Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients

To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed prior to and independent from our study as part of the epilepsy diagnostics. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control. This allowed us to define two distinct sets of signals: One set of signals recorded from brain areas where the first ictal EEG signal changes were detected as judged by expert visual inspection ("focal signals") and one set of signals recorded from brain areas that were not involved at seizure onset ("nonfocal signals"). We find more rejections for both the randomness and the nonlinear-independence test for focal versus nonfocal signals. In contrast more rejections of the stationarity test are found for nonfocal signals. Furthermore, while for nonfocal signals the rejection of the stationarity test increases the rejection probability of the randomness and nonlinear-independence test substantially, we find a much weaker influence for the focal signals. In consequence, the contrast between the focal and nonfocal signals obtained from the randomness and nonlinear-independence test is further enhanced when we exclude signals for which the stationarity test is rejected. To study the dependence between the randomness and nonlinear-independence test we include only focal signals for which the stationarity test is not rejected. We show that the rejection of these two tests correlates across signals. The rejection of either test is, however, neither necessary nor sufficient for the rejection of the other test. Thus, our results suggest that EEG signals from epileptogenic brain areas are less random, more nonlinear-dependent, and more stationary compared to signals recorded from nonepileptogenic brain areas. We provide the data, source code, and detailed results in the public domain.

Leg ischemia: assessment with MR angiography and spectroscopy

PURPOSE: To prospectively determine reproducibility of magnetic resonance (MR) angiography and MR spectroscopy of deoxymyoglobin in assessment of collateral vessels and tissue perfusion in patients with critical limb ischemia (CLI) and to follow changes in patients undergoing intramuscular vascular endothelial growth factor (pVEGF)-C gene therapy, percutaneous transluminal angioplasty, supervised exercise training, or no therapy. MATERIALS AND METHODS: Study and gene therapy protocols were approved, and all patients gave written informed consent. To determine repeatability and reproducibility, seven patients underwent MR angiography and five underwent MR spectroscopy. The techniques were used to judge disease progress in 12 other patients with or without therapy: MR angiography to help determine change in visualization of collateral vessels and MR spectroscopy to help assess change in perfusion at proximal and distal calf levels. MR angiographic results were subjectively analyzed by three blinded readers. Intraobserver variability was expressed as 95% confidence interval (CI) (n=7); interobserver variability, as kappa statistic (n=15). Reexamination variability of MR spectroscopy was given as 95% CI for subsequent recovery times, and correlation with disease extent was calculated with Kendall taub rank correlation. Fisher-Yates test was used to correlate changes with pressure measurements and clinical course. RESULTS: Intraobserver and interobserver concordance was sensitive for detection of collateral vessels. Intraobserver agreement was 85.7% (95% CI: 42.1%, 99.6%). Interobserver agreement was high for small collateral vessels (kappa=0.74, P <.001) and fair for large collateral vessels (kappa=0.36, P=.002). MR spectroscopy was reproducible (95% CI: +/-26 seconds for proximal, +/-21 seconds for distal) and showed a correlation with disease extent (proximal calf, taub=0.84, P <.001; distal calf, taub=0.68, P=.04). Small collateral vessels increased over time (P=.04) but did not correlate with pressure measurements and clinical course. Recovery time correlated with clinical course (proximal calf, P=.03; distal calf, P=.005). CONCLUSION: MR angiography and MR spectroscopy of deoxymyoglobin can help document changes in visualization of collateral vessels and tissue perfusion in patients with CLI.

A Donor-Acceptor Tetrathiafulvalene Ligand Complexed to Iron(II): Synthesis, Electrochemistry, and Spectroscopy of Fe(phen)(2)(TTF-dppz)(PF6)(2)

The synthesis and photophysical properties of the complex Fe(phen)(2)(TTF-dppz)(2+) (TTF-dppz = 4',5'-bis-(propylthio)tetrathiafulvenylidipyrido3,2-a:2',3'-c-phenazine, phen = 1,10-phenanthroline) are described. In this complex, excitation into the metal ligand charge transfer bands results in the population of a high-spin state of iron(II), with a decay lifetime of approximately 1.5 ns, in dichloromethane, at room temperature. An intraligand charge transfer state can also be obtained and has a lifetime of 38 ps. A mechanism for the different states reached is proposed based on transient absorption spectroscopy.

Effect of oral D-tagatose on liver volume and hepatic glycogen accumulation in healthy male volunteers

Standard toxicity tests with high levels of D-tagatose showed a reversible enlargement of the liver in Sprague-Dawley rats without increase of liver enzymes. The present study tests the hypotheses that partial substitution of dietary sucrose by D-tagatose for 28 days increases the volume of human liver and the concentration of liver glycogen. Twelve healthy, male volunteers were studied in a double-blind crossover study with ingestion of D-tagatose (3x15 g daily) and placebo (sucrose, 3x15 g daily) for periods of 28 days each. Liver volume and glycogen concentration have been determined by magnetic resonance (MR) imaging and spectroscopy, which were accompanied by routine medical examinations. MR examinations before and after the treatments revealed no effects (P>0.05) of treatment, period, or subject for changes in liver volume or glycogen concentration. A steady increase of liver volumes, independent of the D-tagatose or placebo intake, has been observed over the study in parallel with a slight increase in body weight. The treatment with D-tagatose was not associated with clinically relevant changes of the examined clinico-chemical and hematological parameters, including liver enzymes and uric acid.

Combining Monte Carlo methods with coherent wave optics for the simulation of phase-sensitive X-ray imaging

Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle- and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle- and wave-like properties into account. The framework can be adapted to different phase-sensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging.

Optogenetics: opsins and optical interfaces in neuroscience.

Optogenetics is defined as the integration of optics and genetics to control well-defined events within specified cells of living tissue. In this introduction, we focus on the basic techniques necessary for employing microbial opsins as optogenetic tools in mammalian brains. We provide a guide for the fundamentals of optogenetic application-selecting an opsin, implementing expression of opsins based on the neuroscientific experimental requirements, and adapting the corresponding optical hardware for delivery of light into mammalian brains.