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Biology can often be explained by structures and interactions between molecules. It is therefore of importance for medical sciences that the chemical reactions and molecular compositions of biological samples can be measured. The purpose of this thesis is twofold. Firstly, to develop methods for measuring the underlying mechanisms of the lung disorder pulmonary hypertension. Secondly, to investigating the possibility of classifying brain tissue for safer resection of brain tumors. A multimodal approach is often motivated, as there exist many different measurement techniques. In this thesis Raman spectroscopy has been applied both as the main measurement modality and in cooperation with other methods. Raman spectroscopy is a label free optical measurement technique that measure inelastic scattering from materials that are illuminated by a monochromatic light source. Raman scattering results in a weak signal that is uniquely proportional to the chemical structure of the sample. When measuring biological samples, Raman scattering is accompanied by a strong intrinsic fluorescent signature that can overshadow the signal. To elucidate the underlying Raman spectrum, it is generally preprocessed to allow further analysis. There are many methods available for preprocessing; a selection of commonly used methodologies has been included here, as well as methods of my own design. The most novel approach being a neural network that was trained on synthetic spectra to perform preprocessing without relying on user defined variables, which is common for other methods (Paper A). The neural network resulted in improved preprocessing when compared to a control predictor, with test data from paraffin, ethanol, and polyethylene, as well as spectra based on simulations. Hypoxic pulmonary hypertension (PH) is a condition where the arteries in the lung-walls are blocked due to prolonged oxygen deprivation or lung disease. People who suffer from PH, often experience shortness of breath and fatigue. If the condition persists the added strain upon the heart from the increased resistance in the arteries will result in right-heart failure. Hypoxic PH is the result of permanently constricted pulmonary arterial smooth muscle cells (PASMCs). PASMCs reside in the arterial walls and react locally to reduced oxygen content by constricting. This effect is called pulmonary vasoconstriction (HPV) and results in the regulation of deoxygenated blood to areas of the lung that have more oxygen available. Full understanding of the mechanisms of oxygen sensing in PASMCs has importance for the development of new treatments against PH. To this end a sealed microfluidic system was designed with the purpose to enable multimodal measurements of the response of cultivated PASMCs to acute hypoxia including Raman spectroscopy, patch clamp, and imaging (Paper B). The microfluidic system was initially tested using Raman spectroscopy and oxygen sensing to investigate the reaction of PASMCs to hypoxia. The results were compared to an open flow system that showed a higher variation of the desired oxygen content (21% or 4%) compared to the designed closed microfluidic system. The system was later reworked and tested with simultaneous measurements using Raman spectroscopy, oxygen sensing, imaging, and patch-clamp (Paper C). With this setup it was possible to track the molecular response in the mitochondria in correlation with the activity of the calcium-ion channels and the mechanical response of the PASMCs. The main modality used in clinics for brain tumor imaging is magnetic resonance imaging (MRI). Structural MRI gives neurosurgeons information regarding the size and mass effects of tumors. However, during surgery it can be difficult to assess the marginal zone of tumors. Improvements have been made by incorporating fluorescence guided resection (FGR) in the standard practice of many operating rooms in Europe. FGR relies on measuring the emission from metabolized precursor molecules. However, the drawback of FGR is that it is not tumor specific and has reduced sensitivity in low-grade tumors and children. In this thesis the option of incorporating a Raman probe setup, to fill in the gaps of other methods has been discussed. During this preliminary discussion it was noted that there is no standard approach for preprocessing and many different methodologies have been employed by various researcher. Therefore, measurement on fresh brain tumor tissue from a Raman microscopy setup was preprocessed using commonly applied methods, in addition to a pretrained neural network, to investigate the variations of the outcome (Paper D). It became apparent that different methods and variable choices can alter the distinctive spectral features. The conclusion being that it is important to be both transparent and specific when explaining how data has been prepared prior to analysis to enable reproducible results.

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Delineating cancer tissue while leaving functional tissue intact is crucial in brain tumor resection. Despite several available aids, surgeons are limited by preoperative or subjective tools. Raman spectroscopy is a label-free optical technique with promising indications for tumor tissue identification. To allow direct comparisons between measurements preprocessing of the Raman signal is required. There are many recognized methods for preprocessing Raman spectra; however, there is no universal standard. In this paper, six different preprocessing methods were tested on Raman spectra (n > 900) from fresh brain tissue samples (n = 34). The sample cohort included both primary brain tumors, such as adult-type diffuse gliomas and meningiomas, as well as metastases of breast cancer. Each tissue sample was classified according to the CNS WHO 2021 guidelines. The six methods include both direct and iterative polynomial fitting, mathematical morphology, signal derivative, commercial software, and a neural network. Data exploration was performed using principal component analysis, t-distributed stochastic neighbor embedding, and k-means clustering. For each of the six methods, the parameter combination that explained the most variance in the data, i.e., resulting in the highest Gap-statistic, was chosen and compared to the other five methods. Depending on the preprocessing method, the resulting clusters varied in number, size, and associated spectral features. The detected features were associated with hemoglobin, neuroglobin, carotenoid, water, and protoporphyrin, as well as proteins and lipids. However, the spectral features seen in the Raman spectra could not be unambiguously assigned to tissue labels, regardless of preprocessing method. We have illustrated that depending on the chosen preprocessing method, the spectral appearance of Raman features from brain tumor tissue can change. Therefore, we argue both for caution in comparing spectral features from different Raman studies, as well as the importance of transparency of methodology and implementation of the preprocessing. As discussed in this study, Raman spectroscopy for in vivo guidance in neurosurgery requires fast and adaptive preprocessing. On this basis, a pre-trained neural network appears to be a promising approach for the operating room. Funding Agencies|Swedish Foundation for Strategic Research; [RMX18-0056]

The aim of this thesis is to quantify the contributions of water thermodynamics to the binding free energy in protein-ligand complexes. Various computational tools were directly applied, implemented, benchmarked and discussed. An own implementation of the IFST formulation was developed to facilitate easy integration in workflows that are based on Schrödinger software. By applying the tool to a well-defined test set of congeneric ligand pairs, the potential of IFST for quantitative predictions in lead-optimization was assessed. Furthermore, FEP calculations were applied to an extended test set to validate if these simulations can accurately account for solvent displacement in ligand modifications. As a fast tool that has applications in virtual screening problems, we finally developed and validated a new scoring function that incorporates terms for protein and ligand desolvation. This resulted in total in three distinct studies, that all elucidated different aspects of water thermodynamics in CADD. These three studies are presented in the next section. In the conclusion, the results and implications of these studies are discussed jointly, as well with possible future developments. An additional study was focused on virtual screening and toxicity prediction at the androgen receptor, where distinguishing agonists and antagonists poses difficulties. We proposed and validated an approach based on MD simulations and ensemble docking to improve predictions of androgen agonists and antagonists.

Hypoxic pulmonary vasoconstriction (HPV) is a physiological response to localized alveolarhypoxia that is intrinsic to the pulmonary circulation. By hypoxia-induced contractionof pulmonary arterial smooth muscle cells (PASMCs), the pulmonary capillary bloodflow is redirected to alveolar areas of high oxygen partial pressure, thus maintaining theventilation-perfusion ratio. Although the principle of HPV was recognized decades agothe underlying pathway remains elusive. The patch clamp technique, imaging and Ramanspectroscopy are methods that can be used to investigate parts of the mechanisms. Toenable measurements at controlled oxygen concentrations a gas-tight microfluidic systemwas developed. In this thesis preparatory experiments to couple the gas-tight systemto a microscope that enabled simultaneous measurements with patch clamp, imagingand Raman spectroscopy are discussed. The patch clamp technique is to be used formeasurements on the dynamics of the ion-channels in the cellular membrane as well aschanges in membrane potential as a response to hypoxia. Imaging of PASMCs is requiredto successfully apply the patch clamp technique. Further, imaging will also reveal whetherthe mechanical response of HPV has been triggered, for this purpose image analysis forestimation of optical flow can be used. Raman spectroscopy enables measurements ofbiochemical changes in redox biomarkers, cytochrome c and NADH, of the mitochondrialelectron transport chain. This thesis shows that the gas-tight microfluidic system providesoptimal control of the oxygen content, in an experimantal setting where the patch clamptechnique can be applied. Raman measurements showed significantly larger variationsin spectra compared to an open fluidic system, which is the conventional approach.However, the results showed a need for improved Raman preprocessing. For this purposea Convolutional Neural Network (CNN) was trained using synthetic spectra that providedoptimal reconstruction of the Raman signal. Finally, simultaneous imaging and Ramanspectroscopy of red blood cells were performed in a home built microscope. The resultspave the way for measurements on PASMCs.

Acute hypoxia changes the redox-state of pulmonary arterial smooth muscle cells (PASMCs). This might influence the activity of redox-sensitive voltage-gated K+-channels (Kv-channels) whose inhibition initiates hypoxic pulmonary vasoconstriction (HPV). However, the molecular mechanism of how hypoxia&mdash, or the subsequent change in the cellular redox-state&mdash, inhibits Kv-channels remains elusive. For this purpose, a new multifunctional gas-tight microfluidic system was developed enabling simultaneous single-cell Raman spectroscopic studies (to sense the redox-state under normoxic/hypoxic conditions) and patch-clamp experiments (to study the Kv-channel activity). The performance of the system was tested by optically recording the O2-content and taking Raman spectra on murine PASMCs under normoxic/hypoxic conditions or in the presence of H2O2. Oxygen sensing showed that hypoxic levels in the gas-tight microfluidic system were achieved faster, more stable and significantly lower compared to a conventional open system (1.6 &plusmn, 0.2%, respectively 6.7 &plusmn, 0.7%, n = 6, p &lt, 0.001). Raman spectra revealed that the redistribution of biomarkers (cytochromes, FeS, myoglobin and NADH) under hypoxic/normoxic conditions were improved in the gas-tight microfluidic system (p-values from 0.00% to 16.30%) compared to the open system (p-value from 0.01% to 98.42%). In conclusion, the new redox sensor holds promise for future experiments that may elucidate the role of Kv-channels during HPV.

This report is a master thesis, written by an engineering physics and electrical engineering student at Luleå University of Technology.The desires of this project was to remove dislocations from wrapped phase maps using sparse reconstructive methods. Dislocations is an error that can appear in phase maps due to improper filtering or inadequate sampling. Dislocations makes it impossible to correctly unwrap the phasemap.The report contains a mathematical description of a sparse reconstructive method. The sparse reconstructive method is based on KSVDbox which was created by R. Rubinstein and is free for download and use. The KSVDbox is a MATLAB implementation of a dictionary learning algorithm called K-SVD with Orthogonal Matching Pursuit and a sparse reconstructive algorithm. A guide for adapting the toolbox for inpainting is included, with a couple of examples on natural images which supports the suggested adaptation. For experimental purposes a set of simulated wrapped phase maps with and without disloca-tions were created. These simulated phase maps are based on work by P. Picart. The MATLAB implementation that was used to generate these test images can be found in the appendix of this report such that they can easily be generated by anyone who has the interest to do so. Finally the report leads to an outline of five different experiments that was designed to test the KSVDbox for the processing of dislocations. Each one of these experiments uses a different dictionary. These experiments are due to inpainting with, 1. A dictionary based on Discrete Cosine Transform. 2. An adaptive dictionary, where the dictionary learning algorithm has been shown what thearea in the phase map that was damaged by dislocations should look like. 3. An adaptive dictionary, where the dictionary learning algorithm has been allowed to trainon the phase map that with damages. This is done such that areas with dislocations areignored. 4. An adaptive dictionary, where training is done on a separate image that has been designedto contain general phase patterns. 5. An adaptive dictionary, that results from concatenating the dictionaries used in experiment 3 and 4. The first three experiments are complimented with experiments done on a natural image for comparison purposes.The results show that sparse reconstructive methods, when using the scheme used in this work, is unsuitable for processing of dislocations in phase maps. This is most likely because the reconstructive method has difficulties in acquiring a high contrast reconstruction and there is nothing in the algorithm that causes the inpainting from any direction to match with the inpainting from other directions.