Application Of Raman Spectroscopy Research Articles

Diagnosis of ‘‘Helicobacter pylori infection of the gastric biopsy’’ by rapid urease test, histopathology and Raman spectroscopy

This study aim to investigate the diagnostic potential of Raman spectroscopy in comparison with rapid urease test and histopathology in diagnosis of H. pylori infection.A comparative study was conducted at Pathology Laboratory and a total of 94 samples were collected from patients based on Rome IV criteria. Sensitivity, specificity and accuracy of histopathology, rapid urease test and for Raman spectroscopy were investigated.Rapid urease test showed 23 false negative results of H. pylori as compared to Raman spectroscopy and histopathology.We concluded that Raman spectroscopy showed sensitivity (94.5%), accuracy (94.0%) and specificity of (87.5%) in the diagnosis of H. pylori infection. However rapid urease test showed specificity of 92.5% while low sensitivity 75%, and 78% accuracy as compared to Raman spectroscopy and histopathology . This study illustrates the applicability of Raman spectroscopy as a potent innovative detection tool for the molecular detection of H. pylori infection in gastritis.

Application of Raman Spectroscopy to Dynamic Binding Capacity Analysis.

Protein A affinity chromatography is a key step in isolation of biotherapeutics (BTs) containing fragment crystallizable regions, including monoclonal and bispecific antibodies. Dynamic binding capacity (DBC) analysis assesses how much BT will bind to a protein A column. DBC reduces with column usage, effectively reducing the amount of recovered product over time. Drug regulatory bodies mandate chromatography resin lifetime for BT isolation, through measurement of parameters including DBC, so this feature is carefully monitored in industrial purification pipelines. High-performance affinity chromatography (HPAC) is typically used to assess the concentration of BT, which when loaded to the column results in significant breakthrough of BT in the flowthrough. HPAC gives an accurate assessment of DBC and how this changes over time but only reports on protein concentration, requires calibration for each new BT analyzed, and can only be used offline. Here we utilized Raman spectroscopy and revealed that this approach is at least as effective as both HPAC and ultraviolet chromatogram methods at monitoring DBC of protein A resins. In addition to reporting on protein concentration, the chemical information in the Raman spectra provides information on aggregation status and protein structure, providing extra quality controls to industrial bioprocessing pipelines. In combination with partial least square (PLS) analysis, Raman spectroscopy can be used to determine the DBC of a BT without prior calibration. Here we performed Raman analysis offline in a 96-well plate format, however, it is feasible to perform this inline. This study demonstrates the power of Raman spectroscopy as a significantly improved approach to DBC monitoring in industrial pipelines.

Raman Spectroscopy: Can It Change The Future Of Brain Tumour Surgery?s.

Raman Spectroscopy (RS) is one of several techniques being used to identify tumour tissue during brain surgery. It is emerging as a novel investigative and diagnostic tool. The application of RS in cancer treatment has displayed promising results. This review centers around its clinical implication in brain tumours.

Application of serum Raman spectroscopy combined with classification model for rapid breast cancer screening

IntroductionThis study aimed to evaluate the feasibility of using general Raman spectroscopy as a method to screen for breast cancer. The objective was to develop a machine learning model that utilizes Raman spectroscopy to detect serum samples from breast cancer patients, benign cases, and healthy subjects, with puncture biopsy as the gold standard for comparison. The goal was to explore the value of Raman spectroscopy in the differential diagnosis of breast cancer, benign lesions, and healthy individuals.MethodsIn this study, blood serum samples were collected from a total of 333 participants. Among them, there were 129 cases of tumors (pathologically diagnosed as breast cancer and labeled as cancer), 91 cases of benign lesions (pathologically diagnosed as benign and labeled as benign), and 113 cases of healthy controls (labeled as normal). Raman spectra of the serum samples from each group were collected. To classify the normal, benign, and cancer sample groups, principal component analysis (PCA) combined with support vector machine (SVM) was used. The SVM model was evaluated using a cross-validation method. ResultsThe results of the study revealed significant differences in the mean Raman spectra of the serum samples between the normal and tumor/benign groups. Although the mean Raman spectra showed slight variations between the cancer and benign groups, the SVM model achieved a remarkable prediction accuracy of up to 98% for classifying cancer, benign, and normal groups. DiscussionIn conclusion, this exploratory study has demonstrated the tremendous potential of general Raman spectroscopy as a clinical adjunctive diagnostic and rapid screening tool for breast cancer.

Applications of Raman spectroscopy in the analysis of biological evidence.

During the past few decades, Raman spectroscopy has progressed and captivated added attention in the field of science. However, the application of Raman spectroscopy is not limited to the field of forensic science and analytical chemistry; it is one of the emerging spectroscopic techniques, utilized in the field of forensic science which in turn could be a supporting tool in the law and justice system. The advantage of Raman spectroscopy over the other conventional techniques is that it is rapid, reliable, and non-destructive in nature with minimal or no sample preparation. The quantitative and qualitative analysis of evidence from biological and non-biological origins could easily be performed by using Raman spectroscopy. The forensic domain is highly complex with multidisciplinary branches, and therefore a plethora of techniques are utilized for the detection, identification, and differentiation of innumerable pieces of evidence for the purpose of law and justice. Herein, a systematic review is carried out on the application of Raman spectroscopy in the realm of forensic biology and serology considering its usefulness in practical perspectives. This review paper highlights the significance of modern techniques, including micro-Raman spectroscopy, confocal Raman spectroscopy, surface-enhanced Raman spectroscopy, and paper-based surface-enhanced Raman spectroscopy, in the field of Raman spectroscopy. These techniques have demonstrated notable advancements in terms of their applications and capabilities. Furthermore, to comprehensively capture the progress in the development of Raman spectroscopy, all thepublished paperswhich could be retrieved from the available databases from the year 2007 to 2022 were incorporated.

Investigating Laser-Induced Periodic Surface Structures (LIPSS) Formation in Silicon and Their Impact on Surface-Enhanced Raman Spectroscopy (SERS)

Laser-induced periodic surface structures (LIPSS) have gained significant attention due to their ability to modify the surface morphology of materials at the micro-nanoscale and show great promise for surface functionalization applications. In this study, we specifically investigate the formation of LIPSS in silicon substrates and explore their impact on surface-enhanced Raman spectroscopy (SERS) applications. This study reveals a stepwise progression of LIPSS formation in silicon, involving three distinct stages of LIPSS: (1) integrated low-spatial-frequency LIPSS (LSFL) and high-spatial-frequency LIPSS (HSFL), (2) principally LSFL and, (3) LSFL at the edge of the irradiated spot, elucidating the complex interplay between laser fluence, pulse number, and resulting surface morphology. Furthermore, from an application standpoint, these high-quality multi-scale periodic patterns lead to the next step of texturing the entire silicon surface with homogeneous LIPSS for SERS application. The potential of LIPSS-fabricated silicon substrates for enhancing SERS performance is investigated using thiophenol as a test molecule. The results indicate that the Au-coated combination of LSFL and HSFL substrates showcased the highest enhancement factor (EF) of 1.38×106. This pronounced enhancement is attributed to the synergistic effects of localized surface plasmon resonance (LSPR) and surface plasmon polaritons (SPPs), intricately linked to HSFL and LSFL characteristics. These findings contribute to our understanding of LIPSS formation in silicon and their applications in surface functionalization and SERS, paving the way for sensing platforms.

Raman Spectroscopy as a Potential Adjunct of Thyroid Nodule Evaluation: A Systematic Review.

The incidence of thyroid nodules (TNs) is estimated at 36.5% and 23% in females and males, respectively. A single thyroid nodule is usually detected during ultrasound assessment in patients with symptoms of thyroid dysfunction or neck mass. TNs are classified as benign tumours (non-malignant hyperplasia), benign neoplasms (e.g., adenoma, a non-invasive follicular tumour with papillary nuclear features) or malignant carcinomas (follicular cell-derived or C-cell derived). The differential diagnosis is based on fine-needle aspiration biopsies and cytological assessment (which is burdened with the bias of subjectivity). Raman spectroscopy (RS) is a laser-based, semiquantitative technique which shows for oscillations of many chemical groups in one label-free measurement. RS, through the assessment of chemical content, gives insight into tissue state which, in turn, allows for the differentiation of disease on the basis of spectral characteristics. The purpose of this study was to report if RS could be useful in the differential diagnosis of TN. The Web of Science, PubMed, and Scopus were searched from the beginning of the databases up to the end of June 2023. Two investigators independently screened key data using the terms "Raman spectroscopy" and "thyroid". From the 4046 records found initially, we identified 19 studies addressing the differential diagnosis of TNs applying the RS technique. The lasers used included 532, 633, 785, 830, and 1064 nm lines. The thyroid RS investigations were performed at the cellular and/or tissue level, as well as in serum samples. The accuracy of papillary thyroid carcinoma detection is approx. 90%. Furthermore, medullary, and follicular thyroid carcinoma can be detected with up to 100% accuracy. These results might be biased with low numbers of cases in some research and overfitting of models as well as the reference method. The main biochemical changes one can observe in malignancies are as follows: increase of protein, amino acids (like phenylalanine, tyrosine, and tryptophan), and nucleic acid content in comparison with non-malignant TNs. Herein, we present a review of the literature on the application of RS in the differential diagnosis of TNs. This technique seems to have powerful application potential in thyroid tumour diagnosis.

Hyperspectral Raman Imaging for Automated Recognition of Human Renal Amyloid.

In the clinical setting, routine identification of the main types of tissue amyloid deposits, light-chain amyloid (AL) and serum amyloid A (AA), is based on histochemical staining; rarer types of amyloid require mass spectrometry analysis. Raman spectroscopic imaging is an analytical tool, which can be used to chemically map, and thus characterize, the molecular composition of fluid and solid tissue. In this proof-of-concept study, we tested the feasibility of applying Raman spectroscopy combined with artificial intelligence to detect and characterize amyloid deposits in unstained frozen tissue sections from kidney biopsies with pathologic diagnosis of AL and AA amyloidosis and control biopsies with no amyloidosis (NA). Raman hyperspectral images, mapped in a 2D grid-like fashion over the tissue sections, were obtained. Three machine learning-assisted analysis models of the hyperspectral images could accurately distinguish AL (types λ and κ), AA, and NA 93-100% of the time. Although very preliminary, these findings illustrate the potential of Raman spectroscopy as a technique to identify, and possibly, subtype renal amyloidosis.

In-situ deposition of silver nanoparticles on cuprous oxide hollow spheres for sensitive and recyclable SERS sensing in solution based on electromagnetic and chemical enhancement

In order to achieve widespread application of surface-enhanced Raman spectroscopy (SERS) technique for practical sensing illegal additives in food, it is crucial to construct a reliable SERS substrate that offers both high sensitivity and reusability. This work utilized a simple and rapid in-situ deposition method to deposit Ag nanoparticles onto hollow Cu2O nanospheres, resulting in the formation of Cu2O/Ag nanocomposites with photocatalytic and SERS properties. These nanocomposites were employed as a hopeful SERS analysis for effective sensing of colorant additives in fruit juice, including methylene blue (MB) and rhodamine 6G (R6G). Impressively, the nanocomposites exhibited an exceptional detection limit of 10−9 M for the color agents and demonstrated a strong linear relationship between SERS intensities and the logarithmic concentration (R2 ≥ 0.95). The hollow structure of Cu2O provided low density and long-term dispersion stability in solution, which are beneficial for real-time monitoring the additives in liquid food. The excellent SERS performance can be attributed to the electromagnetic effect of Ag metals and the chemical enhancement of Cu2O semiconductors, as confirmed by the N 1 s XPS spectra from MB. Furthermore, the Cu2O/Ag nanocomposites efficiently degraded dye molecules under UV light irradiation within a short period of 45 min. So, the nanocomposites exhibited practical recyclability, as demonstrated by their consistent performance over five cycles of SERS sensing. These findings highlight their significant potent for SERS sensing trace pollutants and ecological restoration by photocatalytic reaction in the future.

Advancements and prospects of Raman spectroscopy in urological tumors: a bibliometric analysis.

Raman spectroscopy exhibits potential as a tool for identifying the chemical composition of substances and has witnessed a growing application in urological oncology. This study undertook a bibliometric analysis to chart the present state and future prospects of Raman spectroscopy applications in urological tumors. The present study retrieved literature on the utilization of Raman spectroscopy in urological oncology from the Science Citation Index Expanded of Web of Science Core Collection, spanning from its inception to June 2023. Data from included studies were analyzed using CiteSpace, Python, and Excel. Our study examined 897 articles from 65 countries and identified a significant exponential growth in annual publications. The USA and China were prominent contributors to this field, with high publication rates and funding agencies. Shanghai Jiao Tong University emerged as the most influential institution. The journals Analytical Chemistry and Analyst were found to be the most productive. Our keyword analysis revealed an intense interest for "gold nanoparticle" and "pathology," with the most recent bursts occurring for "surface-enhanced Raman scattering (SERS)," "biomarkers," and "prostate specific antigen." As a detection tool, Raman spectroscopy holds the potential to assist in the identification, management, and prognostication of urological tumors. Notably, adjuvant diagnosis and prognosis evaluation based on SERS of tumor markers is a hot research topic. These findings offer valuable insights into the current state of Raman spectroscopy research in urological oncology, which could inform future studies and clinical practice.

B-358 Application of Surface-Enhanced Raman Spectroscopy to Improve Sensitivity of Clinical Assays

Abstract Background Current efforts to expand the pool of available markers that can be analyzed in clinical settings is hampered by limited volumes of biomaterial-rich fluids and low concentrations of certain analytes, coupled with poor sensitivity of existing detection techniques. Although progress has been made using advanced sample preparation or assay techniques such as miRNeasy or ELISA for genomic and protein assays, respectively, little research has focused on adapting new optical methods as detection modes in the clinic. Amplified Sciences has developed an enzymatic activity assay platform using SERS detection to improve diagnostic sensitivities in multiple disease indications. Along with the experts at Wasatch Photonics, research focused on adaptation of this assay platform has enabled investigation of multiple markers of disease that had previously been undervalued or overlooked, as well as stacking of multiple markers in precious, low-volume samples. Methods Building upon previously published data using gastricsin as a marker to identify benign, non-mucinous pancreatic cysts, Amplified Sciences has added several SERS laser wavelengths, and different sample preparation methods to the existing platform. To examine the sensitivities of laser and dye combinations, solutions representative of assay samples containing rhodamine-dimer dye-labeled peptide were tested using Wasatch Photonics Raman spectrometers at 532, 638, 785, and 830 nm laser wavelengths. Samples at different pH were analyzed after addition of colloidal Au or Ag nanoparticles to determine the impacts of sample preparation on SERS spectral features. After drying in a desiccator overnight, the samples were reanalyzed to assess the stability of the SERS signals. As a pertinent application of this technology, an activity assay was developed for the known COVID protease 3ClPro. Release of rhodamine dimer dye as a result of 3ClPro cleavage of the substrate was quantified using SERS. The data were analyzed using Bruker OPUS Software package, and plotted using Graphpad Prism 9. Results Each laser, buffer, and metal used for SERS provided a unique spectral signature, suggesting that different transitions are available and potentially tunable depending on the application under investigation. Sensitivity was, as expected, best with the 532 nm SERS system purportedly due to enhancement factors, and the resonance impacts of rhodamine dyes at 532 nm. It was found that the Limit of Detection of Rhodamine-dimer dye was 100-fold lower with SERS compared to fluorescence, even after a 3-fold dilution with colloidal Ag. However, the remaining lasers could be more finely tuned, and, thus, provide alternate spectral properties, and different sensitivities which has implications when new dye classes are introduced into the platform. Furthermore, when SERS was applied to the 3ClPro assay, it was determined that activity could be detected below the dimerization concentration of 3ClPro, described in the literature as ∼25 nM. Also, a monomeric version of 3ClPro that is expected to have no reactivity with the substrate was found to display activity above background at concentrations as low as 1 µM. Conclusion SERS is an appropriate method for measuring activity in clinically relevant markers of disease, with tunable characteristics based upon the dye composition and the spectrometer in use.

Highly sensitive and uniform Ag nanostructures for surface-enhanced Raman spectroscopy (SERS) applications

The present investigation involves the in situ growth of Ag nanostructures (NSs) onto a rough Cu surface, accomplished through a cost-effective and straightforward fabrication process. The inherent characteristics of the Cu surface contribute to a certain degree of a surface-enhanced Raman spectroscopy (SERS) signal. Upon integration with Ag NSs, the Cu surface serves as an exceptionally sensitive and consistently uniform substrate for surface-enhanced Raman spectroscopy. Notably, a singular substrate accommodates the simultaneous detection of four distinct probe molecules. Subsequent SERS analyses of Ag NSs on Cu were executed under varying laser power conditions. Intriguingly, despite the escalation in laser power, no substantial shifts were discerned in the peak positions corresponding to the probe molecules. Consequently, it can be inferred that, for investigations where peak position shifts hold significance, the utilization of a thermally conductive material in fabricating SERS-active substrates could confer notable advantages.

A Practical Primer: Raman Spectroscopy for Monitoring of Photopolymerization Systems.

Photopolymerization systems provide compelling advantages for industrial applications due to their fast reaction kinetics, wide selection of monomers for physical property development, and energy-efficient initiation via illumination. These same advantages can present challenges when attempting to monitor these reactions or characterize their resulting polymers; however, Raman spectroscopy can provide the flexibility and resolution needed. In this overview, Raman spectroscopy is compared to common characterization techniques, such as photo-differential scanning calorimetry and infrared spectroscopy, highlighting advantages of Raman spectroscopy. Examples are provided of how Raman spectroscopy has been used to monitor photopolymerizations and to provide insight on the impact of monomer chemistry and processing conditions, as well as paired with other techniques to elucidate physical properties. Finally, practical tips are provided for applying Raman spectroscopy and microscopy in photopolymerization systems.

Multifocal Raman Spectrophotometer for Examining Drug-Induced and Chemical-Induced Cellular Changes in 3D Cell Spheroids.

Cell spheroids offer alternative in vitro cell models to monolayer cultured cells because they express complexities similar to those of in vivo tissues, such as cellular responses to drugs and chemicals. Raman spectroscopy emerged as a powerful analytical tool for detecting chemical changes in living cells because it nondestructively provides vibrational information regarding a target. Although multiple iterations are required in drug screening to determine drugs to treat cell spheroids and assess the inter-spheroid heterogeneity, current Raman applications used in spheroids analysis allow the observation of only a few spheroids owing to the low throughput of Raman spectroscopy. In this study, we developed a multifocal Raman spectrophotometer that enables simultaneous analysis of multiple spheroids in separate wells of a regular 96-well plate. By utilizing 96 focal spots excitation and parallel signal collection, our system can improve the throughput by approximately 2 orders of magnitude compared to a conventional single-focus Raman microscope. The Raman spectra of HeLa cell spheroids treated with anticancer drugs and HepG2 cell spheroids treated with free fatty acids were measured simultaneously, and concentration-dependent cellular responses were observed in both studies. Using the multifocal Raman spectrophotometer, we rapidly observed chemical changes in spheroids, and thus, this system can facilitate the application of Raman spectroscopy in analyzing the cellular responses of spheroids.

Application of Raman spectroscopy in breast cancer surgery

The incidence of breast cancer is increasing worldwide. As cancer screening has become more widespread, the rate of early breast cancer detection has increased and treatment methods have changed. Partial mastectomy is performed more often than total mastectomy for the surgical treatment of early breast cancer, and sentinel lymph node biopsy plays an important role. A high level of accuracy is necessary for the intraoperative examination of surgical margins and sentinel lymph nodes to identify malignancies. Therefore, several examination techniques, including Raman spectroscopy, that replace or supplement the currently used frozen-section methods are being studied. Raman spectroscopy has the ability to diagnose cancer in normal tissue by providing in real time a chemical fingerprint that can be used to differentiate between cells and tissues. Numerous studies have investigated the utilization of Raman spectroscopy to identify cancer in the margins of resected tissues and sentinel lymph nodes during breast cancer surgery, showing the potential of this technique for clinical applications. This article introduces and reviews the research on Raman spectroscopy for breast cancer surgery.

Application of Organic Petrology and Raman Spectroscopy in Thermal Maturity Determination of the Karoo Basin (RSA) Shale Samples

An assessment performed using raman spectroscopy has found space in the black shales of the Cisuralian-age rocks of the Karoo Basin in South Africa, particularly those from the Guadalupian Ripon, Cisuralian Whitehill and Prince Albert Formations. It is used in conjunction with geochemical screening techniques such as organic petrology and programmed pyrolysis. In turn, the combination of these techniques is used for the assessment of the thermal maturity of the sedimentary organic matter from the perspective of hydrocarbon generation, retention, and expulsion. To provide further understanding of the black shales in the Cisuralian-age rocks of the Karoo Basin in South Africa, this study focuses on the characterization of samples from the KWV−01 borehole drilled in the southeastern Karoo Basin. In addition, the USA Devonian/Carboniferous Berea Sandstone project samples were included for comparison, and were used as a quality assurance measure. Organic petrology was utilized to assess the organic quality and thermal maturity of the black shales. The results obtained showed that the Karoo Basin shales are overmature, containing an abundance of solid bitumen, and this often characterizes a shale reservoir with moveable hydrocarbons (shale gas). The programmed pyrolysis analysis conducted on the black shales of the Karoo Basin yielded artifact results, as they were determined from a very low and poorly defined S2 peak. This indicated the shales to be overmature and categorized them to be of poor hydrocarbon generation potential. Raman spectroscopy was used to gain insights about the molecular structure of the black shales and to assess if this technique could be used as a complimentary tool to determine the thermal maturity of the shale samples. Raman parameters such as G–D1 Band separation, G and D1 band full width at half maximum (Gfwhm and D1fwhm) and G band position were successfully correlated with vitrinite reflectance (RoV), demonstrating a good potential for Raman spectroscopy to predict the thermal maturity of the shales. Overall, the study provides valuable information and knowledge concerning black shale sample characterization (particularly the thermal maturity and molecular structural characterization) in the Karoo Basin, South Africa.

Application of Raman spectroscopy in relative blue ballpoint pen ink dating for forensic document analysis – a case report

In this case report, blue ballpoint ink on a questioned document was investigated using a newly developed Raman model devoted for dating of documents via writing inks. The majority of blue ballpoint pen inks contain crystal violet - a triarylmethane dye which displays a typical “molecular fingerprint” type of Raman spectrum, of which most intense peaks at 749 cm−1 and 1542 cm−1 (under 785 nm laser excitation) represents the least and the most stable bonds of crystal violet molecules, respectively. The ratios of peak intensities at above mentioned Raman shifts are utilized to estimate the relative dating of the questioned blue ballpoint pen ink in practice, results of which agreed with estimations using other traditional relative dating methods.
 ® 2023 Journal of Science and Technology - NTTU

Machine Learning Analysis of Raman Spectra To Quantify the Organic Constituents in Complex Organic-Mineral Mixtures.

Important decisions in local agricultural policy and practice often hinge on the soil's chemical composition. Raman spectroscopy offers a rapid noninvasive means to quantify the constituents of complex organic systems. But the application of Raman spectroscopy to soils presents a multifaceted challenge due to organic/mineral compositional complexity and spectral interference arising from overwhelming fluorescence. The present work compares methodologies with the capacity to help overcome common obstacles that arise in the analysis of soils. We created conditions representative of these challenges by combining varying proportions of six amino acids commonly found in soils with fluorescent bentonite clay and coarse mineral components. Referring to an extensive data set of Raman spectra, we compare the performance of the convolutional neural network (CNN) and partial least-squares regression (PLSR) multivariate models for amino acid composition. Strategies employing volume-averaged spectral sampling and data preprocessing algorithms improve the predictive power of these models. Our average test R2 for PLSR models exceeds 0.89 and approaches 0.98, depending on the complexity of the matrix, whereas CNN yields an R2 range from 0.91 to 0.97, demonstrating that classic PLSR and CNN perform comparably, except in cases where the signal-to-noise ratio of the organic component is very low, whereupon CNN models outperform. Artificially isolating two of the most prevalent obstacles in evaluating the Raman spectra of soils, we have characterized the effect of each obstacle on the performance of machine learning models in the absence of other complexities. These results highlight important considerations and modeling strategies necessary to improve the Raman analysis of organic compounds in complex mixtures in the presence of mineral spectral components and significant fluorescence.

Comparative study of Raman spectroscopy techniques in blood plasma-based clinical diagnostics: A demonstration on Alzheimer’s disease

Nowadays, there are still many diseases with limited or no reliable methods of early diagnosis. A popular approach in clinical diagnostic research is Raman spectroscopy, as a relatively simple, cost-effective, and high-throughput method for searching for disease-specific alterations in the composition of blood plasma. However, the high variability of the experimental designs, targeted diseases, or statistical processing in the individual studies makes it challenging to compare and compile the results to critically assess the applicability of Raman spectroscopy in real clinical practice. This study aimed to compare data from a single series of blood plasma samples of patients with Alzheimer’s disease and non-demented elderly controls obtained by four different techniques/experimental setups – Raman spectroscopy with excitation at 532 and 785 nm, Raman optical activity, and surface-enhanced Raman scattering spectroscopy. The obtained results showed that the spectra from each Raman spectroscopy technique contain different information about biomolecules of blood plasma or their conformation and may, therefore, offer diverse points of view on underlying biochemical processes of the disease. The classification models based on the datasets generated by the three non-chiroptical variants of Raman spectroscopy exhibited comparable diagnostic performance, all reaching an accuracy close to or equal to 80%. Raman optical activity achieved only 60% classification accuracy, suggesting its limited applicability in the specific case of Alzheimer’s disease diagnostics. The described differences in the outputs of the four utilized techniques/setups of Raman spectroscopy imply that their choice may crucially affect the acquired results and thus should be approached carefully concerning the specific purpose.

Super-Radiant SERS Enhancement by Plasmonic Particle Gratings.

Despite recent developments, surface-enhanced Raman spectroscopy (SERS) applications face challenges in achieving both high sensitivity and uniform Raman signals over a large area. Using the directional self-assembly of plasmonic nanoparticles in lattice structures, we show how one can increase the SERS signal 43-fold over randomly aligned gold nanoparticles without relying on the photoluminescence of Rhodamine 6G. For this study, we have chosen the lattice constant for an off-resonant case that matches the lattice resonance and super-radiant plasmon mode along the particle chain. Supported by electromagnetic simulations, we systematically analyze the radiative components of the plasmon modes by varying the particle size while keeping the lattice periodicity constant. We perform polarization-dependent SERS measurements and compare them with other standard SERS excitation wavelengths. Using the self-assembled plasmonic particle lattice, we have developed an effective SERS substrate that provides a significantly higher signal with 73% less surface coverage. This colloidal approach enables the cost-effective and scalable fabrication of highly sensitive, uniform, and polarization-dependent SERS substrates.