A variation on a numerical model of the motor protein myosin V presentedin a paper by Craig and Linke (2009) is developed. An alternative potential is proposed. All aspects of the model development arederived in detail and tested. Two model tests are created and used toconfirm the correctness of the developed model. A simulation demonstratesthat the developed model is able to produce a myosin V step. Adidactical transposition is presented in the form of a compendium, in which a numerical model of myosin V by Craig and Linke (2009) isdescribed. The didactical transposition is developed using a methodologyof didactical engineering. The didactical study indicated thatthe content was well recieved by the target group of eight individualsin respect to the scientific complexity and that it evokes motivation forlearning. The study also indicated that unsuccessful areas of the didacticaltransposition existed. / En variation av en numerisk modell av motorproteinet myosin V presenteradav Craig och Linke (2009) utvecklas. En alternativ potential föreslås. Alla aspekter av modellutvecklingen härleds i detalj och testas.Två modelltester skapas och används för att bekräfta riktigheteni den utvecklade modellen. En simulering demonstrerar att myosin Vkan ta ett steg i den utvecklade modellen.En didaktisk transposition presenteras i form av ett kompendium,där en numerisk modell av myosin V av Craig och Linke (2009) beskrivs.Metodologiskt utvecklas den didaktiska transpositionen medhjälp av didaktisk ingenjörskonst. Den didaktiska studien indikeradeatt innehållet togs emot väl av målgruppen bestående av åtta personeri hänseende till vetenskaplig komplexitet och att det väckte motivationför lärande. Studien indikerade även att misslyckade områden av dendidaktiska transpositionen förekom.

The integration of artificial intelligence (AI) into biomedical research has given rise to new models and research topics in biomedicine. Whole-cell modeling aims to create a holistic understanding of the cell by integrating diverse data. One method of comprehension is the characterization and imitation of a system. Phenomenological cell models imitate cell structure and behavior based on, for example, images. Thus generative AI image models present one approach to developing such phenomenological models of cell systems. Diffusion models are a popular generative model class for image generation. Briefly, diffusion models consist of a forward and reverse diffusion process, where the forward process iteratively adds noise to an image and the reverse process learns to remove it. Image generation is achieved by sampling from noise and applying the learned reverse process. The generation may be conditioned to achieve a specific output. The diffusion process is computationally expensive to evaluate in pixel space. The latent diffusion model presents a solution by moving the diffusion process to the latent space of an autoencoder. A latent diffusion model has been trained to develop a phenomenological model of cells in mitosis. The aim is to identify spatial and temporal patterns in the dataset, consisting of fluorescence microscopy images of cells in mitosis, and condition the output of the latent diffusion model on labels associated with the data. The latent diffusion can generate images unconditionally and conditionally. The unconditionally generated images appear visually similar, but quantitative metrics suggest the potential for improvement. Qualitative analysis of the conditionally generated images indicates opportunities for enhancement. The analysis from the proposed method for objective assessment of conditionally generated images, feature extraction of images followed by dimension reduction using uniform manifold approximation and projection, concurs with the visual assessment. However, the quantitative metrics and the proposed method of conditional assessment rely upon InceptionV3 to extract features from the images. InceptionV3 has not been trained on biomedical images and thus the metrics and methods should not be overly relied upon. In general, there is a need for new assessment techniques suitable for non-class conditionally generated images that are unsuitable for evaluation using user studies. / Integrering av artificiell intelligens (AI) i biomedicinsk forskning har gett upphov till nya modeller och forskningsfrågor inom biomedicin. Helcellsmodellering syftar till att skapa ett kvantitativt perspektiv på cellbiologi och skapa holistisk kunskap om cellen. Ett system kan förstås genom karaktärisering och imitation. Generativ AI är ett tillvägagångssätt för att utveckla modeller som kan imitera och karaktärisera celler baserat på bilder. Diffusionsmodeller är en populär klass av generativa modeller för bildgenerering. Diffusionsmodeller består av en framåt- och bakåtdiffusionsprocess, där den framåtriktade processen iterativt lägger till brus i en bild och den bakåtriktade processen lär sig att ta bort det. Nya bilder genereras genom att tillämpa den inlärda bakåtriktade processen på en bild av brus. Generationen kan göras villkorlig för att forma bilden efter givna villkor. Den beräkningsintensiva diffusionsprocessen kan effektiviseras genom att introducera en "autoencoder" som flyttar diffusionsprocessen från pixelrummets stora dimension till det latenta rummet, som har en mindre dimension. Det utgör basen för en latent diffusionsmodell. För att utveckla en fenomenologisk modell av celler i mitos har en latent diffusionsmodell tränats på fluorescensmikroskopibilder på celler som genomgår mitos. Målet är att identifiera spatiala och temporala mönster i bilderna och skapa en modell som kan villkora bildgenerationen baserat på givna spatiala och temporala villkor associerade med bilderna. Latenta diffusionsmodeller kan skapa bilder både villkorligen och helt fritt från den underliggande datadistributionen. Den fria generationen av bilder resulterar i visuellt lika bilder men kvantitativa mått indikerar att modellen kan förbättras. Villkorligt genererade bilder håller inte samma visuella kvalité. Behovet av tekniker för att utvärdera villkorligt genererade bilder har identifierats och en metod har föreslagits. Metoden involverar att extrahera attribut från bilderna och reducera dimensionen av attributen för att visualisera de olika villkoren. Utvärderingen av de villkorligt genererade bilderna visar att den villkorliga generationen kan förbättras. Däremot beror metoden och de kvantitativa mått som beräknades för den fria generationen av bilder på ett neuralt nätverk som inte tränats på biomedicinska bilder. Därför bör resultaten tolkas med viss reservation.

X-ray free-electron lasers (XFELs) can achieve near-atomic resolution in imaging organic molecules. As a fourth-generation light source, modern XFELs can generate brilliant ultrashort X-ray pulses at MHz repetition rates. This allows XFELs to image single molecules with great detail, obtaining information about their dynamics and states through the interaction of the electrons within the molecule with the X-rays. A key challenge when imaging biomolecules (e.g. proteins, viruses, or bacteria) is to image the sample within its native environment, in solution. 3D-printed gas-accelerated liquid-sheet jet nozzles for liquid sample-delivery have yielded promising results in this respect, demonstrating that liquid sheets can be a reliable alternative to conventional sample-delivery methods, e.g. electrospray. Although the nozzles that this project uses have been successfully used for measurements at XFELs, the effect of nozzle design and liquid material-properties have not previously been explored. Therefore, the present report aims to explore different flow regimes of gas-accelerated liquid-sheet jets, and to study how the generated sheet jet depends upon different parameters, such as gas and liquid flow-rates, sample solution, and nozzle geometry. The findings suggest that low surface tension is crucial for producing large jets, and that higher viscosity may help to generate more stable sheet jets. However, further studies are required to draw definite conclusions.

In the work presented this thesis, two different conditions that are classified as protein misfolding diseases: Alzheimer's disease and lysozyme amyloidosis and proteins that could have a beneficial effect in these diseases, have been studied using Drosophila melanogaster, commonly known as the fruit fly. The fruit fly has been used for over 100 years to study and better understand fundamental biological processes. Although the fruit fly, unlike humans, is an invertebrate, many of its central biological mechanisms are very similar to ours. The first transgenic flies were designed in the early 1980s, and since then, the fruit fly has been one of the most widely used model organisms in studies on the effects of over-expressed human proteins in a biological system; one can regard the fly as a living, biological test tube. For  most proteins, it is necessary that they fold into a three-dimensional structure to function properly. But sometimes the folding goes wrong; this may be due to mutations that make the protein unstable and subject to misfolding. A misfolded protein molecule can then aggregate with other misfolded proteins. In Alzheimer's disease, which is the most common form of dementia, protein aggregates are present in the brains of patients. These aggregates are composed of the amyloid-β (Aβ) peptide, a small peptide of around 42 amino acids which is cleaved from the larger, membrane-bound, protein AβPP by two different enzymes, BACE1 and γ-secretase. In the first part of this thesis, two different fly models for Alzheimer’s disease were used: the Aβ fly model, which directly expresses the Aβ peptide, and the AβPP-BACE1 fly model, in which all the components necessary to produce the Aβ peptide in the fly are expressed in the fly central nervous system (CNS). The two different fly models were compared and the results show that a significantly smaller amount of the Aβ peptide is needed to achieve the same, or an even greater, toxic effect in the AβPP-BACE1 model compared to the Aβ model. In the second part of the thesis, these two fly models for Alzheimer’s disease were again used, but now to investigate whether lysozyme, a protein involved in our innate immune system, can counteract the toxic effect of Aβ generated in the fly models. And indeed, lysozyme is able to save the flies from Aβ-induced toxicity. Aβ and lysozyme were found to interact with each other in vivo. The second misfolding disease studied in this thesis is lysozyme amyloidosis. It is a rare, dominantly inherited amyloid disease in which mutant variants of lysozyme give rise to aggregates, weighing up to several kilograms, that accumulate around the kidneys and liver, eventually leading to organ failure. In the third part of this thesis, a fly model for lysozyme amyloidosis was used to study the effect of co-expressing the serum amyloid P component (SAP), a protein that is part of all protein aggregates found within this disease class. SAP is able to rescue the toxicity induced by expressing the mutant variant of lysozyme, F57I, in the fly's CNS. To further investigate how SAP was able to do this, double-expressing lysozyme flies, which exhibit stronger disease phenotypes than those of the single-expressing lysozyme flies previously studied, were used in the fourth part of this thesis. SAP was observed to reduce F57I toxicity and promote F57I to form aggregates with more distinct amyloid characteristics. In conclusion, the work included in this thesis demonstrates that: i) Aβ generated from AβPP processing in the fly CNS results in higher proteotoxicity compared with direct expression of Aβ from the transgene, ii) lysozyme can prevent Aβ proteotoxicity in Drosophila and could thus be a potential therapeutic molecule to treat Alzheimer’s disease and iii) in a Drosophila model of lysozyme amyloidosis, SAP can prevent toxicity from the disease-associated lysozyme variant F57I and promote formation of aggregated lysozyme morphotypes with amyloid properties; this is important to take into account when a reduced level of SAP is considered as a treatment strategy for lysozyme amyloidosis.

X-ray lasers bring us into a new world in photon science by delivering extraordinarily intense beams of x-rays in very short bursts that can be more than ten billion times brighter than pulses from other x-ray sources. These lasers find applications in sciences ranging from astrophysics to structural biology, and could allow us to obtain images of single macromolecules when these are injected into the x-ray beam. A macromolecule injected into vacuum in a microdroplet will be affected by evaporation and by the dynamics of the carrier liquid before being hit by the x-ray pulse. Simulations of neutral and charged water droplets were performed to predict structural changes and changes of temperature due to evaporation. The results are discussed in the aspect of single molecule imaging. Further studies show ionization caused by the intense x-ray radiation. These simulations reveal the development of secondary electron cascades in water. Other studies show the development of these cascades in KI and CsI where experimental data exist. The results are in agreement with observation, and show the temporal, spatial and energetic evolution of secondary electron cascades in the sample. X-ray diffraction is sensitive to structural changes on the length scale of chemical bonds. Using a short infrared pump pulse to trigger structural changes, and a short x-ray pulse for probing it, these changes can be studied with a temporal resolution similar to the pulse lengths. Time resolved diffraction experiments were performed on a phase transition during resolidification of a non-thermally molten InSb crystal. The experiment reveals the dynamics of crystal regrowth. Computer simulations were performed on the infrared laser-induced melting of bulk ice, giving a comprehension of the dynamics and the wavelength dependence of melting. These studies form a basis for planning experiments with x-ray lasers.

Coherent diffractive imaging (CDI) has become a very popular technique over the past two decades. CDI is a "lensless" imaging method which replaces the objective lens of a conventional microscope by a computational image reconstruction procedure. Its increase in popularity came together with the development of X-ray free-electron lasers (XFELs) which produce extremely bright and coherent X-rays. By facilitating these unique properties, CDI enables structure determination of non-crystalline samples at nanometre resolution and has many applications in structural biology, material science and X-ray optics among others. This work focuses on two specific CDI techniques, flash X-ray diffractive imaging (FXI) on biological samples and X-ray ptychography. While the first FXI demonstrations using soft X-rays have been quite promising, they also revealed remaining technical challenges. FXI becomes even more demanding when approaching shorter wavelengths to allow subnanometre resolution imaging. We described one of the first FXI experiments using hard X-rays and characterized the most critical components of such an experiment, namely the properties of X-ray focus, sample delivery and detectors. Based on our findings, we discussed experimental and computational strategies for FXI to overcome its current difficulties and reach its full potential. We deposited the data in the Coherent X-ray Database (CXIDB) and made our data analysis code available in a public repository. We developed algorithms targeted towards the needs of FXI experiments and implemented a software package which enables the analysis of diffraction data in real time. X-ray ptychography has developed into a very useful tool for quantitative imaging of complex materials and has found applications in many areas. However, it involves a computational reconstruction step which can be slow. Therefore, we developed a fast GPU-based ptychographic solver and combined it with a framework for real-time data processing which already starts the ptychographic reconstruction process while data is still being collected. This provides immediate feedback to the user and allows high-throughput ptychographic imaging. Finally, we have used ptychographic imaging as a method to study the wavefront of a focused XFEL beam under typical FXI conditions.  We are convinced that this work on developing strategies and algorithms for FXI and ptychography is a valuable contribution to the development of coherent diffractive imaging.

Investigations of soft matter using ultrashort high intensity pulses have been made possible through the advent of X-ray free-electrons lasers. The last decade has seen the development of a new type of protein crystallography where femtosecond dynamics can be studied, and single particle imaging with atomic resolution is on the horizon. The pulses are so intense that any sample quickly turns into a plasma. This thesis studies the ultrafast transition from soft matter to warm dense matter, and the implications for structural determination of proteins.                    We use non-thermal plasma simulations to predict ultrafast structural and electron dynamics. Changes in atomic form factors due to the electronic state, and displacement as a function of temperature, are used to predict Bragg signal intensity in protein nanocrystals. The damage processes started by the pulse will gate the diffracted signal within the pulse duration, suggesting that long pulses are useful to study protein structure. This illustrates diffraction-before-destruction in crystallography. The effect from a varying temporal photon distribution within a pulse is also investigated. A well-defined initial front determines the quality of the diffracted signal. At lower intensities, the temporal shape of the X-ray pulse will affect the overall signal strength; at high intensities the signal level will be strongly dependent on the resolution. Water is routinely used to deliver biological samples into the X-ray beam. Structural dynamics in water exposed to intense X-rays were investigated with simulations and experiments. Using pulses of different duration, we found that non-thermal heating will affect the water structure on a time scale longer than 25 fs but shorter than 75 fs. Modeling suggests that a loss of long-range coordination of the solvation shells accounts for the observed decrease in scattering signal. The feasibility of using X-ray emission from plasma as an indicator for hits in serial diffraction experiments is studied. Specific line emission from sulfur at high X-ray energies is suitable for distinguishing spectral features from proteins, compared to emission from delivery liquids. We find that plasma emission continues long after the femtosecond pulse has ended, suggesting that spectrum-during-destruction could reveal information complementary to diffraction.

Viruses are entities which are made of a few genes and are reliant on obligate parasitism to propagate. Due to the obligate connection to their hosts, virus evolution is constrained to the type of host. Viruses however do transmit to evolutionary distinct hosts; in these cases, the phylogenetic relationship of the hosts usually are close. In some instances, RNA-viruses have made host jumps between evolutionary distant hosts, such as the host jump from invertebrates to vertebrates, and fungi to arthropod. Partitiviruses are double stranded RNA viruses which mainly infect fungi and plants. The defining characteristic of these double stranded RNA viruses are the double layered capsids which are formed by a single open reading frame (ORF). The capsid proteins form icosahedral virus particles which are in the magnitude of 30-40 nm. Metagenomic studies have discovered partitiviruses originating from an insect in the Odanata family, a finding which contradicts the fungal host specificity of partitiviruses. The finding of the Hubei.PLV 11 thus implies the existence of a partitiviruses containing structural elements in their capsids which could be involved in the infection of arthropods. Thus, this virus could be used as a model for a structural comparison with its fungi infecting relatives with hopes to identify common viral structural factors necessary for the infection of arthropods. For this purpose, the Hubei.PLV ORF was cloned and then transfected into insect Spodoptera frugiperda (Sf-9) cells using a baculovirus expression system, “bac-to-bac” expression system. The FLAG-tagged capsid proteins were expressed by the Sf-9 cells to be approximately 60 kDa. After ultra-centrifugation in a sucrose gradient, some spontaneous assembly into the expected ~40 nm icosahedral virus-like particles were observed using low resolution scanning electron microscopy. The observed particles were also confirmed by a dynamic light scattering experiment (DLS) and a higher resolution cryo-EM microscope. Thus, the bac-to-bac expression system can be used to produce VLPs from this genus of viruses, and this metagenomically derived virus genome. However, for future success in defining a high-resolution model of this virus, it is recommended that the Sf-9 culture volume is sufficiently high for enough particle production which is necessary for a high-resolution map. The other virus, the Southern pygmy squid Flavilike virus (SpSFV) has been suggested to be the oldest relative of the land based flaviviruses. The SpSFV was found to be the most divergent of the flaviviruses, and to infect invertebrates. Solving for the structure of the SpSFV and comparing it to vertebrate infecting flaviviruses could therefore lead to the identification of factors necessary for the adaptation to vertebrates and thus the humoral immunity by flaviviruses. The soluble E-protein was expressed using the bac-to-bac expression system. The protein was indicated to be multiglycosylated and approximately 50 kDa which is in line with other strains in the genus. Affinity chromatography did not elute this protein, likely due to the His-tag not being spatially available. Cation exchange could elute some protein, but not much from the small ~30 mL culture. To conclude, VLP assembly was confirmed by the Hubei.PLV, thus, solving for the structure is a distinct possibility when a larger Sf-9 culture is used to produce the VLPs. For the SpSFV soluble E-protein, the protein is secreted into the supernatant of the Sf-9 cultures, making purification a possibility. For this, a large Sf-9 culture can be used to produce this protein and then purify it with a cat-ion exchange chromatography.

Ligand-gated ion channels play an important role in electrochemical signal transduction across diverse organisms, yet their structural and functional intricacies are not fully understood. Particularly lacking is the knowledge of their response to variations in pH, an aspect necessary for understanding their physiological relevance and potential therapeutic targeting in neurological diseases. In this thesis project, I have investigated the mechanistic response of sTeLIC, a recently reported prokaryotic member of the pentameric ligand-gated ion channel family, to different environmental conditions. Using molecular dynamics simulations, a total of 16 different environmental conditions have been explored including variations in pH (neutral and alkaline), the presence and absence of calcium, and the inclusion of an electric field acting as an external driving force on charged atoms. The results reveal a comprehensive pH-sensing and gating mechanism involving key residues, notably E106 (on the β6 strand) and E160 (on loop F), and their local microenvironments. Additionally, an inhibitory mechanism for calcium is proposed, with E160 playing an important role. The simulations including an electric field has provided support for a non-conventional ion pathway through the pore. Collectively, these results offer insights into a mechanistic framework that may extend to other physiologically relevant systems, providing a foundation for further investigations and potential future therapeutic intervention. / pLGICs har en viktig roll i det elektrokemiska signalsystemet i många organismer, men detaljerna i deras struktur och framför allt funktion är fortfarande inte helt klargjorda. Särskilt är detaljerna kring deras reaktion på ändringar i pH-värde relativt okända, vilket är en viktig del i att förstå kanalernas fysiologiska roll och för att potentiellt hitta läkemedel mot neurologiska sjukdomar där dessa är inblandade. I det här arbetet har jag undersökt hur sTeLIC, som är ett nyligen publicerat bakteriellt protein i familjen pLGICs, reagerar på olika ändringar i miljön. Jag har använt molekyldynamiksimuleringar för att unders öka 16 olika miljöer med två olika pH-värden (neutralt och alkaliskt), med eller utan kalcium samt med eller utan en extern drivkraft över membranet i form av ett elektrisk fält. Arbetet har resulterat i en föreslagen mekanism förhur sTeLIC känner av pH och hur öppningen av kanalen går till. Denna mekanism involverar aminosyrorna E106, som finns på β6-strängen, och E160, som finns på F-loopen, samt deras omgivning. Dessutom har en modulatorisk mekanism föreslagits för en kalciuminhiberande effekt på sTeLIC som också involverar E160. Simuleringarna med en drivkraft över membranet har gett stöd för en ny väg för joner genom kanalen. Tillsammans ger dessa resultat insikt i en mekanism som eventuellt kan appliceras p ̊a andra system. Detta har lagt grunden för fortsatt undersökning som potentiellt kan leda till framtida läkemedelsutveckling inom området.