Publications

With a range of desirable mechanical and optical properties, single wall carbon nanotubes (SWCNTs) are a promising material for nanobiotechnologies. SWCNTs also have potential as biomaterials for modulation of cellular structures. Previously, we showed that highly purified, dispersed SWCNTs grossly alter F-actin inside cells. F-actin plays critical roles in the maintenance of cell structure, force transduction, transport and cytokinesis. Thus, quantification of SWCNT-actin interactions ranging from molecular, sub-cellular and cellular levels with both structure and function is critical for developing SWCNT-based biotechnologies. Further, this interaction can be exploited, using SWCNTs as a unique actin-altering material. Here, we utilized molecular dynamics simulations to explore the interactions of SWCNTs with actin filaments. Fluorescence lifetime imaging microscopy confirmed that SWCNTs were located within  5 nm of F-actin in cells but did not interact with G-actin. SWCNTs did not alter myosin II sub-cellular localization, and SWCNT treatment in cells led to significantly shorter actin filaments. Functionally, cells with internalized SWCNTs had greatly reduced cell traction force. Combined, these results demonstrate direct, specific SWCNT alteration of F-actin structures which can be exploited for SWCNT-based biotechnologies and utilized as a new method to probe fundamental actin-related cellular processes and biophysics.

OBJECTIVES: Auditory verbal hallucinations (AVH) are among the most common symptoms in schizophrenia. Earlier studies suggest changes in the structural connectivity of auditory areas involved in the pathophysiology of auditory hallucinations. Combining diffusion tensor imaging (DTI) and fibre tractography provides a unique opportunity to visualize and quantify entire fibre bundles. METHODS: Fibre tracts connecting homotopic auditory areas via the corpus callosum were identified with DTI in ten first episode paranoid schizophrenia patients and ten healthy controls. Regions of interest were drawn manually, to guide tractography, and fractional anisotropy (FA) - a measure of fibre integrity - was calculated and averaged over the entire tract for each subject.

Functional magnetic resonance imaging (fMRI) makes it possible to non-invasively measure brain activity with high spatial resolution. There are however a number of issues that have to be addressed. One is the large amount of spatio-temporal data that needs to be processed. In addition to the statistical analysis itself, several preprocessing steps, such as slice timing correction and motion compensation, are normally applied. The high computational power of modern graphic cards has already successfully been used for MRI and fMRI. Going beyond the first published demonstration of GPU-based analysis of fMRI data, all the preprocessing steps and two statistical approaches, the general linear model (GLM) and canonical correlation analysis (CCA), have been implemented on a GPU. For an fMRI dataset of typical size (80 volumes with 64×64×22voxels), all the preprocessing takes about 0.5s on the GPU, compared to 5s with an optimized CPU implementation and 120s with the commonly used statistical parametric mapping (SPM) software. A random permutation test with 10,000 permutations, with smoothing in each permutation, takes about 50s if three GPUs are used, compared to 0.5-2.5h with an optimized CPU implementation. The presented work will save time for researchers and clinicians in their daily work and enables the use of more advanced analysis, such as non-parametric statistics, both for conventional fMRI and for real-time fMRI.

Several statistical models have been proposed in the literature to describe the behavior of speckles. Among them, the Nakagami distribution has proven to very accurately characterize the speckle behavior in tissues. However, it fails when describing the heavier tails caused by the impulsive response of a speckle. The Generalized Gamma (GG) distribution (which also generalizes the Nakagami distribution) was proposed to overcome these limitations. Despite the advantages of the distribution in terms of goodness of fitting, its main drawback is the lack of a closed-form maximum likelihood (ML) estimates. Thus, the calculation of its parameters becomes difficult and not attractive. In this work, we propose (1) a simple but robust methodology to estimate the ML parameters of GG distributions and (2) a Generalized Gama Mixture Model (GGMM). These mixture models are of great value in ultrasound imaging when the received signal is characterized by a different nature of tissues. We show that a better speckle characterization is achieved when using GG and GGMM rather than other state-of-the-art distributions and mixture models. Results showed the better performance of the GG distribution in characterizing the speckle of blood and myocardial tissue in ultrasonic images.

Age-related decline in microstructural integrity of certain white matter tracts may explain cognitive decline associated with normal aging. Whole brain tractography and a clustering segmentation in 48 healthy individuals across the adult lifespan were used to examine: interhemispheric (corpus callosum), intrahemispheric association (cingulum, uncinate, arcuate, inferior longitudinal, inferior occipitofrontal), and projection (corticospinal) fibers. Principal components analysis reduced cognitive tests into 6 meaningful factors: (1) memory and executive function; (2) visuomotor dexterity; (3) motor speed; (4) attention and working memory; (5) set-shifting/flexibility; and (6) visuospatial construction. Using theory-based structural equation modeling, relationships among age, white matter tract integrity, and cognitive performance were investigated. Parsimonious model fit demonstrated relationships where decline in white matter integrity may explain age-related decline in cognitive performance: inferior longitudinal fasciculus (ILF) with visuomotor dexterity; the inferior occipitofrontal fasciculus with visuospatial construction; and posterior fibers (i.e., splenium) of the corpus callosum with memory and executive function. Our findings suggest that decline in the microstructural integrity of white matter fibers can account for cognitive decline in normal aging.

Any etiological theory of schizophrenia must account for at least 3 distinctive features of the disorder, namely its excessive dopamine neurotransmission, its frequent periadolescent onset, and its bizarre, pathognomonic symptoms. In this article, we theorize that each of these features could arise from a single underlying cause—namely abnormal myelination of late-developing frontal white matter fasciculi. Specifically, we suggest that abnormalities in frontal myelination result in conduction delays in the efference copies initiated by willed actions. These conduction delays cause the resulting corollary discharges to be generated too late to suppress the sensory consequences of the willed actions. The resulting ambiguity as to the origins of these actions represents a phenomenologically and neurophysiologically significant prediction error. On a phenomenological level, the perception of salience in a self-generated action leads to confusion as to its origins and, consequently, passivity experiences and auditory hallucinations. On a neurophysiological level, this prediction error leads to the increased activity of dopaminergic neurons in the midbrain. This dopaminergic activity causes previously insignificant events to be perceived as salient, which exacerbates the budding hallucinations and passivity experiences and triggers additional first-rank symptoms such as delusions of reference. The article concludes with a discussion of the implications of the theory and some testable predictions which may form a worthwhile basis for future research.

The goal of the present analyses was to examine the hypothesis that mild forms of thought disorder (TD) may serve as an indicator of genetic liability for schizophrenia. A subset of 232 subjects drawn from the New York High-Risk Project was used to compare individuals at high risk for schizophrenia (ie, offspring of parents with schizophrenia; n = 63) with 2 groups of individuals at low risk for schizophrenia (ie, offspring of parents with affective disorder [n = 52] and offspring of psychiatrically normal parents [n = 117]). Subjects were administered the Rorschach Inkblot Test, and their responses were assessed according to the Thought Disorder Index (TDI). The high-risk offspring displayed significantly more TD than the other 2 groups, as shown by significantly higher TDI scores. Moreover, they had more deviant verbalizations, according to their significantly higher scores on a composite Idiosyncratic Verbalizations score. As expected, the offspring who developed psychosis produced more TD in adolescence than those who did not develop psychosis. In the sample as a whole, TD scores during late adolescence/early adulthood were positively associated with schizotypal features during mid-adulthood. These findings support the assertion that the presence of TD serves as an endophenotypic marker of a schizophrenia diathesis.

BACKGROUND: Phase-contrast MRI (PC MRI) can be used to assess blood flow dynamics noninvasively inside the human body. The acquired images can be reconstructed into flow vector fields. Traditionally, streamlines can be computed based on the vector fields to visualize flow patterns and particle trajectories. OBJECTIVES: The traditional methods may give a false impression of precision, as they do not consider the measurement uncertainty in the PC MRI images. In our prior work, we incorporated the uncertainty of the measurement into the computation of particle trajectories. METHODS: As a major part of the contribution, a novel numerical scheme for solving the anisotropic Fast Marching problem is presented. A computing time comparison to state-of-the-art methods is conducted on artificial tensor fields. A visual comparison of healthy to pathological blood flow patterns is given. RESULTS: The comparison shows that the novel anisotropic Fast Marching solver outperforms previous schemes in terms of computing time. The visual comparison of flow patterns directly visualizes large deviations of pathological flow from healthy flow. CONCLUSIONS: The novel anisotropic Fast Marching solver efficiently resolves even strongly anisotropic path costs. The visualization method enables the user to assess the uncertainty of particle trajectories derived from PC MRI images.

Individuals with 22q11.2 deletion syndrome (22q11.2DS) evince a 30% incidence of schizophrenia. We compared the white matter (WM) of 22q11.2DS patients without schizophrenia to a group of matched healthy controls using Tract-Based-Spatial-Statistics (TBSS). We found localized reduction of Fractional Anisotropy (FA) and Axial Diffusivity (AD; measure of axonal integrity) in WM underlying the left parietal lobe. No changes in Radial Diffusivity (RD; measure of myelin integrity) were observed. Of note, studies in chronic schizophrenia patients report reduced FA, no changes in AD, and increases in RD in WM. Our findings suggest different WM microstructural pathology in 22q11.2DS than in patients with schizophrenia.

CONTEXT: Hot flashes are a common side effect of adjuvant endocrine therapies (AET; leuprolide, tamoxifen, aromatase inhibitors) that reduce quality of life and treatment adherence in breast cancer patients. Because hot flashes affect only some women, preexisting neurobiological traits might predispose to their development. Previous studies have implicated the insula during the perception of hot flashes and the hypothalamus in thermoregulatory dysfunction. OBJECTIVE: The aim of the study was to understand whether neurobiological factors predict hot flashes. DESIGN: [18F]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) brain scans coregistered with structural magnetic resonance imaging were used to determine whether metabolic activity in the insula and hypothalamic thermoregulatory and estrogen-feedback regions measured before and in response to AET predict hot flashes. Findings were correlated with CYP2D6 genotype because of CYP2D6 polymorphism associations with tamoxifen-induced hot flashes. OUTCOME MEASURES: We measured regional cerebral metabolic rate of glucose uptake (rCMRglu) in the insula and hypothalamus on FDG-PET.