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Innovative Sensors and Biosensors for In Vitro/In Vivo Diagnostics
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Innovative Sensors and Biosensors for In Vitro/In Vivo Diagnostics

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

Deadline for manuscript submissions: closed (20 April 2022) | Viewed by 15038

Special Issue Editor

Dr. Emanuele Rizzuto

E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy
Interests: mechanical and thermal measurements; storage systems; energy systems; sensors; industrial measurement; battery testing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The term “biosensor” generally describes a device that is composed of at least a biologically-based component and a reporter, to detect chemical or (specific) biomolecules. Biosensors are designed for continuous and long-term monitoring of target analytes in real biological systems, where a constant equilibrium is ideally required. Moreover, biosensors should be selective, sensitive, reversible, and biocompatible. On the other hand, a series of new in vitro or 3D printed tissues have been recently proposed for tissue engineering, thus requiring the generation of novel sensors for the measurement of their fundamental properties. It should be noted that these sensors may not completely fall within the standard definition of a biosensor for the bioreceptor or the transducer. However, they are expected to be selective, sensitive, and biocompatible, as well as biosensors.

The aim of this Special Issue is to focus on the most recent strategies and development of innovative sensors and biosensors for diagnosis of both in in vitro and in vivo conditions. Papers should address the development of novel bioreceptors, transducers, application or diagnostic methodologies. Particular attention should be given to the metrological characterization of the sensor.

Both review articles and original research papers are welcome.

Prof. Emanuele Rizzuto

Guest Editor

 

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Biosensors
  • Innovative sensors 
  • Biological tissues
  • Diagnostic
  • Metrological properties
  • Point of care biosensing device
  • Lab-on-chip

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Published Papers (4 papers)

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Research

15 pages, 3615 KiB  
Article
The Development of an Innovative Embedded Sensor for the Optical Measurement of Ex-Vivo Engineered Muscle Tissue Contractility
by Ludovica Apa, Marianna Cosentino, Flavia Forconi, Antonio Musarò, Emanuele Rizzuto and Zaccaria Del Prete
Sensors 2022, 22(18), 6878; https://doi.org/10.3390/s22186878 - 12 Sep 2022
Cited by 4 | Viewed by 2450
Abstract
Tissue engineering is a multidisciplinary approach focused on the development of innovative bioartificial substitutes for damaged organs and tissues. For skeletal muscle, the measurement of contractile capability represents a crucial aspect for tissue replacement, drug screening and personalized medicine. To date, the measurement [...] Read more.
Tissue engineering is a multidisciplinary approach focused on the development of innovative bioartificial substitutes for damaged organs and tissues. For skeletal muscle, the measurement of contractile capability represents a crucial aspect for tissue replacement, drug screening and personalized medicine. To date, the measurement of engineered muscle tissues is rather invasive and not continuous. In this context, we proposed an innovative sensor for the continuous monitoring of engineered-muscle-tissue contractility through an embedded technique. The sensor is based on the calibrated deflection of one of the engineered tissue’s supporting pins, whose movements are measured using a noninvasive optical method. The sensor was calibrated to return force values through the use of a step linear motor and a micro-force transducer. Experimental results showed that the embedded sensor did not alter the correct maturation of the engineered muscle tissue. Finally, as proof of concept, we demonstrated the ability of the sensor to capture alterations in the force contractility of the engineered muscle tissues subjected to serum deprivation. Full article
(This article belongs to the Special Issue Innovative Sensors and Biosensors for In Vitro/In Vivo Diagnostics)
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12 pages, 1746 KiB  
Article
A Novel Microwave Resonant Sensor for Measuring Cancer Cell Line Aggressiveness
by Livio D’Alvia, Serena Carraro, Barbara Peruzzi, Enrica Urciuoli, Luigi Palla, Zaccaria Del Prete and Emanuele Rizzuto
Sensors 2022, 22(12), 4383; https://doi.org/10.3390/s22124383 - 9 Jun 2022
Cited by 10 | Viewed by 3984
Abstract
The measurement of biological tissues’ dielectric properties plays a crucial role in determining the state of health, and recent studies have reported microwave biosensing to be an innovative method with great potential in this field. Research has been conducted from the tissue level [...] Read more.
The measurement of biological tissues’ dielectric properties plays a crucial role in determining the state of health, and recent studies have reported microwave biosensing to be an innovative method with great potential in this field. Research has been conducted from the tissue level to the cellular level but, to date, cellular adhesion has never been considered. In addition, conventional systems for diagnosing tumor aggressiveness, such as a biopsy, are rather expensive and invasive. Here, we propose a novel microwave approach for biosensing adherent cancer cells with different malignancy degrees. A circular patch resonator was designed adjusting its structure to a standard Petri dish and a network analyzer was employed. Then, the resonator was realized and used to test two groups of different cancer cell lines, based on various tumor types and aggressiveness: low- and high-aggressive osteosarcoma cell lines (SaOS-2 and 143B, respectively), and low- and high-aggressive breast cancer cell lines (MCF-7 and MDA-MB-231, respectively). The experimental results showed that the sensitivity of the sensor was high, in particular when measuring the resonant frequency. Finally, the sensor showed a good ability to distinguish low-metastatic and high-metastatic cells, paving the way to the development of more complex measurement systems for noninvasive tissue diagnosis. Full article
(This article belongs to the Special Issue Innovative Sensors and Biosensors for In Vitro/In Vivo Diagnostics)
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14 pages, 3233 KiB  
Article
Automatic Prediction of Ischemia-Reperfusion Injury of Small Intestine Using Convolutional Neural Networks: A Pilot Study
by Jie Hou, Runar Strand-Amundsen, Christian Tronstad, Jan Olav Høgetveit, Ørjan Grøttem Martinsen and Tor Inge Tønnessen
Sensors 2021, 21(19), 6691; https://doi.org/10.3390/s21196691 - 8 Oct 2021
Cited by 3 | Viewed by 2429
Abstract
Acute intestinal ischemia is a life-threatening condition. The current gold standard, with evaluation based on visual and tactile sensation, has low specificity. In this study, we explore the feasibility of using machine learning models on images of the intestine, to assess small intestinal [...] Read more.
Acute intestinal ischemia is a life-threatening condition. The current gold standard, with evaluation based on visual and tactile sensation, has low specificity. In this study, we explore the feasibility of using machine learning models on images of the intestine, to assess small intestinal viability. A digital microscope was used to acquire images of the jejunum in 10 pigs. Ischemic segments were created by local clamping (approximately 30 cm in width) of small arteries and veins in the mesentery and reperfusion was initiated by releasing the clamps. A series of images were acquired once an hour on the surface of each of the segments. The convolutional neural network (CNN) has previously been used to classify medical images, while knowledge is lacking whether CNNs have potential to classify ischemia-reperfusion injury on the small intestine. We compared how different deep learning models perform for this task. Moreover, the Shapley additive explanations (SHAP) method within explainable artificial intelligence (AI) was used to identify features that the model utilizes as important in classification of different ischemic injury degrees. To be able to assess to what extent we can trust our deep learning model decisions is critical in a clinical setting. A probabilistic model Bayesian CNN was implemented to estimate the model uncertainty which provides a confidence measure of our model decisions. Full article
(This article belongs to the Special Issue Innovative Sensors and Biosensors for In Vitro/In Vivo Diagnostics)
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12 pages, 3278 KiB  
Article
In Vivo Dual-Modal Photoacoustic and Ultrasound Imaging of Sentinel Lymph Nodes Using a Solid-State Dye Laser System
by Moongyu Han, Wonseok Choi, Joongho Ahn, Hanyoung Ryu, Youngseok Seo and Chulhong Kim
Sensors 2020, 20(13), 3714; https://doi.org/10.3390/s20133714 - 2 Jul 2020
Cited by 14 | Viewed by 4247
Abstract
Photoacoustic imaging (PAI) is being actively investigated as a non-invasive and non-radioactive imaging technique for sentinel lymph node (SLN) biopsy. By taking advantage of optical and ultrasound imaging, PAI probes SLNs non-invasively with methylene blue (MB) in both live animals and breast cancer [...] Read more.
Photoacoustic imaging (PAI) is being actively investigated as a non-invasive and non-radioactive imaging technique for sentinel lymph node (SLN) biopsy. By taking advantage of optical and ultrasound imaging, PAI probes SLNs non-invasively with methylene blue (MB) in both live animals and breast cancer patients. However, these PAI systems have limitations for widespread use in clinics and commercial marketplaces because the lasers used by the PAI systems, e.g., tunable liquid dye laser systems and optical parametric oscillator (OPO) lasers, are bulky in size, not economical, and use risky flammable and toxic liquid dyes. To overcome these limitations, we are proposing a novel dual-modal photoacoustic and ultrasound imaging system based on a solid-state dye laser (SD-PAUSI), which is compact, convenient, and carries far less risk of flammability and toxicity. Using a solid-state dye handpiece that generates 650-nm wavelength, we successfully imaged the MB tube positioned deeply (~3.9 cm) in chicken breast tissue. The SLNs were also photoacoustically detected in the in vivo rats beneath a 2.2-cm-thick layer of chicken breast, which is deeper than the typical depth of SLNs in humans (1.2 ± 0.5 cm). Furthermore, we showed the multispectral capability of the PAI by switching the dye handpiece, in which the MB-dyed SLN was selectively highlighted from the surrounding vasculature. These results demonstrated the great potential of the SD-PAUSI as an easy but effective modality for SLN detection. Full article
(This article belongs to the Special Issue Innovative Sensors and Biosensors for In Vitro/In Vivo Diagnostics)
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