Talanta最新文献

Recently, organic electrochemical transistors (OECTs) have emerged as robust platforms for chemical and biological sensing, due to their intrinsic signal amplification, biocompatibility, and low-voltage functionality. OECTs have exhibited tremendous promise for detecting small molecule metabolites (SMMs), which are crucial as biomarkers in medical diagnosis, environmental surveillance, and food quality monitoring. This review provides an in-depth analysis of recent advancements in OECT-based sensing devices for the detection of SMMs. Besides, the fundamental design concepts of OECTs, device structures, choice of materials, and functionalization techniques are studied to enhance selectivity and sensitivity. The incorporation of recognition elements-such as enzymes, aptamers, and molecularly imprinted polymers-on the gate or channel to facilitate target-specific interactions has been studied. Furthermore, the significance of channel engineering, microfluidic integration, and nanomaterial inclusion in improving device performance has also been discussed. The review highlights the main obstacles that impede the extensive development of OECTs, including baseline drift, signal instability, and selectivity. Finally, future prospects are explored, emphasizing rising trends in smart materials, micro platforms, and wearable diagnosis. This study seeks to assist researchers in creating next-generation OECT sensors designed for real-time, selective, and sensitive identification of SMMs.

The development of simple and efficient analytical methods is fundamental for controlling the levels of toxic metals in liquid samples. In the present study, it is proposed the fabrication of a microstructured substrate based on filter paper, using in situ growth method of silver nanoparticles (AgNPs) into silver microparticles (AgMPs) to enhance the LIBS emission signal in the determination of Cu(II) in different liquid samples. Initially, ascorbic acid, NaBH₄ and SnCl₂ were evaluated as reducing agents for Ag particle formation. An 8-fold improvement in the copper signal was obtained when SnCl₂ was used. The Ag particles obtained with the latter reducing agent were further grown, and the signal was enhanced up to 14-fold compared to the traditional LIBS method using unmodified filter paper. UV-Vis diffuse reflectance spectroscopy, X-ray diffraction measurements, and scanning electron microscopy (SEM) indicated efficient immobilization of both Ag nano- and microparticles on the microfibers of substrate. A calibration analytical curve for Cu(II) ions was obtained with a coefficient of determination (R²) of 0.99, a linear response from 0.2 to 1.0 mg L^-1, and LOD and LOQ of 34 and 114 μg L^-1, respectively. The signal enhancement achieved with the microstructured substrate fabricated using the in situ growth method can be attributed to the synergistic effect of the nanostructures present in the cellulosic microfibers and the surface enhancement caused by the dense layer of Ag microparticles. The developed analytical strategy was successfully applied to the determination of Cu(II) ions in fortified samples of river water, artificial urine, tea infusion, and canned tea, providing recoveries ranging from 85 to 112 %. These results indicate the effectiveness of a microstructured silver substrate for sensitive detection of metal ions at low concentrations in liquid samples.

Characterization of the triacylglycerol (TAG) composition of food oils is challenging, in particular due to the presence of isomers. The main bottleneck is the incomplete separation of isomeric TAGs in liquid chromatography coupled to mass spectrometry (LC-MS), hindering identification because of mixed fragmentation spectra. In this study, the potential of adding cyclic ion mobility spectrometry (cIMS) as an additional dimension of separation in LC-MS analysis of food oils was explored to improve TAG isomer characterization. An analytical framework was created to achieve TAG isomer characterization by combining gas chromatography-MS (GC-MS), LC-MS, and cIMS-MS. TAG standards were used to evaluate the best option(s) for TAG isomer identification: fragmentation ratios, which can only be determined from pure fragmentation spectra obtained after separation of isomers in cIMS-MS; collisional cross section (^cIMSCCS_N2) values; or a combination thereof. Fragmentation ratios from pure fragmentation spectra yielded the strongest approach for isomer identification, as some TAG isomers were too close in ^cIMSCCS_N2 for confident identification. Finally, using this framework, we identified 21 TAG isomers in sunflower and olive oils, 11 of which would not have been identified without the use of cIMS-MS. Overall, this study demonstrates the potential of the extra separation dimension provided by cIMS and its complementarity with classical GC- and LC-MS analyses.

Microplastics and nanoplastics (MNPs) as emerging pollutants present substantial risks to both the environment and human health. Developing highly sensitive methods to rapidly identify and detect low concentrations of MNPs in complex systems remains a considerable challenge. Here, an "off-on" switch-type photoelectrochemical (PEC) aptasensor was employed for the sensitive detection of polyvinyl chloride (PVC) and polystyrene (PS) MNPs. This PEC aptasensor was based on a two-dimensional organic-inorganic Z-scheme heterojunction and utilized an acetylferrocene-modified aptamer (Apt-AcFc) as PEC recognition and quencher probes. In general, combining Apt-AcFc with the photoelectrode efficiently quenches the photocurrent, transitioning it to the 'off' state. Conversely, the presence of MNPs greatly increases the photocurrent because the MNPs were specifically recognized by Apt-AcFc, causing Apt-AcFc detaching from the photoelectrode and transition to the 'on' state. The developed PEC aptasensor was employed for the detection of MNPs released from food packaging materials. Although the aptasensor displayed distinct sensitivities toward PVC and PS, it demonstrated a consistent linear dynamic range of 1-200 μg mL^-1 and a low detection limit of 0.1 μg mL^-1. This switching-type PEC aptasensor provides a rapid, sensitive, and reliable analytical platform for the determination of MNPs in food and environmental matrices.

This study compares methodologies and provides insights on best approaches for quantifying EU-listed critical raw materials. Europe's strategy towards greater resilience involves valorization of secondary resources such as mine tailings or by-products of metallurgical production that are typically discarded as waste, despite containing valuable resources. Thus, identifying the best methods to determine elemental concentrations in various resources is crucial for evaluating their recovery, both environmentally and economically. Elemental content is usually determined using techniques such as inductively coupled plasma mass spectrometry (ICP-MS) by digesting solid samples into liquid solutions, although challenging for some refractory materials. Direct analysis of solids by laser ablation (LA)-ICP-MS is another alternative and can be used for both bulk analysis and spatially resolved mapping of critical elements throughout the supply value chain, from raw materials to refined products. Here, we compare ICP-MS/MS analysis on dissolved samples, obtained after microwave-assisted acid dissolution, with LA-ICP-MS analysis on solid samples for determining rare earth element (REE) compositions of manganese ores and slags. For LA-ICP-MS, we present two approaches, particularly useful in cases where dissolution proves challenging: (i) analysis of glass beads obtained through borate flux fusion of raw powders, and (ii) direct analysis on pelletized powders using a novel non-matrix matched calibration strategy. Each method's feasibility and strengths are considered for the specific chemical composition of the samples of interests. The study shows that different methods have advantages and disadvantages related to particle size distributions and preparation costs that need to be considered during characterization of secondary resources.

Lateral flow assay (LFA) is the most widely used point-of-care (PoC) diagnostic tools due to their simplicity, rapid turnaround, portability, and low cost. Despite their extensive adoption in clinical diagnostics, food safety, and environmental monitoring, conventional LFA remain limited by inadequate sensitivity, poor quantification, and restricted multiplexing capability particularly for early-stage disease detection. This review systematically examines recent engineering strategies developed to overcome these limitations and advance LFA toward next-generation diagnostic platforms. We highlight progress in biorecognition element engineering, including antibodies, nanobodies, and aptamers, alongside innovations in nanomaterial-enabled engineering through advanced nanoparticle labels, signal reporters, such as nanozymes, fluorescent probes to improve signal amplification systems. Emerging approaches for sample preconcentration, nucleic acid amplification, and multiplex assay architectures are critically discussed in the context of analytical sensitivity enhancement and improving specificity. Importantly, recent integration of artificial intelligence (AI) and smartphone-based readout systems has transformed LFA into digitally enabled diagnostics, allowing objective interpretation, wireless data transmission and semi-quantitative analysis while preserving portability and low manufacturing cost. Collectively, these advances position modern LFA as adaptable, cost-effective, and scalable diagnostic tools capable of bridging the gap between rapid field tests and centralized laboratory assays, with significant implications for decentralized healthcare, large-scale screening, and global disease surveillance.

This study presents a dual-signal biosensing platform for glucose detection based on alginate hydrogel beads (AlgelBeads). Its primary innovation lies in the integration of enzyme co-encapsulation with advanced image processing and pattern-matching algorithms. Glucose oxidase, horseradish peroxidase, and bovine serum albumin-templated gold nanoclusters are co-encapsulated within the AlgelBeads, which are uniform spheres approximately 2.1 mm in diameter, featuring a unique vein-like surface pattern that provides sites for glucose recognition and substrate catalysis. Upon exposure to glucose, an enzymatic cascade reaction is initiated, producing a visible color change to blue and simultaneous fluorescence quenching. For high-throughput analysis, a custom array plate was designed. The interpretation of the dual signals (colorimetric and fluorescent) is automated and enhanced using a Hough circle algorithm for AlgelBeads localization and a dictionary-based spatial classification algorithm for robust pattern recognition. Under optimized parameters, these AlgelBeads enable quantitative detection of glucose from 0.0625 to 4.0 mg/mL. The limits of detection are 0.077 mg/mL (colorimetric) and 0.030 mg/mL (fluorescent), with both precision and accuracy falling within acceptable limits. The AlgelBeads were applied for determining 54 serum samples collected from 18 pregnant women undergoing the oral glucose tolerance test, yielding results consistent with Beckman Coulter Glucose Assay Kit. These findings affirm the AlgelBeads offer an accurate and effective platform for glucose detection, holding potential for assisting in the diagnosis of gestational diabetes mellitus and other diabetes types in clinical settings.