Preparation of 3D flexible SERS substrates by mixing gold nanorods in hydrogels for the detection of malachite green and crystal violet.

A simple and cost-effective fabrication method of gold nanorods (AuNRs) nanoparticles hybridized with polyvinyl alcohol hydrogel (AuNR/PVA) for SERS substrate is described. The AuNR/PVA achieves the control of inter-particle nanogap by modulating the density of gold nanorods, and inter-particle nanogap by the spatial deformation of the hydrogel, and the reduction of the gap between the AuNRs deposited on hydrogel makes the SERS enhancement. In addition, the AuNR/PVA substrate maintains high SERS activity after more than 100 cycles of bending and storage in air for 30 days, and the substrate possesses high sensitivity and high reproducibility. Combining a flexible and transparent surface-enhanced Raman spectroscopy (SERS) substrate for in situ detection with a small portable Raman can be applied to scenarios such as environmental detection and hazardous materials detection. The substrate showed excellent SERS activity against malachite green (MG) and crystal violet (CV) with limits of detection of 1.18 × 10-13 M and 7.17 × 10-12 M, respectively. The usability of the proposed SERS substrate was demonstrated by detecting the above contaminants in aquatic water. This work not only utilizes a cost-effective method for mass production but also provides a reliable and convenient platform for the preparation of other noble metal flexible substrates.

Machine learning-based exosome profiling of multi-receptor SERS sensors for differentiating adenocarcinoma in situ from early-stage invasive adenocarcinoma.

Exosomes, extracellular vesicles released by cells, hold potential as diagnostic markers for the early detection of lung cancer. Despite their clinical promise, current technologies lack rapid and effective means to discriminate between exosomes derived from adenocarcinoma in situ (AIS) and early-stage invasive adenocarcinoma (IAC). This challenge arises from the intrinsic structural heterogeneity of exosomes, necessitating the development of advanced methodologies for precise differentiation. Here, we demonstrate a novel approach for plasma exosome detection utilizing multi-receptor surface-enhanced Raman spectroscopy (SERS) technology to differentiate between AIS and early-stage IAC. To accomplish this, we synthesized a stable and uniform two-dimensional SERS substrate (BC/Au NPs film) by fabricating gold nanoparticles onto bacterial cellulose. We then enhanced its capabilities by introducing multi-receptor SERS functionality via modifying the substrate with both low-specificity and physicochemical-selective molecules. Furthermore, by strategically combining all capturer-exosome SERS spectra, comprehensive "combined-SERS spectra" are reconstructed to enhance spectral variations of the exosome. Combining these features with partial least squares regression-discriminant analysis (PLS-DA) modeling significantly improved discriminatory accuracy, achieving 90% sensitivity and 95% specificity in distinguishing AIS from early-stage IAC. Our developed SERS sensor provides an effective method for early detection of lung cancer, thereby paving a new way for innovative advancements in diagnosing lung cancer.

Preparation of cellulose-based flexible SERS and its application for rapid and ultra-sensitive detection of thiram on fruits and vegetables.

In response to the prevalent issue of thiram as a common pesticide residue on the surface of fruits and vegetables, our research team employed an acidic hydrated metal salt low co-fusion solvent to dissolve cellulose lysis slurry. Subsequently, a regenerated cellulose membrane (RCM) was successfully prepared via sol-gel method. Uniformly sized Ag nanoparticles (NPs) were deposited on RCM utilizing the continuous ion layer adsorption and reaction (SILAR) technique. The resulting Ag NPs/RCM flexible surface-enhanced Raman spectroscopy (SERS) substrates exhibited a minimum detection limit of 5 × 10-9 M for Rhodamine 6G (R6G), demonstrating good uniformity (RSD = 4.86 %) and reproducibility (RSD = 3.07 %). Moreover, the substrate displayed a remarkable sensitivity of 10-10 M toward thiram standard solution. Given its inherent flexibility, the substrate proves advantageous for the detection of three-dimensional environments such as fruit and vegetable surfaces, and its practicality has been confirmed in the detection of thiram residue on apples, tomatoes, pears, and other fruits and vegetables.

Ultra-sensitive detection of tumor necrosis factor alpha based on silver-coated gold core shell and magnetically separated recognition of SERS aptamer sensors.

A highly sensitive tumor necrosis factor α (TNF-α) detection method based on a surface-enhanced Raman scattering (SERS) magnetic patch sensor is reported. Magnetic beads (MNPs) and core shells were used as the capture matrix and signaling probe, respectively. For this purpose, antibodies were immobilized on the surface of magnetic beads, and then Au@4-MBN@Ag core-shell structures coupled with aptamers and TNF-α antigen were added sequentially to form a sandwich immune complex. Quantitative analysis was performed by monitoring changes in the characteristic SERS signal intensity of the Raman reporter molecule 4-MBN. The results showed that the limit of detection (LOD) of the proposed method was 4.37 × 10-15 mg·mL-1 with good linearity (R2 = 0.9918) over the concentration range 10-12 to 10-5 mg·mL-1. Excellent assay accuracy was also demonstrated, with recoveries in the range 102% to 114%. Since all reactions occur in solution and are separated by magnetic adsorption of magnetic beads, this SERS-based immunoassay technique solves the kinetic problems of limited diffusion and difficult separation on solid substrates. The method is therefore expected to be a good clinical tool for the diagnosis of the inflammatory biomarker THF-α and in vivo inflammation screening.

Preparation of SERS base membrane with cellulose compound dopamine and determination of hypochlorite.

Flexible silver substrates were made by in situ reduction of silver nanoparticles in bacterial cellulose membranes using the unique advantage of dopamine. Subsequently, we modified the substrate with 4-mercaptophenol (4-MP), a molecule capable of specifically recognizing ClO-, and its corresponding SERS signal changes with the concentration of hypochlorite, thus allowing the quantitative detection of ClO- content. The method showed a negative linear correlation (R2 = 0.9567) with the SERS intensity at 1077 cm-1 over the concentration range 0.5-100 µM, and the detection limit was 0.15 µM. The RSD of the SERS intensity at 1077 cm-1 under five batches was 4.2%, which proved the good reproducibility of P-BCM-Ag NP-MP. Finally, the P-BCM-Ag NPs were used for the detection of hypochlorite in cell contents, artificial urine, and clinical serum samples, utilizing spike experiments in all three environments. The recoveries were in the range 90-110% indicating the accuracy of the method for the detection of hypochlorite and validating the promising application of this assay for practical detection in intricate biological samples.

Research Progress of SERS Sensors Based on Hydrogen Peroxide and Related Substances.

Hydrogen peroxide (H2O2) has an important role in living organisms, and its detection is of great importance in medical, chemical, and food safety applications. This review provides a comparison of different types of Surface-enhanced Raman scattering (SERS) sensors for H2O2 and related substances with respect to their detection limits, which are of interest due to high sensitivity compared to conventional sensors. According to the latest research report, this review focuses on the sensing mechanism of different sensors and summarizes the linear range, detection limits, and cellular applications of new SERS sensors, and discusses the limitations in vivo and future prospects of SERS technology for the detection of H2O2.

A study on the collapse characteristics of loess based on energy spectrum superposition method.

Mineral types form the basis for studying the structural stability of loess, and identifying mineral types at the microscopic scale has always been a difficult task. Identifying mineral types at the microscopic scale is very helpful in understanding the differential role that different minerals play in the structural stability of loess, and it can also clarify the specific mineral changes that occur during the process of humidification and dehumidification. Using an innovative energy spectrum superposition method, this article combines backscattered electron imaging and X-ray energy spectrum analysis results to achieve direct identification of the eight main minerals in loess, including quartz, illite, and chlorite, within SEM images. The mineral identification results provide a basis for statistical analysis of mineral water sensitivity and morphological changes under wetting conditions. The results demonstrate that chlorite and hematite, which account for no more than 23% of the loess composition, play a crucial role in binding. Furthermore, these minerals exhibit significant hydrolysis phenomena. Particularly, the intense decomposition of chlorite leads to the displacement of non-binding quartz and feldspar particles, thereby altering the pore structure of loess. These findings are of great significance in understanding the multi-level collapsibility of loess.

Green in situ immobilisation of gold nanoparticles on bacterial nanocellulose membranes using Tannic acid and its detection of Fe3.

Oxidative stress is one of the factors that promote melanogenesis. Trivalent iron ions play a key role in regulating the iron-catalysed oxidative stress response. A novel SERS flexible membrane sensor based on tannic acid with good sensitivity and uniformity was prepared by green in situ reduction of gold nanoparticles on bacterial cellulose membrane（BCM）with a simple and highly selective method to detect Fe3+. Under alkaline conditions, Fe3+ is adsorbed on the BCM-TA@Au NPs flexible membrane by tannic acid (TA) through chelation, thus enabling the detection of Fe3+. Furthermore, this simple detection system has a wide linear detection range and high sensitivity to effortlessly evaluate Fe3+ at concentrations up to 10-7 M. More importantly, the proposed SERS flexible substrate performed well in determining Fe3+ concentrations in B16 melanocytes, providing new insights into the factors affecting the melanin synthesis pathway and providing a potential biomarker for melanoma treatment.

Two-dimensional substrate assisted SERS immunosensor for accurate detection of carcinoembryonic antigen.

Accurate and sensitive detection of carcinoembryonic antigen (CEA) is essential for the detection of various diseases in healthcare and the medical field. Currently, due to the high false negative rate of CEA assay in clinical setting and its use as a common indicator for early cancer screening, a novel CEA detection method with high sensitivity, increased specificity and the lower cost has become a clinical challenge. Here, a facile sandwich type immunosensor based on surface-enhanced Raman scattering (SERS) was presented including 4-mercaptobenzonitrile (4MBN) labeled gold core-silver shell nanoparticles (Au@4MBN@Ag NPs) as SERS tag and 4-mercaptophenylboronic acid (4-MPBA) functionalized two-dimensional (2D) silver nanoparticle film (Ag FM) as SERS capture substrate for CEA detection. A linearity of 10-9-10-14M was observed with high sensitivity and excellent selectivity for the detection of CEA. Additionally, the spiking experiment yielded 105.33-127.00% recovery with variation coefficients below 10% demonstrating high assay accuracy and precision. The immunosensor we proposed here is a promising approach to quantify CEA in liquid biopsy samples with high sensitivity, which could be further developed for early cancer screening.

A novel "on-off" SERS nanoprobe based on sulfonated cellulose nanofiber-Ag composite for selective determination of NADH in human serum.

A novel S-CNF-based nanocomposite was created using sulfonated cellulose nanofiber (S-CNF) to enable the detection of NADH in serum by surface-enhanced Raman spectroscopy (SERS). The numerous hydroxyl and sulfonic acid groups on the S-CNF surface absorbed silver ions and converted them to silver seeds, which formed the load fulcrum. After adding a reducing agent, silver nanoparticles (Ag NPs) were firmly adhered to the S-CNF surface to form stable 1D "hot spots." The S-CNF-Ag NP substrate demonstrated outstanding SERS performance, including good uniformity with an RSD of 6.88% and an enhancement factor (EF) of 1.23 × 107. Owing to the anionic charge repulsion effect, the S-CNF-Ag NP substrate still maintains remarkable dispersion stability after 12 months of preservation. Finally, S-CNF-Ag NPs' surface was modified with 4-mercaptophenol (4-MP), a special redox Raman signal molecule, to detect reduced nicotinamide adenine dinucleotide (NADH). The results showed that the detection limit (LOD) of NADH was 0.75 µM; a good linear relationship (R2 = 0.993) was established in the concentration range 10-6 - 10-2 M. The SERS nanoprobe enabled rapid detection of NADH in human serum without any complicated sample pretreatment and provides a new potential to detect biomarkers.

Preparation and Application of Magnetic Molecularly Imprinted Plasmonic SERS Composite Nanoparticles.

Magnetic molecularly imprinted polymers (MMIPs) are used as artificial antibody materials. MMIPs have attracted a great deal of interest because of their low cost, wide practicality, predetermination, stability and their ability to achieve rapid separation from complex sample environments by the action of external magnetic field. MMIPs can simulate the natural recognition of entities. They are widely used because of their great advantages in terms of high selectivity. In this review article, the preparation methods of Fe3O4 NPs and a detailed summary of the commonly used methods for amination modification of Fe3O4 NPs are introduced, preparation of Ag NPs of different sizes and Au NPs of various shapes and preparation methods of magnetic molecularly imprinted plasmonic SERS composite nanoparticles such as Fe3O4@Ag NPs, Fe3O4/Ag NPs, Fe3O4@Au NPs, Fe3O4/Au NPs, Fe3O4@Au/Ag NPs and Fe3O4@Ag@Au NPs are main summarized. In addition, preparation process and the current application of MMIPs prepared from magnetic molecularly imprinted plasmonic SERS composite nanoparticles incorporating different functional monomers in a nuclear-satellite structure are also presented. Finally, the existing challenges and future prospects of MMIPs in applications are discussed.

Bacterial cellulose loaded with silver nanoparticles as a flexible, stable and sensitive SERS-active substrate for detection of the shellfish toxin DTX-1.

Diarrheal shellfish toxins are considered one of the most lethal red tide algae toxins in the worldwide. In this work, we propose an Ag NPs-loaded bacterial cellulose membrane (BCM) surface-enhanced Raman scattering (SERS) sensor based on an aptamer (Apt) for the ultrasensitive detection of dinophysistoxin (DTX-1), a type of diarrheal shellfish toxin. During drying, Ag NPs can be further densified on "gel-like" BCM to form high-density SERS "hot spots". We developed the "Apt-SH@Ag NPs@BCM" SERS sensor and used the competition of DTX-1 and complementary base (Cob) in the process of base complementary pairing to achieve SERS detection of DTX-1, with a minimum detection limit of 9.5 × 10-10 mol/L. Sample assays showed DTX-1 recovery rates ranging from 95.8% and 108.2% and the detection results were comparable to those obtained by LC-MS. Therefore, this work holds great potential for detecting of toxic substances in shellfish products, especially for the oyster (portuguese oyster) and mussel (blue mussel).

Machine learning-assisted global DNA methylation fingerprint analysis for differentiating early-stage lung cancer from benign lung diseases.

DNA methylation plays a critical role in the development of human tumors. However, routine characterization of DNA methylation can be time-consuming and labor-intensive. We herein describe a sensitive, simple surface-enhanced Raman spectroscopy (SERS) approach for identifying the DNA methylation pattern in early-stage lung cancer (LC) patients. By comparing SERS spectra of methylated DNA bases or sequences with their counterparts, we identified a reliable spectral marker of cytosine methylation. To move toward clinical applications, we applied our SERS strategy to detect the methylation patterns of genomic DNA (gDNA) extracted from cell line models as well as formalin-fixed paraffin-embedded tissues of early-stage LC and benign lung diseases (BLD) patients. In a clinical cohort of 106 individuals, our results showed distinct methylation patterns in gDNA between early-stage LC (n = 65) and BLD patients (n = 41), suggesting cancer-induced DNA methylation alterations. Combined with partial least square discriminant analysis, early-stage LC and BLD patients were differentiated with an area under the curve (AUC) value of 0.85. We believe that the SERS profiling of DNA methylation alterations, together with machine learning could potentially offer a promising new route toward the early detection of LC.

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.

Ratiometric SERS-based assay with "sandwich" structure for detection of serotonin.

A ratiometric nanoensemble-functionalized Surface-Enhanced Raman Spectroscopy (SERS) chip is proposed and an ultrasensitive "sandwich" structure introduced for the detection of 5-HT to achieve early diagnosis of colon cancer. The SERS-based chip contains core-shell SERS active substrates coded by different Raman tags with Raman-silent region peaks (Au@EBP@Au NR arrays and Au@MBN@Ag NPs) and then identify-function molecule modification to construct the "sandwich" structure (Au@EBP@Au NR arrays/5-HT/Au@MBN@Ag NPs). Au@EBP@Au NR arrays showed excellent SERS performance, including good uniformity with an RSD of 5.53% and an enhancement factor (EF) of 2.13 × 107. The intensity ratio of the peaks in the Raman silent region was proportional to the concentration of 5-HT in the range 5 × 10-7-1 × 10-3 M, with a detection limit (LOD) of 4.9 × 10-9 M. Excellent assay accuracy was also demonstrated, with recoveries in the range 96.80% to 104.96%. Finally, we found that 5-HT expression levels in normal human sera were much lower than those in colon cancer patients by using a SERS-based chip for determination of the concentration of 5-HT in clinical colon cancer serum. This result suggested that the proposed approach has potential for detecting 5-HT by ratiometric SERS-based chips for early diagnosis of colon cancer.

Machine learning-assisted internal standard calibration label-free SERS strategy for colon cancer detection.

Liquid biopsies have significance for early colon cancer screening and improving patient survival. Recently, several researchers have applied surface-enhanced Raman spectroscopy (SERS) for the label-free and non-invasive detection of serum. Most of these studies performed the assay using a mixture of noble metal nanoparticles (NMNPs) with serum. However, SERS analysis of serum remains a challenge in terms of reproducibility and stability, as NMNPs tend to aggregate when mixed with serum, resulting in a non-uniform distribution of hot spots. Here, we report on the non-invasive identification of colon cancer (CC) using an internal standard (IS)-calibrated label-free serum SERS assay in combination with machine learning. Serum SERS spectra of 50 CC patients and 50 health volunteers have been obtained using silver nanoparticle (Ag NP) colloid and mercaptopropionic acid-modified Ag NPs (Ag NPs-MPA) as the SERS substrates. Decision tree (DT), random forest (RF), and principal component and linear discriminant analysis (PCA-LDA) algorithms were utilized to establish the diagnosis model for SERS spectra data classifying. The results show that the RF model provides a high diagnostic accuracy compared to PCA-LDA. Following calibration with IS molecules, high diagnostic accuracy of over 90% and 100% specificity can be achieved with DT, RF, and PCA-LDA algorithms to differentiate between cancer and normal groups. The results from this exploratory work demonstrate that serum SERS detection combined with multivariate statistical methods and IS calibration has great potential for the non-invasive and label-free detection of CC.

Preparation of SERS substrate with 2D silver plate and nano silver sol for plasticizer detection in edible oil.

As a widely used industrial additive of plastic products, phthalate ester (PAE) plasticizers can easily migrate into food, threatening human health. In this work, we proposed a rapid, precise, and reliable method to detect PAE plasticizers in edible oils by using surface-enhanced Raman spectroscopy (SERS) technology. A two-dimensional (2D) silver plate synergizing with a nanosilver sol was prepared as a substrate for SERS to detect potassium hydrogen phthalate (PHP), a hydrolysate of a PAE plasticizer. Detection conditions, such as pH values, drying times, and hydrolysate interference, were optimized. The working curve was well fitted with a linear parameter R2 of 0.9994, and the minimum detection limit was evaluated as 10-9 mol/L. Furthermore, the detection accuracy was supported by five edible oil samples. Therefore, using SERS technology to detect PHP is expected to provide an avenue for PAE plasticizer detection in oils and fats, and it features promising potential applications in food safety.

Label-Free SERS Analysis of Serum Using Ag NPs/Cellulose Nanocrystal/Graphene Oxide Nanocomposite Film Substrate in Screening Colon Cancer.

Label-free surface-enhanced Raman scattering (SERS) analysis shows tremendous potential for the early diagnosis and screening of colon cancer, owing to the advantage of being noninvasive and sensitive. As a clinical diagnostic tool, however, the reproducibility of analytical methods is a priority. Herein, we successfully fabricated Ag NPs/cellulose nanocrystals/graphene oxide (Ag NPs/CNC/GO) nanocomposite film as a uniform SERS active substrate for label-free SERS analysis of clinical serum. The Ag NPs/CNC/GO suspensions by self-assembling GO into CNC solution through in-situ reduction method. Furthermore, we spin-coated the prepared suspensions on the bacterial cellulose membrane (BCM) to form Ag NPs/CNC/GO nanocomposite film. The nanofilm showed excellent sensitivity (LOD = 30 nM) and uniformity (RSD = 14.2%) for Nile Blue A detection. With a proof-of-concept demonstration for the label-free analysis of serum, the nanofilm combined with the principal component analysis-linear discriminant analysis (PCA-LDA) model can be effectively employed for colon cancer screening. The results showed that our model had an overall prediction accuracy of 84.1% for colon cancer (n = 28) and the normal (n = 28), and the specificity and sensitivity were 89.3% and 71.4%, respectively. This study indicated that label-free serum SERS analysis based on Ag NPs/CNC/GO nanocomposite film combined with machine learning holds promise for the early diagnosis of colon cancer.

Clinical Evaluation of Efficacy on Ultrasound Combined with Neuromuscular Electrical Stimulation in Treating Lumbar Disc Herniation.

Purpose: To investigate the clinical efficacy of ultrasound (US) combined with neuromuscular electrical stimulation (NMES) in treating lumbar disc herniation (LDH) and its effect on the level of inflammatory factors. Methods: The data of 240 patients with LDH treated at our hospital from January 2020 to February 2021 were reviewed and classified into an US combined with NMES treatment group (US+NMES, n = 80), NMES only treatment group (NMES, n = 80), and US only treatment group (US, n = 80). Their Visual Analogue Scale (VAS) and Oswestry Disability Index (ODI) scores, levels of inflammatory factors and pain mediators, recovery rate, and total recovery time before and after treatment were compared. Additionally, the incidence of complications/adverse reactions was also investigated. Results: Compared with data before treatment, the three groups had lower VAS and ODI scores, inflammatory factor levels (interleukin- [IL-] 1, IL-6, and tumor necrosis factor- [TNF-] α), and pain mediators (transforming growth factor- [TGF-] ß1, prostaglandin E2 [PEG2], and 5-hydroxytryptamine [5-HT]) after treatment, with the most significant decrease observed in the US+NMES group. Compared with patients who received US or NMES treatment alone, patients from the US+NMES had faster recovery time and lower incidence of complications/adverse reactions. Conclusion: Collectively, US combined with NMES was associated with significant relief in pain and lumbar dysfunction and reduced local inflammatory response and pain mediator levels in LDH patients, suggesting that this combined approach could achieve better efficacy than US or NMES alone.