Tomographic Imaging and Localization of Nanoparticles in Tissue Using Surface-Enhanced Spatially Offset Raman Spectroscopy

In Situ Imaging of Subcutaneous Drug Delivery Systems Using Microspatially Offset Low-Frequency Raman Spectroscopy

The noninvasive in situ monitoring of the status of drug retention and implant integrity of subcutaneous implants would allow optimization of therapy and avoid periods of subtherapeutic delivery kinetics. A proof-of principle study was conducted to determine the use of microspatially offset low-frequency Raman spectroscopy (micro-SOLFRS) for nonintrusive in situ analysis of subcutaneous drug delivery systems. Caffeine was used as the model drug, and it was embedded in a circular-shape Soluplus matrix via vacuum compression molding. For the exploratory analysis, prototype implants were positioned underneath skin tissue samples, and various caffeine concentrations (1-50% w/w) and micro-SOLFRS displacement settings (Δz = 0-8 mm) were tested from the pseudo three-dimensional (3D)-imaging perspective. This format allowed the optimization of real-time micro-SOLFRS analysis of implants through skin tissue that was embedded in an agarose hydrogel. Notably, this analytical approach allowed the temporal and spatial erosion of the implant and solid-state transformations of caffeine to be distinguished. The spectrometric results correlated with complementary high-performance liquid chromatography (HPLC) determination of changes in drug concentration, illustrating drug dissipation/diffusion characteristics. The discovered capability of micro-SOLFRS for in situ measurements of drugs and implants makes it attractive for biomedical diagnostics that, ultimately, could result in development of a new point-of-care technology.

Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects

Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer's and Parkinson's diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.

Plasmonic and Photothermal Properties of Silica-Capped Gold Nanoparticle Aggregates

Owing to their biocompatibility, gold nanoparticles have many applications in healthcare, notably for targeted drug delivery and the photothermal therapy of tumors. The addition of a silica shell to the nanoparticles can help to minimize the aggregation of the nanoparticles upon exposure to harsh environments and protect any Raman reporters adsorbed onto the metal surface. Here, we report the effects of the addition of a silica shell on the photothermal properties of a series of gold nanostructures, including gold nanoparticle aggregates. The presence of a Raman reporter at the surface of the gold nanoparticles also allows the structures to be evaluated by surface-enhanced Raman scattering (SERS). In this work, we explore the relationship between the degree of aggregation and the position and the extinction of the near-infrared plasmon on the observed SERS intensity and in the increase in bulk temperature upon near-infrared excitation. By tailoring the concentration of the silane and the thickness of the silica shell, it is possible to improve the photothermal heating capabilities of the structures without sacrificing the SERS intensity or changing the optical properties of the gold nanoparticle aggregates.

Guided principal component analysis (GPCA): a simple method for improving detection of a known analyte

There is increasing interest in the application of Raman spectroscopy in a medical setting, ranging from supporting real-time clinical decisions e.g. surgical margins to assisting pathologists with disease classification. However, there remain a number of barriers for adoption in the medical setting due to the increased complexity of probing highly heterogeneous, dynamic biological materials. This inherent challenge can also limit the deployment of higher level analytical approaches such as Artificial Intelligence (AI) including convolutional neural networks (CNN), as there is a lack of a ground truth required for training purposes i.e. in complex clinical samples. Principal component analysis (PCA) is an unsupervised data reduction approach (orthogonal linear transformation) that has been used extensively in spectroscopy for 30+ years, due to its capability to simplify analysis of complex spectroscopic data. However, due to PCA being unsupervised features will inherently appear mixed and their rank may vary between experiments. Here we propose Guided PCA (GPCA), a simple approach that allows PCA to be guided with spectral data to ensure a consistent rank of a key target moiety by the inclusion of a reference (guiding) spectrum to the data set. This simplifies analysis, increases robustness of PCA analysis and improves quantification and the limits of detection and decreases RMSE.

Locating Three-Dimensional Position of Deep-Seated SERS Phantom Lesions in Thick Tissues Using Tomographic Transmission Raman Spectroscopy

Locating distinct objects within a thick scattering medium remains a long-standing challenge in the fields of materials science, health, and engineering. Transmission Raman spectroscopy (TRS) with the use of surface-enhanced Raman scattering (SERS) nanoparticles has proven to be an effective approach to detect deep-seated lesions inside thick biological tissues. However, it has not yet been proven to spatially locate deep lesions in three dimensions using optical modalities. Herein, we present the concept of tomographic TRS and report its successful use for accurately locating SERS nanoparticles in elongated rod-like thick tissues. Our work starts with theoretical simulations of Raman photon propagation in tissues. We discovered a linear relationship between the Raman spectral peak ratio and propagation distance of Raman photons in tissues, allowing us to predict the location of lesions tagged by SERS NPs. Based on this, we propose a two-step tomographic TRS strategy, which includes axial scanning and ring scanning. We demonstrate the robustness of our approach using ex vivo thick tissue (4.5 cm in thickness) and locate an embedded SERS phantom lesion, with a ring scanning step of 10-30°. We successfully locate multiple SERS phantom lesions in the ex vivo porcine muscle stack with high accuracy (absolute error of <2 mm). Our method is rapid, efficient, and of low cost compared to current tomographic medical imaging techniques. This work advances Raman techniques for three-dimensional positioning and offers new insights toward practical diagnosis applications.

A review on current progress of Raman-based techniques in food safety: From normal Raman spectroscopy to SESORS

Frequently occurrence of food safety incidents has induced global concern over food safety. To ensure food quality and safety, an increasing number of rapid and sensitive analytical methods have been developed for analysis of all kinds of food composition and contaminants. As one of the high-profile analytical techniques, Raman spectroscopy has been widely applied in food analysis with simple, rapid, sensitive, and nondestructive detection performance. Research on Raman techniques is a direction of great interest to many fields, especially in food safety. Hence, it is crucial to gain insight into recent advances on the use of Raman-based techniques in food safety applications. In this review, we introduce Raman techniques from normal Raman spectroscopy to developed ones (e.g., surface enhanced Raman scattering (SERS), spatially offset Raman spectroscopy (SORS), surface-enhanced spatially offset Raman spectroscopy (SESORS)), in view of their history and development, principles, design, and applications. In addition, future challenges and trends of these techniques are discussed regarding to food safety.

In Vivo Surface-Enhanced Transmission Raman Spectroscopy under Maximum Permissible Exposure: Toward Photosafe Detection of Deep-Seated Tumors

The detection of deep-seated lesions is of great significance for biomedical applications. However, due to the strong photon absorption and scattering of biological tissues, it is challenging to realize in vivo deep optical detections, particularly for those using the safe laser irradiance below clinical maximum permissible exposure (MPE). In this work, the combination of ultra-bright surface-enhanced Raman scattering (SERS) nanotags and transmission Raman spectroscopy (TRS) is reported to achieve the non-invasive and photosafe detection of "phantom" lesions deeply hidden in biological tissues, under the guidance of theoretical calculations showing the importance of SERS nanotags' brightness and the expansion of laser beam size. Using a home-built TRS system with a laser power density of 0.264 W cm^-2 (below the MPE criteria), we successfully demonstrated the detection of SERS nanotags through up to 14-cm-thick ex vivo porcine tissues, as well as in vivo imaging of "phantom" lesions labeled by SERS nanotags in a 1.5-cm-thick unshaved mouse under MPE. This work highlights the potential of transmission Raman-guided identification and non-invasive imaging toward clinically photosafe cancer diagnoses.