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The residues of organophosphorus pesticides (OPs) in food pose a huge threat to human health. Therefore, the development of detection methods with simple design and high sensitivity is urgently needed. Here, a colorimetric/chemiluminescence (CL) dual-mode aptasensor strategy with high selectivity and sensitivity for detecting Parathion-methyl (PM) was designed based on aptamer-regulated nanozyme activity. The Parathion-methyl specific aptamer was anchored onto the surface of trimesic acid-Cu (TA-Cu) nanozyme, which can regulate the catalytic ability of TA-Cu nanozyme towards substrates and also serve as a specific recognition unit for PM. In the presence of PM, the aptamers bind to PM and detach from the surface of TA-Cu nanozyme, which effects the catalytic ability of TA-Cu nanozyme towards substrates. Based on the above experimental phenomena, a colorimetric/CL dual-mode aptasensor method for PM was developed, with the linear ranges of 0.01-20 and 1-100 ng/mL, the limit of detections of 0.004 and 0.45 ng/mL, respectively. More importantly, compared with most single mode analysis methods, this dual-mode sensing system can conduct self-inspection by comparing the detection results of each mode, thus improving the reliability of the detection results.

Genetic testing plays a crucial role in guiding individualized medication, however, detecting fine structural mutations in genes continues to present significant challenges. This study introduces a dual-signal fluorescence system, termed Fe₃O₄@Au@PEG@P1+MOF@P₂, that integrates magnetic separation of Fe₃O₄@Au with NH₂-MIL-88 (MOF) catalysis. Initially, the specimen (T1/T2) facilitated the formation of a specific complex (Fe₃O₄@Au@PEG@P1+T1/T2) with Fe₃O₄@Au@PEG@P1. The subsequent addition of Hoechst-33258 produced a robust fluorescence signal at 460 nm, enabling the identification of mutations in the first gene regions. Following this, MOF@P₂ was introduced to activate the catalyst through P2 pairing with T2. The complex Fe₃O₄@Au@PEG@P1+T1/T2+P2+Hoechst-33258 was subsequently isolated using an external magnetic field. Upon adding OPD, fluorescent DAP was detected at 560 nm, allowing for the identification of mutations in the second gene regions. The research demonstrated that the variation in fluorescence signals increased with a higher number of base substitutions and deletion mutations, with deletion mutations resulting in a notably greater alteration rate compared to substitution mutations. Interestingly, triple base substitution mutations, characterized by lower clustering of non-continuous mutations, produced a more pronounced change in fluorescence signal than did a higher clustering of continuous mutations (codon mutations). This single-step methodology effectively differentiates among the number and types of mutations across multiple gene regions while assessing the degree of mutation clustering. Overall, this technology significantly enhances the current capabilities for detecting fine structural mutations in genes. Furthermore, the approach exhibits high sensitivity in detecting concentrations of T1 and T2 ranging from 10^-15 M to 10^-9 M, with detection limits of 0.19 fM and 0.24 fM, even in 5 % serum samples.

Although nanozyme has shown great potential in designing fluorescent assays for pesticide residue, most of them are based on single emission, thus affecting the detection accuracy. Herein, a copper-based fluorescent nanozyme (Cu-BH) synthesized with dual-ligand, integrating fluorescence and oxidase-mimic into one spherical nanomaterial, was used firstly to establish a ratiometric approach for visual detection of thiophanate methyl (TM). Cu-BH possesses excellent oxidase-like activities, triggering the oxidation of colorless o-phenylenediamine (OPD) into yellow luminescent products (oxOPD, λem = 564 nm). Besides, the ligand of 2-amino-1,4-benzene-dicarboxylic acid imparts Cu-BH blue fluorescence (λem = 425 nm), which is quenched by oxOPD via inner filtration effect (IFE). The introduction of TM can prevent not only the oxidase-like activity remarkably but also the intrinsic luminescence of Cu-BH slightly because of the complexation of TM with Cu²⁺. As a result, the fluorescence intensity at 564 nm and 425 nm presents a significant decrease and a slight increase, respectively, producing a ratiometric fluorescent signal (F₄₂₅/F₅₆₄). Therefore, a novel ratiometric fluorescent strategy has been proposed to detect TM ranging from 0.1 to 100 μM with detection limit of 0.03 μM (S/N = 3). Besides, visual detection of TM can be achieved by RGB reading with the assistance of smartphone owing to the color variation from yellow to blue. This fluorescent nanozyme-based ratiometric strategy provides a specific method for the detection of TM in food samples.

Simultaneous detection of biomarkers in sweat is crucial for comprehensive health assessment and personalized monitoring. However, the low sweat secretion rate and low metabolite concentrations present challenges for developing non-invasive wearable sensors. This study aims to develop a flexible wearable biosensor for simultaneous detection of low-concentration biomarkers in sweat, enabling comprehensive health assessment. This study synthesized an innovative bimetallic tungstate Ag@Ag₂WO₄ and evaluated its performance for detecting uric acid (UA, 10-1000 μM), dopamine (DA, 3-500 μM), and tyrosine (Tyr, 5-1000 μM). The detection limits (LODs) for DA, UA, and Tyr sensors were 3.10 μM, 8.47 μM, and 4.17 μM, respectively, with relative standard deviations (RSDs) of 4.76 %, 2.66 %, and 3.51 %, respectively. Additionally, this study designed a hydrophilic microfluidic collection system inspired by bamboo leaf structures to enhance sweat collection efficiency. Validation studies demonstrated that the wearable biosensor effectively detects UA and TA in the sweat of volunteers. We believe this research could contribute to advancing personalized healthcare by improving the convenience and effectiveness of health monitoring technologies.

An europium metal organic framework (Eu-DBPA-Phen) was synthesized using 2,5-dibromoterephthalic acid (H₂DBPA) and 1-10-phenanthroline (Phen) as ligands. A straightforwardc quasi-ratiometric fluorescence probe was then developed for the detection of levofloxacin (LVF) by the simplistic combination of red-emitting Eu-DBPA-Phen and the inherent blue auto-fluorescence of the target. The probe exhibits the advantages of wide linear range (0.01-50 and 50-175 μM), good selectivity, low detection limit (4.53 nM) and fast response time. In addition, a smartphone-assisted fluorescent test strip analysis platform was established for the visual and on-site detection of LVF in milk and fish samples, achieving satisfactory recovery rates ranging from 101.7 % to 103.4 % and low standard deviations (RSD ≤2.890, n = 3). Furthermore, a hierarchical clustering algorithm integrating machine learning and smartphone-test strip platform was devised to streamline the detection process. The proposed intelligent detection platform introduces a novel approach for LVF detection, thereby enhancing food safety and human health.

Glutathione (GSH) is a key biomarker closely associated with cancer, and its content varies greatly between normal cells and cancer cells. However, intracellular detection of GSH was challenging because existing probes not only have a long detection time but also have fluorescence in the blue-green region that overlaps with the biological matrix's spontaneous fluorescence, thus affecting the detection accuracy. Therefore, a new red fluorescent nano-probe was needed to rapidly and accurately detected GSH within the biological matrix. Herein, red carbon dots (R-CDs) synthesized via hydrothermal method using N-(4-amino phenyl) acetamide and 4-Bromo-1,2-diaminobenzene as precursors offer enhanced fluorescence that could be quenched by MnO₂ nanosheets (MnO₂ NS) and restored by GSH. By combining R-CDs with the AS1411 aptamer and using rolling circle amplification, a multivalent aptamer modified R-CDs assembly (Assembly@R-CDs) was created for swift cancer cell targeting. Compared to monomeric aptamer, such multivalent aptamers exhibited higher affinity and selectivity, thereby enhancing the specificity and sensitivity of detection. After the fluorescence of the multivalent assembly was quenched by MnO₂ NS (Assembly@R-CDs@MnO₂ NS), it could be restored when targeting cancer cells, which could realize the distinction between normal cells and cancer cells. The experiment showed that 4T1 cancer cells took up more Assembly@R-CDs@MnO₂ NS than L929 normal cells and generated stronger fluorescence, indicating the high selectivity for cancer cell detection. The potential of such nanosystem for tumor diagnosis combination therapy is promising, especially considering the embedding properties of anthracene drugs such as doxorubicin in DNA carriers.

A microanalytical technique based on the photothermal effect in conjunction with back-scattering interferometry (BSI) using a single laser beam was developed for quantitative detection of heavy metals. After the chromogenic reaction of an analyte in a capillary tube, the photothermal effect induced by irradiation with the same laser beam leads to a change of the refractive index of the solution, which can be "quantified" using the BSI technique. For prove-of-concept, Cu(II) was chosen as the trial analyte, for which the solution changes to purplish through reacting with the chromogenic reagent; a single laser beam of 532 nm was adapted for both inducing the photothermal effect and realizing BSI detection. With as little as 1.0 μL solution, a limit of detection (LOD) of 0.10 mg/L for Cu(II) was achieved. In addition, the versatility of the technique was demonstrated by detecting other two heavy metal ions, Fe(II) and Cr(VI), with limits of detection of 0.06 mg/L and 0.04 mg/L, respectively. The demonstrated detection sensitivity, application versatility, and instrumentation simplicity of this new technique promises it as a practical tool for environmental monitoring and beyond.

A significant challenge in membrane production is the need for affordable materials that provide high efficiency for their designated applications. Employing recycled materials in membrane manufacturing is viewed as a promising solution to tackle this challenge. In this work, a superwettable polyethylene terephthalate membrane modified with cobalt zeolitic imidazolate framework (PET/Co ZIF) is prepared for the first time from recycled plastic mineral water bottles and used to extract polycyclic aromatic hydrocarbons (PAHs) from aqueous samples followed by high-performance liquid chromatography with UV detection (HPLC-UV). The characterization of functional groups, crystalline structure, elemental analysis, morphology, and wettability of membrane was performed by Fourier transform-infrared (FT-IR), X-ray powder diffraction (XRD), field emission-scanning electronic microscope (FE-SEM), energy dispersion spectroscopy (EDS) and contact angles techniques, respectively. The effect of type of eluent and membrane was investigated and optimized. After studying the effect of other factors named volume of eluent, sample pass cycles and ionic strength of sample solution by Box-Behnken design (BBD) and response surface methodology (RSM), a linear range of 0.1-600 μg/L with a coefficient of determination (R²) of more than 0.9982 was obtained for fluorene, phenanthrene, pyrene and chrysene. The limit of detection for the mentioned compounds was in the range of 0.05-0.34 μg/L. This method was successfully applied to determine PAHs in river water and wastewater samples. The relative recovery of more than 88.0 % and the error of less than 5.7 % indicate the applicability of this method.

The combined application of near-infrared spectroscopy (NIRS) and X-ray fluorescence spectroscopy (XRF) has achieved remarkable results in coal quality analysis by leveraging NIRS's sensitivity to organic compounds and XRF's reliability for inorganic composition. However, variations in particle size distribution negatively affect the diffuse reflectance of NIRS and the fluorescence signal intensities of XRF, leading to decreased accuracy and repeatability in predictions. To address this issue, this study innovatively proposes a particle size correction method that integrates image processing and deep learning. The method first captures micro-images of the coal sample surface using a microscope camera and employs the Segment Anything Model (SAM) for binarization to represent particle size distribution. Subsequently, a Spatial Transformer Network (STN) is applied for geometric correction, followed by feature extraction using a Convolutional Neural Network (CNN) to establish a correlation model between particle size distribution and ash measurement errors. In experiments involving 56 coal samples, including 48 at 0.2 mm for the standard ash prediction model and 8 within a 0∼1 mm range for correction, the results showed significant improvements: standard deviation (SD), mean absolute error (MAE), and root mean square error of prediction (RMSEP) decreased from 0.321%, 0.317%, and 0.335% to 0.229%, 0.225%, and 0.257%, respectively. Using the accuracy of the 0.2 mm particle size validation set as a reference, compared to before correction, the errors in these metrics were reduced by 64.06%, 50%, and 60.80%, respectively. This study demonstrates that integrating deep learning and image analysis significantly enhances the repeatability and accuracy of NIRS-XRF measurements, effectively mitigating sub-millimeter particle size effects on spectral detection results and improving model adaptability. This method, through automated particle size distribution analysis and real-time result correction, holds promise for providing essential technical support for the development of online quality detection technologies for conveyor belt materials.

Methotrexate (MTX) is a widely used antimetabolite drug, mainly used in the treatment of a variety of cancer. Given the low therapeutic index and significant individual variability of MTX, it was critical to perform therapeutic drug monitoring (TDM) to minimize the side effects. Here, we designed a rapid and sensitive fluorescence/colorimetric assay for the detection of MTX in diluted human serum. After the aptamer binds specifically to MTX, the Walking strand cleaves the Hairpin strand and releases a large amount of fluorescent signal, and the color of the gold nanoparticles changes after the addition of sodium chloride. The change of color could be visualized by eyes to achieve point-of-care TDM of MTX. The quantitative detection of MTX concentration is carried out through the collection of fluorescent signals or absorptions. The fluorescence method can detect MTX in the range of 0.05-1000 μM with the detection limit of 0.0243 μM, meanwhile, the colorimetric method can detect MTX in the range of 0.01-100 μM with the detection limit of 0.0097 μM. The magnetic separation-assisted DNAzyme walker-based nanosensor exhibited good sensitivity, selectivity and stability for detecting MTX in serum and achieve point-of-care methods of TDM of MTX and the nanocarriers has demonstrated significant potential for clinical application.