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Novel Sensors for Bioimaging

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (30 May 2018) | Viewed by 68492

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Special Issue Editors

Dr. Steven Ripp

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Guest Editor

Center for Environmental Biotechnology, University of Tennessee, Knoxville, Knoxville, TN, USA
Interests: pre-clinical in vivo imaging; in vitro diagnostics; bioluminescent imaging; bioluminescent reporters; biosensors; bioassays

Dr. Dan Close

E-Mail Website
Guest Editor

490 BioTech Inc., Knoxville, TN, USA
Interests: optical imaging; metabolic activity tracking; toxicology; high throughput screening; bioluminescent imaging; cancer imaging; synthetic biology

Special Issue Information

Dear Colleagues,

Bioimaging refers to a toolset of techniques that enables the minimally or non-invasive imaging of biological processes directly from within living subjects or in isolated cells, tissue, organs, or other biological structures. The field has a strong medical focus, where bioimaging data is applied toward disease diagnostics, therapeutic monitoring, theranostics, cell tracking, the probing of biochemical interactions, the quantification of metabolites, and the measurement of interactions occurring at levels from the subcellular to the organismal. A wide variety of instrumentation is used to achieve bioimaging endpoints, including NMR, PET, SPECT, MRI, CT, in vivo fluorescent/bioluminescent, microscopy-based, lab-on-chip-based, and various other derivatives of these instrument and technological classes.

We invite manuscripts for this forthcoming Special Issue among all aspects of sensor and biosensor applications within the bioimaging fields. Both reviews and original research articles are welcome. Review articles should provide topical overviews of novel sensor/biosensor bioimaging applications or technologies that are not covered in the current literature. Research articles should illustrate state-of-the-art sensor/biosensor techniques that integrate with bioimaging applications to facilitate novel and enriched imaging under clinical and/or pre-clinical investigational endpoints. A small sampling of technologies of interest would include bioimaging applications that focus on aptamers, nanomaterials, quantum dots, polymers, optical, fluorescent, and bioluminescent sensors, and lab-on-chip sensors. Reviews or original research relating to the development of supporting imaging technologies, such as engineered fluorescent and bioluminescent proteins, fluorescent nanodiamonds, or improved excitation or signal detection equipment, are also welcome.

Dr. Steven Ripp
Dr. Dan Close
Guest Editors

Manuscript Submission Information

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Keywords

Bioimaging
Sensors
Biosensors
In vivo
In vitro
Nanomaterial
Clinical
Pre-clinical

Published Papers (12 papers)

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Research

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15 pages, 3083 KiB

Open AccessArticle

Theoretical Design of a Two-Photon Fluorescent Probe for Nitric Oxide with Enhanced Emission Induced by Photoninduced Electron Transfer

by Yujin Zhang, Jiancai Leng and Wei Hu

Sensors 2018, 18(5), 1324; https://doi.org/10.3390/s18051324 - 25 Apr 2018

Cited by 15 | Viewed by 4513

Abstract

In the present work, we systematically investigate the sensing abilities of two recently literature-reported two-photon fluorescent NO probes, i.e., the o-phenylenediamine derivative of Nile Red and the p-phenylenediamine derivative of coumarin. The recognition mechanisms of these probes are studied by using the molecular orbital classifying method, which demonstrates the photoinduced electron transfer process. In addition, we have designed two new probes by swapping receptor units present on fluorophores, i.e., the p-phenylenediamine derivative of Nile Red and the o-phenylenediamine derivative of coumarin. However, it illustrates that only the latter has ability to function as off-on typed fluorescent probe for NO. More importantly, calculations on the two-photon absorption properties of the probes demonstrate that both receptor derivatives of coumarin possess larger TPA cross-sections than Nile Red derivatives, which makes a better two photon fluorescent probe. Our theoretical investigations reveal that the underlying mechanism satisfactorily explain the experimental results, providing a theoretical basis on the structure-property relationships which is beneficial to developing new two-photon fluorescent probes for NO. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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13 pages, 11669 KiB

Open AccessArticle

Effects of Cable Sway, Electrode Surface Area, and Electrode Mass on Electroencephalography Signal Quality during Motion

by Evangelia-Regkina Symeonidou, Andrew D. Nordin, W. David Hairston and Daniel P. Ferris

Sensors 2018, 18(4), 1073; https://doi.org/10.3390/s18041073 - 03 Apr 2018

Cited by 70 | Viewed by 8850

Abstract

More neuroscience researchers are using scalp electroencephalography (EEG) to measure electrocortical dynamics during human locomotion and other types of movement. Motion artifacts corrupt the EEG and mask underlying neural signals of interest. The cause of motion artifacts in EEG is often attributed to electrode motion relative to the skin, but few studies have examined EEG signals under head motion. In the current study, we tested how motion artifacts are affected by the overall mass and surface area of commercially available electrodes, as well as how cable sway contributes to motion artifacts. To provide a ground-truth signal, we used a gelatin head phantom with embedded antennas broadcasting electrical signals, and recorded EEG with a commercially available electrode system. A robotic platform moved the phantom head through sinusoidal displacements at different frequencies (0–2 Hz). Results showed that a larger electrode surface area can have a small but significant effect on improving EEG signal quality during motion and that cable sway is a major contributor to motion artifacts. These results have implications in the development of future hardware for mobile brain imaging with EEG. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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15 pages, 7021 KiB

Open AccessArticle

A Novel Anti-Spoofing Solution for Iris Recognition Toward Cosmetic Contact Lens Attack Using Spectral ICA Analysis

by Sheng-Hsun Hsieh, Yung-Hui Li, Wei Wang and Chung-Hao Tien

Sensors 2018, 18(3), 795; https://doi.org/10.3390/s18030795 - 06 Mar 2018

Cited by 20 | Viewed by 5908

Abstract

In this study, we maneuvered a dual-band spectral imaging system to capture an iridal image from a cosmetic-contact-lens-wearing subject. By using the independent component analysis to separate individual spectral primitives, we successfully distinguished the natural iris texture from the cosmetic contact lens (CCL) pattern, and restored the genuine iris patterns from the CCL-polluted image. Based on a database containing 200 test image pairs from 20 CCL-wearing subjects as the proof of concept, the recognition accuracy (False Rejection Rate: FRR) was improved from FRR = 10.52% to FRR = 0.57% with the proposed ICA anti-spoofing scheme. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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3590 KiB

Open AccessArticle

Uniformity Study of Two-Functional Luminescent Dyes Adsorbed over an Anodized Aluminum Coating for Motion-Capturing Pressure- and Temperature-Sensitive Paint Imaging

by Masato Ishii, Takeshi Miyazaki and Hirotaka Sakaue

Sensors 2018, 18(1), 26; https://doi.org/10.3390/s18010026 - 23 Dec 2017

Cited by 6 | Viewed by 3271

Abstract

The pressure- and temperature-sensitive paint (PSP/TSP) technique, for steady-state and unsteady-state measurements, is becoming widespread. However, unsteady quantitative measurement is still difficult because non-uniform distribution of the probes over a test model may cause errors in the results. We focus on the dipping method that applies two luminophores into a binding material to improve sensitivity uniformity over a model surface. A bullet-shaped axisymmetric test model with motion-capturing TSP was used to evaluate the sensitivity uniformity, and three dipping methods (static, convectional, and rotational) were examined. The average peak ratios in the longitudinal direction were 1.17–1.46 for static, 1.38–1.51 for convectional, and 1.42–1.45 for rotational dipping. The standard deviations in the transverse direction were the smallest for rotational (0.022–0.033), relative to static (0.086–0.104), and convectional (0.044–0.065) dipping. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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2985 KiB

Open AccessArticle

Co-Cultured Continuously Bioluminescent Human Cells as Bioreporters for the Detection of Prodrug Therapeutic Impact Pre- and Post-Metabolism

by Tingting Xu, Michael Conway, Ashley Frank, Steven Ripp, Gary Sayler and Dan Close

Sensors 2017, 17(12), 2827; https://doi.org/10.3390/s17122827 - 06 Dec 2017

Cited by 2 | Viewed by 3224

Abstract

Modern drug discovery workflows require assay systems capable of replicating the complex interactions of multiple tissue types, but that can still function under high throughput conditions. In this work, we evaluate the use of substrate-free autobioluminescence in human cell lines to support the performance of these assays with reduced economical and logistical restrictions relative to substrate-requiring bioluminescent reporter systems. The use of autobioluminescence was found to support assay functionality similar to existing luciferase reporter targets. The autobioluminescent assay format was observed to correlate strongly with general metabolic activity markers such as ATP content and the presence of reactive oxygen species, but not with secondary markers such as glutathione depletion. At the transcriptional level, autobioluminescent dynamics were most closely associated with expression of the CYP1A1 phase I detoxification pathway. These results suggest constitutively autobioluminescent cells can function as general metabolic activity bioreporters, while pairing expression of the autobioluminescent phenotype to detoxification pathway specific promoters could create more specific sensor systems. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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5559 KiB

Open AccessArticle

Dual-Wavelength Laser Speckle Contrast Imaging (dwLSCI) Improves Chronic Measurement of Superficial Blood Flow in Hands

by Lingke Zhang, Li Ding, Miao Li, Xiaoli Zhang, Diansan Su, Jie Jia and Peng Miao

Sensors 2017, 17(12), 2811; https://doi.org/10.3390/s17122811 - 05 Dec 2017

Cited by 11 | Viewed by 5829

Abstract

Laser speckle contrast imaging (LSCI) has been widely used to determine blood flow and perfusion in biological tissues. The physical model of traditional LSCI ignores the effects of scattering property distribution in relation to speckle correlation time τ_c and blood flow v, which further results in biased estimation. In this study, we developed a dual-wavelength laser speckle contrast imaging (dwLSCI) method and a portable device for imaging the blood flow and tissue perfusion in human hands. Experimental data showed that dwLSCI could retrieve the vein vasculatures under the surface skin, and it further provided accurate measurements of vein blood flow signals, tissue perfusion signals, and fingertip perfusion signals, which assist with assessments of rehabilitation therapy for stroke patients. Fingertip perfusion signals demonstrated better performance in early assessments, while vein blood flow signals assisted the Fugl–Meyer Assessment Scale (FMA) and the Wolf Motor Function Test (WMFT) behavior assessments. As a general noninvasive imaging method, dwLSCI can be applied in clinical studies related to hand functions combined with behavior assessments. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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3002 KiB

Open AccessArticle

Effect of Shot Noise on Simultaneous Sensing in Frequency Division Multiplexed Diffuse Optical Tomographic Imaging Process

by Hansol Jang, Gukbin Lim, Keum-Shik Hong, Jaedu Cho, Gultekin Gulsen and Chang-Seok Kim

Sensors 2017, 17(12), 2752; https://doi.org/10.3390/s17122752 - 28 Nov 2017

Cited by 3 | Viewed by 4229

Abstract

Diffuse optical tomography (DOT) has been studied for use in the detection of breast cancer, cerebral oxygenation, and cognitive brain signals. As optical imaging studies have increased significantly, acquiring imaging data in real time has become increasingly important. We have developed frequency-division multiplexing (FDM) DOT systems to analyze their performance with respect to acquisition time and imaging quality, in comparison with the conventional time-division multiplexing (TDM) DOT. A large tomographic area of a cylindrical phantom 60 mm in diameter could be successfully reconstructed using both TDM DOT and FDM DOT systems. In our experiment with 6 source-detector (S-D) pairs, the TDM DOT and FDM DOT systems required 6.18 and 1 s, respectively, to obtain a single tomographic data set. While the absorption coefficient of the reconstruction image was underestimated in the case of the FDM DOT, we experimentally confirmed that the abnormal region can be clearly distinguished from the background phantom using both methods. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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1234 KiB

Open AccessArticle

Feature Weight Driven Interactive Mutual Information Modeling for Heterogeneous Bio-Signal Fusion to Estimate Mental Workload

by Pengbo Zhang, Xue Wang, Junfeng Chen and Wei You

Sensors 2017, 17(10), 2315; https://doi.org/10.3390/s17102315 - 12 Oct 2017

Cited by 17 | Viewed by 4200

Abstract

Many people suffer from high mental workload which may threaten human health and cause serious accidents. Mental workload estimation is especially important for particular people such as pilots, soldiers, crew and surgeons to guarantee the safety and security. Different physiological signals have been used to estimate mental workload based on the n-back task which is capable of inducing different mental workload levels. This paper explores a feature weight driven signal fusion method and proposes interactive mutual information modeling (IMIM) to increase the mental workload classification accuracy. We used EEG and ECG signals to validate the effectiveness of the proposed method for heterogeneous bio-signal fusion. The experiment of mental workload estimation consisted of signal recording, artifact removal, feature extraction, feature weight calculation, and classification. Ten subjects were invited to take part in easy, medium and hard tasks for the collection of EEG and ECG signals in different mental workload levels. Therefore, heterogeneous physiological signals of different mental workload states were available for classification. Experiments reveal that ECG can be utilized as a supplement of EEG to optimize the fusion model and improve mental workload estimation. Classification results show that the proposed bio-signal fusion method IMIM can increase the classification accuracy in both feature level and classifier level fusion. This study indicates that multi-modal signal fusion is promising to identify the mental workload levels and the fusion strategy has potential application of mental workload estimation in cognitive activities during daily life. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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30634 KiB

Open AccessArticle

Improving the Accuracy and Training Speed of Motor Imagery Brain–Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors

by David Lee, Sang-Hoon Park and Sang-Goog Lee

Sensors 2017, 17(10), 2282; https://doi.org/10.3390/s17102282 - 07 Oct 2017

Cited by 15 | Viewed by 5205

Abstract

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain–computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG) and principal component analyses are used to reduce the dimensionality of the feature vectors and linearly combine them. Subsequently, the GMM universal background model is trained by the expectation–maximization (EM) algorithm to purify the training data and reduce its size. Finally, a purified and reduced GMM-supervector is used to train the support vector machine classifier. The performance of the proposed method was evaluated for three different motor imagery datasets in terms of accuracy, kappa, mutual information, and computation time, and compared with the state-of-the-art algorithms. The results from the study indicate that the proposed method achieves high accuracy with a small amount of training data compared with the state-of-the-art algorithms in motor imagery EEG classification. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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4069 KiB

Open AccessArticle

Non-Destructive Analysis of the Internal Anatomical Structures of Mosquito Specimens Using Optical Coherence Tomography

by Naresh Kumar Ravichandran, Ruchire Eranga Wijesinghe, Seung-Yeol Lee, Kwang Shik Choi, Mansik Jeon, Hee-Young Jung and Jeehyun Kim

Sensors 2017, 17(8), 1897; https://doi.org/10.3390/s17081897 - 17 Aug 2017

Cited by 17 | Viewed by 6217

Abstract

The study of mosquitoes and analysis of their behavior are of crucial importance in the on-going efforts to control the alarming increase in mosquito-borne diseases. Furthermore, a non-destructive and real-time imaging technique to study the anatomical features of mosquito specimens can greatly aid the study of mosquitoes. In this study, we demonstrate the three-dimensional imaging capabilities of optical coherence tomography (OCT) for structural analysis of Anopheles sinensis mosquitoes. The anatomical features of An. sinensis head, thorax, and abdominal regions, along with the morphology of internal structures, such as foregut, midgut, and hindgut, were studied using OCT imaging. Two-dimensional and three-dimensional OCT images, used in conjunction with histological images, proved useful for anatomical analysis of mosquito specimens. By presenting this work as an initial study, we demonstrate the applicability of OCT for future mosquito-related entomological research, and also in identifying changes in mosquito anatomical structure. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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Review

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21 pages, 8044 KiB

Open AccessReview

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

by Andrea Loddo, Cecilia Di Ruberto and Michel Kocher

Sensors 2018, 18(2), 513; https://doi.org/10.3390/s18020513 - 08 Feb 2018

Cited by 54 | Viewed by 8918

Abstract

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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2087 KiB

Open AccessReview

Recent Advances in Fluorescence Lifetime Analytical Microsystems: Contact Optics and CMOS Time-Resolved Electronics

by Liping Wei, Wenrong Yan and Derek Ho

Sensors 2017, 17(12), 2800; https://doi.org/10.3390/s17122800 - 04 Dec 2017

Cited by 27 | Viewed by 7337

Abstract

Fluorescence spectroscopy has become a prominent research tool with wide applications in medical diagnostics and bio-imaging. However, the realization of combined high-performance, portable, and low-cost spectroscopic sensors still remains a challenge, which has limited the technique to the laboratories. A fluorescence lifetime measurement seeks to obtain the characteristic lifetime from the fluorescence decay profile. Time-correlated single photon counting (TCSPC) and time-gated techniques are two key variations of time-resolved measurements. However, commercial time-resolved analysis systems typically contain complex optics and discrete electronic components, which lead to bulkiness and a high cost. These two limitations can be significantly mitigated using contact sensing and complementary metal-oxide-semiconductor (CMOS) implementation. Contact sensing simplifies the optics, whereas CMOS technology enables on-chip, arrayed detection and signal processing, significantly reducing size and power consumption. This paper examines recent advances in contact sensing and CMOS time-resolved circuits for the realization of fully integrated fluorescence lifetime measurement microsystems. The high level of performance from recently reported prototypes suggests that the CMOS-based contact sensing microsystems are emerging as sound technologies for application-specific, low-cost, and portable time-resolved diagnostic devices. Full article

(This article belongs to the Special Issue Novel Sensors for Bioimaging)

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