High-sensitivity and point-of-care detection of SARS-CoV-2 from nasal and throat swabs by magnetic SERS biosensor

Magnetic-plasmonic nanoparticle-based surface-enhanced Raman scattering for biomedical detection

Surface-enhanced Raman scattering (SERS) is a powerful spectroscopic technique that enables rapid, non-destructive, and susceptible detection of biological samples. The magnetic-plasmonic composite materials composed of magnetic and plasmonic nanoparticles have attracted extensive attention as SERS substrates in the biomedical field because of their ability to enrich, separate, and selectively identify biomolecules. In this review, the state-of-art progress of magnetic-plasmonic nanoparticle (MPNP)-based SERS substrates for biomedical detection is highlighted, covering the design and construction of MPNPs with different morphologies, organic and inorganic surface functionalization strategies adopted to improve the adaptability and applicability in biological systems for MPNPs, application development of MPNPs in biomedical detection, as well as the future challenges and issues to be addressed. It is highly expected that this review will help to fully understand the research status of MPNP-based SERS substrates and facilitate their further development and wider application in biological systems.

Single-shot, receptor-free, rapid detection and classification of five respiratory viruses by machine learning integrated SERS sensing platform

A machine learning integrated SERS sensing platform is developed for a single-shot, receptor-free, rapid detection and classification of five respiratory viruses including Influenza A, Respiratory Syncytial Virus (RSV), Human Rhinoviruses (Rhino), and two variants of SARS-CoV-2 virus such as Omicron and Delta in clinical nasal and/or nasopharyngeal samples (CNS) in viral transport media (VTM). SERS sensor composed of Ag nano-sculptured thin film (nSTF) is fabricated by glancing angle deposition (GLAD) technique and possess a SERS enhancement factor of the order of 1011. Various machine learning (ML) algorithms like Random Forest Classifier (RF), Support Vector Machine (SVM), Logistic Regression (LR), k-Nearest Neighbor (KNN), and Multilayer Perceptron (MLP) are trained on SERS spectra dataset of CNS for classification of the viruses. MLP shows the best performance for the analysis and classification of complex SERS spectra with a 5-fold validation accuracy of 97.61 ± 0.30 %, test accuracy 97.47 %, sensitivity 97 %, precision 97 %, and specificity 99 %. The SERS sensor integrated with ML has a rapid response of 11 minutes, which makes it appropriate for practical implementations in clinical environments, speeding up virus detection and efficient management of respiratory viral infections.

Transformative biomedical devices to overcome biomatrix effects

The emergence of high-performance biomedical devices and sensing technologies highlights the technological advancements in the field. Recently during COVID-19 pandemic, biosensors played an important role in medical diagnostics and disease monitoring. In the past few decades, biosensors have made impressive advances in terms of sensing capability, methodology, and applications, and modern biosensors show higher performance and functionality compared to traditional biosensing platforms. Currently, various biomedical devices are already in the market or on the verge of commercialization, such as disposable paper-based devices, lab-on-a-chip devices, wearable sensors, and artificial intelligence-assisted systems, all contributing to the evolution of digital health. Despite the promising features of detection methods for developing practical biosensors, there are substantial barriers to the commercialization of biomedical devices. An important challenge is the matrix effect in the detection of clinical samples. Although achieving low limit of detection values under controlled laboratory conditions is feasible, maintaining performance in real clinical samples is difficult. Matrix molecules present in these samples can interact with analytes, potentially affecting sensitivity, specificity, and sensor response. Approaches to reduce nonspecific adsorption and cross-reactivity are imperative for improving sensor performance. The detection of diagnostic biomarkers in complex biological matrices often requires laborious sample preparation, which may affect accuracy and precision. In this review, we highlight the recent efforts to detect analytes in real samples, both invasively and noninvasively, and underline technological advancements that mitigate the biomatrix effects. We also discuss commercially available biosensors and technologies promising commercial success, highlighting their potential effect on healthcare and diagnostics.

Plasmon-activated water innovatively applicable for improving the performance of surface-enhanced Raman scattering

The effect of surface-enhanced Raman scattering is responsible for its sensibility, and the reproducibility of its corresponding surface-enhanced Raman spectroscopy (SERS) is evaluated using the relative standard deviation (RSD); these are two important performances in sensing. Interestingly, innovative plasmon-activated water (PAW) is a kind of pure water, which features an electron-doping structure with reduced-affinity hydrogen bonds (HBs). This review describes the innovative green applications of PAW to improve SERS performances with higher sensitivity and lower RSDs in sensing model probe molecules of rhodamine 6G (R6G) and pesticides. First, we report a facile one-step fabrication method of SERS-active Au and Ag substrates with improved SERS activity and excellent signal reproducibility using simple oxidation-reduction cycles (ORCs) performed in PAW solutions, compared to deionized water (DIW) solutions. Then, based on the designed in situ PAW, SERS enhancement of two-fold higher intensity of R6G and a corresponding low RSD of 5 %, which was comparable to and even better than those based on complicated processes shown in the literature, are encouraging. Furthermore, for SERS-active substrates with gold/silver (Au/Ag) nanocomposites prepared using galvanic replacement reactions (GRRs) based on the PAW system, the intensity and corresponding RSDs of the SERS signal of R6G were higher and lower, respectively, compared to the DIW system. Moreover, using PAW to dissolve analytes, including pesticides, was effective in improving SERS performances. Finally, environmentally friendly etchants of vapor from in situ PAW to improve SERS sensing of pesticides are discussed.

Nanotechnology-Based Wearable Electrochemical Biosensor for Disease Diagnosis

Recently, flexible electronics have significantly transformed information and communications technology (ICT). In particular, wearable devices, via integration with attachable biosensors, have driven the development of new types of biosensors and diagnostic devices for point-of-care testing (POCT). Moreover, wearable electrochemical biosensors can be applied to diagnose diseases in real time based on the synergistic effect generated from the incorporation of the electrochemical technique. Besides, to improve the sensitivity of electrochemical biosensors while retaining their wearability, novel nanomaterials and nanotechnologies have been introduced. In this review, recent studies on nanotechnology-based wearable electrochemical biosensors for accurate disease diagnosis are discussed. First, widely used techniques for developing flexible electrodes, including nanolithography- and nano/microneedle-based patches, are presented. Next, the latest studies on developing wearable electrochemical biosensors for the diagnosis of diseases such as diabetes and dermatitis are discussed by categorizing the biosensors into nanolithography- and nano/microneedle-based categories. Finally, this review explores the latest research trends on the application of nanotechnology-enabled nanopatterning and nano/microneedle technologies to electrochemical wearable biosensors. This review suggests novel approaches and methods for developing wearable electrochemical biosensors for real-time disease diagnosis under POCT applications.

The Potential of Optical Technologies in Early Virus Detection; Prospects in Addressing Future Viral Outbreaks

The urgent need for sensitive, rapid, and reliable diagnostic methodologies to control and prevent life-threatening pandemic infectious disease, such as COVID-19, remains a critical priority. Timely and on-site detection of viral pathogens is essential for effective disease management and mitigation of societal disruptions. Recent advancements in optical diagnostic methods have positioned them at the forefront of healthcare diagnostics, offering high sensitivity and specificity as viable alternatives to conventional techniques such as the Polymerase Chain Reaction (PCR), which often suffer from time delays and limited accessibility in resource-constrained environments. This review elucidates the potential of various optical diagnostic techniques, highlighting their advantages over traditional methods. It encompasses a range of optical modalities, including fluorescence-based approaches, Raman spectroscopy (RS), Plasmonic techniques (e.g., surface plasmon resonance (SPR), localized SPR, (LSPR), surface-enhanced Raman spectroscopy (SERS), and surface-enhanced fluorescence (SEF)), super resolution microscopies (SRMs), attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and integrated platforms such as waveguides and molecularly imprinted polymer (MIP)-based biosensors. Additionally, the evolution of novel biosensors, particularly 5th and 6th generation biosensors, in healthcare and the challenges related to these technologies were discussed. This studies reviewed aims to advance the development of portable, sensitive, specific, and cost-effective point-of-care (POC) diagnostic devices for the rapid detection of viral pathogens.

Recent Plasmonic Gold- and Silver-Assisted Raman Spectra for Advanced SARS-CoV-2 Detection

COVID-19 has become one of the deadliest epidemics in the past years. In efforts to combat the deadly disease besides vaccines, drug therapies, and facemasks, significant focus has been on designing specific methods for the sensitive and accurate detection of SARS-CoV-2. Of these, surface-enhanced Raman scattering (SERS) is an attractive analytical tool for the identification of SARS-CoV-2. SERS is the phenomenon of enhancement of Raman intensity signals from molecular analytes anchored onto the surfaces of roughened plasmonic nanomaterials. This work gives an updated summary of plasmonic gold nanomaterials (AuNMs) and silver nanomaterials (AgNMs)-based SERS technologies to identify SARS-CoV-2. Due to extreme "hot spots" promoting higher electromagnetic fields on their surfaces, different shapes of AuNMs and AgNMs combined with Raman probes have been reviewed for enhancing Raman signals of probe molecules for quantifying the virus. It also reviews progress made recently in the design of certain specific Raman probe molecules capable of imparting characteristic SERS response/tags for SARS-CoV-2 detection.

Machine Learning-Assisted Surface-Enhanced Raman Spectroscopy Detection for Environmental Applications: A Review

Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance its appeal for widespread application. However, challenges such as the management of voluminous quantities of high-dimensional data, its capacity to detect low-concentration targets in the presence of environmental interferents, and the navigation of the complex relationships arising from overlapping spectral peaks have emerged. In response, there is a growing trend toward the use of machine learning (ML) approaches that encompass multivariate tools for effective SERS data analysis. This comprehensive review delves into the detailed steps needed to be considered when applying ML techniques for SERS analysis. Additionally, we explored a range of environmental applications where different ML tools were integrated with SERS for the detection of pathogens and (in)organic pollutants in environmental samples. We sought to comprehend the intricate considerations and benefits associated with ML in these contexts. Additionally, the review explores the future potential of synergizing SERS with ML for real-world applications.

Focused ion beam-fabricated nanorod substrate for label-free surface-enhanced Raman spectroscopy and enabling dual virus detection

The COVID-19 pandemic presents global challenges, notably with co-infections in respiratory tract involving SARS-CoV-2 variants and influenza strains. Detecting multiple viruses simultaneously is crucial for accurate diagnosis, effective tracking infectious sources, and containment of the epidemic. This study uses a label-free surface-enhanced Raman spectroscopy (SERS) method using Au NPs/pZrO2 (250) and FIB-made Au NRs (100) to detect dual viruses, including SARS-CoV-2 Delta variant (D) and influenza A (A) or B (B) virus. Results demonstrate distinct peaks facilitating virus differentiation, especially between D and A or B, with clear disparities between substrates; specific peaks at 950 and 1337 cm-1 are pivotal for discerning viruses using Au NPs/pZrO2 (250), while those at 1050, 1394, and 1450 cm-1 and 1033, 1165, 1337, and 1378 cm-1 are key for validation using Au NRs (100). Differences in substrate surface morphology and spatial disposition of accommodating viruses significantly influence hotspot formation and Raman signal amplification efficiency, thereby affecting the ability to distinguish various viruses. Furthermore, both substrates offer insights, even in the presence of oxymetazoline hydrochloride (an interfering substance), with practical implications in viral diagnosis. The customized design and reproducibility underscore efficient Raman signal amplification, even in challenging environments, highlighting potential for widespread virus detection.

Single-molecule detection of SARS-CoV-2 N protein on multilayered plasmonic nanotraps with surface-enhanced Raman spectroscopy

The spread of the SARS-CoV-2 virus has had an unprecedented impact, both by posing a serious risk to human health and by amplifying the burden on the global economy. The rapid identification of the SARS-CoV-2 virus has been crucial to preventing and controlling the spread of SARS-CoV-2 infections. In this study, we propose a multilayered plasmonic nanotrap (MPNT) device for the rapid identification of single particles of SARS-CoV-2 virus in ultra-high sensitivity by surface-enhanced Raman scattering (SERS). The MPNT device is composed of arrays of concentric cylindrical cavities with Ag/SiO2/Ag multilayers deposited on the top and at the bottom. By varying the diameter of the cylinders and the thickness of the multilayers, the resonant optical absorption and local electric field were optimized. The SERS enhancement factors of the proposed device are of the order of 108, which enable the rapid identification of SARS-CoV-2 N protein in concentrations as low as 1.25 × 10-15－12.5 × 10-15 g mL-1 within 1 min. The developed MPNT SERS device provides a label-free and rapid detection platform for SARS-CoV-2 virus. The general nature of the device makes it equally suitable to detect other infectious viruses.

Rapid Detection of SARS-CoV-2 Variants Using an Angiotensin-Converting Enzyme 2-Based Surface-Enhanced Raman Spectroscopy Sensor Enhanced by CoVari Deep Learning Algorithms

An integrated approach combining surface-enhanced Raman spectroscopy (SERS) with a specialized deep learning algorithm to rapidly and accurately detect and quantify SARS-CoV-2 variants is developed based on an angiotensin-converting enzyme 2 (ACE2)-functionalized AgNR@SiO2 array SERS sensor. SERS spectra with concentrations of different variants were collected using a portable Raman system. After appropriate spectral preprocessing, a deep learning algorithm, CoVari, is developed to predict both the viral variant species and concentrations. Using a 10-fold cross-validation strategy, the model achieves an average accuracy of 99.9% in discriminating between different virus variants and R2 values larger than 0.98 for quantifying viral concentrations of the three viruses, demonstrating the high quality of the detection. The limit of detection of the ACE2 SERS sensor is determined to be 10.472, 11.882, and 21.591 PFU/mL for SARS-CoV-2, SARS-CoV-2 B1, and CoV-NL63, respectively. The feature importance of virus classification and concentration regression in the CoVari algorithm are calculated based on a permutation algorithm, which showed a clear correlation to the biochemical origins of the spectra or spectral changes. In an unknown specimen test, classification accuracy can achieve >90% for concentrations larger than 781 PFU/mL, and the predicted concentrations consistently align with actual values, highlighting the robustness of the proposed algorithm. Based on the CoVari architecture and the output vector, this algorithm can be generalized to predict both viral variant species and concentrations simultaneously for a broader range of viruses. These results demonstrate that the SERS + CoVari strategy has the potential for rapid and quantitative detection of virus variants and potentially point-of-care diagnostic platforms.

Optical biosensors for diagnosis of COVID-19: nanomaterial-enabled particle strategies for post pandemic era

The COVID-19 pandemic underlines the need for effective strategies for controlling virus spread and ensuring sensitive detection of SARS-CoV-2. This review presents the potential of nanomaterial-enabled optical biosensors for rapid and low-cost detection of SARS-CoV-2 biomarkers, demonstrating a comprehensive analysis including colorimetric, fluorescence, surface-enhanced Raman scattering, and surface plasmon resonance detection methods. Nanomaterials including metal-based nanomaterials, metal-organic frame-based nanoparticles, nanorods, nanoporous materials, nanoshell materials, and magnetic nanoparticles employed in the production of optical biosensors are presented in detail. This review also discusses the detection principles, fabrication methods, nanomaterial synthesis, and their applications for the detection of SARS-CoV-2 in four categories: antibody-based, antigen-based, nucleic acid-based, and aptamer-based biosensors. This critical review includes reports published in the literature between the years 2021 and 2024. In addition, the review offers critical insights into optical nanobiosensors for the diagnosis of COVID-19. The integration of artificial intelligence and machine learning technologies with optical nanomaterial-enabled biosensors is proposed to improve the efficiency of optical diagnostic systems for future pandemic scenarios.

Advancements in magnetic nanoparticle-based biosensors for point-of-care testing

The significance of point-of-care testing (POCT) in early clinical diagnosis and personalized patient care is increasingly recognized as a crucial tool in reducing disease outbreaks and improving patient survival rates. Within the realm of POCT, biosensors utilizing magnetic nanoparticles (MNPs) have emerged as a subject of substantial interest. This review aims to provide a comprehensive evaluation of the current landscape of POCT, emphasizing its growing significance within clinical practice. Subsequently, the current status of the combination of MNPs in the Biological detection has been presented. Furthermore, it delves into the specific domain of MNP-based biosensors, assessing their potential impact on POCT. By combining existing research and spotlighting pivotal discoveries, this review enhances our comprehension of the advancements and promising prospects offered by MNP-based biosensors in the context of POCT. It seeks to facilitate informed decision-making among healthcare professionals and researchers while also promoting further exploration in this promising field of study.

Dual-Mode Lateral Flow Immunoassay Based on "Pompon Mum"-Like Fe3O4@MoS2@Pt Nanotags for Sensitive Detection of Viral Pathogens

Lateral flow immunoassay (LFIA) has been widely used for the early diagnosis of diseases. However, conventional colorimetric LFIA possesses limited sensitivity, and the single-mode readout signal is easily affected by the external environment, leading to insufficient accuracy. Herein, multifunctional Fe3O4@MoS2@Pt nanotags with a unique "pompon mum"-like structure were triumphantly prepared, exhibiting excellent peroxidase (POD)-like activity, photothermal properties, and magnetic separation capability. Furthermore, the Fe3O4@MoS2@Pt nanotags were used to establish dual-mode LFIA (dLFIA) for the first time, enabling the catalytic colorimetric and photothermal dual-mode detection of severe acute respiratory syndrome coronavirus 2 nucleocapsid protein (SARS-CoV-2 NP) and influenza A (H1N1). The calculated limits of detection (cLODs) of SARS-CoV-2 NP and H1N1 were 80 and 20 ng/mL in catalytic colorimetric mode and 10 and 8 ng/mL in photothermal mode, respectively, demonstrating about 100 times more sensitive than the commercial colloidal Au-LFIA strips (1 ng/mL for SARS-CoV-2 NP; 1 μg/mL for H1N1). The recovery rates of dLFIA in simulated nose swab samples were 95.2-103.8% with a coefficient of variance of 2.3-10.1%. These results indicated that the proposed dLFIA platform showed great potential for the rapid diagnosis of respiratory viruses.

Single-Atom Site SERS Chip for Rapid, Ultrasensitive, and Reproducible Direct-Monitoring of RNA Binding

Ribonucleic acids (RNA) play active roles within cells or viruses by catalyzing biological reactions, controlling gene expression, and communicating responses to cellular signals. Rapid monitoring RNA variation has become extremely important for appropriate clinical decisions and frontier biological research. However, the most widely used method for RNA detection, nucleic acid amplification, is restricted by a mandatory temperature cycling period of ≈1 h required to reach target detection criteria. Herein, a direct detection approach via single-atom site integrated surface-enhanced Raman scattering (SERS) monitoring nucleic acid pairing reaction, can be completed within 3 min and reaches high sensitivity and extreme reproducibility for COVID-19 and two other influenza viruses' detection. The mechanism is that a single-atom site on SERS chip, enabled by positioning a single-atom oxide coordinated with a specific complementary RNA probe on chip nanostructure hotspots, can effectively bind target RNA analytes to enrich them at designed sites so that the binding reaction can be detected through Raman signal variation. This ultrafast, sensitive, and reproducible single-atom site SERS chip approach paves the route for an alternative technique of immediate RNA detection. Moreover, single-atom site SERS is a novel surface enrichment strategy for SERS active sites for other analytes at ultralow concentrations.

Hierarchical Nanobiosensors at the End of the SARS-CoV-2 Pandemic

Nanostructures have played a key role in the development of different techniques to attack severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Some applications include masks, vaccines, and biosensors. The latter are of great interest for detecting diseases since some of their features allowed us to find specific markers in secretion samples such as saliva, blood, and even tears. Herein, we highlight how hierarchical nanoparticles integrated into two or more low-dimensional materials present outstanding advantages that are attractive for photonic biosensing using their nanoscale functions. The potential of nanohybrids with their superlative mechanical characteristics together with their optical and optoelectronic properties is discussed. The progress in the scientific research focused on using nanoparticles for biosensing a variety of viruses has become a medical milestone in recent years, and has laid the groundwork for future disease treatments. This perspective analyzes the crucial information about the use of hierarchical nanostructures in biosensing for the prevention, treatment, and mitigation of SARS-CoV-2 effects.

SERS-based immunoassay on a plasmonic syringe filter for improved sampling and labeling efficiency of biomarkers

Rapid, sensitive, and quantitative detection of biomarkers is needed for early diagnosis of disease and surveillance of infectious outbreaks. Here, we exploit a plasmonic syringe filter and surface-enhanced Raman spectroscopy (SERS) in the development of a rapid detection system, using human IgG as a model diagnostic biomarker. The novel assay design facilitates multiple passages of the sample and labeling solution through the detection zone enabling us to investigate and maximize sampling efficiency to the capture substrate. The vertical flow immunoassay process in this study involves the utilization of filter paper embedded with gold nanoparticles (AuNPs) to form a plasmonic substrate. Capture antibody (anti-human IgG) is then immobilized onto the prepared plasmonic paper and inserted into a vertical flow device (syringe filter holder). Sample solution is passed through the filter paper and the target antigen (human IgG) is selectively captured by the immobilized antibody to form an antibody-antigen complex. Next, functionalized AuNPs as extrinsic Raman labels (ERLs) are passed through the filter paper to label the captured biomarker molecules forming a layered structure. This sandwiched geometry enhances plasmonic coupling and SERS signal to provide highly sensitive detection of biomolecules. Systematic studies to investigate the impact of multiple infuse/withdraw cycles of the sample and labeling solutions reveal that antigen and ERL binding are maximized with 10 and 20 cycles, respectively. The optimized assay achieves a detection limit of ∼0.2 ng mL-1 for human IgG with a total assay time of less than 5 minutes, meeting the demands for rapid point of care diagnostics. Additionally, the optimized platform was implemented in the quantitative analysis of the SARS-CoV-2 nucleocapsid protein, the typical target in commercial, FDA-approved rapid antigen tests for COVID-19.

Next-Generation Rapid and Ultrasensitive Lateral Flow Immunoassay for Detection of SARS-CoV-2 Variants

The coronavirus disease 2019 (COVID-19) pandemic highlighted the need for rapid and accurate viral detection at the point-of-care testing (POCT). Compared with nucleic acid detection, lateral flow immunoassay (LFIA) is a rapid and flexible method for POCT detection. However, the sensitivity of LFIA limits its use for early identification of patients with COVID-19. Here, an innovative surface-enhanced Raman scattering (SERS)-LFIA platform based on two-dimensional black phosphorus decorated with Ag nanoparticles as important antigen-capturing and Raman-signal-amplification unit was developed for detection of SARS-CoV-2 variants within 5-20 min. The novel SERS-LFIA platform realized a limit of detection of 0.5 pg/mL and 100 copies/mL for N protein and SARS-CoV-2, demonstrating 1000 times more sensitivity than the commercial LFIA strips. It could reliably detect seven different SARS-CoV-2 variants with cycle threshold (Ct) < 38, with sensitivity and specificity of 97 and 100%, respectively, exhibiting the same sensitivity with q-PCR. Furthermore, the detection results for 48 SARS-CoV-2-positive nasopharyngeal swabs (Ct = 19.8-38.95) and 96 negative nasopharyngeal swabs proved the reliability of the strips in clinical application. The method also had good specificity in double-blind experiments involving several other coronaviruses, respiratory viruses, and respiratory medications. The results showed that the innovative SERS-LFIA platform is expected to be the next-generation antigen detection technology. The inexpensive amplification-free assay combines the advantages of rapid low-cost POCT and highly sensitive nucleic acid detection, and it is suitable for rapid detection of SARS-CoV-2 variants and other pathogens. Thus, it could replace existing antigens and nucleic acids to some extent.

One-step-one-pot hydrothermally derived metal-organic-framework-nanohybrids for integrated point-of-care diagnostics of SARS-CoV-2 viral antigen/pseudovirus utilizing electrochemical biosensor chip

The COVID-19 pandemic has become a global catastrophe, affecting the health and economy of the human community. It is required to mitigate the impact of pandemics by developing rapid molecular diagnostics for SARS-CoV-2 virus detection. In this context, developing a rapid point-of-care (POC) diagnostic test is a holistic approach to the prevention of COVID-19. In this context, this study aims at presenting a real-time, biosensor chip for improved molecular diagnostics including recombinant SARS-CoV-2 spike glycoprotein and SARS-CoV-2 pseudovirus detection based on one-step-one-pot hydrothermally derived CoFeBDCNH₂-CoFe₂O₄ MOF-nanohybrids. This study was tested on a PalmSens-EmStat Go POC device, showing a limit of detection (LOD) for recombinant SARS-CoV-2 spike glycoprotein of 6.68 fg/mL and 6.20 fg/mL in buffer and 10% serum-containing media, respectively. To validate virus detection in the POC platform, an electrochemical instrument (CHI6116E) was used to perform dose dependent studies under similar experimental conditions to the handheld device. The results obtained from these studies were comparable indicating the capability and high detection electrochemical performance of MOF nanocomposite derived from one-step-one-pot hydrothermal synthesis for SARS-CoV-2 detection for the first time. Further, the performance of the sensor was tested in the presence of Omicron BA.2 and wild-type D614G pseudoviruses.

Simple, Fast and Convenient Magnetic Bead-Based Sample Preparation for Detecting Viruses via Raman-Spectroscopy

We introduce a magnetic bead-based sample preparation scheme for enabling the Raman spectroscopic differentiation of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-positive and -negative samples. The beads were functionalized with the angiotensin-converting enzyme 2 (ACE2) receptor protein, which is used as a recognition element to selectively enrich SARS-CoV-2 on the surface of the magnetic beads. The subsequent Raman measurements directly enable discriminating SARS-CoV-2-positive and -negative samples. The proposed approach is also applicable for other virus species when the specific recognition element is exchanged. A series of Raman spectra were measured on three types of samples, namely SARS-CoV-2, Influenza A H1N1 virus and a negative control. For each sample type, eight independent replicates were considered. All of the spectra are dominated by the magnetic bead substrate and no obvious differences between the sample types are apparent. In order to address the subtle differences in the spectra, we calculated different correlation coefficients, namely the Pearson coefficient and the Normalized cross correlation coefficient. By comparing the correlation with the negative control, differentiating between SARS-CoV-2 and Influenza A virus is possible. This study provides a first step towards the detection and potential classification of different viruses with the use of conventional Raman spectroscopy.

Recent development of surface-enhanced Raman scattering for biosensing

Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

Perspective Chapter: Novel Diagnostics Methods for SARS-CoV-2

A novel coronavirus of zoonotic origin (SARS-CoV-2) has recently been recognized in patients with acute respiratory disease. COVID-19 causative agent is structurally and genetically similar to SARS and bat SARS-like coronaviruses. The drastic increase in the number of coronavirus and its genome sequence has given us an unprecedented opportunity to perform bioinformatics and genomics analysis on this class of viruses. Clinical tests such as PCR and ELISA for rapid detection of this virus are urgently needed for early identification of infected patients. However, these techniques are expensive and not readily available for point-of-care (POC) applications. Currently, lack of any rapid, available, and reliable POC detection method gives rise to the progression of COVID-19 as a horrible global problem. To solve the negative features of clinical investigation, we provide a brief introduction of the various novel diagnostics methods including SERS, SPR, electrochemical, magnetic detection of SARS-CoV-2. All sensing and biosensing methods based on nanotechnology developed for the determination of various classes of coronaviruses are useful to recognize the newly immerged coronavirus, i.e., SARS-CoV-2. Also, the introduction of sensing and biosensing methods sheds light on the way of designing a proper screening system.

Recent Advances of Representative Optical Biosensors for Rapid and Sensitive Diagnostics of SARS-CoV-2

The outbreak of Corona Virus Disease 2019 (COVID-19) has again emphasized the significance of developing rapid and highly sensitive testing tools for quickly identifying infected patients. Although the current reverse transcription polymerase chain reaction (RT-PCR) diagnostic techniques can satisfy the required sensitivity and specificity, the inherent disadvantages with time-consuming, sophisticated equipment and professional operators limit its application scopes. Compared with traditional detection techniques, optical biosensors based on nanomaterials/nanostructures have received much interest in the detection of SARS-CoV-2 due to the high sensitivity, high accuracy, and fast response. In this review, the research progress on optical biosensors in SARS-CoV-2 diagnosis, including fluorescence biosensors, colorimetric biosensors, Surface Enhancement Raman Scattering (SERS) biosensors, and Surface Plasmon Resonance (SPR) biosensors, was comprehensively summarized. Further, promising strategies to improve optical biosensors are also explained. Optical biosensors can not only realize the rapid detection of SARS-CoV-2 but also be applied to judge the infectiousness of the virus and guide the choice of SARS-CoV-2 vaccines, showing enormous potential to become point-of-care detection tools for the timely control of the pandemic.

Optimization of surface enhanced Raman scattering performance based on Ag nanoparticle-modified vanadium-titanium nanorods with tunable nanogaps

The combination of new noble metal nanomaterials and surface enhanced Raman scattering (SERS) technology has become a new strategy to solve the problem of low sensitivity in the detection of traditional Chinese medicine. In this work, taking natural cicada wing (C.w.) as a template, by optimizing the magnetron sputtering experimental parameters for the growth of Ag nanoparticles (NPs) on vanadium-titanium (V-Ti) nanorods, the nanogaps between the nanorods were effectively regulated and the Raman signal intensity of the Ag₁₅/V-Ti₂₀/C.w. substrate was improved. The proposed homogeneous nanostructure exhibited high SERS activity through the synergistic effect of the electromagnetic enhancement mechanism at the nanogaps between the Ag NPs modified V-Ti nanorods. The analytical enhancement factor (AEF) value was as high as 1.819 × 10⁸, and the limit of detection (LOD) was 1 × 10^-11 M for R6G. The large-scale distribution of regular electromagnetic enhancement "hot spots" ensured the good reproducibility with the relative standard deviation (RSD) value less than 7.31%. More importantly, the active compound of Artemisinin corresponded the pharmacological effect of Artemisia annua was screened out by SERS technology, and achieved a LOD of 0.01 mg/l. This reliable preparation technology was practically applicable to produce SERS-active substrates in detection of pharmacodynamic substance in traditional Chinese medicine.

Magnetic nanocomposites for biomedical applications

Tissue engineering and regenerative medicine have solved numerous problems related to the repair and regeneration of damaged organs and tissues arising from aging, illnesses, and injuries. Nanotechnology has further aided tissue regeneration science and has provided outstanding opportunities to help disease diagnosis as well as treat damaged tissues. Based on the most recent findings, magnetic nanostructures (MNSs), in particular, have emerged as promising materials for detecting, directing, and supporting tissue regeneration. There have been many reports concerning the role of these nano-building blocks in the regeneration of both soft and hard tissues, but the subject has not been extensively reviewed. Here, we review, classify, and discuss various synthesis strategies for novel MNSs used in medicine. Advanced applications of magnetic nanocomposites (MG-NCs), specifically magnetic nanostructures, are further systematically reviewed. In addition, the scientific and technical aspects of MG-NC used in medicine are discussed considering the requirements for the field. In summary, this review highlights the numerous opportunities and challenges associated with the use of MG-NCs as smart nanocomposites (NCs) in tissue engineering and regenerative medicine.

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.

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

COVID-19 continues to spread and has been declared a global emergency. Individuals with current or past infection should be identified as soon as possible to prevent the spread of disease. Surface-enhanced Raman spectroscopy (SERS) is an analytical technique that has the potential to be used to detect viruses at the site of therapy. In this context, SERS is an exciting technique because it provides a fingerprint for any material. It has been used with many COVID-19 virus subtypes, including Deltacron and Omicron, a novel coronavirus. Moreover, flexible SERS substrates, due to their unique advantages of sensitivity and flexibility, have recently attracted growing research interest in real-world applications such as medicine. Reviewing the latest flexible SERS-substrate developments is crucial for the further development of quality detection platforms. This article discusses the ultra-responsive detection methods used by flexible SERS substrate. Multiplex assays that combine ultra-responsive detection methods with their unique biomarkers and/or biomarkers for secondary diseases triggered by the development of infection are critical, according to this study. In addition, we discuss how flexible SERS-substrate-based ultrasensitive detection methods could transform disease diagnosis, control, and surveillance in the future. This study is believed to help researchers design and manufacture flexible SERS substrates with higher performance and lower cost, and ultimately better understand practical applications.