Advanced wide-field interferometric microscopy for nanoparticle sensing and characterization

Nanoparticles have a key role in today's biotechnological research owing to the rapid advancement of nanotechnology. While metallic, polymer, and semiconductor based artificial nanoparticles are widely used as labels or targeted drug delivery agents, labeled and label-free detection of natural nanoparticles promise new ways for viral diagnostics and therapeutic applications. The increasing impact of nanoparticles in bio- and nano-technology necessitates the development of advanced tools for their accurate detection and characterization. Optical microscopy techniques have been an essential part of research for visualizing micron-scale particles. However, when it comes to the visualization of individual nano-scale particles, they have shown inadequate success due to the resolution and visibility limitations. Interferometric microscopy techniques have gained significant attention for providing means to overcome the nanoparticle visibility issue that is often the limiting factor in the imaging techniques based solely on the scattered light. In this dissertation, we develop a rigorous physical model to simulate the single nanoparticle optical response in a common-path wide-field interferometric microscopy (WIM) system. While the fundamental elements of the model can be used to analyze nanoparticle response in any generic wide-field imaging systems, we focus on imaging with a layered substrate (common-path interferometer) where specular reflection of illumination provides the reference light for interferometry. A robust physical model is quintessential in realizing the full potential of an optical system, and throughout this dissertation, we make use of it to benchmark our experimental findings, investigate the utility of various optical configurations, reconstruct weakly scattering nanoparticle images, as well as to characterize and discriminate interferometric nanoparticle responses. This study investigates the integration of advanced optical schemes in WIM with two main goals in mind: (i) increasing the visibility of low-index nanoscale particles via pupil function engineering, pushing the limit of sensitivity; (ii) improving the resolution of sub-diffraction-limited, low-index particle images in WIM via reconstruction strategies for shape and orientation information. We successfully demonstrate an overall ten-fold improvement in the visibility of the low-index sub-wavelength nanoparticles as well as up to two-fold extended spatial resolution of the interference-enhanced nanoparticle images. We also systematically examine the key factors that determine the signal in WIM. These factors include the particle type, size, layered substrate design, defocus and nanoparticle polarizability. We use the physical model to demonstrate how these factors determine the signal levels, and demonstrate how the layered substrate can be designed to optimize the overall signal, while defocus scan can be used to maximize it, as well as its signature can be utilized for particle discrimination purposes for both dielectric particles and resonant metallic particles. We introduce a machine learning based particle characterization algorithm that relies on supervised learning from model. The particle characterization is limited to discrimination based on nanosphere size and type in the scope of this dissertation

Nanoparticle Classification in Wide-field Interferometric Microscopy by Supervised Learning from Model

Interference enhanced wide-field nanoparticle imaging is a highly sensitive technique that has found numerous applications in labeled and label-free sub-diffraction-limited pathogen detection. It also provides unique opportunities for nanoparticle classification upon detection. More specif- ically, the nanoparticle defocus images result in a particle-specific response that can be of great utility for nanoparticle classification, particularly based on type and size. In this work, we com- bine a model based supervised learning algorithm with a wide-field common-path interferometric microscopy method to achieve accurate nanoparticle classification. We verify our classification schemes experimentally by using gold and polystyrene nanospheres.Comment: 5 pages, 2 figure

Is My Model Up-to-date? Detecting CoViD-19 Variants by Machine Learning

Machine learning extracts models from huge quantities of data. Models trained and validated over past data can be deployed in making forecasts as well as in classifying new incoming data. The real world which generates data may change over time, making the deployed model an obsolete one. To preserve the quality of the currently deployed model, continuous machine learning is required. Our approach retrospectively evaluates in an online fashion the behaviour of the currently deployed model. A drift detector detects any performance slump, and, in case, can replace the previous model with an up-to-date one. The approach experiments on a dataset of 8642 hematochemical examinations from hospitalized patients gathered over 6 months: the outcome of the model predicts the RT-PCR test result about CoViD-19. The method reached an area under the curve (AUC) of 0.794, 6% better than offline and 5% better than standard online-binary classification techniques

Robust visualization and discrimination of nanoparticles by interferometric imaging

Single-molecule and single-nanoparticle biosensors are a growing frontier in diagnostics. Digital biosensors are those which enumerate all specifically immobilized biomolecules or biological nanoparticles, and thereby achieve limits of detection usually beyond the reach of ensemble measurements. Here we review modern optical techniques for single nanoparticle detection and describe the single-particle interferometric reflectance imaging sensor (SP-IRIS). We present challenges associated with reliably detecting faint nanoparticles with SP-IRIS, and describe image acquisition processes and software modifications to address them. Specifically, we describe a image acquisition processing method for the discrimination and accurate counting of nanoparticles that greatly reduces both the number of false positives and false negatives. These engineering improvements are critical steps in the translation of SP-IRIS towards applications in medical diagnostics.R01 AI096159 - NIAID NIH HHSFirst author draf

High-resolution Imaging of nanoparticles in wide-field interferometric scattering microscopy

Single particle interferometric scattering microscopy has demonstrated great capability in label-free imaging of sub-wavelength dielectric nanoparticles (r<25 nm); however, it suffers from diffraction-limited resolution. Here, we demonstrate ~2-fold improvement in lateral resolution upon asymmetric illumination.Published versio

Impact of deformed wing virus master variants (dwv-a, dwv-b, and dwv-c) in managed honey bee colonies of türkiye

Aim: This study aimed to determine the deformed wing virus (DWV) master variants in managed honey bee hives in Central Anatolia and the Mediterranean Regions of Türkiye. Also, the relationship of DWV genotypes circulating in the apiaries with clinical signs observed in honey bee hives was investigated. Materials and Methods: For this study, adult honey bees were collected from the same 25 hives in the spring-summer and autumn seasons of 2019 from the provinces of Aksaray, Isparta, Karaman, Konya and Nigde. DWV-specific nucleic acid and DWV genotypes were detected by DWV real-time RT-PCR assay and ABC assay, respectively. Results: Deformed wing virus infection was detected in each sampling season. While many colonies were without any clinical signs, in some of the apiaries where samples were collected, wing deformity, trembling, paralysis, swelling in the abdomen, loss of productivity, and dead bees were observed. The prevalences of DWV-A, DWV-B, and DWV-C in adult honey bees were 62%, 82%, and 24%, respectively. The dominant genotype detected in bee hives was the DWV-B master variant (98%). Also, the virus load of the DWV-A master variant was high in all of the honey bee hives with wintering losses. Conclusion: In this present study, data on the current status of DWV master variants circulating in Turkey and their impacts on honey bee colonies are reported for the first time. Thus, it is thought that DWV, which causes yield losses at varying rates in every season of the year in Turkish bee hives, should be carefully monitored

The Serological and Virological Investigation of Canine Adenovirus Infection on the Dogs

Two types of Canine Adenovirus (CAVs), Canine Adenovirus type 1 (CAV-1), the virus which causes infectious canine hepatitis, and Canine Adenovirus type 2 (CAV-2), which causes canine infectious laryngotracheitis, have been found in dogs. In this study, blood samples taken from 111 dogs, which were admitted to the Internal Medicine Clinic of Selcuk University, Faculty of Veterinary Medicine, with clinical symptoms. Seventy-seven dogs were sampled from Isparta and Burdur dog shelters by random sampling, regardless of the clinical findings. Dogs showed a systemic disease, characterized by fever, diarrhea, vomiting, oculonasal discharge, conjunctivitis, severe moist cough, signs of pulmonary disease and dehydration. Two dogs had corneal opacity and photophobia. In serological studies, 188 serum samples were investigated on the presence of CAV antibodies by ELISA. Total 103 (103/188–54.7%) blood samples were detected to be positive for CAV antibodies by ELISA. However, 85 (85/188–45.2%) blood samples were negative. Blood leukocyte samples from dogs were processed and inoculated onto confluent monolayers of MDCK cells using standard virological techniques. After third passage, cells were examined by direct immunoflourescence test for virus isolation. But positive result was not detected. In conclusion, this study clearly demonstrates the high prevalence of CAV infection in dogs

High-throughput, high-resolution interferometric light microscopy of biological nanoparticles

Label-free, visible light microscopy is an indispensable tool for studying biological nanoparticles (BNPs). However, conventional imaging techniques have two major challenges: (i) weak contrast due to low-refractive-index difference with the surrounding medium and exceptionally small size and (ii) limited spatial resolution. Advances in interferometric microscopy have overcome the weak contrast limitation and enabled direct detection of BNPs, yet lateral resolution remains as a challenge in studying BNP morphology. Here, we introduce a wide-field interferometric microscopy technique augmented by computational imaging to demonstrate a 2-fold lateral resolution improvement over a large field-of-view (>100 × 100 μm2), enabling simultaneous imaging of more than 104 BNPs at a resolution of ∼150 nm without any labels or sample preparation. We present a rigorous vectorial-optics-based forward model establishing the relationship between the intensity images captured under partially coherent asymmetric illumination and the complex permittivity distribution of nanoparticles. We demonstrate high-throughput morphological visualization of a diverse population of Ebola virus-like particles and a structurally distinct Ebola vaccine candidate. Our approach offers a low-cost and robust label-free imaging platform for high-throughput and high-resolution characterization of a broad size range of BNPs.Accepted manuscrip

IN VITRO ANTIVIRAL AND ANTIOXIDANT ACTIVITIES OF SILYMARIN AND PANAX GINSENG ON VERO CELLS INFECTED WITH BOVINE EPHEMERAL FEVER VIRUS AND BLUE TONGUE VIRUS

The inadequacy of antiviral drugs in the treatment of viral diseases, has led to herbal medicine. It was aimed to determine the antiviral and antioxidant activities of Silymarin and Panax ginseng against Bovine Ephemeral Fever Virus (BEFV) and Bluetongue virus (BTV) in cell culture. Silymarin and Panax ginseng were dissolved at the concentration of 400 µg/ml within distillated water. The cell proliferation test was used to evaluate the cytotoxic activity of the Silymarin and Panax ginseng. They were cytotoxic over 50 μg / ml dose in Vero cells. Hence, antiviral activities of subjects were investigated against BEFV at the 25 and 50 µg/ ml doses. However, they did not show antiviral activity at any dose level against BTV. Effects of Silymarin and Panax ginseng were evaluated on the total antioxidant capacity (TAC) and thiobarbituric acid reactive substances (TBARS), oxidative stress marker, levels in Vero cells infected with BEFV and BTV. Silymarin (25 and 50 µg/ ml) affected TAC levels in Vero cells infected with BEFV, but it did no effect the TBARS levels in Vero cells infected with BEFV and BTV. Panax ginseng decreased TBARS levels in both diseases, although it did not change TAC levels at same doses on Vero cells infected with BEFV and BTV. In conclusion, it is referred that Silymarin and Panax ginseng may have antiviral some viruses and they have antioxidant, cell protective and inhibitory effects of virus replication