Master Thesis Proposals

Presented here are thesis proposals for students, supervised by staff at the Ultrasound, Microscopy and Optics group.  


The scope of these proposals can be adjusted and are equally suitable for students from the 5-year integrated masters (30sp) and the 2-year master’s program in Physics (60sp) 

 

The Ultrasound, Microscopy and Optics group currently have the following project proposals:


 

Computational super-resolution imaging of nanoparticles using label-free microscopy with polarization separated imaging

Supervisors: Krishna Agarwal and Zicheng Liu

Introduction

Label-free microscopy is soon catching up as a preferred form of imaging living systems in non-toxic manner. Super-resolution in label-free far-field microscopy is an open challenge, if elastic scattering has to be exploited for imaging. In such situations, full 3D electromagnetic scattering model, including multiple scattering has to be considered. In addition, it is preferred to measure quantities directly proportional to electric far field and across the complete aperture, i.e. the 4πsolid angle. If these characteristics are satisfied, it has been shown that super-resolution can be achieved [1,2]. Achieving measurements with these two characteristics is close to impossible in practical microscopes in the visible spectrum. Then, it is important to understand the limitations on super-resolution in the case of limited aperture and absence of electric field measurements. It is also required to design super-resolution algorithms optimized for these limitations.

Research & Objectives

The student will simulate a simplified version of computational microscope capable of simulating the electric field and intensity on the camera for nanoparticles under different orientations and polarizations of incident light. Then, the student will implement an existing algorithm [1] for performing computational imaging of the nanoparticles and study the effect of limited aperture and camera pixilation on resolution, assuming that electric field measurements are hypothetically possible. The student will develop an intensity only super-resolution approach for computational imaging based directly on [1,2] and study the artefacts arising from unavailability of electric field measurements. Lastly, depending upon the progress, observations, and available time, the student may explore design of new computational imaging algorithm for super-resolved imaging of nanoparticles. The student will learn about computational modeling, applied electromagnetism, optics, and super-resolution imaging. The student will therefore gain experience of developing theoretical concepts rooted in physics and mathematics to application in technology development. The student will receive a direct exposure of academic research, in the meanwhile developing orientation for computation and programming intensive tasks desirable in industry.

Pre-requisites:

The student is required to have studied electromagnetism, linear algebra, and preferably computational modeling and calculus.

Referances

[1] Chen, Xudong, and Yu Zhong. "MUSIC electromagnetic imaging with enhanced resolution for small inclusions."Inverse Problems 25.1 (2008): 015008.

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High-resolution microscopy of salmon skin cells exposed to microplastics

Supervisors: Deanna Wolfson, Roy A. Dalmo (BFE), and Balpreet Singh Ahluwalia
 
Introduction
Fluorescence microscopy has enabled countless breakthroughs in medical and biological research. It combines the basic idea of ‘seeing is believing’ with molecular or biochemical specificity using specially-targeted fluorescent labelling. The optical nanoscopy group at UiT has expertise in and access to a variety of advanced fluorescence microscopes, including several that we have developed ourselves.
 
UiT also has expertise in arctic marine aquaculture, particularly in the farming of Atlantic salmon, a critical part of Norway’s economy. In collaboration with Roy A. Dalmo (UiT BFE, NFH) we have been studying the interactions of skin cells isolated from farmed salmon. Previous work has shown that these cells will take up microplastic particles aspart of their response to foreign matter [1] , and our lab has been successful in capturing the dynamics of these cells in connection with these plastic particles (see video [2], microplastics shown in blue). We have been able to observe the movement of the cytoskeleton of these cells as they move across a petri dish, and can also observe howthe cell’s internal recycling system (lysosomes) behaves in the presence or absence of these plastic particles. Additionally, we have found indications that the cells may be exchanging mitochondria (the power producers of cells). However, much of this research has been preliminary and limited in scope. This project aims to study in more detail how the cells interact with a variety of microplastics, and/or to further evaluate the interactions between cells e.g. through mitochondrial exchange probably caused by a stress response.
 
Research & Objectives
Previous work on these cells focused on optimizing harvesting and labelling conditions for these cells. Studies on microplastics in our labs has been limited to 0.5 or 1 μm round polystyrene beads, instead of the much larger variety of sizes, shapes, and plastic types found in the oceans. While we have preliminary results showing that salmon skin cells will uptake these plastic particles, we are lacking details on the dynamics of these processes and which cellular mechanisms are involved. The timescale of uptake is unknown, and the fate of cells after uptake has been called into question by recent data collected in our labs. The master’s student would therefore be responsible for a more detailed study on the uptake of different microplastic particles by salmon skin cells over a range of timescales (minutes to days). Depending on student interest on initial results, the student could additionally study the interaction between cells as it regards mitochondrial exchange or the shuttling of cells in a balled-up state by the surrounding healthy cells.
 
The candidate would learn the following skills
-How to harvest salmon skin cells at the aquaculture research station in Tromsø (Kårvika)
-How to fluorescently label cells using commercially-available dyes
-How to operate the DeltaVision deconvolution fluorescent microscope
-How to plan and execute microscopy experiments including planning relevant control experiments
-Image analysis using FIJI to evaluate results of imaging experiments
 
Strong interaction with Roy A. Dalmo’s group is anticipated, including training in and ongoing collection of fish skin cells. It is preferred that the candidate will work closely with another Master’s candidate from BFE to plan, perform, and analyse experiments, although the specific research aims may vary somewhat between the candidates.
 
References
[1] Asbakk, K., and R. A. Dalmo. "Atlantic Salmon (Salmo salar L.) Epidermal Malpighian Cells - Motile Cells Clearing Away Latex Beads in Vitro." Journal of Marine Biotechnology 6.1 (1998): 30-34.
 

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Improving the MUSICAL super-resolution imaging technique through optimization of labeling and imaging conditions

Supervisors: Deanna Wolfson and Krishna Agarwal

Introduction

Fluorescence microscopy has enabled countless breakthroughs in medical and biological research. It combines the basic idea of ‘seeing is believing’ with molecular or biochemical specificity using specially-targeted fluorescent labelling. The optical nanoscopy group at UiT has expertise in and access to a variety of advanced microscopy techniques, including several that we have developed ourselves. Multiple Signal Classification Algorithm (MUSICAL) is one such technique; it uses an algorithm to super-resolve the distribution of fluorophores by utilizingfluctuations in fluorescence intensity [1] . It can support 100-50 nm resolution with shortacquisition time (seconds), which makes it a valuable tool for imaging biological samples. In this project, the student will optimize the labeling and imaging protocols and benchmark the performance of MUSICAL.

Research & Objectives

The student will design systematic measurements to characterize and optimize the performance of MUSICAL. The student will also consider the strengths and weaknesses of various metrics, such as Rayleigh resolution limit, Fourier ring correlation, metrics for fluctuation characterization, etc. for studying the performance. The student will also perform comparison of MUSICAL results with other super-resolution techniques, such as structured illumination microscopy, localization microscopy, and other computational nanoscopy techniques.In order to perform this work, the student will also need to learn techniques in several related areas. The student will be trained in biological sample preparation, including sterile handling techniques, basic cell culture, and fluorescence labeling of samples. Additionally, the student will learn fluorescence microscopy, primarily working on the DeltaVision Elite deconvolution microscope available in our lab. The student will learn basic image processing using FIJI and receive further instruction in computational nanoscopy.The project requires meticulous experimentation and interest in bioimaging and microscopy. It is preferred that the student has taken a course in microscopy or nanoscopy (or is taking it this semester). The student will gain multi-disciplinary experience spanning physics and biology.

References

[J1] K. Agarwal and R. Machan. “Multiple Signal Classification Algorithm for super-resolution fluorescence microscopy.” Nature Communications(2016).

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Label-free microscopy of the uptake of microplastics in salmon skin cells

Supervisors: Deanna Wolfson, Roy A. Dalmo (BFE), and Balpreet Singh Ahluwalia
 
Introduction
Microscopes have enabled countless breakthroughs in medical and biological research, but much of this work has relied on the addition of dyes to the sample in order to achieve sufficient contrast. These dyes can alter the biology of the systems under study, thus compromising the results and hindering longer-term studies. Microscopy techniques which use inherent properties of the sample to show contrast – without the addition of external labels – have been gaining increased attention in recent years. In addition to developing our own systems, the optics group at UiT has recently acquired a new label-free microscope (the CX-F from NanoLive), which uses differences in the index of refraction within cells to create a 3D map of the cellular structure.
 
UiT also has expertise in arctic marine biology, particularly in the farming of Atlantic salmon, a critical part of Norway’s economy. In collaboration with Roy A. Dalmo (UiT BFE, NFH) we have been studying the interactions of skin cells isolated from farmed salmon. Previous work has shown that these cells will take up microplastic particles as part of their response to foreign matter [1] , and our lab has been successful in capturing the dynamics of these cells in connection with these plastic particles. Using dyes to label the membranes of these cells has been largely unsuccessful, however, making it difficult to see when exactly a particle enters the cell instead of simply being carried around on the surface. However, using the new label-free microscope, both the membranes of the cells and the microplastic particles can easily be seen (see video [2] for a timelapsed 3D rendering of these cells and their microplastic), and imaged at a rate as fast as every 2 seconds. This master’s project focuses on investigating the dynamics of the cell-microplastic interaction.
 
Research & Objectives
Studies on microplastic uptake in our labs has so far been limited to 0.5 or 1 μm round polystyrene beads, instead of the much larger variety of sizes, shapes, and plastic types found in the oceans. Additionally, most of this work was done using fluorescent dyes, as we have only recently acquired the new label-free CX-F microscope. Thus, this project will focus on using the CX-F to characterize the interactions between isolated salmon skin cells and microplastics of different sizes and, ideally, shapes and plastic types. The candidate will characterize if all cells interact equally to microplastics, or if there are sub-populations of cells that behave differently. They will also characterize the timing of the interactions, including how long it takes for a plastic particle to be taken up, as well as the fate of the plastics within the cells and the fate of the cells which take up the most microplastics. As these dynamics have been little studied, we anticipate that there will be unexpected behaviours observed that will require additional study. As needed by the experiments, label-free imaging may be combined with the use of fluorescence microscopy to better elucidate the mechanisms and timing of plastic uptake.
 
The candidate would learn the following skills
-How to harvest salmon skin cells at the aquaculture research station in Tromsø (Kårvika)
-How to operate the CX-F label-free microscope
-How to plan and execute microscopy experiments including planning relevant control experiments
-Image analysis using STEVE and FIJI to evaluate results of imaging experiments
 
Strong interaction with Roy A. Dalmo’s group is anticipated, including training in and ongoing collection of fish skin cells. It is preferred that the candidate work closely with another Master’s candidate from BFE to plan, perform, and analyse experiments, although the specific research aims may vary somewhat between the candidates.
 
References
[1] Asbakk, K., and R. A. Dalmo. "Atlantic Salmon (Salmo Salar L.) Epidermal Malpighian Cells - Motile Cells Clearing Away Latex Beads in Vitro." Journal of Marine Biotechnology 6.1 (1998): 30-34.
[2] https://youtu.be/OR0JwN2OAcs

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Nanoscopy-associated image and data processing tools on JavaPython platform

Supervisors: Krishna Agarwaland Sebastian Acuna.

Introduction

Fluorescence microscopy has enabled countless breakthroughs in medical and biological research. It combines the basic idea of ‘seeing is believing’ with molecular or biochemical specificity using specially-targeted fluorescent labelling. The optical nanoscopy group at UiT has expertise in and access to a variety of advanced microscopy techniques, including several that we have developed ourselves.Multiple Signal Classification Algorithm (MUSICAL) isone such nanoscopy technique; it uses analgorithm to super-resolve the distribution of fluorophoresby utilizingfluctuations in fluorescence intensity[1]. It can support 100-50 nm resolution with shortacquisition time (seconds), which makes it a valuable tool for imaging biological samples.In this project, the student will create nanoscopy data processing tools for MUSICAL in order to allow the user to explore various options and perform advanced image processing tasks on MUSICAL’s raw microscopy and processed nanoscopy images.

Research & Objectives

The student will develop user friendly toolkit on java (FIJI) or python platforms to allow powerful investigation of MUSICAL, such as including tools for

1.Threshold suggestion and orautomatic thresholding

2.Options for indicator functions

3.Contrast enhancements

4.Video nanoscopy and temporal multi-scale MUSICAL analysis

5.Denoising as pre-or post-processing

6.Artefact suppression anddrift correctionusing deep learning

7.Raw data and MUSICAL image analytics and statistics generation

8.Foreground segmentation/background suppression, etc.

The project stands at a junction of advanced software programming, new algorithm development, physics-based deep learning, statistics, user-interface design, etc.

It is preferred that the student has takenacourse in microscopy or nanoscopy (or is taking it this semester). There is a publication component and potential to participate in business plan development of MUSICAL.

References

[J1] K. Agarwal and R. Machan. “Multiple Signal Classification Algorithm for super-resolution fluorescence microscopy.”Nature Communications(2016).

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On-chip super-resolution microscopy of pathology and tissue section

Supervisors: Balpreet Singh Ahluwalia, Vishesh Dubey,Luis Enrique Villegas Hernandez

Introduction

In several diseases, change in the tissue morphology is consider as the marker of disease. Till now histology is most preferred method to visualize these changes in the morphology.Unfortunately, present techniqueis not capable todetect the changes at sub-cellular level.The invention of super-resolution fluorescence optical microscopy (commonly referred as opticalnanoscopy) has provided us with a glimpse of future impacts on cell-biology and medical diagnosticswithcapabilityto visualize the structures even far beyond the diffraction limit.Untiltoday,tissueand pathology slides are mostlyexplored usingstandard optical microscopy and have not been extensively studied usingsuper-resolutionmicroscopy methodswhich can provide abundant amount of useful information.AtUiTthenanoscopygroup have recently developed, patented,photonic chip-basednanoscopy, to be used in a standard optical microscope, where sample is placed on top of a photonic chip (PC) capable of both holding and illuminating the sample, enabling to acquire super-resolved imagesover extra-ordinary large areas.

Project setting

The group has received Research Council of Norway project, BioTek2021 to develop, chip-basednanoscopyplatform for pathology application. This master project is announced within the horizon of BioTekl2021 project. The master student will have good support from the existing team of one post-doc and one PhD working in this project and it is anticipated that they will work closely. Moreover, there will be close co-operation with the hospitals from either UNNTromsøorRadiumhospitalOslo.

Research & Objectives

The focus of thismaster thesis is to perform high-resolution imaging on tissues sections primarily using homemade chip-basednanoscope. The focus will be onoptimization of labelling and imaging of tissue biopsies. The conventional tissues biopsies are 4-8μm thick. We will investigate the usage of chip-based microscopes to image different tissue sections. Both pre-labelled tissues sections and labelling tissues after hosting them on waveguide chip will be explored. Candidate will firstoptimize the labelling strategy suitable for chip platform andperform diffraction limited multi-colortissues imaging and based on the progress super-resolution imagingon tissues sectionscan alsobe investigated. Aberrations from tissues sections could be challenging for super-resolution imaging. To reduce such aberrations ultramicrotome will be used to section 200 nm thin tissues sections. These thin tissue sections (200 nm) can then be completely illuminated using the surface evanescent field generated from the waveguide surface.Work will be done in close collaborations with the medical faculty/ UNN providing tissues samples.

Candidate willlearn and develop followingskills:

a. Labelling of tissue section with primary and secondary anti-bodies

b. Operational skills on super-resolution bio-imaging

c. Imaging and handling of tissue sections

d. Data handlingand manuscript writing

e. Possibility of publication and international working environment

f. Close co-operation and cross-disciplinary exposure

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Performance analysis and application study of MUSICAL

Supervisors: Krishna Agarwaland, Balpreet Singh Ahluwalia

Introduction

Fluorescence microscopy has enabled countless breakthroughs in medical and biological research. It combines the basic idea of ‘seeing is believing’ with molecular or biochemical specificity usingspecially-targetedfluorescent labelling. The opticalnanoscopygroup atUiThas expertise in and access to a variety of advancedmicroscopy techniques, including several that we have developed ourselves.Multiple Signal Classification Algorithm (MUSICAL) isone such technique; it uses analgorithmto super-resolvethe distribution of fluorophoresby utilizingfluctuations in fluorescence intensity[1]. It can support100-50 nm resolution withshortacquisition time (seconds), which makes it a valuable toolfor imaging biological samples.In this project, the student willoptimize the labeling and imaging protocols and benchmark the performance of MUSICAL.

Research & Objectives

The student willcurate data from the current users of MUSICAL, including data on a variety of sample types, microscopes, and labeling conditions. In addition, the student will create benchmark data using DNA templates, DNA combs, and liposomes. The student will systematically categorize the raw microscopy and MUSICAL data into different pools of study for performance analysis and generate the MUSICAL results from the raw data with different control parameters. The student will also generate performance metrics regarding resolution, contrast, side lobes, artefacts, and threshold selection for MUSICAL results and also suitability metrics for the raw data in terms of signal to background ratio, fluctuations, sparsity of features, etc. The student will then write an application white paper that can be utilized by a user of MUSICAL for deriving insight about the optimal conditions of raw data for a given sample and label type, optimal MUSICAL parameters, and expected nature of performance. The student will then participate in data management for public use and scientific information sharing channels.

In order to perform this work, the student will be trained in scientific data curation, benchmark data creation, scientific data assessment and characterization, big data management, scientific writing, and application/case creation. The student will be trained in  nanoscopy and microscopy data analysis and qualification. The student will gain medium to advance expertise in image processing using FIJI. The student may also opportunistically learn to acquire microscopy data.

The project requires meticulousdataexperimentation and interest in microscopy, image analysis, and scientific study design. It is preferred that the student has takenacourse in microscopy ornanoscopy(or is taking it this semester).There is a publication component and potential to participate inbusiness plan development of MUSICAL.

References

[J1] K. Agarwal and R. Machan. “Multiple Signal Classification Algorithm for super-resolution fluorescence microscopy.”Nature Communications(2016).

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Raman-spectroscopy of extracellular vesices

Supervisor: Professor Olav Gaute Hellesø, olav.gaute.helleso@uit.no

Required course: FYS-3009 Photonics

Recommended courses: FYS-2008 Measurement techniques

Background

Extracellular vesicles (EVs)are bilayer membrane vesicles released from various cells into their surroundings. EVs include exosomes (30-100 nm in diameter) and microvesicles (100-1000 nm) and express surface antigens specific of parental cells. EVs are considered a mechanism for intercellular communications, allowing cells to exchange proteins, lipids and genetic material [1]. Being essential components in the life and functioning of living cells, EVs can be important indicators of different conditions of a producing organism, and therefore can have applications in clinical settings. Thus, elevated plasma levels of EVs have been associated with several disease states such as atherosclerosis, diabetes, cancer, arterial cardiovascular diseases and venous thromboembolism [2]. New methods to characterise and analyse EVs are essential to understand the physiological and pathological functions of these vesicles, and to develop new clinical methods involving their use and/or analysis.

Raman-spectroscopycan reveal the chemical composition, or 'chemical fingerprint', of a sample. However, owing to the small EV size, acquisition of Raman signals from EVs is very demanding. By combining optical trappingwith Raman-spectroscopy, it is possible to collect the Raman-spectrum of a few EVs [3].

Project description

The aim of theproject is to link the composition of EVs to the risk of venous thromboembolism using Raman-spectroscopy. The student will make a set-up which combines a microscope, optical trapping and Raman-spectroscopy. Using this set-up, the student will trap particles and do Raman-spectroscopy of them. Initially, the particles will be fluorescent polystyrene beads, before the method is tested with EVs. Data analysis of the acquired spectra is necessary to find a link between EVs and venous thromboembolism. A commercial Raman-microscope (without trapping) and an FTIR-ATR spectrometer will be used initially and for reference measurements.

The main part of the project is experimental optics, with building, trouble-shooting and improving the set-up as major tasks. Some programming might be necessary, e.g. to control the instruments and analyse the data. Numerical simulations in Comsol can be included if the student wishes.

References

1. van Niel, G., G. D'Angelo, and G. Raposo, Nature Reviews Molecular Cell Biology, 2018. 19(4): p. 213-228.

2. Jamaly, S., et al., Scientific Reports, 2018. 8.

3. Kruglik, S.G., et al., Nanoscale, 2019. 11(4): p. 1661-1679.

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