ABSTRACT
Rapid biosensing assays to detect SARS-CoV-2 are critical in mitigating the impact of the pandemic. Here, we use a lens-free holographic microscope coupled with deep learning in a rapid and sensitive assay to detect SARS-CoV-2. © 2022 The Author(s)
ABSTRACT
Rapid biosensing assays to detect SARS-CoV-2 are critical in mitigating the impact of the pandemic. Here, we use a lens-free holographic microscope coupled with deep learning in a rapid and sensitive assay to detect SARS-CoV-2. © 2022 The Author(s)
ABSTRACT
An X-band, free-space microwave sensor consisting of 30 radial spokes connected in a central hub with a gap region was designed, fabricated and tested. The sensor structure results in an electric dipole at 10 GHz with a split circular disc capacitor at the center. Viruses, dust, and soot particles in the gap region change the sensor’s impedance and its reflection coefficient monitored by a horn antenna and a network analyzer. The sensor sensitivity was 85.02 MHz/microliter for deionized water, 89.5 MHz/microliter for uninfected saliva, and 94.6 MHz/microliter for SARS-COV-2 infected saliva with 103 viruses/μL. Its sensitivity to a dielectric sample (ερ~5.84) was 3.23 MHz/mm3, and for iron particles was 16.25 MHz/mm3. All these samples were smaller than λ/30 at 10 GHz and could not be detected on uniform dielectric or metallic substrates without the spoke structure. A 2x2 array of spoke sensors was also constructed and tested as a feasibility study for designing larger metamaterial (MTM) periodic arrays. IEEE
ABSTRACT
Medicine is heading towards personalized care based on individual situations and conditions. With smartphones and increasingly miniaturized wearable devices, the sensors available on these devices can perform long-term continuous monitoring of several user health-related parameters, making them a powerful tool for a new medicine approach for these patients. Our proposed system, described in this article, aims to develop innovative solutions based on artificial intelligence techniques to empower patients with cardiovascular disease. These solutions will realize a novel 5P (Predictive, Preventive, Participatory, Personalized, and Precision) medicine approach by providing patients with personalized plans for treatment and increasing their ability for self-monitoring. Such capabilities will be derived by learning algorithms from physiological data and behavioral information, collected using wearables and smart devices worn by patients with health conditions. Further, developing an innovative system of smart algorithms will also focus on providing monitoring techniques, predicting extreme events, generating alarms with varying health parameters, and offering opportunities to maintain active engagement of patients in the healthcare process by promoting the adoption of healthy behaviors and well-being outcomes. The multiple features of this future system will increase the quality of life for cardiovascular diseases patients and provide seamless contact with a healthcare professional.
Subject(s)
Artificial Intelligence , Wearable Electronic Devices , Delivery of Health Care , Humans , Quality of Life , SmartphoneABSTRACT
In recent decades, the use of engineered nanoparticles has been increasing in various sectors, including biomedicine, diagnosis, water treatment, and environmental remediation leading to significant public concerns. Among these nanoparticles, magnetic nanoparticles (MNPs) have gained many attentions in medicine, pharmacology, drug delivery system, molecular imaging, and bio-sensing due to their various properties. In addition, various studies have reviewed MNPs main applications in the biomedical engineering area with intense progress and recent achievements. Nanoparticles, especially the magnetic nanoparticles, have recently been confirmed with excellent antiviral activity against different viruses, including SARS-CoV-2(Covid-19) and their recent development against Covid-19 also has also been discussed. This review aims to highlight the recent development of the magnetic nanoparticles and their biomedical applications such as diagnosis of diseases, molecular imaging, hyperthermia, bio-sensing, gene therapy, drug delivery and the diagnosis of Covid-19.
ABSTRACT
With their ubiquitous nature, bacteria have had a significant impact on human health and evolution. Though as commensals residing in/on our bodies several bacterial communities support our health in many ways, bacteria remain one of the major causes of infectious diseases that plague the human world. Adding to this, emergence of antibiotic resistant strains limited the use of available antibiotics. The current available techniques to prevent and control such infections remain insufficient. This has been proven during one of greatest pandemic of our generation, COVID-19. It has been observed that bacterial coinfections were predominantly observed in COVID-19 patients, despite antibiotic treatment. Such higher rates of coinfections in critical patients even after antibiotic treatment is a matter of concern. Owing to many reasons across the world drug resistance in bacteria is posing a major problem i. According to Center for Disease control (CDC) antibiotic report threats (AR), 2019 more than 2.8 million antibiotic resistant cases were reported, and more than 35,000 were dead among them in USA alone. In both normal and pandemic conditions, failure of identifying infectious agent has played a major role. This strongly prompts the need to improve upon the existing techniques to not just effective identification of an unknown bacterium, but also to discriminate normal Vs drug resistant strains. New techniques based on Aggregation Induced Emission (AIE) are not only simple and rapid but also have high accuracy to visualize infection and differentiate many strains of bacteria based on biomolecular variations which has been discussed in this chapter.
Subject(s)
COVID-19 , Anti-Bacterial Agents , Bacteria , Humans , SARS-CoV-2ABSTRACT
In order to treat severe acute respiratory syndrome coronavirus (SARS-CoV), till now, no such specific treatment is available. Various coronaviruses (CoV) such as SARS-CoV, MERS-CoV (Middle East Respiratory Syndrome), and SARS-CoV-2 can infect humans and the name was implicated due to their crown shape. SARS-CoV-2 is also called COVID-19 which was found to be a novel strain of coronavirus and is transmitted primarily through small droplets of viral particles that target the human body through the open pathways. Researchers have observed that microbes can survive for a longer duration as they get adhered to any object or surface. Nanoparticles have the capability to disable these pathogens even before they enter the body. To eradicate conventional time consuming steps like quantitative real-time polymerase chain reaction for detection of COVID-19, nanoparticles mediated sensing approaches provide great advances in rapid diagnosis. Nanoparticles- based biosensors are comparatively beneficial which offer tremendous potential for rapid medical diagnosis. Nanotechnology can be refined and optimized to attack a wide variety of pathogens. As compared to other large molecular structures, nanoparticles being small in size, have high sensitivity for bio-sensing and can move throughout the body without disruption of the immune function.
Subject(s)
COVID-19 , Middle East Respiratory Syndrome Coronavirus , Biocompatible Materials , Humans , SARS-CoV-2ABSTRACT
The COVID-19 virus has been recently identified as a new species of virus that can cause severe infections such as pneumonia. The sudden outbreak of this disease is being considered a pandemic. Given all this, it is essential to develop smart biosensors that can detect pathogens with minimum time delay. Surface plasmon resonance (SPR) biosensors make use of refractive index (RI) changes as the sensing parameter. In this work, based on actual data taken from previous experimental works done on plasmonic detection of viruses, a detailed simulation of the SPR scheme that can be used to detect the COVID-19 virus is performed and the results are extrapolated from earlier schemes to predict some outcomes of this SPR model. The results indicate that the conventional Kretschmann configuration can have a limit of detection (LOD) of 2E-05 in terms of RI change and an average sensitivity of 122.4 degRIU-1 at a wavelength of 780 nm.