Highly Sensitive Flexible SERS-Based Sensing Platform for Detection of COVID-19

Biosensors for metastatic cancer cell detection

Early detection and effective cancer treatment are critical to improving metastatic cancer cell diagnosis and management today. In particular, accurate qualitative diagnosis of metastatic cancer cell represents an important step in the diagnosis of cancer. Today, biosensors have been widely developed due to the daily need to measure different chemical and biological species. Biosensors are utilized to quantify chemical and biological phenomena by generating signals that are directly proportional to the quantity of the analyte present in the reaction. Biosensors are widely used in disease control, drug delivery, infection detection, detection of pathogenic microorganisms, and markers that indicate a specific disease in the body. These devices have been especially popular in the field of metastatic cancer cell diagnosis and treatment due to their portability, high sensitivity, high specificity, ease of use and short response time. This article examines biosensors for metastatic cancer cells. It also studies metastatic cancer cells and the mechanism of metastasis. Finally, the function of biosensors and biomarkers in metastatic cancer cells is investigated.

Applications of peptides in nanosystems for diagnosing and managing bacterial sepsis

Sepsis represents a critical medical condition stemming from an imbalanced host immune response to infections, which is linked to a significant burden of disease. Despite substantial efforts in laboratory and clinical research, sepsis remains a prominent contributor to mortality worldwide. Nanotechnology presents innovative opportunities for the advancement of sepsis diagnosis and treatment. Due to their unique properties, including diversity, ease of synthesis, biocompatibility, high specificity, and excellent pharmacological efficacy, peptides hold great potential as part of nanotechnology approaches against sepsis. Herein, we present a comprehensive and up-to-date review of the applications of peptides in nanosystems for combating sepsis, with the potential to expedite diagnosis and enhance management outcomes. Firstly, sepsis pathophysiology, antisepsis drug targets, current modalities in management and diagnosis with their limitations, and the potential of peptides to advance the diagnosis and management of sepsis have been adequately addressed. The applications have been organized into diagnostic or managing applications, with the last one being further sub-organized into nano-delivered bioactive peptides with antimicrobial or anti-inflammatory activity, peptides as targeting moieties on the surface of nanosystems against sepsis, and peptides as nanocarriers for antisepsis agents. The studies have been grouped thematically and discussed, emphasizing the constructed nanosystem, physicochemical properties, and peptide-imparted enhancement in diagnostic and therapeutic efficacy. The strengths, limitations, and research gaps in each section have been elaborated. Finally, current challenges and potential future paths to enhance the use of peptides in nanosystems for combating sepsis have been deliberately spotlighted. This review reaffirms peptides' potential as promising biomaterials within nanotechnology strategies aimed at improving sepsis diagnosis and management.

Development of a SERS aptasensor for the determination of L-theanine using a noble metal nanoparticle-magnetic nanospheres composite

An ultrasensitive surface-enhanced Raman spectroscopy (SERS) aptamer sensor (aptasensor) using a noble metal nanoparticle-magnetic nanospheres composite was developed for L-theanine detection. It makes use of Fe3O4@Au MNPs and Au@Ag NPs embedded with the Raman reporter 4-mercaptobenzoic acid (4MBA). Au@4MBA@Ag NPs modified by aptamer and Fe3O4@Au MNPs modified by cDNA created the aptasensor with the strongest Raman signal of 4MBA through the specific binding of the aptamer. With the preferred binding of L-theanine aptamer to L-theanine, Au@4MBA@Ag NPs were released from Fe3O4@Au MNPs, causing a linear decrease in SERS intensity to achieve the SERS detection of the L-theanine. The SERS peak of 4MBA at 1078 cm-1 was used for quantitative determination. SERS intensity showed a good log-linear relationship within the range 10-10 to 10-6 M of L-theanine. The aptasensor has a high selectivity for L-theanine compared with other twelve tested analytes. Hence, this aptasensor is a promising analytical tool for L-theanine detection. The developed method was applied to the analysis of real samples, demonstrating excellent performance. The comparison with the standard liquid chromatography mass spectrometry method showed an error within 20%.

Recent Progress in Prompt Molecular Detection of Exosomes Using CRISPR/Cas and Microfluidic-Assisted Approaches Toward Smart Cancer Diagnosis and Analysis

Exosomes are essential indicators of molecular mechanisms involved in interacting with cancer cells and the tumor environment. As nanostructures based on lipids and nucleic acids, exosomes provide a communication pathway for information transfer by transporting biomolecules from the target cell to other cells. Importantly, these extracellular vesicles are released into the bloodstream by the most invasive cells, i. e., cancer cells; in this way, they could be considered a promising specific biomarker for cancer diagnosis. In this matter, CRISPR-Cas systems and microfluidic approaches could be considered practical tools for cancer diagnosis and understanding cancer biology. CRISPR-Cas systems, as a genome editing approach, provide a way to inactivate or even remove a target gene from the cell without affecting intracellular mechanisms. These practical systems provide vital information about the factors involved in cancer development that could lead to more effective cancer treatment. Meanwhile, microfluidic approaches can also significantly benefit cancer research due to their proper sensitivity, high throughput, low material consumption, low cost, and advanced spatial and temporal control. Thereby, employing CRISPR-Cas- and microfluidics-based approaches toward exosome monitoring could be considered a valuable source of information for cancer therapy and diagnosis. This review assesses the recent progress in these promising diagnosis approaches toward accurate cancer therapy and in-depth study of cancer cell behavior.

Bioresource Polymer Composite for Energy Generation and Storage: Developments and Trends

The ever-growing demand of human society for clean and reliable energy sources spurred a substantial academic interest in exploring the potential of biological resources for developing energy generation and storage systems. As a result, alternative energy sources are needed in populous developing countries to compensate for energy deficits in an environmentally sustainable manner. This review aims to evaluate and summarize the recent progress in bio-based polymer composites (PCs) for energy generation and storage. The articulated review provides an overview of energy storage systems, e. g., supercapacitors and batteries, and discusses the future possibilities of various solar cells (SCs), using both past research progress and possible future developments as a basis for discussion. These studies examine systematic and sequential advances in different generations of SCs. Developing novel PCs that are efficient, stable, and cost-effective is of utmost importance. In addition, the current state of high-performance equipment for each of the technologies is evaluated in detail. We also discuss the prospects, future trends, and opportunities regarding using bioresources for energy generation and storage, as well as the development of low-cost and efficient PCs for SCs.

Recent advances in point-of-care testing of COVID-19

Advances in microfluidic device miniaturization and system integration contribute to the development of portable, handheld, and smartphone-compatible devices. These advancements in diagnostics have the potential to revolutionize the approach to detect and respond to future pandemics. Accordingly, herein, recent advances in point-of-care testing (POCT) of coronavirus disease 2019 (COVID-19) using various microdevices, including lateral flow assay strips, vertical flow assay strips, microfluidic channels, and paper-based microfluidic devices, are reviewed. However, visual determination of the diagnostic results using only microdevices leads to many false-negative results due to the limited detection sensitivities of these devices. Several POCT systems comprising microdevices integrated with portable optical readers have been developed to address this issue. Since the outbreak of COVID-19, effective POCT strategies for COVID-19 based on optical detection methods have been established. They can be categorized into fluorescence, surface-enhanced Raman scattering, surface plasmon resonance spectroscopy, and wearable sensing. We introduced next-generation pandemic sensing methods incorporating artificial intelligence that can be used to meet global health needs in the future. Additionally, we have discussed appropriate responses of various testing devices to emerging infectious diseases and prospective preventive measures for the post-pandemic era. We believe that this review will be helpful for preparing for future infectious disease outbreaks.

Recent Development and Applications of Stretchable SERS Substrates

Surface-enhanced Raman scattering (SERS) is a cutting-edge technique for highly sensitive analysis of chemicals and molecules. Traditional SERS-active nanostructures are constructed on rigid substrates where the nanogaps providing hot-spots of Raman signals are fixed, and sample loading is unsatisfactory due to the unconformable attachment of substrates on irregular sample surfaces. A flexible SERS substrate enables conformable sample loading and, thus, highly sensitive Raman detection but still with limited detection capabilities. Stretchable SERS substrates with flexible sample loading structures and controllable hot-spot size provide a new strategy for improving the sample loading efficiency and SERS detection sensitivity. This review summarizes and discusses recent development and applications of the newly conceptual stretchable SERS substrates. A roadmap of the development of SERS substrates is reviewed, and fabrication techniques of stretchable SERS substrates are summarized, followed by an exhibition of the applications of these stretchable SERS substrates. Finally, challenges and perspectives of the stretchable SERS substrates are presented. This review provides an overview of the development of SERS substrates and sheds light on the design, fabrication, and application of stretchable SERS systems.

Advances in surface-enhanced Raman spectroscopy-based sensors for detection of various biomarkers

Surface enhanced Raman spectroscopy (SERS) allows the ultrasensitive detection of analytes present in traces or even single molecule levels by the generation of electromagnetic fields. It is a powerful vibrational spectroscopic method that is capable to detect traces of chemical and biological analytes. SERS technique is involved in the extremely sophisticated studies of molecules with high specificity and sensitivity. In the vicinity of nanomaterials decorated surfaces, SERS can monitor extremely low concentrations of analytes in a non-destructive manner with narrow line widths. This review article is focused on some recently developed SERS-based sensors for distinct types of analytes like disease-related biomarkers, organic and inorganic molecules, various toxins, dyes, pesticides, bacteria as well as single molecules. This study aims to enlighten the arising sensing approaches based on the SERS technique. Apart from this, some basics of the SERS technique like their mechanism, detection strategy, and involvement of some specific nanomaterials are also highlighted herein. Finally, the study concluded with some discussion of applications of SERS in various fields like food and environmental analysis.

Raman-Based Techniques in Medical Applications for Diagnostic Tasks: A Review

Raman spectroscopy is a widely developing approach for noninvasive analysis that can provide information on chemical composition and molecular structure. High chemical specificity calls for developing different medical diagnostic applications based on Raman spectroscopy. This review focuses on the Raman-based techniques used in medical diagnostics and provides an overview of such techniques, possible areas of their application, and current limitations. We have reviewed recent studies proposing conventional Raman spectroscopy and surface-enhanced Raman spectroscopy for rapid measuring of specific biomarkers of such diseases as cardiovascular disease, cancer, neurogenerative disease, and coronavirus disease (COVID-19). As a result, we have discovered several most promising Raman-based applications to identify affected persons by detecting some significant spectral features. We have analyzed these approaches in terms of their potentially diagnostic power and highlighted the remaining challenges and limitations preventing their translation into clinical settings.

Recent Advances in DNA Nanotechnology-Enabled Biosensors for Virus Detection

Virus-related infectious diseases are serious threats to humans, which makes virus detection of great importance. Traditional virus-detection methods usually suffer from low sensitivity and specificity, are time-consuming, have a high cost, etc. Recently, DNA biosensors based on DNA nanotechnology have shown great potential in virus detection. DNA nanotechnology, specifically DNA tiles and DNA aptamers, has achieved atomic precision in nanostructure construction. Exploiting the programmable nature of DNA nanostructures, researchers have developed DNA nanobiosensors that outperform traditional virus-detection methods. This paper reviews the history of DNA tiles and DNA aptamers, and it briefly describes the Baltimore classification of virology. Moreover, the advance of virus detection by using DNA nanobiosensors is discussed in detail and compared with traditional virus-detection methods. Finally, challenges faced by DNA nanobiosensors in virus detection are summarized, and a perspective on the future development of DNA nanobiosensors in virus detection is also provided.

Recent Advances in Quantum Dot-Based Lateral Flow Immunoassays for the Rapid, Point-of-Care Diagnosis of COVID-19

The COVID-19 pandemic has spurred demand for efficient and rapid diagnostic tools that can be deployed at point of care to quickly identify infected individuals. Existing detection methods are time consuming and they lack sensitivity. Point-of-care testing (POCT) has emerged as a promising alternative due to its user-friendliness, rapidity, and high specificity and sensitivity. Such tests can be conveniently conducted at the patient's bedside. Immunodiagnostic methods that offer the rapid identification of positive cases are urgently required. Quantum dots (QDs), known for their multimodal properties, have shown potential in terms of combating or inhibiting the COVID-19 virus. When coupled with specific antibodies, QDs enable the highly sensitive detection of viral antigens in patient samples. Conventional lateral flow immunoassays (LFAs) have been widely used for diagnostic testing due to their simplicity, low cost, and portability. However, they often lack the sensitivity required to accurately detect low viral loads. Quantum dot (QD)-based lateral flow immunoassays have emerged as a promising alternative, offering significant advancements in sensitivity and specificity. Moreover, the lateral flow immunoassay (LFIA) method, which fulfils POCT standards, has gained popularity in diagnosing COVID-19. This review focuses on recent advancements in QD-based LFIA for rapid POCT COVID-19 diagnosis. Strategies to enhance sensitivity using QDs are explored, and the underlying principles of LFIA are elucidated. The benefits of using the QD-based LFIA as a POCT method are highlighted, and its published performance in COVID-19 diagnostics is examined. Overall, the integration of quantum dots with LFIA holds immense promise in terms of revolutionizing COVID-19 detection, treatment, and prevention, offering a convenient and effective approach to combat the pandemic.

Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection

Viral infections can pose a major threat to public health by causing serious illness, leading to pandemics, and burdening healthcare systems. The global spread of such infections causes disruptions to every aspect of life including business, education, and social life. Fast and accurate diagnosis of viral infections has significant implications for saving lives, preventing the spread of the diseases, and minimizing social and economic damages. Polymerase chain reaction (PCR)-based techniques are commonly used to detect viruses in the clinic. However, PCR has several drawbacks, as highlighted during the recent COVID-19 pandemic, such as long processing times and the requirement for sophisticated laboratory instruments. Therefore, there is an urgent need for fast and accurate techniques for virus detection. For this purpose, a variety of biosensor systems are being developed to provide rapid, sensitive, and high-throughput viral diagnostic platforms, enabling quick diagnosis and efficient control of the virus's spread. Optical devices, in particular, are of great interest due to their advantages such as high sensitivity and direct readout. The current review discusses solid-phase optical sensing techniques for virus detection, including fluorescence-based sensors, surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), optical resonators, and interferometry-based platforms. Then, we focus on an interferometric biosensor developed by our group, the single-particle interferometric reflectance imaging sensor (SP-IRIS), which has the capability to visualize single nanoparticles, to demonstrate its application for digital virus detection.

Determination of benzo(a)pyrene in peanut oil based on Raman spectroscopy and machine learning methods

Benzo(a)pyrene (BaP) generated in the production process of oil is harmful to human severely as a kind of carcinogenic substance. In this study, the qualitative and quantitative detection of BaP concentration in peanut oil was investigated based on Raman spectroscopy combined with machine learning methods. The glass substrates and magnetron sputtered gold substrates for the Raman spectra were compared and the data preprocessing methods of principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) were used to process Raman signal. Back propagation neural network (BPNN), partial least squares regression (PLSR), support vector machine (SVM) and random forest (RF) algorithms were developed to obtain the qualitative and quantitative detection model of BaP concentration in peanut oil. The results showed that the Raman spectra with the glass substrate was more suitable for the BaP detection than magnetron sputtered gold substrates. RF combined with t-SNE could achieve an accuracy of 97.5% in the qualitative detection of BaP concentration levels in model validation experiment, and the correlation coefficient of the prediction set (R_p) in the quantitative detection was 0.9932, the root mean square error (RMSEP) was 0.8323 μg/kg and the bias was 0.1316 μg/kg. It can be concluded that Raman spectroscopy combined with machine learning methods could provide an effective method for the rapid determination of BaP concentration in peanut oil.

Silver nanostar films for surface-enhanced Raman spectroscopy (SERS) of the pesticide imidacloprid

Strategies for synthetic control of anisotropic metal nanostructures have grown in recent years in part due to their great potential for application as surface-enhanced Raman scattering (SERS) sensing substrates. It has been shown that SERS using silver substrates is a powerful tool for identification and qualification of trace chemical analysis on the basis of their unique molecular vibrations. In this work, we synthesized star-shaped silver nanostructures and fabricated SERS substrates to use the SERS enhancement of the Raman signal to detect neonicotinoid pesticides. These silver nanostar substrates were prepared by assembling the nanostar particles on a glass substrate surface using a self-assembly technique with various layers of silver nanostars film. The silver nanostar distribution on the solid substrate surface was found to have good reproducibility, reusability and were a stable SERS substrate giving SERS enhancements for pesticide detection at concentrations as low as 10⁻⁶ mg/ml. The distribution of these silver nanostars on the surface allowed excellent reproducibility of the detection with a low relative standard derivation (RSD) of SERS intensity of 8%. This work potentially builds a platform for an ultrasensitive detector where samples can be probed with little to no pre-processing and a range of pollutants can be detected at very low levels.

Plasmonic Sensors: A New Frontier in Nanotechnology

Plasmonics is the study of surface plasmons formed by the interaction of incident light with electrons to form a surface-bound electromagnetic wave [...].

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

Smart Nanostructured Materials for SARS-CoV-2 and Variants Prevention, Biosensing and Vaccination

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has raised great concerns about human health globally. At the current stage, prevention and vaccination are still the most efficient ways to slow down the pandemic and to treat SARS-CoV-2 in various aspects. In this review, we summarize current progress and research activities in developing smart nanostructured materials for COVID-19 prevention, sensing, and vaccination. A few established concepts to prevent the spreading of SARS-CoV-2 and the variants of concerns (VOCs) are firstly reviewed, which emphasizes the importance of smart nanostructures in cutting the virus spreading chains. In the second part, we focus our discussion on the development of stimuli-responsive nanostructures for high-performance biosensing and detection of SARS-CoV-2 and VOCs. The use of nanostructures in developing effective and reliable vaccines for SARS-CoV-2 and VOCs will be introduced in the following section. In the conclusion, we summarize the current research focus on smart nanostructured materials for SARS-CoV-2 treatment. Some existing challenges are also provided, which need continuous efforts in creating smart nanostructured materials for coronavirus biosensing, treatment, and vaccination.

Label-Free Surface-Enhanced Raman Spectroscopic Analysis of Proteins: Advances and Applications

Surface-enhanced Raman spectroscopy (SERS) is powerful for structural characterization of biomolecules under physiological condition. Owing to its high sensitivity and selectivity, SERS is useful for probing intrinsic structural information of proteins and is attracting increasing attention in biophysics, bioanalytical chemistry, and biomedicine. This review starts with a brief introduction of SERS theories and SERS methodology of protein structural characterization. SERS-active materials, related synthetic approaches, and strategies for protein-material assemblies are outlined and discussed, followed by detailed discussion of SERS spectroscopy of proteins with and without cofactors. Recent applications and advances of protein SERS in biomarker detection, cell analysis, and pathogen discrimination are then highlighted, and the spectral reproducibility and limitations are critically discussed. The review ends with a conclusion and a discussion of current challenges and perspectives of promising directions.

Bioresource-Functionalized Quantum Dots for Energy Generation and Storage: Recent Advances and Feature Perspective

The exponential increase in global energy demand in daily life prompts us to search for a bioresource for energy production and storage. Therefore, in developing countries with large populations, there is a need for alternative energy resources to compensate for the energy deficit in an environmentally friendly way and to be independent in their energy demands. The objective of this review article is to compile and evaluate the progress in the development of quantum dots (QDs) for energy generation and storage. Therefore, this article discusses the energy scenario by presenting the basic concepts and advances of various solar cells, providing an overview of energy storage systems (supercapacitors and batteries), and highlighting the research progress to date and future opportunities. This exploratory study will examine the systematic and sequential advances in all three generations of solar cells, namely perovskite solar cells, dye-sensitized solar cells, Si cells, and thin-film solar cells. The discussion will focus on the development of novel QDs that are economical, efficient, and stable. In addition, the current status of high-performance devices for each technology will be discussed in detail. Finally, the prospects, opportunities for improvement, and future trends in the development of cost-effective and efficient QDs for solar cells and storage from biological resources will be highlighted.

A review of cardiac troponin I detection by surface enhanced Raman spectroscopy: Under the spotlight of point-of-care testing

Cardiac troponin I (cTnI) is a biomarker widely related to acute myocardial infarction (AMI), one of the leading causes of death around the world. Point-of-care testing (POCT) of cTnI not only demands a short turnaround time for its detection but the highest accuracy levels to set expeditious and adequate clinical decisions. The analytical technique Surface-enhanced Raman spectroscopy (SERS) possesses several properties that tailor to the POCT format, such as its flexibility to couple with rapid assay platforms like microfluidics and paper-based immunoassays. Here, we analyze the strategies used for the detection of cTnI by SERS considering POCT requirements. From the detection ranges reported in the reviewed literature, we suggest the diseases other than AMI that could be diagnosed with this technique. For this, a section with information about cardiac and non-cardiac diseases with cTnI release, including their release kinetics or cut-off values are presented. Likewise, POCT features, the use of SERS as a POCT technique, and the biochemistry of cTnI are discussed. The information provided in this review allowed the identification of strengths and lacks of the available SERS-based point-of-care tests for cTnI and the disclosing of requirements for future assays design.

Antiproliferative and Apoptotic Effects of Graphene Oxide @AlFu MOF Based Saponin Natural Product on OSCC Line

The increasing rate of oral squamous cell carcinoma (OSCC) and the undesirable side effects of anticancer agents have enhanced the demand for the development of efficient, detectable, and targeted anticancer systems. Saponins are a diverse family of natural glycosides that have recently been evaluated as an effective compound for the targeted therapy of squamous cell carcinoma. Due to their porous nature and stable structure, metal–organic frameworks (MOFs) are a well-known substance form for various biological applications, such as drug delivery. In this study, we fabricated a novel hybrid, highly porous and low-toxic saponin-loaded nanostructure by modifying graphene oxide (GO)/reduced GO (rGO) with aluminum fumarate (AlFu) as MOF core–shell nanocomposite. The characterization of the nanostructures was investigated by FTIR, TEM, EDX, FESEM, and BET. MTT assay was used to investigate the anticancer activity of these compounds on OSCC and PDL normal dental cells. The effect of the nanocomposites on OSCC was then investigated by studying apoptosis and necrosis using flow cytometry. The GO/rGO was decorated with a saponin–AlFu mixture to further investigate cytotoxicity. The results of the MTT assay showed that PDL cells treated with AlFu–GO–saponin at a concentration of 250 μg/mL had a viability of 74.46 ± 16.02%, while OSCC cells treated with this sample at a similar concentration had a viability of only 38.35 ± 19.9%. The anticancer effect of this nanostructure on OSCC was clearly demonstrated. Moreover, the number of apoptotic cells in the AlFu–GO–saponin and AlFu–rGO–saponin groups was 10.98 ± 2.36%–26.90 ± 3.24% and 15.9 ± 4.08%–29.88 ± 0.41%, respectively, compared with 2.52 ± 0.78%–1.31 ± 0.62% in the untreated group. This significant increase in apoptotic effect observed with AlFu–rGO–saponin was also reflected in the significant anticancer effect of saponin-loaded nanostructures. Therefore, this study suggests that an effective saponin delivery system protocol for the precise design and fabrication of anticancer nanostructures for OSCC therapy should be performed prior to in vivo evaluations.

Biomedical Applications of an Ultra-Sensitive Surface Plasmon Resonance Biosensor Based on Smart MXene Quantum Dots (SMQDs)

In today’s world, the use of biosensors occupies a special place in a variety of fields such as agriculture and industry. New biosensor technologies can identify biological compounds accurately and quickly. One of these technologies is the phenomenon of surface plasmon resonance (SPR) in the development of biosensors based on their optical properties, which allow for very sensitive and specific measurements of biomolecules without time delay. Therefore, various nanomaterials have been introduced for the development of SPR biosensors to achieve a high degree of selectivity and sensitivity. The diagnosis of deadly diseases such as cancer depends on the use of nanotechnology. Smart MXene quantum dots (SMQDs), a new class of nanomaterials that are developing at a rapid pace, are perfect for the development of SPR biosensors due to their many advantageous properties. Moreover, SMQDs are two-dimensional (2D) inorganic segments with a limited number of atomic layers that exhibit excellent properties such as high conductivity, plasmonic, and optical properties. Therefore, SMQDs, with their unique properties, are promising contenders for biomedicine, including cancer diagnosis/treatment, biological sensing/imaging, antigen detection, etc. In this review, SPR biosensors based on SMQDs applied in biomedical applications are discussed. To achieve this goal, an introduction to SPR, SPR biosensors, and SMQDs (including their structure, surface functional groups, synthesis, and properties) is given first; then, the fabrication of hybrid nanoparticles (NPs) based on SMQDs and the biomedical applications of SMQDs are discussed. In the next step, SPR biosensors based on SMQDs and advanced 2D SMQDs-based nanobiosensors as ultrasensitive detection tools are presented. This review proposes the use of SMQDs for the improvement of SPR biosensors with high selectivity and sensitivity for biomedical applications.

The Pivotal Role of Quantum Dots-Based Biomarkers Integrated with Ultra-Sensitive Probes for Multiplex Detection of Human Viral Infections

The spread of viral diseases has caused global concern in recent years. Detecting viral infections has become challenging in medical research due to their high infectivity and mutation. A rapid and accurate detection method in biomedical and healthcare segments is essential for the effective treatment of pathogenic viruses and early detection of these viruses. Biosensors are used worldwide to detect viral infections associated with the molecular detection of biomarkers. Thus, detecting viruses based on quantum dots biomarkers is inexpensive and has great potential. To detect the ultrasensitive biomarkers of viral infections, QDs appear to be a promising option as biological probes, while physiological components have been used directly to detect multiple biomarkers simultaneously. The simultaneous measurement of numerous clinical parameters of the same sample volume is possible through multiplex detection of human viral infections, which reduces the time and cost required to record any data point. The purpose of this paper is to review recent studies on the effectiveness of the quantum dot as a detection tool for human pandemic viruses. In this review study, different types of quantum dots and their valuable properties in the structure of biomarkers were investigated. Finally, a vision for recent advances in quantum dot-based biomarkers was presented, whereby they can be integrated into super-sensitive probes for the multiplex detection of human viral infections.