Biosensors: Classifications, medical applications, and future prospective

Alhadrami, Hani A.

doi:10.1002/bab.1621

Cited by 128 publications

(55 citation statements)

References 117 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The literature search resulted in 59 papers for “genotoxicity & 3D in vitro model”, 73 papers for “genotoxicity & advanced in vitro model”, 134 papers for “genotoxicity & high throughput”, eight papers for “genotoxicity & high throughput & nanomaterials” [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ] and six papers for “genotoxicity & high throughput & nanoparticles” (4 are the same as for “genotoxicity & high throughput & nanomaterials”) [ 16 , 17 , 18 , 19 , 21 , 22 ], seven papers for “genotoxicity & organ on chip“ [ 23 , 24 , 25 , 26 , 27 , 28 , 29 ], seven papers for “genotoxicity & 3D models & nanoparticles” [ 30 , 31 , 32 , 33 , 34 , 35 , 36 ], 11 papers for “genotoxicity & 3D models & nanomaterials” [ 30 , 31 , 33 , 36 , 37 , 38 , 39 , 40 , 41 ] for the period of 20 years (2000–2020), whereby the year 2020 was considered only from January to August. ( Table 1 ).…”

Section: Results Of Literature Searchmentioning

confidence: 99%

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

et al. 2020

View full text Add to dashboard Cite

Changes in the genetic material can lead to serious human health defects, as mutations in somatic cells may cause cancer and can contribute to other chronic diseases. Genotoxic events can appear at both the DNA, chromosomal or (during mitosis) whole genome level. The study of mechanisms leading to genotoxicity is crucially important, as well as the detection of potentially genotoxic compounds. We consider the current state of the art and describe here the main endpoints applied in standard human in vitro models as well as new advanced 3D models that are closer to the in vivo situation. We performed a literature review of in vitro studies published from 2000–2020 (August) dedicated to the genotoxicity of nanomaterials (NMs) in new models. Methods suitable for detection of genotoxicity of NMs will be presented with a focus on advances in miniaturization, organ-on-a-chip and high throughput methods.

show abstract

Section: Results Of Literature Searchmentioning

confidence: 99%

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Detection using biosensors is achieved through a process in which measurable optical or electrical signals are derived from the binding of an analyte and a receptor specific to this analyte ( Figure 1 a) [ 2 , 3 , 4 , 5 ]. Biosensors are used in various fields, including medical diagnostics, which require highly sensitive detecting of low-concentration analytes below ng/mL for early diagnosis or precise analysis [ 1 , 6 , 7 , 8 ]. To achieve this, a wide variety of studies are being conducted on improving the binding efficiency between analytes and receptors, or the signal efficiency and intensity from the analyte-receptor binding [ 9 , 10 , 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Binding of Analyte-Receptor in a Micro-Fluidic Channel for a Biosensor Based on Brownian Motion

Choi

Lee

et al. 2020

Micromachines

View full text Add to dashboard Cite

This study experimentally analyses the binding characteristics of analytes mixed in liquid samples flowing along a micro-channel to the receptor fixed on the wall of the micro-channel to provide design tools and data for a microfluidic-based biosensor. The binding or detection characteristics are analyzed experimentally by counting the number of analytes bound to the receptor, with sample analyte concentration, sample flow rate, and the position of the receptor along the micro-channel length as the main variables. A mathematical model is also proposed to predict the number of analytes transported and bound to the receptor based on a probability density function for Brownian motion. The coefficient in the mathematical model is obtained by using a dimensionless mathematical model and the experimental results. The coefficient remains valid for all different conditions of the sample analyte concentration, flow rate, and the position of the receptor, which implies the possibility of deriving a generalized model. Based on the mathematical model derived from mathematical and experimental analysis on the detection characteristics of the microfluidic-based biosensor depending on previously mentioned variables and the height of the micro-channel, this study suggests a design for a microfluidic-based biosensor by predicting the binding efficiency according to the channel height. The results show the binding efficiency increases as the flow rate decreases and as the receptor is placed closer to the sample-injecting inlet, but is unaffected by sample concentration.

show abstract

“…Biosensor platforms are increasingly being developed for use in point-of-care diagnostics [ 8 ], drug delivery and environmental monitoring [ 9 ]. Specific applications include pathogen detection [ 10 ], monitoring glucose concentration in tears [ 11 ] and rapid detection of human papilloma virus [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

On the electrical conductivity of alginate hydrogels

Kaklamani

Kazaryan

Bowen

et al. 2018

Regenerative Biomaterials

View full text Add to dashboard Cite

Hydrogels have been extensively used in the field of biomedical applications, offering customizable natural, synthetic or hybrid materials, particularly relevant in the field of tissue engineering. In the bioelectronics discipline, hydrogels are promising mainly as sensing platforms with or without encapsulated cells, showing great potential in healthcare and medicine. However, to date there is little data in the literature which characterizes the electrical properties of tissue engineering materials which are relevant to bioelectronics. In this work, we present electrical characterization of alginate hydrogels, a natural polysaccharide, using a four-probe method similar to electrical impedance spectroscopy. The acquired conductance data show distinct frequency-dependent features that change as a function of alginate and crosslinker concentration reflecting ion kinetics inside the measured sample. Furthermore, the presence of NIH 3T3 fibroblasts encapsulated in the hydrogels matrix was found to alter the artificial tissue’s electrical properties. The method used provides valuable insight to the frequency-dependent electrical response of the resulting systems. It is hoped that the outcome of this research will be of use in the development of cell/electronic interfaces, possibly toward diagnostic biosensors and therapeutic bioelectronics.

show abstract

Biosensors: Classifications, medical applications, and future prospective

Cited by 128 publications

References 117 publications

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

Genotoxicity of Nanomaterials: Advanced In Vitro Models and High Throughput Methods for Human Hazard Assessment—A Review

Analysis of the Binding of Analyte-Receptor in a Micro-Fluidic Channel for a Biosensor Based on Brownian Motion

On the electrical conductivity of alginate hydrogels

Contact Info

Product

Resources

About