scholarly journals Label-Free Sensing in Microdroplet-Based Microfluidic Systems

Chemosensors ◽  
2018 ◽  
Vol 6 (2) ◽  
pp. 23 ◽  
Author(s):  
Ali Kalantarifard ◽  
Abtin Saateh ◽  
Caglar Elbuken
Keyword(s):  
Sample Volume ◽  
Detection Methods ◽  
Label Free ◽  
Microfluidic Systems ◽  
Microfluidic Platforms ◽  
Detection Scheme ◽  
Detection Techniques ◽  
Detection Schemes ◽  
Targeted Approach

Droplet microfluidic systems have evolved as fluidic platforms that use much less sample volume and provide high throughput for biochemical analysis compared to conventional microfluidic devices. The variety of droplet fluidic applications triggered several detection techniques to be applied for analysis of droplets. In this review, we focus on label-free droplet detection techniques that were adapted to various droplet microfluidic platforms. We provide a classification of most commonly used droplet platform technologies. Then we discuss the examples of various label-free droplet detection schemes implemented for these platforms. While providing the research landscape for label-free droplet detection methods, we aim to highlight the strengths and shortcomings of each droplet platform so that a more targeted approach can be taken by researchers when selecting a droplet platform and a detection scheme for any given application.

scholarly journals Electrokinetic Formation of “Microbridges” for Protein Biomarkers as Sensors

2007 ◽  
Vol 12 (5) ◽  
pp. 311-317 ◽  
Author(s):  
Vindhya Kunduru ◽  
Shalini Prasad
Keyword(s):  
Electric Fields ◽  
Microelectrode Array ◽  
Protein Detection ◽  
High Specificity ◽  
Detection Methods ◽  
Label Free ◽  
Protein Biomarkers ◽  
Detection Scheme ◽  
Polystyrene Beads ◽  
Conducting Path

We demonstrate a technique to detect protein biomarkers contained in vulnerable coronary plaque using a platform-based microelectrode array (MEA). The detection scheme is based on the property of high specificity binding between antibody and antigen similar to most immunoassay techniques. Rapid clinical diagnosis can be achieved by detecting the amount of protein in blood by analyzing the protein's electrical signature. Polystyrene beads which act as transportation agents for the immobile proteins (antigen) are electrically aligned by application of homogenous electric fields. The principle of electrophoresis is used to produce calculated electrokinetic movement among the anti-C-reactive protein (CRP), or in other words antibody funtionalized polystyrene beads. The electrophoretic movement of antibody-functionalized polystyrene beads results in the formation of “Microbridges” between the two electrodes of interest which aid in the amplification of the antigen—antibody binding event. Sensitive electrical equipment is used for capturing the amplified signal from the “Microbridge” which essentially behaves as a conducting path between the two electrodes. The technique circumvents the disadvantages of conventional protein detection methods by being rapid, noninvasive, label-free, repeatable, and inexpensive. The same principle of detection can be applied for any receptor—ligand-based system because the technique is based only on the volume of the analyte of interest. Detection of the inflammatory coronary disease biomarker CRP is achieved at concentration levels spanning over the lower microgram/milliliter to higher order nanogram/milliliter ranges.

APPROACH TO DETERMINING THE VALUE OF THE DYNAMIC RANGE OF AN OPTICAL RECEIVER THAT IMPLEMENTS DIRECT AND HETERODYNE DETECTION METHODS

2020 ◽  
pp. 86-91
Author(s):  
А.Ю. Козирацкий ◽  
А.И. Гревцев ◽  
Р.И. Буров
Keyword(s):  
Dynamic Range ◽  
Direct Detection ◽  
Decisive Role ◽  
Comparative Assessment ◽  
Optical Receiver ◽  
Heterodyne Detection ◽  
Detection Methods ◽  
Detection Scheme ◽  
Value Analysis ◽  
Detection Schemes

Рассматриваются вопросы, связанные с определением возможностей использования фотодетекторов в различных схемах детектирования при приеме сигналов с изменяющейся амплитудой. Определены особенности влияния реализуемых на практике схем детектирования на величину динамического диапазона фотодетектора и потенциально достижимую чувствительность. Разработан подход, позволяющий провести сравнительную оценку изменения величины динамического диапазона в зависимости от реализуемой схемы оптического приемника. Показано, что в отличие от схемы прямого детектирования, где величина динамического диапазона напрямую определяется свойствами самого фотодетектора, при гетеродинном детектировании основную роль в определении указанной величины играет уровень опорного колебания. Анализ полученных результатов показывает, что адаптивное управление величиной опорного колебания при переходе к схеме гетеродинного детектирования с сохранением типа фотодетектора позволяет не только существенно расширить диапазон изменения амплитуды принимаемых сигналов и максимизировать величину динамического диапазона, но и реализовать потенциально достижимую чувствительность, величина которой определяется шумовыми свойствами самого фотодетектора. Конкретизация типа рассматриваемых фотодетекторов позволила ограничиться рассмотрением только теплового и дробового шумов. Определение величины динамического диапазона для других типов фотодетекторов в рамках данного подхода возможно с учетом присущих им шумовых свойств Here we consider issues related to determining the possibilities of using photodetectors in various detection schemes when receiving signals with varying amplitudes. We determined the features of the influence of practical detection schemes on the value of the dynamic range of the photodetector and the potentially achievable sensitivity. We developed an approach that allows for a comparative assessment of changes in the dynamic range depending on the implemented optical receiver scheme. We show that in contrast to the direct detection scheme, where the value of the dynamic range is directly determined by the properties of the photodetector itself, in the case of heterodyne detection, the level of the reference oscillation plays a decisive role in determining this value. Analysis of the obtained results shows that adaptive control of the reference oscillation value when switching to the heterodyne detection scheme with the preservation of the photodetector type allows us not only to significantly expand the range of changes in the amplitude of the received signals and maximize the dynamic range but also to realize a potentially achievable sensitivity, the value of which is determined by the noise properties of the photodetector itself

scholarly journals Advances in Label-Free Detections for Nanofluidic Analytical Devices

Micromachines ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 885 ◽  
Author(s):  
Thu Le ◽  
Hisashi Shimizu ◽  
Kyojiro Morikawa
Keyword(s):  
Single Molecule ◽  
Detection Methods ◽  
Label Free ◽  
Practical Applications ◽  
Detection Techniques ◽  
Kinetic Information ◽  
Label Free Detection ◽  
Nanofluidic Devices ◽  
Nanofluidic Device ◽  
New Research

Nanofluidics, a discipline of science and engineering of fluids confined to structures at the 1–1000 nm scale, has experienced significant growth over the past decade. Nanofluidics have offered fascinating platforms for chemical and biological analyses by exploiting the unique characteristics of liquids and molecules confined in nanospaces; however, the difficulty to detect molecules in extremely small spaces hampers the practical applications of nanofluidic devices. Laser-induced fluorescence microscopy with single-molecule sensitivity has been so far a major detection method in nanofluidics, but issues arising from labeling and photobleaching limit its application. Recently, numerous label-free detection methods have been developed to identify and determine the number of molecules, as well as provide chemical, conformational, and kinetic information of molecules. This review focuses on label-free detection techniques designed for nanofluidics; these techniques are divided into two groups: optical and electrical/electrochemical detection methods. In this review, we discuss on the developed nanofluidic device architectures, elucidate the mechanisms by which the utilization of nanofluidics in manipulating molecules and controlling light–matter interactions enhances the capabilities of biological and chemical analyses, and highlight new research directions in the field of detections in nanofluidics.

scholarly journals Survey on Botnet Detection Techniques: Classification, Methods, and Evaluation

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Ying Xing ◽  
Hui Shu ◽  
Hao Zhao ◽  
Dannong Li ◽  
Li Guo
Keyword(s):  
Evaluation System ◽  
Detection Methods ◽  
The Internet ◽  
Botnet Detection ◽  
Four Dimensions ◽  
Detection Techniques ◽  
And Control ◽  
The Internet Of Things ◽  
Detection Evaluation

With the continuous evolution of the Internet, as well as the development of the Internet of Things, smart terminals, cloud platforms, and social platforms, botnets showing the characteristics of platform diversification, communication concealment, and control intelligence. This survey analyzes and compares the most important efforts in the botnet detection area in recent years. It studies the mechanism characteristics of botnet architecture, life cycle, and command and control channel and provides a classification of botnet detection techniques. It focuses on the application of advanced technologies such as deep learning, complex network, swarm intelligence, moving target defense (MTD), and software-defined network (SDN) for botnet detection. From the four dimensions of service, intelligence, collaboration, and assistant, a common bot detection evaluation system (CBDES) is proposed, which defines a new global capability measurement standard. Combing with expert scores and objective weights, this survey proposes quantitative evaluation and gives a visual representation for typical detection methods. Finally, the challenges and future trends in the field of botnet detection are summarized.

scholarly journals Review of 3D cell culture with analysis in microfluidic systems

2019 ◽  
Vol 11 (33) ◽  
pp. 4220-4232 ◽  
Author(s):  
Andre D. Castiaux ◽  
Dana M. Spence ◽  
R. Scott Martin
Keyword(s):  
Cell Culture ◽  
3D Cell Culture ◽  
Research Area ◽  
Microfluidic Systems ◽  
Microfluidic Platforms ◽  
Integrated Detection ◽  
Detection Schemes

A review with 105 references that analyzes the emerging research area of 3D cell culture in microfluidic platforms with integrated detection schemes.

ARFIS: Adaptive-Receiver-Based Fuzzy Inference System for Diffusion- Based Molecular Communications

2020 ◽  
Vol 16 (2) ◽  
pp. 280-289
Author(s):  
Ghalib H. Alshammri ◽  
Walid K. M. Ahmed ◽  
Victor B. Lawrence
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Detection Threshold ◽  
Learning Rule ◽  
Optimal Number ◽  
Molecular Communication ◽  
Inference System ◽  
Detection Scheme ◽  
Adaptive Receiver ◽  
Detection Schemes

Background: The architecture and sequential learning rule-based underlying ARFIS (adaptive-receiver-based fuzzy inference system) are proposed to estimate and predict the adaptive threshold-based detection scheme for diffusion-based molecular communication (DMC). Method: The proposed system forwards an estimate of the received bits based on the current molecular cumulative concentration, which is derived using sequential training-based principle with weight and bias and an input-output mapping based on both human knowledge in the form of fuzzy IFTHEN rules. The ARFIS architecture is employed to model nonlinear molecular communication to predict the received bits over time series. Result: This procedure is suitable for binary On-OFF-Keying (Book signaling), where the receiver bio-nanomachine (Rx Bio-NM) adapts the 1/0-bit detection threshold based on all previous received molecular cumulative concentrations to alleviate the inter-symbol interference (ISI) problem and reception noise. Conclusion: Theoretical and simulation results show the improvement in diffusion-based molecular throughput and the optimal number of molecules in transmission. Furthermore, the performance evaluation in various noisy channel sources shows promising improvement in the un-coded bit error rate (BER) compared with other threshold-based detection schemes in the literature.

Label-free metabolic clustering through unsupervised pixel classification of multiparametric fluorescent images

2020 ◽  
Author(s):  
Giada Bianchetti ◽  
Fabio Ciccarone ◽  
Maria Rosa Ciriolo ◽  
Marco De Spirito ◽  
Giovambattista Pani ◽  
...  
Keyword(s):  
Label Free ◽  
Pixel Classification

scholarly journals Demonstration of a Label-Free and Low-Cost Optical Cavity-Based Biosensor Using Streptavidin and C-Reactive Protein

Biosensors ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 4
Author(s):  
Donggee Rho ◽  
Seunghyun Kim
Keyword(s):  
Limit Of Detection ◽  
Point Of Care ◽  
Low Cost ◽  
Optical Cavity ◽  
Sample Volume ◽  
Small Sample ◽  
Label Free ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Cavity Structure

An optical cavity-based biosensor (OCB) has been developed for point-of-care (POC) applications. This label-free biosensor employs low-cost components and simple fabrication processes to lower the overall cost while achieving high sensitivity using a differential detection method. To experimentally demonstrate its limit of detection (LOD), we conducted biosensing experiments with streptavidin and C-reactive protein (CRP). The optical cavity structure was optimized further for better sensitivity and easier fluid control. We utilized the polymer swelling property to fine-tune the optical cavity width, which significantly improved the success rate to produce measurable samples. Four different concentrations of streptavidin were tested in triplicate, and the LOD of the OCB was determined to be 1.35 nM. The OCB also successfully detected three different concentrations of human CRP using biotinylated CRP antibody. The LOD for CRP detection was 377 pM. All measurements were done using a small sample volume of 15 µL within 30 min. By reducing the sensing area, improving the functionalization and passivation processes, and increasing the sample volume, the LOD of the OCB are estimated to be reduced further to the femto-molar range. Overall, the demonstrated capability of the OCB in the present work shows great potential to be used as a promising POC biosensor.

Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network

2021 ◽  
Vol 137 ◽  
pp. 106861
Author(s):  
Deepa Joshi ◽  
Ankit Butola ◽  
Sheetal Raosaheb Kanade ◽  
Dilip K. Prasad ◽  
S.V. Amitha Mithra ◽  
...  
Keyword(s):  
Neural Network ◽  
Optical Coherence Tomography ◽  
Deep Neural Network ◽  
Optical Coherence ◽  
Label Free ◽  
Non Invasive ◽  
Rice Seeds

scholarly journals Indirectly Supervised Anomaly Detection of Clinically Meaningful Health Events from Smart Home Data

2021 ◽  
Vol 12 (2) ◽  
pp. 1-18
Author(s):  
Jessamyn Dahmen ◽  
Diane J. Cook
Keyword(s):  
Anomaly Detection ◽  
Time Series Data ◽  
Bayesian Optimization ◽  
Detection Methods ◽  
Series Data ◽  
Detection Techniques ◽  
Health Events ◽  
Warm Start ◽  
Health Related ◽  
Unsupervised Algorithms

Anomaly detection techniques can extract a wealth of information about unusual events. Unfortunately, these methods yield an abundance of findings that are not of interest, obscuring relevant anomalies. In this work, we improve upon traditional anomaly detection methods by introducing Isudra, an Indirectly Supervised Detector of Relevant Anomalies from time series data. Isudra employs Bayesian optimization to select time scales, features, base detector algorithms, and algorithm hyperparameters that increase true positive and decrease false positive detection. This optimization is driven by a small amount of example anomalies, driving an indirectly supervised approach to anomaly detection. Additionally, we enhance the approach by introducing a warm-start method that reduces optimization time between similar problems. We validate the feasibility of Isudra to detect clinically relevant behavior anomalies from over 2M sensor readings collected in five smart homes, reflecting 26 health events. Results indicate that indirectly supervised anomaly detection outperforms both supervised and unsupervised algorithms at detecting instances of health-related anomalies such as falls, nocturia, depression, and weakness.

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