Gold nanostars (GNS) have increasingly seen usage in photothermal treatment of diseases such as cancer. Owing to their flexible synthesis, GNS can be easily tuned to absorption wavelengths that bypass the absorption of non-target tissue. The particles can also be easily coupled with other sensing modalities such as molecular imaging using surface-enhanced Raman spectroscopy (SERS) and Immunotherapy in a synergistic manner. We have developed a combination treatment for cancer therapy called Synergistic Immuno Photo Nanotherapy (SYMPHONY) effectively uses photothermal heating as an adjunct treatment with immune check-point inhibitors. Here we develop several methods to simulate and analyze the optical and thermal effects of GNS absorption. In particular, the optimal conditions of GNS heating are investigated for understanding specific targeted therapy with limitations surrounding tissue absorption.
Plasmonic nanoparticles are used in many biomedical applications, ranging from sensing to in vivo imaging and photothermal transduction. The tunable morphology of nanostars including metallic composition, spike length, spike sharpness, and overall size greatly impacts their optical and plasmonic properties. Here, we highlight 3 distinct classes of nanostar-based particle groups where the effect of tuning these properties was investigated: improved gold nanostars (GNS), bimetallic nanostars (BNS), and caged nanostars (CNS). After characterization and simulation via FDTD modeling, particles were assessed for their utility in small-molecule detection, gene probe-based plasmonic sensing, in vivo tumor imaging and detection, and photothermal transduction.
MicroRNAs (miRNAs) are an emerging biotarget for clinical applications such as non-invasive detection of diseases such as cancer. However, current methods of miRNA quantification require tedious processing and amplification with highly trained specialists. Herein we show a simple and rapid colorimetric smartphone system that takes advantage of plasmonic nanoparticle-based assays to easily quantify miR-21 biomarker as a representative target for cancer disease detection. To achieve this, we use a unique assay known as Plasmonic Coupling Interference (PCI) to optically quantify the amount of biomarkers present. In addition, we utilize a specialized colorimetric processing method paired with accessible and cheap 3D printed parts to obviate the need for specialists to analyze and interpret the data. Our smart phone sensing system offers a practical miRNA diagnostic platform for the point-of-care applications as an alternative to more expensive lab-based methods.
MicroRNAs (miRNAs) have increasingly become an important biomarker target for applications ranging from clinical diagnostics to biofuel production monitoring. However, the current state of the art for the detection of such markers requires tedious processing and amplification techniques such as polymerase chain reaction (PCR). In an effort to create a relatively simple biosensing platform, we have developed a combined plasmonic biosensing method based on a Surface-Enhanced Raman Spectroscopy (SERS) platform called the inverse Molecular Sentinel (iMS) to directly detect in vivo miRNA such as miR858a. With Shifted Excitation Raman Difference Spectroscopy (SERDS), we can remotely detect these targets in the field in the presence of interfering background signal. The application of such technology can pave the way not just for biofuel monitoring but early and non-invasive disease detection and diagnostics.
In recent years, imaging systems have increasingly become more powerful and have allowed for better spatial resolution. Such systems, however, are limited to surface level interrogation of samples. Here we have developed a general optical technique referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID) as means of obtaining a multidimensional image containing information in the three spatial (X, Y, and Z) and spectral dimensions. Spatial offsets, obtained using selected binning of radially positioned pixels on the CCD, are coupled with stage and spectral scanning to collect a hyperdimensional data cube of the sample. We demonstrate this technique on gel phantoms containing target nanoparticles such as gold nanostars and quantum dots as way to demonstrate in-depth 3D imaging.
Plant biotechnology and biofuel research is critical in addressing increasing global demands for energy. Further understanding of biomass producing associated metabolic pathways in plants can be used to exploit and increase the production of biomass for energy purposes. In vivo detection of biomarkers associated with plant growth for bioenergy has proved to be limited due to complex sample preparation required by traditional methods. In addition, genetic transformation and biomolecule monitoring inside plant cells is regulated by diameter and size exclusion limits of the plant cell wall (5 - 20 nm). Currently limited methods exist for enabling direct entry into plant cells. Moreover, these methods, such as biolistic particle delivery and electroporation use mechanical force that causes damages to the plant tissue. Nanoparticles could serve as promising platforms for probes to characterize intercellular and intracellular plant biomarkers and pathways. Bi-metallic nanostars are a plasmonics-active nanoplatform capable of high surface-enhanced Raman scattering (SERS) which can enter plant cells and have the future potential for nucleic acid sensing. Imaging technologies such as SERS mapping, confocal imaging, X-ray fluorescence imaging, multi-photon imaging, and transmission electron microscopy have been utilized to determine the compartmentalization and location of the SERS iMS biosensors inside Arabidopsis plants.
Surface-enhanced Raman scattering (SERS) is emerging as an alternative non-invasive detection method in many applications. We recently show the use of SERS nanoprobes to detect tumors in vivo in mice, as well as the use of SERS sensors in vivo in plants for the detection of mIRNA. In spite of these advancements, the translation of SERS to real-world settings has been limited due to issues with observing Raman signal over complex background. For example, it remains challenging to observe SERS under sunlight or under strong illumination (e.g., operating room), using a conventional Raman setup. To this end, we combined a Raman setup with a newly developed dual-wavelength laser to perform shifted-excitation Raman difference spectroscopy (SERDS). Using SERDS, we demonstrate that the use of SERS sensors to detect miRNA in live plants inside a growth chamber, under full illumination. Additionally, we show that SERDS can be used to accurately identify tumors in mice, under ambient light. In both these applications, we demonstrate that the combination of SERS with SERDS improves the sensitivity and accuracy. This work will aid the translation of Raman and SERS to real-world settings.
The ability to monitor gene expression within living plants is of importance in many applications ranging from plant biology research to biofuel development; however, no method currently exists without requiring sample extraction. Herein, we report a multimodal imaging method based on plasmonic nanoprobes for in vivo imaging and biosensing of microRNA biotargets within whole plant leaves. This method integrates three different but complementary techniques: surfaceenhanced Raman scattering (SERS), X-ray fluorescence (XRF), and plasmonics-enhanced two-photon luminescence (TPL). The multimodal method utilizes plasmonic nanostars, which not only provide large Raman signal enhancement, but also allow for localization and quantification by XRF and plasmonics-enhanced TPL, owing to gold content and high two-photon luminescence cross-sections. For the sensing mechanism, inverse molecular sentinel (iMS) nanoprobes are used for SERS bioimaging of microRNA within Arabidopsis thaliana leaves to provide a dynamic SERS map of detected microRNA targets while also quantifying nanoprobe concentrations using XRF and TPL. This report lays the foundation for the use of plasmonic nanoprobes for in vivo functional imaging of nucleic acid biotargets in whole plants, a tool that will allow the study of these biotargets with previously unmet spatial and temporal resolution.
Early detection of molecular targets can greatly impact the clinical diagnosis and outcome of many diseases such as cancer. Methods utilizing optical detection systems and Surface-Enhanced Raman Scattering (SERS)-labeled nanoparticles provide a way of selectively targeting and obtaining signals unique to the target diseases as well as in-vivo applications for biomass and biofuel research with plants. However, these modalities are often limited to surface level detection due to attenuation from layers of highly scattering and absorbing tissue. In this work, we utilize surface-enhanced spatially offset Raman spectroscopy (SESORS) to probe through thick tissue to overcome this limitation. This modality combines high SERS signals generated by nanoparticles with a depth resolved detection technique called spatially offset Raman spectroscopy (SORS). We show the detection and recovery of SERS signal in layered systems comprising of optically mimicking gel as well as bone material.
While the use of nanomaterials in medical diagnostics has received increasing interest, in vivo detection of nanoparticles using optical techniques is still a challenge. Among other techniques, surface-enhanced Raman scattering (SERS)-labeled nanoparticles offer many potential applications in the field of disease diagnostics and biomedical monitoring, due to the advantages offered by SERS. We have previously developed a unique plasmonics-active nanoplatform, gold nanostars (GNS) for in vitro and in vivo multiplexed detection and diagnostics. To date conventional optical setups are typically limited in obtaining SERS signals at the sample surface, due to the strong attenuation caused by the highly scattering and absorbing tissue. Herein, we utilize spatially offset Raman spectroscopy (SORS) to overcome this depth limitation and obtain specific spectrochemical signatures of SERS-labeled nanoparticles, such as gold nanostars, beneath thick material and bone. In particular, we developed an optical setup for inverse spatially offset Raman spectroscopy to improve the robustness of the method developed. The efficacy of this method, referred to as inverse Surface-Enhanced Spatially Offset Raman Spectroscopy (SESORS) is demonstrated through the detection of layer-specific and subsurface SERS signals beneath different layers and substrates: (1) 4-mm tissue phantom, (2) 4-mm paraffin film, and (3) 5 mm bone of a macaque skull. Additionally, we show the possibility of recovering the pure SERS signal that belongs to a specific layer within a two-layer system using scaled subtraction. We will discuss the use of inverse SESORS in applications relevant to biomedical research.
Detection of surface-enhanced Raman scattering (SERS) tagged nanoparticles in-vivo is critical for its potential application in cancer diagnostics, inflammation monitoring, and glucose quantification. However, traditional optical methods are typically limited to surface level detection due to attenuation from layers of highly scattering and absorbing tissue. To break through this depth limitation, we utilize surface-enhanced spatially offset Raman spectroscopy (SESORS), a recent development for probing deep tissue that combines the high SERS signals generated by nanoparticles with a depth resolved detection technique called spatially offset Raman spectroscopy (SORS). We create a series of tissue phantoms that optically mimic tissue and embedded SERS tagged gold nanostars within them to demonstrate the ability of SESORS to distinguish signals from different layers by simply offsetting the excitation spot from the collection spot. We also show the ability to recover the subsurface SERS signal by a scaled subtraction between the spectra obtained at the 0 mm offset position and the spectra obtained at 10 mm offset position, demonstrating the ability of SESORS to isolate the subsurface SERS spectra of tagged nanoparticles.
An optically tunable, solid tissue phantom was developed in order to aid in the verification and validation of non-destructive cancer detection technologies based on fluorescence spectroscopy. The solid tissue phantom contained agarose, hemoglobin, Intralipid, NADH, and FAD. The redox ratio of the solid phantoms were shown to be tunable; thus, indicating that these phantoms could be used to tailor specific optical conditions that mimic cancerous and healthy tissues. Therefore, this solid tissue phantom can serve as a suitable test bed to evaluate fluorescence spectroscopy based cancer detection devices.
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