Two-dimensional linear-combination model fitting of magnetic resonance spectra to define the macromolecule baseline using FiTAID, a Fitting Tool for Arrays of Interrelated Datasets

To propose the determination of the macromolecular baseline (MMBL) in clinical 1H MR spectra based on T(1) and T(2) differentiation using 2D fitting in FiTAID, a general Fitting Tool for Arrays of Interrelated Datasets.

Surface-acoustic-wave counterflow micropumps for on-chip liquid motion control in two-dimensional microchannel arrays

Fully controlled liquid injection and flow in hydrophobic polydimethylsiloxane (PDMS) two-dimensional microchannel arrays based on on-chip integrated, low-voltage-driven micropumps are demonstrated. Our architecture exploits the surface-acoustic-wave (SAW) induced counterflow mechanism and the effect of nebulization anisotropies at crossing areas owing to lateral propagating SAWs. We show that by selectively exciting single or multiple SAWs, fluids can be drawn from their reservoirs and moved towards selected positions of a microchannel grid. Splitting of the main liquid flow is also demonstrated by exploiting multiple SAW beams. As a demonstrator, we show simultaneous filling of two orthogonal microchannels. The present results show that SAW micropumps are good candidates for truly integrated on-chip fluidic networks allowing liquid control in arbitrarily shaped two-dimensional microchannel arrays.

Two-Dimensional Manganese(II) Coordination Polymer Based on Phthalate and Pyrazine Bridges Exhibiting Antiferromagnetic Porperties

Benzodifuran-functionalised pyrene and anthracene fluorophores 1 and 2 were obtained in reasonable yields. Their single crystal structures, electrochemical, optical absorption, and fluorescence characteristics have been described. They show strong luminescence with high quantum yields of 0.53 for 1 and 0.48 for 2. Magnetic measurements for the 2D coordination polymer [Mn(Pht(Pyz(H2O)2]n (1), in which metal centres are linked together by pyrazine (Pyz) and 1,6-bridging o-phthalate ligand (Pht2-), revealed antiferromagnetic interactions between Mn(II) ions.

Exploring High-resolution Magic Angle Spinning (HR-MAS) NMR Spectroscopy for Metabonomic Analysis of Apples

Classical liquid-state high-resolution (HR) NMR spectroscopy has proved a powerful tool in the metabonomic analysis of liquid food samples like fruit juices. In this paper the application of (1)H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to apple tissue is presented probing its potential for metabonomic studies. The (1)H HR-MAS NMR spectra are discussed in terms of the chemical composition of apple tissue and compared to liquid-state NMR spectra of apple juice. Differences indicate that specific metabolic changes are induced by juice preparation. The feasibility of HR-MAS NMR-based multivariate analysis is demonstrated by a study distinguishing three different apple cultivars by principal component analysis (PCA). Preliminary results are shown from subsequent studies comparing three different cultivation methods by means of PCA and partial least squares discriminant analysis (PLS-DA) of the HR-MAS NMR data. The compounds responsible for discriminating organically grown apples are discussed. Finally, an outlook of our ongoing work is given including a longitudinal study on apples.

Distinct DNA methylation patterns in cirrhotic liver and hepatocellular carcinoma

Abberrant DNA methylation is one of the hallmarks of cancerogenesis. Our study aims to delineate differential DNA methylation in cirrhosis and hepatic cancerogenesis. Patterns of methylation of 27,578 individual CpG loci in 12 hepatocellular carcinomas (HCCs), 15 cirrhotic controls and 12 normal liver samples were investigated using an array-based technology. A supervised principal component analysis (PCA) revealed 167 hypomethylated loci and 100 hypermethylated loci in cirrhosis and HCC as compared to normal controls. Thus, these loci show a "cirrhotic" methylation pattern that is maintained in HCC. In pairwise supervised PCAs between normal liver, cirrhosis and HCC, eight loci were significantly changed in all analyses differentiating the three groups (p < 0.0001). Of these, five loci showed highest methylation levels in HCC and lowest in control tissue (LOC55908, CELSR1, CRMP1, GNRH2, ALOX12 and ANGPTL7), whereas two loci showed the opposite direction of change (SPRR3 and TNFSF15). Genes hypermethylated between normal liver to cirrhosis, which maintain this methylation pattern during the development of HCC, are depleted for CpG islands, high CpG content promoters and polycomb repressive complex 2 (PRC2) targets in embryonic stem cells. In contrast, genes selectively hypermethylated in HCC as compared to nonmalignant samples showed an enrichment of CpG islands, high CpG content promoters and PRC2 target genes (p < 0.0001). Cirrhosis and HCC show distinct patterns of differential methylation with regards to promoter structure, PRC2 targets and CpG islands.

Change mechanisms of schema-centered group psychotherapy with personality disorder patients

Background This study addressed the temporal properties of personality disorders and their treatment by schema-centered group psychotherapy. It investigated the change mechanisms of psychotherapy using a novel method by which psychotherapy can be modeled explicitly in the temporal domain. Methodology and Findings 69 patients were assigned to a specific schema-centered behavioral group psychotherapy, 26 to social skills training as a control condition. The largest diagnostic subgroups were narcissistic and borderline personality disorder. Both treatments offered 30 group sessions of 100 min duration each, at a frequency of two sessions per week. Therapy process was described by components resulting from principal component analysis of patients' session-reports that were obtained after each session. These patient-assessed components were Clarification, Bond, Rejection, and Emotional Activation. The statistical approach focused on time-lagged associations of components using time-series panel analysis. This method provided a detailed quantitative representation of therapy process. It was found that Clarification played a core role in schema-centered psychotherapy, reducing rejection and regulating the emotion of patients. This was also a change mechanism linked to therapy outcome. Conclusions/Significance The introduced process-oriented methodology allowed to highlight the mechanisms by which psychotherapeutic treatment became effective. Additionally, process models depicted the actual patterns that differentiated specific diagnostic subgroups. Time-series analysis explores Granger causality, a non-experimental approximation of causality based on temporal sequences. This methodology, resting upon naturalistic data, can explicate mechanisms of action in psychotherapy research and illustrate the temporal patterns underlying personality disorders.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

BOLD correlates of continuously fluctuating epileptic activity isolated by independent component analysis

Combined EEG/fMRI recordings offer a promising opportunity to detect brain areas with altered BOLD signal during interictal epileptic discharges (IEDs). These areas are likely to represent the irritative zone, which is itself a reflection of the epileptogenic zone. This paper reports on the imaging findings using independent component analysis (ICA) to continuously quantify epileptiform activity in simultaneously acquired EEG and fMRI. Using ICA derived factors coding for the epileptic activity takes into account that epileptic activity is continuously fluctuating with each spike differing in amplitude, duration and maybe topography, including subthreshold epileptic activity besides clear IEDs and may thus increase the sensitivity and statistical power of combined EEG/fMRI in epilepsy. Twenty patients with different types of focal and generalized epilepsy syndromes were investigated. ICA separated epileptiform activity from normal physiological brain activity and artifacts. In 16/20 patients, BOLD correlates of epileptic activity matched the EEG sources, the clinical semiology, and, if present, the structural lesions. In clinically equivocal cases, the BOLD correlates aided to attribute proper diagnosis of the underlying epilepsy syndrome. Furthermore, in one patient with temporal lobe epilepsy, BOLD correlates of rhythmic delta activity could be employed to delineate the affected hippocampus. Compared to BOLD correlates of manually identified IEDs, the sensitivity was improved from 50% (10/20) to 80%. The ICA EEG/fMRI approach is a safe, non-invasive and easily applicable technique, which can be used to identify regions with altered hemodynamic effects related to IEDs as well as intermittent rhythmic discharges in different types of epilepsy.