high detection rates (69.23%) of thiamethoxam in LJF were observed. The CNP-ICS prepared in this study has the merits of low cost, simple preparation, non-toxicity, and high sensitivity, which can be utilized for rapid field screening of thiamethoxam residues in complex matrices such as herbal medicines.

Compound-specific isotope analysis (CSIA) is a potent method for illustrating the in situ degradation of aquatic contaminants. However, its application to surface and groundwater is hindered by low contaminant concentrations, typically in the nanogram-per-litre range, requiring the processing of large water volumes. Polar organic chemical integrative samplers (POCIS) have shown promising results when combined with CSIA, yet their extended deployment time to accumulate sufficient analyte mass remains a major limitation. In our study, we addressed this issue by increasing the pore size of the polyethersulfone membrane (PES) from 0.1 to 8 $\mu$ m. This resulted in significant increases in the mass accumulation rates of atrazine (3.5-fold), S-metolachlor (3.4-fold), and boscalid (3.0-fold). Importantly, the larger pore sizes did not compromise isotopic integrity, with $\Delta {\delta }^{13}$ C $\le +0.4\pm 0.1$ ‰ and $\Delta {\delta }^{15}$ N $\le -0.6\pm 0.4$ ‰, both within accepted uncertainties. Additionally, we observed an enhanced selectivity of the larger pores towards the target analytes over humic acids, whereas no significant increase in (bio)fouling potential was detected for the 8 $\mu$ m membrane, as demonstrated by gravimetric analysis, SEM measurements, mass accumulation rates, and isotope ratios of fouled and unfouled POCIS. Our findings show that increasing the membrane pore size from 0.1 to 8 $\mu$ m reduces deployment time and expedites the accumulation of analyte mass required for gas chromatography isotope ratio mass spectrometry, offering a promising method to expand CSIA for low-concentration pesticide analysis in the field.

Given the inherent complexity of natural medicines, finding a straightforward and efficient method for identifying active ingredients remains a significant challenge, yet it is of paramount importance. Influenza virus neuraminidase (NA), a primary target for anti-influenza drug development, plays a crucial role in the infection process, making it essential to develop rapid and facile methods for screening NA inhibitors. Herein, we developed a novel and efficient analytical technique for the identification of NA inhibitors from complex herbal medicines by integrating dual sensing with affinity chromatography. This approach simplifies the experimental process and highlights the benefits of being quicker, more sensitive, and cost-effective. Regarding the biosensing section, the innovative concept of a 4-methylumbelliferyl-N-acetylneuraminic acid-NA-based fluorescence paper sensor strategy enables the rapid detection of NA inhibitors in complex herbal samples. In affinity chromatography, bioactive compounds were precisely captured, separated, and identified. The efficacy and reliability of the developed method were confirmed using both negative and positive controls. Then, the method was applied to screen for NA inhibitors in 20 different herbal medicines. The results revealed that Bupleurum chinense DC. exhibited the most pronounced inhibitory effect on NA. Subsequent analysis utilizing affinity chromatography identified three bioactive compounds, namely saikosaponin a, saikosaponin d, and baicalin, as the active agents responsible for this inhibitory effect, with IC₅₀ values of 177.3 μM, 262.9 μM, and 241.4 μM, respectively. Molecular docking studies further indicated that these three bioactive compounds exhibit a strong binding affinity with NA. This research provides novel insights into the screening of enzyme inhibitors within herbal medicines.

The global food industry faces significant challenges in ensuring the safety and authenticity of food products. Economic adulteration and counterfeiting of food are estimated to cost the industry US$30-40 billion annually. Analytical testing plays a vital role in detecting food fraud. For ensuring the metrological traceability and comparability of testing results, the use of reference materials (RMs) is crucial. The article describes the role of RMs in food authenticity testing, including their applications in method validation, calibration, quality control, and the definition of conventional measurement scales. It also reviews the availability of RMs that can be used in measurement procedures to authenticate food. Furthermore, the applications of RMs in targeted adulterant detection methods, for compositional parameters used to authenticate foods and food supplements, isotopic measurements, untargeted food authenticity testing methods, and detection and quantification of genetically modified organisms (GMOs), are explored. The document concludes by recommending the development of research grade test materials or representative test materials to harmonise untargeted testing methods and improve comparability of results across laboratories and over time.

Aminopolyphosphonates (APPs) are widely used as chelating agents, and their increasing release into the environment has raised concerns due to their transformation into aminomethylphosphonic acid (AMPA) and glyphosate, compounds of controversial environmental impact. This transformation highlights the urgent need for detailed studies under controlled conditions. Despite the availability of various methods for quantifying individual aminopolyphosphonates and aminomonophosphonates, a green, low-cost approach for the simultaneous quantification of APPs and their transformation products in laboratory experiments has been lacking. In this study, we present a novel analytical method utilizing ion chromatography (IC) coupled to integrated pulsed amperometric detection (IPAD) to simultaneously quantify the six aminophosphonates: AMPA, glyphosate, iminodi(methylene phosphonate) (IDMP), aminotrismethylene(phosphonates) (ATMP), ethylenediamine tetra(methylene phosphonate) (EDTMP), and diethylenetriamine penta(methylene phosphonate) (DTPMP). This method achieves separation within a 35-min run time and method detection limits (MDLs) ranging from 0.014 μM for AMPA to 0.14 μM for DTPMP. The method's applicability was successfully shown by monitoring DTPMP, IDMP, and AMPA during DTPMP transformation on manganese dioxide. A key advantage of this method is its environmental friendliness compared to existing aminophosphonate quantification techniques. Next to the simultaneous analysis, it avoids the use of derivatization agents and organic solvents and employs an energy-efficient detector. While the method's limitations lie in the detector's inherent non-specific nature, it offers a low-cost and sustainable alternative to existing methods.

Insulin bound with ligand molecules can improve its bioavailability in oral formulations. In this work, the interactions between insulin and bile acids of taurocholic acid (TCA) and glycocholic acid (GCA) are characterized using different mass spectrometry (MS) methods. Electrospray (ESI)-MS analysis revealed that GCA and TCA could interact with insulin individually or together through non-covalent bonds, and the products included mGCA-insulin, nTCA-insulin, and mGCA-nTCA-insulin complexes. Their binding stoichiometry, relative intensity ratio (IRa), and binding affinity were determined. ESI-MS/MS data and the calculated association constants both suggest that TCA has stronger affinity to insulin than GCA. The mixtures of various insulin, GCA, and TCA complexes with different charge states were separated, and distinct trend lines were observed using ion mobility mass spectrometry (IMMS). Moreover, liposomes containing insulin and GCA and/or TCA were prepared, and directly characterized using ESI-MS, and the interaction products of insulin with GCA and TCA were found in the liposome formulation. AutoDock was used to simulate molecular binding and select binding sites between insulin and GCA or TCA to explore the interaction mechanisms. The findings in this work could help understand the mechanism of action of insulin protection with bile acids in the body.

This study presents the development and validation of a precise analytical method for the speciation analysis of arsenic (As) compounds, including inorganic species [As(III) and As(V)] and organic species such as monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). The method employs anion-exchange high-performance liquid chromatography (AE HPLC) coupled with inductively coupled plasma-mass spectrometry (ICP-MS). To optimize the sample preparation process, microwave-assisted extraction (MAE) and heat-assisted extraction (HAE) techniques were evaluated and compared. Separation of all four arsenic species was achieved with baseline resolution within 10 min, utilizing an anion-exchange column and a mobile phase gradient of 0.5 and 5 mM ammonium carbonate with 3% (v/v) methanol at a pH of 9.3. The method validation followed the accuracy profile approach, employing six different food matrices analyzed in duplicate over six separate days within a 6-week period. The method demonstrated good intermediate reproducibility, with coefficients of variation (CV_R) ranging from 4.7% to 5.5%, while the bias was < 3%. The limit of quantification (LOQ) for the four species was 6.25 μg/kg (dry weight, dw), and the limit of detection (LOD) was 1.88 µg/kg (dw). These results confirm the robustness, accuracy, and suitability of the method for routine As speciation analysis across a variety of food matrices. The method is specifically intended to be applied to the analysis of a panel of food samples as part of the ongoing (French) third total diet study.

When performing effect studies to investigate the impact of microplastic (MP) on cell lines, algae, or daphnia, it is advantageous if such experiments can be performed without the use of surfactants. The need for surfactants arises from the fact that finely milled pristine MP particles generally are hydrophobic. Methods for the preparation of larger amounts of hydrophilic and hence artificially aged MP particles and approaches for their characterization are of high importance. Here we present methods to artificially age polyethylene terephthalate (PET) and low-density polyethylene (PE) using alkaline and acidic treatments that reproducibly result in large quantities of particles below 5 µm with considerably increased hydrophilicity. The artificially aged MP particles were characterized using particle counting by single-particle extinction and scattering (SPES), particle size by laser diffraction measurements, zeta potential using electrophoretic light scattering, hydrophobicity index (Hy) through dark-field (DF) microscopy, chemical composition by inductively coupled plasma-mass spectrometry (ICP-MS), Fourier transform infrared (FTIR) microscopy, and Raman microscopy. The hydrophobicity index values obtained should allow the aged MP particles to be characterized as qualitative reference materials (RMs) with an ordinal property. Evidence for the maintained integrity and hydrophilicity of the artificially aged MP particles (in powder form) over time was obtained by measurements of zeta potential with a 33-month interval. Uniformity of subsampling with respect to particle number concentration in suspensions within a 10-day period was also investigated. It provided evidence for the possibility of reproducible spiking of a specific number of hydrophilic MP particles with relative standard deviations (RSDs) from 6.2 to 13.6%. For the development of future reference materials of artificially aged microplastics, they should be characterized for an ordinal property (artificial age as Hy-index) and nominal property (identity of PET or PE based on spectral matching).

Quantitative measurement of metabolites is essential to understand biological and disease processes. Absolute quantification by spiking heavy isotope-labeled internal standards and analyzing on mass spectrometry (MS) platform is a key method to determine the concentration of metabolites in biological samples. However, MS-based absolute quantification is often challenged by the commercial availability and high costs of isotope-labeled internal standards. Here, we establish an absolute quantification method for amine metabolites utilizing isotopic N,N-dimethyl leucine (iDiLeu) tagging on the LC-MS/MS platform. Absolute quantification of metabolites with excellent accuracy and precision can be achieved with five-plex iDiLeu labeling without the need of isotope-labeled internal standards. We demonstrated that iDiLeu labeling improved the separation and detection limits of polar metabolites. Particularly, detection limits for glycine, GABA, and serotonin have been improved by more than 20 folds, and valine by more than 2000 folds. With iDiLeu tagging, 87 amine-containing metabolites were identified and quantified in human cerebrospinal fluid (CSF) samples, revealing potential metabolic changes in Alzheimer's disease patients.

Urinary exosome metabolite analysis has demonstrated notable advantages in uncovering disease status, yet its potential in decoding the intricacies of clear cell renal cell carcinoma (ccRCC) remains untapped. To address this, a core-shell magnetic titanium organic framework was designed to capture urinary exosomes and assist laser desorption/ionization mass spectrometry (LDI MS) to decipher the exosomal metabolic profile of ccRCC, with high sensitivity, throughput, and speed. A total of 492 urinary exosome metabolite fingerprints (UEMFs) from 176 samples were extracted for exploring the differences between ccRCC and healthy individuals. Leveraging machine learning algorithms, the exosomal metabolic profile was disclosed, achieving accurate differentiation and prediction of ccRCC patients versus healthy individuals, with an accuracy exceeding 97.3%. Furthermore, an optimized algorithm panel comprising five key features demonstrated consistent and high diagnosing accuracy rates of over 94.0% both in the training and blind test sets for ccRCC, underscoring the remarkable effectiveness and superiority of this strategy in ccRCC detection. This study not only refines the LDI MS method for metabolite analysis in urinary exosomes but also introduces a promising technical approach for unraveling the mysteries of ccRCC.