SERS-Based Immunoassay Enhanced with Silver Probe for Selective Separation and Detection of Alzheimer's Disease Biomarkers

Competitive electrochemical immunosensor for trace phosphorylated Tau181 analysis in plasma: Toward point-of-care technologies of Alzheimer's disease

Accurate detection of core Alzheimer's disease (AD) biomarkers in biofluids is crucial for identifying preclinical AD and predicting disease progression. Phosphorylated tau 181 (p-tau181), a key biomarker, holds promise for early diagnosis. This work presents a sensitive and rapid electrochemical immunosensor (EC-iSensor) based on screen-printed electrodes (SPEs) for p-tau181 quantification. Employing a competitive immunoassay format, the EC-iSensor utilizes biotinylated p-tau181 as a competitor against the target analyte for binding to immobilized capture antibodies. Signal transduction is achieved via horseradish peroxidase (HRP) and tetramethylbenzidine (TMB) substrate. The EC-iSensor exhibits a low detection limit of 1.91 fg/mL and a wide dynamic range spanning 6.97 fg/mL to 100 ng/mL in PBS. Furthermore, successful detection of p-tau181 in blood samples from AD patients demonstrated its practical applicability. This cost-effective SPE-based EC-iSensor offers a simple and highly sensitive platform for p-tau181 detection, presenting potential for point-of-care technologies (POCT) of AD.

Ultrasensitive Detection of Blood-Based Alzheimer's Disease Biomarkers: A Comprehensive SERS-Immunoassay Platform Enhanced by Machine Learning

Accurate and early disease detection is crucial for improving patient care, but traditional diagnostic methods often fail to identify diseases in their early stages, leading to delayed treatment outcomes. Early diagnosis using blood derivatives as a source for biomarkers is particularly important for managing Alzheimer's disease (AD). This study introduces a novel approach for the precise and ultrasensitive detection of multiple core AD biomarkers (Aβ40, Aβ42, p-tau, and t-tau) using surface-enhanced Raman spectroscopy (SERS) combined with machine-learning algorithms. Our method employs an antibody-immobilized aluminum SERS substrate, which offers high precision, sensitivity, and accuracy. The platform achieves an impressive detection limit in the attomolar (aM) range and spans a wide dynamic range from aM to micromolar (μM) concentrations. This ultrasensitive and specific SERS immunoassay platform shows promise for identifying mild cognitive impairment (MCI), a potential precursor to AD, from blood plasma. Machine-learning algorithms applied to the spectral data enhance the differentiation of MCI from AD and healthy controls, yielding excellent sensitivity and specificity. Our integrated SERS-machine-learning approach, with its interpretability, advances AD research and underscores the effectiveness of a cost-efficient, easy-to-prepare Al-SERS substrate for clinical AD detection.

SERS-Based Microfluidic Bioscreening Platform for Selective Detection of β-Amyloid Peptides

This study reports development of a microfluidic device for highly sensitive and selective detection of a β-amyloid peptide (Aβ1-42) in simulated cerebrospinal fluid, using surface-enhanced Raman spectroscopy (SERS). The device ensemble comprises a purine ligand (Pu) and its interaction with silver nanoparticles (AgNPs) to generate SERS hotspots. The low surface energy of the synthesized Pu ligand and high surface energy of AgNPs are utilized for the functionalization and formation of a Pu-AgNP SERS substrate. We have integrated a novel polydimethylsiloxane (PDMS) microfluidic device with Pu-AgNPs using a combination of photo- and soft lithography fabrication, sealed by thermal cross-linking with another layer of PDMS, to produce an effective screening platform for Aβ1-42. The SERS spectrum from the microfluidic device affords almost noise-free measurements, with excellent limit-of-detection values.

Unlocking early detection of Alzheimer's disease: The emerging role of nanomaterial-based optical sensors

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disorder that affects millions of individuals worldwide. Researchers have conducted numerous studies to find accurate biomarkers for early AD diagnosis and develop more effective treatments. The main pathological hallmarks of AD are amyloid beta and Tau proteins. Other biomarkers, such as DNA, RNA, and proteins, can also be helpful in early AD diagnosis. To diagnose and treat AD promptly, it is essential to accurately measure the concentration of biomarkers in the cerebrospinal fluid or blood. However, due to the low concentrations of these biomarkers in the body, highly sensitive analytical techniques are required. To date, sensors have become increasingly important due to their high sensitivity, swift detection, and adaptable manipulation features. These qualities make them an excellent substitute for conventional instruments. Nanomaterials are commonly employed in sensors to amplify signals and improve sensitivity. This review paper summarized the integration of nanomaterials in optical sensor systems, including colorimetric, fluorescent, and surface-enhanced Raman scattering sensors for AD biomarkers detection.

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience

Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

Unveiling brain disorders using liquid biopsy and Raman spectroscopy

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.

A SERS nanocellulose-paper-based analytical device for ultrasensitive detection of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), one of the most prevalent neurodegenerative diseases, results in severe cognitive decline and irreversible memory loss. Early detection of AD is significant to patients for personalized intervention since effective cure and treatment methods for AD are still lacking. Despite the severity of the disease, existing highly sensitive AD detection methods, including neuroimaging and brain deposit-positive lesion tests, are not suitable for screening purposes due to their high cost and complicated operation. Therefore, these methods are unsuitable for early detection, especially in low-resource settings. Although regular paper-based microfluidics are cost-efficient for AD detection, they are restricted by a poor limit of detection (LOD).

RESULTS

To address the above limitations, we report the ultrasensitive and low-cost nanocellulose paper (nanopaper)-based analytical microfluidic devices (NanoPADs) for detecting one of the promising AD blood biomarkers (glial fibrillary acidic protein, GFAP) using Surface-enhanced Raman scattering (SERS) immunoassay. Nanopaper offers advantages as a SERS substrate, such as an ultrasmooth surface, high optical transparency, and tunable chemical properties. We detected the target GFAP in artificial serum, achieving a LOD of 150 fg mL-1.

SIGNIFICANCE

The developed NanoPADs are distinguished by their cost-efficiency and ease of implementation, presenting a promising avenue for effective early detection of AD's GFAP biomarker with ultrahigh sensitivity. More importantly, our work provides the experimental routes for SERS-based immunoassay of biomarkers on NanoPADs for various diseases in the future.

Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects

Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer's and Parkinson's diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.

Functional Nanomaterials for the Diagnosis of Alzheimer's Disease: Recent Progress and Future Perspectives

Alzheimer's disease (AD) is one of the main causes of dementia worldwide, whereby neuronal death or malfunction leads to cognitive impairment in the elderly population. AD is highly prevalent, with increased projections over the next few decades. Yet current diagnostic methods for AD occur only after the presentation of clinical symptoms. Evidence in the literature points to potential mechanisms of AD induction beginning before clinical symptoms start to present, such as the formation of amyloid beta (Aβ) extracellular plaques and neurofibrillary tangles (NFTs). Biomarkers of AD, including Aβ 40, Aβ 42, and tau protein, amongst others, show promise for early AD diagnosis. Additional progress is made in the application of biosensing modalities to measure and detect significant changes in these AD biomarkers within patient samples, such as cerebral spinal fluid (CSF) and blood, serum, or plasma. Herein, a comprehensive review of the emerging nano-biomaterial approaches to develop biosensors for AD biomarkers' detection is provided. Advances, challenges, and potential of electrochemical, optical, and colorimetric biosensors, focusing on nanoparticle-based (metallic, magnetic, quantum dots) and nanostructure-based biomaterials are discussed. Finally, the criteria for incorporating these emerging nano-biomaterials in clinical settings are presented and assessed, as they hold great potential for enhancing early-onset AD diagnostics.

SERS-Based Optical Nanobiosensors for the Detection of Alzheimer's Disease

Alzheimer's disease (AD) is a leading cause of dementia, impacting millions worldwide. However, its complex neuropathologic features and heterogeneous pathophysiology present significant challenges for diagnosis and treatment. To address the urgent need for early AD diagnosis, this review focuses on surface-enhanced Raman scattering (SERS)-based biosensors, leveraging the excellent optical properties of nanomaterials to enhance detection performance. These highly sensitive and noninvasive biosensors offer opportunities for biomarker-driven clinical diagnostics and precision medicine. The review highlights various types of SERS-based biosensors targeting AD biomarkers, discussing their potential applications and contributions to AD diagnosis. Specific details about nanomaterials and targeted AD biomarkers are provided. Furthermore, the future research directions and challenges for improving AD marker detection using SERS sensors are outlined.

Electrochemical impedance-based biosensor for label-free determination of plasma P-tau181 levels for clinically accurate diagnosis of mild cognitive impairment and Alzheimer's disease

Plasma phosphorylated-tau threonine 181 (p-tau181) is a promising biomarker for predicting Alzheimer's disease (AD) and mild cognitive impairment (MCI), which is the symptomatic pre-dementia stage of AD. To date, there are limitations in the current diagnosis and classification of the two stages of MCI and AD in clinical practice remain a dilemma. In this study, we aimed to discriminate and diagnose patients with MCI, AD, and healthy participants based on the accurate, label-free, and ultrasensitive detection of p-tau181 levels in human clinical plasma samples using our developed electrochemical impedance-based biosensor, which allows to detect p-tau181 at a very low concentration of 0.92 fg mL^-1. Human plasma samples were collected from 20 patients with AD, 20 patients with MCI, and 20 individuals with healthy control. The change in charge-transfer resistance of the developed impedance-based biosensor caused by capturing p-tau181 in plasma samples was recorded to evaluate the determination of plasma p-tau181 levels in human clinical samples for discrimination and diagnosis of AD, MCI, and healthy control individuals, respectively. Receiver operating characteristic (ROC) curve, a standard analysis to judge the clinically diagnostic capability of our biosensor platform based on the estimated levels of plasma p-tau181, resulted a sensitivity of 95%, a specificity of 85%, the area under the ROC curve (AUC) value of 0.94 of the accuracy for discriminating AD patients from healthy controls; a sensitivity of 70%, a specificity of 70%, the AUC of 0.75 to discriminate MCI patients from healthy controls. Statistical analysis (one-way analysis of variance (ANOVA)) was used to compare the estimated plasma p-tau181 levels in clinical samples, indicated significantly higher for AD patients with healthy controls (***p ≤ 0.001), AD with MCI patients (***p ≤ 0.001), and MCI patients with healthy controls (*p ≤ 0.05), respectively. In addition, we compared our sensor to the global cognitive function scales and discovered that it performed noticeably improvement in diagnosing the stages of AD. These results demonstrated the good application of our developed electrochemical impedance-based biosensor in the identification of clinical disease stages. Moreover, in this study, a small dissociation constant (K_D) of 0.533 pM was first determined to evaluate the high binding affinity between the p-tau181 biomarker and its antibody, providing a reference parameter for future studies of the p-tau181 biomarker and AD.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

The mechanical, optical, and thermal properties of graphene influencing its pre-clinical use in treating neurological diseases

Rapid progress in nanotechnology has advanced fundamental neuroscience and innovative treatment using combined diagnostic and therapeutic applications. The atomic scale tunability of nanomaterials, which can interact with biological systems, has attracted interest in emerging multidisciplinary fields. Graphene, a two-dimensional nanocarbon, has gained increasing attention in neuroscience due to its unique honeycomb structure and functional properties. Hydrophobic planar sheets of graphene can be effectively loaded with aromatic molecules to produce a defect-free and stable dispersion. The optical and thermal properties of graphene make it suitable for biosensing and bioimaging applications. In addition, graphene and its derivatives functionalized with tailored bioactive molecules can cross the blood-brain barrier for drug delivery, substantially improving their biological property. Therefore, graphene-based materials have promising potential for possible application in neuroscience. Herein, we aimed to summarize the important properties of graphene materials required for their application in neuroscience, the interaction between graphene-based materials and various cells in the central and peripheral nervous systems, and their potential clinical applications in recording electrodes, drug delivery, treatment, and as nerve scaffolds for neurological diseases. Finally, we offer insights into the prospects and limitations to aid graphene development in neuroscience research and nanotherapeutics that can be used clinically.

Competitive fluorescent immunoassay for the ultrasensitive determination of amyloid beta peptide1-42 based on Ag@SiO2@N, S-GQD nanocomposites

A competitive fluorescent immunoassay is described for the ultrasensitive determination of amyloid beta peptide1-42 (Aβ1-42), a biomarker for early diagnosis of Alzheimer's disease. N, S-doped graphene quantum dots (N, S-GQDs) were freely assembled on the surface of Ag@SiO₂ nanoparticles to obtain a composite (Ag@SiO₂@N, S-GQD nanocomposite), which was successfully prepared and characterized. By theoretical study, the optical properties of nanocomposites are improved compared with GQDs, due to the advantages of combining N, S co-doping and metal-enhanced fluorescence (MEF) effect of Ag NPs. In addition, Aβ1-42 was modified by Ag@SiO₂@N, S-GQDs to prepare a probe with high photoluminescence properties (Ag@SiO₂@N, S-GQDs-Aβ1-42). In the presence of Aβ1-42, a competitive reaction towards anti-Aβ1-42 fixed on the ELISA plate was proceeded between Aβ1-42 and Ag@SiO₂@N, S-GQDs-Aβ1-42 by specific capture of antigen-antibody. The emission peak of Ag@SiO₂@N, S-GQDs-Aβ1-42 (400 nm emission) was used for the quantitative determination of Aβ1-42. Under the optimal conditions, the fluorescent immunoassay exhibited a linear range of 0.32 pg·mL^-1-5 ng·mL^-1 with a detection limit of 0.098 pg·mL^-1. The results show that the immunoassay has good analytical ability and can provide a new method for the clinical determination of Aβ1-42.

Construction of a novel nano-enzyme for ultrasensitive glucose detection with surface-enhanced Raman scattering

Fabricating more sensitive, stable and low-cost nanomaterials for the detection of glucose is important for the disease diagnosis and monitoring. Herein, we established a nanocomposite (polypyrrole bridging GO@Au@MnO₂) as a novel surface-enhanced Raman scattering (SERS) nanoprobe for the quantitative detection of glucose in trace serum. Each component in the nanocomposites played an irreplaceable role in SERS detection of glucose. Polypyrrole (PPy) could act as Raman signal and extra SERS signal molecules didn't need to be introduced; Graphene oxide (GO) and gold nanoparticles (Au NPs) could enhance Raman signal of PPy; Au NPs also acted as glucose oxidase, which can oxidize glucose to produce gluconic acid and hydrogen peroxide(H₂O₂); Manganese oxide (MnO₂) further enhanced Raman signal of PPy and responded to hydrogen peroxide, which will induce the decrease of Raman intensity of PPy. Thus, glucose can be quantified according to Raman signal output of PPy, which displayed a liner range from 1 to 10 μM, with detectable limit of 0.114 μM. Because of the merits in sensitivity, convenience and versatility, the novel method shows large potential space for disease-related substance detection in the future.

Evolution of Detecting Early Onset of Alzheimer's Disease: From Neuroimaging to Optical Immunoassays

Alzheimer's disease (AD) is a pathological disorder defined by the symptoms of memory loss and deterioration of cognitive abilities over time. Although the etiology is complex, it is mainly associated with the accumulation of toxic amyloid-β peptide (Aβ) aggregates and tau protein-induced neurofibrillary tangles (NFTs). Even now, creating non-invasive, sensitive, specific, and cost-effective diagnostic methods for AD remains challenging. Over the past few decades, polymers, and nanomaterials (e.g., nanodiamonds, nanogold, quantum dots) have become attractive and practical tools in nanomedicine for diagnosis and treatment. This review focuses on current developments in sensing methods such as enzyme-linked immunosorbent assay (ELISA) and surface-enhanced Raman scattering (SERS) to boost the sensitivity in detecting related biomarkers for AD. In addition, optical analysis platforms such as ELISA and SERS have found increasing popularity among researchers due to their excellent sensitivity and specificity, which may go as low as the femtomolar range. While ELISA offers easy technological usage and high throughput, SERS has the advantages of improved mobility, simple electrical equipment integration, and lower cost. Both portable optical sensing techniques are highly superior in terms of sensitivity, specificity, human application, and practicality, enabling the early identification of AD biomarkers.

A SERS Platform for Rapid Detection of Drug Resistance of Non-Candida albicans Using Fe3O4@PEI and Triangular Silver Nanoplates

Purpose

Candida infection has a high mortality rate, and the increasing prevalence of non-Candida albicans drug resistance in recent years poses a potential threat to human health. Non-Candida albicans has long culture cycles, and its firm cell walls making it difficult to isolate DNA for sequencing.

Materials and Methods

Fe₃O₄@PEI (PEI, polyvinyl imine) was mixed with clinical samples to form Fe₃O₄@PEI@non-Candida albicans and enriched them with magnets. Triangular silver nanoplates enhanced the surface-enhanced Raman scattering (SERS) signal. SERS was used to detect the fingerprint spectrum of non-Candida albicans. Then, orthogonal partial least squares discriminant analysis (OPLS-DA) was used to analyze the drug resistance of non-Candida albicans.

Results

SERS combined with OPLS-DA could well analyze the drug resistance of non-Candida albicans. Through 10-fold-cross validation, the accuracy of training and test data is greater than 99%, indicating that the model has good classification ability. We used SERS for the first time to detect the drug resistance of non-Candida albicans directly.

Conclusion

This approach can be utilized without causing damage to the cell wall and can be accomplished in as little as 90 minutes. It can provide timely guidance for the treatment of patients with good clinical application potential.

From Research to Diagnostic Application of Raman Spectroscopy in Neurosciences: Past and Perspectives

In recent years, Raman spectroscopy has been more and more frequently applied to address research questions in neuroscience. As a non-destructive technique based on inelastic scattering of photons, it can be used for a wide spectrum of applications including neurooncological tumor diagnostics or analysis of misfolded protein aggregates involved in neurodegenerative diseases. Progress in the technical development of this method allows for an increasingly detailed analysis of biological samples and may therefore open new fields of applications. The goal of our review is to provide an introduction into Raman scattering, its practical usage and also commonly associated pitfalls. Furthermore, intraoperative assessment of tumor recurrence using Raman based histology images as well as the search for non-invasive ways of diagnosis in neurodegenerative diseases are discussed. Some of the applications mentioned here may serve as a basis and possibly set the course for a future use of the technique in clinical practice. Covering a broad range of content, this overview can serve not only as a quick and accessible reference tool but also provide more in-depth information on a specific subtopic of interest.

Toward Sensitive and Reliable Surface-Enhanced Raman Scattering Imaging: From Rational Design to Biomedical Applications

Early specific detection through indicative biomarkers and precise visualization of lesion sites are urgent requirements for clinical disease diagnosis. However, current detection and optical imaging methods are insufficient for these demands. Molecular imaging technologies are being intensely studied for reliable medical diagnosis. In the past several decades, molecular imaging with surface-enhanced Raman scattering (SERS) has significant advances from analytical chemistry to medical science. SERS is the inelastic scattering generated from the interaction between photons and substances, presenting molecular structure information. The outstanding SERS virtues of high sensitivity, high specificity, and resistance to biointerference are highly advantageous for biomarker detection in a complex biological matrix. In this work, we review recent progress on the applications of SERS imaging in clinical diagnostics. With the assistance of SERS imaging, the detection of disease-related proteins, nucleic acids, small molecules, and pH of the cellular microenvironment can be implemented for adjuvant medical diagnosis. Moreover, multimodal imaging integrates the high penetration and high speed of other imaging modalities and imaging precision of SERS imaging, resulting in final complete and accurate imaging outcomes and exhibiting robust potential in the discrimination of pathological tissues and surgical navigation. As a promising molecular imaging technology, SERS imaging has achieved remarkable performance in clinical diagnostics and the biomedical realm. It is expected that this review will provide insights for further development of SERS imaging and promote the rapid progress and successful translation of advanced molecular imaging with clinical diagnostics.

Potential Role of Nanoparticles in Treating the Accumulation of Amyloid-Beta Peptide in Alzheimer's Patients

The disorder of Alzheimer's is marked by progressive pathophysiological neurodegeneration. The amino acid peptides in the amyloid plaques found in the brains of people with Alzheimer's disease (AD) are known as amyloid-beta (Aβ). Current treatments are not curative, and the effects associated with AD are reduced. Improving treatment results involved the targeting of drugs at optimum therapeutic concentration. Nanotechnology is seen as an unconventional, modern technology that plays a key role in the treatment of Alzheimer's disease. Using nanoparticles, molecular detection, effective drug targeting, and their combination offer high sensitivity. The aim of this review is to shed light on the function and successful role of nanoparticles to resolve Aβ aggregation and thus to help cure Alzheimer's disease. The analysis divides these nanoparticles into three categories: polymer, lipid, and gold nanoparticles. A thorough comparison was then made between the nanoparticles, which are used according to their role, properties, and size in the procedure. The nanoparticles can prevent the accumulation of Aβ during the efficient delivery of the drug to the cells to treat Alzheimer's disease. Furthermore, this comparison demonstrated the ability of these nanoparticles to deal efficiently with Alzheimer's disease. The role of these nanoparticles varied from delivering the drug to brain cells to dealing with the disease-causing peptide.