Towards structured sharing of raw and derived neuroimaging data across existing resources

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery

Breakdown of Lindstedt Expansion for Chaotic Maps

In a previous paper of one of us [Europhys. Lett. 59 (2002), 330--336] the validity of Greene's method for determining the critical constant of the standard map (SM) was questioned on the basis of some numerical findings. Here we come back to that analysis and we provide an interpretation of the numerical results by showing that no contradiction is found with respect to Greene's method. We show that the previous results based on the expansion in Lindstedt series do correspond to the transition value but for a different map: the semi-standard map (SSM). Moreover, we study the expansion obtained from the SM and SSM by suppressing the small divisors. The first case turns out to be related to Kepler's equation after a proper transformation of variables. In both cases we give an analytical solution for the radius of convergence, that represents the singularity in the complex plane closest to the origin. Also here, the radius of convergence of the SM's analogue turns out to be lower than the one of the SSM. However, despite the absence of small denominators these two radii are lower than the ones of the true maps for golden mean winding numbers. Finally, the analyticity domain and, in particular, the critical constant for the two maps without small divisors are studied analytically and numerically. The analyticity domain appears to be an perfect circle for the SSM analogue, while it is stretched along the real axis for the SM analogue yielding a critical constant that is larger than its radius of convergence.Comment: 12 pages, 3 figure

Bubbles, clusters and denaturation in genomic DNA: modeling, parametrization, efficient computation

The paper uses mesoscopic, non-linear lattice dynamics based (Peyrard-Bishop-Dauxois, PBD) modeling to describe thermal properties of DNA below and near the denaturation temperature. Computationally efficient notation is introduced for the relevant statistical mechanics. Computed melting profiles of long and short heterogeneous sequences are presented, using a recently introduced reparametrization of the PBD model, and critically discussed. The statistics of extended open bubbles and bound clusters is formulated and results are presented for selected examples.Comment: to appear in a special issue of the Journal of Nonlinear Mathematical Physics (ed. G. Gaeta

A stitch in time: Efficient computation of genomic DNA melting bubbles

Background: It is of biological interest to make genome-wide predictions of the locations of DNA melting bubbles using statistical mechanics models. Computationally, this poses the challenge that a generic search through all combinations of bubble starts and ends is quadratic. Results: An efficient algorithm is described, which shows that the time complexity of the task is O(NlogN) rather than quadratic. The algorithm exploits that bubble lengths may be limited, but without a prior assumption of a maximal bubble length. No approximations, such as windowing, have been introduced to reduce the time complexity. More than just finding the bubbles, the algorithm produces a stitch profile, which is a probabilistic graphical model of bubbles and helical regions. The algorithm applies a probability peak finding method based on a hierarchical analysis of the energy barriers in the Poland-Scheraga model. Conclusions: Exact and fast computation of genomic stitch profiles is thus feasible. Sequences of several megabases have been computed, only limited by computer memory. Possible applications are the genome-wide comparisons of bubbles with promotors, TSS, viral integration sites, and other melting-related regions.Comment: 16 pages, 10 figure

Heritability and reliability of automatically segmented human hippocampal formation subregions

The human hippocampal formation can be divided into a set of cytoarchitecturally and functionally distinct subregions, involved in different aspects of memory formation. Neuroanatomical disruptions within these subregions are associated with several debilitating brain disorders including Alzheimer's disease, major depression, schizophrenia, and bipolar disorder. Multi-center brain imaging consortia, such as the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) consortium, are interested in studying disease effects on these subregions, and in the genetic factors that affect them. For large-scale studies, automated extraction and subsequent genomic association studies of these hippocampal subregion measures may provide additional insight. Here, we evaluated the test-retest reliability and transplatform reliability (1.5 T versus 3 T) of the subregion segmentation module in the FreeSurfer software package using three independent cohorts of healthy adults, one young (Queensland Twins Imaging Study, N=39), another elderly (Alzheimer's Disease Neuroimaging Initiative, ADNI-2, N=163) and another mixed cohort of healthy and depressed participants (Max Planck Institute, MPIP, N=598). We also investigated agreement between the most recent version of this algorithm (v6.0) and an older version (v5.3), again using the ADNI-2 and MPIP cohorts in addition to a sample from the Netherlands Study for Depression and Anxiety (NESDA) (N=221). Finally, we estimated the heritability (h(2)) of the segmented subregion volumes using the full sample of young, healthy QTIM twins (N=728). Test-retest reliability was high for all twelve subregions in the 3 T ADNI-2 sample (intraclass correlation coefficient (ICC)=0.70-0.97) and moderate-to-high in the 4 TQTIM sample (ICC=0.5-0.89). Transplatform reliability was strong for eleven of the twelve subregions (ICC=0.66-0.96); however, the hippocampal fissure was not consistently reconstructed across 1.5 T and 3 T field strengths (ICC=0.47-0.57). Between-version agreement was moderate for the hippocampal tail, subiculum and presubiculum (ICC=0.78-0.84; Dice Similarity Coefficient (DSC)=0.55-0.70), and poor for all other subregions (ICC=0.34-0.81; DSC=0.28-0.51). All hippocampal subregion volumes were highly heritable (h(2)=0.67-0.91). Our findings indicate that eleven of the twelve human hippocampal subregions segmented using FreeSurfer version 6.0 may serve as reliable and informative quantitative phenotypes for future multi-site imaging genetics initiatives such as those of the ENIGMA consortium. (C) 2016 The Authors. Published by Elsevier Inc

The NeuroDante Project: Neurometric measurements of participant’s reaction to literary auditory stimuli from dante’s “divina commedia”

Neurodante. Progetto di analisi neurometrica di alcuni brani della Commedi

The impact of a 1-hour time interval between pazopanib and subsequent intake of gastric acid suppressants on pazopanib exposure

Co-treatment with gastric acid suppressants (GAS) in patients taking anticancer drugs that exhibit pH-dependant absorption may lead to decreased drug exposure and may hamper drug efficacy. In our study, we investigated whether a 1-hour time interval between subsequent intake of pazopanib and GAS could mitigate this negative effect on drug exposure. We performed an observational study in which we collected the first steady-state pazopanib trough concentration (C(min) ) levels from patients treated with pazopanib 800 mg once daily (OD) taken fasted or pazopanib 600 mg OD taken with food. All patients were advised to take GAS 1 hour after pazopanib. Patients were grouped based on the use of GAS and the geometric (GM) C(min) levels were compared between groups for each dose regimen. Additionally, the percentage of patients with exposure below the target threshold of 20.5 mg/L and the effect of the type of PPI was explored. The GM C(min) levels were lower in GAS users vs non-GAS users for both the 800 and 600 mg cohorts (23.7 mg/L [95% confidence interval [CI]: 21.1-26.7] vs 28.2 mg/L [95% CI: 25.9-30.5], P = .015 and 26.0 mg/L [95% CI: 22.4-30.3] vs 33.5 mg/L [95% CI: 30.3-37.1], P = .006). Subtherapeutic exposure was more prevalent in GAS users vs non-GAS users (33.3% vs 19.5% and 29.6% vs 14%). Sub-analysis showed lower GM pazopanib C(min) in patients who received omeprazole, while minimal difference was observed in those receiving pantoprazole compared to non-users. Our research showed that a 1-hour time interval between intake of pazopanib and GAS did not mitigate the negative effect of GAS on pazopanib exposure and may hamper pazopanib efficacy

Serum miRNAs as potential biomarkers for the bronchiolitis obliterans syndrome after lung transplantation

Lung transplantation (LTx) is the last treatment for patients suffering from end-stage lung diseases. Survival post-LTx is hampered by the development of the bronchiolitis obliterans syndrome (BOS) and diagnosis is often late. Given the urgent clinical need to recognize BOS patients at an early stage, we analyzed circulating miRNAs to identify possible stratification markers for BOS development post-transplantation. Therefore, pro-fibrotic (miR-21, miR-155), anti-fibrotic (miR-29a) and fibrosis-unrelated (miR-103, miR-191) miRNAs were analyzed in serum of end-stage lung disease patients and during LTx follow-up.Significant elevated levels of serum miRNAs were observed for all investigated miRNAs in both chronic obstructive pulmonary disease and interstitial lung disease patients compared to healthy controls. The same miRNAs were also significantly increased in the serum of BOS + vs. BOS - patients. Most importantly, miR-21, miR-29a, miR-103, and miR-191 levels were significantly higher in BOS + patients prior to clinical BOS diagnosis.We demonstrated that a selected group of miRNAs investigated is elevated in end-stage lung disease and BOS + patients, prior to clinical BOS diagnosis. Even if further research is expedient on the prognostic value of circulating miRNAs in BOS and lung conditions in general, these results strongly suggest that circulating miRNAs could be used as potential biomarkers for BOS development

The Effect of Using Pazopanib With Food vs. Fasted on Pharmacokinetics, Patient Safety, and Preference (DIET Study)

Pazopanib is taken fasted in a fixed oral daily dose of 800 mg. We hypothesized that ingesting pazopanib with food may improve patients' comfort and reduce gastrointestinal (GI) adverse events. Therefore, we investigated the bioequivalent dose of pazopanib when taken with food compared with 800 mg pazopanib taken fasted. In addition, we investigated the differences in GI toxicity, patient satisfaction, and patient's preference for either intake. The intake of 600 mg pazopanib with food resulted in a bioequivalent exposure and was preferred over a standard pazopanib dose without food. No differences were seen in GI toxicities under both intake regimens. Patients seem to be more positive about their feelings about side effects and satisfaction with their therapy when pazopanib was taken with food. Forty-one of the patients (68%) preferred the intake with a continental breakfast

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors