Recent advances of Au@Ag core-shell SERS-based biosensors

Raspberry-Like Plasmonic Nanoaggregates with Programmable Hierarchical Structures for Reproducible SERS Detection of Wastewater Pollutants and Biomarkers

Conventional solid-based SERS substrates often face challenges with inconsistent sample distribution, while liquid-based SERS substrates are prone to aggregation and precipitation, resulting in irreproducible signals in both cases. In this study, we tackled this dilemma by designing and synthesizing raspberry-like plasmonic nanoaggregates that exhibit a high density of hotspots and are colloidally stable at the same time. In particular, the nanoaggregates consist of a core made of functionalized polystyrene (PS) microspheres, which act as a template for rapid self-assembly of Au@Ag core-shell nanoparticles to form raspberry-like hierarchical nanoaggregates within 5 min of mixing. The optimized nanoaggregates can be used as reproducible and stable SERS substrates for a range of wastewater pollutants (e.g., rhodamine 6G (R6G) and malachite green (MG)) and nucleobases (e.g., adenine and uracil), with the detection limits as low as 1 × 10-10, 1 × 10-16, 3 × 10-8, and 3 × 10-7 M, respectively. Additionally, the trace detection of adenine in clinical urine samples has been successfully demonstrated. Our modular assembly approach opens up new possibilities in SERS substrate design and advanced trace-chemical detection technologies.

Green synthesis of multifunctional bamboo-based nonwoven fabrics for medical treatment

Medical nonwovens fabrics are pivotal materials in modern healthcare systems, and find extensively application in surgical gowns, masks, nursing pads, and surgical instrument packaging. As healthcare requirements evolve and medical technology advances, the demand for functional nonwoven medical devices is continuously increasing. In addition, numerous environmental challenges and the need to transition to a sustainable society have increased the popularity of studies on environmentally friendly multifunctional nonwoven materials prepared from biomass fibers. Therefore, in this study, ecofriendly bamboo fibers were used to fabricate multifunctional medical nonwoven materials with superhydrophobic, antibacterial, flame-retardant, and biocompatible properties. Specifically, ZIF-67 was grown in situ on natural bamboo cellulose fibers (BCFs) extracted from natural bamboo and coated with polydimethylsiloxane to construct an environmentally friendly and versatile nonwoven fabric. The treated nonwoven fabric exhibited superhydrophobicity with contact angle of 163° and possess excellent self-cleaning properties. The antibacterial activity of the samples was investigated by the plate-counting method; the results showed that the untreated BCFs did not exhibit antibacterial activity, whereas the treated bamboo nonwoven fabrics demonstrated significant antibacterial activity (p < 0.001), with an antibacterial rate of >99 % against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Bacillus subtilis, and Candida albicans. In addition, when the samples were exposed to different temperatures (-4 and 50 °C) and humidities (0 % and 95 %), they demonstrated an antibacterial activity of >99 % against E. coli (F5,10 = 0.602; p = 0.670) and S. aureus (F4,10 = 0.289; p = 0.879). The heat release rate and smoke production rate of the nonwoven fabric decreased by 54.64 % and 93.18 %, respectively, compared to those of the BCFs, indicating excellent flame retardancy. The nonwoven fabric also exhibited satisfactory biocompatibility and breathability, ensuring user comfortability. This research not only has significant implications for producing low-cost, environmentally friendly, sustainable, and multifunctional medical products and openi up new pathways for the diversified utilization of bamboo, thereby expanding its applicability.

Unlocking the potential of RGD-conjugated gold nanoparticles: a new frontier in targeted cancer therapy, imaging, and metastasis inhibition

In the rapidly evolving field of cancer therapeutics, the potential of gold nanoparticles (AuNPs) conjugated with RGD peptides has emerged as a promising avenue for targeted therapy and imaging. Despite numerous studies demonstrating the effectiveness of RGD-conjugated AuNPs in specifically targeting tumor cells and enhancing radiation therapy (RT), a comprehensive review of these advancements is currently lacking. This review aims to fill this critical gap in the literature. Our analysis reveals that RGD-conjugated AuNPs have shown significant promise in improving the diagnosis and treatment of various types of cancer, including breast cancer. However, the full potential of this technology is yet to be realized. The development of multifunctional nanoplatforms incorporating AuNPs has opened new horizons for targeted therapy, dual-mode imaging, and inhibition of tumor growth and metastasis. This review is of paramount importance as it provides a comprehensive overview of the current state of research in this area, and highlights the areas where further research is needed. It is hoped that this review will inspire further investigations into this promising nanotechnology, ultimately leading to improved cancer diagnosis and therapy. Therefore, the findings presented in this review underscore the potential of AuNPs conjugated with RGD peptides as a revolutionary approach in cancer therapeutics. It is our fervent hope that this review will serve as a catalyst for further research in this exciting field.

On-Chip Droplet Splitting with High Volume Ratios Using a 3D Conical Microstructure-Based Microfluidic Device

This work reports a simple microfluidic method for splitting a mother droplet into two daughter droplets with high and precise volume ratios. To achieve this, a droplet-splitting microfluidic device embedded with a three-dimensional (3D) conical microstructure is fabricated, in which the high splitting ratios of monodisperse mother droplets are achieved. The volume ratio of the split daughter droplets can reach up to 265. In addition, we examined factors that affect the splitting ratio of the daughter droplets and found that the ratio is affected by the flow rates of the two individual outlet channels, the injection length of the conical microstructure, and the diameter of the original mother droplets. Numerical simulations of these parameters were conducted to gain a clearer understanding of the splitting behavior. The proposed droplet splitting device with a conical microstructure enables on-chip sample extraction and droplet volume control, which can be a powerful tool for various droplet-based applications in microfluidic devices such as viral infectivity assays and sequencing heterogeneous populations.

NIR-II Surface-Enhanced Raman Scattering Nanoprobes in Biomedicine: Current Impact and Future Directions

The field of second near-infrared (NIR-II) surface-enhanced Raman scattering (SERS) nanoprobes has made commendable progress in biomedicine. This article reviews recent advances and future development of NIR-II SERS nanoprobes. It introduces the fundamental principles of SERS nanoprobes and highlights key advances in the NIR-II window, including reduced tissue attenuation, deep penetration, maximized allowable exposure, and improved photostability. The discussion of future directions includes the refinement of nanoprobe substrates, emphasizing the tailoring of optical properties of metallic SERS-active nanoprobes, and exploring non-metallic alternatives. The intricacies of designing Raman reporters for the NIR-II resonance and the potential of these reporters to advance the field are also discussed. The integration of artificial intelligence (AI) into nanoprobe design represents a cutting-edge approach to overcome current challenges. This article also examines the emergence of deep Raman techniques for through-tissue SERS detection, toward NIR-II SERS tomography. It acknowledges instrumental advancements like improved charge-coupled device sensitivity and accelerated imaging speeds. The article concludes by addressing the critical aspects of biosafety, ease of functionalization, compatibility, and the path to clinical translation. With a comprehensive overview of current achievements and future prospects, this review aims to illuminate the path for NIR-II SERS nanoprobes to innovate diagnostic and therapeutic approaches in biomedicine.

SERS analysis of single cells and subcellular components: A review

SERS is a rapidly advancing and non-destructive technique that has been proven to be more reliable and convenient than other traditional analytical methods. Due to its sensitivity and specificity, this technique is earning its place as a routine and powerful tool in biological and medical studies, especially for the analysis of living cells and subcellular components. This paper reviewed the research progress of single-cell SERS that has been made in the last few years and discussed challenges and future perspectives of this technique. The reviewed SERS platforms have been categorized according to their nature into the following types: (1) colloid-based, substrate-based, or hybrid; (2) ligand-based or ligand-free, and (3) label-based or label-free. The advantages and disadvantages of each type and their potential applications in various fields are thoroughly discussed.

Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer

Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the current diagnostic methods, either pathological frozen section or paraffin section examination, are laborious, time-consuming, and inconvenient. Raman spectroscopy is a label-free and non-invasive analytical technique that provides molecular information with high specificity. Here, we report the use of a portable Raman system and machine learning algorithms to achieve accurate diagnosis of esophageal tumor tissue in surgically resected specimens. We tested five machine learning-based classification methods, including k-Nearest Neighbors, Adaptive Boosting, Random Forest, Principal Component Analysis-Linear Discriminant Analysis, and Support Vector Machine (SVM). Among them, SVM shows the highest accuracy (88.61 %) in classifying the esophageal tumor and normal tissues. The portable Raman system demonstrates robust measurements with an acceptable focal plane shift of up to 3 mm, which enables large-area Raman mapping on resected tissues. Based on this, we finally achieve successful Raman visualization of tumor boundaries on surgical margin specimens, and the Raman measurement time is less than 5 min. This work provides a robust, convenient, accurate, and cost-effective tool for the diagnosis of esophageal cancer tumors, advancing toward Raman-based clinical intraoperative applications.

Raman spectroscopy analysis combined with computed tomography imaging to identify microsatellite instability in gastric cancers

Accurate determination of microsatellite instability (MSI) status is critical for tailoring treatment approaches for gastric cancer patients. Existing clinical techniques for MSI diagnosis are plagued by problems of suboptimal time efficiency, high cost, and burdensome experimental requirements. Here, we for the first time establish the classification model of gastric cancer MSI status based on Raman spectroscopy. To begin with, we reveal that tumor heterogeneity-induced signal variations pose a prominent impact on MSI classification. To eliminate this issue, we develop Euclidean distance-based Raman Spectroscopy (EDRS) algorithm, which establishes a standard spectrum to represent the "most microsatellite stable" status. The similarity between each spectrum of tissues with the standard spectrum is calculated to provide a direct assessment on the MSI status. Compared to machine learning-algorithms including k-Nearest Neighbors, Random Forest, and Extreme Learning Machine, the EDRS method shows the highest accuracy of 94.6 %. Finally, we integrate the EDRS method with the clinical diagnostic modality, computed tomography, to construct an innovative joint classification model with good classification performance (AUC = 0.914, Accuracy = 94.6 %). Our work demonstrates a robust, rapid, non-invasive, and convenient tool in identifying the MSI status, and opens new avenues for Raman techniques to fit into existing clinical workflow.

Aptamer-free upconversion nanoparticle/silk biosensor system for low-cost and highly sensitive detection of antibiotic residues

The detection of antibiotics is crucial for safeguarding the environment, ensuring food safety, and promoting human health. However, developing a rapid, convenient, low-cost, and sensitive method for antibiotic detection presents significant challenges. Herein, an aptamer-free biosensor was successfully constructed using upconversion nanoparticles (UCNPs) coated with silk fibroin (SF), based on Förster resonance energy transfer (FRET) and the charge-transfer effect, for detecting roxithromycin (RXM). A synergistic FRET efficiency was achieved by utilizing alizarin red and RXM complexes as energy acceptors, with UCNP as the energy donor, and immobilizing an ultrathin SF protein corona within 10 nm. The biosensor detects RXM in deionized water with high sensitivity primarily through monolayer adsorption, with a detection range of 1.0 nM-141.6 nM and a detection limit as low as 0.68 nM. The performance of this biosensor was compared with the ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) method for detecting antibiotics in river water separately and a strong correlation between the two methods was observed. The biosensor exhibited long-term stability in aqueous solutions (up to 60 d) with no attenuation of fluorescence intensity. Furthermore, the biosensor's applicability extended to the highly sensitive detection of other antibiotics, such as azithromycin. This study introduces a low-cost, eco-friendly, and highly sensitive method for antibiotic detection, with broad potential for future applications in environmental, healthcare, and food-related fields.

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples

The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk of false-negative results. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms holds promise for cancer diagnosis. In this study, we develop a label-free SERS liquid biopsy method with machine learning for the rapid and accurate diagnosis of thyroid cancer by using thyroid FNA washout fluids. These liquid supernatants are mixed with silver nanoparticle colloids, and dispersed in quartz capillary for SERS measurements to discriminate between healthy and malignant samples. We collect Raman spectra of 36 thyroid FNA samples (18 malignant and 18 benign) and compare four classification models: Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). The results show that the CNN algorithm is the most precise, with a high accuracy of 88.1%, sensitivity of 87.8%, and the area under the receiver operating characteristic curve of 0.953. Our approach is simple, convenient, and cost-effective. This study indicates that label-free SERS liquid biopsy assisted by deep learning models holds great promise for the early detection and screening of thyroid cancer.

Application of Surface-Enhanced Raman Spectroscopy Combined with Immunoassay for the Detection of Adrenoceptor Agonists

Rapid, sensitive, and accurate detection of adrenoceptor agonists is a significant research topic in the fields of food safety and public health. Immunoassays are among the most widely used methods for detecting adrenoceptor agonists. In recent years, surface-enhanced Raman spectroscopy combined with immunoassay (SERS-IA) has become an effective technique for improving detection sensitivity. This review focuses on the innovation of Raman reporter molecules and substrate materials for the SERS-IA of adrenoceptor agonists. In addition, it also investigates the challenges involved in potentially applying SERS-IA in the detection of adrenoceptor agonists. Overall, this review provides insight into the design and application of SERS-IA for the detection of adrenoceptor agonists, which is critical for animal-derived food safety and public health.

Aptamer-conjugated gold nanoparticles for portable, ultrasensitive naked-eye detection of C-reactive protein based on the Tyndall effect

BACKGROUND

C-reactive protein (CRP) represents an early clinical biomarker that indicates the presence of inflammatory or infectious conditions in the human body. Today's procedures approved by the Food and Drug Administration (FDA) imply expensive equipment and highly trained personnel to perform the test. Therefore, a new diagnostic method with high detection efficiency and less cost is urgently needed for delivering rapid and timely results in point-of-care (POC) service.

RESULTS

Herein, we propose a new, equipment-free, and portable sensing method for the future POC detection of CRP based on the Tyndall effect (TE). In our study, aptamer-conjugated citrate-stabilized gold nanoparticles (apta-AuNPs) are exploited as the sensing platform. The apta-AuNPs' interaction with CRP in a saline environment leads to their aggregation, thus enhancing the scattering of light when the solution is exposed to a 640 nm pointer laser line. Firstly, the enhancement of the scattering light as a function of increasing concentration of CRP in solution is measured spectroscopically using a typical 90-degree angle spectrofluorometer and then the measurements are compared to the classic colorimetric detection using an UV-Vis spectrophotometer. Finally, to achieve high portability and accessibility, we demonstrate that the measurement of CRP concentration can be performed with similar accuracy but in a more direct and inexpensive way by using a laser pointer pen as the excitation source and a camera of a low-budget smartphone as a quantitative reader instead of most expensive spectrofluorometer.

SIGNIFICANCE

The portable TE-based assay exhibits a wide linear dynamic range (1-60 μg/mL) for the detection of CRP with a limit of detection (LOD) of 92 ng/mL The proposed method is capable to integrate both standard and high-sensitivity CRP analysis in a single procedure with increased sensitivity and prompt delivery of analysis results. Moreover, the sensing procedure is significantly faster than the FDA approved ones with a detection time of only 10 min. Finally, as a proof-of-concept, our findings demonstrate excellent recovery for CRP detection in spiked and diluted urine samples, highlighting the strong potential of this sensing method for POC applications.

Ag@Au core-shell nanoparticle-based surface-enhanced Raman scattering coupled with chemometrics for rapid determination of chloramphenicol residue in fish

The alarming increase in drug-resistant bacteria in fish resulting from the misuse of antibiotics poses a significant threat to ecosystems and human health. Therefore, the development of a reliable approach for detecting antibiotic residues in fish is crucial. In this study, a rapid and simple method for detecting chloramphenicol (CAP) residue in tilapia was developed using surface-enhanced Raman scattering (SERS) combined with chemometric algorithms. Silver and gold core-shell nanoparticles (Ag@Au CSNPs) were used as SERS nanosensors to achieve strong signal amplification with an enhancement factor of 2.67 × 106. The results demonstrated that the variable combination population analysis-partial least square (VCPA-PLS) model combined with the standard normal variable transformation pretreatment method exhibited the best predictive performance with a detection limit of 1 × 10-5 µg/mL. Thus, an SERS technique was established based on Ag@Au CSNPs combined with VCPA-PLS to rapidly detect CAP in tilapia.

Lectin-conjugated nanotags with high SERS stability: selective probes for glycans

Surface-enhanced Raman scattering (SERS) nanotags functionalized with lectins as the biological recognition element can be used to target the carbohydrate portion of carbohydrate-carrying molecules (glycoconjugates). An investigation of the optical stability of such functionalized SERS nanotags is an essential initial step before future application and quantification of surface glycan biomarkers on cells and extracellular vesicles. Herein, we report an innovative approach to evaluate the SERS stability of lectin-conjugated nanotags by investigating any possible interfering lectin-lectin interactions in a mixture of different lectin-conjugated SERS nanotags, as well as an assessment of lectin-glycan interaction by mixing wheat germ agglutinin (WGA)-conjugated SERS nanotags with different glycoproteins. No lectin cross-reactivity was found in the mixture of lectin-conjugated SERS nanotags, evidenced by the constant SERS intensity. Additionally, the results showed that the lectins conjugated to SERS nanotags retain their ability to interact with glycans, as evidenced by the changes in the nanotag color and extinction spectra. Their SERS intensity remained constant as supported by finite-element method (FEM) simulation results, demonstrating a high SERS stability and selectivity of lectin-conjugated nanotags towards multiplex applications.

Simultaneous detection of urea and lactate in sweat based on a wearable sweat biosensor

Urea and lactate are biomarkers in sweat that is closely associated with human health. This study introduces portable, rapid, sensitive, stable, and high-throughput wearable sweat biosensors utilizing Au-Ag nanoshuttles (Au-Ag NSs) for the simultaneous detection of sweat urea and lactate. The Au-Ag NSs arrays within the biosensor's microfluidic cavity provide a substantial surface-enhanced Raman scattering (SERS) enhancement effect. The limit of detection (LOD) for urea and lactate are 2.35 × 10-6 and 8.66 × 10-7 mol/L, respectively. This wearable sweat biosensor demonstrates high resistance to compression bending, repeatability, and stability and can be securely attached to various body parts. Real-time sweat analysis of volunteers wearing the biosensors during exercise demonstrated the method's practicality. This wearable sweat biosensor holds significant potential for monitoring sweat dynamics and serves as a valuable tool for assessing bioinformation in sweat.

Plasmonic Nanoparticle-Enhanced Optical Techniques for Cancer Biomarker Sensing

This review summarizes recent advances in leveraging localized surface plasmon resonance (LSPR) nanotechnology for sensitive cancer biomarker detection. LSPR arising from noble metal nanoparticles under light excitation enables the enhancement of various optical techniques, including surface-enhanced Raman spectroscopy (SERS), dark-field microscopy (DFM), photothermal imaging, and photoacoustic imaging. Nanoparticle engineering strategies are discussed to optimize LSPR for maximum signal amplification. SERS utilizes electromagnetic enhancement from plasmonic nanostructures to boost inherently weak Raman signals, enabling single-molecule sensitivity for detecting proteins, nucleic acids, and exosomes. DFM visualizes LSPR nanoparticles based on scattered light color, allowing for the ultrasensitive detection of cancer cells, microRNAs, and proteins. Photothermal imaging employs LSPR nanoparticles as contrast agents that convert light to heat, producing thermal images that highlight cancerous tissues. Photoacoustic imaging detects ultrasonic waves generated by LSPR nanoparticle photothermal expansion for deep-tissue imaging. The multiplexing capabilities of LSPR techniques and integration with microfluidics and point-of-care devices are reviewed. Remaining challenges, such as toxicity, standardization, and clinical sample analysis, are examined. Overall, LSPR nanotechnology shows tremendous potential for advancing cancer screening, diagnosis, and treatment monitoring through the integration of nanoparticle engineering, optical techniques, and microscale device platforms.

Signal Amplification Strategy Design in Nanozyme-Based Biosensors for Highly Sensitive Detection of Trace Biomarkers

Nanozymes show great promise in enhancing disease biomarker sensing by leveraging their physicochemical properties and enzymatic activities. These qualities facilitate signal amplification and matrix effects reduction, thus boosting biomarker sensing performance. In this review, recent studies from the last five years, concentrating on disease biomarker detection improvement through nanozyme-based biosensing are examined. This enhancement primarily involves the modulations of the size, morphology, doping, modification, electromagnetic mechanisms, electron conduction efficiency, and surface plasmon resonance effects of nanozymes for increased sensitivity. In addition, a comprehensive description of the synthesis and tuning strategies employed for nanozymes has been provided. This includes a detailed elucidation of their catalytic mechanisms in alignment with the fundamental principles of enhanced sensing technology, accompanied by the presentation of quantitatively analyzed results. Moreover, the diverse applications of nanozymes in strip sensing, colorimetric sensing, electrochemical sensing, and surface-enhanced Raman scattering have been outlined. Additionally, the limitations, challenges, and corresponding recommendations concerning the application of nanozymes in biosensing have been summarized. Furthermore, insights have been offered into the future development and outlook of nanozymes for biosensing. This review aims to serve not only as a reference for enhancing the sensitivity of nanozyme-based biosensors but also as a catalyst for exploring nanozyme properties and their broader applications in biosensing.

Application of Anodic Titanium Oxide Modified with Silver Nanoparticles as a Substrate for Surface-Enhanced Raman Spectroscopy

The formation of nanostructured anodic titanium oxide (ATO) layers was explored on pure titanium by conventional anodizing under two different operating conditions to form nanotube and nanopore morphologies. The ATO layers were successfully developed and showed optimal structural integrity after the annealing process conducted in the air atmosphere at 450 °C. The ATO nanopore film was thinner (1.2 +/- 0.3 μm) than the ATO nanotube layer (3.3 +/- 0.6 μm). Differences in internal pore diameter were also noticeable, i.e., 88 +/- 9 nm and 64 +/- 7 nm for ATO nanopore and nanotube morphology, respectively. The silver deposition on ATO was successfully carried out on both ATO morphologies by silver electrodeposition and Ag colloid deposition. The most homogeneous silver deposit was prepared by Ag electrodeposition on the ATO nanopores. Therefore, these samples were selected as potential surface-enhanced Raman spectroscopy (SERS) substrate, and evaluation using pyridine (aq.) as a testing analyte was conducted. The results revealed that the most intense SERS signal was registered for nanopore ATO/Ag substrate obtained by electrodeposition of silver on ATO by 2.5 min at 1 V from 0.05M AgNO3 (aq.) (analytical enhancement factor, AEF ~5.3 × 104) and 0.025 M AgNO3 (aq.) (AEF ~2.7 × 102). The current findings reveal a low-complexity and inexpensive synthesis of efficient SERS substrates, which allows modification of the substrate morphology by selecting the parameters of the synthesis process.

Strategies for Mitigating Commercial Sensor Chip Variability with Experimental Design Controls

Surface plasmon resonance (SPR) is a popular real-time technique for the measurement of binding affinity and kinetics, and bench-top instruments combine affordability and ease of use with other benefits of the technique. Biomolecular ligands labeled with the 6xHis tag can be immobilized onto sensing surfaces presenting the Ni2+-nitrilotriacetic acid (NTA) functional group. While Ni-NTA immobilization offers many advantages, including the ability to regenerate and reuse the sensors, its use can lead to signal variability between experimental replicates. We report here a study of factors contributing to this variability using the Nicoya OpenSPR as a model system and suggest ways to control for those factors, increasing the reproducibility and rigor of the data. Our model ligand/analyte pairs were two ovarian cancer biomarker proteins (MUC16 and HE4) and their corresponding monoclonal antibodies. We observed a broad range of non-specific binding across multiple NTA chips. Experiments run on the same chips had more consistent results in ligand immobilization and analyte binding than experiments run on different chips. Further assessment showed that different chips demonstrated different maximum immobilizations for the same concentration of injected protein. We also show a variety of relationships between ligand immobilization level and analyte response, which we attribute to steric crowding at high ligand concentrations. Using this calibration to inform experimental design, researchers can choose protein concentrations for immobilization corresponding to the linear range of analyte response. We are the first to demonstrate calibration and normalization as a strategy to increase reproducibility and data quality of these chips. Our study assesses a variety of factors affecting chip variability, addressing a gap in knowledge about commercially available sensor chips. Controlling for these factors in the process of experimental design will minimize variability in analyte signal when using these important sensing platforms.

Surface-Enhanced Raman Scattering (SERS) Substrates Based on Ag-Nanoparticles and Ag-Nanoparticles/Poly (methyl methacrylate) Composites

SERS substrates formed by spherical silver nanoparticles (Ag-NPs) with a 15 nm average diameter adsorbed on Si substrate at three different concentrations and Ag/PMMA composites formed by an opal of PMMA microspheres of 298 nm average diameter were synthesized. The Ag-NPs were varied at three different concentrations. We have observed from SEM micrographs, in the Ag/PMMA composites, the periodicity of the PMMA opals is slightly altered as the Ag-NP concentration is increased; as a consequence of this effect, the PBGs maxima shift toward longer wavelengths, decrease in intensity, and broaden as the Ag-NP concentration is increased in the composites. The performance of single Ag-NP and Ag/PMMA composites as SERS substrates was determined using methylene blue (MB) as a probe molecule with concentrations in the range of 0.5 µM to 2.5 µM. We found that in both single Ag-NP and Ag/PMMA composites as SERS substrates, the enhancement factor (EF) increases as the Ag-NP concentration is increased. We highlight that the SERS substrate with the highest concentration of Ag-NPs has the highest EF due to the formation of metallic clusters on the surface, which generates more "hot spots". The comparison of the EFs of the single Ag-NP with those of Ag/PMMA composite SERS substrates shows that the EFs of the former are nearly 10-fold higher than those of Ag/PMMA composites. This result is obtained probably due to the porosity of the PMMA microspheres that decreases the local electric field strength. Furthermore, PMMA exerts a shielding effect that affects the optical efficiency of Ag-NPs. Moreover, the metal-dielectric surface interaction contributes to the decrease in the EF. Other aspect to consider in our results is in relation to the difference in the EF of the Ag/PMMA composite and Ag-NP SERS substrates and is due to the existing mismatch between the frequency range of the PMMA opal stop band and the LSPR frequency range of the Ag metal nanoparticles adsorbed on the PMMA opal host matrix.

Carbon dots-mediated synthesis of gold nanodendrites with extended absorption into NIR-II window for in vivo photothermal therapy

BACKGROUND

Photothermal therapy (PTT) in the second near-infrared (NIR-II) window has attracted extensive attention due to the benefits in high maximum permissible exposure and penetration depth. Current photothermal agents generally show a broadband absorption accompanied by a gradual attenuation of absorption in the NIR-II window, leading to poor effect of PTT. It remains a great challenge to gain photothermal agents with strong and characteristic absorption in NIR-II regions. To overcome this problem, based on carbon dots (CDs)-mediated growth strategy, we proposed a simple and feasible approach to prepare plasmonic gold nanodendrites (AuNDs) with NIR-II absorption to enhance the therapeutic effect of PTT.

RESULTS

By rationally regulating the size and branch length of AuNDs, the AuNDs exhibited a broadband absorption from 300 to 1350 nm, with two characteristic absorption peaks located at 1077 and 1265 nm. The AuNDs demonstrated desired optical photothermal conversion efficiency (38.0%), which was further applied in NIR-II photoacoustic imaging (PAI) and PTT in human colon cancer cells (HCT 116)-tumor-bearing mice model. The tumor cells could be effectively eliminated in vivo under 1064 nm laser irradiation by the guidance of PAI.

CONCLUSIONS

We reported a simple but powerful synthetic method to obtain the unique AuNDs with strong and characteristic absorption peaks in the NIR-II window. This study provides a promising solution to tuning the growth of nanoparticles for bioimaging and phototherapy in the NIR-II window.