Article
Computer Science, Information Systems
Wan-Lei Zhao, Hui Wang, Peng-Cheng Lin, Chong-Wah Ngo
Summary: This paper addresses the issue of merging k-nearest neighbor (k-NN) graphs in two different scenarios. A symmetric merge algorithm is proposed to combine two approximate k-NN graphs, facilitating large-scale processing. A joint merge algorithm is also proposed to expand an existing k-NN graph with a raw dataset, enabling the incremental construction of a hierarchical approximate k-NN graph.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Engineering, Electrical & Electronic
B. Sangamithra, B. E. Manjunath Swamy, M. Sunil Kumar
Summary: Every client uses web service technology for data retrieval. Current search engines fail to provide personalized results, which can be improved by incorporating machine learning classifiers. This study evaluates the performance of different algorithms using metrics like accuracy, precision, and recall to enhance web search.
OPTICAL AND QUANTUM ELECTRONICS
(2023)
Article
Engineering, Multidisciplinary
S. Naveen Venkatesh, V. Sugumaran
Summary: This study aims to identify visual faults in photovoltaic modules using machine vision and machine learning techniques, specifically through the classification of normal RGB images with the fusion of deep learning and machine learning methods.
Article
Computer Science, Hardware & Architecture
Martin Aumueller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri
Summary: This paper studies the r-NN problem in similarity search in the context of individual fairness and equal opportunities. The authors propose efficient data structures for the fair NN problem and highlight the inherent unfairness of existing NN data structures through experimental evaluation.
COMMUNICATIONS OF THE ACM
(2022)
Article
Automation & Control Systems
Hongjiao Guan, Long Zhao, Xiangjun Dong, Chuan Chen
Summary: Imbalanced data classification is a challenging problem in many applications. We propose an extended natural neighbor (ENaN) concept without parameter k to improve the quality of generated examples by accurately reflecting the local distribution. ENaN-based SMOTE (ENaNSMOTE) can improve the sample distribution obtained by SMOTE and NaNSMOTE.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Jianping Gou, Liyuan Sun, Lan Du, Hongxing Ma, Taisong Xiong, Weihua Ou, Yongzhao Zhan
Summary: This article proposes a novel representation coefficient-based k-nearest centroid neighbor method (RCKNCN) aiming to improve the classification performance and reduce the sensitivity to the neighborhood size k. The method captures both the proximity and geometry of k-nearest neighbors and learns to differentiate the contribution of each neighbor to the classification of a testing sample. A weighted majority voting algorithm is also proposed under the RCKNCN framework.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo
Summary: This paper presents a simple yet effective solution for approximate k-nearest neighbor search and graph construction. The solution integrates graph construction and search tasks, and supports dynamic updates on the built graph.
IEEE TRANSACTIONS ON MULTIMEDIA
(2022)
Article
Automation & Control Systems
Amit Kumar Gangwar, Om Prakash Mahela, Bhuvnesh Rathore, Baseem Khan, Hassan Haes Alhelou, Pierluigi Siano
Summary: This article introduces an algorithm for protecting transmission lines, which detects and locates faults using k-means clustering and weighted k-nearest neighbor (k-NN) regression. The algorithm synchronizes and samples three-phase current signals, computes cumulative differential sum (CDS), and uses various case studies to validate its robustness.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Benqiang Wang, Shunxiang Zhang
Summary: The study proposes a new locally adaptive k-nearest centroid neighbour classification method based on average distance, which improves classification performance by finding nearest centroid neighbours to determine k neighbours and deriving discrimination classes with different k values based on the number and distribution of neighbours, resulting in better performance compared to other state-of-the-art KNN algorithms.
CONNECTION SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Simone Disabato, Manuel Roveri
Summary: Tiny machine learning (TML) is a new research area focused on designing machine and deep learning techniques for embedded systems and IoT devices. This article introduces a TML for concept drift (TML-CD) solution, which utilizes deep learning feature extractors and a k-nearest neighbors (k-NNs) classifier to adapt to changes in the data-generating process. Experimental results demonstrate the effectiveness of the proposed solution.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Engineering, Biomedical
Chayashree Patgiri, Amrita Ganguly
Summary: Detection of anomalous cells in blood diseases is crucial, and automatic recognition with robust segmentation and classification methods can improve efficiency. A novel hybrid segmentation method using features extracted from cells for training and testing classifiers shows potential for high performance in classifying normal and sickle cells.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Engineering, Electrical & Electronic
Amit Kumar Gangwar, Abdul Gafoor Shaik
Summary: This paper presents a novel protection algorithm based on K-medoids clustering and weighted k-Nearest neighbor regression. K-medoids clustering is used for fault detection and classification, while weighted k-Nearest neighbor regression is used to locate the fault. The algorithm achieves fault detection, classification, and location within half a cycle, and is robust against various factors such as DG trip, islanding, and noise.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Computer Science, Information Systems
Yibang Ruan, Yanshan Xiao, Zhifeng Hao, Bo Liu
Summary: The paper introduces a nearest-neighbor search model for distance metric learning (NNS-DML), which constructs metric optimization constraints by searching different optimal nearest-neighbor numbers for each training instance. This model reduces the influence of irrelevant features on similar and dissimilar instance pairs and develops a k-free nearest-neighbor model for classification problems. Extensive experiments show that NNS-DML outperforms state-of-the-art distance metric learning methods.
INFORMATION SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Hardeep Sandhu, Rajaram Naresh Kumar, Prabha Garg
Summary: The study aims to distinguish between AChE inhibitors and non-inhibitors using machine learning models, with key features identified through descriptor analysis. The fingerprint model based on the random forest algorithm performed the best, achieving an accuracy of 85.38% on the test set.
MOLECULAR DIVERSITY
(2022)
Article
Computer Science, Information Systems
Pengcheng Zhang, Yaling Zhang, Hai Dong, Huiying Jin
Summary: Mobile edge computing is a new computing paradigm that performs computing on the edge of a network. However, due to changing edge environments, services may encounter quality issues. This article proposes a novel QoS monitoring approach ghBSRM-MEC, which can accurately monitor service quality in the mobile edge environment.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2021)
Article
Oncology
Sied Kebir, Vivien Ullrich, Pia Berger, Celia Dobersalske, Sarah Langer, Laurel Rauschenbach, Daniel Trageser, Andreas Till, Franziska K. Lorbeer, Anja Wieland, Timo Wilhelm-Buchstab, Ashar Ahmad, Holger Froehlich, Igor Cima, Shruthi Prasad, Johann Matschke, Verena Jendrossek, Marc Remke, Barbara M. Gruener, Alexander Roesch, Jens T. Siveke, Christel Herold-Mende, Tobias Blau, Kathy Keyvani, Frank K. H. van Landeghem, Torsten Pietsch, Jorg Felsberg, Guido Reifenberger, Michael Weller, Ulrich Sure, Oliver Bruestle, Matthias Simon, Martin Glas, Bjoern Scheffler
Summary: This study aimed to identify and target tumor cells that can survive, adapt, and expand under primary therapy in glioblastoma. The researchers found that ALDH1A1+/pAKT+ subclones accumulate and acquire drug resistance in response to temozolomide treatment. They propose a combination therapy of temozolomide and AKT inhibitors as a potential treatment strategy.
CLINICAL CANCER RESEARCH
(2023)
Article
Oncology
Daria Klusa, Fabian Lohaus, Andre Franken, Marian Baumbach, Monica Cojoc, Paul Dowling, Annett Linge, Anne Offermann, Steffen Loeck, Dejan Husman, Mahdi Rivandi, Bernhard Polzer, Vera Freytag, Tobias Lange, Hans Neubauer, Michael Kuecken, Sven Perner, Tobias Hoelscher, Anna Dubrovska, Mechthild Krause, Ina Kurth, Michael Baumann, Claudia Peitzsch
Summary: We investigated the circulating tumor cells (CTCs) of patients with metastatic prostate cancer, and found that the number of CTCs is associated with the time of biochemical progression after radiotherapy. Specifically, the expression of CXCR4 and CCL2 is related to cellular radiosensitivity, tumorigenicity, and stem-like potential.
INTERNATIONAL JOURNAL OF CANCER
(2023)
Review
Pharmacology & Pharmacy
Darius P. Zlotos, Thales Kronenberger, Stefan A. Laufer
Summary: Hormone-dependent cancers, such as certain types of breast cancer, can be treated with anticancer drug conjugates that combine estrogen receptor (ER) ligands with other anticancer agents. These conjugates not only have dual action at anti-cancer targets, but also selectively deliver cytotoxic agents to ER-positive tumor cells, reducing toxicity and adverse effects. They can also overcome resistance to anti-hormonal monotherapy. This review discusses the design, structures, and pharmacological effects of various drug conjugates containing ER ligands linked to diverse anticancer agents.
Article
Chemistry, Medicinal
Nadine Kruger, Thales Kronenberger, Hang Xie, Cheila Rocha, Stefan Pohlmann, Haixia Su, Yechun Xu, Stefan A. A. Laufer, Thanigaimalai Pillaiyar
Summary: The development of direct-acting antiviral drugs is necessary due to the COVID-19 pandemic caused by SARS-CoV-2. In this study, natural products were tested for their ability to inhibit the main protease M-pro of SARS-CoV-2. Some compounds were found to effectively inhibit M-pro and exhibited antiviral properties without cytotoxicity. The compound robinetin was able to form a covalent interaction with the catalytic site of M-pro.
Article
Oncology
Andre Franken, Annika Kraemer, Alicia Sicking, Meike Watolla, Mahdi Rivandi, Liwen Yang, Jens Warfsmann, Bernhard M. M. Polzer, Thomas W. P. Friedl, Franziska Meier-Stiegen, Nikolas H. H. Stoecklein, Davut Dayan, Sabine Riethdorf, Volkmar Mueller, Klaus Pantel, Andre Koch, Andreas D. D. Hartkopf, Natalia Krawczyk, Eugen Ruckhaeberle, Dieter Niederacher, Tanja Fehm, Hans Neubauer
Summary: The study found that circulating tumor cells (CTCs) with low expression of EpCAM are difficult to capture using traditional methods. In breast cancer patients, CTCs can be enriched using antibodies against Trop-2 and CD-49f, and it was discovered that EpCAM high-expressing CTCs and low-expressing CTCs have similar chromosomal aberrations and mutations, indicating a close evolutionary relationship.
BRITISH JOURNAL OF CANCER
(2023)
Article
Chemistry, Medicinal
Jean Quancard, Anna Vulpetti, Anders Bach, Brian Cox, Stephanie M. Gueret, Ingo V. Hartung, Hannes F. Koolman, Stefan Laufer, Josef Messinger, Gianluca Sbardella, Russell Craft
Summary: Hit generation is a crucial step in drug discovery that determines the speed and success rate of identifying drug candidates. Different strategies are available for identifying chemical starting points for each biological target. This article discusses the best practices for target-centric hit generation, validation of hits, and the design of integrated strategies to maximize the chance of identifying high-quality starting points.
Review
Biochemistry & Molecular Biology
Leon Katzengruber, Pascal Sander, Stefan Laufer
Summary: MKK4 is a dual-specificity protein kinase that regulates JNK and p38 MAPK signaling pathways, impacting cell proliferation, differentiation, and apoptosis. It is overexpressed in aggressive cancer types and plays a key role in liver regeneration. MKK4 is a promising target for cancer therapeutics and the treatment of liver-associated diseases. Recent progress in MKK4 drug discovery and the interest from a startup company highlight its importance in drug development.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Chemistry, Medicinal
Debora Bublitz Anton, Julia Galvez Bulhoes Pedreira, Maria Luiza Zvirtes, Stefan A. Laufer, Rodrigo Gay Ducati, Marcia Goettert, Luis Fernando Saraiva Macedo Timmers
Summary: The SARS-CoV-2 virus has caused a global pandemic, infecting over 688 million people and resulting in around 6.8 million deaths. The virus induces lung inflammation and the release of pro-inflammatory cytokines, making anti-inflammatory therapies important in addition to antiviral drugs. The main protease (MPro) of SARS-CoV-2 is a potential drug target as it is essential for viral replication. In this study, six kinase inhibitors were evaluated for their inhibitory activity against SARS-CoV-2 MPro, and BIRB-796 and Baricitinib were identified as potential inhibitors with dual antiviral and anti-inflammatory activity.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Biochemical Research Methods
Tamara Raschka, Meemansa Sood, Bruce Schultz, Aybuge Altay, Christian Ebeling, Holger Froehlich
Summary: This study proposes a novel hybrid AI approach named iVAMBN, which combines clinical and patient level gene expression data with a disease focused knowledge graph to develop a validated multi-scale model connecting molecular mechanisms with clinical outcomes in the field of Alzheimer's Disease (AD).
PLOS COMPUTATIONAL BIOLOGY
(2023)
Review
Chemistry, Medicinal
Valentin R. Wydra, Raphael B. Ditzinger, Nico J. Seidler, Frederik W. Hacker, Stefan A. Laufer
Summary: This article summarizes newly patented MAPK inhibitors from 2018 to early 2023, providing information on the patents, corresponding publications, development process, and clinical trials involving these compounds. Recently reported inhibitors show excellent selectivity and even achieve selectivity between closely related isoforms. This progress offers the possibility of eliminating unwanted side effects and may lead to the approval of the first MAPK inhibitor.
EXPERT OPINION ON THERAPEUTIC PATENTS
(2023)
Article
Biochemistry & Molecular Biology
Fatma Al-Rubaiai, Zakiya Zahran Al-Shariqi, Khalsa S. Al-Shabibi, John Husband, Asmaa M. Al-Hattali, Marcia Goettert, Stefan Laufer, Younis Baqi, Syed Imran Hassan, Majekodunmi O. Fatope
Summary: Maytenus dhofarensis Sebsebe is a shrub native to Oman that causes shivering attacks on grazed goats. Chemical investigation of its fruits and stems led to the discovery of new compounds, including a sesquiterpene pyridine alkaloid and lignanolactone. The structures and relative configurations of these compounds were determined through various analytical techniques. One of the compounds showed no inhibition activity on a kinase enzyme, while another compound exhibited strong antioxidant activity.
Article
Pharmacology & Pharmacy
Diego Valderrama, Ana Victoria Ponce-Bobadilla, Sven Mensing, Holger Froehlich, Sven Stodtmann
Summary: Recently, there has been significant growth in the use of machine learning models for pharmacokinetic (PK) modeling. This study proposes a scientific machine learning (SciML) framework for learning an unknown absorption process using neural networks, while simultaneously estimating other parameters of drug distribution. The results show that the model accurately predicts concentrations and produces reliable forecasts for new dosing regimens and patients.
CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY
(2023)
Article
Multidisciplinary Sciences
Sophia Krix, Lauren Nicole Delong, Sumit Madan, Daniel Domingo-Fernandez, Ashar Ahmad, Sheraz Gul, Andrea Zaliani, Holger Froehlich
Summary: This study proposes an integrative and explainable multimodal Graph Machine Learning approach (MultiGML) to predict drug-related adverse events and drug target-phenotype associations. MultiGML demonstrates excellent prediction performance and provides in-depth explanations of model predictions.
Article
Chemistry, Medicinal
Julian Laux, Mariella Martorelli, Simon Strass, Dieter Schollmeyer, Florian Maier, Michael Burnet, Stefan A. Laufer
Summary: This study investigated the distribution of small molecule pharmacology in blood, organs, and cells using fluorescent ligands. The results showed that the substance was mainly associated with granules or organelles, and azalide macrolides concentrated in lung and gut epithelia. These findings suggest that current estimation methods may underestimate the drug concentration in mucous membranes.
ACS PHARMACOLOGY & TRANSLATIONAL SCIENCE
(2023)
Article
Chemistry, Medicinal
Karoline B. Waitman, Larissa C. de Almeida, Marina C. Primi, Jorge A. E. G. Carlos, Claudia Ruiz, Thales Kronenberger, Stefan Laufer, Marcia Ines Goettert, Antti Poso, Sandra V. Vassiliades, Vinicius A. M. de Souza, Monica F. Z. J. Toledo, Neuza M. A. Hassimotto, Michael D. Cameron, Thomas D. Bannister, Leticia Costa-Lotufo, Joa o A. Machado-Neto, Mauricio T. Tavares, Roberto Parise-Filho
Summary: A series of hybrid inhibitors combining pharmacophores of known kinase inhibitors and benzohydroxamate HDAC inhibitors were synthesized and evaluated for their anticancer activity and pharmacokinetic properties. Compounds 4d-f exhibited promising cytotoxicity against hematological cells and moderate activity against solid tumor models. Compound 4d showed potent inhibition of multiple kinase targets and had stable interactions with HDAC and members of the JAK family. These compounds showed selective cytotoxicity with minimal effects on non-tumorigenic cells and favorable pharmacokinetic profiles.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2024)
Article
Chemistry, Analytical
Yujia Ying, Huilin Li
Summary: Enzymes play a crucial role as biological catalysts in accelerating biochemical reactions in living organisms. This study proposes a convenient method for monitoring enzymatic catalytic processes using native top-down mass spectrometry. By exploring the heterogeneity of the chymotrypsin sample and using tandem mass spectrometry, the researchers were able to monitor covalent and noncovalent enzymatic complexes, substrates, and products during catalysis. The results demonstrate that this method has the potential to be a promising tool for characterizing biocatalysts.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Kang Yang, Shuaibo Shi, Jinyu Wu, Shaolong Han, Shengdi Tai, Shishen Zhang, Kun Zhang
Summary: H2O and D2O are important analogues closely related to various industries and monitoring fields. This study successfully distinguishes and detects H2O and D2O by designing a novel eu(III)-macrocycle with dual emitters, Eu-2a, and conducting fluorescence titration experiments.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Julia Kuligowski, Alvaro Perez-Rubio, Marta Moreno-Torres, Polina Soluyanova, Judith Perez-Rojas, Ivan Rienda, David Perez-Guaita, Eugenia Pareja, Ramon Trullenque-Juan, Jose Castell, Marcha Verheijen, Florian Caiment, Ramiro Jover, Guillermo Quintas
Summary: This study introduces a novel variable selection approach called cluster PLS (c-PLS) to assess the joint impact of variable groups selected based on biological characteristics on the predictive performance of a multivariate model. The usefulness of c-PLS is shown using miRNomic and metabolomic datasets obtained from the analysis of liver tissue biopsies.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Meixue Lai, Lijie Zhong, Siyi Liu, Yitian Tang, Tingting Han, Huali Deng, Yu Bao, Yingming Ma, Wei Wang, Li Niu, Shiyu Gan
Summary: This study presents a method for constructing wearable sweat electrolyte sensors using carbon fiber-based solid-contact ion-selective electrodes (SC-ISEs). By using carbon fibers extracted from commercial cloth as electrode material, the cost and reproducibility issues of flexible SC-ISEs were addressed. The results showed that the carbon fiber-based SC-ISEs exhibited reversible voltammetric and stable impedance performances, and had high reproducibility of standard potentials between normal and bending states.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Ke Yang, Ying Liu, Min Deng, Peipei Wang, Dan Cheng, Songjiao Li, Longwei He
Summary: A near-infrared fluorescent probe has been developed to accurately measure the levels of peroxynitrite (ONOO-) in the endoplasmic reticulum (ER) in acute lung injury (ALI). The probe demonstrated rapid response, high selectivity, good sensitivity, and enhanced fluorescence intensity in response to ONOO-. It was successfully used to detect changes in ONOO- levels and showed significant increases in an ALI cell model and an ALI mouse model.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Yanping Wang, Yuemei Chen, Kejun Li, Jinrong Zhou, Xin Yuan, Mei Zhang, Ke Huang
Summary: In this work, a portable analytical system based on point discharge chemical vapor generation atomic emission spectrometry (PD-CVG-AES) coupling with gold filament enrichment was designed. The highly sensitive analysis of Hg2+ indirectly realized the detection of ascorbic acid (AA). The measurement is based on the fact that Ag+ can decrease the concentration of Hg2+ by forming Ag-Hg amalgam in the presence of the reductant SnCl2, while AA can pre-reduce Ag+ to Ag0, leading to the generation of silver nanoparticles (Ag NPs). The developed novel analytical strategy broadens the application of microplasma-based AES and offers a higher level of sensitivity compared to current AA detection techniques.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Yundi Huang, Bo Song, Kaiwen Chen, Deshu Kong, Jingli Yuan
Summary: This study developed two lysosome-targetable background-free TGL probes for efficient and accurate detection of 1O2, which can be used for monitoring endogenous 1O2 concentrations in lysosomes and discriminating variability induced by different photosensitizers. Furthermore, a smart luminescent sensor film was successfully prepared for on-site 1O2 production detection during PDT processes, offering a promising clinical monitoring tool for skin diseases.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Wei Lang, Jia-Mei Qin, Qian-Yong Cao
Summary: A novel polymer-based probe P1 was successfully synthesized for fluorescently ratiometric sensing of H2S with high selectivity and sensitivity. A smartphone sensing platform was constructed to conduct visual quantitative detection of H2S. P1 can be employed in evaluating the level fluctuations of H2S in living cells, testing water samples/wine samples, and monitoring food freshness.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Yuanyuan Qin, Shuda Liu, Shuyun Meng, Dong Liu, Tianyan You
Summary: The study developed a split aptamer-based sandwich-type ratiometric biosensor for the detection of 17 beta-estradiol (E2) using photoelectrochemical and electrochemical assays. The biosensor utilized split aptamer fragments to recognize E2 and trigger a hybridization chain reaction, resulting in the production of double-stranded DNA labeled with CdTe quantum dots. This DNA complex was able to sensitize CdTe quantum dots and generate response signals for E2 detection. The developed biosensor demonstrated high sensitivity and accuracy with two linear ranges and low detection limits.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Siriwan Teepoo, Jongjit Jantra, Khaunnapa Panapong, David Taiwo Ajayi
Summary: A novel immunochromatographic assay based on hyperbranched Au plasmonic blackbodies with a smartphone readout was developed for rapid and sensitive detection of leucomalachite green residues in fish and shrimp products.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Andrea L. Larraga-Urdaz, Borja Moreira-Alvarez, Jorge Ruiz Encinar, Jose M. Costa-Fernandez, Maria Luisa Fernandez-Sanchez
Summary: A major challenge in the 21st century is the development of point-of-care diagnostic tools. In this study, a highly sensitive and simple bioassay using AuNPs and MNAzymes was developed for rapid detection and quantification of miRNA-4739. The proposed strategy shows potential for breast cancer diagnosis.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Xiaohan Zhao, Anyu Wang, Lingzi Zhai, Jiuhe Gao, Sizhe Lyu, Yingshan Jiang, Tian Zhong, Ying Xiao, Xi Yu
Summary: A novel method using polystyrene-coated magnetic nanoparticles for extracting monohydroxy polycyclic aromatic hydrocarbons from urine samples was investigated. The proposed method is simple, sensitive, and efficient, with desirable sensitivity for analyzing low-abundance metabolites in large volumes of complex urine samples.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Ke Quan, Yuqing Zeng, Wenke Zhang, Fengfeng Li, Mengjiao Li, Zhihe Qing, Linlin Wu
Summary: In this study, a visual and reusable biosensor was developed for detecting substrates that are closely associated with human physiological health. The immobilized oxidase showed higher stability and sensitivity under harsh conditions, enabling reliable detection of substrates in complex fluids.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Dongjuan Wang, Xiuqian Ding, Jinling Xie, Juan Wang, Guanhao Li, Xin Zhou
Summary: In this study, a three-in-one sensor was developed for real-time detection of biogenic amines (BAs) with high sensitivity and selectivity. The sensor showed multimodal responses and could be used to fabricate portable devices for on-site non-destructive assessment of food spoilage indicators.
ANALYTICA CHIMICA ACTA
(2024)
Article
Chemistry, Analytical
Jinting Meng, Zihao Xu, Shasha Zheng, Hongqun Yang, Tianfu Wang, Hong Wang, Yingwei Zhang
Summary: This study demonstrates the development of a cascade signal amplification system using a multi-pedal DNA walker and strand displacement reactions for the electrochemical detection of miRNA-155. The biosensor exhibited high sensitivity, selectivity, and the potential for clinical applications.
ANALYTICA CHIMICA ACTA
(2024)
