Aptamers obtained through systematic evolution of ligands by exponential enrichment (SELEX) techniques are single stranded deoxyribonucleic acid (ssDNA) or RNA molecules capable of specifically recognizing target molecules. Such aptamers are easily chemically synthesized and modified, highly thermally stable, and are low toxicity and low immunogenicity. Aptamers that target small molecules have broad applications prospects for the development of new drugs, treating tumors, diagnosing diseases, monitoring environmental pollution, detecting drugs, and in ultrafast and sensitive detection applications. However, the simple structures and low molecular masses of small molecules, along with the limited number of binding groups available for interacting with nucleic acids lead to unstable aptamer-small molecule binding, which poses significant challenges for aptamer screening and sensor development. Efficient screening techniques are crucial for identifying aptamers with excellent performance characteristics. At present, the aptamer screening techniques suitable for small-molecule targets are mainly divided into three categories: target-immobilized-based screening technique, nucleic acid library-immobilized-based screening technique, and target-non-immobilized screening technique. Among them, target-non-immobilized screening technique require fewer screening rounds and result in aptamers with superior (typically nmol/L level) affinities. This paper summarized non-immobilized aptamer screening techniques for small-molecule targets, including principle, advantages, disadvantages and application progress associated with graphene oxide (GO)-SELEX, capillary electrophoresis (CE)-SELEX, and gold nanoparticle-assisted (GNP)-SELEX techniques. In addition, strategies for selecting control targets in aptamer-specific evaluation were summarized.

Organophosphate esters (OPEs) are widely used as flame retardants in most regions, they adversely affect ecosystems and threaten human health. OPEs have attracted significant public attention because they are toxic and ubiquitously present in the environment. While China is among the world’s largest users and producers of OPEs, limited data on the exposure of animal-derived foods to OPEs exist; consequently, a method for quantifying OPEs in animal-derived food samples is needed.

In this study, a method was developed for the determination of eight OPEs, including triethyl phosphate (TEP), tripropyl phosphate (TPrP), tri-n-butyl phosphate (TnBP), tris(2-chloroethyl) phosphate (TCEP), tris(2-chloroisopropyl) phosphate (TCIPP), tris(1,3-dichloro-2-propyl) phosphate (TDCIPP), triphenyl phosphate (TPHP), and 2,2-bis(chloromethyl) trimethylene bis[bis(2-chloroethyl) phosphate] (V6), from twelve types of typical animal-derived foods by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The samples were purified using an HMR-Lipid SPE column. The effects of mobile phase A (water, 5 mmoL/L ammonium acetate aqueous solution, and 0.1% formic acid aqueous solution) and mobile phase B (methanol and acetonitrile), as well as the methanol/acetonitrile ratio on the separation and extraction efficiencies for the eight OPEs were investigated using one-way analysis. The results showed that optimal response values and peak shapes were obtained for the various compounds using 0.1% formic acid aqueous solution-acetonitrile system as the mobile phase. The following pretreatment procedure was used: A 0.5 g sample was accurately weighed and ultrasonically extracted with 5 mL of acetonitrile. The supernatant was collected after freezing and centrifugation, and cleaned-up was performed using an HMR-Lipid SPE column. The target analytes were analyzed using a Waters Acquity BEH C₁₈ column (100 mm×2.1 mm, 1.7 μm) and ESI⁺ MS conditions. Compound V6 was quantified by the external standard method, with the other seven compounds quantified using the internal standard method. The method exhibited linearity with r²≥0.9900, limits of detection (LODs) of 0.01-0.87 μg/kg, and limits of quantification (LOQs) of 0.02-2.62 μg/kg for the various substances. Spiked recoveries of the eight OPEs at three levels (2, 20, and 100 μg/kg) were in the range of 80.5%-117.8% and RSDs ≤ 14.8% (n=6). Twelve animal-derived foods (grass carp, bass, Procambarus clarkii, milk, milk powder, yogurt, pork, beef, chicken, duck meet, egg, and duck egg) were analyzed using the developed method. Compounds TnBP and TCIPP were detected at rates of 100%, and TEP, TCEP, TPHP, and TDCIPP at rates greater than 50%, while TPrP and V6 were not detected. The method has a simple-to-operate pre-treatment step, analyzes rapidly with good recoveries and precisions, and is suitable for rapidly analyzing and detecting eight OPEs in a variety of animal-derived foods.

Oxidative stress biomarkers are measurable biological indicators that reflect the balance between the production of reactive oxygen species (ROS) and the body’s ability to neutralize them using antioxidants. Elevated oxidative stress is associated with a number of health effects. Herein, we report the development of a comprehensive and sensitive method for quantifying four typical oxidative stress biomarkers in human urine using solid-phase extraction (SPE) in conjunction with ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The quantified biomarkers include L,L-dityrosine (diY), 8-hydroxy-2'-deoxyguanosine (8-OHdG), 8-hydroxyguanosine (8-OHG), and 4-hydroxynonenal mercapturic acid (HNEMA), which are markers of oxidative-stress-related damage in proteins, DNA, RNA, and lipids, respectively. To that end, we systematically optimized the MS parameters, SPE cartridge, and elution conditions of the method. Briefly, 0.2 mL of a urine sample was mixed with 0.8 mL of pure water, after which an internal-standard mixture was added. The four target analytes were enriched and purified using an HLB SPE cartridge. The diY and the other three compounds were eluted with 2% (volume fraction) methanol aqueous solution and methanol, respectively. The two groups of eluates containing different target analytes were separately injected onto an Acquity UPLC HSS T3 column (100 mm×2.1 mm, 1.8 μm) and gradient eluted using 0.05% (v/v) acetic acid aqueous solution and methanol. The target analytes were identified using both negative and positive electrospray ionization (ESI^- and ESI⁺) and multiple reaction monitoring (MRM) modes, and quantified using stable-isotope-labeled internal standards. The four typical oxidative-stress biomarkers exhibited good linearities within the mass concentration range of 0.01-100 μg/L, with correlation coefficients ≥0.9998, and limits of detection (LODs) and limits of quantification (LOQs) of 7-18 and 22-60 ng/L, respectively. The spiked recoveries of the target analytes at three levels (5, 10 and 50 μg/L) were 103.0%-105.6%(8-OHdG), 100.8%-104.2%(8-OHG), 97.2%-100.2%(diY) and 96.9%-106.0%(HNEMA), with intra-day precisions of between 1.6% and 5.2%. Moderate-to-strong matrix effects of between 42% and 137% were observed for each target analyte. The target compounds exhibited weak matrix effects of 99%-102% (8-OHdG), 97%-98% (8-OHG), 97%-106% (diY), and 94%-110% (HNEMA) after adjustment using the stable-isotope-labeled internal-standard method. The developed method was used to determine the abovementioned four typical oxidative stress biomarkers in 40 urine samples. All target compounds were detected in human urine at rates of 100%, with mass concentrations of 0.52-14.40 μg/L, 2.75-38.15 μg/L, 8.92-82.28 μg/L, and 1.74-575.29 μg/L recorded for 8-OHdG, 8-OHG, diY, and HNEMA, respectively, along with median values of 2.89, 12.36, 37.66, and 96.92 μg/L, respectively. The developed method is simple to operate, highly sensitive, and is very precise and accurate; consequently, it is suitable for determining the abovementioned four typical oxidative stress biomarkers in human urine.

Ergot alkaloids (EAs) are mycotoxins produced by Claviceps and are present in cereals and their products; their residues pose significant threats to human health through food consumption, resulting in ergotism and sickness. Herein, a sensitive and rapid method for the determination of 11 EAs in cereals and their products using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) were developed. Eleven EAs were extracted with 20 mL acetonitrile-200 mg/L ammonium acetate solution (80∶20, v/v) for 15 min using the vortex shock method followed by 15 min of ultrasonication. The mixture was subsequently centrifuged at 10000 r/min for 10 min, and the supernatant was purified by a Captiva EMR-Lipid column. Target analytes were separated on an ACQUITY UPLC HSS T3 chromatography column (100 mm×3 mm, 1.8 μm) at a column temperature of 40 ℃ and a flow rate of 0.4 mL/min using an injection volume of 5 μL. Gradient elution was performed using 1 mmol/L ammonium acetate solution and acetonitrile as mobile phases. Data were collected in electrospray positive-ion (ESI⁺) and multi-reaction monitoring (MRM) modes, and quantified using matrix-matched standard curves. The 11 EAs exhibited good linearities in their linear ranges, with correlation coefficients (r²) of 0.9933-0.9999, with limits of detection (LODs) and limits of quantification (LOQs) of 0.002-0.2 and 0.006-0.6 μg/kg, respectively. Recoveries and relative standard deviations (RSDs) of the 11 EAs in matrix samples of wheat flour, coix seed, wheat flour products, and corn flour at low, medium, and high spiked levels were 80.1%-118% and 0.2%-13.3%, respectively. The established method was used to determine EAs in 240 wheat flour, 80 corn flour, 30 rice, and 30 coix seed samples, as well as 146 wheat flour products, with the detection rates of the 11 EAs of 0.57%-20.3%. A maximum total content of EAs of 56.7 μg/kg was recorded for a single sample. The sample pretreatment process used in this method is simple and fast, and the detection method is highly sensitive, with accurate and reliable results obtained. This method is suitable for simultaneously determining various EAs in cereals and their products. The results of this study provide valuable information for future EA risk-assessment studies.

Two-dimensional metal-organic-framework (2D-MOF) materials have emerged as a new class of functional 2D material. Compared to bulk crystals, 2D-MOFs are easily derivatized, highly porous, and have sufficient active sites. While 2D-MOFs are of considerable research interest, they are also efficient candidates for multiple applications in a variety of fields owing to their numerous advantages. The ability to separate and analyze chiral compounds is greatly significant for progressing human society, and chromatographic separation is widely used in this regard owing to its high resolution and sensitivity. Few reports on the use of 2D-MOFs in chromatographic-separation applications currently exist, and those use gas chromatography to analyze and separate enantiomers are even rarer. Unsurprisingly, the development of novel stationary phases has become a popular topic in the chiral-chromatography field. In this study, 2D-MOF nanosheets (Co-BDC-NH₂) were synthesized using a surfactant-assisted solvothermal method. The nanosheets were subsequently characterized by scanning electron microscopy and X-ray diffractometry. MOFs can be post-synthetically modified without affecting their frameworks, and such modifications can lead to the construction of chiral MOFs. Accordingly, Co-BDC-NH₂ was post-synthetically modified with glycyl-L-aspartic acid and glycyl-L-glutamic acid as chiral ligands to afford two chiral 2D-MOF nanosheets, namely Co-BDC-NH₂-glycyl-L-aspartic acid and Co-BDC-NH₂-glycyl-L-glutamic acid. These chiral 2D-MOF nanosheets were characterized by Fourier-transform infrared spectroscopy, circular dichroism, and thermogravimetric analysis. The two 2D-MOF nanosheet materials were used as chiral stationary phases in gas chromatography by coating them onto prepared capillary columns using a dynamic coating method; this process leaves a homogeneous coating layer on the inner wall of the column. Scanning electron microscopy confirmed that the two chiral columns had been successfully prepared. The columns were finally tested through gas-chromatography-separation experiments. Theoretical plates can be used to evaluate column efficiency. The Co-BDC-NH₂-glycyl-L-aspartic acid and Co-BDC-NH₂-glycyl-L-glutamic acid columns were determined to have 3538 and 3108 N/m theoretical plates, respectively, which implies that these columns are highly efficient. The McReynolds constant can be used to determine the polarity of the stationary phase in a chromatographic column; the two capillary columns exhibited McReynolds constants of 181 and 208, consistent with materials of medium polarity. The two chromatographic columns exhibited good abilities to resolve positional isomers and racemates (especially amino-acid derivatives), with seven racemates identified using the Co-BDC-NH₂-glycyl-L-aspartic acid column, and eight identified using the Co-BDC-NH₂-glycyl-L-glutamic acid column. In addition, the former column also separated mixed n-alkanes, mixed n-alcohols, and Grob mixtures. In this study, we augmented 2D-MOF nanosheets with chiral functional groups and confirmed that they are effective stationary phases for use in gas-chromatography applications. The study also expands the applicability of 2D-MOF nanosheets to chiral separation.

Ocean acts as a “sink” for pollutants in the natural environment. Consequently, issues focused on marine pollution from terrestrial origin is attracting increasing attention. Persistent organic pollutants (POPs), including organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), short-chain chlorinated paraffins (SCCPs), and dechlorane plus isomers (DPs), are serious hazards for both the environment and humans. These POPs have been widely detected in the marine environment and are typically present at trace levels; however, separating and determining individual contaminants require large amounts of sampling and time. Establishing an accurate analytical method for determining typical POPs is critical for studying their environmental behavior and associated ecological risks to the marine environment.

In this study, we developed a method based on solid-phase extraction (SPE) combined with gas chromatography-electrostatic field orbitrap high resolution mass spectrometry (GC-Orbitrap-HRMS) for determining 34 chlorinated POPs in seawater, including 25 OCPs, six PCB congeners, SCCPs and two DPs. The chromatographic conditions and MS parameters were optimized, and the effects of the extraction solvent and purification method were systematically studied. Dichloromethane exhibited satisfactory extraction efficiencies during the liquid-liquid extraction (LLE) of seawater samples, with recoveries of 73.1%-120.5% for OCPs, 87.2%-101.7% for PCBs, 105.5% for SCCPs, and 74.9%-78.6% for DPs, respectively. Purification using a SPE column with 500 mg of Florisil was adopted, and 9∶1 (v/v) n-hexane/acetone was confirmed as the eluent with recoveries between 68.2% and 122.8% for all the 34 chlorinated POPs. A DB-5MS (15 m×0.25 mm×0.10 μm) capillary chromatographic column was used to separate the target compounds, with an electron ionization (EI) source used to detect OCPs and PCBs, whereas SCCPs and DPs were determined in negative chemical ionization (NCI) source. All target compounds were analyzed in full-scan mode. An internal standard quantification method was used for OCPs and SCCPs while isotope dilution quantification was used for PCBs and DPs. The severe interference observed during the detection of chlorinated POPs in the mixture of co-extracted substances was completely eliminated following the purification.

The 34 target chlorinated POPs exhibited good linearities in their corresponding ranges, with correlation coefficients (R²) exceeding 0.9. The method demonstrated low detection limits under the optimized conditions, with values of 0.009-0.061 ng/L for the 25 OCPs, 0.006-0.016 ng/L for the six PCBs, 2.78 ng/L for the SCCPs, and 0.021-0.023 ng/L for the two DPs, with lower limits of determination of 0.06-0.24, 0.02-0.06, 11.12, and 0.08-0.09 ng/L, respectively. Accuracy and precision were validated by the recoveries of samples spiked at low, medium, and high levels, which ranged between 70.6% and 128.9%. Relative standard deviations (n=6) were determined to be 0.2%-19.2%. These results highlight the suitability of the developed method for analyzing trace amounts of chlorinated POPs in seawater. The method is characterized by simple sample pretreatment, high sensitivity, fast analytical throughput, cost-effectiveness, and good stability for trace-level detection; hence, it is suitable for the rapid and accurate analysis of typical chlorinated POPs in seawater. This method is expected to play a significant role in marine environmental monitoring and the emergency surveillance of seawater pollution. The developed method was applied to seawater samples collected from Bohai, which revealed that the highest detection frequency (90%) was recorded for the SCCPs, while α-hexachlorocyclohexane (α-HCH) was only detected in 30% of the samples. All other OCPs were below the detection limit. PCB-52 was the only PCB congener detected in the seawater samples. The SCCPs were detected in much higher concentrations than the other POPs, with the highest value of 130.6 ng/L recorded. Consequently, particular attention must be paid to SCCPs.

Gas chromatography is an analytical technique that is widely used to separate and identify various compounds. The retention index (RI) plays a significant role in gas chromatography because it provides a standardized measure for characterizing the retention performance of compounds under specific conditions and is a powerful compound-identification tool, particularly when dealing with complex mixtures. Consequently, the ability to predict RI values is a meaningful objective, particularly for multipolar phases, owing to significant variations in RI across various polar stationary phases. To address this issue, we developed a model for predicting gas-chromatographic RIs on stationary phases of varying polarity by collecting 4183 pieces of retention-index data for 2499 compounds on eight types of stationary phase from the literature and databases. Stationary phases were further classified into five categories based on their the McReynolds constants, namely: strongly polar, polar, medium polar, weakly polar, and non-polar. This classification ensured that the model is capable of handling a wide range of polarities, thereby enhancing its versatility and applicability to various analytical scenarios. The predictive model was constructed by integrating two types of composite feature. The 1D and 2D molecular-structural features of the compounds were first determined; these features capture the chemical and physical properties of the compounds, including their relative molecular masses, functional groups, and topological indices. These descriptors provide a comprehensive understanding of the molecular characteristics that influence retention behavior. Stationary-phase polarity was then one-hot encoded, which converted categorical stationary-phase-polarity information into a format that can be effectively used by machine-learning algorithms. This encoding technique ensures that the model can distinguish among the effects of various polarities on the retention behavior of the compounds. Nine algorithms were used to construct predictive machine-learning models, including linear regression, decision tree, random forest, support vector machine (SVM), k-nearest-neighbor (KNN), gradient-boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting (LightGBM) algorithms. Voting regression was used to build an optimally performing ensemble learning model based on the XGBoost and LightGBM algorithms. This ensemble model, which combines the strengths of multiple individual models, exhibited exceptional performance, with a training set coefficient of determination (R²) of 0.99, a training set root mean square error (RMSE) of 101.85, a test set R² of 0.97, and a test set RMSE of 107.44. Williams plots were used to characterize the application domain of the model, with over 94% of the data lying within the domain, indicative of broad applicability and high predictive confidence. The successful development of this predictive retention-index model represents a significant advancement in the gas-chromatography field. The developed model offers several key benefits by integrating advanced machine learning techniques with comprehensive chemical- and physical-property data; it highly accurately predicts RI values across a wide range of polar stationary phases. The developed ensemble model exhibits superior robustness and predictive abilities compared to individual machine-learning models. The establishment of this model is of great scientific significance and practical value for improving the efficiency and accuracy of target and non-target gas-chromatographic analyses.

Nicotine, the principal alkaloid in tobacco, exhibits significant central nervous system activity and induces a wide array of physiological effects. In addition to its well-documented role in tobacco dependence, previous studies have suggested that nicotine also has diverse pharmacological properties. These include alleviating symptoms associated with Parkinson’s disease, potentially reducing the risk of Alzheimer’s disease, mitigating oxidative stress, as well as anti-inflammatory and anxiolytic effects. Neuroscientists frequently use an array of molecular biology techniques to elucidate the mechanisms responsible for the effects of nicotine on the central nervous system. However, disease onset is invariably accompanied by metabolic dysfunction, and organisms often exhibit complex and unpredictable responses to pharmacological stimuli. As a bioactive alkaloid with potent pharmacological properties, nicotine is able to cross the blood-brain barrier and induce brain-compound changes, which serves as the basis for its effects on the central nervous system. Consequently, examining the extensive impact of nicotine exposure on endogenous metabolites and metabolic pathways in the brain is an indispensable step toward providing a more robust foundation for understanding the complex physiological effects of nicotine.

In this study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) metabolomic-analysis method was established to systematically examine the effects of repeated nicotine exposure on endogenous metabolites in mouse brains. Two chromatographic systems fitted with Acquity UPLC BEH HILIC (150 mm×2.1 mm, 1.7 μm) and BEH C18 (150 mm×2.1 mm, 1.7 μm) columns were used to determine the nicotine present in samples. As a result, the established UHPLC-MS/MS method identified a total of 759 endogenous metabolites. Compared with the saline group, nicotine exposure resulted in 575 significantly different metabolites, with 434 metabolites down-regulated and 141 up-regulated. Further pathway-enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that nicotine exposure primarily affects essential-amino-acid, lipid, nucleotide, carbohydrate, cofactor, and vitamin metabolism, as well as other amino-acid metabolic pathways in the brain. Although non-targeted metabolomics can simultaneously detect and analyze all small-molecule metabolites in an unbiased manner, accurately capturing metabolite changes in specific brain regions is challenging when dealing with complex brain-tissue systems. Targeting the aggregation of material bases and the delivery of precision treatment to certain brain regions is expected to be significant for the targeted therapy of central nervous system diseases. Airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) was further used to directly visualize the nicotine-induced distributions and variations of differentially expressed metabolites in various brain regions, which revealed that nicotine exposure leads to the significant downregulation of choline, serine, aspartate, and malate levels throughout the brain. Specifically, taurine, acetylcholine, and adenosine levels were notably affected in the cortical, hippocampal, and striatal regions, respectively. Essential-amino-acid metabolism was most affected by nicotine, with lipid metabolism found to be the next-most affected pathway. These metabolic pathways predominantly affected the cortical region, whereas the striatum, hippocampus, thalamus, and cerebellum were affected to varying degrees. These findings provide novel experimental evidence that enhances our understanding of metabolic biomarkers associated with nicotine exposure.

The determination of free amino acids is important for quality evaluation and nutritional studies of strawberries. In this study, an ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method using hydrophilic interaction chromatographic column was established for the simultaneous determination of 18 free amino acids in strawberries, and the pretreatment, chromatography, and mass spectrometry conditions were optimized. Specific pretreatment processes include grinding, extraction with water, centrifugation, and membrane filtration. The treated samples were then analyzed by hydrophilic interaction liquid chromatography (HILIC)-tandem mass spectrometry. The separation was performed on an ACQUITY UPLC Glycan BEH Amide column (150 mm×2.1 mm, 1.7 μm), with a water-acetonitrile system containing 5 mmol/L ammonium formate and 0.1% (v/v) formic acid as the mobile phase for gradient elution. A triple quadrupole mass spectrometer was used in positive-ion electrospray ionization (ESI) scanning mode, with target amino acids quantified using the matrix-matched standard-curve method. Eighteen free amino acids were determined with good linearities in the range of 0.5-40.0 μmol/L, along with r² greater than 0.992. The intra-day and inter-day precisions of the method were 1.0%-14.8% and 3.6%-17.6%, respectively. The limits of detection (LODs) were in the range of 50-250 nmol/L. The recoveries of the 18 amino acids were 75.0%-114.6% with relative standard deviations (RSDs) of 0.3%-13.5%. The contents of free amino acids in strawberries at different ripening stages were statistically analyzed, and a total of seven differentiated free amino acids (phenylalanine, isoleucine, glutamine, 4-aminobutyric acid, arginine, glutamic acid, and aspartic acid) were statistically screened. The method is rapid, accurate, reproducible and stable, and can quantitatively determine the content of amino acids in strawberries.

A gas-liquid separator (GLS) for the removal of carbon dioxide in the eluent of an ion chromatography (IC) system was developed. Firstly, the microporous hollow fiber polypropylene tube (PP-T) was inserted into the polytetrafluoroethylene tube (PTFE-T) with suitable inner diameter to form a double casing structure and wound into a spiral shape. Each terminal of the PP-T is 3 cm longer than that of the PTFE-T. Then the terminals of PP-T and PTFE-T were fixed respectively on two horizontal joints equipped with tee joints, and the regenerated liquid pipeline was fixed on a vertical arm interface equipped with tee joints. When the carbonate eluent flows into PP-T from the upstream suppressor, the inhibited carbonate solution will decompose and produce CO₂, which then escapes through PP-T and enters the flowing absorption solution located in the annular space between PP-T and PTFE-T, so as to achieve continuous and effective CO₂ removal. The production conditions and operating conditions of GLS were optimized, including the length of PP-T, the inner diameter of PTFE-T, the operating temperature, the type, concentration and flow rate of the absorption solution. The experimental results show that when 40 mmol/L potassium hydroxide solution is used as absorption solution, the removal efficiency of CO₂ can reach more than 98% at the flow rate of 1 mL/min. Higher operating temperature is helpful to improve the removal efficiency of CO₂ and reduce the baseline noise. The optimized operating temperature in this study was 40 ℃. When applying this GLS to the IC system for carbonate eluent, using a mixed eluent of 1.8 mmol/L potassium carbonate-3.2 mmol/L potassium bicarbonate (1∶1, v/v), the background conductance signal decreased from 41.6 mV without GLS to 5.5 mV after using GLS. Using a mixed standard solution of common anions (F^-、Cl^-、 ${{\mathrm{NO}}_2}^{-}$、Br^-、 ${{\mathrm{NO}}_3}^{-}$、 ${{\mathrm{SO}}_4}^{2-}$) at 150 μmol/L as the reference sample, the signal-to-noise ratio (SNR) after applying the GLS has been significantly improved by a factor of 6.01 to 11.8 times. In addition, the GLS can also be used to remove CO₂ from large volume samples in hydroxide eluent system, reducing the interference of ${{\mathrm{CO}}_3}^{2-}$ on the separation of other anions.

Atrazine is a triazine pesticide that interferes with normal physiological activities, induces oxidative stress, and is significantly toxic to plants. Therefore, the ability to quantitatively detect atrazine and study the mechanisms responsible for its toxicity are crucial for ensuring food safety and maintaining plant growth. Herein, a method was developed by QuEChERS combined with fluorescence derivatization to rapidly, sensitively, and quantitatively detect atrazine in real samples. This approach offers excellent selectivity and high sensitivity, and is simple to operate. In addition, we also investigated the effect of atrazine on catalase activity through enzyme-activity assays and molecular-docking studies to explore the mechanism responsible for the toxicity of atrazine on the molecular level. This experiment involves knowledge related to sample pretreatment, spectroscopy, and molecular docking, while the instruments used are widely available in colleges and universities and are very suitable for teaching open experiments. This experiment aims to provide students with a comprehensive understanding of experimental operations integrated with theory, as well as applied research aimed at helping students understand the use of separation materials, the selection and application of fluorescent derivatization reagents, the principles of analytical instruments, the use of enzymes, and the principles of molecular docking. This experiment is expected to enhance students’ awareness of people’s livelihoods, analytical chemistry concepts, and operational standards, which will guide the development of their scientific research thinking and improve their abilities to solve real-world problems.