Using Graphene-Based Biosensors to Detect Dopamine for Efficient Parkinson's Disease Diagnostics

Advancing Biosensing Frontiers Through Gold Nanoparticle Engineering: Synthesis Strategies and Detection Paradigms

Gold Nanoparticles (GNPs) play a pivotal role in nanobiotechnology because of their distinct physicochemical traits, such as optical properties, compatibility with biological systems, and their ability to be easily functionalized. The top-down and bottom-up approaches are for the synthesis of GNPs. There are various chemical, physical, and green synthesis techniques, such as chemical reduction, seed-mediated growth, physical ablation method, pyrolysis, sputtering, etc. are some methods for the synthesis of GNPs. The use of plants, algae, fungi, and other microorganisms has recently arisen as a new approach for the eco-friendly synthesis with precise control over NP size, shape, and surface properties. The functionalization strategies involving biomolecules, polymers, and ligands enhance their stability and target specificity, facilitating their integration into biosensors. The detection of biomolecules, pathogens, and environmental toxins with high sensitivity and accuracy is facilitated by multiple signals such as localized surface plasmon resonance (LSPR), alterations in color, and electrochemical characteristics. Furthermore, their role in point-of-care diagnostics, drug delivery, and imaging underscores their versatility in biomedical applications. This review provides a comprehensive overview of recent advancements in the synthesis, functionalization, and GNPs-based biosensors. In addition, the review highlights recent advancements, challenges, and future prospects of GNPs in biosensing and nanomedicine, offering an understanding of diagnostics and therapeutic monitoring. The key challenges include stability, reproducibility, and scalability, and the future focuses on green synthesis with enhanced sensitivity and multiplexed biosensing applications.

Biosensors for Early Detection of Parkinson's Disease: Principles, Applications, and Future Prospects

Parkinson's disease (PD), a neurodegenerative disorder marked by the progressive loss of dopaminergic neurons in the substantia nigra, imposes substantial economic burdens, including both direct and indirect costs. The medical community currently lacks a definitive cure for Parkinson's disease, and early detection is crucial for timely intervention and disease management. As innovative diagnostic tools, biosensors have shown great potential in detecting PD at its early stages. This review comprehensively summarizes recent advances in biosensors for the early detection of PD, with a particular focus on the detection of two key biomarkers: dopamine (DA) and α-synuclein (α-syn). Furthermore, it illustrates a variety of nanotechnology-based biosensors, including optical, electrochemical, and transistor biosensors, detailing their underlying principles, advantages, limitations, and applications in PD detection. Moreover, the review explores the challenges and prospects of advancing biosensors for early PD diagnosis.

Electrochemical biosensors in early detection of Parkinson disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting the motor system, with symptoms including tremors, rigidity, bradykinesia, and postural instability. Affecting over six million people globally, PD's pathophysiology is marked by the loss of dopaminergic neurons in the substantia nigra. Early diagnosis is crucial for effective management, yet current methods are limited by low sensitivity, high cost, and the need for advanced equipment. Electrochemical biosensors have emerged as promising tools for early PD diagnosis, converting biological reactions into measurable electrical signals for evaluating PD biomarkers. Advances in nanotechnology and material science have led to innovative sensing platforms with enhanced sensitivity and selectivity. Key biomarkers such as alpha-synuclein (α-syn), dopamine (DA), and microRNAs (miRNAs) have been targeted using these biosensors. For instance, gold nanoparticle-modified graphene immunosensors have shown ultra-sensitive detection of α-syn, while graphene-based biosensors have demonstrated high sensitivity for DA detection. Additionally, nanobiosensors for miR-195 and electrochemical aptasensors have shown potential for early PD diagnosis. The integration of nanomaterials like gold nanoparticles, quantum dots, and carbon nanotubes has further advanced the field, enhancing electrochemical activity and sensitivity. These developments offer a reliable, rapid, and cost-effective approach for early PD diagnosis, paving the way for better management and treatment. Continued research is essential for the commercialization and clinical integration of these biosensors, ultimately improving patient outcomes.

Sensing the Future-Frontiers in Biosensors: Exploring Classifications, Principles, and Recent Advances

Biosensors are transforming healthcare by delivering swift, precise, and economical diagnostic solutions. These analytical instruments combine biological indicators with physical transducers to identify and quantify biomarkers, thereby improving illness detection, management, and patient surveillance. Biosensors are widely utilized in healthcare for the diagnosis of chronic and infectious diseases, tailored treatment, and real-time health monitoring. This thorough overview examines several categories of biosensors and their uses in the detection of numerous biomarkers, including glucose, proteins, nucleic acids, and infections. Biosensors are commonly classified based on the type of transducer employed or the specific biorecognition element utilized. This review introduces a novel classification based on substrate morphology, offering a comprehensive perspective on biosensor categorization. Considerable emphasis is placed on the advancement of point-of-care biosensors, facilitating decentralized diagnostics and alleviating the strain on centralized healthcare systems. Recent advancements in nanotechnology have significantly improved the sensitivity, selectivity, and downsizing of biosensors, rendering them more efficient and accessible. The study examines problems such as stability, reproducibility, and regulatory approval that must be addressed to enable the widespread implementation of biosensors in clinical environments. The study examines the amalgamation of biosensors with wearable devices and smartphones, emphasizing the prospects for ongoing health surveillance and individualized medical care. This viewpoint clarifies the distinct types of biosensors and their particular roles, together with recent developments in the "smart biosensor" sector, facilitated by artificial intelligence and the Internet of Medical Things (IoMT). This novel approach seeks to deliver a comprehensive evaluation of the present condition of biosensor technology in healthcare, recent developments, and prospective paths, emphasizing their significance in influencing the future of medical diagnostics and patient care.

Snowflake Iron Oxide Architectures: Synthesis and Electrochemical Applications

The synthesis and characterization of iron oxide nanostructures, specifically snowflake architecture, are investigated for their potential applications in electrochemical sensing systems. A Raman spectroscopy analysis reveals phase diversity in the synthesized powders. The pH of the synthesis affects the formation of the hematite (α-Fe2O3) and goethite (α-FeOOH). Scanning electron microscopy (SEM) images confirm the distinct morphologies of the particles, which are selectively obtained through recrystallization during the elongated reaction time. An electrochemical analysis demonstrates the differing behaviors of the particles, with synthesis pH affecting the electrochemical activity and surface area differently for each shape. Cyclic voltammetry measurements reveal reversible dopamine detection processes, with snowflake iron oxide showing lower detection limits than a mixture of snowflakes and cube-like particles. This research contributes to understanding the relationship between iron oxide nanomaterials' structural, morphological, and electrochemical properties. It offers practical insights into their potential applications in sensor technology, particularly dopamine detection, with implications for biomedical and environmental monitoring.

Common Transition Metal Oxide Nanomaterials in Electrochemical Sensors for the Diagnosis of Monoamine Neurotransmitter‐Related Disorders

Monoamine neurotransmitters are essential for learning, mental alertness, emotions, and blood flow, among other functions. Fatal neurological disorders that signal the imbalance of these biomolecules in the human system include Parkinson's disease, myocardial infarction, Alzheimer's disease, hypoglycemia, Schizophrenia, and a host of other ailments. The diagnosis of these monoamine neurotransmitter‐related conditions revolves around the development of analytical tools with high sensitivity for the four major monoamine neurotransmitters namely dopamine, epinephrine, norepinephrine, and serotonin. The application of electrochemical sensors made from notable metal oxide nanoparticles or composites containing the metal oxide nanoparticles for the detection of these monoamine neurotransmitters was discussed herein. More importantly, the feasibility of the application of the ZnO, CuO, and TiO2 nanoparticle‐based electrochemical sensors for a comprehensive diagnosis of monoamine neurotransmitter‐related conditions was critically investigated in this review.

Graphene and Natural Products: A Review of Antioxidant Properties in Graphene Oxide Reduction

This review article addresses the antioxidant properties of different natural products, including ascorbic acid, gallic acid, oxalic acid, L-glutathione (GSH), bacteriorhodopsin, green tea polyphenols, glucose, hydroxycinnamic acid, ethanoic acid, betanin, and L-glutathione, in the reduction of graphene oxide (rGO). rGO can cause damage to cells, including oxidative stress and inflammation, limiting its application in different sectors that use graphene, such as technologies used in medicine and dentistry. The natural substances reviewed have properties that help reduce this damage, neutralizing free radicals and maintaining cellular integrity. This survey demonstrates that the combination of these antioxidant compounds can be an effective strategy to minimize the harmful effects of rGO and promote cellular health.

A review on the new age methodologies for early detection of Alzheimer's and Parkinson's disease

BACKGROUNDS

Neurodegenerative diseases (NDDs) such as Alzheimer's (AD) and Parkinson's (PD) are often diagnosed late, impeding effective treatment; therefore, early detection is imperative. Modern methodologies can serve a pivotal role in fulfilling the crucial need for timely detection and intervention in this context.

OBJECTIVES

Evaluate early detection's significance and summarize key technologies (biomarkers, neuroimaging, AI/ML, genetics, digital health) for enhanced diagnostic strategies in AD and PD.

METHODS

This study employs a focused descriptive review approach, encompassing analysis of peer-reviewed articles and clinical trials from existing literature, to provide a nuanced exploration of the subject matter.

FINDINGS

This review underscores the efficacy of non-invasive biomarkers, biosensors and emerging promising technologies for advancing early diagnosis of AD and PD.

CONCLUSION

The landscape of early NDD detection has been reshaped by technology, yet challenges persist, encompassing the domains of validation and ethics. A collaborative effort between medical professionals, researchers and technologists is imperative to effectively address and combat NDDs.

Employing nano-enabled artificial intelligence (AI)-based smart technologies for prediction, screening, and detection of cancer

Cancer has been classified as a diverse illness with a wide range of subgroups. Its early identification and prognosis, which have become a requirement of cancer research, are essential for clinical treatment. Patients have already benefited greatly from the use of artificial intelligence (AI), machine learning (ML), and deep learning (DL) algorithms in the field of healthcare. AI simulates and combines data, pre-programmed rules, and knowledge to produce predictions. Data are used to improve efficiency across several pursuits and tasks through the art of ML. DL is a larger family of ML methods based on representational learning and simulated neural networks. Support vector machines, convulsion neural networks, and artificial neural networks, among others, have been widely used in cancer research to construct prediction models that enable precise and effective decision-making. Although using these innovative methods can enhance our comprehension of how cancer progresses, further validation is required before these techniques can be used in routine clinical practice. We cover contemporary methods used in the modelling of cancer development in this article. The presented prediction models are built using a variety of guided ML approaches, as well as numerous input attributes and data collections. Early identification and cost-effective detection of cancer's progression are equally necessary for successful treatment of the disease. Smart material-based detection techniques can give end consumers a portable, affordable instrument to easily detect and monitor their health issues without the need for specialized knowledge. Owing to their cost-effectiveness, excellent sensitivity, multimodal detection capacity, and miniaturization aptitude, two-dimensional (2D) materials have a lot of prospects for clinical examination of various compounds as well as cancer biomarkers. The effectiveness of traditional devices is moving faster towards more useful techniques thanks to developments in 2D material-based biosensors/sensors. The most current developments in the design of 2D material-based biosensors/sensors-the next wave of cancer screening instruments-are also outlined in this article.

Recent Advances in Metallic Nanostructures-assisted Biosensors for Medical Diagnosis and Therapy

The field of nanotechnology has witnessed remarkable progress in recent years, particularly in its application to medical diagnosis and therapy. Metallic nanostructures-assisted biosensors have emerged as a powerful and versatile platform, offering unprecedented opportunities for sensitive, specific, and minimally invasive diagnostic techniques, as well as innovative therapeutic interventions. These biosensors exploit the molecular interactions occurring between biomolecules, such as antibodies, enzymes, aptamers, or nucleic acids, and metallic surfaces to induce observable alterations in multiple physical attributes, encompassing electrical, optical, colorimetric, and electrochemical signals. These interactions yield measurable data concerning the existence and concentration of particular biomolecules. The inherent characteristics of metal nanostructures, such as conductivity, plasmon resonance, and catalytic activity, serve to amplify both sensitivity and specificity in these biosensors. This review provides an in-depth exploration of the latest advancements in metallic nanostructures-assisted biosensors, highlighting their transformative impact on medical science and envisioning their potential in shaping the future of personalized healthcare.

Laser Scribing Turns Plastic Waste into a Biosensor via the Restructuration of Nanocarbon Composites for Noninvasive Dopamine Detection

The development of affordable and compact noninvasive point-of-care (POC) dopamine biosensors for the next generation is currently a major and challenging problem. In this context, a highly sensitive, selective, and low-cost sensing probe is developed by a simple one-step laser-scribing process of plastic waste. A flexible POC device is developed as a prototype and shows a highly specific response to dopamine in the real sample (urine) as low as 100 pmol/L in a broad linear range of 10-10-10-4 mol/L. The 3D topological feature, carrier kinetics, and surface chemistry are found to improve with the formation of high-density metal-embedded graphene-foam composite driven by laser irradiation on the plastic-waste surface. The development of various kinds of flexible and tunable biosensors by plastic waste is now possible thanks to the success of this simple, but effective, laser-scribing technique, which is capable of modifying the matrix's electronic and chemical composition.

Neural stem cells for Parkinson's disease management: Challenges, nanobased support, and prospects

Parkinson's disease (PD), characterized by loss of nigrostriatal dopaminergic neurons, is one of the most predominant neurodegenerative diseases affecting the elderly population worldwide. The concept of stem cell therapy in managing neurodegenerative diseases has evolved over the years and has recently rapidly progressed. Neural stem cells (NSCs) have a few key features, including self-renewal, proliferation, and multipotency, which make them a promising agent targeting neurodegeneration. It is generally agreed that challenges for NSC-based therapy are present at every stage of the transplantation process, including preoperative cell preparation and quality control, perioperative procedures, and postoperative graft preservation, adherence, and overall therapy success. In this review, we provided a comprehensive, careful, and critical discussion of experimental and clinical data alongside the pros and cons of NSC-based therapy in PD. Given the state-of-the-art accomplishments of stem cell therapy, gene therapy, and nanotechnology, we shed light on the perspective of complementing the advantages of each process by developing nano-stem cell therapy, which is currently a research hotspot. Although various obstacles and challenges remain, nano-stem cell therapy holds promise to cure PD, however, continuous improvement and development from the stage of laboratory experiments to the clinical application are necessary.

Development of Two-Dimensional Functional Nanomaterials for Biosensor Applications: Opportunities, Challenges, and Future Prospects

New possibilities for the development of biosensors that are ready to be implemented in the field have emerged thanks to the recent progress of functional nanomaterials and the careful engineering of nanostructures. Two-dimensional (2D) nanomaterials have exceptional physical, chemical, highly anisotropic, chemically active, and mechanical capabilities due to their ultra-thin structures. The diversity of the high surface area, layered topologies, and porosity found in 2D nanomaterials makes them amenable to being engineered with surface characteristics that make it possible for targeted identification. By integrating the distinctive features of several varieties of nanostructures and employing them as scaffolds for bimolecular assemblies, biosensing platforms with improved reliability, selectivity, and sensitivity for the identification of a plethora of analytes can be developed. In this review, we compile a number of approaches to using 2D nanomaterials for biomolecule detection. Subsequently, we summarize the advantages and disadvantages of using 2D nanomaterials in biosensing. Finally, both the opportunities and the challenges that exist within this potentially fruitful subject are discussed. This review will assist readers in understanding the synthesis of 2D nanomaterials, their alteration by enzymes and composite materials, and the implementation of 2D material-based biosensors for efficient bioanalysis and disease diagnosis.

Neuroprotective and Anti-Inflammatory Effects of Pioglitazone on Parkinson's Disease: A Comprehensive Narrative Review of Clinical and Experimental Findings

Parkinson's disease (PD) is a chronic and progressive neurological disorder characterized by the degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc). The pathogenesis of PD is strongly related to mitochondrial dysfunction, oxidative stress, and neuroinflammation. This indicates that PD can be treated with anti-oxidative substitutes and anti-inflammatory compounds. The neuroprotective and anti-inflammatory effects of peroxisome proliferator-activated receptor γ (PPAR-γ) agonists decrease cell death and halt the increase in neurodegeneration, which is why they have been given a lot of importance in research. Antidiabetic and anti-inflammatory effects have been observed to be generated by pioglitazone (PG), a selective peroxisome proliferator-activated receptor γ (PPAR-γ) agonist that regulates neural plasticity in various neurodegenerative disorders. The neuroprotective and anti-inflammatory effects of PG are assessed in this article. It was found that the patients with DM who received PG treatment were noticeably at a lower risk of PD. However, some clinical studies have not proven a strong link between the therapeutic effects of PG on PD. As per suggestions of preclinical studies, the therapeutic effects of PG treatment include; increased life expectancy of neurons, decreased oxidative stress, halted microglial activity, lower inflammation (reduced NF-κB, COX-2, and iNOS), reduced mitochondrial dysfunction, rise in motor function (motor agility) and non-motor function (lowered cognitive dysfunction). In conclusion, we determined that PG exerts neuroprotective and anti-inflammatory effects in PD models and it can be considered a potential therapeutic candidate for PD.

Advances in graphene-based nanoplatforms and their application in Parkinson's disease

Graphene and GBNs offer diverse PD management modalities by targeting neurodegeneration, exerting regenerative properties and their use as carriers, biosensors, and imaging agents.

Nanomaterial-Based Electrochemical Nanodiagnostics for Human and Gut Metabolites Diagnostics: Recent Advances and Challenges

Metabolites are the intermediatory products of metabolic processes catalyzed by numerous enzymes found inside the cells. Detecting clinically relevant metabolites is important to understand their physiological and biological functions along with the evolving medical diagnostics. Rapid advances in detecting the tiny metabolites such as biomarkers that signify disease hallmarks have an immense need for high-performance identifying techniques. Low concentrations are found in biological fluids because the metabolites are difficult to dissolve in an aqueous medium. Therefore, the selective and sensitive study of metabolites as biomarkers in biological fluids is problematic. The different non-electrochemical and conventional methods need a long time of analysis, long sampling, high maintenance costs, and costly instrumentation. Hence, employing electrochemical techniques in clinical examination could efficiently meet the requirements of fully automated, inexpensive, specific, and quick means of biomarker detection. The electrochemical methods are broadly utilized in several emerging and established technologies, and electrochemical biosensors are employed to detect different metabolites. This review describes the advancement in electrochemical sensors developed for clinically associated human metabolites, including glucose, lactose, uric acid, urea, cholesterol, etc., and gut metabolites such as TMAO, TMA, and indole derivatives. Different sensing techniques are evaluated for their potential to achieve relevant degrees of multiplexing, specificity, and sensitivity limits. Moreover, we have also focused on the opportunities and remaining challenges for integrating the electrochemical sensor into the point-of-care (POC) devices.

Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare

Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subsets, including machine learning (ML), deep learning (DL), conventional neural networks, fuzzy logic, and speech recognition, with unique capabilities and functionalities that can improve the performances of modern medical sciences. Such intelligent systems simplify human intervention in clinical diagnosis, medical imaging, and decision-making ability. In the same era, the Internet of Medical Things (IoMT) emerges as a next-generation bio-analytical tool that combines network-linked biomedical devices with a software application for advancing human health. In this review, we discuss the importance of AI in improving the capabilities of IoMT and point-of-care (POC) devices used in advanced healthcare sectors such as cardiac measurement, cancer diagnosis, and diabetes management. The role of AI in supporting advanced robotic surgeries developed for advanced biomedical applications is also discussed in this article. The position and importance of AI in improving the functionality, detection accuracy, decision-making ability of IoMT devices, and evaluation of associated risks assessment is discussed carefully and critically in this review. This review also encompasses the technological and engineering challenges and prospects for AI-based cloud-integrated personalized IoMT devices for designing efficient POC biomedical systems suitable for next-generation intelligent healthcare.

Fluorescent Biosensors for the Detection of Viruses Using Graphene and Two-Dimensional Carbon Nanomaterials

Two-dimensional carbon nanomaterials have been commonly employed in the field of biosensors to improve their sensitivity/limits of detection and shorten the analysis time. These nanomaterials act as efficient transducers because of their unique characteristics, such as high surface area and optical, electrical, and magnetic properties, which in turn have been exploited to create simple, quick, and low-cost biosensing platforms. In this review, graphene and two-dimensional carbon material-based fluorescent biosensors are covered between 2010 and 2021, for the detection of different human viruses. This review specifically focuses on the new developments in graphene and two-dimensional carbon nanomaterials for fluorescent biosensing based on the Förster resonance energy transfer (FRET) mechanism. The high-efficiency quenching capability of graphene via the FRET mechanism enhances the fluorescent-based biosensors. The review provides a comprehensive reference for the different types of carbon nanomaterials employed for the detection of viruses such as Rotavirus, Ebola virus, Influenza virus H3N2, HIV, Hepatitis C virus (HCV), and Hepatitis B virus (HBV). This review covers the various multiplexing detection technologies as a new direction in the development of biosensing platforms for virus detection. At the end of the review, the different challenges in the use of fluorescent biosensors, as well as some insights into how to overcome them, are highlighted.

CRISPR-Cas9-Based Technology and Its Relevance to Gene Editing in Parkinson's Disease

Parkinson's disease (PD) and other chronic and debilitating neurodegenerative diseases (NDs) impose a substantial medical, emotional, and financial burden on individuals and society. The origin of PD is unknown due to a complex combination of hereditary and environmental risk factors. However, over the last several decades, a significant amount of available data from clinical and experimental studies has implicated neuroinflammation, oxidative stress, dysregulated protein degradation, and mitochondrial dysfunction as the primary causes of PD neurodegeneration. The new gene-editing techniques hold great promise for research and therapy of NDs, such as PD, for which there are currently no effective disease-modifying treatments. As a result, gene therapy may offer new treatment options, transforming our ability to treat this disease. We present a detailed overview of novel gene-editing delivery vehicles, which is essential for their successful implementation in both cutting-edge research and prospective therapeutics. Moreover, we review the most recent advancements in CRISPR-based applications and gene therapies for a better understanding of treating PD. We explore the benefits and drawbacks of using them for a range of gene-editing applications in the brain, emphasizing some fascinating possibilities.

Recent Advances in Electrochemical Biosensors for the Detection of Salmonellosis: Current Prospective and Challenges

Salmonellosis is a major cause of foodborne infections, caused by Salmonella, posing a major health risk. It possesses the ability to infiltrate the food supply chain at any point throughout the manufacturing, distribution, processing or quality control process. Salmonella infection has increased severely and requires effective and efficient methods for early monitoring and detection. Traditional methods, such as real-time polymerase chain reaction and culture plate, consume a lot of time and are labor-intensive. Therefore, new quick detection methods for on-field applications are urgently needed. Biosensors provide consumer-friendly approaches for quick on-field diagnoses. In the last few years, there has been a surge in research into the creation of reliable and advanced electrochemical sensors for the detection of Salmonella strains in food samples. Electrochemical sensors provide extensive accuracy and reproducible results. Herein, we present a comprehensive overview of electrochemical sensors for the detection of Salmonella by focusing on various mechanisms of electrochemical transducer. Further, we explain new-generation biosensors (microfluidics, CRISPR- and IOT-based) for point-of care applications. This review also highlights the limitations of developing biosensors in Salmonella detection and future possibilities.

Energy-Efficient, On-Demand Activation of Biosensor Arrays for Long-Term Continuous Health Monitoring

Wearable biosensors for continuous health monitoring, particularly those used for glucose detection, have a limited operational lifetime due to biodegradation and fouling. As a result, patients must change sensors frequently, increasing cost and patient discomfort. Arrays of multiple sensors, where the individual devices can be activated on demand, increase overall operational longevity, thereby reducing cost and improving patient outcomes. This work demonstrates the feasibility of this approach via decomposition of combustible nitrocellulose membranes that protect the individual sensors from exposure to bioanalytes using a current pulse. Metal contacts, connected by graphene-loaded PEDOT:PSS polymer on the surface of the membrane, deliver the required energy to decompose the membrane. Nitrocellulose membranes with a thickness of less than 1 µm consistently transfer on to polydimethylsiloxane (PDMS) wells. An electrical energy as low as 68 mJ has been shown to suffice for membrane decomposition.

Current Advancements and Future Road Map to Develop ASSURED Microfluidic Biosensors for Infectious and Non-Infectious Diseases

Better diagnostics are always essential for the treatment and prevention of a disease. Existing technologies for detecting infectious and non-infectious diseases are mostly tedious, expensive, and do not meet the World Health Organization's (WHO) ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end user) criteria. Hence, more accurate, sensitive, and faster diagnostic technologies that meet the ASSURED criteria are highly required for timely and evidenced-based treatment. Presently, the diagnostics industry is finding interest in microfluidics-based biosensors, as this integration comprises all qualities, such as reduction in the size of the equipment, rapid turnaround time, possibility of parallel multiple analysis or multiplexing, etc. Microfluidics deal with the manipulation/analysis of fluid within micrometer-sized channels. Biosensors comprise biomolecules immobilized on a physicochemical transducer for the detection of a specific analyte. In this review article, we provide an outline of the history of microfluidics, current practices in the selection of materials in microfluidics, and how and where microfluidics-based biosensors have been used for the diagnosis of infectious and non-infectious diseases. Our inclination in this review article is toward the employment of microfluidics-based biosensors for the improvement of already existing/traditional methods in order to reduce efforts without compromising the accuracy of the diagnostic test. This article also suggests the possible improvements required in microfluidic chip-based biosensors in order to meet the ASSURED criteria.

Wearable Electrochemical Sensors in Parkinson's Disease

Parkinson’s disease (PD) is a neurodegenerative disorder associated with widespread aggregation of α-synuclein and dopaminergic neuronal loss in the substantia nigra pars compacta. As a result, striatal dopaminergic denervation leads to functional changes in the cortico-basal-ganglia-thalamo-cortical loop, which in turn cause most of the parkinsonian signs and symptoms. Despite tremendous advances in the field in the last two decades, the overall management (i.e., diagnosis and follow-up) of patients with PD remains largely based on clinical procedures. Accordingly, a relevant advance in the field would require the development of innovative biomarkers for PD. Recently, the development of miniaturized electrochemical sensors has opened new opportunities in the clinical management of PD thanks to wearable devices able to detect specific biological molecules from various body fluids. We here first summarize the main wearable electrochemical technologies currently available and their possible use as medical devices. Then, we critically discuss the possible strengths and weaknesses of wearable electrochemical devices in the management of chronic diseases including PD. Finally, we speculate about possible future applications of wearable electrochemical sensors in PD, such as the attractive opportunity for personalized closed-loop therapeutic approaches.

MXene-modified molecularly imprinted polymer as an artificial bio-recognition platform for efficient electrochemical sensing: progress and perspectives

The development of efficient electrochemical sensors of exceptional features, molecularly imprinted polymers (MIPs) have been extensively utilized due to their great vitality as an alternative to bio-recognition elements. MIPs as...