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Optical molecular imaging has burgeoned into a major field within biomedicine, and technologies that incorporate surface plasmon resonance effects have become a major focus within this field. Plasmon resonance has been defined as the collective oscillation of the conduction band electrons in certain metals (such as gold) in response to an electric field, such as an impinging wave of light. We show that elastic light scattering due to the plasmon resonance of nanometer-sized gold particles makes them powerful tools for optical imaging of epidermal growth factor receptor (EGFR) expression -- a major biomarker for carcinogenesis. Optical technologies in general are poised as cheap, flexible ways to aid in diagnosis and treatment of disease. In addition to supplying a bright, stable optical scattering signal and a convenient conjugation platform for targeting molecules, these materials display a unique behavior termed "plasmon coupling". This term refers to the dramatic optical property changes brought about by the presence of other nearby nanoparticles. These changes include a dramatic red-shifting in their peak plasmon resonance wavelength, as well as a non-linear, per-particle increase in the overall scattered power. We show that such conditions exist in cells and are primarily due to intricate protein trafficking mechanisms as part of the EGFR life-cycle. The observed variations in plasmon coupling can give clues as to the nanoscale organization of these important proteins. In addition, the resulting optical property changes result in a large, molecular-specific contrast enhancement due to the shifting of the resonance closer to the near infrared region, where biological tissues tend to be most transparent. Despite this enhancement, however, many tissues contain large endogenous signals, as well as barriers to delivery of both light and the nanoparticles. As such, we also show an example of a multifaceted approach for further increasing the apparent molecular-specific optical signals in imaging of EGFR expression by using an oscillating magnetic field. This serves to encode the signal from magnetically susceptible plasmonic nanoparticles, making their extraction from the background possible. Overall, the studies presented in this dissertation should serve to stimulate further investigations into a wide variety of technologies, techniques, and applications.

In 2012, more than 1.6 million new cases of breast cancer were diagnosed and about half a million women died of breast cancer. The incidence has increased in the developing world. The mortality, however, has decreased. This is thought to partly be the result of advances in diagnosis and treatment. Studying tissue samples from biopsies through a microscope is an important part of diagnosing breast cancer. Recent techniques include camera-equipped microscopes and whole slide scanning systems that allow for digital high-throughput scanning of tissue samples. The introduction of digital pathology has simplified parts of the analysis, but manual interpretation of tissue slides is still labor intensive and costly, and involves the risk for human errors and inconsistency. Digital image analysis has been proposed as an alternative approach that can assist the pathologist in making an accurate diagnosis by providing additional automatic, fast and reproducible analyses. This thesis addresses the automation of conventional analyses of tissue, stained for biomarkers specific for the diagnosis of breast cancer, with the purpose of complementing the role of the pathologist. In order to quantify biomarker expression, extraction and classification of sub-cellular structures are needed. This thesis presents a method that allows for robust and fast segmentation of cell nuclei meeting the need for methods that are accurate despite large biological variations and variations in staining. The method is inspired by sparse coding and is based on dictionaries of local image patches. It is implemented in a tool for quantifying biomarker expression of various sub-cellular structures in whole slide images. Also presented are two methods for classifying the sub-cellular localization of staining patterns, in an attempt to automate the validation of antibody specificity, an important task within the process of antibody generation.  In addition, this thesis explores methods for evaluation of multimodal data. Algorithms for registering consecutive tissue sections stained for different biomarkers are evaluated, both in terms of registration accuracy and deformation of local structures. A novel region-growing segmentation method for multimodal data is also presented. In conclusion, this thesis presents computerized image analysis methods and tools of potential value for digital pathology applications.

Thesis (Ph. D.)--Biomedical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Nie, Shuming; Committee Member: Parkos, Charles; Committee Member: Petros, John; Committee Member: Voit, Eberhard; Committee Member: Zhu, Cheng. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Submitted in fulfillment of the requirements of the Degree in Chemistry, Durban University of Technology, 2017. / High prevalence and mortality cases of prostate cancer (PCa) have increased around the world, particularly in developing countries. Several forthcoming factors have been revealed nowadays, one of them is due to the incapability of the diagnostic methods to produce reliable results, which impacts negatively on cancer-treatment. However, a sensitive diagnosis of PCa cells remains a challenge in the field of biosensors. Emerging whole-cell detection as biosensing targets has opened up avenues for successful cancer diagnostics, due to high selectivity among other cells. A switchable and flexible surface-based graphene material is one of the techniques that revolutionized smart biodevice platforms in biosensor technology. In this present study, a covalently linked poly-(N-isopropylacrylamide) (PNIPAM) to graphene oxide surface has been employed as “on/off”-switchable aptamer-based sensor for the detection of PC3 whole-cancer cell. The constructed surface has benefitted from PNIPAM, as the thermal-stimulus agent, which allows the coil-to-globule transitions by triggering temperature changes. When the system is above its lower critical solution temperature (LCST) of 32oC, PNIPAM will exist as hydrophobic -globular state providing an “on” binding region for the whole-cell, reaching the interactions on the biosurface. The “off” binding systems is only possibly when the PNIPAM turns into extended-state by lowering its temperature below LCST. The first principle studies have successfully characterized the electronic behavior with particular emphasis of PNIPAM monomer functions along with the description of the structural energetics of complex through density functional theory (DFT). Docking studies have further been performed to predict a plausible binding aptamer toward the protein-representative PCa cell. To better understand the prospect of an aptamer-based tunable biosensor, molecular dynamics (MD) highlighted the behavior of PNIPAM-grafted GO in exhibiting a globular and extended conformations at above and below LCST, permitting the biomolecules to interact with each other as well as to avoid interactions, respectively. Experimental studies have been included to validate the theoretical predictions by fabricating real-biosensor systems using electrochemical impedance technique, resulting a low-detection limit down to 14 cells/mL. Engagement between theoretical and experimental studies delivered an enhanced tunable-biosensor performance for the detection of whole cell prostate cancer. / M

The high incidence rate of Nasopharyngeal Carcinoma (NPC) in southern China, including Hong Kong, has attracted worldwide attention. According to the Center for Health Protection in Hong Kong, there were 841 new cases of NPC, with 655 cases of males and 186 cases of females in 2013. The development of NPC is highly associated with the infection of one human herpes virus, the Epstein-Barr virus (EBV). Given that the homodimerization of one of the EBV endogenous protein-Epstein-Barr Nuclear Antigen 1 (EBNA1) is essential for both viral genome maintenance and infected-cell survival, thus the interference of EBNA1 homodimerization would be a novel strategy for the inhibition of EBV-positive tumours. In this thesis we devote to conjugate several kinds of organic fluorophores with various EBV-specific peptides in order to achieve the highly responsive and selective imaging, as well as the effective inhibition of EBV-positive tumours in vitro and in vivo. The first research focused on the conjugation of a styrene pyridine fluorophore with two EBNA1-specific peptides, aiming to develop a dual-probe for the imaging and inhibition of EBV-positive tumour cells. Then we tried to introduce a Nuclear Localization Sequence into the EBNA1-specific peptide, and used an Intra-molecular Charge Transfer characterized fluorophore for the following second research, it showed an impressively responsive signal when the probe binds with EBNA1 both in vitro and in vivo, more importantly, only 4 μg probe can inhibit 92.8% of growth inhibition of an EBV-positive tumour. Along this line, our last research centred on the further improvement of the imaging by taking advantage of lanthanide.

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Designing and developing a diagnostic technology that is capable of highly sensitive and specific, multiplexed, high-throughput, and quantitative biomarker assays for disease diagnosis and progression is of the upmost importance in modern medicine and patient care. Current diagnostic assays capable of multiplexed and high-throughput analysis include mass spectrometry, electrochemistry, polymerase chain reaction (PCR), and fluorescence-based techniques, however, these techniques suffer from a lack in sensitivity, false responses, or extensive sample processing that are detrimental to clinical diagnostics. To overcome these sensitivity challenges, the field of nanoplasmonics has become utilized when developing diagnostic assays. Plasmonic-based diagnostic tests utilize the unique optical, chemical, and physical property of nanoparticles to increase the sensitivity of the assay. In this dissertation, novel diagnostic platforms that utilize nanoparticles and their localized surface plasmon resonance (LSPR) property will be introduced. LSPR is an optical property in noble metallic nanoparticles that is referred to as the collective oscillation of free electrons upon light irradiation. It is highly dependent on the shape, size, and dielectric constant (refractive index) of the surrounding medium of the nanoparticle and LSPR sensing is based on a change in these properties. In this dissertation, the LSPR property is utilized to fabricate nanoplasmonic-based diagnostic platforms that are capable of multiplexed and high-throughput biomarker assays, with high sensitivity and specificity. The work presented in this dissertation is presented as six chapters, (1) Introduction. (2) Methods, (3) Fabrication of a LSPR-based multiplexed and high-throughput biosensor platform and its application in performing microRNA assays for the diagnosis of bladder cancer. In this chapter, the advancement of single-plex solid state LSPR-based biosensors into a multiplexed and high-throughput diagnostic biosensor platform is reported for the first time. The diagnostic biosensor platform is first fabricated utilizing different gold nanoparticles (spherical nanoparticles, nanorods, and triangular nanoprisms), and then with the gold triangular nanoprisms as the nanoparticle of choice, microRNA assays were performed. The developed biosensor platform is capable of assaying five different types of microRNAs simultaneously at an attomolar limit of detection. Additionally, five microRNA were assayed in 20-bladder cancer patient plasma samples. (4) Development/optimization of the biosensor platform presented in Chapter 3 for the detection of COVID-19 biomarkers. In this chapter, the biosensor platform utilized in Chapter 3 was designed to assay 10 different COVID-19 specific biomarkers from three classes (six viral nucleic acid gene sequences, two spike protein subunits, and two antibodies) with limit of detections in the attomolar range and with high specificity. The high-throughput capability of the biosensor platform was advanced, with the platform performing analysis of a single biomarker in 92 patient samples simultaneously. Additionally, the biomarker platform was utilized to assay all 10 biomarkers in a total of 80 COVID-19 patient samples. (5) Further optimization of the biosensor platform for the development of a highly specific antibody detection test for COVID-19. During the COVID-19 pandemic, knowledge was gained on the specificity of antibodies produced against COVID-19. In this chapter, that knowledge was applied towards the optimization of the biosensor platform presented in Chapter 4 in order to assay SARS-CoV-2 neutralizing antibody IgG. The optimization of the biosensor platform included the size of the gold triangular nanoprisms and the receptor molecule of choice. The biosensor platform assayed this highly specific COVID-19 IgG antibody with a limit of detection as low as 30.0 attomolar with high specificity and no cross reactivity. Additionally, as a proof of concept, the biosensor platform was utilized in a high-throughput format to assay SARS-CoV-2 IgG in a large cohort of 121 COVID-19 patient samples simultaneously. (6) Advancement of the biosensor platform from a 96-well plate to a 384-well plate and its application in assaying microRNA for early diagnosis of pancreatic cancer. In this chapter, the high-throughput capabilities of the biosensor platform presented in Chapters 3-5 was expanded by increasing the sensor amount in one platform from 92 to 359. The 384-well plate biosensor platform was designed, optimized, and utilized to perform microRNA assays for early-stage pancreatic cancer diagnosis. The optimization of the biosensor platform included the manipulation of LSPR-based parameters and the -ssDNA receptor molecule in order to obtain low limit of detections (high sensitivity). Additionally, the biosensor platform assayed two microRNA in a large cohort (n=110) of pancreatic cancer and chronic pancreatitis patient samples.

Breast cancer is the most common cancer in women, accounting for almost one-thirdof new cancer diagnoses in the United States. The mortality rate has decreased by 42% since 1989 due to early diagnosis, improvements in imaging techniques and treatment regimens. Despite all the advances in imaging modalities, there is still a need for a non-invasive, nonionizing, and low-cost diagnosis technique with high sensitivity and specificity to reduce the rate of invasive biopsies. For individuals diagnosed with locally advanced breast cancer and early-stage breast cancer, neoadjuvant chemotherapy (NACT) has become the standard of care. Pathologic complete response (pCR) is the ideal outcome of NACT, which is correlated with the prognosis and overall survival of the patients. The pCR is achieved in only about 15-20% of patients determined at the time of surgery; therefore, most patients receive a treatment that is not beneficial for them and has considerable side effects. Thus, early detection and monitoring of breast tumor response to NACT is critical for treatment planning and improving overall survival. Ultrasound-based elasticity imaging techniques have gained interest in the clinic due to their potential to provide qualitative and/or quantitative information about tissue stiffness, which is presently not unachievable with standard ultrasonography. These techniques rely on the fact that a breast tumor’s stiffness or Young’s modulus is higher than that of the surrounding normal tissues. In this dissertation, the clinical feasibility of a technique called harmonic motion imaging (HMI) for breast tumor classification, as well as for NACT response prediction and monitoring of solid tumors is investigated. HMI is an ultrasound-based elasticity imaging technique that evaluates the mechanical properties of the underlying tissues by inducing amplitude modulated (AM) displacements at a specific frequency. First, we investigated whether HMI can characterize and differentiate human breast tumors based on their relative stiffness. We enrolled female patients with benign and malignant tumors and imaged them with a clinical HMI system. The malignant tumors were found to be associated with lower HMI displacements or higher stiffness than the benign tumors. Then, in order to verify our clinical findings, we estimated HMI displacements in the postsurgical breast specimens from the same subjects and compared them against the in-vivo estimations. Our findings indicated that HMI successfully differentiated tumors from the surrounding tissue in both ex-vivo and in-vivo conditions, with an excellent correlation between the results in the two different settings. Second, we introduced and characterized a new HMI setup consisted of a multi-element focused ultrasound transducer (FUS) with electronic beam steering capability. Therefore, instead of mechanical translation of the HMI setup, the acoustic force could be electronically steered in the volumetric space to accelerate the data acquisition. A pulse sequence was developed to drive the HMI transducers assembly, the FUS and imaging transducer, using a single ultrasound data acquisition system to have a compact setup that is more applicable for clinical settings. The data acquisition was further improved by investigating the effect of AM frequencies on the quality of the HMI images and tumor detection. We found that higher AM frequencies are needed in order to improve the detection and characterization of small and stiff inclusions. On the contrary, soft and large inclusions are better resolved at lower AM frequencies. Lastly, we investigated the feasibility of using HMI for early prediction of response to neoadjuvant chemotherapy in cancer mouse models and breast cancer patients. We acquired longitudinal HMI images from pancreatic and breast cancer murine tumors during treatment with chemotherapeutic drugs and monitored the changes in the mechanical properties of the tumors. The tumors were found to soften when responsive to treatment, followed by the stiffness increase in the case of drug resistance. However, the untreated mice underwent steady stiffening of the tumors. Next, we imaged breast cancer patients at different timepoints during their chemotherapy treatment. We found that tumors in the patients who achieved pCR had higher pre-treatment stiffness and higher softening from pre-treatment to a short-interval follow-up on treatment compared to the ones in patients with residual cancer cells at the completion of treatment. These findings indicate the promising potential of HMI in the early prediction of solid tumor response to chemotherapy interventions.