Handheld Raman System Research Articles

3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening

Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples, providing insights for disease diagnosis and finding of new biomarkers. Here, we introduce a label-free surface-enhanced Raman scattering sensor based on a three-dimensional plasmonic coral nanoarchitecture (3D-PCN), which has strong electromagnetic field enhancement through multiple hot spots. The 3D-PCN was synthesized on a paper substrate via direct one-step gold reduction, forming a coral-like nanoarchitecture with high absorption property for biofluids. This was fabricated as a urine test strip and then integrated with a handheld Raman system to develop an on-site urine diagnostic platform. The developed platform successfully classified the human prostate and pancreatic cancer urines in a label-free method supported by two types of deep learning networks, with high clinical sensitivity and specificity. Our technology has the potential to be utilized not only for urinary cancer diagnosis but also for various human biofluid sensing systems as a future point-of-care testing platform.

Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study human hepatic tissue samples, developing and validating a workflow for in vitro and intraoperative pathological diagnosis of liver cancer. We distinguish carcinoma tissues from adjacent non-tumour tissues in a rapid, non-disruptive, and label-free manner by using Raman spectroscopy combined with deep learning, which is validated by tissue metabolomics. This technique allows for detailed pathological identification of the cancer tissues, including subtype, differentiation grade, and tumour stage. 2D/3D Raman images of unprocessed human tissue slices with submicrometric resolution are also acquired based on visualization of molecular composition, which could assist in tumour boundary recognition and clinicopathologic diagnosis. Lastly, the potential for a portable handheld Raman system is illustrated during surgery for real-time intraoperative human liver cancer diagnosis.

Multivariate Analysis Aided Surface-Enhanced Raman Spectroscopy (MVA-SERS) Multiplex Quantitative Detection of Trace Fentanyl in Illicit Drug Mixtures Using a Handheld Raman Spectrometer.

Recently there has been upsurge in reports that illicit seizures of cocaine and heroin have been adulterated with fentanyl. Surface-enhanced Raman spectroscopy (SERS) provides a useful alternative to current screening procedures that permits detection of trace levels of fentanyl in mixtures. Samples are solubilized and allowed to interact with aggregated colloidal nanostars to produce a rapid and sensitive assay. In this study, we present the quantitative determination of fentanyl in heroin and cocaine using SERS, using a point-and-shoot handheld Raman system. Our protocol is optimized to detect pure fentanyl down to 0.20 ± 0.06 ng/mL and can also distinguish pure cocaine and heroin at ng/mL levels. Multiplex analysis of mixtures is enabled by combining SERS detection with principal component analysis and super partial least squares regression discriminate analysis (SPLS-DA), which allow for the determination of fentanyl as low as 0.05% in simulated seized heroin and 0.10% in simulated seized cocaine samples.

Rapid Authentication of Potato Chip Oil by Vibrational Spectroscopy Combined with Pattern Recognition Analysis.

The objective of this study was to develop a rapid technique to authenticate potato chip frying oils using vibrational spectroscopy signatures in combination with pattern recognition analysis. Potato chip samples (n = 118) were collected from local grocery stores, and the oil was extracted by a hydraulic press and characterized by fatty acid profile determined by gas chromatography equipped with a flame ionization detector (GC-FID). Spectral data was collected by a handheld Raman system (1064 nm) and a miniature near-infrared (NIR) sensor, further being analyzed by SIMCA (Soft Independent Model of Class Analogies) and PLSR (Partial Least Square Regression) to develop classification algorithms and predict the fatty acid profile. Supervised classification by SIMCA predicted the samples with a 100% sensitivity based on the validation data. The PLSR showed a strong correlation (Rval > 0.97) and a low standard error of prediction (SEP = 1.08–3.55%) for palmitic acid, oleic acid, and linoleic acid. 11% of potato chips (n = 13) indicated a single oil in the label with a mislabeling problem. Our data supported that the new generation of portable vibrational spectroscopy devices provided an effective tool for rapid in-situ identification of oil type of potato chips in the market and for surveillance of accurate labeling of the products.

Aptamer-based surface-enhanced resonance Raman scattering assay on a paper fluidic platform for detection of cardiac troponin I.

.Significance: Cardiac troponin I (cTnI) is a primary biomarker for diagnosis of myocardial infarction (MI). In contrast to central laboratory tests for cTnI, point-of-care (POC) testing has the advantage of providing results when the patient is first encountered, which helps high-risk patients to be treated more rapidly and low-risk patients to be released in a timely fashion. A paper fluidic platform is good for POC testing because the paper is abundant, low cost, and disposable. However, current cTnI assays on paper platforms use antibodies as the recognition element, which has limitations due to the high cost of production and antibody stability issues at the POC.Aim: To develop an aptamer-based assay on a paper strip using surface-enhanced resonance Raman spectroscopy (SERRS) for detection of cTnI in the clinically relevant range at the POC.Approach: Gold nanoparticles (AuNPs) were functionalized with a Raman reporter molecule, malachite green isothiocyanate. The functionalized AuNPs were encapsulated in a silica shell and provided a SERRS signal using a handheld Raman system with a 638-nm excitation wavelength. A primary aptamer and a secondary aptamer of cTnI were used in a sandwich assay format to bind the cTnI on a test line of a paper fluidic platform. By measuring the SERRS signal from the test line, the concentration of cTnI was quantitatively determined.Results: The aptamer-based SERRS assay on a paper strip had a detection range of 0.016 to for cTnI, had good selectivity for cTnI compared to three other markers, had good stability over 10 days, and had good performance in the more complex serum sample matrix.Conclusions: The aptamer-based SERRS assay on a paper strip has the potential to provide a sensitive, selective, stable, repeatable, and cost-effective platform for the detection of cTnI toward eventual use in diagnosis of MI at the POC.

Authentication of commercial honeys based on Raman fingerprinting and pattern recognition analysis

Our aim was to develop a rapid non-targeted approach to authenticate commercial honey combining Raman spectroscopy and pattern recognition analysis. Honey samples (n = 97) were collected from local and global grocery stores and online vendors. Spectra were collected by handheld and compact benchtop Raman systems equipped with a 1064 nm excitation laser and analyzed by pattern recognition techniques (Soft Independent Model of Class Analogies, SIMCA) to develop classification algorithms. High-performance liquid chromatography (HPLC-RI, AOAC#977.20) was used to verify the authenticity of honeys. Both Raman systems formed distinct SIMCA clusters for the samples associated with their unique sugar profile. Evaluation of store-bought commercial samples indicated adulteration in 16 samples (17%); all samples predicted by the Raman algorithms as non-authentic were confirmed by HPLC-RI. Raman technology provides analytical features for ingredient verification, offering the industry and regulatory agencies valuable resources to ensure accurate labeling of honey products.

Rapid and noninvasive diagnostics of Huanglongbing and nutrient deficits on citrus trees with a handheld Raman spectrometer.

Huanglongbing (HLB) or citrus greening is a devastating disease of citrus trees that is caused by the gram-negative Candidatus Liberibacter spp. bacteria. The bacteria are phloem limited and transmitted by the Asian citrus psyllid, Diaphorina citri, and the African citrus psyllid, Trioza erytreae, which allows for a wider dissemination of HLB. Infected trees exhibit yellowing of leaves, premature leaf and fruit drop, and ultimately the death of the entire plant. Polymerase chain reaction (PCR) and antibody-based assays (ELISA and/or immunoblot) are commonly used methods for HLB diagnostics. However, they are costly, time-consuming, and destructive to the sample and often not sensitive enough to detect the pathogen very early in the infection stage. Raman spectroscopy (RS) is a noninvasive, nondestructive, analytical technique which provides insight into the chemical structures of a specimen. In this study,by using a handheld Raman system in combination with chemometric analyses, we can readily distinguish between healthy and HLB (early and late stage)-infected citrus trees, as well as plants suffering from nutrient deficits. The detection rate of Raman-based diagnostics of healthy vs HLB infected vs nutrient deficit is ~ 98% for grapefruit and ~ 87% for orange trees, whereas the accuracy of early- vs late-stage HLB infected is 100% for grapefruits and ~94% for oranges. This analysis is portable and sample agnostic, suggesting that it could be utilized for other crops and conducted autonomously. Graphical abstract.

SERS based monitoring of toluene vapors at ambient and elevated temperatures by using a ruffled silver nanolayer as a substrate.

The authors describe a Surface enhanced Raman spectroscopy (SERS)-based method for the detection of gaseous toluene at different temperature regimes using 3D ruffled silver SERS substrates and a commercially available handheld Raman system equipped with a785nm laser. The 3D silver SERS substrates were synthesized via electroless deposition of silver on the ruffled sandpaper and HF-etched silicon wafers. The morphological characterization of the silver SERS substrates was carried out by atomic force microscopy and scanning electron microscopy. UV-Vis spectroscopy absorption spectra of the silver nanostructures showed plasmonicpeaks at 522nm and 731nm. Toluene vapors were collected with asyringe at ambient temperature and at 100°C, while SERS detection was always performed at room temperature. Toluene detection was based on the measurement of the Raman bands at 787cm-1 and 1003cm-1 (in thefingerprint region). The method allow gaseous toluene to be detected at its vapor concentrations of 522ppm (mg/L), 261ppm (mg/L) and 26ppm (mg/L). Graphical abstract Schematic presentation of an original method for the detection of toluene vapors by SERS technique. The collection of toluene vapors was carried out at room and at high temperatures. The vapors were transferred to methanol by bubbling. The SERS measurements were carried out at room temperature.

Development of a miRNA surface-enhanced Raman scattering assay using benchtop and handheld Raman systems.

DNA-functionalized nanoparticles, when paired with surface-enhanced Raman spectroscopy (SERS), can rapidly detect microRNA. However, widespread use of this approach is hindered by drawbacks associated with large and expensive benchtop Raman microscopes. MicroRNA-17 (miRNA-17) has emerged as a potential epigenetic indicator of preeclampsia, a condition that occurs during pregnancy. Biomarker detection using an SERS point-of-care device could enable prompt diagnosis and prevention as early as the first trimester. Recently, strides have been made in developing portable Raman systems for field applications. An SERS assay for miRNA-17 was assessed and translated from traditional benchtop Raman microscopes to a handheld system. Three different photoactive molecules were compared as potential Raman reporter molecules: a chromophore, malachite green isothiocyanate (MGITC), a fluorophore, tetramethylrhodamine isothiocyanate, and a polarizable small molecule 5,5-dithio-bis-(2-nitrobenzoic acid) (DTNB). For the benchtop Raman microscope, the DTNB-labeled assay yielded the greatest sensitivity under 532-nm laser excitation, but the MGITC-labeled assay prevailed at 785nm. Conversely, DTNB was preferable for the miniaturized 785-nm Raman system. This comparison showed significant SERS enhancement variation in response to 1-nM miRNA-17, implying that the sensitivity of the assay may be more heavily dependent on the excitation wavelength, instrumentation, and Raman reporter chosen than on the plasmonic coupling from DNA/miRNA-mediated nanoparticle assemblies.

Handheld dual-wavelength Raman instrument for the detection of chemical agents and explosives

Handheld Raman systems have become powerful analytical tools for the detection and identification of hazardous chemical materials that are now commonly used by both the civilian and military communities. Due to the availability of compact lasers and sensitive detectors, systems typically operate at 785 nm. However, the Raman return at this wavelength can still be obscured by fluorescent impurities in the targeted materials or their matrices. To potentially mitigate this shortcoming, a prototype dual-wavelength Raman incorporating both 785- and 1064-nm excitations was developed and assessed at the Edgewood Chemical Biological Center. The results of that evaluation are discussed here.

Detection of pigments of halophilic endoliths from gypsum: Raman portable instrument and European Space Agency's prototype analysis.

A prototype instrument, under development at the University of Leicester, for the future European Space Agency (ESA) ExoMars mission, was used for the analysis of microbial pigments within a stratified gypsum crust from a hypersaline saltern evaporation pond at Eilat (Israel). Additionally, the same samples were analysed using a miniaturized Raman spectrometer, featuring the same 532 nm excitation. The differences in the position of the specific bands, attributed to carotenoid pigments from different coloured layers, were minor when analysed by the ESA prototype instrument; therefore, making it difficult to distinguish among the different pigments. The portable Delta Nu Advantage instrument allowed for the discrimination of microbial carotenoids from the orange/green and purple layers. The purpose of this study was to complement previous laboratory results with new data and experience with portable or handheld Raman systems, even with a dedicated prototype Raman system for the exploration of Mars. The latter is equipped with an excitation wavelength falling within the carotenoid polyene resonance region. The ESA prototype Raman instrument detected the carotenoid pigments (biomarkers) with ease, although further detailed distinctions among them were not achieved.

Innovative Raman Sampling

AbstractConventional portable and handheld Raman systems are based on a dispersive design. The drawback of this design is the tradeoff between laser spot size and resolution. Most conventional instruments have a very small laser spot size. This tightly focused beam produces high resolution but may miss the target material completely. Increasing the sampling area using a large beam requires a larger aperture and consequently, a corresponding loss of resolution, making accurate library matching difficult and prone to error.

Detection and differentiation of foodborne pathogenic bacteria in mung bean sprouts using field deployable label-free SERS devices

Vancomycin functionalized silver nanorod arrays substrates were used to obtain the surface enhanced Raman scattering (SERS) signals of six foodborne pathogenic bacteria in mung bean sprouts samples using both a portable and a handheld Raman system. The silver nanorod arrays substrates were optimized to facilitate quantitative, rapid, and sensitive detection of Salmonella enterica serotype Anatum, Salmonella enterica serotype Cubana, Salmonella enterica serotype Stanley, Salmonella enteritidis, Escherichia coli O157:H7, and Staphylococcus epidermidis. Substrate optimization was achieved by varying the nanorod length and vancomycin incubation concentration. By combining these substrates with a two-step filtration process we found that the foodborne pathogenic bacteria used in this study can be identified in mung bean sprouts with a limit of detection as low as 100 CFU ml(-1) in less than 4 h using both portable and handheld Raman systems. The results show that SERS spectra can be used to differentiate between bacterial species and serotypes when chemometric methods are employed. The low detection limit and rapid detection time of this biosensing platform for foodborne pathogenic bacteria could be a valuable field detection method for the fresh produce and food processing industries.

Preliminary investigation on the relationship of Raman spectra of sheep meat with shear force and cooking loss

A prototype handheld Raman system was used as a rapid non-invasive optical device to measure raw sheep meat to estimate cooked meat tenderness and cooking loss. Raman measurements were conducted on m. longissimus thoracis et lumborum samples from two sheep flocks from two different origins which had been aged for five days at 3–4°C before deep freezing and further analysis. The Raman data of 140 samples were correlated with shear force and cooking loss data using PLS regression. Both sample origins could be discriminated and separate correlation models yielded better correlations than the joint correlation model. For shear force, R2=0.79 and R2=0.86 were obtained for the two sites. Results for cooking loss were comparable: separate models yielded R2=0.79 and R2=0.83 for the two sites. The results show the potential usefulness of Raman spectra which can be recorded during meat processing for the prediction of quality traits such as tenderness and cooking loss.