Exploring the margins of SERS in practical domain: An emerging diagnostic modality for modern biomedical applications

Surface-enhanced Raman spectroscopy for the characterization of filtrate portions of hepatitis B blood serum samples using 100 kDa ultra filtration devices

The blood serum of patients infected by the Hepatitis B virus contains high molecular weight fractions and low molecular weight fractions (LMWF) of biomarker proteins of the disease. The LMWF including the associated peptidome and metabolome, is recognized as a critical molecular population with high potential for research on disease-associated biomarkers. This fraction of biomarkers can be suppressed by HMWF, proteins such as albumin, and immunoglobulins hence difficult to be detected. The purpose of this study is to separate HMWF) and LMWF using 100 kDa centrifugal filtration devices resulting in two parts including residue (HMWF) and filtrate parts (LMWF) of blood serum followed by the analysis of the later part employing surface-enhanced Raman spectroscopy (SERS). This strategy can enhance this optical technique's capability to characterize the biochemical changes caused by the infection of HBV and the diagnosis of the disease. The silver nanoparticles (Ag-NPs) were employed as a SERS substrate to distinguish between filtrate parts of the blood serum of HBV patients and healthy individuals based on their specific SERS peaks. The SERS spectral features associated with the filtrate parts of HBV patients' blood serum are well differentiated from the healthy volunteers. Principle component analysis (PCA) was applied on the SERS spectral data sets of HBV patients and healthy individuals and found extremely beneficial for the classification of their SERS spectral groups. Moreover, partial least square regression analysis (PLSR) has shown excellent performance in the quantitative analysis of the viral load values of the HBV patients using their SERS spectral data sets.

Recent advances in semiconductor nanostructure-based surface-enhanced Raman scattering sensors

Surface-enhanced Raman scattering (SERS) has become a transformative analytical tool, attracting growing interest for its wide-ranging applications. The development of SERS-active materials is now a central research area, spurring innovation in various types of SERS substrates. While noble metal-based substrates remain extensively studied, semiconductor-based, non-metal substrates are garnering attention due to their unique advantages: excellent chemical stability, high carrier mobility, biocompatibility, and precise fabrication control. However, their generally weaker enhancement effects limit their utility, underscoring the need for strategies to boost their SERS activity. Understanding the complex enhancement mechanisms in semiconductor-based SERS substrates is critical for designing next-generation materials with metal-like enhancement factors (EFs). The interplay of charge transfer, localized surface plasmon resonance, and photonic effects makes the enhancement process inherently challenging to unravel. Therefore, the search for new materials with exciting optoelectronic properties, as well as more innovative solutions to increase their SERS sensitivity, continues to grow. In this review, we explore the latest advancements in semiconductor-based SERS substrates, dissecting the complex enhancement mechanisms and various modification strategies aimed at achieving metal-like high EFs. We present a comprehensive analysis of the methods used to improve the SERS performance of semiconductor substrates and conclude with potential future directions for advancing this dynamic field.

An efficient SERS detection platform based on roseate petal homochiral nanogold (Au RHNs) as substrate for sensitive detection of plastics in environmental water samples

Excessive plastic consumption can pose potential risks to the human respiratory and circulatory systems, leading to various diseases. Therefore, the sensitive detection of plastics holds significant implications for ensuring food safety, environmental protection, and human health. Conducting tests on rivers and drinking water can ensure their compliance with relevant safety standards, thereby mitigating the potential environmental and health risks associated with plastic pollution. In this experiment, we prepared a roseate petal homochiral nanogold (Au RHNs) as a surface-enhanced Raman scattering (SERS) substrate for detecting plastics in the water. Due to the intricate rose petal-like surface and structures with symmetry breaking, which result in a large surface area, the mean enhancement factor (EF) of the Au RHNs was determined to be 8.4696 × 105. The Au RHNs as the SERS substrate were used to test the plastic polyethylene (PE) and polyvinyl chloride (PVC), with the detection limits of 0.0986 mg/mL and 0.0975 mg/mL, respectively. Moreover, the prepared Au RHNs substrate were successfully applied for ananlyzing analyze actual samples (tap water, mineral water, river water), yielding a satisfactory recovery rate. The exceptional performance of Au RHNs as a SERS detection substrate indicated its promising potential for practical detection of plastic samples.

Recent advances in SERS assays for detection of multiple extracellular vesicles biomarkers for cancer diagnosis

As the prevalence of cancer is escalating, there is an increased demand for early and sensitive diagnostic tools. A major challenge in early detection is the lack of specific biomarkers, and a readily accessible, sensitive and rapid detection method. To meet these challenges, cancer-derived small extracellular vesicles (sEVs) have been discovered as a new promising cancer biomarker due to the high abundance of sEVs in body fluids and their extensive cargo of biomarkers. Additionally, surface-enhanced Raman scattering (SERS) presents a sensitive, multiplexed, and rapid method that has gained attraction with recent studies showing promising results from patient samples for the multiplex detection of cancer sEVs. Various label-based SERS multiplex assays have been developed in the field of SERS including bead assays, lateral flow immunoassays, microfluidic devices, and artificial intelligence (AI)-based label-free SERS chips, targeting multiple surface proteins to ensure comprehensive multiplex diagnostics. These assays hold promise for enabling early detection, quantification, and subtyping of cancer-derived sEVs for cancer diagnostic applications. This review aims to provide a summary of the recent advances in the field of SERS multiplex assays for detection, quantification, and subtyping of sEVs to facilitate cancer diagnosis. This review further provides unique insights into the use of sEVs as a biomarker and aims to address the issues surrounding their translation from laboratories to clinics.

Lithium-doped ZrO2 nanoparticles for SERS-based norfloxacin drug detection

Surface-enhanced Raman scattering (SERS) spectroscopy is a highly specific and ultrasensitive analytical technique; thus, it is an ideal candidate for therapeutic drug monitoring. However, SERS measurements of drugs in a sample are inevitably affected by the environment. In this study, we synthesized ZrO2 nanoparticles (NPs) doped with the first group of elements (Li, Na, and K) in the main block and evaluated their SERS performance. The results showed that Li-ion doping could significantly enhance the SERS effect, and the degree of enhancement depended on the type and concentration of the doped ions. Compared with the highly stable ZrO2, Li ion-doped ZrO2 (Li-ZrO2) exhibited a significant increase in SERS activity. In particular, 1 % Li-ZrO2 NPs exhibited excellent SERS enhancement with an enhancement factor (EF) of 2.60 × 104, which was attributed to the decreased band gap and improved the charge transfer (CT) process after Li ion doping. The adsorption capacity of the Li-ZrO2 NPs for norfloxacin (NOR) molecules was gradually saturated with time. In addition, both acidic and alkaline conditions were unfavorable for NOR detection by the substrate. The SERS intensity exhibited a linear relationship within the NOR concentration range of 10-3-10-6 mol/L, and approximately 97.51 % of the active ingredients were detected, with a competitive detection limit of 10-6 mol/L. Furthermore, NOR detection is cost-effective and time-efficient, and the results of our study can aid in the research process and support practical applications. The proposed study provides a guidance for improving the SERS activity of semiconductors for sensing.

Porous Nanoframe Based Plasmonic Structure With High-Density Hotspots for the Quantitative Detection of Gaseous Benzaldehyde

Owing to its high sensitivity, surface-enhanced Raman scattering (SERS) has immense potential for the identification of lung cancer from the variation in volatile biomarkers in the exhaled gas. However, two prevailing factors limit the application of SERS: 1) the adsorption of target molecules into SERS hotspots and 2) the detection specificity in multiple interference environments. To improve the density of the SERS hotspots, 3D Au@Ag-Au particles are prepared in a porous nanoframes (PPFs) based plasmonic structure, which facilitated a richer local electromagnetic field distribution among the Au nanocubic (NC) cores, Au-Ag porous nanoframes, and Au nanoparticles, thereby promoting the adsorption probability of gaseous aldehydes into the hotspots. L-cysteines (l-Cys)-modified 3D Au@Ag-Au PPFs are proposed as a benzaldehyde (BA) gas detection carrier to accurately detect biomarkers in complex exhaled gases and eliminate interference from other components. Unlike the conventional use of 4-aminothiophenol as a linker molecule, the novel L-Cys-modified SERS substrate is sensitive toward the aldehyde molecules and immune to other volatile organic compounds (ethanol, cyclohexane, toluene, etc.). Furthermore, a medical mask consisting of this SERS substrate is designed to realize intelligent detection of gaseous BA concentrations assisted by a machine learning algorithm.

Innovative applications of advanced nanomaterials in cerebrovascular imaging

Cerebrovascular imaging is essential for the diagnosis, treatment, and prognosis of cerebrovascular disease, including stroke, aneurysms, and vascular malformations. Conventional imaging techniques such as MRI, CT, DSA and ultrasound have their own strengths and limitations, particularly in terms of resolution, contrast and safety. Recent advances in nanotechnology offer new opportunities for improved cerebrovascular imaging. Nanomaterials, including metallic nanoparticles, magnetic nanoparticles, quantum dots, carbon-based nanomaterials, and polymer nanoparticles, show great potential due to their unique physical, chemical, and biological properties. This review summarizes recent advances in advanced nanomaterials for cerebrovascular imaging and their applications in various imaging techniques, and discusses challenges and future research directions. The aim is to provide valuable insights for researchers to facilitate the development and clinical application of these innovative nanomaterials in cerebrovascular imaging.

Recent Progress in Nanomaterial-Based Surface-Enhanced Raman Spectroscopy for Food Safety Detection

Food safety has recently become a widespread concern among consumers. Surface-enhanced Raman scattering (SERS) is a rapidly developing novel spectroscopic analysis technique with high sensitivity, an ability to provide molecular fingerprint spectra, and resistance to photobleaching, offering broad application prospects in rapid trace detection. With the interdisciplinary development of nanomaterials and biotechnology, the detection performance of SERS biosensors has improved significantly. This review describes the advantages of nanomaterial-based SERS detection technology and SERS's latest applications in the detection of biological and chemical contaminants, the identification of foodborne pathogens, the authentication and quality control of food, and the safety assessment of food packaging materials. Finally, the challenges and prospects of constructing and applying nanomaterial-based SERS sensing platforms in the field of food safety detection are discussed with the aim of early detection and ultimate control of foodborne diseases.

Hydrogen Sulfide-Induced Activatable Photodynamic Therapy Adjunct to Disruption of Subcellular Glycolysis in Cancer Cells by a Fluorescence-SERS Bimodal Iridium Metal-Organic Hybrid

The practical application of photodynamic therapy (PDT) demands targeted and activatable photosensitizers to mitigate off-target phototoxicity common in "always on" photosensitizers during light exposure. Herein, a cyclometalated iridium complex-based activatable photodynamic molecular hybrid, Cy-Ir-7-nitrobenzofurazan (NBD), is demonstrated as a biomedicine for molecular precision. This design integrates a hydrogen sulfide (H2S)-responsive NBD unit with a hydroxy-appended iridium complex, Cy-Ir-OH. In normal physiological conditions, the electron-rich Ir metal center exerts electron transfer to the NBD unit, quenches the excited state dynamics, and establishes a PDT-off state. Upon exposure to H2S, Cy-Ir-NBD activates into the potent photosensitizer Cy-Ir-OH through nucleophilic substitution. This mechanism ensures exceptional specificity, enabling targeted phototherapy in H2S-rich cancer cells. Additionally, we observed that Cy-Ir-NBD-induced H2S depletion disrupts S-sulfhydration of the glyceraldehyde-3-phosphate dehydrogenase enzyme, impairing glycolysis and ATP production in the cellular milieu. This sequential therapeutic process of Cy-Ir-NBD is governed by the positively charged central iridium ion that ensures mitochondria-mediated apoptosis in cancer cells. Dual-modality SERS and fluorescence imaging validate apoptotic events, highlighting Cy-Ir-NBD as an advanced theranostic molecular entity for activatable PDT. Finally, as a proof of concept, clinical assessment is evaluated with the blood samples of breast cancer patients and healthy volunteers, based on their H2S overexpression capability through SERS and fluorescence, revealing Cy-Ir-NBD to be a promising predictor for PDT activation in advanced cancer phototherapy.

Raman Spectroscopic Insights of Phase-Separated Insulin Aggregates

Phase-separated protein accumulation through the formation of several aggregate species is linked to the pathology of several human disorders and diseases. Our current investigation envisaged detailed Raman signature and structural intricacy of bovine insulin in its various forms of aggregates produced in situ at an elevated temperature (60 °C). The amide I band in the Raman spectrum of the protein in its native-like conformation appeared at 1655 cm-1 and indicated the presence of a high content of α-helical structure as prepared freshly in acidic pH. The disorder content (turn and coils) also was predominately present in both the monomeric and oligomeric states and was confirmed by the presence shoulder amide I maker band at ∼1680 cm-1. However, the band shifted to ∼1671 cm-1 upon the transformation of the protein solution into fibrillar aggregates as produced for a longer time of incubation. The protein, however, maintained most of its helical conformation in the oligomeric phase; the low-frequency backbone α-helical conformation signal at ∼935 cm-1 was similar to that of freshly prepared aqueous protein solution enriched in helical conformation. The peak intensity was significantly weak in the fibrillar aggregates, and it appeared as a good Raman signature to follow the phase separation and the aggregation behavior of insulin and similar other proteins. Tyrosine phenoxy moieties in the protein may maintained its H-bond donor-acceptor integrity throughout the course of fibril formation; however, it entered in more hydrophobic environment in its journey of fibril formation. In addition, it was noticed that oligomeric bovine insulin maintained the orientation/conformation of the disulfide bonds. However, in the fibrillar state, the disulfide linkages became more strained and preferred to maintain a single conformation state.

Bifunctional folic acid targeted biopolymer Ag@NMOF nanocomposite [{Zn2 (1,4-bdc) 2 (DABCO)} n] as a novel theranostic agent for molecular imaging of colon cancer by SERS

Without a doubt, cancer and its negative impact on human health have created many hurdles for people across the world since conventional approaches have not offered a reliable ability in the eradication of cancer. As a result, finding novel approaches, like using bimodal nanoparticles as a potential nanocarrier in molecular imaging and cancer therapy, is remarkably required these days. In the present study, ex-situ (Ge) and in-situ (Gi) green synthesized silver (Ag) nanoparticles entrapped in metal-organic framework nanocomposites (NMOF) coated with folic acid (FA) targeted chitosan (CS) was successfully developed as a novel bifunctional nanocarrier for detection and treatment of colon cancer cells. Then nanocarriers, such as NMOF-CS-FA, Ge-Ag@NMOF-CS-FA, Gi-Ag@NMOF-CS-FA, and C-Ag@NMOF-CS-FA, were characterized via FT-IR, DLS, SERS, TEM, and SEM and results have potentially confirmed the quality and quantity of synthesized nanocomposites. The hydrodynamic diameters of NMOF-CS, Ge-Ag@NMOF-CS, Gi-Ag@NMOF-CS, and C-Ag@NMOF-CS specimens were measured at around 99.7 ± 10 nm, 110 ± 10 nm, 118 ± 10 nm, 115 ± 10 nm, respectively. Also, the PDI values less than 0.2 confirm the reliable distribution of these nanocomposites. Afterward, the cell viability assay was conducted on HCT116 and HGF cell lines for evaluating biocompatibility and targeting efficiency of nanocomposites; FA functionalized nanocomposites have intensively indicated better performance in cancer cells targeting and their inhibition, and IC50 was attained for 10 ng/mL of Ge-Ag@NMOF-CS-FA while non-targeted nanocarriers did not have toxicity more than 20 % on HCT116 colon cancer cells. Moreover, according to the results, the cell viability of HGF normal cells was at least 85 % after being exposed to different concentrations of nanocomposites for 24 h. This indicates that the synthesized nanocomposites do not have significant toxic effects on normal cells. The results indicate that this novel nanocomposite has the potential to effectively deliver drugs to cancer cells.

SERS sensing for cancer biomarker: Approaches and directions

These days, cancer is thought to be more than just one illness, with several complex subtypes that require different screening approaches. These subtypes can be distinguished by the distinct markings left by metabolites, proteins, miRNA, and DNA. Personalized illness management may be possible if cancer is categorized according to its biomarkers. In order to stop cancer from spreading and posing a significant risk to patient survival, early detection and prompt treatment are essential. Traditional cancer screening techniques are tedious, time-consuming, and require expert personnel for analysis. This has led scientists to reevaluate screening methodologies and make use of emerging technologies to achieve better results. Using time and money saving techniques, these methodologies integrate the procedures from sample preparation to detection in small devices with high accuracy and sensitivity. With its proven potential for biomedical use, surface-enhanced Raman scattering (SERS) has been widely used in biosensing applications, particularly in biomarker identification. Consideration was given especially to the potential of SERS as a portable clinical diagnostic tool. The approaches to SERS-based sensing technologies for both invasive and non-invasive samples are reviewed in this article, along with sample preparation techniques and obstacles. Aside from these significant constraints in the detection approach and techniques, the review also takes into account the complexity of biological fluids, the availability of biomarkers, and their sensitivity and selectivity, which are generally lowered. Massive ways to maintain sensing capabilities in clinical samples are being developed recently to get over this restriction. SERS is known to be a reliable diagnostic method for treatment judgments. Nonetheless, there is still room for advancement in terms of portability, creation of diagnostic apps, and interdisciplinary AI-based applications. Therefore, we will outline the current state of technological maturity for SERS-based cancer biomarker detection in this article. The review will meet the demand for reviewing various sample types (invasive and non-invasive) of cancer biomarkers and their detection using SERS. It will also shed light on the growing body of research on portable methods for clinical application and quick cancer detection.

Aiming for Maximized and Reproducible Enhancements in the Obstacle Race of SERS

Surface enhanced Raman scattering (SERS), since its discovery in the mid-1970s, has taken on many roles in the world of analytical measurement science. From identifying known and unknown chemicals in mixtures such as pharmaceutical and environmental samples to enabling qualitative and quantitative analysis of biomolecules and biomedical disease markers (or biomarkers), furthermore expanding to tracking nanostructures in vivo for medical diagnosis and therapy. This is because SERS combines the inherent power of Raman scattering capable of molecular species identification, topped with tremendous amplification in the Raman signal intensity when the molecule of interest is positioned near plasmonic nanostructures. The higher the SERS signal amplification, the lower the limit of detection (LOD) that could be achieved for the above applications. Therefore, improving SERS sensing efficiencies is vital. The signal reproducibility and SERS enhancement factor (EF) heavily rely on plasmonic nanostructure design, which has led to tremendous work in the field. But SERS signal and EF reproducibility remain key limitations for its wider market usability. This Review will scrutinize factors, some recognized and some often overlooked, that dictate the SERS signal and are of utmost importance to enable reproducible SERS EFs. Most of the factors pertain to colloidal labeled SERS. Some critically reviewed factors include the nanostructure's surface area as a limiting factor, SERS hot-spots including optimizing the SERS EF within the hot-spot volume and positioning labels, properties of label molecules governing molecule orientation in hot-spots, and resonance effects. A better understanding of these factors will enable improved optimization and control of the experimental SERS, enabling extremely sensitive LODs without overestimating the SERS EFs. These are crucial steps toward identification and reproducible quantification in SERS sensing.

Application of microfluidic technology based on surface-enhanced Raman scattering in cancer biomarker detection: A review

With the continuous discovery and research of predictive cancer-related biomarkers, liquid biopsy shows great potential in cancer diagnosis. Surface-enhanced Raman scattering (SERS) and microfluidic technology have received much attention among the various cancer biomarker detection methods. The former has ultrahigh detection sensitivity and can provide a unique fingerprint. In contrast, the latter has the characteristics of miniaturization and integration, which can realize accurate control of the detection samples and high-throughput detection through design. Both have the potential for point-of-care testing (POCT), and their combination (lab-on-a-chip SERS (LoC-SERS)) shows good compatibility. In this paper, the basic situation of circulating proteins, circulating tumor cells, exosomes, circulating tumor DNA (ctDNA), and microRNA (miRNA) in the diagnosis of various cancers is reviewed, and the detection research of these biomarkers by the LoC-SERS platform in recent years is described in detail. At the same time, the challenges and future development of the platform are discussed at the end of the review. Summarizing the current technology is expected to provide a reference for scholars engaged in related work and interested in this field.

The bioengineered and multifunctional nanoparticles in pancreatic cancer therapy: Bioresponisive nanostructures, phototherapy and targeted drug delivery

The multidisciplinary approaches in treatment of cancer appear to be essential in term of bringing benefits of several disciplines and their coordination in tumor elimination. Because of the biological and malignant features of cancer cells, they have ability of developing resistance to conventional therapies such as chemo- and radio-therapy. Pancreatic cancer (PC) is a malignant disease of gastrointestinal tract in which chemotherapy and radiotherapy are main tools in its treatment, and recently, nanocarriers have been emerged as promising structures in its therapy. The bioresponsive nanocarriers are able to respond to pH and redox, among others, in targeted delivery of cargo for specific treatment of PC. The loading drugs on the nanoparticles that can be synthetic or natural compounds, can help in more reduction in progression of PC through enhancing their intracellular accumulation in cancer cells. The encapsulation of genes in the nanoparticles can protect against degradation and promotes intracellular accumulation in tumor suppression. A new kind of therapy for cancer is phototherapy in which nanoparticles can stimulate both photothermal therapy and photodynamic therapy through hyperthermia and ROS overgeneration to trigger cell death in PC. Therefore, synergistic therapy of phototherapy with chemotherapy is performed in accelerating tumor suppression. One of the important functions of nanotechnology is selective targeting of PC cells in reducing side effects on normal cells. The nanostructures are capable of being surface functionalized with aptamers, proteins and antibodies to specifically target PC cells in suppressing their progression. Therefore, a specific therapy for PC is provided and future implications for diagnosis of PC is suggested.

DNA origami-mediated plasmonic dimer nanoantenna-based SERS biosensor for ultrasensitive determination of trace diethylstilbestrol

Diethylstilbestrol (DES) is a threatening factor to the human endocrine system. Here, we reported a DNA origami-assembled plasmonic dimer nanoantenna-based surface-enhanced Raman scattering (SERS) biosensor for measuring trace DES in foods. A critical factor influencing the SERS effect is interparticle gap modulation of SERS hotspots with nanometer-scale accuracy. DNA origami technology aims to generate naturally perfect structures with nano-scale precision. Exploiting the specificity of base-pairing and spatial addressability of DNA origami to form plasmonic dimer nanoantenna, the designed SERS biosensor generated electromagnetic-enhancement and uniform-enhancement hotspots to improve sensitivity and uniformity. Owing to their high target-binding affinity, aptamer-functionalized DNA origami biosensors transduced the target recognition into dynamic structural transformations of plasmonic nanoantennas, which were further converted to amplified Raman outputs. A broad linear range from 10-10 to 10-5 M was obtained with the detection limit of 0.217 nM. Our findings demonstrate the utility of aptamer-integrated DNA origami-based biosensors as a promising approach for trace analysis of environmental hazards.

Two-dimensional glass/p-ATP/Ag NPs as multifunctional SERS substrates for label-free quantification of uric acid in sweat

Abnormal uric acid (UA) content in body fluids can fully reflect the status of metabolism and immunity in the body. We have developed a simple, efficient and label-free surface enhanced Raman scattering (SERS) method for UA detection. Briefly, p-aminothiophenol (p-ATP) was used as the internal standard molecule and linking molecule to prepare a glass/p-ATP/Ag NPs SERS substrate. The Raman characteristic peak of p-ATP at 1076 cm^-1 can be used as an internal standard molecule to correct the signal fluctuation of UA detection. The results show that the SERS method owns a linear response with a ranging from 5 × 10^-6 to 10^-3 M of UA characteristic peak of both 693 cm^-1 and 493 cm^-1 with a determination coefficient (R²) of 0.9878 and 0.9649, respectively. Additionally, the SERS sensor has been further used for the analysis of UA in sweat and good recoveries were obtained for the sensing of sweat. We believe that the developed SERS substrate has potential for applications in healthcare monitoring.

Rapid Detection of the Monkeypox Virus Genome and Antigen Proteins Based on Surface-Enhanced Raman Spectroscopy

The conventional detection methods cannot satisfy the need for early and rapid detection of monkeypox virus (MPXV) infection. This is due to complicated pretreatment, time consumption, and complex operation of the diagnostic tests. Based on surface-enhanced Raman spectroscopy (SERS), this study attempted to capture the characteristic fingerprints of the MPXV genome and multiple antigenic proteins without the need to design specific probes. The minimum detection limit of this method is 100 copies/mL, with good reproducibility and signal-to-noise ratio. Therefore, the relationship between characteristic peak intensity and the protein and nucleic acid concentration can be used to construct a concentration-dependent spectral line with a good linear relationship. Additionally, principal component analysis (PCA) could identify the SERS spectra of four different MPXV proteins in serum. Therefore, this rapid detection method in the current outbreak of monkeypox control and the future response to possible new outbreaks has broad application prospects.

A cell wall-targeted organic-inorganic hybrid nano-catcher for ultrafast capture and SERS detection of invasive fungi

Due to the extended culture period and various inconveniences in vitro culture, the detection of invasive fungi is rather difficult, leading to high mortality rates of the diseases caused by them. It is, however, crucial for clinical therapy and lowering patient mortality to quickly identify invasive fungus from clinical specimens. A promising non-destructive method for finding fungi is surface-enhanced Raman scattering (SERS), however, its substrate has a low level of selectivity. Clinical sample components can obstruct the target fungi's SERS signal on account of their complexity. Herein, an MNP@PNIPAMAA hybrid organic-inorganic nano-catcher was created by using ultrasonic-initiated polymerization. The caspofungin (CAS), a fungus cell wall-targeting drug, is used in this study. We investigated MNP@PNIPAMAA-CAS as a technique to rapidly extract fungus from complex samples under 3 s. SERS could subsequently be used to instantly identify the fungi that were successfully isolated with an efficacy rate of about 75%. The entire process took just 10 min. This method is an important breakthrough that might be advantageous in terms of the rapid detection of invasive fungi.

A clinically feasible diagnostic spectro-histology built on SERS-nanotags for multiplex detection and grading of breast cancer biomarkers

Simultaneous detection of multiple biomarkers is always an obstacle in immunohistochemical (IHC) analysis. Herein, a straightforward spectroscopy-driven histopathologic approach has emerged as a paradigm of Raman-label (RL) nanoparticle probes for multiplex recognition of pertinent biomarkers in heterogeneous breast cancer. The nanoprobes are constructed by sequential incorporation of signature RL and target specific antibodies on gold nanoparticles, which are coined as Raman-Label surface enhanced Raman scattering (RL-SERS)-nanotags to evaluate simultaneous recognition of clinically relevant breast cancer biomarkers i.e., estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor2 (HER2). As a foot-step assessment, breast cancer cell lines having varied expression levels of the triple biomarkers are investigated. Subsequently, the optimized detection strategy using RL-SERS-nanotags is subjected to clinically confirmed, retrospective formalin-fixed paraffin embedded (FFPE) breast cancer tissue samples to fish out the quick response of singleplex, duplex as well as triplex biomarkers in a single tissue specimen by adopting a ratiometric signature RL-SERS analysis which enabled to minimize the false negative and positive results. Significantly, sensitivity and specificity of 95% and 92% for singleplex, 88% and 85% for duplex, and 75% and 67% for triplex biomarker has been achieved by assessing specific Raman fingerprints of the respective SERS-tags. Furthermore, a semi-quantitative evaluation of HER2 grading between 4+/2+/1+ tissue samples was also achieved by the Raman intensity profiling of the SERS-tag, which is fully in agreement with the expensive fluorescent in situ hybridization analysis. Additionally, the practical diagnostic applicability of RL-SERS-tags has been achieved by large area SERS imaging of areas covering 0.5-5 mm2 within 45 min. These findings unveil an accurate, inexpensive and multiplex diagnostic modality envisaging large-scale multi-centric clinical validation.

Recent advances in optical aptasensors for biomarkers in early diagnosis and prognosis monitoring of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) accounts for approximately 90% of all primary liver cancers and is one of the main malignant tumor types globally. It is essential to develop rapid, ultrasensitive, and accurate strategies for the diagnosis and surveillance of HCC. In recent years, aptasensors have attracted particular attention owing to their high sensitivity, excellent selectivity, and low production costs. Optical analysis, as a potential analytical tool, offers the advantages of a wide range of targets, rapid response, and simple instrumentation. In this review, recent progress in several types of optical aptasensors for biomarkers in early diagnosis and prognosis monitoring of HCC is summarized. Furthermore, we evaluate the strengths and limitations of these sensors and discuss the challenges and future perspectives for their use in HCC diagnosis and surveillance.

Application of SERS in In-Vitro Biomedical Detection

Surface-enhanced Raman scattering (SERS), as a rapid and nondestructive biological detection method, holds great promise for clinical on spot and early diagnosis. In order to address the challenging demands of on spot detection of biomedical samples, a variety of strategies has been developed. These strategies include substrate structural and component engineering, data processing techniques, as well as combination with other analytical methods. This report summarizes the recent SERS developments for biomedical detection, and their promising applications in cancer detection, virus or bacterial infection detection, miscarriage spotting, neurological disease screening et al. The first part discusses the frequently used SERS substrate component and structures, the second part reports on the detection strategies for nucleic acids, proteins, bacteria, and virus, the third part summarizes their promising applications in clinical detection in a variety of illnesses, and the forth part reports on recent development of SERS in combination with other analytical techniques. The special merits, challenges, and perspectives are discussed in both introduction and conclusion sections.

Monolayer Iron Oxychloride with a Resonant Band Structure for Ultrasensitive Molecular Sensing

Two-dimensional layered materials (2DLMs) are expected to be next-generation commercial sensors for surface-enhanced Raman scattering (SERS) sensing owing to their unique structural features and physicochemical properties. The low sensitivity and poor universality of 2DLMs are the dominant barriers toward their practical applications. Herein, we report that monolayer iron oxychloride (FeOCl) with a naturally suitable band structure is a promising candidate for ultrasensitive SERS sensing. The generally boosted Raman scattering cross section of different analyte-FeOCl systems benefits from the resonant photoinduced charge transfer processes and strong ground-state interactions. In addition, the strong adsorption ability of monolayer FeOCl is crucial for rapid detection in practical applications, which is proven to be much better than those of conventional SERS sensors. Consequently, monolayer FeOCl enables diverse SERS applications, including multicomponent analysis, chemical reaction monitoring, and indirect ion sensing.

Nanomaterials meet surface-enhanced Raman scattering towards enhanced clinical diagnosis: a review

Surface-enhanced Raman scattering (SERS) is a very promising tool for the direct detection of biomarkers for the diagnosis of i.e., cancer and pathogens. Yet, current SERS strategies are hampered by non-specific interactions with co-existing substances in the biological matrices and the difficulties of obtaining molecular fingerprint information from the complex vibrational spectrum. Raman signal enhancement is necessary, along with convenient surface modification and machine-based learning to address the former issues. This review aims to describe recent advances and prospects in SERS-based approaches for cancer and pathogens diagnosis. First, direct SERS strategies for key biomarker sensing, including the use of substrates such as plasmonic, semiconductor structures, and 3D order nanostructures for signal enhancement will be discussed. Secondly, we will illustrate recent advances for indirect diagnosis using active nanomaterials, Raman reporters, and specific capture elements as SERS tags. Thirdly, critical challenges for translating the potential of the SERS sensing techniques into clinical applications via machine learning and portable instrumentation will be described. The unique nature and integrated sensing capabilities of SERS provide great promise for early cancer diagnosis or fast pathogens detection, reducing sanitary costs but most importantly allowing disease prevention and decreasing mortality rates.

Vibrational spectroscopy for decoding cancer microbiota interactions: Current evidence and future perspective

The role of human microbiota in cancer initiation and progression is recognized in recent years. In order to investigate the interactions between cancer cells and microbes, a systematic analysis using various emerging techniques is required. Owing to the label-free, non-invasive and molecular fingerprinting characteristics, vibrational spectroscopy is uniquely suited to decode and understand the relationship and interactions between cancer and the microbiota at the molecular level. In this review, we first provide a quick overview of the fundamentals of vibrational spectroscopic techniques, namely Raman and infrared spectroscopy. Next, we discuss the emerging evidence underscoring utilities of these spectroscopic techniques to study cancer or microbes separately, and share our perspective on how vibrational spectroscopy can be employed at the intersection of the two fields. Finally, we envision the potential opportunities in exploiting vibrational spectroscopy not only in basic cancer-microbiome research but also in its clinical translation, and discuss the challenges in the bench to bedside translation.

Early assessment of chemotherapeutic response in hepatocellular carcinoma based on serum surface-enhanced Raman spectroscopy

In clinical practice, the transcatheter arterial chemoembolization (TACE) has been widely accepted as the first option for non-surgical hepatocellular carcinoma (HCC) treatment. However, patients with HCC often suffer from poor response to TACE therapy. This can be prevented if the chemotherapeutic response can be early and accurately assessed, which is essential to guide timely and rational management. In this study, the serum SERS technique was for the first time investigated as a potential prognostic tool for early assessment of HCC chemotherapeutic response. According to the SERS spectral analysis results, it is newly found that not only the absolute circulating nucleic acids and collagen levels in pre-therapeutic serum but also the changes in circulating nucleic acids and amino acids between pre-therapeutic and post-therapeutic serum are expected to be potential serum markers for HCC prognosis. By further applying chemometrics methods to establish prognostic models, excellent prognostic accuracies were achieved within only 3 days after TACE therapy. Thus, the proposed method is expected to provide guidance on timely and rational management of HCC to improve its survival rate.

A non-invasive ultrasensitive diagnostic approach for COVID-19 infection using salivary label-free SERS fingerprinting and artificial intelligence

Clinical diagnostics for SARS-CoV-2 infection usually comprises the sampling of throat or nasopharyngeal swabs that are invasive and create patient discomfort. Hence, saliva is attempted as a sample of choice for the management of COVID-19 outbreaks that cripples the global healthcare system. Although limited by the risk of eliciting false-negative and positive results, tedious test procedures, requirement of specialized laboratories, and expensive reagents, nucleic acid-based tests remain the gold standard for COVID-19 diagnostics. However, genetic diversity of the virus due to rapid mutations limits the efficiency of nucleic acid-based tests. Herein, we have demonstrated the simplest screening modality based on label-free surface enhanced Raman scattering (LF-SERS) for scrutinizing the SARS-CoV-2-mediated molecular-level changes of the saliva samples among healthy, COVID-19 infected and COVID-19 recovered subjects. Moreover, our LF-SERS technique enabled to differentiate the three classes of corona virus spike protein derived from SARS-CoV-2, SARS-CoV and MERS-CoV. Raman spectral data was further decoded, segregated and effectively managed with the aid of machine learning algorithms. The classification models built upon biochemical signature-based discrimination method of the COVID-19 condition from the patient saliva ensured high accuracy, specificity, and sensitivity. The trained support vector machine (SVM) classifier achieved a prediction accuracy of 95% and F1-score of 94.73%, and 95.28% for healthy and COVID-19 infected patients respectively. The current approach not only differentiate SARS-CoV-2 infection with healthy controls but also predicted a distinct fingerprint for different stages of patient recovery. Employing portable hand-held Raman spectrophotometer as the instrument and saliva as the sample of choice will guarantee a rapid and non-invasive diagnostic strategy to warrant or assure patient comfort and large-scale population screening for SARS-CoV-2 infection and monitoring the recovery process.

Visual Detection of COVID-19 from Materials Aspect

Abstract

In the recent COVID-19 pandemic, World Health Organization emphasized that early detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses. Several diagnostic methods, such as reverse transcription-polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA), have been applied based on the mechanism of specific recognition and binding of the probes to viruses or viral antigens. Although the remarkable progress, these methods still suffer from inadequate cellular materials or errors in the detection and sampling procedure of nasopharyngeal/oropharyngeal swab collection. Therefore, developing accurate, ultrafast, and visualized detection calls for more advanced materials and technology urgently to fight against the epidemic. In this review, we first summarize the current methodologies for SARS-CoV-2 diagnosis. Then, recent representative examples are introduced based on various output signals (e.g., colorimetric, fluorometric, electronic, acoustic). Finally, we discuss the limitations of the methods and provide our perspectives on priorities for future test development.

Graphical Abstract

Plasma Electroless Reduction: A Green Process for Designing Metallic Nanostructure Interfaces onto Polymeric Surfaces and 3D Scaffolds

The design of metal nanoparticle-modified polymer surfaces in a green and scalable way is both desirable and highly challenging. Herein, a new green low-temperature plasma-based in situ surface reduction strategy termed plasma electroless reduction (PER) is reported for achieving in situ metallic nanostructuring on polymer surfaces. Proof of concept for this new method was first demonstrated on hydrophilic cellulose papers. Cellulose papers were dip-coated with different metal ion (Ag⁺ and Au³⁺) solutions and then subjected to hydrogen plasma treatment for this PER process. Transmission electron microscopy (TEM) analysis has revealed that this PER process caused anisotropic growth of either gold or silver nanoparticles, resulting in the time-dependent formation of both distinct spherical nanoparticles (∼20 nm) and anisotropic 2D nanosheets. Furthermore, we have demonstrated the adaptability of this process by applying it to hydrophobic fibrous and 3D printed polymeric materials such as surgical face masks and 3D printed polylactic acid scaffolds. The PER process on these hydrophobic polymer surfaces was accomplished via a sequential combination of air plasma and hydrogen plasma treatment. The metallic nanostructuring caused by the PER process on these hydrophobic surfaces was systematically studied using different surface imaging techniques including 3D confocal laser surface scanning microscopy and scanning electron microscopy. We have also systematically optimized the PER process on the surface of 3D scaffolds via varying the concentration of the silver ion precursor and by different postprocessing methods such as sonication and medium soaking. These optimization processes were found to be very important in generating uniform metallic nanoparticle-modified 3D printed scaffolds while simultaneously improving cytocompatibility. Through joint disk diffusion and inhibitory concentration testing, the antibacterial efficacy of silver coatings on face masks and 3D scaffolds was established. Altogether, these results clearly suggest the excellent futuristic potential of this new PER method for designing metallic nanostructured interfaces for different biomedical applications.

Boosting bacteria differentiation efficiency with multidimensional surface-enhanced Raman scattering: the example of Bacillus cereus

Surface-enhanced Raman scattering (SERS) is a powerful tool for constructing biomolecular fingerprints, which play a vital role in differentiation of bacteria. Due to the rather subtle differences in the SERS spectra among different bacteria, artificial intelligence is usually adopted and enormous amounts of spectral data are required to improve the differentiation efficiency. However, in many cases, large volume data acquisition on bacteria is not only technical difficult but labour intensive. It is known that surface modification of SERS nanomaterials can bring additional dimensionality (difference) of the SERS fingerprints. Here in this work, we show that the concept could be used to improve the bacteria differentiation efficiency. Ag NPs were modified with 11-mercaptoundecanoic acid, 11-mercapto-1-undecanol, and 1-dodecanethiol to provide additional dimensionality. The modified NPs then were mixed with cell lysate from different strains of Bacillus cereus (B. cereus). Even by applying a simple PCA process to the resulting SERS spectra data, all the three modified Ag NPs showed superior differentiation results compared with bare Ag NPs, which could only separate Staphylococcus aureus (S. aureus) and B. cereus. It is believed that the multidimensional SERS could find great potential in bacteria differentiation.

Insight into prognostics, diagnostics, and management strategies for SARS CoV-2

The foremost challenge in countering infectious diseases is the shortage of effective therapeutics. The emergence of coronavirus disease (COVID-19) outbreak has posed a great menace to the public health system globally, prompting unprecedented endeavors to contain the virus. Many countries have organized research programs for therapeutics and management development. However, the longstanding process has forced authorities to implement widespread infrastructures for detailed prognostic and diagnostics study of severe acute respiratory syndrome (SARS CoV-2). This review discussed nearly all the globally developed diagnostic methodologies reported for SARS CoV-2 detection. We have highlighted in detail the approaches for evaluating COVID-19 biomarkers along with the most employed nucleic acid- and protein-based detection methodologies and the causes of their severe downfall and rejection. As the variable variants of SARS CoV-2 came into the picture, we captured the breadth of newly integrated digital sensing prototypes comprised of plasmonic and field-effect transistor-based sensors along with commercially available food and drug administration (FDA) approved detection kits. However, more efforts are required to exploit the available resources to manufacture cheap and robust diagnostic methodologies. Likewise, the visualization and characterization tools along with the current challenges associated with waste-water surveillance, food security, contact tracing, and their role during this intense period of the pandemic have also been discussed. We expect that the integrated data will be supportive and aid in the evaluation of sensing technologies not only in current but also future pandemics.

Diagnosis and staging of diffuse large B-cell lymphoma using label-free surface-enhanced Raman spectroscopy

Non-invasive diagnosis and staging of diffuse large B-cell lymphoma (DLBCL) were achieved using label-free surface-enhanced Raman spectroscopy (SERS). SERS spectra were measured for serum samples of DLBCL patients at different progressive stages and healthy controls (HCs), using colloidal silver nano-particles (AgNPs) as the substrate. Differences in the spectral intensities of Raman peaks were observed between the DLBCL and HC groups, and a close correlation between the spectral intensities of Raman peaks with the progressive stages of the cancer was obtained, demonstrating the possibility of diagnosis and staging of the disease using the serum SERS spectra. Multivariate analysis methods, including principal component analysis (PCA), linear discriminant analysis (LDA), support vector machine (SVM) classifier, and k-nearest neighbors (kNN) classifier, were used to build the diagnosis and staging models for DLBCL. Leave-one-out cross-validation was used to evaluate the performances of the models. The kNN model achieved the best performances for both diagnosis and staging of DLBCL: for the diagnosis analysis, the accuracy, sensitivity, and specificity were 87.3%, 0.921, and 0.809, respectively; for the staging analysis between the early (Stage I & II) and the late (Stage III & IV) stages, the accuracy was 90.6%, and the sensitivity values for the early and the late stages were 0.947 and 0.800, respectively. The label-free serum SERS in combination with multivariate analysis could serve as a potential technique for non-invasive diagnosis and staging of DLBCL.

Towards a protein-selective Raman enhancement by a glycopolymer-based composite surface

Surface-enhanced Raman scattering (SERS), which is based on the surface plasmon resonance (LSPR) of noble metal nanostructures, is widely used in the biological field due to its advantages of non-damaging samples and detection up to the molecular level. For biological SERS detection, preparation of substrates with biocompatibility and specific adsorption, leading to selective enhancement of the target biomolecules, are important design strategies. Utilizing the specific interaction between a carbohydrate and protein, a glycopolymer-based composite surface is fabricated to realize specific SERS detection of proteins. Herein, we use N-3,4-dihydroxybenzeneethyl methacrylamide (DMA), 2-deoxy-2-(methacrylamido)glucopyranose (MAG) and methacrylic acid (MAA) as monomers in a sunlight-induced RAFT polymerization to synthesize a dopamine-containing glycopolymer. The glycopolymers are used to prepare a SERS substrate. The composite surface shows specific protein adsorption capacity, and the selective Raman enhancement of specific proteins was successfully achieved between the two different proteins Con A and BSA. This provides a feasible approach to design a SERS surface for protein detection and the study of the interaction between sugar and proteins.

SERS nanotags for folate receptor α detection at the single cell level: discrimination of overexpressing cells and potential for live cell applications

Development of nanotags based on Surface-Enhanced Raman Scattering (SERS) for the discrimination of cancer cells overexpressing folate receptor α. Nanotags are also applicable for live cell measurements.

Decreasing hyaluronic acid combined with drug-loaded nanoprobes improve the delivery and efficacy of chemotherapeutic drugs for pancreatic cancer

Pancreatic cancer is one of the common malignant tumors of the digestive system, and its clinical treatment is still very challenging. Most of the pancreatic cancer chemotherapeutic drugs have poor plasma stability, low cell uptake efficiency, and are prone to developing drug resistance and toxic side effects. Besides, pancreatic cancer often has a dense extracellular matrix, which consists of collagens, hyaluronic acid, and other proteoglycans. Among them, hyaluronic acid is a key component of the dense matrix, which results in vascular compression and insufficient perfusion, and hinders the delivery of chemotherapeutic drugs. In this study, we explore using hyaluronidase in tumor-bearing mice to eliminate the hyaluronic acid barrier, to reduce blood vessel compression and reshape the tumor microenvironment. In addition, we evaluate using doxorubicin-loaded nanoprobes to improve the stability and local tumor-killing effect of the drug. The nanoprobes have the characteristics of near-infrared optical imaging, which are used to monitor the tumor size in real-time during the treatment process, and dynamically observe the tumor inhibitory effect. The results show that elimination of the hyaluronic acid barrier combined with the doxorubicin-loaded nanoprobes can greatly increase drug penetration into tumor tissue and improve the effectiveness of chemotherapy drugs. This study provides a novel strategy for the treatment of pancreatic cancer.

Dynamic self-assembly of mannosylated-calix[4]arene into micelles for the delivery of hydrophobic drugs

Carbohydrate-lectin interactions and glycol-molecule-driven self-assembly are powerful yet challenging strategies to create supramolecular nanostructures for biomedical applications. Herein, we develop a modular approach of micellization with a small molecular mannosylated-calix[4]arene synthetic core, CA₄-Man3, to generate nano-micelles, CA₄-Man3-NPs, which can target cancer cell surface receptors and facilitate the delivery of hydrophobic cargo. The oligomeric nature of the calix[4]arene enables the dynamic self-assembly of calix[4]arene (CA₄), where an amphiphile, functionalized with mannose units (CA-glycoconjugates) in the upper rim and alkylated lower rim, afforded the CA₄-Man3-NPs in a controllable manner. The presence of thiourea units between calixarene and tri-mannose moiety facilitated the formation of a stable core with bidentate hydrogen bonds, which in turn promoted mannose receptor targeted uptake and helped in the intracellular pH-responsive release of antineoplastic doxorubicin (Dox). Physiochemical features including the stability of the nanomicelle could circumvent the undesirable leakage of the cargoes, ensuring maximum therapeutic output with minimum off-targeted toxicity. Most importantly, surface-enhanced Raman scattering (SERS) was utilized for the first time to evaluate the critical micelle concentration during the formation, cellular uptake and intracellular drug release. The present study not only provides an architectural design of a new class of organic small molecular nanomicelles but also unveils a robust self-assembly approach that paves the way for the delivery of a wide range of hydrophobic chemotherapeutic drugs.

A Novel and Rapid Serum Detection Technology for Non-Invasive Screening of Gastric Cancer Based on Raman Spectroscopy Combined With Different Machine Learning Methods

Gastric cancer (GC) is the fifth most common cancer in the world and a serious threat to human health. Due to its high morbidity and mortality, a simple, rapid and accurate early screening method for GC is urgently needed. In this study, the potential of Raman spectroscopy combined with different machine learning methods was explored to distinguish serum samples from GC patients and healthy controls. Serum Raman spectra were collected from 109 patients with GC (including 35 in stage I, 14 in stage II, 35 in stage III, and 25 in stage IV) and 104 healthy volunteers matched for age, presenting for a routine physical examination. We analyzed the difference in serum metabolism between GC patients and healthy people through a comparative study of the average Raman spectra of the two groups. Four machine learning methods, one-dimensional convolutional neural network, random forest, support vector machine, and K-nearest neighbor were used to explore identifying two sets of Raman spectral data. The classification model was established by using 70% of the data as a training set and 30% as a test set. Using unseen data to test the model, the RF model yielded an accuracy of 92.8%, and the sensitivity and specificity were 94.7% and 90.8%. The performance of the RF model was further confirmed by the receiver operating characteristic (ROC) curve, with an area under the curve (AUC) of 0.9199. This exploratory work shows that serum Raman spectroscopy combined with RF has great potential in the machine-assisted classification of GC, and is expected to provide a non-destructive and convenient technology for the screening of GC patients.

Elucidating Gold-MnO2 Core-Shell Nanoenvelope for Real Time SERS-Guided Photothermal Therapy on Pancreatic Cancer Cells

Pancreatic cancer represents one of the most aggressive in nature with a miserable prognosis that warrants efficient diagnostic and therapeutic interventions. Herein, a MnO₂ overlaid gold nanoparticle (AuNPs) based photothermal theranostic nanoenvelope (PTTNe:MnO₂@AuNPs) was fabricated to substantiate surface-enhanced Raman spectroscopy (SERS) guided real-time monitoring of photothermal therapy (PTT) in pancreatic cancer cells. A sharp enhancement of the fingerprint Raman signature of MnO₂ at 569 cm^-1 exhibited as a marker peak for the first time to elucidate the intracellular PTT event. In this strategic design, the leftover bare AuNPs after the degradation of the MnO₂ layer from the nanoenvelope in the presence of intracellular H₂O₂ enabled real-time tracking of biomolecular changes of Raman spectral variations during PTT. Moreover, the surface of the as-synthesized nanoenvelope was functionalized with a pancreatic cancer cell targeting peptide sequence for cholecystokinin fashioned the PTTNe with admirable stability and biocompatibility. Finally, the precise cell death mechanism was explicitly assessed by SERS spectral analysis as a complementary technique. This targeted phototheranostic approach demonstrated in pancreatic cancer cells presented a therapeutically viable prototype for futuristic personalized cancer nanomedicine.

Sensitive, Reusable, Surface-Enhanced Raman Scattering Sensors Constructed with a 3D Graphene/Si Hybrid

Surface-enhanced Raman scattering (SERS) substrates based on graphene and its derivatives have recently attracted attention among those interested in the detection of trace molecules; however, these substrates generally show poor uniformity, an unsatisfactory enhancement factor, and require a complex fabrication process. Herein, we design and fabricate three-dimensional (3D) graphene/silicon (3D-Gr/Si) heterojunction SERS substrates to detect various types of molecules. Notably, the detection limit of 3D-Gr/Si can reach 10^-10 M for rhodamine 6G (R6G) and rhodamine B (RB), 10^-7 M for crystal violet (CRV), copper(II) phthalocyanine (CuPc), and methylene blue (MB), 10^-8 M for dopamine (DA), 10^-6 M for bovine serum albumin (BSA), and 10^-5 M for melamine (Mel), which is superior to most reported graphene-based SERS substrates. Besides, the proposed 3D-Gr/Si heterojunction SERS substrates can achieve a high uniformity with relative standard deviations (RSDs) of less than 5%. Moreover, the 3D-Gr/Si SERS substrates are reusable after washing with ethyl alcohol to remove the adsorbed molecules. These excellent SERS performances are attributed to the novel 3D structure and abundantly exposed atomically thin edges, which facilitate charge transfer between 3D-Gr and probe molecules. We believe that the 3D-Gr/Si heterojunction SERS substrates offer potential for practical applications in biochemical molecule detection and provide insight into the design of high-performance SERS substrates.

SERS Based Lateral Flow Immunoassay for Point-of-Care Detection of SARS-CoV-2 in Clinical Samples

The current scenario, an ongoing pandemic of COVID-19, places a dreadful burden on the healthcare system worldwide. Subsequently, there is a need for a rapid, user-friendly, and inexpensive on-site monitoring system for diagnosis. The early and rapid diagnosis of SARS-CoV-2 plays an important role in combating the outbreak. Although conventional methods such as PCR, RT-PCR, and ELISA, etc., offer a gold-standard solution to manage the pandemic, they cannot be implemented as a point-of-care (POC) testing arrangement. Moreover, surface-enhanced Raman spectroscopy (SERS) having a high enhancement factor provides quantitative results with high specificity, sensitivity, and multiplex detection ability but lacks in POC setup. In contrast, POC devices such as lateral flow immunoassay (LFIA) offer rapid, simple-to-use, cost-effective, reliable platform. However, LFIA has limitations in quantitative and sensitive analyses of SARS-CoV-2 detection. To resolve these concerns, herein we discuss a unique modality that is an integration of SERS with LFIA for quantitative analyses of SARS-CoV-2. The miniaturization ability of SERS-based devices makes them promising in biosensor application and has the potential to make a better alternative of conventional diagnostic methods. This review also demonstrates the commercially available and FDA/ICMR approved LFIA kits for on-site diagnosis of SARS-CoV-2.

Raman Imaging: An Impending Approach Towards Cancer Diagnosis

In accordance with the recent studies, Raman spectroscopy is well experimented as a highly sensitive analytical and imaging technique in biomedical research, mainly for various disease diagnosis including cancer. In comparison with other imaging modalities, Raman spectroscopy facilitate numerous assistances owing to its low background signal, immense spatial resolution, high chemical specificity, multiplexing capability, excellent photo stability and non-invasive detection capability. In cancer diagnosis Raman imaging intervened as a promising investigative tool to provide molecular level information to differentiate the cancerous vs non-cancerous cells, tissues and even in body fluids. Anciently, spontaneous Raman scattering is very feeble due to its low signal intensity and long acquisition time but new advanced techniques like coherent Raman scattering (CRS) and surface enhanced Raman scattering (SERS) gradually superseded these issues. So, the present review focuses on the recent developments and applications of Raman spectroscopy-based imaging techniques for cancer diagnosis.

Highly Biocompatible Plasmonically Encoded Raman Scattering Nanoparticles Aid Ultrabright and Accurate Bioimaging

Plasmonically engineered nanomaterials based on Au-Ag for surface-enhanced Raman scattering (SERS)-based biomedicine is of great importance but is still far behind clinical needs because of the poor compatibility between sensitivity and safety. Here, robust plasmonically encoded Raman scattering nanoparticles, named Au core-Raman-active molecule-Ag shell-Au shell nanoparticles (CMSS NPs), were synthesized. The as-developed CMSS NPs possess a unique exterior ultrathin Au shell (∼2.2 nm thickness) that plays double key roles as an effective wrapping layer as well as a plasmonic enhancing layer, thereby showing not only extraordinary stability against oxidative damages and bioerosion but also outstanding SERS sensitivity because of the stronger in-built electromagnetic field, achieving a significant SERS enhancement factor of 3.3 × 108. The results confirm that the individual CMSS NPs show ultrahigh brightness, reproducibility, selectivity, and biocompatibility in single-cell Raman imaging. Moreover, ultrabright in vivo tumor imaging with 1 × 1 mm2 area can be quickly achieved within 35 s under open-air condition. Furthermore, by secondary plasmonic encoding, the CMSS NPs flexibly serve as nanobeacon to monitor single-cell autophagy with improved accuracy. The CMSS NPs are expected as versatile SERS probes that enable ultrabright, fast, and precise Raman-based bioimaging and clinical bioapplications.

De novo design and synthesis of boomerang-shaped molecules and their in silico and SERS-based interactions with SARS-CoV-2 spike protein and ACE2

Boomerang shaped molecule and its interaction study with SARS-CoV-2 S-protein–ACE2 using molecular docking, SERS and UV-Vis spectroscopy.

Targeted Theranostic Nano Vehicle Endorsed with Self-Destruction and Immunostimulatory Features to Circumvent Drug Resistance and Wipe-Out Tumor Reinitiating Cancer Stem Cells

The downsides of conventional cancer monotherapies are profound and enormously consequential, as drug-resistant cancer cells and cancer stem cells (CSC) are typically not eliminated. Here, a targeted theranostic nano vehicle (TTNV) is designed using manganese-doped mesoporous silica nanoparticle with an ideal surface area and pore volume for co-loading an optimized ratio of antineoplastic doxorubicin and a drug efflux inhibitor tariquidar. This strategically framed TTNV is chemically conjugated with folic acid and hyaluronic acid as a dual-targeting entity to promote folate receptor (FR) mediated cancer cells and CD44 mediated CSC uptake, respectively. Interestingly, surface-enhanced Raman spectroscopy is exploited to evaluate the molecular changes associated with therapeutic progression. Tumor microenvironment selective biodegradation and immunostimulatory potential of the MSN-Mn core are safeguarded with a chitosan coating which modulates the premature cargo release and accords biocompatibility. The superior antitumor response in FR-positive syngeneic and CSC-rich human xenograft murine models is associated with a tumor-targeted biodistribution, favorable pharmacokinetics, and an appealing bioelimination pattern of the TTNV with no palpable signs of toxicity. This dual drug-loaded nano vehicle offers a feasible approach for efficient cancer therapy by on demand cargo release in order to execute complete wipe-out of tumor reinitiating cancer stem cells.

Surface charge modulates the internalization vs. penetration of gold nanoparticles: comprehensive scrutiny on monolayer cancer cells, multicellular spheroids and solid tumors by SERS modality

Precise control over the dynamics of nanoparticles (NPs) in a tumor microenvironment is highly warranted for the development of an efficient nanotheranostic agent. Even though inductively coupled plasma mass spectrometry can provide a quantitative assessment regarding the uptake efficiency of metal NPs, enumeration of deep tissue penetration capacity remains as a challenge. Herein, we have demonstrated an accurate tracking of the uptake efficiency and penetration phenomenon of gold nanoparticles (AuNPs: 40-50 nm) with respect to three different surface charges in monolayer (2D) cells, multicellular spheroids (3D) and in vivo tumors by surface-enhanced Raman spectroscopy (SERS). While positively charged AuNPs showed around two-fold increased internalization in monolayer cells, SERS-tag-based line scanning on multi-layered tumor spheroids illustrated almost nine-fold superior penetration capability with negatively charged AuNPs. Further, the enhanced solid tumor distribution contributed by the negatively charged AuNPs could appreciably escalate its clinical utility in cancer management.