Biosensors for detection of prostate cancer: a review

Diagnosis of prostate cancer (PC) has posed a challenge worldwide due to the sophisticated and costly diagnostics tools, which include DRE, TRUS, GSU, PET/CT scan, MRI, and biopsy. These diagnostic techniques are very helpful in the detection of PCs; however, all the techniques have their serious limitations. Biosensors are easier to fabricate and do not require any cutting-edge technology as required for other imaging techniques. In this regard, point-of-care (POC) biosensors are important due to their portability, convenience, low cost, and fast procedure. This review explains the various existing diagnostic tools for the detection of PCs and the limitation of these methods. It also focuses on the recent studies on biosensors technologies as an alternative to the conventional diagnostic techniques for the detection of PCs.

Cancer and Disease Diagnosis - Biosensor as Potential Diagnostic Tool for Biomarker Detection

Analysis of cancer biomarkers has enormous promise for advancing our molecular understanding of illness and facilitating more precise and timely diagnosis and follow-up care. MicroRNA, exosomes, ctDNA, CTCs, and proteins are only some of the circulating biomarkers that can be detected by liquid biopsy instead of the more intrusive and time-consuming process of doing a tissue biopsy. As the cancer diagnosis bio-markers reveal ultra-low levels in the early stages of the disease, highly sensitive approaches are urgently required. Researchers have taken an interest in a optical biosensor for detecting cancer biomarkers as a potential tool for early disease diagnosis. These techniques have the potential to aid in the development of effective treatments, ultimately leading to a higher rate of patient survival. This review briefly discuss the i) understanding of cancer and biomarkers for early diagonosis purpose ii) Molecular methods and ii) biosensor-based diagnostics. The reseach primary focus on advancement in biosensor design using various concepts ie., Electrochemical, Chemiluminescence and Colorimetric, Surface plasmons (SP), Surface plasmon resonance (SPR), localized surface plasmon resonance (LSPR), Fluorescence, Fiber-based sensors, Terahertz based biosensors, and Surface enhanced Raman spectroscopy (SERS). As a result of the local electric field amplification around plasmonic (usually gold and silver) nanostructures, surface-enhanced Raman spectroscopy (SERS) has emerged as a rapid, selective, and sensitive alternative to conventional laboratory analytical methods, making significant strides in a number of biosensing applications but still under developing stage to be used as diagnostic tool in clinical research.

A Proposal for a Novel Surface-Stress Based BioMEMS Sensor Using an Optical Sensing System for Highly Sensitive Diagnoses of Bio-particles

In this paper, a BioMEMS sensor by using a surface-stress sensing approach, connected to a highly sensitive optical sensing system, is proposed to diagnose various types of biomolecules. The MEMS transducer is composed of a fixed-fixed beam with immobilized receptors on the surface which is connected to a Ring Resonator (RR) filter. The interaction between the target biomolecules and the receptors induces surface stresses on the beam. This stress results in the beam deformation which leads to changes in the coupling coefficient of the RR. Consequently, the transmission spectrum of the RR experiences changes, measured by using an optical photo-detector. Therefore, by analyzing the response of the photo-detector output, one can detect the number of target biomolecules in the sample and assign a level of contamination, infection or bioparticles, caused by the specific disease. Furthermore, the MEMS functional characteristics and the optical properties of the proposed biosensor are designed and analyzed respectively by using the finite element method (FEM) and the finite difference time domain (FDTD) approach. The obtained functional characteristics of the proposed device show that the present optical BioMEMS sensor can be used for highly sensitive diagnoses of various types of diseases and their progress level.

Review: Cantilever-Based Sensors for High Speed Atomic Force Microscopy

This review critically summarizes the recent advances of the microcantilever-based force sensors for atomic force microscope (AFM) applications. They are one the most common mechanical spring-mass systems and are extremely sensitive to changes in the resonant frequency, thus finding numerous applications especially for molecular sensing. Specifically, we comment on the latest progress in research on the deflection detection systems, fabrication, coating and functionalization of the microcantilevers and their application as bio- and chemical sensors. A trend on the recent breakthroughs on the study of biological samples using high-speed atomic force microscope is also reported in this review.

Smart diagnostics devices through artificial intelligence and mechanobiological approaches

The present work illustrates the promising intervention of smart diagnostics devices through artificial intelligence (AI) and mechanobiological approaches in health care practices. The artificial intelligence and mechanobiological approaches in diagnostics widen the scope for point of care techniques for the timely revealing of diseases by understanding the biomechanical properties of the tissue of interest. Smart diagnostic device senses the physical parameters due to change in mechanical, biological, and luidic properties of the cells and to control these changes, supply the necessary drugs immediately using AI techniques. The latest techniques like sweat diagnostics to measure the overall health, Photoplethysmography (PPG) for real-time monitoring of pulse waveform by capturing the reflected signal due to blood pulsation), Micro-electromechanical systems (MEMS) and Nano-electromechanical systems (NEMS) smart devices to detect disease at its early stage, lab-on-chip and organ-on-chip technologies, Ambulatory Circadian Monitoring device (ACM), a wrist-worn device for Parkinson's disease have been discussed. The recent and futuristic smart diagnostics tool/techniques like emotion recognition by applying machine learning algorithms, atomic force microscopy that measures the fibrinogen and erythrocytes binding force, smartphone-based retinal image analyser system, image-based computational modeling for various neurological disorders, cardiovascular diseases, tuberculosis, predicting and preventing of Zika virus, optimal drugs and doses for HIV using AI, etc. have been reviewed. The objective of this review is to examine smart diagnostics devices based on artificial intelligence and mechanobiological approaches, with their medical applications in healthcare. This review determines that smart diagnostics devices have potential applications in healthcare, but more research work will be essential for prospective accomplishments of this technology.

On-Chip Detection of the Biomarkers for Neurodegenerative Diseases: Technologies and Prospects

Alzheimer's disease (AD), Parkinson's disease (PD) and glaucoma are all regarded as neurodegenerative diseases (neuro-DDs) because these diseases are highly related to the degeneration loss of functions and death of neurons with aging. The conventional diagnostic methods such as neuroimaging for these diseases are not only expensive but also time-consuming, resulting in significant financial burdens for patients and public health challenge for nations around the world. Hence early detection of neuro-DDs in a cost-effective and rapid manner is critically needed. For the past decades, some chip-based detection technologies have been developed to address this challenge, showing great potential in achieving point-of-care (POC) diagnostics of neuro-DDs. In this review, chip-based detection of neuro-DDs' biomarkers enabled by different transducing mechanisms is evaluated.

Simulation of an electrically actuated cantilever as a novel biosensor

Recently, detecting biological particles by analyzing their mechanical properties has attracted increasing attention. To detect and identify different bioparticles and estimate their dimensions, a mechanical nanosensor is introduced in this paper. To attract particles, numerous parts of the substrate are coated with different chemicals as probe detectors or receptors. The principal of cell recognition in this sensor is based on applying an electrical excitation and measuring the maximum deflection of the actuated cantilever electrode. Investigating the critical voltage that causes pull-in instability is also important in such highly-sensitive detectors. The governing equation of motion is derived from Hamilton’s principle. A Galerkin approximation is applied to discretize the nonlinear equation, which is solved numerically. Accuracy of the proposed model is validated by comparison studies with available experimental and theoretical data. The coupled effects of geometrical and mechanical properties are included in this model and studied in detail. Moreover, system identification is carried out to distinguish bioparticles by a stability analysis. Due to the absence of a similar concept and device, this research is expected to advance the state-of-the-art biosystems in identifying particles.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.