Advancing Raman spectroscopy from research to clinic: Translational potential and challenges

Unveiling brain disorders using liquid biopsy and Raman spectroscopy

Brain disorders, including neurodegenerative diseases (NDs) and traumatic brain injury (TBI), present significant challenges in early diagnosis and intervention. Conventional imaging modalities, while valuable, lack the molecular specificity necessary for precise disease characterization. Compared to the study of conventional brain tissues, liquid biopsy, which focuses on blood, tear, saliva, and cerebrospinal fluid (CSF), also unveils a myriad of underlying molecular processes, providing abundant predictive clinical information. In addition, liquid biopsy is minimally- to non-invasive, and highly repeatable, offering the potential for continuous monitoring. Raman spectroscopy (RS), with its ability to provide rich molecular information and cost-effectiveness, holds great potential for transformative advancements in early detection and understanding the biochemical changes associated with NDs and TBI. Recent developments in Raman enhancement technologies and advanced data analysis methods have enhanced the applicability of RS in probing the intricate molecular signatures within biological fluids, offering new insights into disease pathology. This review explores the growing role of RS as a promising and emerging tool for disease diagnosis in brain disorders, particularly through the analysis of liquid biopsy. It discusses the current landscape and future prospects of RS in the diagnosis of brain disorders, highlighting its potential as a non-invasive and molecularly specific diagnostic tool.

Label-free plasmonic spectral profiling of serum DNA

Genetic and epigenetic modifications are linked to the activation of oncogenes and inactivation of tumor suppressor genes. Likewise, the associated molecular alternations can best inform precision medicine for personalized tumor treatment. Therefore, performing characterization of genetic and epigenetic alternations at the molecular level represents a crucial step in early diagnosis and/or therapeutics of cancer. However, the prevailing methods for DNA analysis involve a series of tedious and complicated steps, in which important genetic and epigenetic information could be lost or altered. To provide a potential approach for non-invasive, direct, and efficient DNA analysis, herein, we present a promising strategy for label-free molecular profiling of serum DNA in its pristine form by fusing surface-enhanced Raman spectroscopy with machine learning on a superior plasmonic nanostructured platform. Using DNA methylation and single-point mutation as two case studies, the presented strategy allows a well-balanced sensitive and specific detection of epigenetic and genetic changes at the single-nucleotide level in serum. We envision the presented label-free strategy could serve as a versatile tool for direct molecular profiling in pristine forms of a wide range of biological markers and aid biomedical diagnostics as well as therapeutics.

RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis

Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.

Advances in Bio-Optical Imaging Systems for Spatiotemporal Monitoring of Intestinal Bacteria

Vast and complex intestinal communities are regulated and balanced through interactions with their host organisms, and disruption of gut microbial balance can cause a variety of diseases. Studying the mechanisms of pathogenic intestinal flora in the host and early detection of bacterial translocation and colonization can guide clinical diagnosis, provide targeted treatments, and improve patient prognosis. The use of in vivo imaging techniques to track microorganisms in the intestine, and study structural and functional changes of both cells and proteins, may clarify the governing equilibrium between the flora and host. Despite the recent rapid development of in vivo imaging of intestinal microecology, determining the ideal methodology for clinical use remains a challenge. Advances in optics, computer technology, and molecular biology promise to expand the horizons of research and development, thereby providing exciting opportunities to study the spatio-temporal dynamics of gut microbiota and the origins of disease. Here, this study reviews the characteristics and problems associated with optical imaging techniques, including bioluminescence, conventional fluorescence, novel metabolic labeling methods, nanomaterials, intelligently activated imaging agents, and photoacoustic (PA) imaging. It hopes to provide a valuable theoretical basis for future bio-intelligent imaging of intestinal bacteria.

Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges

Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed.

A Smart Intracellular Self-Assembling Bioorthogonal Raman Active Nanoprobe for Targeted Tumor Imaging

Inspired by the principle of in situ self-assembly, the development of enzyme-activated molecular nanoprobes can have a profound impact on targeted tumor detection. However, despite their intrinsic promise, obtaining an optical readout of enzyme activity with high specificity in native milieu has proven to be challenging. Here, a fundamentally new class of Raman-active self-assembling bioorthogonal enzyme recognition (nanoSABER) probes for targeted tumor imaging is reported. This class of Raman probes presents narrow spectral bands reflecting their vibrational fingerprints and offers an attractive solution for optical imaging at different bio-organization levels. The optical beacon harnesses an enzyme-responsive peptide sequence, unique tumor-penetrating properties, and vibrational tags with stretching frequencies in the cell-silent Raman window. The design of nanoSABER is tailored and engineered to transform into a supramolecular structure exhibiting distinct vibrational signatures in presence of target enzyme, creating a direct causality between enzyme activity and Raman signal. Through the integration of substrate-specific for tumor-associated enzyme legumain, unique capabilities of nanoSABER for imaging enzyme activity at molecular, cellular, and tissue levels in combination with machine learning models are shown. These results demonstrate that the nanoSABER probe may serve as a versatile platform for Raman-based recognition of tumor aggressiveness, drug accumulation, and therapeutic response.

Strategies and Progress of Raman Technologies for Cellular Uptake Analysis of the Drug Delivery Systems

Nanoparticle (NP)-based drug delivery systems have the potential to significantly enhance the pharmacological and therapeutic properties of drugs. These systems enhance the bioavailability and biocompatibility of pharmaceutical agents via enabling targeted delivery to specific tissues or organs. However, the efficacy and safety of these systems are largely dependent on the cellular uptake and intracellular transport of NPs. Thus, it is crucial to monitor the intracellular behavior of NPs within a single cell. Yet, it is challenging due to the complexity and size of the cell. Recently, the development of the Raman instrumentation offers a versatile tool to allow noninvasive cellular measurements. The primary objective of this review is to highlight the most recent advancements in Raman techniques (spontaneous Raman scattering, bioorthogonal Raman scattering, coherence Raman scattering, and surface-enhanced Raman scattering) when it comes to assessing the internalization of NP-based drug delivery systems and their subsequent movement within cells.

Advance in Detection Technique of Lean Meat Powder Residues in Meat Using SERS: A Review

Food that contains lean meat powder (LMP) can cause human health issues, such as nausea, headaches, and even death for consumers. Traditional methods for detecting LMP residues in meat are often time-consuming and complex and lack sensitivity. This article provides a review of the research progress on the use of surface-enhanced Raman spectroscopy (SERS) technology for detecting residues of LMP in meat. The review also discusses several applications of SERS technology for detecting residues of LMP in meat, including the enhanced detection of LMP residues in meat based on single metal nanoparticles, combining metal nanoparticles with adsorbent materials, combining metal nanoparticles with immunizing and other chemicals, and combining the SERS technology with related techniques. As SERS technology continues to develop and improve, it is expected to become an even more widely used and effective tool for detecting residues of LMP in meat.

Evaluation of near-infrared Raman spectroscopy in the differentiation of cortical bone, trabecular bone, and Bio-Oss bone graft: an ex-vivo study

OBJECTIVE

We evaluated the ability of near-infrared Raman spectroscopy (near-IR RS) to differentiate among cortical bone, trabecular bone, and Bio-Oss, a bovinebone-based graft material.

STUDY DESIGN

We obtained a thinly sliced section of the mandible to collect cortical and trabecular bone samples and placed compacted Bio-Oss bone graft into a partially edentulous mandible in a dry human skull to obtain a comparable Bio-Oss sample. We performed near-IR RS of the 3 samples and evaluated the resultant Raman spectra to evaluate their differences.

RESULTS

We identified 3 sets of spectroscopic markers that differentiated Bio-Oss from human bone. The first consisted of significant shifts in the location of the 960 cm-1 phosphate (PO43-) peak and a reduction in its width, suggesting that Bio-Oss is more crystalline than bone. The second was the reduced carbonate content of Bio-Oss compared to bone, as determined from the 1070 cm-1/960 cm-1 peak area ratio. The final marker was the lack of collagen-associated peaks in Bio-Oss compared to cortical and trabecular bone.

CONCLUSIONS

Near-IR RS can reliably differentiate human cortical and trabecular bone from Bio-Oss via 3 sets of spectral markers associated with mineral crystallinity, carbonate content, and collagen content that differ significantly between them. Integrating this modality into dental practice may assist in implant treatment planning.

Nanotechnology-Assisted Biosensors for the Detection of Viral Nucleic Acids: An Overview

The accurate and rapid diagnosis of viral diseases has garnered increasing attention in the field of biosensors. The development of highly sensitive, selective, and accessible biosensors is crucial for early disease detection and preventing mortality. However, developing biosensors optimized for viral disease diagnosis has several limitations, including the accurate detection of mutations. For decades, nanotechnology has been applied in numerous biological fields such as biosensors, bioelectronics, and regenerative medicine. Nanotechnology offers a promising strategy to address the current limitations of conventional viral nucleic acid-based biosensors. The implementation of nanotechnologies, such as functional nanomaterials, nanoplatform-fabrication techniques, and surface nanoengineering, to biosensors has not only improved the performance of biosensors but has also expanded the range of sensing targets. Therefore, a deep understanding of the combination of nanotechnologies and biosensors is required to prepare for sanitary emergencies such as the recent COVID-19 pandemic. In this review, we provide interdisciplinary information on nanotechnology-assisted biosensors. First, representative nanotechnologies for biosensors are discussed, after which this review summarizes various nanotechnology-assisted viral nucleic acid biosensors. Therefore, we expect that this review will provide a valuable basis for the development of novel viral nucleic acid biosensors.

Correlative Fluorescence and Raman Microscopy to Define Mitotic Stages at the Single-Cell Level: Opportunities and Limitations in the AI Era

Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in understanding biology better. These methods are utilized for cell phenotyping and in-depth studies of cellular processes, such as mitosis. Fluorescence microscopy and optical spectroscopy techniques, including Raman micro-spectroscopy, allow researchers to examine biological samples at the single-cell level in a non-destructive manner. Fluorescence microscopy can give detailed morphological information about the localization of stained molecules, while Raman microscopy can produce label-free images at the subcellular level; thus, it can reveal the spatial distribution of molecular fingerprints, even in live samples. Accordingly, the combination of correlative fluorescence and Raman microscopy (CFRM) offers a unique approach for studying cellular stages at the single-cell level. However, subcellular spectral maps are complex and challenging to interpret. Artificial intelligence (AI) may serve as a valuable solution to characterize the molecular backgrounds of phenotypes and biological processes by finding the characteristic patterns in spectral maps. The major contributions of the manuscript are: (I) it gives a comprehensive review of the literature focusing on AI techniques in Raman-based cellular phenotyping; (II) via the presentation of a case study, a new neural network-based approach is described, and the opportunities and limitations of AI, specifically deep learning, are discussed regarding the analysis of Raman spectroscopy data to classify mitotic cellular stages based on their spectral maps.

Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications

Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.

Vibrational spectroscopy for decoding cancer microbiota interactions: Current evidence and future perspective

The role of human microbiota in cancer initiation and progression is recognized in recent years. In order to investigate the interactions between cancer cells and microbes, a systematic analysis using various emerging techniques is required. Owing to the label-free, non-invasive and molecular fingerprinting characteristics, vibrational spectroscopy is uniquely suited to decode and understand the relationship and interactions between cancer and the microbiota at the molecular level. In this review, we first provide a quick overview of the fundamentals of vibrational spectroscopic techniques, namely Raman and infrared spectroscopy. Next, we discuss the emerging evidence underscoring utilities of these spectroscopic techniques to study cancer or microbes separately, and share our perspective on how vibrational spectroscopy can be employed at the intersection of the two fields. Finally, we envision the potential opportunities in exploiting vibrational spectroscopy not only in basic cancer-microbiome research but also in its clinical translation, and discuss the challenges in the bench to bedside translation.

Biochemical changes of macrophages and U87MG cells occurring as a result of the exposure to iron oxide nanoparticles detected with the Raman microspectroscopy

The core size of iron oxide nanoparticles (IONPs) is a crucial factor defining not only their magnetic properties but also toxicological profile and biocompatibility. On the other hand, particular IONPs may induce different biological response depending on the dose, exposure time, but mainly depending on the examined system. New light on this problem may be shed by the information concerning biomolecular anomalies appearing in various cell lines in response to the action of IONPs with different core diameters and this was accomplished in the present study. Using Raman microscopy we studied the abnormalities in the accumulation of proteins, lipids and organic matter within the nucleus, cytoplasm and cellular membrane of macrophages, HEK293T and U87MG cell line occurring as a result of 24-hour long exposure to PEG-coated magnetite IONPs. The examined nanoparticles had 5, 10 and 30 nm cores and were administered in doses 5 and 25 μg Fe/ml. The obtained results showed significant anomalies in biochemical composition of macrophages and the U87MG cells, but not the HEK293T cells, occurring as a result of exposure to all of the examined nanoparticles. However, IONPs with 10 nm core diminished the accumulation of biomolecules in cells only when they were administered at a larger dose. The Raman spectra recorded for the macrophages subjected to 30 nm IONPs and for the U87MG cells exposed to 5 and 10 nm showed the presence of additional bands in the wavenumber range 1700-2400 cm^-1, probably resulting from the appearance of Fe adducts within cells. Our results indicate, moreover, that smaller IONPs may be effectively internalized into the U87MG cells, which points at their diagnostic/therapeutic potential in the case of glioblastoma multiforme.

Differentiation of glioblastoma tissues using spontaneous Raman scattering with dimensionality reduction and data classification

The neurosurgery of intracranial tumors is often complicated by the difficulty of distinguishing tumor center, infiltration area, and normal tissue. The current standard for intraoperative navigation is fluorescent diagnostics with a fluorescent agent. This approach can be further enhanced by measuring the Raman spectrum of the tissue, which would provide additional information on its composition even in the absence of fluorescence. However, for the Raman spectra to be immediately helpful for a neurosurgeon, they must be additionally processed. In this work, we analyzed the Raman spectra of human brain glioblastoma multiforme tissue samples obtained during the surgery and investigated several approaches to dimensionality reduction and data classificatin to distinguish different types of tissues. In our study two approaches to Raman spectra dimensionality reduction were approbated and as a result we formulated new technique combining both of them: feature filtering based on the selection of those shifts which correspond to the biochemical components providing the statistically significant differences between groups of examined tissues (center of glioblastoma multiforme, tissues from infiltration area and normally appeared white matter) and principal component analysis. We applied the support vector machine to classify tissues after dimensionality reduction of registered Raman spectra. The accuracy of the classification of malignant tissues (tumor edge and center) and normal ones using the principal component analysis alone was 83% with sensitivity of 96% and specificity of 44%. With a combined technique of dimensionality reduction we obtained 83% accuracy with 77% sensitivity and 92% specificity of tumor tissues classification.

Surface-enhanced Raman scattering: An emerging tool for sensing cellular function

Continuous long-term intracellular imaging and multiplexed monitoring of biomolecular changes associated with key cellular processes remains a challenge for the scientific community. Recently, surface-enhanced Raman scattering (SERS) has been demonstrated as a powerful spectroscopic tool in the field of biology owing to its significant advantages. Some of these include the ability to provide molecule-specific information with exquisite sensitivity, working with small volumes of precious samples, real-time monitoring, and optimal optical contrast. More importantly, the availability of a large number of novel Raman reporters with narrower full width at half maximum (FWHM) of spectral peaks/vibrational modes than conventional fluorophores has created a versatile palette of SERS-based probes that allow targeted multiplex sensing surpassing the detection sensitivity of even fluorescent probes. Due to its nondestructive nature, its applicability has been recognized for biological sensing, molecular imaging, and dynamic monitoring of complex intracellular processes. We critically discuss recent developments in this area with a focus on different applications where SERS has been used for obtaining information that remains elusive for conventional imaging methods. Current reports indicate that SERS has made significant inroads in the field of biology and has the potential to be used for in vivo human applications. This article is categorized under: Diagnostic Tools > In Vitro Nanoparticle-Based Sensing Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Diagnostic Tools > Biosensing Diagnostic Tools > In Vivo Nanodiagnostics and Imaging.

Electrospun fiber-based strategies for controlling early innate immune cell responses: Towards immunomodulatory mesh designs that facilitate robust tissue repair

Electrospun fibrous meshes are widely used for tissue repair due to their ability to guide a host of cell responses including phenotypic differentiation and tissue maturation. A critical factor determining the eventual biological outcomes of mesh-based regeneration strategies is the early innate immune response following implantation. The natural healing process involves a sequence of tightly regulated, temporally varying and delicately balanced pro-/anti-inflammatory events which together promote mesh integration with host tissue. Matrix designs that do not account for the immune milieu can result in dysregulation, chronic inflammation and fibrous capsule formation, thus obliterating potential therapeutic outcomes. In this review, we provide systematic insights into the effects of specific fiber/mesh properties and mechanical stimulation on the responses of early innate immune modulators viz., neutrophils, monocytes and macrophages. We identify matrix characteristics that promote anti-inflammatory immune phenotypes, and we correlate such responses with pro-regenerative in vivo outcomes. We also discuss recent advances in 3D fabrication technologies, bioactive functionalization approaches and biomimetic/bioinspired immunomodulatory mesh design strategies for tissue repair and wound healing. The mechanobiological insights and immunoregulatory strategies discussed herein can help improve the translational outcomes of fiber-based regeneration and may also be leveraged for intervention in degenerative diseases associated with dysfunctional immune responses. STATEMENT OF SIGNIFICANCE: The crucial role played by immune cells in promoting biomaterial-based tissue regeneration is being increasingly recognized. In this review focusing on the interactions of innate immune cells (primarily neutrophils, monocytes and macrophages) with electrospun fibrous meshes, we systematically elucidate the effects of the fiber microenvironment and mechanical stimulation on biological responses, and build upon these insights to inform the rational design of immunomodulatory meshes for effective tissue repair. We discuss state-of-the-art fabrication methods and mechanobiological advances that permit the orchestration of temporally controlled phenotypic switches in immune cells during different phases of healing. The design strategies discussed herein can also be leveraged to target several complex autoimmune and inflammatory diseases.

A Single-Cell Raman Spectroscopy Analysis of Bone Marrow Mesenchymal Stem/Stromal Cells to Identify Inter-Individual Diversity

The heterogeneity of stem cells represents the main challenge in regenerative medicine development. This issue is particularly pronounced when it comes to the use of primary mesenchymal stem/stromal cells (MSCs) due to a lack of identification markers. Considering the need for additional approaches in MSCs characterization, we applied Raman spectroscopy to investigate inter-individual differences between bone marrow MSCs (BM-MSCs). Based on standard biological tests, BM-MSCs of analyzed donors fulfill all conditions for their characterization, while no donor-related specifics were observed in terms of BM-MSCs morphology, phenotype, multilineage differentiation potential, colony-forming capacity, expression of pluripotency-associated markers or proliferative capacity. However, examination of BM-MSCs at a single-cell level by Raman spectroscopy revealed that despite similar biochemical background, fine differences in the Raman spectra of BM-MSCs of each donor can be detected. After extensive principal component analysis (PCA) of Raman spectra, our study revealed the possibility of this method to diversify BM-MSCs populations, whereby the grouping of cell populations was most prominent when cell populations were analyzed in pairs. These results indicate that Raman spectroscopy, as a label-free assay, could have a huge potential in understanding stem cell heterogeneity and sorting cell populations with a similar biochemical background that can be significant for the development of personalized therapy approaches.

Raman spectral analysis for rapid determination of zearalenone and alpha-zearalanol

Mycotoxins, including zearalenone, are important natural products produced by fungi that occasionally contaminate agricultural commodities and pose serious health risks to consumers of food and feed. Zearalenone and its metabolite, α-zearalanol, are of significant concern due to their estrogenic and anabolic steroid activity. Several governments have regulatory standards and advisory guidelines for zearalenone and α-zearalanol. Raman and ultraviolet spectroscopy were employed with density functional theory methods to evaluate spectroscopic properties to distinguish between zearalenone and α-zearalanol systematically. Raman bands were assigned based on vibrational frequency calculations. A portable Raman spectroscopy instrument (785 nm laser) distinguished between zearalenone and α-zearalanol in a label-free manner. Many vibrational bands of zearalenone and α-zearalanol are similar, including high-intensity peaks at 1315 cm^-1 and 1650 cm^-1. However, the intensities in the Raman spectra at 1465 cm^-1, 1495 cm^-1, and 1620 cm^-1 enabled the identification of zearalenone. The Raman peak at 1450 cm^-1 is associated with α-zearalanol. These vibrational bands serve as spectral indicators to differentiate between the structurally similar zearalenone and α-zearalanol.

Raman Spectroscopic Study of Amyloid Deposits in Gelatinous Drop-like Corneal Dystrophy

The genetic and histopathological features of the cornea of a Polish patient with Gelatinous Drop-like Corneal Dystrophy (GDCD) and the molecular composition with Raman spectroscopy of corneal deposits were examined. A 62 year-old Polish woman was diagnosed with GDCD and underwent penetrating corneal transplant. A blood sample was collected, and genetic analysis was performed. The cornea was processed for light microscopy and Raman analysis. The genetic exam revealed a previously undescribed homozygous 1-base pair deletion in exon 1 of TACSTD2 gene (c.185delT), resulting in a frame shift causing a premature stop codon. When compared with a control cornea, in GDCD cornea stained with PAS evident deposits were present over the anterior stroma, with apple green birefringence under polarized light. Raman spectroscopy showed peculiar differences between normal and GDCD cornea, consisting in peaks either of different height or undetectable in the normal cornea and related to amyloid. The possible causative role of the novel mutation was discussed and Raman spectroscopy as a further morphological tool in the evaluation of corneal dystrophies, characterized by the deposition of abnormal materials, was suggested.

Determination of Drugs in Clinical Trials: Current Status and Outlook

All pharmaceutical drugs, vaccines, cosmetic products, and many medical breakthroughs must first be approved through clinical research and trials before advancing to standard practice or entering the marketplace. Clinical trials are sets of tests that are required to determine the safety and efficacy of pharmaceutical compounds, drugs, and treatments. There is one pre-phase and four main clinical phase requirements that every drug must pass to obtain final approval. Analytical techniques play a unique role in clinical trials for measuring the concentrations of pharmaceutical compounds in biological matrices and monitoring the conditions of patients (or volunteers) during various clinical phases. This review focuses on recent analytical methods that are employed to determine the concentrations of drugs and medications in biological matrices, including whole blood, plasma, urine, and breast milk. Four primary analytical techniques (extraction, spectroscopy, chromatography, and electrochemical) are discussed, and their advantages and limitations are assessed. Subsequent to a survey of evidence and results, it is clear that microelectromechanical system (MEMS) based electrochemical sensor and biosensor technologies exhibit several notable advantages over other analytical methods, and their future prospects are discussed.

Advances in the Application of Exosomes Identification Using Surface-Enhanced Raman Spectroscopy for the Early Detection of Cancers

Exosomes are small nanoscale vesicles with a double-layered lipid membrane structure secreted by cells, and almost all types of cells can secrete exosomes. Exosomes carry a variety of biologically active contents such as nucleic acids and proteins, and play an important role not only in intercellular information exchange and signal transduction, but also in various pathophysiological processes in the human body. Surface-enhanced Raman Spectroscopy (SERS) uses light to interact with nanostructured materials such as gold and silver to produce a strong surface plasmon resonance effect, which can significantly enhance the Raman signal of molecules adsorbed on the surface of nanostructures to obtain a rich fingerprint of the sample itself or Raman probe molecules with ultra-sensitivity. The unique advantages of SERS, such as non-invasive and high sensitivity, good selectivity, fast analysis speed, and low water interference, make it a promising technology for life science and clinical testing applications. In this paper, we briefly introduce exosomes and the current main detection methods. We also describe the basic principles of SERS and the progress of the application of unlabeled and labeled SERS in exosome detection. This paper also summarizes the value of SERS-based exosome assays for early tumor diagnosis.

Raman Scattering-Based Biosensing: New Prospects and Opportunities

The growing interest in the development of new platforms for the application of Raman spectroscopy techniques in biosensor technologies is driven by the potential of these techniques in identifying chemical compounds, as well as structural and functional features of biomolecules. The effect of Raman scattering is a result of inelastic light scattering processes, which lead to the emission of scattered light with a different frequency associated with molecular vibrations of the identified molecule. Spontaneous Raman scattering is usually weak, resulting in complexities with the separation of weak inelastically scattered light and intense Rayleigh scattering. These limitations have led to the development of various techniques for enhancing Raman scattering, including resonance Raman spectroscopy (RRS) and nonlinear Raman spectroscopy (coherent anti-Stokes Raman spectroscopy and stimulated Raman spectroscopy). Furthermore, the discovery of the phenomenon of enhanced Raman scattering near metallic nanostructures gave impetus to the development of the surface-enhanced Raman spectroscopy (SERS) as well as its combination with resonance Raman spectroscopy and nonlinear Raman spectroscopic techniques. The combination of nonlinear and resonant optical effects with metal substrates or nanoparticles can be used to increase speed, spatial resolution, and signal amplification in Raman spectroscopy, making these techniques promising for the analysis and characterization of biological samples. This review provides the main provisions of the listed Raman techniques and the advantages and limitations present when applied to life sciences research. The recent advances in SERS and SERS-combined techniques are summarized, such as SERRS, SE-CARS, and SE-SRS for bioimaging and the biosensing of molecules, which form the basis for potential future applications of these techniques in biosensor technology. In addition, an overview is given of the main tools for success in the development of biosensors based on Raman spectroscopy techniques, which can be achieved by choosing one or a combination of the following approaches: (i) fabrication of a reproducible SERS substrate, (ii) synthesis of the SERS nanotag, and (iii) implementation of new platforms for on-site testing.

Translational biophotonics with Raman imaging: clinical applications and beyond

Clinical medicine continues to seek novel rapid non-invasive tools capable of providing greater insight into disease progression and management. Raman scattering based technologies constitute a set of tools under continuing development to address outstanding challenges spanning diagnostic medicine, surgical guidance, therapeutic monitoring, and histopathology. Here we review the mechanisms and clinical applications of Raman scattering, specifically focusing on high-speed imaging methods that can provide spatial context for translational biomedical applications.