Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy最新文献

A self-driven and self-catalytic (SDSC) tripedal DNA nanomachine was developed for microRNA-21 (miR-21) detection. The microRNA could open one arm of tripedal DNA nanomachine to form DNAzyme with a nearby arm through the proximity effect. After DNAzyme's cleavage, the exposed DNA arm region competed with the third arm and produced a DNA segment (sequence Q). The released sequence Q initiated the next SDSC cycle of tripedal DNA nanomachine. In the special DNA nanomachines design, the components with close spatial localization were constructed on a single nanostructure, which significantly increased local reactant concentrations and reaction rates. A dynamic correlation was obtained from 10 pM to 50 nM between fluorescence signal and miR-21 concentration. The effective concentration of reactant greatly increased, compared with the free diffusible reactants. Consequently, the incubation time was significantly shorted to 35 min. This strategy showed a promising potential in miRNA detection and disease diagnosis.

The signal intensity ratio (SIR) is a crucial factor in advancing probe technology due to its direct impact on sensitivity and precision, particularly in applications such as medical imaging, environmental monitoring, and food safety testing. However, the development of high-SIR probes is challenged by complexities in fabrication, cost, and mechanical stability. In this study, we address these limitations by investigating the role of halogen atom substitutions in modulating the intermolecular binding energy and aggregation behavior of Ce-Salen Schiff base complexes. We synthesized a novel Schiff base pH probe, Ce-3,5-Cl-Salpn (3,5-Cl-Salpn = N, N'-bis (3,5-dichlorosalicylidene)ethylene-1,3-diaminopropane), and introduced its analogues Ce-5-Cl-Salpn (5-Cl-Salpn = N, N'-bis (5-chlorosalicylidene)ethylene-1,3-diaminopropane) and Ce-Salpn (Salpn = N, N'-bis (salicylidene)ethylene-1,3-diaminopropane) for comparative analysis. Through fluorescence measurements, single-crystal analysis, and theoretical calculations, we demonstrate that halogen substitution leads to significant modulation of fluorescence intensity and SIR in the pH range of 6.0 to 7.0. Notably, Ce-3,5-Cl-Salpn exhibited the highest SIR, with a 182.5-fold increase, compared to the non-halogenated variant's 9.2-fold rise. Frontier molecular orbital (FMO) analysis revealed a reduction in the HOMO-LUMO energy gap as halogen substitution increased, resulting in enhanced optical properties and more efficient electronic transitions. Additionally, binding energy calculations confirmed that halogen atoms strengthen intermolecular interactions, thereby improving molecular stability and aggregation-caused quenching effects.

Rapid, sensitive, and accurate detection of heavy metal ions is significant for human health and ecological security. Herein, a novel single-stranded DNA with poly(thymidine) tail is tactfully designed as template to synthesize dual-emission silver nanoclusters (ssDNA-AgNCs). The obtained AgNCs simultaneously emit red and green fluorescence, and the red emission can be selectively quenched by Hg²⁺, meanwhile the green emission of AgNCs increases synchronously. Thus ssDNA-AgNCs as a single probe shows excellent ratiometric fluorescence sensing for Hg²⁺ with a detection limit of 0.2 nM, and Hg²⁺ as low as 10.0 nM can be fluorescently identified by naked eye within 5 min. Moreover, the proposed nanoprobe also exhibits a good ratiometric colorimetric sensing for Hg²⁺, and the obvious color change of nanoprobe also enables a rapid and visual monitoring of Hg²⁺ under visible light. The dual mode ratiometric response of Hg²⁺ can be ascribed to the rapid redox reaction between Hg²⁺ and Ag⁰ on the surface of AgNCs and the subsequent formation of silver amalgam. The resultant dual-mode ratiometric sensor has been successfully applied to the determination of Hg²⁺ in environmental water samples. This study provides a new strategy to synthesize dual-emission AgNCs by scientifically designing terminus sequence of ssDNA template, and develops a facile and efficient single-probe and dual-mode ratiometric sensor for visual monitoring of Hg²⁺.

For on-site analysis, the combination of surface enhanced Raman scattering (SERS) and colorimetry, as a dual-mode detection, can effectively improve the accuracy of detection, and reduce the influence of instrument fluctuation, which greatly improves the accuracy and reliability of the results. However, the preparation of SERS/colorimetry substrates are usually time-consuming and costly, which limits their practical applications. In this paper, a hydrophobic paper-based SERS/colorimetry substrate can be prepared by a simple spraying method. The hydrophobicity is introduced by the structures formed with polydimethylsiloxane and polymethylmethacrylate, which leads to high detection sensitivity due to its enrichment effect. Moreover, the electrostatic interaction between Ag nanoparticles and the analytes further enhances the performance of SERS and colorimetry in detection of thiram and aspartame. It also provides a new method for the detection of aspartame with colorimetry. Finally, the detection limits of SERS and colorimetry for thiram and aspartame are 0.1 mg/L and 0.1 g/L, 1 mg/L and 0.1 g/L, respectively. The paper-based SERS/colorimetry substrate makes the results more reliable through dual-mode detection, which shows great potential in the detection of real samples.

In recent years, it has become a development trend to design multi-application luminescent materials with rare earth ion doping. In this work, a series of Eu³⁺/Sm³⁺ doped self-activated Na₂YMg₂V₃O₁₂ (NYMVO) phosphors were synthesized through a simple high-temperature solid-state reaction method. Interestingly, due to the energy transfer (ET) from the matrix to the activators, the luminescence color of the phosphors changed from turquoise to orange-red and yellow-green under near-ultraviolet (n-UV) 365 nm excitation. Based on the fluorescence intensity ratio of the matrix to Eu³⁺/Sm³⁺, the optical thermometry performances of the NYMVO:0.20Eu³⁺ and NYMVO:0.06Sm³⁺ phosphors were described. Notably, the maximum absolute sensitivity (S_a) values for NYMVO:0.20Eu³⁺ and NYMVO:0.06Sm³⁺ phosphors were 0.30 K^-1 and 0.032 K^-1, respectively. Correspondingly, the maximum relative sensitivity (S_r) values were 2.17 %K^-1 and 1.22 %K^-1, respectively. Moreover, the light-emitting devices based on NYMVO:0.20Eu³⁺ and NYMVO:0.06Sm³⁺ phosphors had excellent optical properties, with correlated color temperature (CCT) of 4552 K and 4470 K, and color-rendering index (CRI) of 84.6 and 88.5. These results suggested that the two vanadate phosphors prepared had potential applications in both warm white light-emitting diodes (WLEDs) and optical thermometry.

To investigate the fluorescent properties of defects found on the surface of harvested soybeans, the front-face method was used to measure the Excitation Emission Matrix (EEM) on 106 samples of two varieties of soybeans to evaluate fluorescent properties according to defect type. The EEM showed four main peaks at Excitation/Emission (Ex/Em): 350-430 nm/420-510 nm, 410-450 nm/460-530 nm, 260-290 nm/300-350 nm and 210-230 nm/310-340 nm. In the Diseased, Pest, and Denatured (Black) soybeans, the above four main peaks were weakened. In addition, in the Denatured (White) Ex/Em: 260-290 nm/300-350 nm specific peak was observed. Furthermore, dimensionality reduction was performed using principal component analysis (PCA), and visualization was performed according to defect type on a two-dimensional plot. The loading of the first and second principal components were also visualized.

Soil nitrogen content and pH value are two pivotal factors that critically determine soil fertility and plant growth. As key indicators of soil health, they each play distinct yet complementary roles in the soil ecosystem. Nitrogen is one of the essential nutrients for plant growth, while soil pH directly influences the activity of soil microorganisms. These microbes are essential for breaking down minerals and organic materials, which in turn affects the availability and conversion of key nutrients like nitrogen and phosphorus. A comprehensive understanding of the distribution of total nitrogen content and pH value is crucial for ensuring the sustainability of agricultural production and maintaining soil and ecosystem health. Existing models for estimating soil property based on near-infrared (NIR) spectral data often overlook the spatial non-stationarity of the relationship between soil spectra and composition content. Therefore, we proposed a new model for estimating soil total nitrogen content and pH value, which combined geographically neural network weighted regression (GNNWR) with extreme gradient boosting (XGBoost), utilizing neural networks to improve the accuracy of predicting total nitrogen content and pH value, efficiently captured the spatial heterogeneity between spectral reflectance and soil total nitrogen content and pH value in different regions. Using the soil nutrient and visible near-infrared spectral samples collected by Eurostat in 2009 for the land use and coverage area frame survey of the 23 members of the European Union, the Geographically Neural Network Weighted-eXtreme Gradient Boosting (GNNW-XGBoost) model was used to estimate total nitrogen content and pH value. The spatial correlation between reflectance of spectral characteristic bands and soil total nitrogen content, pH value was trained in the model to verify its robustness and superiority, and the experimental process was improved by 10-fold cross-validation. In terms of model evaluation, compared to the standalone XGBoost and GNNWR models, the GNNW-XGBoost model demonstrated superior predictive accuracy. It achieved a highest coefficient of determination (R²) of 0.84 for total nitrogen and 0.80 for pH. Additionally, it reduced the root mean square error (RMSE) by 7.64 %, 7.61 % for total nitrogen, and 8.96 %, 4.69 % for pH, respectively. This study not only provides a new method for accurate prediction of soil total nitrogen content and pH value, but also has significant reference value for other estimation issues involving geographic data, which can help to improve the accuracy of environmental monitoring, optimize resource management strategies, and promote the development of sustainable agriculture.

The detection of pesticide residues in agricultural products is crucial for ensuring food safety. However, traditional methods are often constrained by slow processing speeds and a restricted analytical scope. This study presents a novel method that uses filter-array-based hyperspectral imaging enhanced by a dynamic filtering demosaicking algorithm, which significantly improves the speed and accuracy of detecting pesticide residues. Our approach enhances the spatial and spectral resolution of hyperspectral images, thereby providing a rapid and cost-effective alternative to conventional methods with an image integration time of 20 ms. Tested on both synthetic datasets and real agricultural samples, this technology demonstrates superior performance under high noise conditions and exceptional precision in spectral reconstruction at critical color edges. The practicality of this system is demonstrated by integrating a hyperspectral microfilter array with a smartphone's imaging sensor, thereby showcasing the feasibility of deploying this advanced detection technology in everyday portable devices for quick and convenient monitoring of pesticide residues.

An imbalance in iron homeostasis contributes to mitochondrial dysfunction, which is closely linked to the pathogenesis of various diseases. Herein, we developed a nanosensor for detecting mitochondrial ferrous ions in vitro and in vivo. A poly(N-isopropylacrylamine)-coacrylic acid nanohydrogel was synthesized, and ferrous ions were detected using the fluorescent probe FeRhonox-1 embedded within it. (3-Carboxypropyl)-triphenylphosphonium bromide was chemically conjugated to the hydrogel matrix to enable mitochondrial targeting. The developed nanosensor showed a narrow particle size distribution, high sensitivity and selectivity for ferrous ions, and low cytotoxicity, enabling the nanosensor to sense and image ferrous ions in mitochondria with high spatial resolution. Changes in ferrous ion concentrations in human umbilical vein endothelial cells were measured and imaged after lipopolysaccharide (LPS) or iron dextran treatment. Moreover, the nanosensor was successfully used for ferrous ion imaging in live mice. The in vivo results showed that LPS injection induced the accumulation of mitochondrial ferrous ions. The proposed nanosensor could serve as a powerful tool for monitoring ferrous ions in mitochondria, providing strong support for studying disorders of iron metabolism.

The study focuses on the synthesis of V₄O₇ microcubes for the non-enzymatic colorimetric determination of H₂O₂.Vanadium oxide nanostructures are known for their redox activity and layered structures, making V₄O₇ a valuable material for sensing applications. The characterization of the prepared sample was done using XPS, XRD, Raman spectroscopy, and SEM techniques. The V₄O₇ microcube showed a rapid response to H₂O₂ through direct color change without the need for peroxidase enzymes or TMB. Upon exposure to H₂O₂, the mixed valence V₄O₇ oxidized to produce V₂O₅, enabling sensitive detection of H₂O₂. The V₄O₇ sensing system exhibited a wide linear response range from 0.025 to 300 µM with a low detection limit of 7.6 nM for H₂O₂ detection. When combined with glucose oxidase, the system could detect glucose levels as low as 18 nM within a linear range of 0.05 µM to 300 µM. The proposed sensor demonstrated high selectivity and robust potential for sensing H₂O₂ in biological samples. The system offers advantages such as fast response, simple operation, naked-eye observation, and cost-effectiveness. The novel sensing system holds promise for visual detection in H₂O₂ diagnostic clinics, highlighting its potential for practical applications in healthcare settings.