ESSENCE – A rapid, shear-enhanced, flow-through, capacitive electrochemical platform for rapid detection of biomolecules

Point-of-care diagnostic devices for periodontitis - current trends and urgent need

Point of care (POC) diagnostic devices provide a method for rapid accurate identification of disease through analysis of biologically relevant substances. This review focuses on the utility of POC testing for early detection of periodontitis, a critical factor in treating the disease. Accessing the oral cavity for biological sampling is less invasive when compared to other internal test sites, and oral fluids contain biomarkers indicative of periodontitis. The ease of access makes the mouth an excellent target location for the development of POC devices. In this review, accepted standards in industry by which these devices must adhere, provided by the World Health Organization such as REASSURED and CLIA, are discussed. An overview is provided for many periodontal biomarkers currently being investigated as a means of predicting periodontal disease and its progression. POC devices currently being investigated for the identification and monitoring of periodontal disease such as paper-based and lab-on-a-chip based devices are outlined. Limitations of current POC devices on the market are provided and future directions in leveraging biomarkers as an adjunctive method for oral diagnosis along with AI-based analysis systems are discussed. Here, we present the ESSENCE sensor platform, which combines a porous non-planar electrode with enhanced shear flow to achieve unprecedented sensitivity and selectivity. The combination of the ESENCE chip with an automated platform allows us to meet the WHO's ASSURED criteria. This platform promises to be an exciting POC candidate for early detection of periodontitis.

Artificial Intelligence-Based Microfluidic Platform for Detecting Contaminants in Water: A Review

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed.

Optimization of Electrolytes with Redox Reagents to Improve the Impedimetric Signal for Use with a Low-Cost Analyzer

The most well-known criterion for POC devices is ASSURED, and affordability, i.e., using low-cost instrumentation, is the most challenging one. This manuscript provides a pathway for transitioning ESSENCE, an impedance-based biosensor platform, from using an expensive benchtop analyzer-KeySight 4294A (~$50k)-to using a significantly portable and cheaper USB oscilloscope-Analog Discovery 2 (~$200) -with similar sensitivity (around 100 times price difference). To achieve this, we carried out a fundamental study of the interplay between an electrolyte like potassium chloride (KCl), and an electrolyte buffer like phosphate buffered saline (PBS) in the presence and absence of a redox buffer like ferro/ferricyanide system and ([Ru(bpy)3]2+). Redox molecules in the electrolyte caused a significant change in the Nyquist curve of the impedance depending on the redox molecule type. The redox species and the background electrolyte have their own RC semicircles in the Nyquist curve, whose overlap depends on the redox concentration and electrolyte ionic strength. We found that by increasing the electrolyte ionic strength or the redox concentration, the RC semicircle moves to higher frequencies and vice versa. Importantly, the use of the buffer electrolyte, instead of KCl, led to a lower standard deviation and overall signal (lesser sensitivity). However, to achieve the best results from the biorecognition signal, we chose a buffered electrolyte like PBS with high ionic strength and lowered the redox probe concentrations to minimize the standard deviation and reduce any noise from migrating to the low-cost analyzer. Comparing the two analyzers shows similar results, with a lowered detection limit from the low-cost analyzer.

Electrochemical nucleic acid sensors: Competent pathways for mobile molecular diagnostics

Electrochemical nucleic acid biosensor has demonstrated great promise in clinical diagnostic tests, mainly because of its flexibility, high efficiency, low cost, and easy integration for analytical applications. Numerous nucleic acid hybridization-based strategies have been developed for the design and construction of novel electrochemical biosensors for diagnosing genetic-related diseases. This review describes the advances, challenges, and prospects of electrochemical nucleic acid biosensors for mobile molecular diagnosis. Specifically, the basic principles, sensing elements, applications in diagnosis of cancer and infectious diseases, integration with microfluidic technology and commercialization are mainly included in this review, aiming to provide new insights and directions for the future development of electrochemical nucleic acid biosensors.

Microfluidic Gas Sensors: Detection Principle and Applications

With the rapid growth of emerging point-of-use (POU)/point-of-care (POC) detection technologies, miniaturized sensors for the real-time detection of gases and airborne pathogens have become essential to fight pollution, emerging contaminants, and pandemics. However, the low-cost development of miniaturized gas sensors without compromising selectivity, sensitivity, and response time remains challenging. Microfluidics is a promising technology that has been exploited for decades to overcome such limitations, making it an excellent candidate for POU/POC. However, microfluidic-based gas sensors remain a nascent field. In this review, the evolution of microfluidic gas sensors from basic electronic techniques to more advanced optical techniques such as surface-enhanced Raman spectroscopy to detect analytes is documented in detail. This paper focuses on the various detection methodologies used in microfluidic-based devices for detecting gases and airborne pathogens. Non-continuous microfluidic devices such as bubble/droplet-based microfluidics technology that have been employed to detect gases and airborne pathogens are also discussed. The selectivity, sensitivity, advantages/disadvantages vis-a-vis response time, and fabrication costs for all the microfluidic sensors are tabulated. The microfluidic sensors are grouped based on the target moiety, such as air pollutants such as carbon monoxide and nitrogen oxides, and airborne pathogens such as E. coli and SARS-CoV-2. The possible application scenarios for the various microfluidic devices are critically examined.

A novel 3D Tesla valve micromixer for efficient mixing and chitosan nanoparticle production

Current three-dimensional micromixers for continuous flow reactions and nanoparticle synthesis are complex in structure and difficult to fabricate. This paper investigates the design, fabrication, and characterization of a novel micromixer that uses a simple spatial Tesla valve design to achieve efficient mixing of multiple solutions. The flow characteristics and mixing efficiencies of our Tesla valve micromixer are investigated using a combination of numerical simulations and experiments. The results show that in a wide range of flow rates, viscoelastic solutions with different concentrations can be well mixed in our micromixer. Finally, experiments on the synthesis of chitosan nanoparticles are conducted to verify the practicability of our micromixer. Compared with nanoparticles prepared by conventional magnetic stirring, the size of nanoparticles prepared by micromixing is smaller and the distribution is more uniform. Therefore, our Tesla valve micromixer has significant advantages and implications for mixing chemical and biological reactions.

Recent advances in the highly sensitive determination of zearalenone residues in water and environmental resources with electrochemical biosensors

Zearalenone (ZEN), a significant class of mycotoxin which is considered as a xenoestrogen, permits, similar to natural estrogens, it's binding to the receptors of estrogen resulting in various reproductive diseases especially, hormonal misbalance. ZEN has toxic effects on human and animal health as a result of its teratogenicity, carcinogenicity, mutagenicity, nephrotoxicity, genotoxicity, and immunotoxicity. To ensure water and environmental resources safety, precise, rapid, sensitive, and reliable analytical and conventional methods can be progressed for the determination of toxins such as ZEN. Different selective nanomaterial-based compounds are used in conjunction with different analytical detection approaches to achieve this goal. The current review demonstrates the state-of-the-art advances of nanomaterial-based electrochemical sensing assays including various sensing, apta-sensing and, immunosensing studies to the highly sensitive determination of various ZEN families. At first, a concise study of the occurrence, structure, toxicity, legislations, and distribution of ZEN in monitoring has been performed. Then, different conventional and clinical techniques and procedures to sensitive and selective sensing techniques have been reviewed and the efficient comparison of them has been thoroughly discussed. This study has also summarized the salient features and the requirements for applying various sensing and biosensing platforms and diverse immobilization techniques in ZEN detection. Finally, we have defined the performance of several electrochemical sensors applying diverse recognition elements couples with nanomaterials fabricated using various recognition elements coupled with nanomaterials (metal NPs, metal oxide nanoparticles (NPs), graphene, and CNT) the issues limiting development, and the forthcoming tasks in successful construction with the applied nanomaterials.

High-Fidelity and Simultaneous Sensing of Endogenous Mutant and Wild p53 Proteins for Precise Cancer Diagnosis and Drug Screening

The simultaneous sensing of endogenous wild and mutant proteins plays a critical role in disease diagnosis and drug screening, and this remains a major current challenge. Here, we present a new and highly specific target-triggered dual proximity ligation assay (dPLA) strategy for sensitive and simultaneous sensing of wild and mutant p53 proteins from cancer cells. Two proximity DNA probes bind the target protein to form the primer/circular DNA template complexes with two nicks in the presence of the hairpin and ssDNA connector sequences via the strand displacement reaction. Only when the two nicks are simultaneously ligated can the rolling circle amplification be triggered with high fidelity for yielding substantially enhanced fluorescence. By encoding the hairpin sequence, two distinct fluorescence signals can be generated for simultaneous detection of the wild and mutant p53 proteins. Importantly, our method significantly reduces the possibility of nonspecific ligation reactions by using two ligation nicks, which minimizes the background noise. With this dPLA method, the regulation transition of intracellular mutant p53 to wild p53 proteins upon anticancer drug treatment has also been demonstrated, highlighting its usefulness for potential early disease diagnosis and drug screening with high fidelity.