JOURNAL OF COLLOID AND INTERFACE SCIENCE
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2024
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IF 9.4
Minghui Kong,Yang Lu,Yuan Ma,Xu Zhao,Jiahang Wu,Geyu Lu,Xu Yan,Xiaomin Liu
On-site quantitative analysis of pesticide residues is crucial for monitoring environmental quality and ensuring food safety. Herein, we have developed a reliable hydrogel portable kit using NaYbF 4 @NaYF 4 : Yb, Tm upconversion nanoparticles (UCNPs) combined with MnO 2 nanoflakes. This portable kit is integrated with a smartphone reader and Python-assisted analysis platform to enable sample-to-result analysis for chlorpyrifos. The novel UCNPs maximizes energy donation to MnO 2 acceptor by employing 100 % of activator Yb 3+ in the nucleus for NIR excitation energy collection and confining emitter Tm 3+ to the surface layer to shorten energy transfer distance. Under NIR excitation, efficient quenching of upconversion blue-violet emission by MnO 2 nanoflakes occurs, and the quenched emission is recovered with acetylcholinesterase-mediated reactions. This process allows for the determination of chlorpyrifos by inhibiting enzymatic activity. The UCNPs/MnO 2 were embedded to fabricate a hydrogel portable kit, the blue-violet emission images captured by smartphone were converted into corresponding gray values by Python-assisted superiority chart algorithm which achieves a real-time rapid quantitative analysis of chlorpyrifos with a detection limit of 0.17 ng mL −1 . At the same time, pseudo-color images were also added by Python in “one run” to distinguish images clearly. This sensor detection with Python-assisted analysis platform provides a new perspective on pesticide monitoring and broadens the application prospects in bioanalysis.
研究领域:
环境科学
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食品安全
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生物分析化学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
TALANTA
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2024
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IF 5.6
Kai Zhang,Yule Qian,Chaoyan Lou,Mingli Ye,Yan Zhu
PyICLab is an open-source Python-based package featuring an object-oriented programming (OOP) interface, providing tools for realistic and customized numerical simulations of ion chromatography (IC). In this paper, we showcase PyICLab's use in simulating diverse separation scenarios, including isocratic carbonate elution, gradient hydroxide elution, high-concentration and large-volume injections. The accuracy of the embedded models was validated by demonstrating strong correlations between predicted and experimental results. Additionally, PyICLab's capability to handle complex IC configurations was demonstrated through a simulation of a column-switching system for seawater analysis. PyICLab offers valuable resources for chromatographic optimization, method development, and educational purposes. It is available on PyPI at pypi.org/project/pyIClab. Interested readers can install PyICLab using the pip command in a Python 3.11 or higher environment.
研究领域:
分析化学
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计算科学
✓ 已验证
DOI
PubMed
高影响因子
JOURNAL OF FOOD COMPOSITION AND ANALYSIS
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2024
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IF 4
Caiyun Liu,Siye Gao,Jialin Ma,Yongliang Lu,Mario Prejanò,Yunkui Li
Increasing consumer demand for high-quality wines required the introduction of more comprehensive monitoring indicators for quality management, necessitating winemakers to strive for rapid, real-time, and affordable monitoring tools during winemaking. This study investigated the feasibility of cost-efficient and easy-to-implement ultraviolet-visible (UV-Vis) spectroscopy combined with chemometric methods to predictively monitor the evolution of wine color and phenolics throughout commercial fermentation. Fermentations on a winery scale were carried out with a daily analysis of the UV-Vis spectra, color, and phenolics. Furthermore, characteristic wavelengths were established by a self-compiled Python program to reduce redundancy in spectra. The optimized partial least squares (PLS) model predicted well with a residual prediction deviation (RPD) greater than 2.54, and the robustness was further verified by a robust external Bland-Altman method. UV-Vis spectroscopy can achieve objective monitoring of the practical fermentation profile, which can better help winemakers make decisions to improve wine quality and consistency.
研究领域:
食品科学
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分析化学
✓ 已验证
产品关联
DOI
高影响因子
SENSORS AND ACTUATORS B-CHEMICAL
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2024
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IF 8
Tianfei Qi,Ruonan Jia,Linbo Zhang,Guanyu Li,Xuefeng Wei,Jianting Ye,Ruilian Qi,Haiyuan Chen
Self-reporting corrosion protection coatings offer effective means to detect potential failures in advance, allowing for timely maintenance and extending the lifespan of metal materials. However, there currently remains a challenge in developing techniques capable of concurrently monitoring coating damage and metal corrosion throughout a procedure. Herein, N-CDs/Fe 3 O 4 hybrid nanoparticles with high peroxidase-like activity were fabricated through a two-step hydrothermal process which exhibit superior affinity (K m =1.2 mM) towards H 2 O 2 than HRP and effectively turn-on the color of TMB . Combined with the excellent responsiveness towards 8-HQ and the strict linear dependent relationships towards Fe 3+ (ranging from 0.75 to 15.15 μM), a novel colorimetric assay is established to not only turn on the signals to report the appearance of damage, but additionally switch the colors of TMB system to reveal the possible crack propagation and metal corrosion underneath. Moreover, the pre-existing corrosion, characterized by higher Fe 3+ concentration, is successfully indicated according to the color intensity enhancement compared with pristine metal sheet. Notably, such a multifunctional colorimetric assay enables the real-time and visual monitoring coating damage and metal corrosion simply through a Python program integrated into smartphones, serving as a promising strategy for promptly alerting of potential structural failures.
研究领域:
材料科学
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腐蚀科学
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分析化学
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传感器与执行器
✓ 已验证
产品关联
DOI
高影响因子
FOOD CHEMISTRY
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2023
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IF 8.8
Yelin Ding,Qirui Bi,Dongdong Huang,Jingmei Liao,Lin Yang,Xiaoxiao Luo,Peilei Yang,Yun Li,Changliang Yao,Wenlong Wei,Jianqing Zhang,Jiayuan Li,Yong Huang,De-an Guo
The composition and quantity of amino acids (AAs) in seeds are complicated due to the various origins and modifications of different species. In this study, a novel automatic neutral loss filtering (ANLF) strategy based on accurate mass searching by Python was developed to analyze the free and hydrolyzed AA-phenyl isothiocyanate (PITC) derivatives from seeds of Gymnosperm and Angiosperm phyla. Compared with traditional strategies, ANLF showed much higher accuracy in screening AA derivatives by filtering nitrogen-containing non-AA compounds and efficiency in processing large datasets. Meanwhile, the content phenotype of 20 proteinogenic AAs from seeds of these two families was characterized by a 35-min HPLC method combined with an automated peak-matching strategy. AA profiles of 232 batches of seeds from 67 species, consisting of 19 proteinogenic AAs, 21 modified AAs, and 77 unknown AAs, would be a good reference for their application in food and medicine.
研究领域:
生物化学
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植物科学
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分析化学
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食品科学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）