Elsevier最新文献

A three-dimensional DNA walker offers an efficient strategy for sensitive detection of analytes with signal amplification. In this study, we report a target-silent, self-driven DNA walker for detecting small molecules (SMs). The DNA walker is composed of the Mg²⁺-dependent 8-17E DNAzyme walking strand conjugated with an SM (W-SM) and the three-dimensional walking track on gold nanoparticle (AuNP). The AuNP surface is functionalized with monoclonal antibody (mAb) and fluorescently labeled substrate of DNAzyme. Without target molecules, the W-SM is attached to the surface of AuNP via the antigen-antibody interaction. The DNAzyme catalytically cleaves the substrate, driving the W-SM autonomously moving along the walking track and generating high fluorescence. In the presence of SM target, the SM target competes with the W-SM in binding with the antibody on AuNP, and the DNA walker becomes inactive, causing fluorescence decline. This DNA walker enabled detection of digoxin and folic acid at concentrations as low as 0.2nM and 1 nM, respectively. It also performed well in diluted serum samples in responding to targets. This proposed strategy provides a new approach for constructing a DNA walker with a simple design for sensitive detection of small molecules in solution phase, showing promise in applications.

In this work, a potential-resolved electrochemiluminescence (ECL) multiplex immunoassay (MIA) was developed using Ag-doping methionine-stabilized Au nanoclusters (Met-AuAgNCs) with immobilized co-reactant as the anodic ECL tag and nanocomposite of gold nanoparticles/graphene oxide/N, N'-dicaproate sodium-3,4,9,10-perylene-dicarboximide (AuNPs/GO/PDI) as the cathodic ECL tag. Compared with methionine-stabilized Au nanoclusters (Met-AuNCs), the ECL of Met-AuAgNCs was enhanced 5.61-fold. When anodic co-reactant of N,N-diethylethylenediamine (DEDA) was connected to Met-AuAgNCs, the ECL of DEDA-Met-AuAgNCs was 11.3-fold of that of Met-AuAgNCs in DEDA solution due to the shorter charge transfer distance between Met-AuAgNCs and DEDA. After a pre-oxidation at 0.95 V for 60 s, the ECL of DEDA-Met-AuAgNCs was further enhanced by 10.6- and 27.9-fold in the cyclic voltammetric and potential step modes, respectively. The pre-oxidation ECL enhancement was demonstrated by an immobilized co-reactant promoters mechanism. In a potential-resolved ECL-MIA, carbohydrate antigen 125 and carbohydrate antigen 19-9 were adopted as model analytes, with the detection limits of 0.029 and 0.076 mU mL^-1, respectively. The work provides a proof of concept using self-ECL luminophores with immobilized co-reactant promoters in situ formed for potential-resolved ECL-MIAs with isolated anodic and cathodic co-reactants.

The study of drug metabolites is essential for evaluating safety and optimizing drug design. Recent classes of high-molecular-weight drugs, such as PROTACs and LYTACs, present challenges for traditional metabolite identification approaches due to their complex structures. To address these limitations, we developed Drug Metabolite Finder (DMetFinder), a novel mass spectrometry-based tool designed to enhance metabolite identification. DMetFinder employs cosine similarity algorithms to filter compounds with similar structures, minimizing the risk of overlooking metabolites with large fragment losses. It also efficiently detects multiply charged ions and incorporates isotope abundance and adduct ion scoring to refine identification accuracy. By calculating a total weighted score, DMetFinder reduces false positives associated with single-filter strategies. Experimental validation demonstrates that DMetFinder significantly improves the identification of metabolites from PROTACs, providing valuable insights for future drug development.

Diethylamine (DEA) is a known precursor to some of the most toxic chemical warfare agents (CWA) as both V-agents and Fourth Generation Agents (FGAs) contain the dialkylamine functionality. DEA is also a readily available commercial substance with extensive use in the chemical industry for legitimate purposes. Because of this potential dual use, it is desirable to develop methods to trace the origin of dialkylamines if they are used for illicit purposes. We herein demonstrate that it is possible to differentiate six commercial batches of DEA using position-specific isotope analysis (PSIA) by both ²H and ¹³C NMR. Using a high-field NMR spectrometer together with a cryogenic ²H probe, we have produced ²H-{¹H} NMR data with high accuracy and precision. The PSIA by NMR results show that the intramolecular ²H ratios of all six DEAs are significantly different while two of the six DEAs have unique ¹³C ratios. Further, the intramolecular isotopic variations can be used to link the DEAs to different suppliers. The two nuclei separately contribute to isotopic profiles of the DEAs. However, combining the two techniques provides a higher-resolved isotopic profile that can differentiate all DEAs and thus be useful in forensic investigations of illegal use of chemical weapons.

This study focuses on the development of an integrated analytical platform with in situ surface-enhanced Raman spectroscopy (SERS) monitoring capabilities, achieved through the design of a dual-functional, two-dimensional microporous covalent organic framework (COF). The hydrazone-functionalized COF not only exhibits selective recognition for Au(III)/Pt(IV) ions but also achieves efficient recovery of Au(III) from the leachate of waste electronic components, with a recovery efficiency of 95.73 %. By harnessing the enzyme-like catalytic activity of the COF@Au composite and the synergistic combination of COF's confinement effects with the localized surface plasmon resonance of Au nanoparticles, we created enhanced electromagnetic field regions on the material surface. This configuration enables real-time SERS tracking of reactant-product evolution during the reduction of 4-nitrothiophenol (4-NTP), with a reaction rate constant of 0.0181 s^-1. This integrated platform combines precious metal recovery reactions, catalytic processes and in-situ SERS monitoring (" recovery - catalysis - monitoring "), establishing a new paradigm of green and real-time tracking analysis.

Four-dimensional printing technologies are accelerating the development and fabrication of stimuli-responsive devices for analytical applications. Herein, we employed the multi-material fused deposition modeling printing technique, iron(II,III) oxide nanoparticle-incorporated polylactic acid filaments, and acrylonitrile butadiene styrene filaments to fabricate an all-in-one solid-phase extraction (SPE) device, which featured the flow manifolds connecting a monolithic packing and four temperature-controlled and magnetically actuated switching valves that were actuated by a hammer-shaped cantilever. When the inner chamber of the cantilever was filled with warm water (above the glass transition temperature of the polylactic acid), the applied external magnetic field induced the bending of the cantilever to switch the flow direction. When removing the external magnetic field, the cantilever returned to its original position, allowing recovery of the flow direction for magnetically actuated fluid control. The optimized SPE device manipulated the sample and eluent streams to pass through the monolithic packing and enabled an automated SPE scheme coupled with inductively coupled plasma mass spectrometry for determination of Mn, Co, Ni, Cu, Zn, Cd, and Pb ions, with the method's detection limits ranging from 0.3 to 2.8 ng L^-1. We validated the reliability and applicability of this analytical method through determining the metal ions in reference materials (CASS-4, SLRS-5, 1643f, and Seronorm™ Trace Elements Urine L-2) and real samples (seawater, river water, ground water, and human urine). Our results suggest that four-dimensional printing technologies can effectively fabricate thermo-magneto-responsive analytical devices and enhance the practical applicability of conventional SPE schemes for multiple trace metal analysis.

With the widespread use of pesticides and antibiotics in agriculture and healthcare, their associated environmental pollution and potential health hazards have emerged as a global concern. This study presents a novel deep learning-based spectral image analysis approach that is dedicated to the intelligent monitoring of multiple pesticides and antibiotics in agricultural water bodies. A total of 6100 samples containing glyphosate (GL), bentazone (BE), benzylpenicillin potassium (BP), and tetracycline hydrochloride (TH) at concentrations range of 3.8-550 μg/L were prepared. After the samples were mixed with selected composite chromogenic reagents, the specific absorbance characteristics of the stabilized reaction mixtures were measured using a custom-designed spectrometer. The preprocessed spectral data were used to train a fine-tuned ResNet-50 deep learning model. By establishing mappings between spectral features and reference concentrations, the model effectively predicted unknown pollutant concentrations. The results indicated that the proposed method enables rapid and simultaneous detection of GL, BE, BP and TH. Under laboratory conditions, the coefficient of determination exceeded 0.993, the reliable prediction rate was over 80 % in the concentration range of 10-550 μg/L. The limits of detection for GL, BE, BP, and TH were 0.23, 0.32, 0.38, and 0.28 μg/L, respectively. In addition, the frequency of abnormal predictions for natural water samples exhibited an increase over the concentration range of 3.8-10 μg/L, while the overall accuracy remained relatively high. Our research provides a new perspective on the rapid identification of pesticides and antibiotics. In the future, we hope this method can offer a timely, cost-effective and scalable solution for the early warning and real-time tracking of pollutants in water bodies.

Lead is a highly toxic element which poses a serious threat to human health when it dissolves in water. Laser induced breakdown spectroscopy is a simple and fast element detection method which can be used to detect liquid samples. In order to improve the limit of detection of Pb²⁺ in water, chelating agent assisted LIBS is investigated in this work. Sodium diethyldithiocarbamate (DDTC) is a commonly used Pb²⁺ chelating agent which can chelate Pb²⁺ bidentately. In experiments, sodium DDTC is used to chelate Pb²⁺ and deposits at the bottom of liquid sample by centrifugation. The precipitate is dried and concentrated on the graphite substrate. Under the optimal conditions, such as optimal concentration of sodium DDTC (0.25 mg/mL) and centrifugation time (5 min), the limits of detection of Pb²⁺ are 2.82 ng/mL for tap water and 3.64 ng/mL for river water are achieved. Without using sodium DDTC, the limits of detection of Pb²⁺ for tap water and river water are 18.20 ng/mL and 23.00 ng/mL respectively. Sodium DDTC can improve the limit of detection by more than 6 times. The work in this paper proposes a fast, simple and cost-effectively method to quantitatively measure heavy metallic elements in water samples.

A automated microextraction method based on temperature-responsive deep eutectic solvents (TRDESs) was developed for the determination of synthetic dyes in food samples. The system employs a homogeneous aqueous TRDES solution, composed of lidocaine and heptanoic acid (1:1 mol/mol), which acts both as extraction medium and as a thermally induced phase-separating agent. Upon heating above the lower critical solution temperature, spontaneous phase separation occurs, allowing direct collection of the enriched TRDES phase without centrifugation or manual handling. The entire process from sample introduction to extract collection is integrated into a programmable flow-based platform. The method was optimized and validated for four banned synthetic dyes: Rhodamine 6G, Sudan I, II, and III. Good linearity (0.025-100 mg L^-1), low limits of detection (0.001-0.008 mg L^-1), and high intra-/inter-day precision (RSDs: 2-7 %) were achieved. Real beverage samples were successfully analyzed, and spiked recoveries showed good agreement with a reference DLLME method (relative bias: 1-5 %). All steps were performed without the use of toxic organic solvents or centrifugation. Molecular dynamics simulations confirmed that π-π stacking and van der Waals interactions between rhodamine and lidocaine govern the extraction mechanism. Additionally, the green performance of the method was assessed using AGREEprep and ComplexGAPI, demonstrating high environmental sustainability. Overall, the proposed method offers a robust, automated, and environmentally friendly solution for trace-level screening of banned dyes in complex food matrices.