Reagentless blood analysis by near-infrared Raman spectroscopy

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 the published papers which could be retrieved from the available databases from the year 2007 to 2022 were incorporated.

Study of Two Constraints Impacting Measurements of Human Glycemia Using a Microwave Sensor

The measurement of glycemia is impacted by several constraints; those constraints have to be identified and quantified when designing an electromagnetic noninvasive sensor. The second phase concerns the level of the influence of these constraints. In this work, we investigated the impact of vein radius located in the forearm on a resonant microwave sensor to measure glycemia. We performed a numerical simulation using COMSOL Multiphysics of a proposed tissue model that was in contact with a microwave resonator. Some other factors affect the measurement, such as temperature, perfusion, sensor positioning and motion, tissue heterogeneity, and other biological activity. The sensor must be robust to the above-mentioned constraints. Because vein size changes from one person to another, the dielectric properties seen by the sensor will be different. This has been demonstrated by the change created in the resonance frequency of the simulated sensor for different vein sizes. The second constraint that was assessed is the dosimetry. The specific absorption rate (SAR) of any electromagnetic device should be evaluated and compared with SAR limits in the safety standards to ensure the safety of the user. Simulation results are in good agreement with SAR limits in the safety standards.

Multivariate Statistical Analysis of Surface Enhanced Raman Spectra of Human Serum for Alzheimer’s Disease Diagnosis

Alzheimer’s disease (AD) is the most common form of dementia worldwide and is characterized by progressive cognitive decline. Along with being incurable and lethal, AD is difficult to diagnose with high levels of accuracy. Blood serum from Alzheimer’s disease (AD) patients was analyzed by surface-enhanced Raman spectroscopy (SERS) coupled with multivariate statistical analysis. The obtained spectra were compared with spectra from healthy controls (HC) to develop a simple test for AD detection. Serum spectra from AD patients were further compared to spectra from patients with other neurodegenerative dementias (OD). Colloidal silver nanoparticles (AgNPs) were used as the SERS-active substrates. Classification experiments involving serum SERS spectra using artificial neural networks (ANNs) achieved a diagnostic sensitivity around 96% for differentiating AD samples from HC samples in a binary model and 98% for differentiating AD, HC, and OD samples in a tertiary model. The results from this proof-of-concept study demonstrate the great potential of SERS blood serum analysis to be developed further into a novel clinical assay for the effective and accurate diagnosis of AD.

Evaluation of accuracy dependence of Raman spectroscopic models on the ratio of calibration and validation points for non-invasive glucose sensing

Optical monitoring of blood glucose levels for non-invasive diagnosis is a growing area of research. Recent efforts in this direction have been inclined towards reducing the requirement of calibration framework. Here, we are presenting a systematic investigation on the influence of variation in the ratio of calibration and validation points on the prospective predictive accuracy of spectral models. A fiber-optic probe coupled Raman system has been employed for transcutaneous measurements. Limit of agreement analysis between serum and partial least square regression predicted spectroscopic glucose values has been performed for accurate comparison. Findings are suggestive of strong predictive accuracy of spectroscopic models without requiring substantive calibration measurements. Graphical abstract.

Raman spectroscopy of blood serum for Alzheimer's disease diagnostics: specificity relative to other types of dementia

The key moment for efficiently and accurately diagnosing dementia occurs during the early stages. This is particularly true for Alzheimer's disease (AD). In this proof-of-concept study, we applied near infrared (NIR) Raman microspectroscopy of blood serum together with advanced multivariate statistics for the selective identification of AD. We analyzed data from 20 AD patients, 18 patients with other neurodegenerative dementias (OD) and 10 healthy control (HC) subjects. NIR Raman microspectroscopy differentiated patients with more than 95% sensitivity and specificity. We demonstrated the high discriminative power of artificial neural network (ANN) classification models, thus revealing the high potential of this developed methodology for the differential diagnosis of AD. Raman spectroscopic, blood-based tests may aid clinical assessments for the effective and accurate differential diagnosis of AD, decrease the labor, time and cost of diagnosis, and be useful for screening patient populations for AD development and progression. Multivariate data analysis of blood serum Raman spectra allows for the differentiation between patients with Alzheimer's disease, other types of dementia and healthy individuals.

Investigation of Preeclampsia Using Raman Spectroscopy

Preeclampsia is associated with increased perinatal morbidity and mortality. There have been numerous efforts to determine preeclampsia biomarkers by means of biophysical, biochemical, and spectroscopic methods. In this study, the preeclampsia and control groups were compared via band component analysis and multivariate analysis using Raman spectroscopy as an alternative technique. The Raman spectra of serum samples were taken from nine preeclamptic, ten healthy pregnant women. The Band component analysis and principal component analysis-linear discriminant analysis were applied to all spectra after a sensitive preprocess step. Using linear discriminant analysis, it was found that Raman spectroscopy has a sensitivity of 78% and a specificity of 90% for the diagnosis of preeclampsia. Via the band component analysis, a significant difference in the spectra of preeclamptic patients was observed when compared to the control group. 19 Raman bands exhibited significant differences in intensity, while 11 of them decreased and eight of them increased. This difference seen in vibrational bands may be used in further studies to clarify the pathophysiology of preeclampsia.

Progress toward an in vivo surface-enhanced Raman spectroscopy glucose sensor

BACKGROUND

In this report, we detail our current work towards developing a surface-enhanced Raman spectroscopy (SERS) based sensor for in vivo glucose detection. Despite years of innovations in the development of blood glucose monitors, there remains a need for accurate continuous glucose sensors to provide care to rising numbers of diagnosed diabetes patients and mitigate secondary health complications associated with this metabolic disorder.

METHODS

SERS is a highly specific and sensitive optical technique suitable for direct detection of glucose. The SERS effect is highly distance dependent, thus the glucose molecules need to be within a few nanometers or adsorbed to an SERS-active surface. In our sensor, this is achieved with a self-assembled monolayer (SAM) that facilitates reversible interactions between glucose molecules and the surface. The amount of glucose near the surface is proportional to its concentration in the surrounding environment.

RESULTS

We determined that the SAM-functionalized surface is stable for at least 10 days and provides rapid, reversible partitioning. In vitro experiments in bovine plasma as well as in vivo experiments in rats demonstrated quantitative detection.

CONCLUSIONS

We show successful use of the SERS glucose sensor in rats, making it the first in vivo SERS sensor. Furthermore, we demonstrate free space transdermal detection of a SERS signal through the rat's skin as an initial step toward developing a transcutaneous sensor.

Non-contact detection of ciprofloxacin in a model anterior chamber using Raman spectroscopy

We examine the application of an improved noncontact and noninvasive Raman spectroscopic technique in measuring medicines at therapeutic concentrations in a model system mimicking the anterior chamber of the eye. A 90-deg laser Raman scattering geometry is employed to reduce the direct exposure of the basic cordial ocular tissues to the laser beam and increase the signal-to-noise ratio of the spectra. The technique is applied to a commercially available artificial anterior chamber (AAC) fitted with corneas of porcine eyes. Specific Raman signatures of ciprofloxacin (Ciproxin, a fluoroquinolone based antibiotic, have been resolved. Last, a partial least-squares (PLS) chemometric algorithm has been developed to predict the concentration of ciprofloxacin in AAC over the range from 0 to 1 mgmL with a correlation coefficient R(2)=98.4% and an RMS error of prediction equal to 41 microgmL.

Non-invasive detection of antibiotics and physiological substances in the aqueous humor by raman spectroscopy

BACKGROUND AND OBJECTIVES

Laser Raman spectroscopy is an inelastic light scattering technique able to characterize molecules in aqueous environments. The purpose of this work is to develop a non-contact and non-invasive spectroscopic method to identify and eventually quantify the presence of medicines (e.g., antibiotics) and physiological substances (e.g., glucose) in the aqueous humor of the eye.

STUDY DESIGN/MATERIALS AND METHODS

A new laser light delivery probe has been developed and adapted to a Raman spectroscopic system with the ability of favorable collection of the Raman light at 90 degrees scattering geometry while scanning the anterior chamber of the eye. Different amounts of ceftazidime, amphotericin B, and glucose had been injected in the aqueous humor of porcine eyes, maximum 24 hours after death and extraction, in-vitro. Raman measurements were excited with a visible (514.5 nm) laser beam at a power of 25 mW and an exposure/acquisition time of 1 second.

RESULTS

The specific collection optics and Raman analysis components used in the present work have resolved the Raman signatures of probed molecules and low concentrations of ceftazidime (0.9 mg/mL), amphotericin B (9 microg/mL), and glucose (2 mg/ml) separately injected in the anterior chamber of porcine eyes were detected in vitro.

CONCLUSION

This special illumination design gives the opportunity of avoiding the direct exposure to the laser light of basic cordial tissues of the eye, like lens and retina, although an optimum collection of scattered light is accomplished. Concentrations close to the minimum inhibitory concentration (MIC) have been detected for ceftazidime and amphotericin b; the detection of glucose has been realized at concentrations close to the early pathological levels of patients with diabetes.

In vitro long-term performance study of a near-infrared fluorescence affinity sensor for glucose monitoring

The long-term in vitro performance of a fluorescence affinity sensor for transdermal blood glucose monitoring was investigated. Affinity binding of fluorescently labeled concanavalin A (ConA) was used in this application, as previously described by Ballerstadt and Schultz [Anal. Chem. 17 (2000) 4185-4192). In this paper, the fluorescence emission of the sensor was extended to the near infrared (670 nm) using Alexa647 as the fluorochrome conjugated to concanavalin A. Sensors were alternately exposed to glucose solutions having concentrations of 2.5 and 20 mM with a dwell time of 3 h. The optical output of the sensors was monitored over a 4-month period. The sensors showed an initial increase in fluorescence over the first 3-4 weeks before gradually decreasing, with an approximately linear drop of 25% per month. In order to understand the reasons for the decrease in fluorescence output, further experiments were conducted, including time-dependent membrane leakage tests, solubility tests of ConA, temperature-dependent activity tests of ConA, and fluorescence photo-bleaching tests. From these results, it became evident that the decrease in fluorescence was not due to denaturation of the ConA. The most likely cause was leakage of the fluorescently labeled ConA through the interface between the outer sealant and the membrane. This problem is considered to be solvable and future publications will address this issue. Extrapolation of the experimental data suggests that a leak-proof sensor would be remarkably stable with a fluorescence decrease of only 15% over a 1-year period.

Non-invasive glucose measurement technologies: an update from 1999 to the dawn of the new millennium

There are three main issues in non-invasive (NI) glucose measurements: namely, specificity, compartmentalization of glucose values, and calibration. There has been progress in the use of near-infrared and mid-infrared spectroscopy. Recently new glucose measurement methods have been developed, exploiting the effect of glucose on erythrocyte scattering, new photoacoustic phenomenon, optical coherence tomography, thermo-optical studies on human skin, Raman spectroscopy studies, fluorescence measurements, and use of photonic crystals. In addition to optical methods, in vivo electrical impedance results have been reported. Some of these methods measure intrinsic properties of glucose; others deal with its effect on tissue or blood properties. Recent studies on skin from individuals with diabetes and its response to stimuli, skin thermo-optical response, peripheral blood flow, and red blood cell rheology in diabetes shed new light on physical and physiological changes resulting from the disease that can affect NI glucose measurements. There have been advances in understanding compartmentalization of glucose values by targeting certain regions of human tissue. Calibration of NI measurements and devices is still an open question. More studies are needed to understand the specific glucose signals and signals that are due to the effect of glucose on blood and tissue properties. These studies should be performed under normal physiological conditions and in the presence of other co-morbidities.

Prospects for in vivo Raman spectroscopy

Raman spectroscopy is a potentially important clinical tool for real-time diagnosis of disease and in situ evaluation of living tissue. The purpose of this article is to review the biological and physical basis of Raman spectroscopy of tissue, to assess the current status of the field and to explore future directions. The principles of Raman spectroscopy and the molecular level information it provides are explained. An overview of the evolution of Raman spectroscopic techniques in biology and medicine, from early investigations using visible laser excitation to present-day technology based on near-infrared laser excitation and charge-coupled device array detection, is presented. State-of-the-art Raman spectrometer systems for research laboratory and clinical settings are described. Modern methods of multivariate spectral analysis for extracting diagnostic, chemical and morphological information are reviewed. Several in-depth applications are presented to illustrate the methods of collecting, processing and analysing data, as well as the range of medical applications under study. Finally, the issues to be addressed in implementing Raman spectroscopy in various clinical applications, as well as some long-term directions for future study, are discussed.

Introduction to concepts in laser technology for glucose monitoring

Lasers are important tools in many diabetes-related applications, both diagnostic and therapeutic. Despite its wide range of uses, the laser derives all of its advantages over more conventional light sources from a few basic principles. A brief introduction to the fundamental properties of lasers emphasizes these points and suggests ways in which they can be exploited in experiments. Short descriptions of particular laser-based methods for monitoring glucose and related molecules provide introductions to research articles on these subjects.