Epilepsy is a neurological disease characterized by epileptic seizures, which commonly manifest with pronounced frequency and amplitude changes in the EEG signal. In the case of focal seizures, initially localized pathological activity spreads from a so-called "onset zone" to a wider network of brain areas. Chimeras, defined as states of simultaneously occurring coherent and incoherent dynamics in symmetrically coupled networks are increasingly invoked for characterization of seizures. In particular, chimera-like states have been observed during the transition from a normal (asynchronous) to a seizure (synchronous) network state. However, chimeras in epilepsy have only been investigated with respect to the varying phases of oscillators. We propose a novel method to capture the characteristic pronounced changes in the recorded EEG amplitude during seizures by estimating chimera-like states directly from the signals in a frequency- and time-resolved manner. We test the method on a publicly available intracranial EEG dataset of 16 patients with focal epilepsy. We show that the proposed measure, titled Amplitude Entropy, is sensitive to the altered brain dynamics during seizure, demonstrating its significant increases during seizure as compared to before and after seizure. This finding is robust across patients, their seizures, and different frequency bands. In the future, Amplitude Entropy could serve not only as a feature for seizure detection, but also help in characterizing amplitude chimeras in other networked systems with characteristic amplitude dynamics.
- MeSH
- Adult MeSH
- Electroencephalography methods MeSH
- Entropy MeSH
- Epilepsies, Partial * physiopathology MeSH
- Humans MeSH
- Brain * physiopathology MeSH
- Seizures * physiopathology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- MeSH
- Entropy MeSH
- Intelligence MeSH
- Quantum Theory MeSH
- Humans MeSH
- Brain physiology MeSH
- Systems Theory MeSH
- Models, Theoretical MeSH
- Consciousness * MeSH
- Knowledge MeSH
- Check Tag
- Humans MeSH
- Publication type
- Review MeSH
Vagus nerve stimulation (VNS) is a therapeutic option in drug-resistant epilepsy. VNS leads to ≥ 50% seizure reduction in 50 to 60% of patients, termed "responders". The remaining 40 to 50% of patients, "non-responders", exhibit seizure reduction < 50%. Our work aims to differentiate between these two patient groups in preimplantation EEG analysis by employing several Entropy methods. We identified 59 drug-resistant epilepsy patients treated with VNS. We established their response to VNS in terms of responders and non-responders. A preimplantation EEG with eyes open/closed, photic stimulation, and hyperventilation was found for each patient. The EEG was segmented into eight time intervals within four standard frequency bands. In all, 32 EEG segments were obtained. Seven Entropy methods were calculated for all segments. Subsequently, VNS responders and non-responders were compared using individual Entropy methods. VNS responders and non-responders differed significantly in all Entropy methods except Approximate Entropy. Spectral Entropy revealed the highest number of EEG segments differentiating between responders and non-responders. The most useful frequency band distinguishing responders and non-responders was the alpha frequency, and the most helpful time interval was hyperventilation and rest 4 (the end of EEG recording).
- MeSH
- Electroencephalography MeSH
- Entropy MeSH
- Hyperventilation MeSH
- Humans MeSH
- Vagus Nerve MeSH
- Drug Resistant Epilepsy * therapy MeSH
- Scalp MeSH
- Vagus Nerve Stimulation * methods MeSH
- Treatment Outcome MeSH
- Seizures MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROND: One of the important areas of heart research is to analyze heart rate variability during (HRV) walking. OBJECTIVE: In this research, we investigated the correction between heart activation and the variations of walking paths. METHOD: We employed Shannon entropy to analyze how the information content of walking paths affects the information content of HRV. Eight healthy students walked on three designed walking paths with different information contents while we recorded their ECG signals. We computed and analyzed the Shannon entropy of the R-R interval time series (as an indicator of HRV) versus the Shannon entropy of different walking paths and accordingly evaluated their relation. RESULTS: According to the obtained results, walking on the path that contains more information leads to less information in the R-R time series. CONCLUSION: The analysis method employed in this research can be extended to analyze the relation between other physiological signals (such as brain or muscle reactions) and the walking path.
- MeSH
- Time Factors MeSH
- Walking * MeSH
- Electrocardiography * MeSH
- Entropy MeSH
- Humans MeSH
- Heart Rate physiology MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
OBJECTIVE: High-frequency oscillations are considered among the most promising interictal biomarkers of the epileptogenic zone in patients suffering from pharmacoresistant focal epilepsy. However, there is no clear definition of pathological high-frequency oscillations, and the existing detectors vary in methodology, performance, and computational costs. This study proposes relative entropy as an easy-to-use novel interictal biomarker of the epileptic tissue. METHODS: We evaluated relative entropy and high-frequency oscillation biomarkers on intracranial electroencephalographic data from 39 patients with seizure-free postoperative outcome (Engel Ia) from three institutions. We tested their capability to localize the epileptogenic zone, defined as resected contacts located in the seizure onset zone. The performance was compared using areas under the receiver operating curves (AUROCs) and precision-recall curves. Then we tested whether a universal threshold can be used to delineate the epileptogenic zone across patients from different institutions. RESULTS: Relative entropy in the ripple band (80-250 Hz) achieved an average AUROC of .85. The normalized high-frequency oscillation rate in the ripple band showed an identical AUROC of .85. In contrast to high-frequency oscillations, relative entropy did not require any patient-level normalization and was easy and fast to calculate due to its clear and straightforward definition. One threshold could be set across different patients and institutions, because relative entropy is independent of signal amplitude and sampling frequency. SIGNIFICANCE: Although both relative entropy and high-frequency oscillations have a similar performance, relative entropy has significant advantages such as straightforward definition, computational speed, and universal interpatient threshold, making it an easy-to-use promising biomarker of the epileptogenic zone.
INTRODUCTION: Impaired copy of intersecting pentagons from the Mini-Mental State Examination (MMSE), has been used to assess dementia in Parkinson's disease (PD). We used a digitizing tablet during the pentagon copying test (PCT) as a potential tool for evaluating early cognitive deficits in PD without major cognitive impairment. We also aimed to uncover the neural correlates of the identified parameters using whole-brain magnetic resonance imaging (MRI). METHODS: We enrolled 27 patients with PD without major cognitive impairment and 25 age-matched healthy controls (HC). We focused on drawing parameters using a digitizing tablet. Parameters with between-group differences were correlated with cognitive outcomes and were used as covariates in the whole-brain voxel-wise analysis using voxel-based morphometry; familywise error (FWE) threshold p < 0.001. RESULTS: PD patients differed from HC in attention domain z-scores (p < 0.0001). In terms of tablet parameters, the groups differed in Shannon entropy (horizontal in-air, p = 0.003), which quantifies the movements between two strokes. In PD, a correlation was found between the median of Shannon entropy (horizontal in-air) and attention z-scores (R = -0.55, p = 0.006). The VBM revealed an association between our drawing parameter of interest and gray matter (GM) volume variability in the right superior parietal lobe (SPL). CONCLUSION: Using a digitizing tablet during the PCT, we identified a novel entropy-based parameter that differed between the nondemented PD and HC groups. This in-air parameter correlated with the level of attention and was linked to GM volume variability of the region engaged in spatial attention.
- MeSH
- Entropy MeSH
- Cognitive Dysfunction * MeSH
- Humans MeSH
- Magnetic Resonance Imaging methods MeSH
- Neuropsychological Tests MeSH
- Parkinson Disease * complications diagnostic imaging psychology MeSH
- Gray Matter MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
A novel series of proflavine ureas, derivatives 11a-11i, were synthesized on the basis of molecular modeling design studies. The structure of the novel ureas was obtained from the pharmacological model, the parameters of which were determined from studies of the structure-activity relationship of previously prepared proflavine ureas bearing n-alkyl chains. The lipophilicity (LogP) and the changes in the standard entropy (ΔS°) of the urea models, the input parameters of the pharmacological model, were determined using quantum mechanics and cheminformatics. The anticancer activity of the synthesized derivatives was evaluated against NCI-60 human cancer cell lines. The urea derivatives azepyl 11b, phenyl 11c and phenylethyl 11f displayed the highest levels of anticancer activity, although the results were only a slight improvement over the hexyl urea, derivative 11j, which was reported in a previous publication. Several of the novel urea derivatives displayed GI50 values against the HCT-116 cancer cell line, which suggest the cytostatic effect of the compounds azepyl 11b-0.44 μM, phenyl 11c-0.23 μM, phenylethyl 11f-0.35 μM and hexyl 11j-0.36 μM. In contrast, the novel urea derivatives 11b, 11c and 11f exhibited levels of cytotoxicity three orders of magnitude lower than that of hexyl urea 11j or amsacrine.
- MeSH
- Chemical Phenomena MeSH
- Entropy * MeSH
- Fibroblasts cytology drug effects MeSH
- Inhibitory Concentration 50 MeSH
- Kinetics MeSH
- Humans MeSH
- Urea chemical synthesis chemistry pharmacology MeSH
- Models, Molecular MeSH
- Proflavine chemical synthesis chemistry pharmacology MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
Baricitinib is a drug used for the treatment of rheumatoid arthritis. It is a selective and reversible inhibitor of Janus kinases 1 and 2, which play an important role in signalling the pro-inflammatory pathway activated in autoimmune disorders such as rheumatoid arthritis. The pH-spectrophotometric and pH-potentiometric titrations allowed the measurement of three or four successive dissociation constants of Baricitinib. Baricitinib neutral LH2 molecule was able to protonate into two soluble cations LH42+, LH3+ and dissociate into two soluble anions LH- and L2- in pure water. The graph of molar absorption coefficients of differently protonated species versus wavelength indicated that the spectra εL, εLH, εLH2 were the nearly the same for these species and that the spectra εLH4 and εLH3 were also similar. In the pH range from 2-13, four pKa´s of spectra analysis were reliably estimated by REACTLAB at I =0.0020 mol. dm-3 values pKTa1 = 3.07, pKTa2 = 3.87, pKTa3 = 6.27, pKTa4 = 12.78 at 25 °C and pKTa1 = 3.00, pKTa2 = 3.79, pKTa3 = 6.12, pKTa4 = 12.75 at 37 °C. Potentiometric pH-titration analysis for a higher concentration of 1 × 10-3 mol. dm-3 estimated with ESAB at I =0.0001 mol. dm-3 values pKTa1 = 3.69, pKTa2 = 3.81, pKTa3 = 4.73 at 25 °C and pKTa1 = 3.62, pKTa2 = 3.73, pKTa3 = 4.43 at 37 °C. Molar enthalpy ΔH°, molar entropy ΔS° and Gibbs free energy ΔG° were calculated from the spectra using a dependence ln K to 1/T.
- MeSH
- Azetidines * MeSH
- Entropy MeSH
- Hydrogen-Ion Concentration MeSH
- Purines MeSH
- Pyrazoles MeSH
- Sulfonamides MeSH
- Thermodynamics MeSH
- Publication type
- Journal Article MeSH
Hexameric arginine repressor, ArgR, is the feedback regulator of bacterial L-arginine regulons, and sensor of L-arg that controls transcription of genes for its synthesis and catabolism. Although ArgR function, as well as its secondary, tertiary, and quaternary structures, is essentially the same in E. coli and B. subtilis, the two proteins differ significantly in sequence, including residues implicated in the response to L-arg. Molecular dynamics simulations are used here to evaluate the behavior of intact B. subtilis ArgR with and without L-arg, and are compared with prior MD results for a domain fragment of E. coli ArgR. Relative to its crystal structure, B. subtilis ArgR in absence of L-arg undergoes a large-scale rotational shift of its trimeric subassemblies that is very similar to that observed in the E. coli protein, but the residues driving rotation have distinct secondary and tertiary structural locations, and a key residue that drives rotation in E. coli is missing in B. subtilis. The similarity of trimer rotation despite different driving residues suggests that a rotational shift between trimers is integral to ArgR function. This conclusion is supported by phylogenetic analysis of distant ArgR homologs reported here that indicates at least three major groups characterized by distinct sequence motifs but predicted to undergo a common rotational transition. The dynamic consequences of L-arg binding for transcriptional activation of intact ArgR are evaluated here for the first time in two-microsecond simulations of B. subtilis ArgR. L-arg binding to intact B. subtilis ArgR causes a significant further shift in the angle of rotation between trimers that causes the N-terminal DNA-binding domains lose their interactions with the C-terminal domains, and is likely the first step toward adopting DNA-binding-competent conformations. The results aid interpretation of crystal structures of ArgR and ArgR-DNA complexes.
- MeSH
- Allosteric Regulation MeSH
- Arginine chemistry metabolism MeSH
- Bacillus subtilis chemistry genetics metabolism MeSH
- Bacterial Proteins chemistry genetics metabolism MeSH
- Entropy MeSH
- Escherichia coli chemistry genetics metabolism MeSH
- Phylogeny MeSH
- Protein Conformation, alpha-Helical MeSH
- Protein Conformation, beta-Strand MeSH
- Protein Domains MeSH
- Regulon genetics MeSH
- Repressor Proteins chemistry genetics metabolism MeSH
- Amino Acid Sequence MeSH
- Sequence Alignment MeSH
- Molecular Dynamics Simulation MeSH
- Protein Binding MeSH
- Hydrogen Bonding MeSH
- Publication type
- Journal Article MeSH
Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) have been used for recognition of breathing and movement-related sleep disorders. Bio-signal processing has been performed by extracting EMG features exploiting entropy and statistical moments, in addition to developing an iterative pulse peak detection algorithm using synchrosqueezed wavelet transform (SSWT) for reliable extraction of heart rate and breathing-related features from ECG. A deep learning framework has been designed to incorporate EMG and ECG features. The framework has been used to classify four groups: healthy subjects, patients with obstructive sleep apnea (OSA), patients with restless leg syndrome (RLS) and patients with both OSA and RLS. The proposed deep learning framework produced a mean accuracy of 72% and weighted F1 score of 0.57 across subjects for our formulated four-class problem.
- MeSH
- Algorithms MeSH
- Biosensing Techniques * MeSH
- Deep Learning * MeSH
- Respiration MeSH
- Electrocardiography MeSH
- Entropy MeSH
- Humans MeSH
- Sleep Apnea, Obstructive MeSH
- Signal Processing, Computer-Assisted * MeSH
- Polysomnography MeSH
- Sleep Wake Disorders * MeSH
- Heart Rate MeSH
- Wavelet Analysis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
