The quality of data measured in in vivo MR spectroscopy is often insufficient due to a number of limitations such as low concentrations of observed metabolites and restricted measurement time resulting in a low signal-to-noise ratio. However, there are a variety of methods called post-processing techniques which allow the enhancement of the measured signal after measurement. In this review an introduction to the most important post-processing techniques for (1)H MR spectroscopy is given and practical examples are shown. In the first section the concept of FID and spectrum is introduced and the relationship between FID and spectrum is explained. Subsequently, the objectives and description of the following post-processing techniques are provided: eddy current correction, removal of an unwanted component (water), signal filtering for various purposes, zero filling, phase correction and baseline correction.

• MeSH
• algoritmy MeSH
• artefakty MeSH
• lidé MeSH
• magnetická rezonanční spektroskopie metody   MeSH
• počítačové zpracování obrazu metody   MeSH
• počítačové zpracování signálu * MeSH
• tělesná voda metabolismus   MeSH
• vylepšení obrazu metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

Processing of rRNA in mammalian cells includes a series of cleavages of the primary 47S transcript and results in producing three rRNAs: 18S, 28S and 5.8S. The sequence of the main processing events in human cells has been established, but little is yet known about the dynamics of this process, especially the dynamics of its early stages. In the present study, we used real-time PCR to measure levels of pre-rRNA after inhibition of transcription with actinomycin D. Thus we could estimate the half-life time of rRNA transcripts in two human-derived cell lines, HeLa and LEP (human embryonic fibroblasts), as well as in mouse NIH 3T3 cells. The primary transcripts seemed to be more stable in the human than in the murine cells. Remarkably, the graphs in all cases showed more or less pronounced lag phase, which may reflect preparatory events preceding the first cleavage of the pre-rRNA. Additionally, we followed the dynamics of the decay of the 5'ETS fragment which is degraded only after the formation of 41S rRNA. According to our estimates, the corresponding three (or four) steps of the processing in human cells take five to eight minutes.

• Klíčová slova
• cleavage, half-life time, human, mouse, primary transcript, rRNA processing,
• MeSH
• buňky NIH 3T3 MeSH
• daktinomycin farmakologie   MeSH
• genetická transkripce účinky léků   MeSH
• HeLa buňky MeSH
• lidé MeSH
• myši MeSH
• posttranskripční úpravy RNA genetika   MeSH
• prekurzory RNA * genetika   metabolismus   MeSH
• RNA ribozomální genetika   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• myši MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• daktinomycin MeSH
• prekurzory RNA * MeSH
• RNA ribozomální MeSH

• Klíčová slova
• AUTOMATIC DATA PROCESSING *, LANGUAGE *, THINKING *,
• MeSH
• automatizované zpracování dat * MeSH
• duševní procesy * MeSH
• jazyk (prostředek komunikace) * MeSH
• lidé MeSH
• myšlení * MeSH
• signální transdukce * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Proton magnetic resonance spectroscopy is a non-invasive measurement technique which provides information about concentrations of up to 20 metabolites participating in intracellular biochemical processes. In order to obtain any metabolic information from measured spectra a processing should be done in specialized software, like jMRUI. The processing is interactive and complex and often requires many trials before obtaining a correct result. This paper proposes a jMRUI enhancement for efficient and unambiguous history tracking and file identification. RESULTS: A database storing all processing steps, parameters and files used in processing was developed for jMRUI. The solution was developed in Java, authors used a SQL database for robust storage of parameters and SHA-256 hash code for unambiguous file identification. The developed system was integrated directly in jMRUI and it will be publically available. A graphical user interface was implemented in order to make the user experience more comfortable. The database operation is invisible from the point of view of the common user, all tracking operations are performed in the background. CONCLUSIONS: The implemented jMRUI database is a tool that can significantly help the user to track the processing history performed on data in jMRUI. The created tool is oriented to be user-friendly, robust and easy to use. The database GUI allows the user to browse the whole processing history of a selected file and learn e.g. what processing lead to the results, where the original data are stored, to obtain the list of all processing actions performed on spectra.

• Klíčová slova
• Magnetic Resonance Spectroscopy, SQL database, Signal Processing, jMRUI,
• MeSH
• algoritmy MeSH
• automatizované zpracování dat * MeSH
• databáze faktografické MeSH
• magnetická rezonanční spektroskopie * MeSH
• magnetická rezonanční tomografie * MeSH
• reprodukovatelnost výsledků MeSH
• software * MeSH
• Publikační typ
• časopisecké články MeSH

Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).

• Klíčová slova
• biomedical signals, electrogastrography, electrohysterography, electromyography, electroneurography, electrooculography, electroretinography, signal processing,
• MeSH
• elektromyografie MeSH
• elektrookulografie MeSH
• elektroretinografie * MeSH
• počítačové zpracování signálu * MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

• MeSH
• algoritmy MeSH
• elektroencefalografie MeSH
• lidé MeSH
• mozek fyziologie   MeSH
• počítačové zpracování signálu MeSH
• prostorové chování fyziologie   MeSH
• shluková analýza MeSH
• vnímání prostoru fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

• Klíčová slova
• digital signal processing, fetal electrocardiogram extraction, fetal monitoring, non-adaptive filtering,
• MeSH
• algoritmy MeSH
• analýza hlavních komponent MeSH
• elektrody MeSH
• elektrokardiografie metody   MeSH
• lidé MeSH
• plod fyziologie   MeSH
• počítačové zpracování signálu * MeSH
• vlnková analýza MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

As it was mentioned in the previous part of this work (Part I)-the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their increasing usage in current clinical practice. In this paper, which is a Part II work-various innovative methods for the analysis of brain bioelectrical signals were presented and compared. It also describes both classical and advanced approaches for noise contamination removal such as among the others digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation, and wavelet transform.

• Klíčová slova
• bioelectrical signals, brain signals, electrocorticography, electroencephalography, signal processing methods,
• MeSH
• mozek MeSH
• počítačové zpracování signálu * MeSH
• vlnková analýza * MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

• MeSH
• automatizované zpracování dat * MeSH
• chorobopisy MeSH
• děrnoštítkové systémy MeSH
• lékové předpisy * MeSH
• metody MeSH
• počítače MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Československo MeSH

This paper brings a new rigorous and complete statistical approach to the data processing of the mobility curves of univalent weak bases. This approach is based on application of the least square method to the equation of the related mobility curve. Thus, an equation for the best fit is derived and its mathematical solution is found. The solution brings best estimates of the mobility curve parameters, i.e., dissociation constant K and ionic mobility of the protonated base U. Further, explicit formulas have been derived for the calculation of related statistical parameters, i.e., SDs of effective mobility s(u), of the dissociation constant s(K), and of ionic mobility of protonated base s(U). The mathematical functions used in the above approach do not impose any limitations on the data used, i.e., the mobility and pH values used may be real numbers (positive, negative, zero).

• MeSH
• automatizované zpracování dat MeSH
• elektroforéza kapilární metody   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH