Blocking Superantigen-Mediated Diseases: Challenges and Future Trends.

Superantigens are virulence factors secreted by microorganisms that can cause various immune diseases, such as overactivating the immune system, resulting in cytokine storms, rheumatoid arthritis, and multiple sclerosis. Some studies have demonstrated that superantigens do not require intracellular processing and instated bind as intact proteins to the antigen-binding groove of major histocompatibility complex II on antigen-presenting cells, resulting in the activation of T cells with different T-cell receptor Vß and subsequent overstimulation. To combat superantigen-mediated diseases, researchers have employed different approaches, such as antibodies and simulated peptides. However, due to the complex nature of superantigens, these approaches have not been entirely successful in achieving optimal therapeutic outcomes. CD28 interacts with members of the B7 molecule family to activate T cells. Its mimicking peptide has been suggested as a potential candidate to block superantigens, but it can lead to reduced T-cell activity while increasing the host's infection risk. Thus, this review focuses on the use of drug delivery methods to accurately target and block superantigens, while reducing the adverse effects associated with CD28 mimic peptides. We believe that this method has the potential to provide an effective and safe therapeutic strategy for superantigen-mediated diseases.

Tamm Plasmon Polariton Biosensors Based on Porous Silicon: Design, Validation and Analysis.

Tamm Plasmon Polariton (TPP) is a nanophotonic phenomenon that has attracted much attention due to its spatial strong field confinement, ease of mode excitation, and polarization independence. TPP has applications in sensing, storage, lasing, perfect absorber, solar cell, nonlinear optics, and many others. In this work, we demonstrate a biosensing platform based on TPP resonant mode. Both theoretical analyses based on the transfer matrix method and experimental validation through nonspecific detection of liquids of different refractive indices and specific detection of SARS-CoV-2 nucleocapsid protein (N-protein) are presented. Results show that the TPP biosensor has high sensitivity and good specificity. For N-protein detection, the sensitivity can be up to 1.5 nm/(µg/mL), and the limit of detection can reach down to 7 ng/mL with a spectrometer of 0.01 nm resolution in wavelength shift. Both nonspecific detection of R.I. liquids and specific detection of N-protein have been simulated and compared with experimental results to demonstrate consistency. This work paves the way for design, optimization, fabrication, characterization, and performance analysis of TPP based biosensors.

Heterogeneous-Nucleation Biosensor for Long-Term Collection and Mask-Based Self-Detection of SARS-CoV-2.

The effective control of infectious diseases, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, depends on the availability of rapid and accurate monitoring techniques. However, conventional SARS-CoV-2 detection technologies do not support continuous self-detection and may lead to cross-infection when utilized in medical institutions. In this study, we introduce a prototype of a mask biosensor designed for the long-term collection and self-detection of SARS-CoV-2. The biosensor utilizes the average resonance Rayleigh scattering intensity of Au nanocluster-aptamers. The inter-mask surface serves as a medium for the long-term collection and concentration enhancement of SARS-CoV-2, while the heterogeneous-nucleation nanoclusters (NCs) contribute to the exceptional stability of Au NCs for up to 48 h, facilitated by the adhesion of Ti NCs. Additionally, the biosensors based on Au NC-aptamers exhibited high sensitivity for up to 1 h. Moreover, through the implementation of a support vector machine classifier, a significant number of point signals can be collected and differentiated, leading to improved biosensor accuracy. These biosensors offer a complementary wearable device-based method for diagnosing SARS-CoV-2, with a limit of detection of 103 copies. Given their flexibility, the proposed biosensors possess tremendous potential for the continuous collection and sensitive self-detection of SARS-CoV-2 variants and other infectious pathogens.

Machine Learning Techniques for Effective Pathogen Detection Based on Resonant Biosensors.

We describe a machine learning (ML) approach to processing the signals collected from a COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine (SVM) were used to process both the raw data and the feature engineering data, and high performance for the qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID50/mL was achieved. Valid detection experiments contained 486 negative and 108 positive samples, and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contained 36 negative samples and 732 positive samples. The data distribution patterns of the valid and control detection dataset, based on T-distributed stochastic neighbor embedding (t-SNE), were used to study the distinguishability between positive and negative samples and explain the ML prediction performance. This work demonstrates that ML can be a generalized effective approach to process the signals and the datasets of biosensors dependent on resonant modes as biosensing mechanism.

A high-throughput fully automatic biosensing platform for efficient COVID-19 detection.

We propose a label-free biosensor based on a porous silicon resonant microcavity and localized surface plasmon resonance. The biosensor detects SARS-CoV-2 antigen based on engineered trimeric angiotensin converting enzyme-2 binding protein, which is conserved across different variants. Robotic arms run the detection process including sample loading, incubation, sensor surface rinsing, and optical measurements using a portable spectrometer. Both the biosensor and the optical measurement system are readily scalable to accommodate testing a wide range of sample numbers. The limit of detection is 100 TCID50/ml. The detection time is 5 min, and the throughput of one single robotic site is up to 384 specimens in 30 min. The measurement interface requires little training, has standard operation, and therefore is suitable for widespread use in rapid and onsite COVID-19 screening or surveillance.

Biosensors for waterborne virus detection: Challenges and strategies.

Waterborne viruses that can be harmful to human health pose significant challenges globally, affecting health care systems and the economy. Identifying these waterborne pathogens is essential for preventing diseases and protecting public health. However, handling complex samples such as human and wastewater can be challenging due to their dynamic and complex composition and the ultralow concentration of target analytes. This review presents a comprehensive overview of the latest breakthroughs in waterborne virus biosensors. It begins by highlighting several promising strategies that enhance the sensing performance of optical and electrochemical biosensors in human samples. These strategies include optimizing bioreceptor selection, transduction elements, signal amplification, and integrated sensing systems. Furthermore, the insights gained from biosensing waterborne viruses in human samples are applied to improve biosensing in wastewater, with a particular focus on sampling and sample pretreatment due to the dispersion characteristics of waterborne viruses in wastewater. This review suggests that implementing a comprehensive system that integrates the entire waterborne virus detection process with high-accuracy analysis could enhance virus monitoring. These findings provide valuable insights for improving the effectiveness of waterborne virus detection, which could have significant implications for public health and environmental management.

A Closed-Loop Approach to Fight Coronavirus: Early Detection and Subsequent Treatment.

The recent COVID-19 pandemic has caused tremendous damage to the social economy and people's health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this manuscript, we describe a novel solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetic neuromodulation or minimally invasive electrical stimulation to replace traditional ventilation. The solution is a closed-loop system in that the three modules are integrated together and form a loop to cover all-phase strategies for fighting COVID-19. The proposed technique can guarantee ubiquitous and onsite detection, and an electrical hypoglossal stimulator can be more effective in helping severe patients and reducing complications caused by ventilators.

Lab-on-Chip Microsystems for Ex Vivo Network of Neurons Studies: A Review.

Increasing population is suffering from neurological disorders nowadays, with no effective therapy available to treat them. Explicit knowledge of network of neurons (NoN) in the human brain is key to understanding the pathology of neurological diseases. Research in NoN developed slower than expected due to the complexity of the human brain and the ethical considerations for in vivo studies. However, advances in nanomaterials and micro-/nano-microfabrication have opened up the chances for a deeper understanding of NoN ex vivo, one step closer to in vivo studies. This review therefore summarizes the latest advances in lab-on-chip microsystems for ex vivo NoN studies by focusing on the advanced materials, techniques, and models for ex vivo NoN studies. The essential methods for constructing lab-on-chip models are microfluidics and microelectrode arrays. Through combination with functional biomaterials and biocompatible materials, the microfluidics and microelectrode arrays enable the development of various models for ex vivo NoN studies. This review also includes the state-of-the-art brain slide and organoid-on-chip models. The end of this review discusses the previous issues and future perspectives for NoN studies.

Label-Free LSPR-Vertical Microcavity Biosensor for On-Site SARS-CoV-2 Detection.

Cost-effective, rapid, and sensitive detection of SARS-CoV-2, in high-throughput, is crucial in controlling the COVID-19 epidemic. In this study, we proposed a vertical microcavity and localized surface plasmon resonance hybrid biosensor for SARS-CoV-2 detection in artificial saliva and assessed its efficacy. The proposed biosensor monitors the valley shifts in the reflectance spectrum, as induced by changes in the refractive index within the proximity of the sensor surface. A low-cost and fast method was developed to form nanoporous gold (NPG) with different surface morphologies on the vertical microcavity wafer, followed by immobilization with the SARS-CoV-2 antibody for capturing the virus. Modeling and simulation were conducted to optimize the microcavity structure and the NPG parameters. Simulation results revealed that NPG-deposited sensors performed better in resonance quality and in sensitivity compared to gold-deposited and pure microcavity sensors. The experiment confirmed the effect of NPG surface morphology on the biosensor sensitivity as demonstrated by simulation. Pre-clinical validation revealed that 40% porosity led to the highest sensitivity for SARS-CoV-2 pseudovirus at 319 copies/mL in artificial saliva. The proposed automatic biosensing system delivered the results of 100 samples within 30 min, demonstrating its potential for on-site coronavirus detection with sufficient sensitivity.

Energy Solutions for Wearable Sensors: A Review.

Wearable sensors have gained popularity over the years since they offer constant and real-time physiological information about the human body. Wearable sensors have been applied in a variety of ways in clinical settings to monitor health conditions. These technologies require energy sources to carry out their projected functionalities. In this paper, we review the main energy sources used to power wearable sensors. These energy sources include batteries, solar cells, biofuel cells, supercapacitors, thermoelectric generators, piezoelectric and triboelectric generators, and radio frequency (RF) energy harvesters. Additionally, we discuss wireless power transfer and some hybrids of the above technologies. The advantages and drawbacks of each technology are considered along with the system components and attributes that make these devices function effectively. The objective of this review is to inform researchers about the latest developments in this field and present future research opportunities.

Towards wearable and implantable continuous drug monitoring: A review.

Continuous drug monitoring is a promising alternative to current therapeutic drug monitoring strategies and has a strong potential to reshape our understanding of pharmacokinetic variability and to improve individualised therapy. This review highlights recent advances in biosensing technologies that support continuous drug monitoring in real time. We focus primarily on aptamer-based biosensors, wearable and implantable devices. Emphasis is given to the approaches employed in constructing biosensors. We pay attention to sensors' biocompatibility, calibration performance, long-term characteristics stability and measurement quality. Last, we discuss the current challenges and issues to be addressed in continuous drug monitoring to make it a promising, future tool for individualised therapy. The ongoing efforts are expected to result in fully integrated implantable drug biosensing technology. Thus, we may anticipate an era of advanced healthcare in which wearable and implantable biochips will automatically adjust drug dosing in response to patient health conditions, thus enabling the management of diseases and enhancing individualised therapy.

Tailoring Permeability of Microporous Copper Structures through Template Sintering.

Microporous metals are used extensively for applications that combine convective and conductive transport and benefit from low resistance to both modes of transport. Conventional fabrication methods, such as direct sintering of metallic particles, however, often produce structures with limited fluid transport properties due to the lack of control over pore morphologies such as the pore size and porosity. Here, we demonstrate control and improvement of hydraulic permeability of microporous copper structures fabricated using template-assisted electrodeposition. Template sintering is shown to modify the fluid transport network in a manner that increases permeability by nearly an order of magnitude with a less significant decrease (∼38%) in thermal conductivity. The measured permeabilities range from 4.8 × 10-14 to 1.3 × 10-12 m2 with 5 µm pores, with the peak value being roughly 5 times larger than the published values for sintered copper particles of comparable feature sizes. Analysis indicates that the enhancement of permeability is limited by constrictions, i.e., bottlenecks between connecting pores, whose dimensions are highly sensitive to the sintering conditions. We further show contrasting trends in permeability versus conductivity of the electrodeposited microporous copper and conventional sintered copper particles and suggest these differing trends to be the result of their inverse structural relationship.

A method for quantifying in plane permeability of porous thin films.

The in-plane permeability of porous thin films is an important fluid mechanical property that determines wicking and pressure-driven flow behavior in such materials. This property has so far been challenging to measure directly due to the small sidewall cross-sectional area of thin films available for flow. In this work, we propose and experimentally demonstrate a novel technique for directly measuring in-plane permeability of porous thin films of arbitrary thicknesses, in situ, using a manifold pressed to the top surface of the film. We both measure and simulate the influence of the two dimensional flow field produced in a film by the manifold and extract the permeability from measurements of pressure drop at fixed flow rates. Permeability values measured using the technique for a periodic array of channels are comparable to theoretical predictions. We also determine in-plane permeability of arrays of pillars and electrodeposited porous copper films. This technique is a robust tool to characterize permeability of thin films of arbitrary thicknesses on a variety of substrates. In Supplementary material, we provide a solid model, which is useful in three-dimensional printer reproductions of our device.

Nanoscale porous silicon waveguide for label-free DNA sensing.

Porous silicon (PSi) is an excellent material for biosensing due to its large surface area and its capability for molecular size selectivity. In this work, we report the experimental demonstration of a label-free nanoscale PSi resonant waveguide biosensor. The PSi waveguide consists of pores with an average diameter of 20nm. DNA is attached inside the pores using standard amino-silane and glutaraldehyde chemistry. Molecular binding in the PSi is detected optically based on a shift of the waveguide resonance angle. The magnitude of the resonance shift is directly related to the quantity of biomolecules attached to the pore walls. The PSi waveguide sensor can selectively discriminate between complementary and non-complementary DNA. The advantages of the PSi waveguide biosensor include strong field confinement and a sharp resonance feature, which allow for high sensitivity measurements with a low detection limit. Simulations indicate that the sensor has a detection limit of 50nM DNA concentration or equivalently, 5pg/mm2.