Targeting the functional groups present in analytes by nanozyme-catalyzed systems is a promising strategy to construct sensitive and selective platforms for the sensing of specific analytes. Herein, various groups (-COOH, -CHO, -OH, and -NH) on benzene were introduced in an Fe-based nanozyme system with MoS-MIL-101(Fe) as the model peroxidase nanozyme, HO as the oxidizing agent, and TMB as the chromogenic substrate, and the effects of these groups at both a low concentration and high concentration were further investigated. It was found that the hydroxyl group-based substance catechol showed an "on" effect at a low concentration to increase the catalytic rate and enhance the absorbance signal, whereas an "off" effect at a high concentration with a decreased absorbance signal. Based on these results, the "on" mode and "off" mode for the biological molecule dopamine, a type of catechol derivative, were proposed. In the control system, MoS-MIL-101(Fe) catalyzed the decomposition of HO to produce ROS, which further oxidized TMB. In the "on" mode, the hydroxyl groups of dopamine could combine with the Fe(iii) site of the nanozyme to lower its oxidation state, resulting in higher catalytic activity. In the "off" mode, the excess dopamine could consume ROS, which inhibited the catalytic process. Under the optimal conditions, by balancing the "on" and "off" modes, the "on" mode for the detection of dopamine was found to have better sensitivity and selectivity. The LOD was as low as 0.5 nM. This detection platform was successfully applied for the detection of dopamine in human serum with satisfactory recovery. Our results can pave the way for the design of nanozyme sensing systems with sensitivity and selectivity.
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http://dx.doi.org/10.1039/d3ra02946h | DOI Listing |
Sci Data
December 2024
Southern Methodist University Department of Chemistry, Dallas, TX, USA.
The growing popularity of machine learning (ML) and deep learning (DL) in scientific fields is hindered by the scarcity of high-quality datasets. While quantum mechanical (QM) predictions using DL techniques such as graph neural networks (GNNs) and generative models are gaining traction, insufficient training data remains a bottleneck. The QM40 dataset addresses this challenge by representing 88% of the FDA-approved drug chemical space.
View Article and Find Full Text PDFInorg Chem
December 2024
Laboratory for Zero-Carbon Energy, Institute of Integrated Research, Institute of Science Tokyo, 2-12-1 N1-32, O-okayama, Meguro-ku 152-8550, Tokyo, Japan.
A new class of ligands, ,'-dialkyl-2,6-pyridinediamide (DRPDA), has been designed with the specific intention of exhibiting interchangeable diversity in coordination modes, including organometallic interactions, for the purpose of solvent extraction of elements relevant to the proper treatment of high-level radioactive liquid waste (HLLW) generated after nuclear fuel reprocessing. Consequently, DRPDA has been observed to extract Pd(II) and Zr(IV) from HNO(aq) to 1-octanol in nearly quantitative yields when the selected ligand is sufficiently hydrophobic. However, concomitance of some of other HLLW components were also found.
View Article and Find Full Text PDFJ Am Chem Soc
December 2024
State Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Guizhou University, Huaxi District, Guiyang 550025, China.
Enantioenriched phosphorus(V)-stereogenic compounds, featuring a pentavalent phosphorus atom as the stereogenic center, are crucial in various natural products, drugs, bioactive molecules, and catalysts/ligands. While a handful of stereoselective synthetic approaches have been developed, achieving direct stereocontrol at the phosphorus atom through catalytic generation of phosphorus(V)-heteroatom bonds continues to be a formidable challenge. Here, we disclose an organocatalytic asymmetric condensation strategy that employs a novel activation mode of stable feedstock phosphinic acids by the formation of mixed phosphinic anhydride as the reactive species to facilitate further catalyst-controlled asymmetric P-O bond formations, involving a dynamic kinetic asymmetric transformation (DYKAT) process with alcohol nucleophiles via a cinchonidine-derived bifunctional catalyst.
View Article and Find Full Text PDFSensors (Basel)
October 2024
Information Systems and Networks Department, Lviv Polytechnic National University, 12, Bandera Street, 79013 Lviv, Ukraine.
This research focused on the helicopter turboshaft engine dynamic model, identifying task solving in unsteady and transient modes (engine starting and acceleration) based on sensor data. It is known that about 85% of helicopter turboshaft engines operate in steady-state modes, while only around 15% operate in unsteady and transient modes. Therefore, developing dynamic multi-mode models that account for engine behavior during these modes is a critical scientific and practical task.
View Article and Find Full Text PDFMater Horiz
November 2024
Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, College of Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
This study explores the stochastic and binary switching behaviors of a Ta/HfO/RuO memristor to implement a combined data mining approach for outlier detection and data clustering algorithms in a multi-functional memristive crossbar array. The memristor switches stochastically with high state dispersion in the stochastic mode and deterministically between two states with low dispersion in the binary mode, while they can be controlled by varying operating voltages. The stochastic mode facilitates the parallel generation of random hyperplanes in a tree structure, used to compress spatial information of the dataset in the Euclidian space into binary format, still retaining sufficient spatial features.
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