薄膜基荧光气体传感器

薄膜基荧光传感因灵敏度高、可采集信号丰富、实时检测性好和易于器件化等优点备受人们关注,特别是随着微纳米加工、集成制造和物联网技术的发展应用,薄膜基荧光传感器研究已经成为传感器研究的一个重要领域,呈现出广阔的发展前景。 结合课题组工作,本文简要讨论了基于小分子化合物的薄膜基荧光气体传感器在隐藏爆炸物、毒品、挥发性有机污染物检测/监测,重大疾病早期诊断等领域的应用探索。 在此基础上,指出了薄膜基荧光传感器发展面临的问题,评述了薄膜基荧光传感器研究和应用的前景。     

纳米光学传感器用于检测汞离子

汞离子是毒性最大的重金属之一,对环境和人体都会造成严重的不良影响,开发能够快速检测环境中汞离子的分析方法引起了越来越多的关注。纳米材料由于其优良的光学性能和良好的稳定性,被广泛用于环境中汞离子的检测。本文主要综述了近年来一些代表性的基于纳米材料的汞离子荧光、比色传感器。根据纳米材料的不同,将这些传感器分为基于金、银、碳和硅基材料,以及量子点、有机纳米颗粒和其他纳米基材料的荧光、比色传感器,并分别从设计原理、识别性能和实际应用等方面对这些传感器进行了描述和讨论。最后对该领域的研究和发展提出了展望。     

硅基纳米探针用于眼部疾病的成像检测与治疗

快速精准的诊断和高效的治疗对于减轻眼部疾病造成的危害至关重要. 在过去的几十年里, 由于具有尺寸小、 比表面积大、 表面易修饰及独特的光/电子/机械性能等优点, 纳米材料已被用于构建不同种类的高性能纳米探针. 其中, 基于其良好的生物相容性, 科学家们已经将硅纳米材料设计为可用于不同眼部疾病诊断与治疗的功能化纳米探针. 本综述主要概述了将硅基纳米探针用于检测和治疗不同眼部疾病(如角膜疾病、 视网膜疾病、 青光眼等)的近期研究进展. 首先, 重点介绍了硅基纳米探针的设计制备及在角膜新生血管、 细菌性角膜炎等角膜疾病的成像检测与治疗中的应用; 然后, 介绍了用于成像检测和治疗视网膜疾病(如色素性视网膜炎和视网膜新生血管)的硅基持续性给药系统的研究成果; 随后, 概述了多功能硅基纳米载药系统的构建及在青光眼治疗领域的应用研究进展; 最后, 简要讨论了将硅基纳米探针用于眼部疾病诊治面临的挑战并对未来的发展前景进行了展望.     

无酶葡萄糖传感器

葡萄糖传感器在几十年的发展中取得了重大进展,经历了三代基于酶葡萄糖传感器之后,现已进入第四代无酶葡萄糖传感器的发展阶段.本文从基于酶和无酶两类介绍了不同葡萄糖传感器的测试原理,综述了近年来纳米材料在无酶电化学葡萄糖传感器方面应用的主要研究进展,对不同类别纳米材料的制备方法以及所构建传感器的灵敏度、选择性、检测范围和稳定性等进行了评述,分析了制约无酶葡萄糖传感器商业化应用的主要原因.其中,贵金属纳米材料主要讨论了铂、金和钯;过渡金属纳米材料主要讨论了镍、铜以及其氧化物;双金属纳米材料主要讨论了合金和复合物;碳纳米材料主要讨论了单壁(多壁)碳纳米管和石墨烯.此外,本文也对无酶葡萄糖传感器的发展方向和趋势进行了展望.     

电化学葡萄糖传感器

作为电化学生物传感器中最重要的研究内容之一,葡萄糖生物传感器在数十年的发展中取得了巨大进展。本文综述了近年来利用纳米技术设计的新型电化学葡萄糖传感器的主要研究进展,并从纳米材料维度分类进行了讨论。其中,零维纳米材料主要讨论了包括金纳米颗粒、银纳米颗粒以及铜、铂等金属纳米颗粒材料; 一维纳米材料主要讨论了通过模板法制备的金属或金属氧化物纳米线以及单臂或者多壁纳米管材料; 二维纳米材料主要总结了以碳为基础的石墨烯材料和一些片状的金属材料。纳米材料对电化学葡萄糖传感器的影响主要集中在生物相容性、增强检测灵敏度、酶的固定等方面。此外,本文也对电化学葡萄糖传感器的今后发展做了展望。     

表面等离子体共振传感器在癌症早期诊断中的应用

表面等离子体共振传感器作为一种新型光学传感器, 在疾病诊断领域展现出日益广泛的应用性. 借助于纳米材料研究的最新进展, 该传感技术可实现浓度极低生物标记物的有效检测. 我们针对表面等离子体传感器在癌症早期诊断中的应用, 介绍了最新研究进展、重要发现及未来的发展前景.     

基于功能性纳米材料的新型电化学界面的构筑以及相关应用(英文)

由于独特的光、电、磁以及催化性质,功能性纳米材料的研究已经渗透到各个学科并在不同领域展示出潜在的应用前景,尤其是利用纳米材料构建功能性电极界面、研究其电化学行为并发展新颖的电化学纳米器件引起了了人们的广泛关注. 本篇综述中,主要介绍作者研究小组在以功能性纳米材料构建新颖的电化学界面的最新进展,集中关注其在电化学传感器、燃料电池以及光谱电化学中的应用. 这些纳米材料的应用极大地增强了电子转移、提高了电化学传感器的灵敏度以及燃料电池的催化效率. 作者也通过合成一些光谱匹配的荧光以及电致变色纳米材料构建新颖的荧光光谱电化学器件,同时在材料的合成组装、多重刺激响应体系以及多功能化进行探索. 最后,作者对这类基于纳米材料的电化学器件的发展和应用予以展望.     

纳米材料电化学与生物传感器——有机微污染物检测新途径

本文介绍了近年来纳米材料电化学与生物传感器在有机微污染物检测中的研究现状,分析了这些传感器中纳米材料修饰电极的特点,重点阐述了纳米材料在有机微污染物检测中的重要作用,列举了一些纳米材料电化学与生物传感器在有机微污染物检测中的应用。最后对纳米材料电化学与生物传感器用于有机微污染物的检测研究进行了简要评述和展望。     

基于纳米材料电化学生物传感器的研究进展

近年来,纳米材料在电化学生物传感器领域的研究已成为前沿性的内容.纳米材料具备优异的物理、化学、电催化等性能,加之其量子尺寸效应和表面效应,可将传感器的性能提高到一个新的水平.基于纳米材料的电化学生物传感器呈现出体积更小、速度更快、检测灵敏度更高和可靠性更好等优异性能.该文按照纳米结构的分类,综述了近几年基于以下纳米材料...     

基于纸基的荧光碳量子点传感器的可视化检测研究进展

碳量子点作为一种新型的纳米材料,其独特的荧光性能使其在物质检测领域得到了越来越多的关注。利用碳量子点与物质反应导致荧光强度发生变化的特性,可将其应用于可视化检测,检测方法分为荧光猝灭型和荧光恢复型。基于纸基的荧光传感器与基于液相反应的荧光检测相比,其快速、现场和可视化的特点更加突出,因此有着更为广泛的应用。本文针对碳量子点的荧光特性、可视化荧光检测、纸基传感器的研究现状,并结合本课题组相关研究进展进行论述,以期为今后纸基碳量子点荧光传感器的研究和应用提供参考。     

人体呼出气中挥发性有机化合物的检测方法

呼出气检测作为一种潜在的新型临床检测手段受到广泛关注。本文详细综述了人体呼出气中挥发性有机化合物(VOCs)的各类检测方法和技术,分别对色谱法、质谱法和光谱及传感器法的原理、特点和最新研究进展进行了介绍,对照总结了目前已确定的异戊二烯、丙酮等疾病生物标志物的各种分析方法和实测数据,并展望了未来的研究动向。     

Breath biosensing: using electrochemical enzymatic sensors for detection of biomarkers in human breath

Detection of biomarkers for disease by noninvasive methods is critical for the early diagnosis and screening of disease, enabling prompt treatment. Breath biosensors are a viable option as the exhaled breath contains several biomarkers linked to lung cancer, oxidative stress, diabetes, and other diseases. Breath analysis has been achieved by advanced analytical techniques such as gas chromatography and infrared spectroscopy. However, electrochemical enzymatic breath biosensors offer a cost-effective, sensitive platform for biomarker detection without complex analysis and interpretation by trained laboratory personnel. This review aims to summarize recent advances in the field of electrochemical enzymatic breath biosensors and offer future opportunities from other applications of nonelectrochemical enzymatic breath biosensors.     

Recent advances in breath analysis to track human health by new enrichment technologies

Detection of biomarkers in exhaled breath has been gaining increasing attention as a tool for diagnosis of specific diseases. However, rapid and accurate quantification of biomarkers associated with specific diseases requires the use of analytical methods capable of fast sampling and preconcentration from breath matrix. In this regard, solid phase microextraction and needle trap technology are becoming increasingly popular in the field of breath analysis due to the unique benefits imparted by such methods, such as the integration of sampling, extraction, and preconcentration in a single step. This review discusses recent advances in breath analysis using these sample preparation techniques, providing a summary of recent developments of analytical methods based on breath volatile organic compounds analysis, including the successful identification of various biomarkers related to human diseases.     

Volatile Organic Compounds Analysis in Breath Air in Healthy Volunteers and Patients Suffering Epidermoid Laryngeal Carcinomas

Exhaled breath contains thousands of gaseous volatile organic compounds (VOCs) that may be used as non-invasive markers of head and neck epidermoid cancer. We hypothesized that solid phase micro-extraction coupled to gas chromatography–mass spectrometry can discriminate patients with epidermoid head and neck cancer from healthy controls by analyzing the gaseous volatile organic compounds, VOC-profile, in exhaled breath, thus identifying some non-invasive biomarkers to be used in early detection. Twenty healthy subjects participated in a cross-sectional study plus 11 patients with epidermoid supraglottic laryngeal cancer. VOCs from T3 supraglottic cancer were clustered distinctly from those of T1 and healthy subjects. Up to seven VOCs were detected differently from healthy volunteers, mainly 2-butanone and ethanol. Thus VOC-patterns of exhaled breath may discriminate patients with epidermoid head and neck cancer from healthy controls.     

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Cigarette smoking harms nearly every organ of the body and causes many diseases. The analysis of exhaled breath for exogenous and endogenous volatile organic compounds (VOCs) can provide fundamental information on active smoking and insight into the health damage that smoke is creating. Various exhaled VOCs have been reported as typical of smoking habit and recent tobacco consumption, but to date, no eligible biomarkers have been identified. Aiming to identify such potential biomarkers, in this pilot study we analyzed the chemical patterns of exhaled breath from 26 volunteers divided into groups of nonsmokers and subgroups of smokers sampled at different periods of withdrawal from smoking. Solid‐phase microextraction technique and gas chromatography/mass spectrometry methods were applied. Many breath VOCs were identified and quantified in very low concentrations (ppbv range), but only a few (toluene, pyridine, pyrrole, benzene, 2‐butanone, 2‐pentanone and 1‐methyldecyclamine) were found to be statistically significant variables by Mann–Whitney test. In our analysis, we did not consider the predictive power of individual VOCs, as well as the criterion of uniqueness for biomarkers suggests, but we used the patterns of the only statistically significant compounds. Probit prediction model based on statistical relevant VOCs‐patterns showed that assessment of smoking status is heavily time dependent. In a two‐class classifier model, it is possible to predict with high specificity and sensitivity if a subject is a smoker who respected 1 hour of abstinence from smoking (short‐term exposure to tobacco) or a smoker (labelled "blank smoker") after a night out of smoking (long‐term exposure to tobacco). On the other side, in our study "blank smokers" are more like non‐smokers so that the two classes cannot be well distinguished and the corresponding prediction results showed a good sensitivity but low selectivity.     

Human exhaled air analytics: biomarkers of diseases

Over the last few years, breath analysis for the routine monitoring of metabolic disorders has attracted a considerable amount of scientific interest, especially since breath sampling is a non-invasive technique, totally painless and agreeable to patients. The investigation of human breath samples with various analytical methods has shown a correlation between the concentration patterns of volatile organic compounds (VOCs) and the occurrence of certain diseases. It has been demonstrated that modern analytical instruments allow the determination of many compounds found in human breath both in normal and anomalous concentrations. The composition of exhaled breath in patients with, for example, lung cancer, inflammatory lung disease, hepatic or renal dysfunction and diabetes contains valuable information. Furthermore, the detection and quantification of oxidative stress, and its monitoring during surgery based on composition of exhaled breath, have made considerable progress. This paper gives an overview of the analytical techniques used for sample collection, preconcentration and analysis of human breath composition. The diagnostic potential of different disease-marking substances in human breath for a selection of diseases and the clinical applications of breath analysis are discussed.     

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.     

Statistical and bioinformatical methods to differentiate chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control by breath analysis using ion mobility spectrometry

Human breath analysis is a powerful and especially a non-invasive technique for the monitoring and hopefully also for the diagnosis of respiratory diseases, including chronic obstructive pulmonary disease (COPD). The exhaled breath of 95 patients suffering COPD and of 35 healthy controls was investigated using an Ion Mobility Spectrometer (IMS) coupled to a Multi-Capillary Column (MCC) without any pre-separation or pre-enrichment. Starting with the results from a Mann–Whitney-Wilcoxon rank sum test to find analytes with the highest potential with respect to differentiation, box and whisker plots, metabolic maps and probability charts were introduced and compared. In addition, the sensitivity, specificity, positive and negative predictive values and the accuracy of the relation were also summarized. The findings were compared to the results of a principal component analysis. Finally, decision trees were introduced to visualize the interdependencies between the analytes and the classifications. The application of these biostatistical methods with simultaneous inclusion of several VOCs for disease classification by ion mobility spectrometry of human breath will provide much more information than using single peaks and single concentration dependencies for disease classification and discrimination of various groups. Towards the future application of potential biomarkers for clinical diagnostic procedures, complex analytical methods, such as ion mobility spectrometry, need statistical and bioinformatical tools which are simple in application, visualize the results and support decisions on the basis of the data obtained from measurements of analytes in exhaled human breath.     

Noninvasive detection of colorectal cancer by analysis of exhaled breath

There has been growing interest in exhaled breath analysis for cancer screening and disease monitoring; however, limited breath biomarker information exists regarding colorectal cancer (CRC). The objective of this study was to screen for breath biomarkers of CRC. Exhaled breath was collected from 20 CRC patients and 20 healthy controls; subsequently, solid-phase microextraction–gas chromatography/mass spectrometry (SPME-GC/MS) was used to assess the exhaled volatile organic compounds (VOCs) of the study participants. The statistical methods of principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to process the final data. The VOCs in the exhalations of CRC patients exhibited significant differences from the VOCs in the exhalations of healthy controls; in particular, relative to the latter exhalations, the former exhalations contain significantly higher levels of cyclohexanone, 2,2-dimethyldecane, dodecane, 4-ethyl-1-octyn-3-ol, ethylaniline, cyclooctylmethanol, trans-2-dodecen-1-ol, and 3-hydroxy-2,4,4-trimethylpentyl 2-methylpropanoate but significantly lower levels of 6-t-butyl-2,2,9,9-tetramethyl-3,5-decadien-7-yne (P?<?0.05). Analyses of breath VOCs provide a related model of CRC exhalation that could represent an effective and convenient screening method for this disease.

Modular Breath Analyzer (MBA): Introduction of a Breath Analyzer Platform Based on an Innovative and Unique,Modular eNose Concept for Breath Diagnostics and Utilization of Calibration Transfer Methods in Breath Analysis Studies

Exhaled breath analysis for early disease detection may provide a convenient method for painless and non-invasive diagnosis. In this work, a novel, compact and easy-to-use breath analyzer platform with a modular sensing chamber and direct breath sampling unit is presented. The developed analyzer system comprises a compact, low volume, temperature-controlled sensing chamber in three modules that can host any type of resistive gas sensor arrays. Furthermore, in this study three modular breath analyzers are explicitly tested for reproducibility in a real-life breath analysis experiment with several calibration transfer (CT) techniques using transfer samples from the experiment. The experiment consists of classifying breath samples from 15 subjects before and after eating a specific meal using three instruments. We investigate the possibility to transfer calibration models across instruments using transfer samples from the experiment under study, since representative samples of human breath at some conditions are difficult to simulate in a laboratory. For example, exhaled breath from subjects suffering from a disease for which the biomarkers are mostly unknown. Results show that many transfer samples of all the classes under study (in our case meal/no meal) are needed, although some CT methods present reasonably good results with only one class.