Background The recently postulated “disease spreading hypothesis” has gained much attention, especially for Parkinson’s disease (PD). The various non-motor symptoms (NMS) in neurodegenerative diseases would be much better explained by this hypothesis than by the degeneration of disease-specific cell populations. Motor neuron disease (MND) is primarily known as a group of diseases with a selective loss of motor function. However, recent evidence suggests disease spreading into non-motor brain regions also in MND. The aim of this study was to comprehensively detect NMS in patients suffering from MND. Methods We used a self-rating questionnaire including 30 different items of gastrointestinal, autonomic, neuropsychiatric, and sleep complaints [NMS questionnaire (NMSQuest)], which is an established tool in PD patients. 90 MND patients were included and compared to 96 controls. Results In total, MND patients reported significantly higher NMS scores (median: 7 points) in comparison to controls (median: 4 points). Dribbling, impaired taste/smelling, impaired swallowing, weight loss, loss of interest, sad/blues, falling, and insomnia were significantly more prevalent in MND patients compared to controls. Interestingly, excessive sweating was more reported in the MND group. Correlation analysis revealed an increase of total NMS score with disease progression. Conclusion NMS in MND patients seemed to increase with disease progression, which would fit with the recently postulated “disease spreading hypothesis.” The total NMS score in the MND group significantly exceeded the score for the control group, but only 8 of the 30 single complaints of the NMSQuest were significantly more often reported by MND patients. Dribbling, impaired swallowing, weight loss, and falling could primarily be connected to motor neuron degeneration and declared as motor symptoms in MND.

This thesis addresses chemotherapy-induced peripheral neuropathy (CIPN)- a form of pain sensation and a prevalent dose-limiting side-effect of several chemotherapy agents such as vincristine, paclitaxel, and oxaliplatin. These agents are used for treating various cancers such as leukemia, brain tumor, lung cancer. Peripheral neuropathy is a numbing, tingling, and burning sensation felt in the palms and feet, which occurs due to damage to neurons (nerve cells). Prolonged CIPN can impact the quality of life of cancer patients. Occasionally, severe CIPN can result in termination of chemotherapy treatment altogether. Currently, there are no established strategies for treating CIPN due to a lack of understanding of its mechanisms. Moreover, different patients react differently to the same treatment; a subgroup of patient population may never experience CIPN, while another may experience severe CIPN for the same dose. In addition, there are no established strategies for predicting CIPN either. This thesis addresses both prediction and mechanisms of CIPN.<br><br>The following paragraphs reflect the organization of this thesis. Each paragraph introduces a research problem, the approaches taken to investigate it, and states the key results.<br><br>First, a metabolomics-based approach was used to investigate CIPN prediction. Blood samples of pediatric leukemic cancer patients who underwent treatment with a chemotherapy agent - vincristine were provided. These blood samples were analyzed at different treatment time points using mass spectrometry to obtain the metabolite profiles. Machine learning was then employed to identify specific metabolites that can predict overall susceptibility to peripheral neuropathy in those patients at specific treatment time points. Subsequently, selected metabolites were used to train machine learning models to predict neuropathy susceptibility. Finally, the models were deployed into an open-source interactive tool- <i>VIPNp</i>- that can be used by researchers to predict CIPN in new pediatric leukemic cancer patients.<br><br>Second, the focus was shifted to the pathophysiology of pain and the pain-sensing neuron; specifically: (i) investigating pain sensation mutations and the dynamics of the pain-sensing neuron, and (ii) exploring chemotherapy-induced peripheral neuropathy mechanisms. <br><br>While pain is a common experience, genetic mutations in individuals can alter their experience of pain, if any at all (certain mutations yield individuals insensitive to pain). Despite its ubiquity, we do not have a complete understanding of the onset and/or mechanisms of pain sensation. Pain sensation can be broadly classified into three types: (i) nociceptive, (ii) neuropathic, and (iii) inflammatory. Nociceptive pain arises due to a noxious external stimulus (e.g., upon touching a hot object). Neuropathic pain (which is felt as a side-effect of the aforementioned chemotherapy agents) is the numbing and tingling sensation due to nerve damage. Inflammatory pain occurs due to damage to internal tissues. Pain in any form can be characterized in terms of electrical signaling by the pain-sensing neuron. Signal transmission regarding pain occurs through generation of an electrical signal called the action potential- a peak in neuron membrane potential. Excessive firing of action potentials by a pain-sensing neuron indicates pain of a specific form and intensity. In order to investigate this electrical signaling, a mathematical modeling approach was employed. The neuron membrane was assumed to be an electrical circuit and the potential across the membrane was modeled in terms of the sodium and potassium ions flowing across it via voltage-gated sodium and potassium channels, respectively. Generation of a single action potential followed by a resting state corresponds to a normal state, whereas periodic firing of action potentials (an oscillatory state) corresponds to pain of some form and intensity <i>in vitro</i>. Therefore, an investigation into the switch from a resting state to an oscillatory state was proposed. A bifurcation theory approach (generally useful in exploring changes in qualitative behavior of a model) was used to explore possible bifurcations to explain this switch. Firstly, genetic mutations that can shift the pain sensation threshold in the pain-sensing neuron were explored. The detected bifurcation points were found to be sensitive to specific sodium channels’ model parameters, implying sodium channels’ sensitivity towards the pain sensation threshold. This was corroborated by experimental evidence in existing literature. Secondly, a theoretical analysis was performed to explore all possible bifurcations that can explain the dynamics of this pain-sensing neuron model. The mathematical modeling simulations revealed a mixture of small amplitude and large amplitude membrane potential oscillations (mixed-mode oscillations) for specific parameter values. The onset and disappearance of the oscillations were investigated. Model simulations further demonstrated that the mixed-mode oscillations solutions belonged to Farey sequences. Furthermore, regions of bistability- where stable steady state and periodic solutions coexisted- were explored. Additionally, chaotic behavior was observed for specific model parameters.<br><br>Finally, this thesis investigated the role of voltage-gated ion channels in inducing CIPN using the same mathematical model. Repetitive firing of action potentials in the absence of any external stimulus was used as an indicator of peripheral neuropathy. Bifurcation analysis revealed that specific sodium and potassium conductances can induce repetitive firing without any external stimulus. The findings were supplemented by recording the firing rate of a sensory neuron culture. Next, a chemotherapy agent - paclitaxel, was introduced in the model to investigate its potential effects on the firing behavior. It was seen that a medium dose of paclitaxel increased repetitive firing. This was supported by the firing rate recordings of the sensory neuron culture.<br><br>In summary, this thesis presents a prediction strategy for CIPN. Moreover, it presents a bifurcation theory-based framework that can be used to investigate pain sensation, in particular, genetic mutations related to pain sensation and chemotherapy-induced peripheral neuropathy. This framework can be used to find potential voltage-gated ion channels that can be targeted to control the pain sensation threshold in individuals, and can be extended to investigate various degeneracies in CIPN mechanisms to find therapeutic cures for it.

Many people with the incurable and often times fatal motor neuron diseases have pain, but there is lack of knowledge about people’s experiences of living with pain. Further, the correlation between pain and their quality of life is not well understood, and previous studies have not used individual quality of life, namely that people with their own words express what quality of life is.   The aim of these studies was to explore the experiences of pain and the association between pain and quality of life in people with MND. Methods: Study I was explorative about the individual experience of pain, while study II was correlational between pain, pain severity, disease severity and IQOL. Study I was qualitative, whereas study II used both qualitative and quantitative analysis. Results and conclusions: People with motor neuron diseases experienced pain to have multiple characteristics and impact. However, the results emphasise that the individual experienced some pain characteristics as difficult and that pain could worsen functions that were already affected by the disease. The experience was also that it could be challenging to manage pain. However, the symptom of pain could pass unnoticed in contacts with healthcare professionals (study I). The three most important areas for individual quality of life in both participants with and without pain were: Social relations, followed by Activities for amusement and relaxations, and Being in the outdoor environment. Individual quality of life was noticed to be good regardless of pain. Pain and pain severity were not found to be associated with satisfaction of individual quality of life in patients with motor neuron diseases, neither was disease severity. The results support previous findings, that strong associations between symptoms of MND and IQoL are not obvious. However, this does not infer that pain in people with MNDs should be neglected and undertreated. On the contrary, it seems to be important for healthcare to pay more attention to pain in people with motor neuron diseases and that pain continuously is measured, individually treated and followed. Regardless of whether persons with MND have pain or not, the results point to the importance of healthcare professionals providing support to not only the patient but also the patient’s family and friends, as well as assisting in various forms of relaxing activities and possibility of being in the outdoor environment.

Background The recently postulated “disease spreading hypothesis” has gained much attention, especially for Parkinson’s disease (PD). The various non-motor symptoms (NMS) in neurodegenerative diseases would be much better explained by this hypothesis than by the degeneration of disease-specific cell populations. Motor neuron disease (MND) is primarily known as a group of diseases with a selective loss of motor function. However, recent evidence suggests disease spreading into non-motor brain regions also in MND. The aim of this study was to comprehensively detect NMS in patients suffering from MND. Methods We used a self-rating questionnaire including 30 different items of gastrointestinal, autonomic, neuropsychiatric, and sleep complaints [NMS questionnaire (NMSQuest)], which is an established tool in PD patients. 90 MND patients were included and compared to 96 controls. Results In total, MND patients reported significantly higher NMS scores (median: 7 points) in comparison to controls (median: 4 points). Dribbling, impaired taste/smelling, impaired swallowing, weight loss, loss of interest, sad/blues, falling, and insomnia were significantly more prevalent in MND patients compared to controls. Interestingly, excessive sweating was more reported in the MND group. Correlation analysis revealed an increase of total NMS score with disease progression. Conclusion NMS in MND patients seemed to increase with disease progression, which would fit with the recently postulated “disease spreading hypothesis.” The total NMS score in the MND group significantly exceeded the score for the control group, but only 8 of the 30 single complaints of the NMSQuest were significantly more often reported by MND patients. Dribbling, impaired swallowing, weight loss, and falling could primarily be connected to motor neuron degeneration and declared as motor symptoms in MND.

This paper introduces Bayesian neural network based on Occams razor. Basic knowledge about neural networks and Bayes rule is summarized in the first part of this paper. Principles of Occams razor and Bayesian neural network are explained. A real case of use is introduced (about predicting landslide). The second part of this paper introduces how to construct Bayesian neural network in Python. Such an application is shown. Typical behaviour of Bayesian neural networks is demonstrated using example data.

V rámci této práce byl vytvořen popis bezdrátového komunikačního protokolu Wireless M-Bus, zaměřující se zejména na datovou část tohoto protokolu, strukturu jeho informačních polí, režimy komunikace a další specifika linkové a aplikační vrstvy. Na základě tohoto výzkumu byl vytvořen softwarový nástroj v jazyce Java, sloužící jako generátor dat zmíněného protokolu. Pomocí grafického i textového uživatelského rozhraní program umožňuje uživateli vytvořit Wireless M-Bus telegramy s velmi vysokou úrovní detailu a ty následně s využitím některého z podporovaných hardwarových zařízení periodicky odesílat do Wireless M-Bus sítě. Dále byla navržena dvě kompletní řešení, využívající buď samotného bezdrátového IQRF modulu nebo jeho spojení s řídicí deskou UniPi Neuron. Oba návrhy byly zrealizovány, otestovány a jsou v práci detailně popsány.

This diploma thesis deals with the application of deep neural networks with focus on image segmentation. The theoretical part contains a description of deep neural networks and a summary of widely used convolutional architectures for segmentation of objects from the image. Practical part of the work was devoted to testing of an existing network architectures. For this purpose, an open-source software library Tensorflow, implemented in Python programming language, was used. A frequent problem incorporating the use of convolutional neural networks is the requirement on large amount of input data. In order to overcome this obstacle a new data set, consisting of a combination of five freely available databases was created. The selected U-net network architecture was tested by first modification of the newly created data set. Based on the test results, the chosen network architecture has been modified. By these means a new network has been created achieving better performance in comparison to the original network. The modified architecture is then trained on a newly created data set, that contains images of different types taken with various fundus cameras. As a result, the trained network is more robust and allows segmentation of retina blood vessels from images with different parameters. The modified architecture was tested on the STARE, CHASE, and HRF databases. Results were compared with published segmentation methods from literature, which are based on convolutional neural networks, as well as classical segmentation methods. The created network shows a high success rate of retina blood vessels segmentation comparable to state-of-the-art methods.

This master´s thesis deals with blood vessel segmentation in retinal image data. The theoretical part is focused on the basic description of anatomy and physiology of the eye and methods of observing the back of the eye. This thesis also describes the principles of classical and convolutional neural networks and segmentation techniques that are used to segment blood vessel in retinal images. In the practical part, a segmentation method using convolutional neural network U-net is implemented. This neural network is trained on the three datasets. Two datasets include images from experimental video ophthalmoscope. Because it impossible to compare the results of these two datasets with any other methods of retinal blood vessel segmentation, U-net is trained on other dataset that is HRF database. This dataset includes fundus images. The results of testing on this dataset serves for comparing results with other methods of retinal blood vessel segmentation.

This Master’s Thesis consists of description of current routing protocols and routers, basic principles of neural networks and their interpretation in connection with the use for routing in data networks and telecommunications networks. In the thesis I focused on neural networks, which use energetic functions to find solution stabled states and their use for data routing. I produced the application software to test and find suitable variables for each function. This application counts the shortest path and is able to change variables to reach the best solution of stabled state of neural network. These solutions are compared with other functions that are usually used in nowadays systems for data network routing.

The main task of the Master Thesis is introduction into problems of quality of service in converged networks especially with use of IP protocol version 6. Converged networks are able to transfer different data types - voice, data or multimedia stream. Design of active network unit is realized in Matlab Simulink. Designed model consists of simple network with some computer terminals which are connected with network element - switch. Switch model simulates real traffic of computer terminals, that are sending data to remote users. Packets in switch are sorting by data stream type and QoS. Switch is managed by neuron network. Neuron network reacts to input data and controls switch depending on type of recipient. Switch model can be used in laboratory exercising. Solving this theme needs basic skill in Simulink and theme can be done in one laboratory exercise.