Weak Raman Signal Research Articles

Feasibility of a Fiber-Dispersive Raman Spectrometer for Biomarker Detection.

Raman spectroscopy is among the top analytical techniques for ultra-low-dense organic matter, crucial to the search for life and analysis of celestial body surfaces in space exploration missions. Achieving the ultimate sensitivity of in-situ Raman spectroscopy necessitates a breakthrough in detecting inelastically scattered light. Single-photon detectors (SPDs) operating in photon counting mode, which can differentiate between Raman and luminescence responses, are promising candidates for the challenging scientific requirements. Since large SPD arrays are not yet commercially available, a dispersive element can be adapted to a single-pixel detector. By exploiting chromatic dispersion in optical fibers and picosecond-pulsed excitation, we delay the arrivals of different spectral components onto a single-pixel SPD. This method also separates weak Raman signals from stronger luminescence through correlated time-domain measurements. We study the impact of fiber properties and the excitation wavelength of a pulsed laser on the spectral resolution of the fiber-dispersive Raman spectrometer (FDRS). Additionally, we demonstrate the FDRS's potential for studying biomarkers and discuss its feasibility for analyzing inclusions in ice matrices.

Raman cell sorting for single-cell research.

Cells constitute the fundamental units of living organisms. Investigating individual differences at the single-cell level facilitates an understanding of cell differentiation, development, gene expression, and cellular characteristics, unveiling the underlying laws governing life activities in depth. In recent years, the integration of single-cell manipulation and recognition technologies into detection and sorting systems has emerged as a powerful tool for advancing single-cell research. Raman cell sorting technology has garnered attention owing to its non-labeling, non-destructive detection features and the capability to analyze samples containing water. In addition, this technology can provide live cells for subsequent genomics analysis and gene sequencing. This paper emphasizes the importance of single-cell research, describes the single-cell research methods that currently exist, including single-cell manipulation and single-cell identification techniques, and highlights the advantages of Raman spectroscopy in the field of single-cell analysis by comparing it with the fluorescence-activated cell sorting (FACS) technique. It describes various existing Raman cell sorting techniques and introduces their respective advantages and disadvantages. The above techniques were compared and analyzed, considering a variety of factors. The current bottlenecks include weak single-cell spontaneous Raman signals and the requirement for a prolonged total cell exposure time, significantly constraining Raman cell sorting technology's detection speed, efficiency, and throughput. This paper provides an overview of current methods for enhancing weak spontaneous Raman signals and their associated advantages and disadvantages. Finally, the paper outlines the detailed information related to the Raman cell sorting technology mentioned in this paper and discusses the development trends and direction of Raman cell sorting.

Investigation of Melphalan interaction as an alkylating agent with nucleotides by using surface enhanced Raman spectroscopy (SERS)

SERS (Surface Enhanced Raman Spectroscopy) is a new Raman spectroscopy which relies on Surface Plasmon Resonance (SPR) of metal nanoparticles. We have applied colloidal silver and gold nanoparticles as amplifier agents to enhance nucleotide Raman signals. It is observed that without these enhancing agents, it is impossible to investigate nucleotide spectrum due to weak Raman signals. Interaction mechanism of Melphalan, an anticancer drug with four nucleotides (Adenine, Cytosine, Guanine, Thymine) was investigated using SERS to detect and identify changes due to alkylating process in Raman spectra. After incubating Melphalan drug with nucleotides for 24 h at 37 °C, some changes occurred in SERS spectrum and interpretation of SERS spectra revealed the influence of the alkyl substitution on peaks and Raman shifts. After incubation of Melphalan with each nucleotide, intensity of relevant SERS signals assigned to Amid III group of Cytosine and Amid I of Thymine decreased significantly, confirming alkylating taking place. In this study, we also investigated the effect of nanoparticles type on nucleotide spectrum. We could not obtain useful information in the cases of guanine nucleotide. The SERS spectrum of Cytosine as an example of nucleotides in aqueous solution compared to solid state and results demonstrated that in solid state better signals were obtained than in liquid state.

Multimodal fiber probe for simultaneous mid-infrared and Raman spectroscopy

A fiber probe has been developed that enables simultaneous acquisition of mid-infrared (MIR) and Raman spectra in the region of 3100–2600 cm−1. Multimodal measurement is based on a proposed ZrO2 crystal design at the tip of an attenuated total reflection (ATR) probe. Mid-infrared ATR spectra are obtained through a pair of chalcogenide infrared (CIR) fibers mounted at the base of the crystal. The probe enables both excitation and acquisition of a weak Raman signal from a portion of the sample in front of the crystal using an additional pair of silica fibers located in a plane perpendicular to the CIR fibers. The advantages of combining MIR and Raman spectra in a single probe have been discussed.

ELM combined with differential Raman spectroscopy for the detection of microplastics in organisms

Aiming at the problems of low extraction efficiency, high false detection rate, weak Raman signal and serious interference by fluorescence signal in the detection of microplastics in marine organisms, this paper establishes a set of rapid detection methods for microplastics in organisms, including confocal Raman spectroscopy, fluorescence imaging, differential Raman spectroscopy, and rapid identification of microplastics based on the ELM modeling assistance. Firstly, to address the problem of low extraction efficiency of microplastics, we explored and optimized the digestion method of tissues, which effectively improved the digestion effect of fish tissues and excluded the influence of tissues on microplastics detection. Aiming at the problems of high misdetection rate and low pre-screening efficiency of microplastics, fluorescence imaging technology is adopted to realize the visualization and detection of microplastics, which effectively improves the detection efficiency and precision of microplastics. Based on the confocal microscopy Raman spectroscopy detection system built independently in the laboratory, using 784/785 nm as the excitation light, the differential Raman spectroscopy technique effectively excludes the interference of fluorescence signals in the Raman spectra, and improves the signal-to-noise ratio of the Raman spectra, and the recovery rate of the Raman characteristic peaks in the differential Raman spectroscopy reaches 100 % compared to the traditional baseline correction method, which is 33.3 % higher than that of the baseline correction method. Finally, a microplastic identification model is constructed based on ELM to assist in realizing the rapid and accurate identification of microplastics. The more complete detection method of microplastics in marine organisms proposed in this paper can realize the rapid and nondestructive, efficient and accurate detection of microplastics in fish, which can help to further promote the development of marine microplastics monitoring technology.

High‐Sensitive and Background‐Free Coherent Anti‐Stokes Raman Scattering Microscopy Using Delay Modulation

AbstractCoherent anti‐Stokes Raman scattering (CARS) microscopy has demonstrated a powerful platform for label‐free, non‐invasive, and chemically specific imaging of biological samples. However, the non‐resonant background limits its ability to detect weak Raman signals. Here, an approach to eliminate the non‐resonant background in CARS using delay modulation (DM) is presented, which is enabled by an acousto‐optic modulator and spectral focusing. The results demonstrate that DM‐CARS reduces the non‐resonant background by 10 times and improves detection sensitivity by 100‐fold over normal CARS. It also shows that DM‐CARS has potential applications in tracking heavy water metabolism in bacteria for antimicrobial susceptibility testing and imaging liver tumor tissues. Furthermore, a handheld DM‐CARS device has also demonstrated for in vivo imaging, which can be beneficial in various applications.

SERS-based detection of the antibiotic ceftriaxone in spiked fresh plasma and microdialysate matrix by using silver-functionalized silicon nanowire substrates

Therapeutic drug monitoring (TDM) is an important tool in precision medicine as it allows estimating pharmacodynamic and pharmacokinetic effects of drugs in clinical settings. An accurate, fast and real-time determination of the drug concentrations in patients ensures fast decision-making processes at the bedside to optimize the clinical treatment. Surface-enhanced Raman spectroscopy (SERS), which is based on the application of metallic nanostructured substrates to amplify the inherent weak Raman signal, is a promising technique in medical research due to its molecular specificity and trace sensitivity accompanied with short detection times. Therefore, we developed a SERS-based detection scheme using silicon nanowires decorated with silver nanoparticles, fabricated by means of top-down etching combined with chemical deposition, to detect the antibiotic ceftriaxone (CRO) in spiked fresh plasma and microdialysis samples. We successfully detected CRO in both matrices with an LOD of 94 μM in protein-depleted fresh plasma and 1.4 μM in microdialysate.

Simultaneous Surface-Enhanced Raman Scattering with a Kerr Gate for Fluorescence Suppression.

The combination of surface-enhanced and Kerr-gated Raman spectroscopy for the enhancement of the Raman signal and suppression of fluorescence is reported. Surface-enhanced Raman scattering (SERS)-active gold substrates were demonstrated for the expansion of the surface generality of optical Kerr-gated Raman spectroscopy, broadening its applicability to the study of analytes that show a weak Raman signal in highly fluorescent media under (pre)resonant conditions. This approach is highlighted by the well-defined spectra of rhodamine 6G, Nile red, and Nile blue. The Raman spectra of fluorescent dyes were obtained only when SERS-active substrates were used in combination with the Kerr gate. To achieve enhancement of the weaker Raman scattering, Au films with different roughnesses or Au-core-shell-isolated nanoparticles (SHINs) were used. The use of SHINs enabled measurement of fluorescent dyes on non-SERS-active, optically flat Au, Cu, and Al substrates.

The strength of the OH-bend/OH-stretch Fermi resonance in small water clusters.

A novel Raman jet-spectrometer is used to study the Fermi resonance between the OH bending overtone and OH stretching fundamental in small cyclic water clusters (H2O)n with n = 3, 4, 5. The new setup features a recirculating vacuum system which reduces the gas consumption by 2 to 3 orders of magnitude and enables long-term measurements of very weak Raman signals. Raman spectra measured from highly diluted expansions with unprecedented signal-to-noise ratio are presented and cluster-specific intensity ratios and effective coupling constants are derived using Markov-Chain Monte-Carlo methods, yielding a high probability for an almost "perfect" resonance for the tetramer and pentamer, i.e. a close frequency match of bend overtone and stretch fundamental with intensity ratios close to 1, but a larger coupling constant for the trimer, with best estimates close to W5 ≲ 50 cm-1 < W4 ≲ 60 cm-1 < W3 ≈ 65 cm-1.

A novel SERS-lateral flow assay (LFA) tray for monitoring of miR-155-5p during pyroptosis in breast cancer cells.

In the study, a novel surface-enhanced Raman scattering (SERS)-lateral flow assay (LFA) tray for the real-time detection of pyroptosis-associated miR-155-5p in breast cancer cells was established and validated. The SERS probe modified with monoclonal antibodies and functionalized HP1@5-FAM was first synthesized. When miR-155-5p was present, HP1@5-FAM on the SERS probe specifically recognized target miRNAs and hybridized with them, resulting in HP2 on the T line only capturing some SERS probes that were not bound to miR-155-5p. The T line appeared as a light orange band or there was no color change, and the corresponding Raman detection result showed a weak or insignificant Raman signal. The SERS probe showed high selectivity, satisfactory stability, and excellent reproducibility, and the limit of detection (LOD) for miR-155-5p was 7.26 aM. Finally, the proposed SERS-LFA tray was applied to detect miR-155-5p in MBA-MD-468 cells that underwent varying degrees of pyroptosis, and the detection results of SERS were consistent with those of the conventional real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay. The study demonstrated that the SERS-LFA tray was a convenient and ultrasensitive method for miR-155-5p real-time detection, which could provide more detailed information for pyroptosis and be of potential value in guiding the treatment of breast cancer.

Advancing cerumen analysis: exploring innovative vibrational spectroscopy techniques with respect to their potential as new point-of-care diagnostic tools.

Cerumen, commonly known as earwax, is a complex mixture composed of secretions from ceruminous glands. These secretions are heterogeneous mixtures mainly composed of lipids and proteins. Despite its prevalence, the potential diagnostic value of cerumen remains largely unexplored. Here, we present an in-depth analysis of cerumen utilizing well-known vibrational approaches such as conventional Raman spectroscopy or surface-enhanced Raman spectroscopy (SERS) together with advanced vibrational spectroscopy techniques such as coherent Raman scattering (CRS), i.e. broadband coherent anti-Stokes Raman scattering (CARS) or stimulated Raman scattering (SRS), as well as optical photothermal infrared (OPTIR) spectroscopy. Through the integration of these vibrational spectroscopic methods, lipids and proteins can be identified as the main components of cerumen; however, they contribute to the final spectral information to various extents depending on the vibrational detection scheme applied. The inherently weak Raman signal could be enhanced by linear (SERS) and non-linear (CRS) processes, resulting in efficient acquisition of fingerprint information and allowing for the detection of marker modes, which cannot be addressed by conventional Raman spectroscopy. OPTIR spectroscopy provides complementary information to Raman spectroscopy, however, without the contribution of a fluorescence background. Our findings underscore the utility of these cutting-edge techniques in unveiling the intricate molecular landscape of cerumen, paving the way for novel point-of-care diagnostic methodologies and therapeutic interventions.

Conquering Metal–Organic Frameworks by Raman Scattering Techniques

AbstractMetal–organic frameworks (MOFs) have emerged as a versatile class of materials. Understanding the structural and chemical properties of MOFs is essential for tailoring their performance to suit specific applications. In recent years, Raman spectroscopy, a non‐destructive vibrational spectroscopic technique, has evolved into a powerful tool for characterizing MOFs. Beyond spontaneous Raman scattering, numerous advanced Raman techniques have been developed to amplify the inherently weak Raman signal. These innovations have significantly enhanced the spatial resolution, frame rate, and sensitivity of Raman imaging, thereby opening up new possibilities for applications, such as label‐free sensing. This tutorial work is designed to demystify the fundamental theory and instrumentation of Raman spectroscopy, elucidating the differences between commonly used Raman techniques. Particular emphasis is placed on their advantages and limitations when applied to MOF materials. Furthermore, this work showcases how Raman techniques are employed in studying MOF systems to address societal needs and explore future directions. Ultimately, this review emphasizes the crucial role of Raman spectroscopy and the development of novel Raman‐based in situ techniques to conquer the field of MOFs.

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.

Pupil-engineered coherent anti-Stokes Raman scattering spectroscopy

Coherent anti-Stokes Raman scattering (CARS) spectroscopy suffers from non-resonant background (NB) that is several orders of magnitude stronger than CARS signals. NB occupies the camera sensor dynamic range and hampers quantitative detection of weak Raman signals at low molecular concentrations. Here, we propose a novel technique to reduce NB for heterodyne CARS spectroscopy, by independently controlling the parities of the amplitude point spread functions of CARS and NB. We realize the parity control by applying the pupil engineering of the excitation and detection optical systems. A proof-of-concept experiment shows that the signal-to-background ratio (SBR) of the CARS signal to the NB can be improved as designed.

Denoising of Raman Spectra Using a Neural Network Based on Variational Mode Decomposition, Empirical Wavelet Transform, and Encoder-Bidirectional Long Short-Term Memory

Raman spectroscopy has been widely applied in numerous fields including bioanalysis, disease diagnosis, and molecular recognition, owing to its unique advantages of being non-invasive, rapid, and highly specific. However, the acquisition of Raman spectral data is often susceptible to various noise interferences, such as shot noise from the internal detector and dark current noise from the instrument. As a result, the weak Raman signals typically become arduous to discern, which affects the localization and identification of characteristic spectral peaks. This study investigates variational mode decomposition (VMD), empirical wavelet transform (EWT), and integrated encoder-bidirectional long short-term memory (EBiLSTM) modules to propose a neural network algorithm for adaptive denoising of Raman spectra. By combining VMD and EWT, the Raman spectra are decomposed into several sub-sequences, which solves the problem of mode mixing between high-frequency signals and noise in empirical mode decomposition, and significantly reduces the complexity of the original Raman spectral lines. The correlation coefficient between each modal component and the original signal is calculated along with the zero-crossing rate index to categorize the noise and signal sequences. Leveraging the linear differences between the ideal spectral lines and the noisy spectral curves, an encoder-bidirectional long short-term memory (EBiLSTM) denoising network is constructed for hierarchical denoising to extract valid spectral feature information from the high-frequency components, realizing refined adaptive denoising of the Raman spectra. Industry standard objective evaluation metrics on the signal-to-noise ratio and root mean square error are utilized to conduct simulation experiments comparing state-of-the-art algorithms, including empirical mode decomposition, VMD, sliding window averaging, and wavelet thresholding. The experimental results demonstrate that the Raman spectral denoising algorithm combining variational mode decomposition and neural networks improves the denoising performance by 13.38% to 72%, exhibiting higher accuracy and reliability.

More than magnetic isolation: Dynabeads as strong Raman reporters toward simultaneous capture and identification of targets

AbstractDynabeads are superparamagnetic particles used for the immunomagnetic purification of cells and biomolecules. Post‐capture, however, target identification relies on tedious culturing, fluorescence staining, and/or target amplification. Raman spectroscopy presents a rapid detection alternative, but current implementations target cells themselves with weak Raman signals. We present antibody‐coated Dynabeads as strong Raman reporter labels whose effect can be considered a Raman parallel of immunofluorescent probes. Recent developments in techniques for separating target‐bound Dynabeads from unbound Dynabeads make such an implementation feasible with high specificity. We deploy Dynabeads anti‐Salmonella to bind and identify Salmonella enterica, a major foodborne pathogen. Dynabeads present major peaks around 1000 and 1600 cm−1 from aliphatic and aromatic C‐C stretching of the polystyrene coating and near 1350 cm−1 from the ɣ‐Fe2O3 and Fe3O4 core, confirmed with electron dispersive X‐ray (EDX) imaging. Minor to no contributions are made from the surface antibodies themselves as confirmed by Raman analysis of surface‐activated, antibody‐free beads. Dynabeads' Raman signature can be measured in dry and liquid samples even at single shot ~30 × 30 μm area imaging using 0.5 s, 7‐mW laser acquisition with single and clustered beads providing a 44‐ and 68‐fold larger Raman intensity compared with the signature from cells. Higher polystyrene and iron oxide content in clusters yields larger signal intensity, and conjugation to bacteria strengthens clustering as a bacterium can bind to more than one bead as observed via transmission electron microscopy (TEM). Our findings shed light on the intrinsic Raman reporter nature of Dynabeads. When combined with emerging techniques for the separation of target‐bound Dynabeads from unbound Dynabeads such as using centrifugation through a density media bilayer, they have the potential to demonstrate their dual function for target isolation and detection without tedious staining steps or unique plasmonic substrate engineering, advancing their applications in heterogeneous samples like food, water, and blood.

Asymmetric split-ring plasmonic nanostructures for the optical sensing of Escherichia coli.

Strategies for in-liquid micro-organism detection are crucial for the clinical and pharmaceutical industries. While Raman spectroscopy is a promising label-free technique for micro-organism detection, it remains challenging due to the weak bacterial Raman signals. In this work, we exploit the unique electromagnetic properties of metamaterials to identify bacterial components in liquid using an array of Fano-resonant metamolecules. This Fano-enhanced Raman scattering (FERS) platform is designed to exhibit a Fano resonance close to the protein amide group fingerprint around 6030 nm. Raman signatures of Escherichia coli were recorded at several locations on the metamaterial under off-resonance laser excitation at 530 nm, where the photodamage effect is minimized. As the sizes of the Escherichia coli are comparable to the micro-gaps i.e, 0.41 µm, of the metamaterials, its local immobilisation leads to an increase in the Raman sensitivity. We also observed that the time-dependent FERS signal related to bacterial amide peaks increased during the bacteria's mid-exponential phase while it decreased during the stationary phase. This work provides a new set of opportunities for developing ultrasensitive FERS platforms suitable for large-scale applications and could be particularly useful for diagnostics and environmental studies at off-resonance excitation.

Activated carbon@silver nanoparticles conjugates as SERS substrate for capturing malathion analyte molecules for SERS detection

AbstractMalathion is one of the commonly used organophosphate pesticides known to attack the central nervous system, posing a risk to humans and other animals upon exposure. The surface enhanced Raman spectroscopy (SERS) has been identified as an indispensable tool for chemical and biomolecular sensing. In this work, the facile fabrication of activated carbon (AC)‐based colloidal SERS active substrate dubbed AC@AgNPs was designed by trapping AgNPs on the surface of AC for detection of varying concentrations of malathion. Apart from the higher concentrations of malathion, the rest of the normal Raman spectra of malathion standard solutions exhibited weak Raman signals. The intensity of peaks for 0.47 mg L−1 were nearly non‐existent which is an indication that the malathion pesticide could only be detected up to 0.95 mg L−1 when using silica wafer. On the contrary, all the SERS spectra of malathion in wheat extracts adsorbed on AC@AgNPs substrate exhibited strong Raman signals. Quantitative analysis of malathion was performed by regression models developed using PLSR built with the raw spectra (no pretreatment), SNV‐PLSR, and SNV‐CARS‐PLSR. The model with the most remarkable performance was established by using SNV‐PLSR with r = 0.9869 and RPD = 4.61. This research shows that the proposed method can rapidly detect malathion residues in wheat, suggesting that it could be adopted for production process monitoring of other related food products to guarantee their safety for human and animal consumption.

Penetration-then-growth enables label-free surface-enhanced Raman spectroscopic discrimination of fibrotic cells and kidney tissues

Surface-enhanced Raman spectroscopy (SERS) is a highly efficient optical technique that employs metallic nanostructures to amplify the inherently weak Raman signals. Despite its great potential in obtaining fingerprint spectral information in complex biological samples, examining subtle molecular change in fixed cells/tissues by SERS is difficult because large-sized metal nanoparticle (NPs) can generate strong SERS signals but lack the ability to penetrate into the samples, whereas small-sized NPs can easily infiltrate samples but do not exhibit SERS activity. Herein, we propose a penetration-then-growth strategy for SERS-based detection of molecular change in the fibrogenic process. In the proof of concept study, control and fibrotic cells / mouse kidney tissue sections were initially incubated with ∼15 nm Au NPs which were permeable, and then the deposited NPs were grown up in situ to act as SERS substrates for Raman signal amplification. After NP growth, the Raman signals were dramatically enhanced, enabling fast discrimination of molecular changes occurred during fibrosis, which were indiscernible using conventional Raman spectrum or SERS detected with ∼50 nm Au NPs. This method is simple, fast, and can be readily adapted for inspecting molecular changes in other biological events.

A SERS nanoswitch based on Cu(II)-mediated dual-ligand AuNPs reversible aggregation for pyrophosphate ions detection

Surface enhanced Raman spectroscopy (SERS) detection was not as accurate and reproducible as fluorometry due to some uncertainties such as operator's focus adjustment and difference between capillaries. Herein, the weak Raman signal (1640 cm−1) from water bending vibration is adopted as a benchmark to improve the practical applicability of Raman detection. Specifically, amygdalin and citrate sodium were applied as reducing and capping agent to synthesize dual-ligand gold nanoparticles (DL-AuNPs). Additionally, the cyano group of amygdalin can attach to the surface of DL-AuNPs and generate a primary SERS signal (2174 cm−1), which can be significantly enhanced by Cu(II) as DL-AuNPs aggregates. More importantly, the strong binding affinity between pyrophosphate ions (PPi) and Cu(II) redisperses DL-AuNPs and decreases the signal intensity, making the DL-AuNPs/Cu(II) SERS sensor promising for the detection of PPi. This proposed method presents a reliable SERS analysis with the stable water background calibration and broaden the application of SERS technique in aqueous solution target monitoring.