Publications by authors named "Ru-Qin Yu"

The detection and imaging of cysteine (Cys) are vital for clinical applications, given its critical role as a biomarker in various diseases. In this study, a cationic fluorescent probe (probe T) was synthesized, featuring benzothiazole as a fluorescent group and acrylate as a Cys recognition site. Compared to other biothiols, probe T specifically detects Cys while targeting mitochondria and nuclei.

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Asian black truffle Tuber sinense (BT) is a premium edible fungus with medicinal value, but it is often prone to adulteration. This study aims to develop a fast, non-destructive, automatic, and intelligent method for identifying BT. A novel lightweight convolutional neural network model incorporates knowledge distillation (FastBTNet) to improve model efficiency on smartphones while maintaining higher performance.

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Herein, two new or overlooked features of ZIF-90 were identified and investigated. Imidazole-2-carboxaldehyde is fluorescent, but its fluorescence in ZIF-90 is quenched by an ACQ effect. ZIF-90 can enhance the fluorescence of Cy5, but quench that of 6-FAM.

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Blocking mitosis is a promising strategy to induce tumor cell death. However, AMPK- and PFKFB3-mediated glycolysis can maintain ATP supply and help tumor cells overcome antimitotic drugs. Inhibiting glycolysis provides an opportunity to decrease the resistance of tumor cells to antimitotic drugs.

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Lu'an Guapian (LAGP) is a renowned green tea, with its price significantly higher when picked before the Qingming Festival compared to after, posing risks of confusion and counterfeiting. This study proposed using an excitation-emission matrix (EEM) fluorescence method combined with chemometrics for rapid identification of tea picked before and after Qingming Festival. Firstly, the differences among the EEM fingerprints of different tea samples were analyzed using the alternating trilinear decomposition (ATLD) algorithm.

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Effective representation of molecules is a crucial factor affecting the performance of artificial intelligence models. This study introduces a flexible, fragment-based, multiscale molecular representation framework called t-SMILES (tree-based SMILES) with three code algorithms: TSSA (t-SMILES with shared atom), TSDY (t-SMILES with dummy atom but without ID) and TSID (t-SMILES with ID and dummy atom). It describes molecules using SMILES-type strings obtained by performing a breadth-first search on a full binary tree formed from a fragmented molecular graph.

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Telomerase (TE) is a promising diagnostic and prognostic biomarker for many cancers. Quantification of TE activity in living cells is of great significance in biomedical and clinical research. Conventional fluorescence-based sensors for quantification of intracellular TE may suffer from problems of fast photobleaching and auto-fluorescence of some endogenous molecules, and hence are liable to produce false negative or positive results.

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Background: Saffron has gained people's attention and love for its unique flavor and valuable edible value, but the problem of saffron adulteration in the market is serious. It is urgent for us to find a simple and rapid identification and quantitative estimation of adulteration in saffron. Therefore, excitation-emission matrix (EEM) fluorescence combined with multi-way chemometrics was proposed for the detection and quantification of adulteration in saffron.

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Polycyclic aromatic hydrocarbons (PAHs), as a class of organic pollutants that have attracted much attention, are likely to be formed with the production and processing of plastic products, and they may migrate from contaminated plastic products to food, causing the risk of poisoning or cancer. In this study, migration tests were carried out on disposable plastic products for food contact, and a novel strategy that combines excitation-emission matrix (EEM) fluorescence spectroscopy with the advanced second-order calibration method based on the three-direction resection alternating trilinear decomposition (TDR-ATLD) algorithm was used to monitor the migration of three PAHs anthracene (ANT), pyrene (PYR), and phenanthrene (PHE) from the plastic products to food simulants in real-time. With the "second-order advantage", even if the fluorescence spectra of the target analytes overlapped seriously, and other unknown substances migrated from the plastic products to food simulants, accurate qualitative and quantitative results were still obtained by the proposed method.

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The identification of trace textile fabrics discovered at crime scenes plays a crucial role in the case of forensic investigations. Additionally, in practical situations, fabrics may be contaminated, making identification more challenging. To address the aforementioned issue and promote the application of fabrics identification in forensic analysis, front-face excitation-emission matrix (FF-EEM) fluorescence spectra coupled with multi-way chemometric methods were proposed for the interference-free and non-destructive identification of textile fabrics.

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Article Synopsis
  • Unscrupulous traders may sell old Ningxia wolfberry as fresh for high profits, necessitating a reliable identification method.
  • The study proposes using front-face excitation-emission matrix (FF-EEM) fluorescence spectroscopy combined with a deep learning model called EEMnet to accurately determine the storage year of wolfberry samples.
  • The model showcases an impressive classification accuracy of over 98% and includes interpretability analyses to clarify its decision-making process, offering a sustainable solution for identifying storage years of medicinal materials.
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As a common fruit juice, grape juice is delicious and nutritious, making it very popular among consumers. However, some illegal manufacturers used shoddy products to lower costs and obtain high profits, which seriously threatens the health and interests of consumers. Hence, this paper proposed excitation-emission matrix (EEM) fluorescence spectroscopy combined with chemometric methods for the rapid identification and classification of commercial grape juices.

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Article Synopsis
  • A new triple cascade amplification strategy was created for the ultra-sensitive detection of multiple cancer biomarkers using single particle inductively coupled plasma mass spectrometry (spICP-MS).
  • This strategy includes three main parts: a target recycling module using RNA bases for better efficiency, a hybridization chain reaction, and a signal amplification using DNA-templated metal nanoclusters to improve signal quality and reduce interference.
  • The spICP-MS platform showed high accuracy in detecting carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP) in human serum, outpacing traditional methods in sensitivity, operational simplicity, and range, suggesting it could be an effective tool for cancer diagnostics and research.
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Telomerase (TE) is recognized as a potential biomarker for early diagnosis, monitoring and treatment of cancer. At present, most of the methods for TE detection are only applicable to in vitro assays, and unsuitable for in vivo applications. Though a few intracellular probes have been reported to have good specificity for TE, they do not involve signal amplification, which hinders their applicability in scenarios requiring high sensitivity.

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Quantitation of protoberberine alkaloids is an essential guarantee for efficacy control and medication safety of Coptidis Rhizoma (CR) related medicines. Traditional univariate chromatography faced challenges with co-elution, unknown interferences, and retention time shift when analyzing isomeric analytes in varying sample matrices. We presented a chemometrics-enhanced high-performance liquid chromatography-diode array detection (HPLC-DAD) strategy for simultaneous quantification of six protoberberine alkaloids and processed multi-channels chromatographic-spectral data with four second-order calibration algorithms.

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Camellia oil (CAO) is a premium edible vegetable oil with medical value and biological activity, but it is susceptible to adulteration. Therefore, the demand for intelligent analysis to decipher the category and proportion of adulterated oil in CAO was the main driver of this work. Excitation-emission matrix fluorescence (EEMF) spectra of 933 vegetable oil samples were characterized by a chemometric method to obtain chemically meaningful information.

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Geographical origin and authenticity are two core factors to promote the development of traditional Chinese medicine (TCM) herbs perception in terms of quality and price. Therefore, they are important to both sellers and consumers. Herein, we propose an efficient, accurate method for discrimination of genuine and non-authentic producing areas of TCM by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS).

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In this work, a simple and effective strategy for the determination of 12 active compounds of Atractylodes macrocephala Koidz. (AM) was proposed by using high performance liquid chromatography-diode array detection (HPLC-DAD) combined with alternating trilinear decomposition (ATLD) algorithm. Utilizing the "second-order advantage", three common problems in HPLC could be resolved, namely baseline drifts, peak overlaps, and unknown interferences.

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Because of the low atomization and/or ionization efficiencies of many biological macromolecules, the application of mass spectrometry to the direct quantitative detection of low-abundance proteins and nucleic acids remains a significant challenge. Herein, we report mass spectrum tags (MS-tags) based upon gold nanoparticle (AuNP)-templated phosphatidylcholine phospholipid (DSPC) liposomes, which exhibit high and reliable signals via electrospray ionization (ESI). Using these MS-tags, we constructed a liposome signal amplification-based mass spectrometric (LSAMS) "digital" counting assay to enable ultrasensitive detection of target nucleic acids.

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In this paper, in order to solve signal instability of high-performance liquid chromatography-diode array detection (HPLC-DAD) data and maintain the second-order advantage, this work proposed piecewise direct standardization (PDS) assisted with second-order calibration methods to analyze two different complex HPLC-DAD data with signal instability, including simulated HPLC-DAD data and the data of pesticide residues in saffron. Accurate quantitative results of target analytes can be obtained by PDS combined with alternating trilinear decomposition algorithm (ATLD) and alternating trilinear decomposition assisted multivariate curve resolution algorithm (ATLD-MCR) in the presence of signal instability with time shifts and changes of peak shape. Quantitative results of the model after calibration transfer are better than those of the model established by calibration sets and prediction sets with signal instability using ATLD algorithm and ATLD-MCR algorithm under different situations.

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Herein, a label free and sensitive miRNA detection method with enhanced practical applicability was developed based on the locked nucleic acid (LNA) assisted repeated fishing amplification strategy. The working mechanism of the proposed method is as follows: 1) a DNA probe (i.e, L-DNA) with LNA bases is immobilized onto the surface of a gold foil.

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Atractylodes macrocephala Koidz. (AM) is an important plant of traditional Chinese medicine (TCM), and its status can be comparable with ginseng in China. The efficacy and quality of AM are closely related to the place of origin.

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In this work, a simple and fast analytical method based on a self-weighted alternating trilinear decomposition (SWATLD) algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the simultaneous determination of sulfamethoxazole (SMZ) and trimethoprim (TMP) illegally added to health products. With the second-order advantage, the proposed method obtained satisfactory results in the presence of peak overlap and unknown interferences. The analysis time for a single sample is only 0.

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An intelligent chemometric second-order calibration method called alternating trilinear decomposition- assisted multivariate curve resolution combined with high-performance liquid chromatography-diode array detection was used for the simultaneous quantification of nine tyrosine kinase inhibitors in three complex biological systems. The method allows simultaneous quantification of the components in different biological matrices without the need for cumbersome pre-treatment steps, complex elution conditions, and complete peak separation. Even with the varying time shift, severe peak overlap, and various unknown interferences, the proposed method can extract pure chromatographic and spectroscopic information for each analyte, while providing accurate qualitative and quantitative results of nine common tyrosine kinase inhibitors in three different biological matrices.

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In this paper, a fast and efficient analytical strategy was proposed that chemometrics assisted with excitation-emission fluorescence matrices was used to quantify carbaryl (CAR) and thiabendazole (TBZ) in peach, soil and sewage. Even if there are serious overlapped peaks and unknown interferences in fluorescence analysis, the second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm can be used to analyze CAR and TBZ in peach, soil and sewage. The recoveries of CAR and TBZ in peach are 110.

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