Analytical Methods最新文献

Alkaline phosphatase (ALP) is an indispensable hydrolase in living organisms and the abnormality of ALP activity is correlated with a variety of diseases. Exploring ALP activity is important for clinical diagnosis and biomedical research to understand its physiological function. In this study, a dual-mode biosensing platform was constructed based on Cu-based metal-organic frameworks (Cu-MOFs) for electron spin resonance (ESR) and ultraviolet-visible (UV-vis) sensing of ALP. Cu-MOFs, as peroxidase mimics, catalyzed the decomposition of hydrogen peroxide (H₂O₂) and the generation of reactive oxygen species (ROS) which could oxidize ABTS into ABTS˙⁺ with good ESR and UV-vis signals. Pyrophosphate ions (PPi) with high affinity to Cu²⁺ in Cu-MOFs could suppress the peroxidase-like activity of Cu-MOFs, and ALP could hydrolyze PPi, resulting in the recovery of Cu-MOF catalytic activity. Thus, a quantitative dual-mode method for detection of ALP activity was established with good linearity in the range of 0-42 U L^-1 and limits of detection as low as 0.386 and 0.523 U L^-1 respectively for ESR and UV-vis detection. Benefiting from its high sensitivity and excellent selectivity, this method was applied for ALP detection in human serum and satisfactory recoveries were achieved. The off-on dual-mode sensing platform is more reliable than the single-mode sensor and shows merits like simple operation and cost-friendliness, making it have great potential in the diagnosis of ALP-related diseases.

The abuse of prohibited peptide-based drugs with a broad spectrum of chemical characteristics poses a significant concern for the horseracing industry. Recently, there has been a notable increase in positive cases of small-peptide drugs reported in equine and canine sports. In addition to small peptides, large peptides (over 2 kDa) with structural diversity have also entered the market in increasing numbers as drugs for humans and livestock. However, the simultaneous analysis of both small- and large-peptide-based drugs is still challenging. In this study, a screening method was developed to cover 74 analytes, including peptides, their catabolites, and/or their mimetics, with molecular weights ranging from 0.3 kDa to greater than 5 kDa. The simultaneous extraction of both small and large peptides was achieved using a weak cation-exchange solid-phase extraction cartridge with a mixture of different pore sizes (suitable for large peptides), followed by analysis using liquid chromatography high-field asymmetric ion mobility spectrometry tandem mass spectrometry (LC-FAIMS-MS/MS). For method validation, the limits of detection (LoDs), reproducibility, recovery, matrix effect, selectivity, and carryover were evaluated. Remarkably, the LoDs of ∼80% of the analytes were less than or equal to 50 pg ml^-1, with the lowest LoD (1 pg ml^-1) being observed for selected peptides in horse urine. These results indicate a substantial advancement in achieving comprehensive coverage for both small and large peptides with high sensitivity for the purpose of doping control in horseracing and equestrian sports.

Validation of the specificity of ICP-MS methods by ICH Q2 (R2) through spiking experiments cannot characterize the multi-atomic interference of complex high matrix samples, possibly affecting the accuracy of the method and reliability of results. In this study, we highlight this issue by investigating the elemental impurities in lanthanum carbonate raw materials and use isotope ratio analysis to overcome this limitation and establishing an accurate ICP-MS method for 24 elemental impurities (listed in ICH Q3D). An Agilent 7900 ICP-MS was used with an automatic sampler for sample determination in the He mode. The isotope ratio of elemental impurities in the spiked samples was analyzed to characterize polyatomic interference and select the exclusive mass number of elemental impurities. While the recovery rate of most elemental impurities met the requirements, that of selenium (default measurement mass number ⁷⁸Se) exceeded the standard in the matric sample. The isotope ratio of Se (⁷⁸Se/⁸²Se) was much higher than the theoretical value, indicating that the response intensity of m/z 78 was formed by the combination of ⁷⁸Se and other mass-to-charge ratios, such as LaOH²⁺ formed by the large amount of La in the matrix. Therefore, 82 was chosen as the mass number for Se. The validation results indicate that the method has strong specificity, high accuracy, and is simple and facile. This study provides technical support for the control of elemental impurities in lanthanum carbonates and isotope ratios can be used as a supplementary means of spiked recovery rates.

This study investigates the application of near-infrared spectroscopy (NIR) for assessing drought resistance in seeds, aiming to offer a rapid and efficient method suitable for large-scale primary screening. NIR spectroscopy is utilized to analyze four key factors (water, sugars, amino acids content, and genes) associated with maize seed drought responses. Signature NIR bands indicative of drought resistance-related molecules are identified using the Competitive Adaptive Reweighted Sampling (CARS) technique. Furthermore, an Improved Discrete Bayesian Optimization Support Vector Machine (ID-BOA-SVM) classification model is developed to address issues related to sparse features in traditional Bayesian Optimization Support Vector Machines (BOA-SVM). To enhance classification performance, a stacking model integrating Random Forest (RF), ID-BOA-SVM, Logistic Regression (LR), and Gradient Boosted Decision Trees (GBDT) classifiers is constructed, ensuring robustness and minimizing overfitting risks. The model achieves satisfactory recognition accuracy (94.28% accuracy, 94% precision, 94.61% recall, and 94.23% F1-score) even under conditions of substantial interference and dataset variability. This research demonstrates that NIR spectroscopy-derived data can support genetic and physiological studies of drought-resistant seed varieties, facilitating a deeper understanding of drought resistance mechanisms and optimizing breeding strategies.

Chemical imaging of pharmaceutical solid oral dosage forms is a key technique for quality assurance and issue diagnosis. This technique can be further augmented using 3D chemical imaging via serial sections and image stacking. However, the additional collection time this entails means that 3D imaging is utilised for a very niche set of applications. Previous attempts have been made to optimize the process but have often compromised the quality of the resulting chemical images to achieve the gains in process time. In this study, several optimisation strategies are employed to increase the efficiency of 3D chemical image collection without sacrificing the quality of the final chemical images. The use of automated microscope macros and a kinematic mounting system allowed for rapid sample processing and efficient utilisation of equipment time. The automated macros allow the Raman microscope to collect mapping data continuously from multiple samples without the need for operator intervention steps. The kinematic mounting system allows rapid and accurate sample transfer and positioning between instruments. These optimisations resulted in a three times speed increase in collection time while keeping the same signal-to-noise ratio of the resulting chemical images. These optimisations will allow the rapid collection of statistically robust 3D chemical image data within a set time frame that is more amenable to an industrial workflow.

Contamination of ground water with pollutants released from various anthropogenic activities is a major concern due to its adverse effects on the environment and human health. Rapid and efficient detection of such pollutants is the first step toward remediation of the problem. Herein we report a two-point fluorescence turn OFF-ON detection method for Hg²⁺ ions using nitrogen doped carbon dots (NCDs). The NCDs obtained through solvothermal treatment of ammonium citrate tribasic in DMF at 190 °C for four hours exhibited a quantum yield of 9.67%. Hg²⁺ detection is demonstrated in two steps, first the quenching of the fluorescence of NCDs by Hg²⁺ and second the fluorescence recovery upon addition of ascorbic acid from different sources. A rapid filter paper-based detection device is demonstrated based on the principles developed.

An electrochemical sensing approach was developed for the detection of the agricultural antibiotic drug kasugamycin. The method involves the construction of an electrochemical sensor comprising molecularly imprinted polymers (MIPs) embedded within a carbon paste (CP) matrix. The MIPs are designed to have imprinted sites that match the size and geometry of the Cu(II)-kasugamycin coordinated complex. Upon removal of kasugamycin, cavities suitable for the drug's entrance are formed within the MIPs. The presence of Cu(II) facilitates the detection of the drug by generating a redox signal of Cu(II)-Cu(I), which can be easily detected using differential pulse voltammetry (DPV). The signal response of Cu(II)-Cu(I) increases in the presence of the drug, promoting the accumulation of Cu(II) ions within the imprinted cavities. Under optimized conditions, the anodic peak (I_pa) signal of Cu(II)-Cu(I) exhibits an increase proportional to the concentration of kasugamycin within the range of 0.15-140 μM. The detection limit (LOD, S/N = 3) achieved is 0.046 μM. The proposed sensor demonstrates several characteristic features including good stability, reliable performance, a low detection limit, and excellent selectivity. The Cu(II)-MIP@CP sensor proved effective in detecting kasugamycin within complex samples like meat, milk, and cucumber, yielding recovery% ranging from 96.0 to 103.8%. Additionally, the relative standard deviation % (RSD%) fell within the range of 2.2% to 4.0%, indicating good precision and reliability.

A hybrid material, M@C-Br@GMA@Glu, consisting of a porphyrin-based metal-organic framework-covalent organic framework (MOF@COF), has been meticulously synthesized using a post-synthetic modification approach. This advanced material has demonstrated exceptional effectiveness in glycopeptide enrichment, characterized by an impressively low detection limit (0.2 fmol μL^-1), high selectivity (1 : 2000), and loading capacity for glycopeptides (100 mg g^-1). In practical applications with complex biological samples, 210 glycopeptides associated with 87 glycoproteins from the serum of the healthy group, and 156 glycopeptides related to 85 glycoproteins from the serum of cervical cancer were identified after enrichment with M@C-Br@GMA@Glu. Subsequent genetic ontology analysis has elucidated the relationship between cervical cancer and glycosylation, focusing on biological processes such as complement activation, innate immune response mechanisms, and the structural dynamics of the extracellular matrix. The collective findings not only validate the material's proficiency in the sensitive and selective enrichment of glycopeptides, but also underscore its potential in biomarker discovery applications.

Digoxin, a cardiac glycoside drug, is commonly used to treat heart failure and arrhythmias. The therapeutic concentration range of digoxin, with a narrow therapeutic index, is between 0.5 and 2.0 ng mL^-1. Hence, it is important for patients to monitor their blood levels after taking medication to achieve effective treatment and reduce the likelihood of experiencing drug side effects. Due to the complex steps and high cost of immunoassays, aptasensors that use aptamers to recognize the targets offer the advantages of low cost and good stability over other analysis methods. Nicking enzyme-assisted signal amplification is a novel isothermal signal amplification technology that relies on nicking enzymes to recognize and cleave restriction sites on one oligonucleotide strand. In this study, we develop a fluorescent aptasensor coupled with target-triggered aptamer hairpin switch and nicking enzyme-assisted signal amplification for digoxin detection in plasma for therapeutic drug monitoring. After optimizing the experimental parameters, we design hairpin probes with ten base pairs of the aptamer sequence and extended sequence complement to react with digoxin in a 10 mM Tris buffer containing 150 mM NaCl and 50 mM MgCl₂ (pH 7.4). The signal amplification reactions were performed for 3 hours. The fluorescent aptasensor exhibited high sensitivity with a detection limit of 88 pg mL^-1 for detecting digoxin in plasma and a linear range from 0.1 ng mL^-1 to 5 ng mL^-1. This technology was successfully used for digoxin detection to improve treatment effectiveness and minimize the risk of adverse side effects.

Colorectal cancer (CRC) is one of the deadliest malignancies globally, with high incidence and mortality rates. Early detection is crucial for improving treatment success rates and patient survival. However, due to the difficulty in detecting early symptoms, many cases are diagnosed at advanced stages, necessitating more sensitive and accurate detection methods. This study proposes a novel approach combining the Principal Component Analysis (PCA)-Dynamic Weighted Nearest Neighbor (DWNN) model with Surface-Enhanced Raman Scattering (SERS) technology to detect the serum of CRC mice at different stages. Establishing the CRC mice model, serum samples were collected for further analysis. An Au Nanocluster (AuNC) substrate was synthesized to ensure optimal SERS enhancement. The PCA-DWNN recognition model was constructed to classify the SERS spectra of CRC at different stages. The synthesized AuNC substrate has high sensitivity, good reproducibility, uniformity, and stability, making it a high-performance nanomaterial. The PCA-DWNN model has significant advantages in identifying high-dimensional and complex SERS spectra, offering excellent classification accuracy and robustness, with an accuracy rate of 97.5%. By analyzing the PCA loading plot, it was observed that as CRC progressed, the content and structure of proteins, lipids, amino acids, and carbohydrates in the serum changed, reflected in different characteristic peaks in the SERS spectra. This study suggests that SERS combined with PCA-DWNN has potential in the early detection of CRC, possibly providing a novel approach for clinical diagnostics.