Biosensors-Basel最新文献_第9页

Blood Pressure Estimation Through Pulse Wave Analysis Using Features Extracted from Carotid Diameter Distension Waveforms. 基于颈动脉直径扩张波形特征的脉搏波分析血压估计。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-08 DOI: 10.3390/bios16030151

Lirui Xu, Zhenhua Li, Pan Xia, Chen Zhang, Lidong Du, Wei Tian, Zhen Fang

{"title":"Blood Pressure Estimation Through Pulse Wave Analysis Using Features Extracted from Carotid Diameter Distension Waveforms.","authors":"Lirui Xu, Zhenhua Li, Pan Xia, Chen Zhang, Lidong Du, Wei Tian, Zhen Fang","doi":"10.3390/bios16030151","DOIUrl":"10.3390/bios16030151","url":null,"abstract":"Blood pressure estimation through pulse wave analysis (PWA) aims to establish the relationship between features of pulse waveforms and blood pressure. This study is the first to investigate the connection between features of carotid artery diameter waveforms and variations in blood pressure, as well as to develop a blood pressure estimation model based on these features. A dataset was constructed from 14 subjects, with data collected across various physiological states and time points. For each subject, carotid artery diameter waveforms were measured using ultrasound, while synchronous blood pressure data were recorded with a reference device. A total of 52 morphological features were extracted from the diameter waveforms and their first and second derivatives. The influence of different models and feature combinations on blood pressure estimation was analyzed using various machine learning approaches. Ultimately, optimal models were developed for each subject to dynamic blood pressure fluctuations. On independent test data where blood pressure fluctuations exceeded 25 mmHg, the mean absolute error (MAE) of the estimates was 3.3 ± 4.1 mmHg. Even after a period of two days or more, the models remained effective, yielding a MAE of 4.2 ± 5.3 mmHg.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13024020/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Minimally Invasive LC-MS/MS Approach for Assessing Endocannabinoids in Saliva and Capillary Blood Microsamples. 一种微创LC-MS/MS方法评估唾液和毛细血管血液微样本中的内源性大麻素。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-04 DOI: 10.3390/bios16030147

Jessica Hargreaves, Gabrielle Eddes, David S Nichols, Luke J Ney

{"title":"A Minimally Invasive LC-MS/MS Approach for Assessing Endocannabinoids in Saliva and Capillary Blood Microsamples.","authors":"Jessica Hargreaves, Gabrielle Eddes, David S Nichols, Luke J Ney","doi":"10.3390/bios16030147","DOIUrl":"10.3390/bios16030147","url":null,"abstract":"N-arachidonoylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG) are lipid signalling molecules within the endocannabinoid system, which regulates numerous physiological processes and is implicated in diverse pathological conditions. Given the limited feasibility of obtaining human tissue samples, quantifying AEA and 2-AG in biological matrices is essential for understanding the endocannabinoid system in humans. While many studies have used blood samples for this purpose, the collection of this matrix typically requires invasive venipuncture, which limits the scalability and practicality of endocannabinoid research. This study validated extraction and LC-MS/MS methods for quantifying AEA and 2-AG (co-quantified with its isomer 1-AG) in minimally invasive matrices, including saliva and finger-prick blood microsamples, with acceptable linearity, recovery, reproducibility, and matrix effects. The assay additionally enabled exploratory quantification of arachidonic acid, oleoylethanolamide (OEA), palmitoylethanolamide (PEA), and selected steroid hormones, supporting multiplexed assessment from a single sample. Analyte concentrations measured in blood microsamples did not directly correspond to plasma concentrations, indicating that microsampling is suited for assessing relative within-study changes rather than absolute plasma equivalence. Application of the method demonstrated that venipuncture did not significantly alter salivary AEA or 2-AG concentrations. Overall, this method provides a minimally invasive and accessible approach for investigating endocannabinoid dynamics alongside other physiological biomarkers.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear Feature-Based MI Detection Supported by DWT and EMD on ECG: A High-Performance Decision Support Approach. 基于DWT和EMD的心电非线性特征心肌梗死检测：一种高性能决策支持方法。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-04 DOI: 10.3390/bios16030150

Ali Narin, Merve Keser

{"title":"Nonlinear Feature-Based MI Detection Supported by DWT and EMD on ECG: A High-Performance Decision Support Approach.","authors":"Ali Narin, Merve Keser","doi":"10.3390/bios16030150","DOIUrl":"10.3390/bios16030150","url":null,"abstract":"Myocardial infarction (MI) is a life-threatening cardiovascular disorder caused by a partial or complete interruption of oxygenated blood flow to the myocardium, leading to high mortality rates if not diagnosed promptly. Although electrocardiogram (ECG) signals are widely used due to their non-invasive and low-cost nature, MI-specific abnormalities may be subtle and subject to inter-observer variability. Therefore, reliable artificial intelligence-based decision support systems are essential to enhance diagnostic classification accuracy. In this study, only the Lead II derivation from 12-lead ECG recordings of 52 healthy individuals and 148 MI patients was analyzed. To effectively characterize the non-stationary nature of ECG signals, a hybrid time-frequency feature extraction framework was employed. Five-level intrinsic mode functions and wavelet detail and approximation coefficients were obtained using Empirical Mode Decomposition and Discrete Wavelet Transform with a Daubechies-6 wavelet. From these components, 390 times, nonlinear and complexity-based features were extracted using 23 entropy-driven measures. Particle Swarm Optimization was applied to select the most discriminative feature subset, significantly enhancing classification performance. The optimized features were evaluated using Support Vector Machines, Artificial Neural Networks, k-Nearest Neighbors, and Bagged Tree classifiers. The Bagged Trees classifier achieved the best classification performance with an overall correct classification rate of 97.6%. The results demonstrate that the proposed hybrid feature representation combined with PSO-based selection provides a robust and reliable framework for MI detection, offering strong potential for clinical decision support applications.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023795/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electrochemical Sensor of Ciprofloxacin on Screen-Printed Electrode Modified with Boron-Doped Diamond Nanoparticles and Nickel Oxide Nanoparticles Biosynthesized Using Spatholobus littoralis Hassk. Root Extract. 掺硼金刚石纳米粒子和鸡血桃合成氧化镍纳米粒子修饰的丝网印刷电极上环丙沙星电化学传感器。根提取物。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-03 DOI: 10.3390/bios16030148

Laurencia Gabrielle Sutanto, Prastika Krisma Jiwanti, Mirza Ardella Saputra, Mai Tomisaki, Nurul Mutmainah Diah Oktaviani, Widiastuti Setyaningsih, Yasuaki Einaga, Tahta Amrillah, Ilma Amalina, Wan Jeffrey Basirun, Qonita Kurnia Anjani

{"title":"Electrochemical Sensor of Ciprofloxacin on Screen-Printed Electrode Modified with Boron-Doped Diamond Nanoparticles and Nickel Oxide Nanoparticles Biosynthesized Using Spatholobus littoralis Hassk. Root Extract.","authors":"Laurencia Gabrielle Sutanto, Prastika Krisma Jiwanti, Mirza Ardella Saputra, Mai Tomisaki, Nurul Mutmainah Diah Oktaviani, Widiastuti Setyaningsih, Yasuaki Einaga, Tahta Amrillah, Ilma Amalina, Wan Jeffrey Basirun, Qonita Kurnia Anjani","doi":"10.3390/bios16030148","DOIUrl":"10.3390/bios16030148","url":null,"abstract":"Ciprofloxacin (CIP) is an antibiotic that is widely used in humans and animals. However, the compound has been detected in animal-derived products and the environment due to its extensive use, causing serious concern for public health and environmental safety. The issue raises the urgent need to develop innovative techniques to monitor CIP. Therefore, this study aims to develop a simple and sensitive CIP sensor called the boron-doped diamond nanoparticle-modified screen-printed electrode (BDD NPs/SPE) and the nickel oxide nanoparticle-modified BDD NPs/SPE (NiO NPs/BDD NPs/SPE). NiO NPs were synthesized via green synthesis using Spatholobus littoralis Hassk. root extract as the reducing agent. The formation and characteristics of NiO NPs were then confirmed through a UV-Vis spectrophotometer, XRD, PSA, FT-IR, and XPS. The successful modification of SPE was confirmed through SEM-EDX, followed by measurements using square-wave voltammetry. The results showed that the modified SPE could detect CIP over a concentration range of 0.1-100 µM and produced a low detection limit of 0.109 µM for BDD NPs/SPE and 0.054 µM for NiO NPs/BDD NPs/SPE. The proposed method was successfully applied to the determination of CIP in commercial tablets, milk, and human urine, with a satisfactory % recovery from 95 to 100%. The current study successfully developed a simple yet highly sensitive sensor that enabled robust, reliable, and efficient detection of CIP, showing its strong potential for practical applications.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensitive Detection of DJ-1 in Artificial Cerebrospinal Fluid Using a Portable GPTMS-Coordinated Gold Nanoparticle-Based Biosensor. 便携式gptms -协同金纳米颗粒生物传感器对人工脑脊液中DJ-1的灵敏检测

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-03 DOI: 10.3390/bios16030146

Münteha Nur Sonuç Karaboğa

{"title":"Sensitive Detection of DJ-1 in Artificial Cerebrospinal Fluid Using a Portable GPTMS-Coordinated Gold Nanoparticle-Based Biosensor.","authors":"Münteha Nur Sonuç Karaboğa","doi":"10.3390/bios16030146","DOIUrl":"10.3390/bios16030146","url":null,"abstract":"A highly selective and sensitive compact immunosensing strategy was developed for the determination of DJ-1, a potential biomarker of Parkinson's disease, one of the leading neurodegenerative disorders, using a portable potentiostat. Initially, screen-printed carbon electrodes (SPCEs) were modified with gold nanoparticles (AuNPs), followed by functionalization with 4-mercapto-1-butanol (MOH). Subsequently, the AuNPs-doped and hydroxyl-functionalized electrodes were treated with 3-glycidoxypropyltrimethoxysilane (GPTMS) to facilitate immobilization of anti-DJ-1 antibodies. Immobilization steps were monitored using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) performed on a bench potentiostat, while the entire analytical performance of the developed biosensor system and its response in artificial cerebrospinal fluid (aCSF) were evaluated by monitoring cathodic current changes with a portable electrochemical reader. The resulting biorecognition element enabled the detection of DJ-1 within the concentration range of 0.001 to 0.3 ng/mL, based on cathodic current changes, achieving a limit of detection as low as 0.00059 ng/mL. Surface morphology and elemental composition alterations were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDX). A notable advantage of this GPTMS@AuNPs-based biosensor system is its prolonged storage stability and its capability to accurately quantify DJ-1 in artificial cerebrospinal fluid samples, with recovery rates ranging from 98.66% to 123.3%.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023608/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Imprinted Proteins as a Receptor in Fluorescent Sensing Microplate Assay for Herbicide Determination. 印迹蛋白受体在除草剂荧光检测中的应用。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-03 DOI: 10.3390/bios16030149

Kirill Y Presnyakov, Ivan S Matlakhov, Ivan A Reshetnik, Polina M Ilicheva, Daria V Tsyupka, Daria G Koganova, Svetlana A Mescheryakova, Tatyana Y Rusanova, Mikhail V Pozharov, Daniil D Drozd, Pavel S Pidenko, Irina Y Goryacheva, Natalia A Burmistrova

{"title":"Imprinted Proteins as a Receptor in Fluorescent Sensing Microplate Assay for Herbicide Determination.","authors":"Kirill Y Presnyakov, Ivan S Matlakhov, Ivan A Reshetnik, Polina M Ilicheva, Daria V Tsyupka, Daria G Koganova, Svetlana A Mescheryakova, Tatyana Y Rusanova, Mikhail V Pozharov, Daniil D Drozd, Pavel S Pidenko, Irina Y Goryacheva, Natalia A Burmistrova","doi":"10.3390/bios16030149","DOIUrl":"10.3390/bios16030149","url":null,"abstract":"The manuscript describes an optical sensing microplate for the high-throughput screening of imidazolinone herbicides in soil extracts. As far as we know, imprinted proteins (IPs) specific to imidazolinone herbicides have not been synthesized and used as a recognition element for their solid-phase extraction before. Imprinted bovine serum albumin (BSA) and glucose oxidase (GOx) were synthesized in the presence of imazamox as a template and then these IPs were immobilized at the bottom of microplate wells. The sorption capacity (Q) of aminated silica nanoparticles modified by IPs (IP-BIS) was 6.38 mg g-1 while the imprinting factor (IF) equaled 2.6. The concentration of imazamox was determined by a \"turn-off\" solid-phase assay using alloyed CdZnSeS/ZnS quantum dots (QDs) as a component of fluorescent substrate. Alloyed CdZnSeS/ZnS QDs were stabilized in an aqueous phase by positively charged cysteamine that, as far we know, had not been used as this type of ligand before. Our method allows for determining the concentration of imazamox in the range of 0.5-9.2 μg mL-1, with a limit of quantification limit of quantitation (LOQ) equal to 0.45 μg mL-1 The sensing microplate enables parallel detection of up to 96 samples containing herbicides using standard fluorescence microplate readers or smartphones. The paper describes how such sensing microplates can be used for the analysis of artificially contaminated soil samples. The proposed approach combines pre-concentration of analyte at the IPs with its subsequent determination on a single analytical platform, thus allowing for both highly sensitive determination in laboratory conditions and mass screening in the field.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13024476/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Emotion Recognition Using Multi-View EEG-fNIRS and Cross-Attention Feature Fusion. 基于多视角EEG-fNIRS和交叉注意特征融合的情绪识别。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-02 DOI: 10.3390/bios16030145

Ni Yan, Guijun Chen, Xueying Zhang

{"title":"Emotion Recognition Using Multi-View EEG-fNIRS and Cross-Attention Feature Fusion.","authors":"Ni Yan, Guijun Chen, Xueying Zhang","doi":"10.3390/bios16030145","DOIUrl":"10.3390/bios16030145","url":null,"abstract":"To improve the accuracy of emotion recognition, this paper proposes a multi-view EEG-fNIRS and cross-attention fusion module named FGCN-TCNN-CAF, which employs a differentiated modeling strategy for the frequency, spatial, and temporal features of EEG-fNIRS signals. First, frequency-domain and time-domain features are extracted from EEG, and time-domain features are obtained from fNIRS signals. Then, a frequency-domain graph convolutional network (FGCN) and a time-domain convolutional network (TCNN) are deployed in parallel. The EEG feature views from different frequency bands are modeled using an FGCN module to capture graph-structured relationships, while the time-domain views of EEG and fNIRS are processed by a TCNN module to extract spatial and temporal features. Finally, a cross-attention fusion network (CAF) is applied to achieve interactive fusion of multimodal features. Experiments demonstrate that the proposed multi-view EEG approach achieves higher recognition accuracy compared to using only the EEG view. Additionally, the mmultimodalrecognition results outperform single-modal EEG and single-modal fNIRS by 1.73% and 6.65%, respectively. When compared with other emotion recognition models, the proposed method achieves the highest accuracy of 96.09%, proving its superior performance.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning-Enhanced MEC Sensors with Feature Engineering for Quantitative Analysis of Multi-Component Toxicants. 基于特征工程的机器学习增强MEC传感器用于多组分毒物定量分析。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-02 DOI: 10.3390/bios16030144

Jiaguo Yan, Renxin Liang, Wenqing Yan, Xin Wang

{"title":"Machine Learning-Enhanced MEC Sensors with Feature Engineering for Quantitative Analysis of Multi-Component Toxicants.","authors":"Jiaguo Yan, Renxin Liang, Wenqing Yan, Xin Wang","doi":"10.3390/bios16030144","DOIUrl":"10.3390/bios16030144","url":null,"abstract":"Accelerated industrialization has caused complex mixed toxicant pollution, where synergistic or antagonistic interactions render conventional detection methods inadequate. Herein, we develop an integrated framework by pioneering the integration of microbial electrochemical systems (MECs) with machine learning (ML) for quantifying formaldehyde, tetracycline, Ag+, and Cu2+ in multi-component, multi-ratio, and multi-concentration mixtures. MECs generated dynamic current-time (I-t) signals responsive to toxicant stress, though signal overlap from mixed toxicants hindered direct quantification. Guided by toxicokinetics and electrochemical mechanisms, we developed a novel mechanism-driven feature engineering strategy with exclusively original indicators, which extracted 22 multidimensional features capturing instantaneous characteristics, kinetic patterns, and microbial stress-adaptive responses to resolve signal ambiguity, and provided biologically meaningful, high-information feature inputs that effectively bridge electrochemical response signals and ML modeling. Comparative analysis of four ML models (SVM, KNN, PLS, and RF) showed RF outperformed others, achieving R2 > 0.9 for all toxicants (formaldehyde: 0.959; tetracycline: 0.934; Ag+: 0.936; Cu2+: 0.957) with minimized MAE and RMSE. Microbial community analysis identified Geobacter anodireducens (71.5%, electroactive for heavy metals) and Comamonas testosteroni (12.9%, organic degrader) as key functional taxa, supported by KEGG enzyme abundance data. This work overcomes traditional MEC limitations via innovative feature engineering and pioneering ML integration, providing a rapid, low-cost, and high-accuracy tool for environmental mixed toxicant monitoring.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023910/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Liquid-Gated Field-Effect Transistor-Based Biosensor for Uric Acid Detection. 基于液体门控场效应晶体管的尿酸检测生物传感器。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-01 DOI: 10.3390/bios16030142

Rafiq Ahmad, Abdullah, Altaf Khan, Fohad Mabood Husain, Byeong-Il Lee

{"title":"Liquid-Gated Field-Effect Transistor-Based Biosensor for Uric Acid Detection.","authors":"Rafiq Ahmad, Abdullah, Altaf Khan, Fohad Mabood Husain, Byeong-Il Lee","doi":"10.3390/bios16030142","DOIUrl":"10.3390/bios16030142","url":null,"abstract":"Monitoring uric acid (UA) concentration is crucial for human health, enabling early detection and prevention of metabolic disorders as well as assessing renal function and overall metabolic balance. Herein, we developed a field-effect transistor (FET)-based UA biosensor using hydrothermally synthesized vertical zinc oxide (ZnO) nanorods (NRs) and uricase. The fabricated FET biosensor was tested in phosphate-buffered saline (PBS) at increasing UA concentrations to evaluate its biosensing performance. The FET biosensor yields a sensitivity of 12.45 μA·mM-1·cm-2, covering a dynamic range of 0.05-2.75 mM. The calculated detection limit was ~0.0043 mM. The improved sensing performance results in a substantial enhancement of both detection sensitivity and limit of detection compared to the traditional lateral electrode setup. Additionally, selectivity, storage stability, fabrication reproducibility, and applicability for serum UA detection were evaluated. Overall, the vertical electrode configuration of the UA biosensor has the potential to be further extended for the sensitive detection of additional biomarkers.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13023612/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Highly Sensitive Zinc Oxide Nanorods for Non-Enzyme Electrochemical Detection of Ascorbic and Uric Acids. 用于抗坏血酸和尿酸非酶电化学检测的高灵敏度氧化锌纳米棒。

IF 5.6 3区工程技术

Biosensors-Basel Pub Date : 2026-03-01 DOI: 10.3390/bios16030143

Lesya V Gritsenko, Zhaniya U Paltusheva, Dinara T Tastaibek, Khabibulla A Abdullin, Zhanar K Kalkozova, Maratbek T Gabdullin, Juqin Zeng

{"title":"Highly Sensitive Zinc Oxide Nanorods for Non-Enzyme Electrochemical Detection of Ascorbic and Uric Acids.","authors":"Lesya V Gritsenko, Zhaniya U Paltusheva, Dinara T Tastaibek, Khabibulla A Abdullin, Zhanar K Kalkozova, Maratbek T Gabdullin, Juqin Zeng","doi":"10.3390/bios16030143","DOIUrl":"10.3390/bios16030143","url":null,"abstract":"In this study, an enzyme-free electrochemical sensor based on zinc oxide (ZnO) nanorods synthesized by the thermal decomposition of zinc acetate is presented. The suggested approach ensures simplicity, environmental friendliness, and scalability of the process without the use of an autoclave or high pressure. The morphology and structure of the samples are studied using SEM, TEM, XRD, Raman, FTIR, XPS, PL, and UV-Vis spectroscopy. It is found that heat treatment at 450 °C increases the degree of crystallinity, increases the size of crystallites, and reduces the concentration of surface defects, which leads to improved optical and electrochemical characteristics of the material. Beyond conventional sensitivity metrics, our study demonstrates that the selective detection of ascorbic acid (AA) and uric acid (UA) can be achieved by controlling the applied potential on a single ZnO electrode, an approach that leverages differences in redox energetics and surface interaction dynamics rather than complex surface functionalization. It is shown in this work that the synthesized ZnO samples subjected to heat treatment in air at 450 °C exhibit high sensitivity to ascorbic acid (9951.87 μA·mM-1·cm-2; LoD = 1.11 μM) at a potential of 0.2 V and to uric acid (5762.48 μA·mM-1·cm-2; LoD = 1.71 μM) in a phosphate buffer solution (pH 7) at a potential of 0.4 V with a linear range of 3 mM, offering a way to create simplified multicomponent electrochemical biosensors based on potential-controlled selectivity.","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"16 3","pages":""},"PeriodicalIF":5.6,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13024462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147533748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0