Impact of psychiatric follow-up frequency on outcomes and waiting times.

OBJECTIVES: This study determined whether naturally occurring but significantly different outpatient follow-up frequencies are associated with clinical outcomes and service waiting times. STUDY DESIGN: Longitudinal retrospective study. METHODS: This study was conducted in an outpatient setting. Participants consisted of 340 patients with major depressive disorder who were randomly assigned to 4 psychiatrists and were followed at a variable frequency defined by the clinician. Patients were assessed at baseline and at every visit with structured interviews and self-reported questionnaires. These groups were also compared according to their baseline characteristics, treatment, and appointment frequencies. Little's law was used to estimate the impact of modifying the appointment frequencies on the service waiting time. RESULTS: The demographic variables, prescriptions, and depression severity at intake of patients across the 4 groups were similar. The mean times between appointments of the 4 groups were significantly different (87.0, 46.9, 67.9, and 61.5 days, respectively; P < .001), but these differences in outpatient follow-up frequency were not associated with clinical outcomes (eg, mean last Quick Inventory of Depressive Symptomatology Self-Report score, 10.5, 10.0, 11.9, and 9.7; P = .25). However, different outpatient follow-up frequencies had an estimated impact on waiting times for access to care; using Little's law, it was observed that the waiting list would be eliminated by reducing by 23.9% the follow-up frequencies of the 3 psychiatrists with the highest frequencies. CONCLUSIONS: Although variations in appointment frequencies do not appear to have a major impact on clinical outcomes, they could be managed to achieve significant improvements in the accessibility of the clinic.

Integrated open-source software for multiscale electrophysiology.

The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

Brainstorm Pipeline Analysis of Resting-State Data From the Open MEG Archive.

We present a simple, reproducible analysis pipeline applied to resting-state magnetoencephalography (MEG) data from the Open MEG Archive (OMEGA). The data workflow was implemented with Brainstorm, which like OMEGA is free and openly accessible. The proposed pipeline produces group maps of ongoing brain activity decomposed in the typical frequency bands of electrophysiology. The procedure is presented as a technical proof of concept for streamlining a broader range and more sophisticated studies of resting-state electrophysiological data. It also features the recently introduced extension of the brain imaging data structure (BIDS) to MEG data, highlighting the scalability and generalizability of Brainstorm analytical pipelines to other, and potentially larger data volumes.

MEG/EEG Group Analysis With Brainstorm.

Brainstorm is a free, open-source Matlab and Java application for multimodal electrophysiology data analytics and source imaging [primarily MEG, EEG and depth recordings, and integration with MRI and functional near infrared spectroscopy (fNIRS)]. We also provide a free, platform-independent executable version to users without a commercial Matlab license. Brainstorm has a rich and intuitive graphical user interface, which facilitates learning and augments productivity for a wider range of neuroscience users with little or no knowledge of scientific coding and scripting. Yet, it can also be used as a powerful scripting tool for reproducible and shareable batch processing of (large) data volumes. This article describes these Brainstorm interactive and scripted features via illustration through the complete analysis of group data from 16 participants in a MEG vision study.

Fiberweb: Diffusion Visualization and Processing in the Browser.

Data visualization is one of the most important tool to explore the brain as we know it. In this work, we introduce a novel browser-based solution for medical imaging data visualization and interaction with diffusion-weighted magnetic resonance imaging (dMRI) and tractography data: Fiberweb. It uses a recent technology, WebGL, that has yet to be fully explored for medical imaging purposes. There are currently very few software tools that allow medical imaging data visualization in the browser, and none of these tools support efficient data interaction and processing, such as streamlines selection and real-time deterministic and probabilistic tractography (RTT). With Fiberweb allowing these types of interaction, it is no longer the case. We show results of the visualization of medical imaging data, and demonstrate that our new RTT probabilistic algorithm can compare to a state of the art offline algorithm. Overall, Fiberweb pushes the boundary of interaction combined with scientific visualization, which opens great perspectives for quality control and neurosurgical navigation on browser-based mobile and static devices.

A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles.

In this work, we propose a diffusion MRI protocol for mining Parkinson's disease diffusion MRI datasets and recover robust disease-specific biomarkers. Using advanced high angular resolution diffusion imaging (HARDI) crossing fiber modeling and tractography robust to partial volume effects, we automatically dissected 50 white matter (WM) fascicles. These fascicles connect deep nuclei (thalamus, putamen, pallidum) to different cortical functional areas (associative, motor, sensorimotor, limbic), basal forebrain and substantia nigra. Then, among these 50 candidate WM fascicles, only the ones that passed a test-retest reproducibility procedure qualified for further tractometry analysis. Leveraging the unique 2-timepoints test-retest Parkinson's Progression Markers Initiative (PPMI) dataset of over 600 subjects, we found statistically significant differences in tract profiles along the subcortico-cortical pathways between Parkinson's disease patients and healthy controls. In particular, significant increases in FA, apparent fiber density, tract-density and generalized FA were detected in some locations of the nigro-subthalamo-putaminal-thalamo-cortical pathway. This connection is one of the major motor circuits balancing the coordination of motor output. Detailed and quantifiable knowledge on WM fascicles in these areas is thus essential to improve the quality and outcome of Deep Brain Stimulation, and to target new WM locations for investigation.

A resistive mesh phantom for assessing the performance of EIT systems.

Assessing the performance of electrical impedance tomography (EIT) systems usually requires a phantom for validation, calibration, or comparison purposes. This paper describes a resistive mesh phantom to assess the performance of EIT systems while taking into account cabling stray effects similar to in vivo conditions. This phantom is built with 340 precision resistors on a printed circuit board representing a 2-D circular homogeneous medium. It also integrates equivalent electrical models of the Ag/AgCl electrode impedances. The parameters of the electrode models were fitted from impedance curves measured with an impedance analyzer. The technique used to build the phantom is general and applicable to phantoms of arbitrary shape and conductivity distribution. We describe three performance indicators that can be measured with our phantom for every measurement of an EIT data frame: SNR, accuracy, and modeling accuracy. These performance indicators were evaluated on our EIT system under different frame rates and applied current intensities. The performance indicators are dependent on frame rate, operating frequency, applied current intensity, measurement strategy, and intermodulation distortion when performing simultaneous measurements at several frequencies. These parameter values should, therefore, always be specified when reporting performance indicators to better appreciate their significance.

Identification and structure-activity relationships of chromene-derived selective estrogen receptor modulators for treatment of postmenopausal symptoms.

As part of a program aimed at the development of selective estrogen receptor modulators (SERMs), novel chromene scaffolds, benzopyranobenzoxapanes, were discovered. Many compounds showed binding affinity as low as 1.6-200 nM, displayed antagonist behaviors in the MCF-7 human breast adenocarcinoma cell line as well in Ishikawa cell line with IC(50) values in the range 0.2-360 nM. On the basis of the side chain substitution, various compounds demonstrated strong inhibitory activity in anti-uterotropic assay. Compound 7-(R) and its major metabolites 5-(R) and 6-(R) were evaluated in several in vivo models of estrogen action. Relative to a full estrogen agonist (ethynyl estradiol) and the SERM raloxifene, 7-(R) was found to be a potent SERM that behaved as antagonist in the uterus and exhibited estrogen agonistic activity on bone, plasma lipids, hot flush, and vagina. The overall pharmacokinetic profile and stability were significantly improved compared to those of the phase 2 development compound 9-(R).

Altered oral bioavailability and pharmacokinetics of P-glycoprotein substrates by coadministration of biochanin A.

Effects of coadministration of dietary supplement biochanin A (BA) on the pharmacokinetics of three P-glycoprotein substrates, paclitaxel, digoxin, and fexofenadine, were investigated in rats. With BA coadministration, the oral bioavailability and peak plasma concentration were markedly increased by 3.77- and 2.04-fold for paclitaxel, 1.75- and 1.71-fold for digoxin, but were reduced by 0.694- and 0.429-fold for fexofenadine, respectively. Paclitaxel is a Pgp and CYP3A substrate, the drastic increase in systemic exposure may be attributed to the synergistic inhibition of Pgp and CYP3A by BA in the intestine. Digoxin is a substrate for Pgp, CYP3A, and Oatp2. BA may suboptimally inhibit Pgp and CYP3A, resulting in a moderate increase in oral bioavailability of digoxin. Fexofenadine is a substrate for Pgp, Oatp1, Oatp2, and Oatp3. BA appears to preferentially inhibit Oatp3 over Pgp in the intestine, leading to the decreased oral absorption of fexofenadine. No significant changes in mean residence time and terminal half-life were observed for all drugs, suggesting a negligible effect of BA on their hepatic/renal elimination. These findings demonstrate the importance of interplay among uptake/efflux transporters and metabolizing enzymes. The enhanced oral absorption by BA coadministration may be exploited to improve oral bioavailability of Pgp and CYP3A substrate compounds.

A 96-well screen filter plate for high-throughput biological sample preparation and LC-MS/MS analysis.

A novel 96-well screen filter plate (patent pending) has been invented to eliminate a time-consuming and labor-intensive step in preparation of in vivo study samples--to remove blood or plasma clots. These clots plug the pipet tips during a manual or automated sample-transfer step causing inaccurate pipetting or total pipetting failure. Traditionally, these blood and plasma clots are removed by picking them out manually one by one from each sample tube before any sample transfer can be made. This has significantly slowed the sample preparation process and has become a bottleneck for automated high-throughput sample preparation using robotic liquid handlers. Our novel screen filter plate was developed to solve this problem. The 96-well screen filter plate consists of 96 stainless steel wire-mesh screen tubes connected to the 96 openings of a top plate so that the screen filter plate can be readily inserted into a 96-well sample storage plate. Upon insertion, the blood and plasma clots are excluded from entering the screen tube while clear sample solutions flow freely into it. In this way, sample transfer can be easily completed by either manual or automated pipetting methods. In this report, three structurally diverse compounds were selected to evaluate and validate the use of the screen filter plate. The plasma samples of these compounds were transferred and processed in the presence and absence of the screen filter plate and then analyzed by LC-MS/MS methods. Our results showed a good agreement between the samples prepared with and without the screen filter plate, demonstrating the utility and efficiency of this novel device for preparation of blood and plasma samples. The device is simple, easy to use, and reusable. It can be employed for sample preparation of other biological fluids that contain floating particulates or aggregates.