Analysis of Biomolecules Based on the Surface Enhanced Raman Spectroscopy

Multiplex Detection of Foodborne Pathogens using 3D Nanostructure Swab and Deep Learning-Based Classification of Raman Spectra

Proactive management of foodborne illness requires routine surveillance of foodborne pathogens, which requires developing simple, rapid, and sensitive detection methods. Here, a strategy is presented that enables the detection of multiple foodborne bacteria using a 3D nanostructure swab and deep learning-based Raman signal classification. The nanostructure swab efficiently captures foodborne pathogens, and the portable Raman instrument directly collects the Raman signals of captured bacteria. a deep learning algorithm has been demonstrated, 1D convolutional neural network with binary labeling, achieves superior performance in classifying individual bacterial species. This methodology has been extended to mixed bacterial populations, maintaining accuracy close to 100%. In addition, the gradient-weighted class activation mapping method is used to provide an investigation of the Raman bands for foodborne pathogens. For practical application, blind tests are conducted on contaminated kitchen utensils and foods. The proposed technique is validated by the successful detection of bacterial species from the contaminated surfaces. The use of a 3D nanostructure swab, portable Raman device, and deep learning-based classification provides a powerful tool for rapid identification (≈5 min) of foodborne bacterial species. The detection strategy shows significant potential for reliable food safety monitoring, making a meaningful contribution to public health and the food industry.

Highly sensitive detection of tryptophan based on Schiff base reaction and surface-enhanced Raman spectroscopy

In this study, a simple, rapid and sensitive method combining surface-enhanced Raman spectroscopy and Schiff base reaction was developed for the detection of tryptophan. This method does not require product separation to obtain a significant Raman signal of the derivatized product, and the derivatization reaction can be controlled by experimental parameters such as reaction temperature, time, concentration of derivatization reagent and concentration of sodium nitrite. The characteristic peak of the derivative of tryptophan (1620 cm-1) was selected for quantitative analysis, and the intensity of the characteristic Raman spectrum peak showed a linear relationship with the concentration of tryptophan (10-8-10-4 mol/L) in the range of with a correlation coefficient R2 of 0.9922. This assay combines surface-enhanced Raman spectroscopy and Schiff base reaction, which is characterized by high sensitivity and easy operation, and has good application prospects in the detection of tryptophan in food.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Determination of thiram in fruit juices using a bacterial cellulose nanocrystal-based SERS substrate

Pesticide residues in agri-foods have risk to human health and one solution is to develop simple and accurate methods for rapid detection. We developed a SERS sensor composed of gold nanoparticles (AuNPs) and bacterial cellulose nanocrystal (BCNC) to detect thiram in fruit juice. BCNC-SO3H was used as a stabilizer to support AuNPs via electrostatic repulsion, fabricating a BCNC-AuNPs SERS substrate with uniformly distributed AuNPs. This BCNC-AuNPs SERS substrate was applied to determine thiram residues in peach juice, apple juice, and grape juice with the limits of detection of 0.036 ppm, 0.044 ppm, and 0.044 ppm, respectively. The whole test took 12 min including sample preparation and analysis. The detection limits meet the maximum residue levels of thiram in fruit juices required by China, Europe and North America, indicating that this BCNC-based substrate could serve as a satisfactory SERS sensor for pesticide residue monitoring in the food supply chain.

Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

Surface-enhanced Raman spectroscopy long-range detection investigation based on the alternating coupling of a surface plasmonic array and dielectric waveguide

Surface-enhanced Raman spectroscopy (SERS) is widely used to detect low-concentration samples in biology, medicine, etc. We design and theoretically investigate a SERS sensor with a surface plasmonic array coupled alternately with a dielectric waveguide. The effect of the incident angle on the coupling efficiency of an evanescent field is systematically studied. The results show that the maximum evanescent field coupling efficiency can be obtained at an incident angle of 66°. The proposed SERS sensor has a transmission length of 1.027 cm and a high enhancement performance with an enhancement factor of 1.574×104 at a wavelength of 633 nm. The integration of this SERS sensor with a metal array and a dielectric waveguide prevents the direct illumination of the sample molecules by the excited light. Furthermore, the long-range nondestructive detection of the SERS signals of the low-concentration sample molecules can be achieved.

Recent Advances in Biomolecular Detection Based on Aptamers and Nanoparticles

The fast, accurate detection of biomolecules, ranging from nucleic acids and small molecules to proteins and cellular secretions, plays an essential role in various biomedical applications. These include disease diagnostics and prognostics, environmental monitoring, public health, and food safety. Aptamer recognition (DNA or RNA) has gained extensive attention for biomolecular detection due to its high selectivity, affinity, reproducibility, and robustness. Concurrently, biosensing with nanoparticles has been widely used for its high carrier capacity, stability and feasibility of incorporating optical and catalytic activity, and enhanced diffusivity. Biosensors based on aptamers and nanoparticles utilize the combination of their advantages and have become a promising technology for detecting of a wide variety of biomolecules with high sensitivity, reliability, specificity, and detection speed. Via various sensing mechanisms, target biomolecules have been quantified in terms of optical (e.g., colorimetric and fluorometric), magnetic, and electrical signals. In this review, we summarize the recent advances in and compare different aptamer-nanoparticle-based biosensors by nanoparticle types and detection mechanisms. We also share our views on the highlights and challenges of the different nanoparticle-aptamer-based biosensors.

Device Processing Challenges for Miniaturized Sensing Systems Targeting Biological Fluids

This article presents a review of device processing technologies used in the fabrication of biomedical systems, and highlights the requirements of advanced manufacturing technology. We focus on biomedical systems that perform diagnostics of fluidic specimens, with analytes that are in the liquid phase. In the introduction, we define biomedical systems as well as their versatile applications and the essential current trends. The paper gives an overview of the most important biomolecules that typically must be detected or analyzed in several applications. The paper is structured as follows. First, the conventional architecture and construction of a biosensing system is introduced. We provide an overview of the most common biosensing methods that are currently used for the detection of biomolecules and its analysis. We present an overview of reported biochips, and explain the technology of biofunctionalization and detection principles, including their corresponding advantages and disadvantages. Next, we introduce microfluidics as a method for delivery of the specimen to the biochip sensing area. A special focus lies on material requirements and on manufacturing technology for fabricating microfluidic systems, both for niche and mass-scale production segments. We formulate requirements and constraints for integrating the biochips and microfluidic systems. The possible impacts of the conventional microassembly techniques and processing methods on the entire biomedical system and its specific parts are also described. On that basis, we explain the need for alternative microassembly technologies to enable the integration of biochips and microfluidic systems into fully functional systems.

Self-Referenced Surface-Enhanced Raman Scattering Nanosubstrate for the Quantitative Detection of Neurotransmitters

Quantitative, label-free detection of neurotransmitters is of vital importance to the diagnosis and treatment of neurologic diseases. The surface-enhanced Raman scattering (SERS) effect has great application prospects in the field of biosensing and bioimaging because of its unique nondestructive testing and its capability of being used in molecular fingerprint identification. However, the quantitative SERS analysis of neurotransmitters is still a great challenge because of the poor reproducibility of the SERS-active sites, as well as the small Raman cross-section and low physiological concentration of neurotransmitter molecules. Here, we report the development of a stellate gold nanostructure with a 1 nm interior gap for the quantitative detection of neurotransmitters. The internal reference embedded into the hollow gap of the stellate gold nanoparticle allows the calibration of the signal of analytes absorbed on the surface, which improves the R-squared value of the linear fitting curve from 0.56 to 0.97 for quantitative dopamine detection. Our developed self-referenced SERS substrate holds great potential for label-free, quantitative SERS-based biosensing.

Surface-enhanced Raman scattering with gold-coated silicon nanopillars arrays: The influence of size and spatial order

Nanopillars have been extensively explored as promising substrates for surface-enhanced Raman scattering (SERS) owing to their high sensitivity and excellent reproducibility. Most of the researches have been focused on the fabrication methods of nanopillars, and the dependences of SERS effects on geometrical size and spatial order are rarely investigated. In this work, SERS properties of nanopillars with different sizes (115-185 nm) and spatial orders (square and rhombus orders) have been studied. The work has shown that the nanopillars not only have high enhancement capability and high signal reproducibility, but also the enhancement is insensitive to the size and spatial orders. The measured enhancement factors (EFs) are 2.3-4.0 × 10⁶ and signal reproducibility (relative standard deviation, RSD) are ∼ 5.2%-6.9%, which are among the best of the similar SERS substrates reported. The variation of SERS intensity was as low as approximately 4.8% with the variation of pillar size from 115, 135, 145, to 160 nm. The insensitiveness and high reproducibility have been ascribed to the combined excitation of localized surface plasmon resonance (LSPR) and propagating surface plasmons (SPPs) of the nanopillars. Optical properties of the nanopillars are studied both experimentally and numerically to understand the physics behind the SERS performance.

Anisotropy of DNA molecule detection and enhancement by GaN-based electronic sensor

An electrical characterization approach with a newly, to the best of our knowledge, defined electrical anisotropy (η) was proposed to characterize and enhance the anisotropy signals of DNA molecules. This approach utilizes L-shaped aluminum gratings on a gallium nitride PiN electronic sensor system to adjust and improve the η signals. Using this approach, the η signals of DNA molecules can be adjusted more easily and efficiently by changing the electrical parameters of the sensor. For instance, the η modes of DNA were enhanced more than 22 times with the change of the incident power and the reverse bias voltage of the PiN structure.

A SERS aptasensor based on porous Au-NC nanoballoons for Staphylococcus aureus detection

In this work, we developed a new approach for fabricating hollow and porous nitrogen doped carbon nanoballoons loading AuNPs (Au-NC-NBs) with a large specific surface area, a high N and Au content. The surface-enhanced Raman scattering (SERS) aptasensor based on the resulting Au-NC-NBs possess a wider linear range (10 to 10⁷ cells/mL), a lower detection limit (3 cells/mL), better selectivity for detecting bacteria than previously reported sensors. Importantly, Au-NC-NBs SERS aptasensor also exhibits excellent performance for detecting bacteria in the real food and biological samples. This work provides a facile and versatile designing strategy for controlled construction of SERS biosensor by combination of Au nanoparticles and carbon materials, which has a great applied potential in food safety monitoring and clinical diagnosis.

Blood identification at the single-cell level based on a combination of laser tweezers Raman spectroscopy and machine learning

Laser tweezers Raman spectroscopy (LTRS) combines optical tweezers technology and Raman spectroscopy to obtain biomolecular compositional information from a single cell without invasion or destruction, so it can be used to "fingerprint" substances to characterize numerous types of biological cell samples. In the current study, LTRS was combined with two machine learning algorithms, principal component analysis (PCA)-linear discriminant analysis (LDA) and random forest, to achieve high-precision multi-species blood classification at the single-cell level. The accuracies of the two classification models were 96.60% and 96.84%, respectively. Meanwhile, compared with PCA-LDA and other classification algorithms, the random forest algorithm is proved to have significant advantages, which can directly explain the importance of spectral features at the molecular level.

Bimetallic Ag-Cu Alloy Microflowers as SERS Substrates with Single-Molecule Detection Limit

Bimetallic Ag-Cu alloy microflowers with tunable surface compositions were fabricated as surface-enhanced Raman spectroscopy (SERS) substrates with a limit of detection in the zeptomolar range for the analyte molecule rhodamine 6G (R6G). The substrates were prepared on a glass coverslip through a bottom-up strategy by simple thermolysis of metal-alkyl ammonium halide precursors. The reaction temperature and composition of the alloy were varied sequentially to find out the maximum SERS efficiency from the substrates. While UV-vis spectroscopy was employed to characterize the optical properties of the substrates, the bulk and surface compositions of the microflowers were determined using energy-dispersive X-ray fluorescence (ED-XRF) and X-ray photoelectron spectroscopy (XPS) techniques, respectively. Also, the structural and morphological characterizations of the substrates were performed by X-ray diffraction and scanning electron microscope (SEM), respectively. For alloys, the ED-XRF studies confirmed that the bulk compositions matched with the feed ratio, while the surface compositions were found to be rich in copper in the form of both elementary copper and copper oxide, as revealed by XPS studies. From the efficiency studies for different compositions prepared, it was found that 10% Ag-Cu alloy microflowers produced the maximum SERS intensity for resonant R6G molecules as probes. In fact, R6G evidences a 50-fold enhancement in SERS spectra with 10% alloy microflowers as against pure Ag microflowers. Using 1, 2, 3-benzotriazole as a nonresonant Raman probe, uniform enhancement factors on the order of ≈10⁸ were achieved from different parts of the 10% Ag-Cu alloy microflower. The same substrate showed excellent Raman response for detecting R6G at very low concentrations such as 10 zM, leading to detection and analysis of SERS spectra from a single R6G molecule.

Surface-Enhanced Raman Sensing of Semi-Volatile Organic Compounds by Plasmonic Nanostructures

Facile detection of indoor semi-volatile organic compounds (SVOCs) is a critical issue to raise an increasing concern to current researchers, since their emissions have impacted the health of humans, who spend much of their time indoors after the recent incessant COVID-19 pandemic outbreaks. Plasmonic nanomaterial platforms can utilize an electromagnetic field to induce significant Raman signal enhancements of vibrational spectra of pollutant molecules from localized hotspots. Surface-enhanced Raman scattering (SERS) sensing based on functional plasmonic nanostructures has currently emerged as a powerful analytical technique, which is widely adopted for the ultra-sensitive detection of SVOC molecules, including phthalates and polycyclic aromatic hydrocarbons (PAHs) from household chemicals in indoor environments. This concise topical review gives updated recent developments and trends in optical sensors of surface plasmon resonance (SPR) and SERS for effective sensing of SVOCs by functionalization of noble metal nanostructures. Specific features of plasmonic nanomaterials utilized in sensors are evaluated comparatively, including their various sizes and shapes. Novel aptasensors-assisted SERS technology and its potential application are also introduced for selective sensing. The current challenges and perspectives on SERS-based optical sensors using plasmonic nanomaterial platforms and aptasensors are discussed for applying indoor SVOC detection.

A paper-based SERS assay for sensitive duplex cytokine detection towards the atherosclerosis-associated disease diagnosis

Atherosclerosis (AS) is the most common factor causing many cardiovascular and cerebrovascular diseases and has received considerable attention. The occurrence mechanism of AS is uncertain because it is a choronically pathological process that is influenced by multi-aspects, among which cytokines play the key roles in regulating the processes of the immune system. For example, two key cytokines, namely, IL-10 and MCP-1 (chemokine), which are involved in AS progression with varied levels, can be used for AS status monitoring and early diagnosis of AS-associated diseases. Hence, a new paper-based, surface-enhanced Raman spectroscopy (SERS) sensing platform was established for the detection of these two key cytokines. By combining a nanoporous networking membrane as the substrate and SERS nanotags as the probe for signal reading, together with a sandwich design, sensitive and specific identification and quantification of cytokine targets in human serum were achieved with excellent sensing characteristics. The lowest detectable concentration was determined to be 0.1 pg mL-1 for both IL-10 and MCP-1 in human serum. The assay also exhibits high specificity towards target cytokine detection, with low-nonspecific binding and acceptable cross-reactivity in the presence of other structurally similar targets. Finally, the practicability was validated by performing duplex detection in human serum, which further demonstrates the high specificity of the assay for the detection of target cytokines. Taken together, these promising results illustrate that this developed sensing assay is a candidate for clinical multi-target analysis in real environments.

Combined negative dielectrophoresis with a flexible SERS platform as a novel strategy for rapid detection and identification of bacteria

Surface-enhanced Raman spectroscopy (SERS) is a vibrational method successfully applied in analytical chemistry, molecular biology and medical diagnostics. In this article, we demonstrate the combination of the negative dielectrophoretic (nDEP) phenomenon and a flexible surface-enhanced Raman platform for quick isolation (3 min), concentration and label-free identification of bacteria. The platform ensures a strong enhancement factor, high stability and reproducibility for the SERS response of analyzed samples. By introducing radial dielectrophoretic forces directed at the SERS platform, we can efficiently execute bacterial cell separation, concentration and deposition onto the SERS-active surface, which simultaneously works as a counter electrode and thus enables such hybrid DEP-SERS device vibration-based detection. Additionally, we show the ability of our DEP-SERS system to perform rapid, cultivation-free, direct detection of bacteria in urine and apple juice samples. The device provides new opportunities for the detection of pathogens.

Quantitative PCR based detection system for cyanobacterial geosmin/2-methylisoborneol (2-MIB) events in drinking water sources: Current status and challenges

Taste and odor (T&O) are an important issue in drinking water, aquaculture, recreation and a few other associated industries, and cyanobacteria-relevant geosmin and 2-methylisoborneol (2-MIB) are the two most commonly detected T&O compounds worldwide. A rise in the cyanobacterial blooms and associated geosmin/2-MIB episodes due to anthropogenic activities as well as climate change has led to global concerns for drinking water quality. The increasing awareness for the safe drinking, aquaculture or recreational water systems has boost the demand for rapid, robust, on-site early detection and monitoring system for cyanobacterial geosmin/2-MIB events. In past years, research has indicated quantitative PCR (qPCR) as one of the promising tools for detection of geosmin/2-MIB episodes. It offers advantages of detecting the source organism even at very low concentrations, distinction of odor-producing cyanobacterial strains from non-producers and evaluation of odor producing potential of the cyanobacteria at much faster rates compared to conventional techniques.The present review aims at examining the current status of developed qPCR primers and probes in identifying and detecting the cyanobacterial blooms along with geosmin/2-MIB events. Among the more than 100 articles about cyanobacteria associated geosmin/2-MIB in drinking water systems published after 1990, limited reports (approx. 10 each for geosmin and 2-MIB) focused on qPCR detection and its application in the field. Based on the review of literature, a comprehensive open access global cyanobacterial geosmin/2-MIB events database (CyanoGM Explorer) is curated. It acts as a single platform to access updated information related to origin and geographical distribution of geosmin/2-MIB events, cyanobacterial producers, frequency, and techniques associated with the monitoring of the events. Although a total of 132 cyanobacterial strains from 21 genera and 72 cyanobacterial strains from 13 genera have been reported for geosmin and 2-MIB production, respectively, only 58 geosmin and 28 2-MIB synthesis regions have been assembled in the NCBI database. Based on the identity, geosmin sequences were found to be more diverse in the geosmin synthase conserved/primer design region, compared to 2-MIB synthesis region, hindering the design of universal primers/probes. Emerging technologies such as the bioelectronic nose, Surface Enhanced Raman Scattering (SERS), and nanopore sequencing are discussed for future applications in early on-site detection of geosmin/2-MIB and producers. In the end, the paper also highlights various challenges in applying qPCR as a universal system of monitoring and development of response system for geosmin/2-MIB episodes.

Surface-Enhanced Raman Spectroscopy of Organic Molecules and Living Cells with Gold-Plated Black Silicon

Black silicon (bSi) refers to an etched silicon surface comprising arrays of microcones that effectively suppress reflection from UV to near-infrared (NIR) while simultaneously enhancing the scattering and absorption of light. This makes bSi covered with a nm-thin layer of plasmonic metal, i.e., gold, an attractive substrate material for sensing of bio-macromolecules and living cells using surface-enhanced Raman spectroscopy (SERS). The performed Raman measurements accompanied with finite element numerical simulation and density functional theory analysis revealed that at the 785 nm excitation wavelength, the SERS enhancement factor of the bSi/Au substrate is as high as 10⁸ due to a combination of electromagnetic and chemical mechanisms. This finding makes the SERS-active bSi/Au substrate suitable for detecting trace amounts of organic molecules. We demonstrate the outstanding performance of this substrate by highly sensitive and specific detection of a small organic molecule of 4-mercaptobenzoic acid and living C6 rat glioma cell nucleic acids/proteins/lipids. Specifically, the bSi/Au SERS-active substrate offers a unique opportunity to investigate the living cells' malignant transformation using characteristic protein disulfide Raman bands as a marker. Our findings evidence that bSi/Au provides a pathway to the highly sensitive and selective, scalable, and low-cost substrate for lab-on-a-chip SERS biosensors that can be integrated into silicon-based photonics devices.

Theoretical and Experimental Studies of Ti3C2 MXene for Surface-Enhanced Raman Spectroscopy-Based Sensing

Recent advances in MXenes with high carrier mobility show great application prospects in the surface-enhanced Raman scattering (SERS) field. However, challenges remain regarding the improvement of the SERS sensitivity. Herein, an effective strategy considering charge-transfer resonance for semiconductor-based substrates is presented to optimize the SERS sensitivity with the guidance of the density functional theory calculation. The theoretical calculation predicted that the excellent SERS enhancement for methylene blue (MeB) on Ti₃C₂ MXene can be excited by both 633 and 785 nm lasers, and the Raman enhanced effect is mainly originated from the charge-transfer resonance enhancement. In this work, the Ti₃C₂ MXenes exhibit an excellent SERS sensitivity with an enhancement factor of 2.9 × 10⁶ and a low detection limit of 10^-7 M for MeB molecules. Furthermore, the SERS enhancement of Ti₃C₂ and Au-Ti₃C₂ substrates exhibit higher selectivity on different molecules, which contributes to the detection of target molecules in complex solution environments. This work can provide some theoretical and experimental basis for the research on SERS activity of other MXene materials.

Biosensing based on surface-enhanced Raman spectroscopy as an emerging/next-generation point-of-care approach for acute myocardial infarction diagnosis

Cardiovascular disease is a major global health issue. In particular, acute myocardial infarction (AMI) requires urgent attention and early diagnosis. The use of point-of-care diagnostics has resulted in the improved management of cardiovascular disease, but a major drawback is that the performance of POC devices does not rival that of central laboratory tests. Recently, many studies and advances have been made in the field of surface-enhanced Raman scattering (SERS), including the development of POC biosensors that utilize this detection method. Here, we present a review of the strengths and limitations of these emerging SERS-based biosensors for AMI diagnosis. The ability of SERS to multiplex sensing against existing POC detection methods are compared and discussed. Furthermore, SERS calibration-free methods that have recently been explored to minimize the inconvenience and eliminate the limitations caused by the limited linear range and interassay differences found in the calibration curves are outlined. In addition, the incorporation of artificial intelligence (AI) in SERS techniques to promote multivariate analysis and enhance diagnostic accuracy are discussed. The future prospects for SERS-based POC devices that include wearable POC SERS devices toward predictive, personalized medicine following the Fourth Industrial Revolution are proposed.

Bioluminescent Imaging and Tracking of Bacterial Transport in Soils

Bioimaging instrumentation can be used to observe environmental phenomena such as the transport, retention, and distribution of bacteria in soils in situ in a real-time, nondestructive manner. Bacteria designed to emit bioluminescence light signals are injected into a transparent column packed with soils, and then the column is placed into a bioimaging instrument, such as a PerkinElmer IVIS Spectrum, while it is connected through thin teflon tubes to other parts of the column system located outside of the imaging chamber, including a fraction collector for collecting effluent solution and a pump for introducing bacterial suspension or experimental solution. After self-correction of soil autofluorescence and bioluminescence and setup of required imaging parameters, the transport experiment is initiated by introducing the bacterial suspension to the soil column while the spatiotemporal distribution of bioluminescent bacteria in the entire soil column is imaged. Finally, the images are processed to analyze bacterial migration in the soil under various environmental conditions in comparison with the breakthrough and elution curves of the bacteria obtained by analyzing the effluent samples.

Using SERS-based microfluidic paper-based device (μPAD) for calibration-free quantitative measurement of AMI cardiac biomarkers

Recently, surface enhanced Raman scattering (SERS) has attracted much attention in medical diagnosis applications owing to better detection sensitivity and lower limit of detection (LOD) than colorimetric detection. In this paper, a novel calibration-free SERS-based μPAD with multi-reaction zones for simultaneous quantitative detection of multiple cardiac biomarkers - GPBB, CK-MB and cTnT for early diagnosis and prognosis of acute myocardial infarction (AMI) are presented. Three distinct Raman probes were synthesised, subsequently conjugated with respective detecting antibodies and used as SERS nanotags for cardiac biomarker detection. Using a conventional calibration curve, quantitative simultaneous measurement of multiple cardiac biomarkers on SERS-based μPAD was performed based on the characteristic Raman spectral features of each reporter used in different nanotags. However, a calibration free point-of-care testing device is required for fast screening to rule-in and rule-out AMI patients. Partial least squares predictive models were developed and incorporated into the immunosensing system, to accurately quantify the three unknown cardiac biomarkers levels in serum based on the previously obtained Raman spectral data. This method allows absolute quantitative measurement when conventional calibration curve fails to provide accurate estimation of cardiac biomarkers, especially at low and high concentration ranges. Under an optimised condition, the LOD of our SERS-based μPAD was identified at 8, 10, and 1 pg mL^-1, for GPBB, CK-MB and cTnT, respectively, which is well below the clinical cutoff values. Therefore, this proof-of-concept technique shows significant potential for highly sensitive quantitative detection of multiplex cardiac biomarkers in human serum to expedite medical decisions for enhanced patient care.

Near-Infrared Surface-Enhanced Raman Scattering on Silver-Coated Porous Silicon Photonic Crystals

Surface-enhanced Raman scattering (SERS) with near-infrared (NIR) excitation offers a safe way for the detection and study of fragile biomolecules. In this work, we present the possibility of using silver-coated porous silicon photonic crystals as SERS substrates for near-infrared (1064 nm) excitation. Due to the deep penetration of NIR light inside silicon, the fabrication of photonic crystals was necessary to quench the band gap photoluminescence of silicon crystal, which acts as mechanical support for the porous layer. Optimal parameters of the immersion plating process that gave maximum enhancement were found and the activity of SERS substrates was tested using rhodamine 6G and crystal violet dye molecules, yielding significant SERS enhancement for off-resonant conditions. To our knowledge, this is the first time that the 1064 nm NIR laser excitation is used for obtaining the SERS effect on porous silicon as a substrate.

Surface-Enhanced Raman Spectroscopy for Monitoring Extravirgin Olive Oil Bioactive Components

Olive oil is the main fat source of the Mediterranean diet. This seasoning ingredient is highly appreciated for its unique taste, functional properties, and positive impact on human health. The determination of chemical composition is a demanding task in order to fully characterize this precious food product, ensure its quality, and prevent fraudulent practices. Among innovative techniques proposed for the oil analysis, surface-enhanced Raman spectroscopy (SERS) can be an extremely useful tool for olive oil characterization. In this frame, we have investigated five noncommercial olive oils produced in different parts of South Italy by using a commercial Raman microspectroscopy apparatus and home-made signal-enhancing SERS substrates. A wavelet-based data analysis has allowed us to efficiently remove the background and the noise from the acquired spectra. The analysis of these SERS spectra has enabled the quantification of the relative contents of carotene, oleic acid, and phenols. These relative contents differ in the examined samples. In addition, SERS response in the lipid region has indicated differences in the relative abundance of saturated fatty acids. The present results confirm the validity of the SERS technique as a rapid, nondestructive, and reliable analytical technique for identifying olive oil bioactive components.