Analytical and Bioanalytical Chemistry最新文献

Sensitive and accurate detection of the amyloid-β (Aβ) monomer is of fundamental significance for early diagnosis of Alzheimer's disease (AD). Herein, inspired by the specific Cu-Aβ monomer coordination, a cutting-edge colorimetric assay based on single-atom Cu anchored N-doped carbon nanospheres (Cu-NCNSs) was developed for Aβ monomer detection and an amyloidogenesis study. By directly pyrolyzing Cu²⁺-incorporated covalent organic frameworks (COFs), the resulting Cu-NCNSs with a high loading of Cu (8.04 wt %) exhibited outstanding peroxidase-like activity. The strong binding affinity of Aβ monomer to Cu-NCNSs effectively inhibited their catalytic activity, providing the basis for the colorimetric assay. The Cu-NCNSs-based sensor showed a detection limit of 1.182 nM for Aβ monomer, surpassing traditional techniques in terms of efficiency, accuracy and simplicity. Moreover, the system was successfully utilized for Aβ monomer detection in rat cerebrospinal fluid (CSF). Notably, the distinct inhibitory effects of monomeric and aggregated Aβ species on the catalytic activity of Cu-NCNSs were allowed for monitoring of the dynamic aggregation process of Aβ. Compared to thioflavin T (ThT), the most widely used amyloid dye, the detection system exhibited greater sensitivity towards toxic Aβ oligomers, which was crucial for early AD diagnosis and treatment. Our work not only sheds light on the rational design of highly active single-atom nanozymes from COFs but also expands the potential applications of nanozymes in early disease diagnosis.

Hydrogen peroxide (H₂O₂) is a critical signaling molecule with significant roles in various physiological processes in plants. Understanding its regulation through in situ monitoring could offer deeper insights into plant responses and stress mechanisms. In this study, we developed a microneedle electrochemical sensor to monitor H₂O₂ in situ, offering deeper insights into plant stress responses. The sensor features a platinum wire (100 µm diameter) modified with graphene oxide (GO) and gold nanoparticles (AuNPs) as the working electrode, an Ag/AgCl wire (100 µm diameter) as the reference electrode, and an untreated platinum wire (100 µm diameter) as the counter electrode. This innovative design enhances sensitivity and selectivity through the high catalytic activity of AuNPs, increased surface area from GO, and the superior conductivity of platinum. Operating at a low potential of -0.2 V to minimize interference, the sensor detects H₂O₂ concentrations from 10 to 1000 µM with high accuracy. In situ monitoring of H₂O₂ dynamics in tomato stems under the wounding stimulation reveals that H₂O₂ concentration increases as the sensor approaches the wound site, indicating localized production and transport of H₂O₂. This approach not only improves H₂O₂ monitoring in plant systems but also paves the way for exploring its generation, transport, and elimination mechanisms.

Methods that facilitate molecular identification and imaging are required to evaluate drug penetration into tissues. Time-of-flight secondary ion mass spectrometry (ToF-SIMS), which has high spatial resolution and allows 3D distribution imaging of organic materials, is suitable for this purpose. However, the complexity of ToF-SIMS data, which includes nonlinear factors, makes interpretation challenging. Therefore, in this study, ToF-SIMS data of a stratum corneum treated with diclofenac were analyzed using machine learning to enable the evaluation of drug distribution. Diclofenac-related mass peaks were identified using autoencoder results, and the degree of penetration was evaluated across 2-20^th stripped tapes. In addition, the permeation pathway was clarified by comparing the secondary ion images of phosphatidylethanolamine (PhEA; a marker of the inside of the cell); cholesterol, which is abundant in cell membranes; and diclofenac. Based on the biomolecule-related ion images showing the penetration pathway of diclofenac applied to the skin, diclofenac penetrates both the extracellular space and inside cells.

Metabolically active cells emit volatile organic compounds (VOCs) that can be used in real time to non-invasively monitor the health of cell cultures. We utilized these naturally occurring VOCs in an adapted culture method to detect differences in culturing Chinese hamster ovary (CHO) cells with and without Staphylococcus epidermidis and Aspergillus fumigatus contaminations. The VOC emissions from the cell cultures were extracted and measured from the culture flask headspace using polydimethylsiloxane (PDMS)-coated Twisters, which were subjected to thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) analysis. In our initial time points of 1 and 2 h, we detected VOC signatures that differentiated the cultures earlier than traditional plating techniques or visualization methods. Partial least squares-discriminant analysis (PLS-DA) models were built to differentiate the analytes from the CHO cells and S. epidermidis- and A. fumigatus-inoculated CHO cultures. A total of 41 compounds with a variable importance in projection (VIP) score greater than 1 was obtained across the models. Similarly, based on the PLS regression analyses to predict the cell concentration of S. epidermidis (R² = 0.891) and A. fumigatus (R² = 0.375), 15 and 20 relevant compounds were putatively identified, respectively; two known compounds overlapped between the two microbes. Some of the compounds were unidentified and future studies will determine the relationship between the VOCs and the metabolic changes in contaminated cultures.

Although fluorescence analysis methods are widely used in pesticide residue detection, improving their sensitivity and selectivity remains a challenge. This paper presents a novel ratio fluorescence sensor based on the molecular imprinting polymers (MIPs) and metal-enhanced fluorescence for visual detection of dicamba (DIC). Calcium fluoride (CaF₂) quantum dots (QDs) were immobilized on the surface of Ag@MIPs, resulting in a blue fluorescence response signal (Ag@MIPs-CaF₂). The MIPs shell, which possesses a specific recognition capability, serves as an isolation layer to adjust the distance between Ag nanoparticles and CaF₂ QDs for enhancing the fluorescence of CaF₂ QDs by up to 7.1 times under optimal conditions. In the presence of DIC, the blue fluorescence was selectively quenched, while the reference signal red fluorescence from cadmium telluride QDs coated with silicon dioxide (CdTe@SiO₂) remained relatively stable, resulting in a color change from blue to red. The sensor had a detection limit of 0.16 μM for DIC in the range of 1.0 to 50.0 μM, recovery rates of 85.4 to 103.5% for actual samples, and an imprinting factor of 3.28. The 3D finite-difference time-domain simulation revealed that the fluorescence enhancement was due to the local electric field amplification. Therefore, the developed sensing system in this work offers a broad application prospect for visual detection of DIC in food samples.

Matrix effects pose a significant challenge in food analysis for the quantitative analysis of complex food samples. Herein, a novel magnetic covalent organic framework nanocomposite and the copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) click reaction-based stable isotope labeling (SIL) method were presented for highly selective and sensitive detection of steroid hormones in food samples using HPLC-MS/MS. The nanocomposite, Fe₃O₄@TAPB-COF, with a core-shell structure exhibited high adsorption capacities for steroid hormones. Combined with a SIL method based on the CuAAC click reaction, steroid hormones were accurately quantified in food samples with high sensitivity and selectivity. A pair of SIL agents, N-(2-azidoethyl)aniline (d₀-NAEA) and d₅-N-(2-azidoethyl)aniline (d₅-NAEA), was synthesized to label steroid hormones in the samples and standard solutions, respectively. The labeling reaction is highly specific, and the formation of the derivatives is easily ionized by MS, thus overcoming matrix effects. More surprisingly, the ionization efficiency of steroid hormones increased by a factor of 4 to 56, with matrix effects ranging from 87.3 to 99.3%. Under optimal conditions, this method exhibited a low limit of detection (LOD) ranging from 0.1 to 2.6 μg L^-1 and overcame the interference of matrix effects for trace-level steroid hormone analysis in foodstuffs.

Paracetamol (PCM) is a commonly used analgesic and antipyretic agent for humans worldwide. However, PCM overdoses or overuse can cause health issues, such as hepatoxicity. As PCM is also used for the treatment of farm animals, it is essential to monitor these residues in animal-derived matrices at risk-based sites in order to minimize the intake of PCM through the food chain. In the present study, we have developed a novel carbon nanoparticle (CNP)-based indirect competitive lateral flow immunoassay (icLFIA) for the rapid detection of PCM in bovine urine. The developed icLFIA can detect PCM residues within 10 min, and its performance was validated according to Commission Implementing Regulation (EU) 2021/808, i.e., determination of the detection capability (CCβ), specificity, robustness, and stability. The CCβ of the icLFIA for PCM in bovine urine is 5 mg/L and the icLFIA is proven to be selective and specific towards PCM in bovine urine, as no matrix interference and cross-reactivity were observed, except for high concentrations of orthocetamol. The icLFIA for PCM in bovine urine is robust to (small) variations in reading time, but it remains necessary to strictly use a dilution ratio of running buffer/bovine urine of 80/20. Moreover, the produced icLFIAs are stable for at least 56 days under the stored conditions. In conclusion, the developed and validated icLFIA provides a rapid and cost-effective method for on-site monitoring of PCM abuse in cattle.

The abnormal expression of acetylcholinesterase (AChE) is linked to the development of various diseases. Accurate determination of AChE activity as well as screening AChE inhibitors (AChEIs) holds paramount importance for early diagnosis and treatment of AChE-related diseases. Herein, a fluorescent and colorimetric dual-channel probe based on gold nanoclusters (AuNCs) and manganese dioxide nanosheets (MnO₂ NSs) was developed. The fluorescence of AuNCs was suppressed in the presence of MnO₂ NSs, providing a platform for fluorescence-based detection. For colorimetric, the nanocomposites exhibited oxidase-like activity, rapidly catalyzing 3,3',5,5'-tetramethylbenzidine (TMB) to generate a blue color. Thiocholine (TCh), produced through the enzymatic reaction of acetylthiocholine (ATCh) in the presence of AChE, can reduce the MnO₂ NSs, thus recovering the suppressed fluorescence of AuNCs and decreasing oxidase-like activity. Based on this principle, a dual-mode assay for AChE detection was achieved. Compared to the commonly used single-signal detection, multi-mode detection can offer reliable and accurate results, due to its inherent self-validation and self-regulation capabilities. Under optimum conditions, the limit of detection (LOD) for AChE activity was 0.067 mU mL^-1 (fluorescent mode) and 0.042 mU mL^-1 (colorimetric mode). Moreover, the probe realized AChE detection in biological samples and AChEIs screening. This work showed the great prospects for early diagnosis of AChE-related diseases.

Ofloxacin is a commonly used quinolone antibiotic that is also used as a feed supplement in livestock production and in plant disease prevention and treatment. However, the excessive use and abuse of ofloxacin will accumulate along the food chain and endanger human health. Therefore, the development of a simple, rapid, and sensitive detection method for the determination of ofloxacin is critical. Herein, a detection method combining molecularly imprinted magnetic solid-phase extraction (MISPE) and surface-enhanced Raman spectroscopy (SERS) was developed for the detection of ofloxacin. Graphene oxide supported by magnetic beads was synthesized by a one-pot method, producing what was subsequently referred to as magnetic graphene oxide (MGO), and a molecularly imprinted membrane was synthesized on its surface by exploiting the ability of dopamine to self-polymerize under alkaline conditions. MGO@MIPs were obtained as the adsorbent for magnetic solid-phase extraction, which was used for the extraction and enrichment of ofloxacin in complex sample matrix, and then quantitative analysis was conducted by SERS. The developed method exhibited an excellent linear relationship with respect to ofloxacin concentration (10^-5 to 10² μg mL^-1), with a detection limit of 9.7 × 10^-6 μg mL^-1 in ultrapure water. Blank honey, milk, and pork samples spiked with ofloxacin at concentrations of 0.005, 0.1, 1, and 10 μg mL^-1 were extracted and determined using the developed method, with recoveries ranging from 93.1% to 105.6%. The results support the strong application prospects for the method, demonstrating simple and time-efficient operation and high accuracy.

This work provides a statistical analysis of four different approaches suggested in the literature for the estimation of an unknown concentration based on data collected using the standard addition method. These approaches are the conventional extrapolation approach, the interpolation approach, inverse regression, and the normalization approach. These methods are compared under the assumption that the measurement errors are normally distributed and homoscedastic. Comparison is done with respect to the two most important characteristics of every estimator, namely trueness (bias) and precision (variability). In addition, the authors supply, if not already available, mathematical formulas to approximate both quantities. Also, a real-world data set is used to illustrate the performance of all four methods. It turns out, that, given that all assumptions underlying the use of the standard addition method apply, the common extrapolation method is still the most recommendable method with respect to bias and variability. Nonetheless, if additional concerns come into play, other methods like, for example, the normalization approach in the case of increased problems with outliers might also be of interest for the practitioner.