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Butylcholinesterase (BChE) is a key enzyme in living system, closely related to liver and neurological diseases. It is very challenge to develop near-infrared (NIR) fluorescence probe methods for highly selective and sensitive detection of BChE in vivo. Based on the differences in active sites and spatial pockets between acetylcholinesterase (AChE) and BChE, a new NIR BChE-responsive fluorescence probe Probe-BChE (λ_ex/λ_em = 600 nm/676 nm) was designed and synthesized by introducing dimethyl carbamate group as recognizing moiety to a NIR fluorophore hemicyanine skeleton. It was found that Probe-BChE specifically binds with BChE, rather than AChE, since BChE has a big cavity and strong intermolecular forces with Probe-BChE, which was supported by the molecular docking scores. The fluorescence method for the determination of BChE was developed with a detection limit of 0.14 U/mL BChE and high selectivity as well as short reaction time (∼3 s). The fluorescence imaging method using Probe-BChE efficiently image the levels of endogenous BChE in brains and main organs (heart, liver, spleen, lung and kidney) of Alzheimer's disease (AD) mice. The results reveal that the levels of endogenous BChE in old AD mice is higher than that in young AD mice, and endogenous BChE is enriched in the liver of AD mice. This work demonstrates that Probe-BChE is a promising fluorescence probe for imaging of endogenous BChE in AD mice. The design of NIR fluorescence probes for endogenous BChE in this work will promote to design NIR fluorescence probes for endogenous cholinesterase.

Pathogenic bacteria infections are a major public health problem in current society. Rapid and reliable identification of these pathogens can help avoid the misuse of antibiotics and enable precision therapy. In this study, we present a large-spot confocal Raman system based on fiber array (LSCR-FA) for the in situ detection of microbial colonies on agar plates. This method can alleviate the problem of spatial heterogeneity of colonies to a certain extent and is fast and high-throughput. Additionally, we also applied machine learning algorithms with 5-fold cross-validation to analyze colony Raman spectral data and classify seven different pathogenic bacteria. Among them, the Support Vector Machine (SVM) achieved a high accuracy of 98.74 %. The results of the study demonstrate that the mentioned LSCR-FA system combined with machine learning algorithms provides a new, fast, and effective strategy for the identification of pathogenic bacteria and precise clinical treatment.

Branched fatty acid esters of hydroxy fatty acids (FAHFAs) represent a novel class of bioactive lipids with significant physiological roles. However, their identification, particularly of low-abundance FAHFA regioisomers, remains challenging due to their high structural similarity, low natural abundance, and the limited availability of reliable FAHFA standards. In this study, we present a QSAR-based FAHFA annotation strategy that integrates a QSAR model with an ester bond position (EP) rule to determine the EPs of FAHFA regioisomers. The QSAR model quantitatively relates the retention index (RI) of FAHFAs to the EP descriptor and the GATS2m descriptor, while the EP rule establishes a quantitative relationship between the RI of FAHFA regioisomers and their EP within a given FAHFA family. By applying this QSAR-based strategy, we successfully identified a comprehensive set of 507 FAHFA regioisomers from 1207 FAHFA candidates detected across 16 food samples, achieving nearly a threefold increase in annotation coverage compared to our previous method. Overall, this strategy significantly enhances the identification capability in determining EP for FAHFA regioisomers, providing a promising analytical tool for the further exploration into these lipids.

Alzheimer's disease (AD) significantly impacts the well-being of older people around the world. However, the accurate detection of glycosylated amyloid-beta (Aβ) proteins, which serve as important biomarkers for AD, remains challenging due to their extremely low levels. To address these issues, we proposed a method for fabricating a flexible and stable sensor platform based on an innovative boronic acid-based covalent organic framework COF-B(OH)₂. After in situ formation on carbon cloth (CC) by facile interfacial perturbation, this CC-based COF substrate could further serve as an electrochemical platform for detecting glycosylated-Aβ16 via molecular interactions. The substrate offers abundant molecular recognition sites, a large specific surface area, and excellent electrical conductivity. Furthermore, poly(thymine)-templated copper nanoparticles (CuNPs) linked to the aptamer of glycosylated-Aβ16 were employed as electrochemical probes, providing an amplified signal. The proposed assay for the detection of glycosylated-Aβ16 proteins demonstrated a wide detection range of 5-1800 pg/mL, with an ultralow detection limit of 0.32 pg/mL and high stability. This research offers novel insights into the developing electrochemical biosensors for analyzing glycosylated protein, leveraging advanced COF-B(OH)₂ materials.

Sweat lactate levels are closely related to an individual's physiological state and serve as critical indicators for assessing exercise intensity, muscle fatigue, and certain pathological conditions. Screen-printed electrodes (SPEs) offer a promising avenue for the development of low-cost, high-performance wearable devices for electrochemical sweat analysis. The material composition of SPEs significantly impacts their detection sensitivity and stability. In this study, we designed a screen-printed carbon electrode (SPCE) modified with Ti₃C₂T_x Polydopamine (PDA), and silver nanoparticles (AgNPs) (Ti₃C₂T_x-PDA-AgNPs) for lactate detection in sweat. The accordion-like structure of Ti₃C₂T_x provides a large specific surface area and exceptional electrical conductivity. PDA, acting as both a reducing agent and binder, supports the in-situ formation of AgNPs on the Ti₃C₂T_x nanosheets. These AgNPs prevent the restacking of Ti₃C₂T_x layers, further improving conductivity. The sensor exhibited sensitivities of 0.145 μA mM^-1, with limit of detection (LOD) of 0.181 mM (S/N = 3) in phosphate-buffered saline (PBS), meeting the requirements for for sweat lactate detection. The sensor was integrated into a wearable micro-electrochemical platform paired with a custom Android application for real-time sweat analysis. Testing on human sweat demonstrated the platform's potential for practical fitness monitoring and healthcare diagnostics applications.

The excessive presence of the metal ions Cu²⁺ and Fe³⁺ in the environment poses a serious threat to ecosystems and human health, so timely and accurate detection of them has become essential and urgent. In this paper, a novel hydrogel-based fluorescent sensor, named ME-IPA@SA-TbZn, was fabricated facilely through an in-situ cross-linking modification method and was used for the detection of Cu²⁺ and Fe³⁺ in water bodies. The ME-IPA@SA-TbZn is essentially a hybrid hydrogel bead that exhibits vibrant fluorescence, employing Tb and Zn functionalized hydrogen-bonded organic frameworks (HOFs) as the fluorescence functional core and sodium alginate (SA) as the hydrogel matrix. The synthesized hydrogel sensor ME-IPA@SA-TbZn exhibits remarkable capabilities in detecting and distinguishing between Cu²⁺ and Fe³⁺ with high selectivity and sensitivity. Specifically, it achieves limits of detection (LODs) of 1.275 μM for Cu²⁺ and 0.549 μM for Fe³⁺, respectively, both are below the maximum allowable concentrations set by the U.S. Environmental Protection Agency (EPA) for drinking water. Importantly, the hydrogel sensing platform delivers intuitive and visible results under simple operating conditions, and has been successfully applied to Cu²⁺ and Fe³⁺ detection in river samples. In addition, it was demonstrated that disruption of the "antenna" effect, absorption competition quenching (ACQ) effect, and ion exchange (IE) effect are the main mechanisms leading to fluorescence quenching. Based on these results, ME-IPA@SA-TbZn hold promise as a fluorescent sensor for detecting Cu²⁺ and Fe³⁺ ions.

Aflatoxin B1 (AFB1) exhibits significant toxicity and pose a serious threat to food safety, environmental hygiene, and public health even in trace amounts. Hence, the development of a rapid, accurate, and sensitive detection technology has become a pivotal aspect of ensuring control standards. In this study, we introduce the UIO66 and two defective dichloroacetic acid@UIO66 (DCA@UIO66, DU) metal-organic framework nanoparticles, named DU1 and DU2, characterized by different defect levels. It is noteworthy that DU1 exhibits superior DNA sensing capability compared to UIO66 and DU2. With a fluorescence quenching efficiency of 92.66 % and a recovery efficiency of 1256.75 %, DU1 demonstrates the substantial potential in the detection field. Furthermore, we employ cascade isothermal amplification to assist DU1-mediated fluorescence sensors in detecting AFB1. AFB1 is efficiently identified through an aptamer competition process facilitated by magnetic nanoparticles, which initiates the exponential amplification triggered rolling circle amplification reaction, and converts trace amounts of toxin signal into a large number of long single-stranded DNA molecules. Upon recognition of the amplification product by the fluorescent probe on DU1, a more stable double-stranded DNA is formed and leaves the surface of DU1, leading to a significant change in fluorescence intensity. This method exhibits acceptable sensitivity, with a detection limit of 0.09 pg mL^-1 and a wide detection range spanning from 0.2 pg mL^-1 to 20 pg mL^-1. Additionally, this assay exhibits satisfactory specificity and high accuracy in practical sample applications. Our proposed method offers a solid theoretical framework and technical backing, thereby facilitating the establishment of a new generation of mycotoxin detection standards.

Uranium is a toxic radionuclide, and its most stable and common ionic form is water-soluble uranyl ions (UO₂²⁺), which migrates into the environment easily and causes adverse effects on environment and human health. Herein, by cleverly designing the stem of DNA hairpin with palindromic sequence, a self-hybridization chain reaction (SHCR) system was developed for sensitive UO₂²⁺ detection. This detection system showed a good linear correlation between the ratio of fluorescence intensities and UO₂²⁺ concentration within the range of 0.05 nM-20 nM, and the detection limit was calculated to be 0.017 nM. Unlike the traditional HCR system which involves two hairpins, this proposed SHCR system only needs one DNA hairpin, which reduces the complexity of sequence design and experimental operation. And it can be used for the detection of other non-nucleic acid targets by simply changing the target molecule recognition module.

In this study, we report the synthesis, optical characterization and ultra-sensitive ammonia gas sensing properties of Mg-doped ZnO cauliflower like nanostructures obtained via chemical spray pyrolysis technique. The morphological and structural properties of the prepared films were investigated by Field Emission Scanning electron microscope (FESEM) and X-ray diffraction (XRD). Gas sensing and optical characterizations were carried out using Keithley electrometer and Uv-Vis. Spectrophotometer. Cauliflower-like nanostructures were obtained with diameter 33.16 nm of 5 % Mg-doped ZnO films. Significant changes in the pivot-like morphology of 1 % Mg-doped ZnO sample to cauliflower like morphology indicates that higher Mg doping concentration affects the morphology. Surface to volume ratio increased as the particle size reduced from 38 nm to 33 nm with increasing Mg doping. This emphasizes that the morphology and the surface area play an important role in the surface phenomenon of materials. The XRD results reveal that obtained films have hexagonal (wurtzite) crystal structure of ZnO. The gas sensing properties of Mg-doped ZnO nanostructures were tested based on resistance variation upon the exposure of ammonia vapor at room temperature. The ability 5 % Mg-doped ZnO nanostructures to sense 5 ppm ammonia gas was enhanced with least response (24 s) and recovery time (27 s). It may be due to Mg-doping tuned the required surface morphology of ZnO. Moreover, the ammonia gas sensing mechanism of Mg-doped ZnO nanostructures is demonstrated. Optical energy bandgap is decreased due to the increased defects formation with higher Mg doping. Based on the gas sensing and optical properties, Mg-doped ZnO materials are the promising candidate for ammonia gas sensor and opto-electronic device applications.

Environmental exposure to crude oil through seepage and spillage poses risks to the immediate environment and the broader ecosystem as areas along the oil distribution path are affected by the influx of crude petroleum as well as the environmental, economic, and civil unrest that accompanies it. There is a large financial burden associated with the lost resources, including the cost of rehabilitation, and the affected sources of revenue for communities affected by oil spills. As such, it is crucial to determine the responsible parties. This work outlines an environmental forensics approach to determining the source of an un-weathered crude oil sample. The researchers employed solid phase microextraction coupled with gas chromatography mass spectrometry (SPME-GC-MS) to capture and analyze the gaseous components emitted by crude oil samples sourced from five locations. Samples were analyzed using Spearman's rank correlation and 3D covariance analysis. Both chemometric approaches yielded optimal performance results with no misclassifications, true positive rate (TPR) = 100 % and false positive rate (FPR) = 0 %. The similarity metrics calculated by each test noted clear delineations between the values of same-source and differently sourced samples. The Spearman's rank correlation test and 3D covariance calculations both demonstrated the ability to correctly identify sample source origin in this dataset. The authors outline an approach to the future application of these tests and suggest their joint use in future crude oil sourcing endeavors.