Swept-sines provide a tool for fast and high-resolution measurement of evoked otoacoustic emissions. During the measurement, a response to swept-sine(s) is recorded by a probe placed in the ear canal. Otoacoustic emissions can then be extracted by various techniques, e.g., Fourier analysis, the heterodyne method, and the least-square-fitting (LSF) technique. This paper employs a technique originally proposed with exponential swept-sines, which allows for direct emission extraction from the measured intermodulation impulse response. It is shown here that the technique can be used to extract distortion-product otoacoustic emissions (DPOAEs) evoked with two simultaneous swept-sines. For proper extraction of the DPOAE phase, the technique employs previously proposed adjusted formulas for exponential swept-sines generating so-called synchronized swept-sines (SSSs). Here, the SSS technique is verified using responses derived from a numerical solution of a cochlear model and responses measured in human subjects. Although computationally much less demanding, the technique yields comparable results to those obtained by the LSF technique, which has been shown in the literature to be the most noise-robust among the emission extraction methods.

• MeSH
• Fourierova analýza MeSH
• kochlea * fyziologie   MeSH
• lidé MeSH
• otoakustické emise spontánní * fyziologie   MeSH
• zvukovod fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

OBJECTIVE: Voice tremor represents a common but frequently overlooked clinical feature of neurological disease. Therefore, we aimed to quantitatively and objectively assess the characteristics of voice tremor in a large sample of patients with various progressive neurological diseases. METHODS: Voice samples were acquired from 240 patients with neurological disease and 40 healthy controls. The robust automated method was designed, allowing precise tracking of multiple tremor frequencies and distinguish pathological from the physiological tremor. RESULTS: Abnormal tremor was revealed in Huntington's disease (65%), essential tremor (50%), multiple system atrophy (40%), cerebellar ataxia (40%), amyotrophic lateral sclerosis (40%), progressive supranuclear palsy (25%), Parkinson's disease (20%), cervical dystonia (10%), and multiple sclerosis (8%) but not in controls. Low-frequency voice tremor (<4 Hz) was common in all investigated diseases, whereas medium tremor frequencies (4-7 Hz) were specific for movement disorders of Parkinson's disease, multiple system atrophy, essential tremor, and cervical dystonia. CONCLUSIONS: Careful estimation of vocal tremor may help with accurate diagnosis and tailored treatment. SIGNIFICANCE: This study provides (i) more insights into the pathophysiology of vocal tremor in a wide range of neurological diseases and (ii) an accurate method for estimation of vocal tremor suitable for clinical practice.

• MeSH
• akustika řeči * MeSH
• dospělí MeSH
• elektromyografie metody   MeSH
• esenciální tremor diagnóza   patofyziologie   MeSH
• Fourierova analýza * MeSH
• kvalita hlasu fyziologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• nemoci nervového systému diagnóza   patofyziologie   MeSH
• poruchy hlasu diagnóza   patofyziologie   MeSH
• progrese nemoci * MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Butterfly wings have complex structure lending it several interesting properties. Coloration of the wing is one of the first things to encounter and the overall visual effect is in fact influenced by several factors. Chemical pigments set the base color of the wing, topographical structures on the wing scales cause color shift by interference and their arrangement into diffraction grating causes iridescence. The thin film interference can be attributed to microscopic ridges covering wing scales. Observation and calculation of the color shift on wings of Euploea mulciber species using Fourier transform of images obtained by atomic force microscopy is the focus of this article.

• MeSH
• Fourierova analýza MeSH
• křídla zvířecí ultrastruktura   MeSH
• mikroskopie atomárních sil MeSH
• motýli fyziologie   ultrastruktura   MeSH
• pigmentace fyziologie   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

Respiratory sinus arrhythmia (RSA) is an index of cardiovagal regulation, emotional and cognitive processing. RSA is quantified using heart rate variability (HRV) spectral analysis at respiratory-linked high-frequency band (HF-HRV) using Fast Fourier transformation (FFT) or autoregressive (AR) method, both requiring resampling of recordings - a potential source of error. We hypothesized that rarely used HRV time-frequency analysis with Lomb-Scargle periodogram (LSP) without resampling could be more sensitive to detect neurocardiac response to posture change than FFT and AR. Orthostasis (posture change from supine to standing) evoked significant decrease of HF-HRV well detectable by FFT, AR, and LSP. In contrast, during posture change from sitting to lying, significant increase of HF-HRV and peak HF was best detected using LSP. In regression analysis, the associations between RR-interval, HF-HRV, and peak HF were best detected when evaluated using LSP. Time-frequency HRV analysis with LSP could represent an important alternative to conventional FFT and AR methods for assessment of cardiovagal regulation indexed by RSA.

• MeSH
• časové faktory MeSH
• dechová frekvence fyziologie   MeSH
• elektrokardiografie MeSH
• Fourierova analýza MeSH
• lidé MeSH
• mladiství MeSH
• neparametrická statistika MeSH
• regresní analýza MeSH
• respirační sinusová arytmie fyziologie   MeSH
• srdeční frekvence fyziologie   MeSH
• Check Tag
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The peripheral light-harvesting antenna complex (LH2) of purple photosynthetic bacteria is an ideal testing ground for models of structure-function relationships due to its well-determined molecular structure and ultrafast energy deactivation. It has been the target for numerous studies in both theory and ultrafast spectroscopy; nevertheless, certain aspects of the convoluted relaxation network of LH2 lack a satisfactory explanation by conventional theories. For example, the initial carotenoid-to-bacteriochlorophyll energy transfer step necessary on visible light excitation was long considered to follow the Förster mechanism, even though transfer times as short as 40 femtoseconds (fs) have been observed. Such transfer times are hard to accommodate by Förster theory, as the moderate coupling strengths found in LH2 suggest much slower transfer within this framework. In this study, we investigate LH2 from Phaeospirillum (Ph.) molischianum in two types of transient absorption experiments-with narrowband pump and white-light probe resulting in 100 fs time resolution, and with degenerate broadband 10 fs pump and probe pulses. With regard to the split Qx band in this system, we show that vibronically mediated transfer explains both the ultrafast carotenoid-to-B850 transfer, and the almost complete lack of transfer to B800. These results are beyond Förster theory, which predicts an almost equal partition between the two channels.

• MeSH
• bakteriochlorofyly metabolismus   MeSH
• časové faktory MeSH
• Fourierova analýza MeSH
• karotenoidy metabolismus   MeSH
• lasery MeSH
• přenos energie * MeSH
• Proteobacteria metabolismus   MeSH
• spektrofotometrie ultrafialová MeSH
• světlosběrné proteinové komplexy metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH

• MeSH
• behaviorální výzkum metody   trendy   MeSH
• biofeedback (psychologie) fyziologie   metody   přístrojové vybavení   MeSH
• dítě MeSH
• elektroencefalografie metody   trendy   využití   MeSH
• experimenty na lidech MeSH
• Fourierova analýza MeSH
• hyperkinetická porucha * diagnostické zobrazování   diagnóza   etiologie   MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   využití   MeSH
• neurofeedback * fyziologie   metody   přístrojové vybavení   MeSH
• neurofyziologie dějiny   metody   trendy   MeSH
• neurozobrazování metody   přístrojové vybavení   trendy   MeSH
• operantní podmiňování fyziologie   klasifikace   MeSH
• paměť fyziologie   klasifikace   MeSH
• počítačové zpracování signálu přístrojové vybavení   MeSH
• statistika jako téma MeSH
• učení fyziologie   MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• Publikační typ
• úvodní články MeSH

• MeSH
• arousal fyziologie   klasifikace   MeSH
• biofeedback (psychologie) * klasifikace   metody   přístrojové vybavení   MeSH
• diagnostické techniky a postupy * přístrojové vybavení   trendy   využití   MeSH
• diagnostické zobrazování přístrojové vybavení   trendy   využití   MeSH
• Fourierova analýza MeSH
• fyziologický stres fyziologie   imunologie   MeSH
• lidé MeSH
• neurofeedback * klasifikace   metody   přístrojové vybavení   MeSH
• statistika jako téma MeSH
• tremor diagnóza   etiologie   psychologie   MeSH
• učení fyziologie   klasifikace   MeSH
• výzkumné techniky MeSH
• zdravotnické prostředky klasifikace   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH

Around 300 million people all over the world at all age level suffer from asthma [1]. Patients with this disease have primarily difficult breathing with wheezing in respiratory sounds, cough and feeling of constricted chest. Therefore their physical activity is strongly limited [2]. Nowadays, there are several methods for asthma diagnosis, for example spirometry, measuring of peaks of expiratory velocity or measuring of bronchial reactivity. Although these methods are sufficiently reliable in most cases, they have also some imperfections, which are obvious especially by diagnosing of badly collaborating patients, e.g. small children aged up to three years. These infants can’t provide operations required for diagnosis, so results performed diagnosis are not reliable. For this reason, there is an idea of developing non invasive method of asthma diagnosis and other pulmonary diseases that would not need collaboration of patient [3]. One of the most probably working usable principles is comparison of air flow in airways of healthy and ill person. The difference of the air flow is caused by bronchial obstruction and constriction of airways of patient. There are other sounds and wheezing in the respiratory sounds detectable during breathing as a typical manifestation of the disease [4]. These phenomena can be detected by hearing of sound or by harmonic analysis.

• MeSH
• bronchiální astma * diagnóza   klasifikace   MeSH
• dítě MeSH
• Fourierova analýza MeSH
• lidé MeSH
• mechanika dýchání MeSH
• mladiství MeSH
• počítačové zpracování signálu přístrojové vybavení   MeSH
• respirační zvuky diagnóza   klasifikace   MeSH
• software MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• Publikační typ
• práce podpořená grantem MeSH

Alternations in the glycosylation of proteins have been described in connection with several cancers, including hepatocellular carcinoma (HCC) and colorectal cancer. Analytical tools, which use combination of liquid chromatography and mass spectrometry, allow precise and sensitive description of these changes. In this study, we use MRM and FT-ICR operating in full-MS scan, to determine ratios of intensities of specific glycopeptides in HCC, colorectal cancer, and liver metastasis of colorectal cancer. Haptoglobin, hemopexin and complement factor H were detected after albumin depletion and the N-linked glycopeptides with fucosylated glycans were compared with their non-fucosylated forms. In addition, sialylated forms of an O-linked glycopeptide of hemopexin were quantified in the same samples. We observe significant increase in fucosylation of all three proteins and increase in bi-sialylated O-glycopeptide of hemopexin in HCC of hepatitis C viral (HCV) etiology by both LC-MS methods. The results of the MRM and full-MS scan FT-ICR analyses provide comparable quantitative readouts in spite of chromatographic, mass spectrometric and data analysis differences. Our results suggest that both workflows allow adequate relative quantification of glycopeptides and suggest that HCC of HCV etiology differs in glycosylation from colorectal cancer and liver metastasis of colorectal cancer. SIGNIFICANCE: The article compares N- and O-glycosylation of several serum proteins in different diseases by a fast and easy sample preparation procedure in combination with high resolution Fourier transform ion cyclotron resonance mass spectrometry. The results show successful glycopeptides relative quantification in a complex peptide mixture by the high resolution instrument and the detection of glycan differences between the different types of cancer diseases. The presented method is comparable to conventional targeted MRM approach but allows additional curation of the data.

• MeSH
• cyklotrony MeSH
• diferenciální diagnóza MeSH
• Fourierova analýza MeSH
• glykopeptidy analýza   MeSH
• glykosylace MeSH
• hepatitida C komplikace   virologie   MeSH
• hepatocelulární karcinom diagnóza   etiologie   sekundární   MeSH
• hmotnostní spektrometrie přístrojové vybavení   metody   MeSH
• kolorektální nádory diagnóza   etiologie   patologie   MeSH
• lidé MeSH
• nádory jater diagnóza   etiologie   sekundární   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

BACKGROUND: Extracellular microelectrode recording (MER) is a prominent technique for studies of extracellular single-unit neuronal activity. In order to achieve robust results in more complex analysis pipelines, it is necessary to have high quality input data with a low amount of artifacts. We show that noise (mainly electromagnetic interference and motion artifacts) may affect more than 25% of the recording length in a clinical MER database. NEW METHOD: We present several methods for automatic detection of noise in MER signals, based on (i) unsupervised detection of stationary segments, (ii) large peaks in the power spectral density, and (iii) a classifier based on multiple time- and frequency-domain features. We evaluate the proposed methods on a manually annotated database of 5735 ten-second MER signals from 58 Parkinson's disease patients. COMPARISON WITH EXISTING METHODS: The existing methods for artifact detection in single-channel MER that have been rigorously tested, are based on unsupervised change-point detection. We show on an extensive real MER database that the presented techniques are better suited for the task of artifact identification and achieve much better results. RESULTS: The best-performing classifiers (bagging and decision tree) achieved artifact classification accuracy of up to 89% on an unseen test set and outperformed the unsupervised techniques by 5-10%. This was close to the level of agreement among raters using manual annotation (93.5%). CONCLUSION: We conclude that the proposed methods are suitable for automatic MER denoising and may help in the efficient elimination of undesirable signal artifacts.

• MeSH
• artefakty * MeSH
• evokované potenciály fyziologie   MeSH
• Fourierova analýza MeSH
• hluk MeSH
• lidé MeSH
• mikroelektrody škodlivé účinky   MeSH
• mozek cytologie   MeSH
• neurony fyziologie   MeSH
• počítačové zpracování signálu * MeSH
• support vector machine MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH