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The influence of LDL-apheresis on aggregation of blood platelets, blood coagulation, and the effect of standard drugs.
Černotová, Veronika ; Mladěnka, Přemysl (advisor) ; Čečková, Martina (referee)
Charles University Faculty of Pharmacy in Hradec Králové Department of Pharmacology & Toxicology Student: Veronika Černotová Supervisor: prof. Přemysl Mladěnka, PharmD., Ph.D. Consultant: Lukáš Konečný, MSc. Title of diploma thesis: The influence of LDL-apheresis on aggregation of blood platelets, blood coagulation and the effect of standard drugs LDL-apheresis is a method that removes LDL-cholesterol (LDL-C) from the blood. It is used to treat familial hypercholesterolemia (FH), a genetic disorder causing high LDL-C levels and an early development of cardiovascular diseases. Blood platelets and coagulation system play an important role in these diseases and their activity is also affected by lipids. The aim of this thesis was to analyze possible differences in platelet aggregation and blood coagulation in patients suffering from FH. Two methods of treatment in this group were compared - lipid apheresis and PCSK9Ab (proprotein convertase subtilisin/kexin type 9 monoclonal antibodies). The observed parameters were also compared with age-matched healthy volunteers. Our cohort consisted of 15 patients and 15 healthy donors. Six patients were treated with lipid apheresis and also PCSK9Ab, six subjects only with PCSK9Ab. Platelet aggregation was measured with an impedance aggregometer using 7 different...
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Comparison of platelet aggregation in healthy population.
Minarovičová, Júlia ; Mladěnka, Přemysl (advisor) ; Hofman, Jakub (referee)
Charles University Faculty of Pharmacy in Hradec Králové Department of Pharmacology & Toxicology Student: Júlia Minarovičová Supervisor: prof. Přemysl Mladěnka, Pharm.D., Ph.D. Title of diploma thesis: Comparison of platelet aggregation in healthy population Platelets have an irreplaceable role in the process of aggregation. Nevertheless, their increased activity is associated with the development of many cardiovascular diseases. This process can be influenced by clinical used substances from the group of antiplatelet drugs, which differ in their effectiveness within the population. Within this study, platelet aggregation was tested using impedance aggregometry, whose principle is the change in electrical impedance between electrodes caused by the adhesion of activated platelets. Firstly, whole blood was incubated with clinically used antiplatelet drugs (ticagrelor, vorapaxar, and acetylsalicylic acid) and a flavonoid metabolite, 4-methylcatechol. Subsequently, a platelet aggregation inducer (ADP, thrombin receptor activating peptide 6 /TRAP/, collagen, arachidonic acid, ristocetin, U-46619, and platelet-activating factor /PAF/) was added, and the process was monitored for 6 minutes. The most potent inhibitor of the aggregation induced by arachidonic acid was acetylsalicylic acid in a concentration of 70 μM...
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TTP protocol for managing hierarchy trees of RTCP feedback channel
Müller, Jakub ; Komosný, Dan (referee) ; Burget, Radim (advisor)
TTP protocol for managing hierarchy trees of the RTCP feedback channel represents the mechanism for transferring the big amount of data from end users via the “narrow” feedback channel. We are not speaking about thousands of users but about millions of users, which are using services like IPTV. The method of a data summarization is used for this purpose in selected network nodes. The summarized message is transferred and summarized again in higher levels of the hierarchical tree. Both methods allow reducing the amount of data and help to increase information content transferred via the feedback channel. Finding of the correct end user position in a network is also very important aspect. The user must be able to find the closest summarization node with this information and starts sending out the messages to this node for processing. There are several methods for constructing and managing the asynchronous feedback channel that are introduced in this work.
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Adaptive Sampling of Input Packets Implemented in FlowMon Probe
Kaštovský, Petr ; Martínek, Tomáš (referee) ; Kořenek, Jan (advisor)
There is a FlowMon probe being developed in a Libeouter project that is used for passive network measurements. The probe has better stability and accuracy than sofware based solutions even under a heavy load or network attack. To guarantee a precision of results there is a need to data reduction to prevent measuring system overload. There are few kinds of data reduction. Method used in the FlowMon probe is called sampling. Adaptive sampling unit sets the sampling rate (rate of processed and discarded packets) according to actual state of measured network.
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Data flow control in ISP network
Důbrava, Marek ; Jeřábek, Jan (referee) ; Koton, Jaroslav (advisor)
The thesis focuses on the control of data flow in networks of Internet service providers. The problem of aggregation and related overload network elements are shown. Theoretical section describes the standardized methods for managing data flow. The parameters associated with managing data flow are described for devices selected devices. The thesis displays measurements depicting to which extent the ECN algorithm occurs in practice. In the thesis is theoretically described HTB program, which is complemented by a newly described algorithm. The new algorithm is implemented into the program and tested on a real network ISP.
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Prediction of the Effect of Mutation on Protein Solubility
Velecký, Jan ; Martínek, Tomáš (referee) ; Hon, Jiří (advisor)
The goal of the thesis is to create a predictor of the effect of a mutation on protein solubility given its initial 3D structure. Protein solubility prediction is a bioinformatics problem which is still considered unsolved. Especially a prediction using a 3D structure has not gained much attention yet. A relevant knowledge about proteins, protein solubility and existing predictors is included in the text. The principle of the designed predictor is inspired by the Surface Patches article and therefore it also aims to validate the results achieved by its authors. The designed tool uses changes of positive regions of the electric potential above the protein's surface to make a prediction. The tool has been successfully implemented and series of computationally expensive experiments have been performed. It was shown that the electric potential, hence the predictor itself too, can be successfully used just for a limited set of proteins. On top of that, the method used in the article correlates with a much simpler variable - the protein's net charge.
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Removal of micropolutants in drinking water treatment
Hambálková, Kateřina ; Vávrová, Milada (referee) ; Dolejš, Petr (advisor)
Intrusion of pharmaceuticals into surface and drinking water is nowadays a problem, that is solved all over the world. This diploma thesis is focused on the removal of pharmaceuticals from water by coagulation. The efficiency of two coagulant agents - chitosan and ferric sulphate was compared. For comparison was used adsorption on a granular-activated-carbon. Efficiency of removal was investigated by UV-VIS spectrophotometer and HPLC.
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Deep Learning for Facial Recognition in Video
Jeřábek, Vladimír ; Sochor, Jakub (referee) ; Hradiš, Michal (advisor)
This work deals with face recognition in video using neural networks. In the beginning, there is described the process of selection and verification of convolution neural network to generate feature vectors from images of different identities. In the next part, this work deals with the aggregation of feature vectors from video frames. Aggregation takes place through aggregation neural networks. At the end of this work, the results obtained by the aggregation methods are discussed.
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Deep Learning for Facial Recognition in Video
Stratil, Jan ; Sochor, Jakub (referee) ; Hradiš, Michal (advisor)
This bachelor's thesis deals with facial recognition in video using deep neural networks. This task is split into 2 parts. The first part deals with training network that produces compact feature vector which represents the face identity from a video frame. The second part deals with training aggregation network that aggregates those feature vectors into one. This aggregation is fast and it has shown that its results are better than naive pooling methods. Results are tested on the LFW dataset, where it achieves 92.8% accuracy and on the YTF dataset, where the accuracy is 84.06%.
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