Diffusion tensor imaging of cocaine-treated rodents.

Studies in cocaine-dependent human subjects have shown differences in white matter on diffusion tensor imaging (DTI) compared with non-drug-using controls. It is not known whether the differences in fractional anisotropy (FA) seen on DTI in white matter regions of cocaine-dependent humans result from a pre-existing predilection for drug use or purely from cocaine abuse. To study the effect of cocaine on brain white matter, DTI was performed on 24 rats after continuous infusion of cocaine or saline for 4 weeks, followed by brain histology. Voxel-based morphometry analysis showed an 18% FA decrease in the splenium of the corpus callosum (CC) in cocaine-treated animals relative to saline controls. On histology, significant increase in neurofilament expression (125%) and decrease in myelin basic protein (40%) were observed in the same region in cocaine-treated animals. This study supports the hypothesis that chronic cocaine use alters white matter integrity in human CC. Unlike humans, where the FA in the genu differed between cocaine users and non-users, the splenium was affected in rats. These differences between rodent and human findings could be due to several factors that include differences in the brain structure and function between species and/or the dose, timing, and duration of cocaine administration.

Improved cerebellar tissue classification on magnetic resonance images of brain.

PURPOSE: To develop and implement a method for improved cerebellar tissue classification on the MRI of brain by automatically isolating the cerebellum prior to segmentation. MATERIALS AND METHODS: Dual fast spin echo (FSE) and fluid attenuation inversion recovery (FLAIR) images were acquired on 18 normal volunteers on a 3 T Philips scanner. The cerebellum was isolated from the rest of the brain using a symmetric inverse consistent nonlinear registration of individual brain with the parcellated template. The cerebellum was then separated by masking the anatomical image with individual FLAIR images. Tissues in both the cerebellum and rest of the brain were separately classified using hidden Markov random field (HMRF), a parametric method, and then combined to obtain tissue classification of the whole brain. The proposed method for tissue classification on real MR brain images was evaluated subjectively by two experts. The segmentation results on Brainweb images with varying noise and intensity nonuniformity levels were quantitatively compared with the ground truth by computing the Dice similarity indices. RESULTS: The proposed method significantly improved the cerebellar tissue classification on all normal volunteers included in this study without compromising the classification in remaining part of the brain. The average similarity indices for gray matter (GM) and white matter (WM) in the cerebellum are 89.81 (+/-2.34) and 93.04 (+/-2.41), demonstrating excellent performance of the proposed methodology. CONCLUSION: The proposed method significantly improved tissue classification in the cerebellum. The GM was overestimated when segmentation was performed on the whole brain as a single object.

Perfusion in rat brain at 7 T with arterial spin labeling using FAIR-TrueFISP and QUIPSS.

Measurement of perfusion in longitudinal studies allows for the assessment of tissue integrity and the detection of subtle pathologies. In this work, the feasibility of measuring brain perfusion in rats with high spatial resolution using arterial spin labeling is reported. A flow-sensitive alternating recovery sequence, coupled with a balanced gradient fast imaging with steady-state precession readout section was used to minimize ghosting and geometric distortions, while achieving high signal-to-noise ratio. The quantitative imaging of perfusion using a single subtraction method was implemented to address the effects of variable transit delays between the labeling of spins and their arrival at the imaging slice. Studies in six rats at 7 T showed good perfusion contrast with minimal geometric distortion. The measured blood flow values of 152.5+/-6.3 ml/100 g per minute in gray matter and 72.3+/-14.0 ml/100 g per minute in white matter are in good agreement with previously reported values based on autoradiography, considered to be the gold standard.

Quantification of the spatiotemporal microstructural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography.

Using diffusion tensor tractography, we quantified the microstructural changes in the association, projection, and commissural compact white matter pathways of the human brain over the lifespan in a cohort of healthy right-handed children and adults aged 6-68 years. In both males and females, the diffusion tensor radial diffusivity of the bilateral arcuate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, corticospinal, somatosensory tracts, and the corpus callosum followed a U-curve with advancing age; fractional anisotropy in the same pathways followed an inverted U-curve. Our study provides useful baseline data for the interpretation of data collected from patients.

Cryo-EM model of the bullet-shaped vesicular stomatitis virus.

Vesicular stomatitis virus (VSV) is a bullet-shaped rhabdovirus and a model system of negative-strand RNA viruses. Through direct visualization by means of cryo-electron microscopy, we show that each virion contains two nested, left-handed helices: an outer helix of matrix protein M and an inner helix of nucleoprotein N and RNA. M has a hub domain with four contact sites that link to neighboring M and N subunits, providing rigidity by clamping adjacent turns of the nucleocapsid. Side-by-side interactions between neighboring N subunits are critical for the nucleocapsid to form a bullet shape, and structure-based mutagenesis results support this description. Together, our data suggest a mechanism of VSV assembly in which the nucleocapsid spirals from the tip to become the helical trunk, both subsequently framed and rigidified by the M layer.

Organization of hue selectivity in macaque V2 thin stripes.

V2 has long been recognized to contain functionally distinguishable compartments that are correlated with the stripelike pattern of cytochrome oxidase activity. Early electrophysiological studies suggested that color, direction/disparity, and orientation selectivity were largely segregated in the thin, thick, and interstripes, respectively. Subsequent studies revealed a greater degree of homogeneity in the distribution of response properties across stripes, yet color-selective cells were still found to be most prevalent in the thin stripes. Optical recording studies have demonstrated that thin stripes contain both color-preferring and luminance-preferring modules. These thin stripe color-preferring modules contain spatially organized hue maps, whereas the luminance-preferring modules contain spatially organized luminance-change maps. In this study, the neuronal basis of these hue maps was determined by characterizing the selectivity of neurons for isoluminant hues in multiple penetrations within previously characterized V2 thin stripe hue maps. The results indicate that neurons within the superficial layers of V2 thin stripe hue maps are organized into columns whose aggregated hue selectivity is closely related to the hue selectivity of the optically defined hue maps. These data suggest that thin stripes contain hue maps not simply because of their moderate percentage of hue-selective neurons, but because of the columnar and tangential organization of hue selectivity.

Symmetric inverse consistent nonlinear registration driven by mutual information.

A nonlinear viscoelastic image registration algorithm based on the demons paradigm and incorporating inverse consistent constraint (ICC) is implemented. An inverse consistent and symmetric cost function using mutual information (MI) as a similarity measure is employed. The cost function also includes regularization of transformation and inverse consistent error (ICE). The uncertainties in balancing various terms in the cost function are avoided by alternatively minimizing the similarity measure, the regularization of the transformation, and the ICE terms. The diffeomorphism of registration for preventing folding and/or tearing in the deformation is achieved by the composition scheme. The quality of image registration is first demonstrated by constructing brain atlas from 20 adult brains (age range 30-60). It is shown that with this registration technique: (1) the Jacobian determinant is positive for all voxels and (2) the average ICE is around 0.004 voxels with a maximum value below 0.1 voxels. Further, the deformation-based segmentation on Internet Brain Segmentation Repository, a publicly available dataset, has yielded high Dice similarity index (DSI) of 94.7% for the cerebellum and 74.7% for the hippocampus, attesting to the quality of our registration method.

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.

The temporal impulse response function in infantile nystagmus.

Despite rapid to-and-fro motion of the retinal image that results from their incessant involuntary eye movements, persons with infantile nystagmus (IN) rarely report the perception of motion smear. We performed two experiments to determine if the reduction of perceived motion smear in persons with IN is associated with an increase in the speed of the temporal impulse response. In Experiment 1, increment thresholds were determined for pairs of successively presented flashes of a long horizontal line, presented on a 65-cd/m2 background field. The stimulus-onset asynchrony (SOA) between the first and second flash varied from 5.9 to 234 ms. In experiment 2, temporal contrast sensitivity functions were determined for a 3-cpd horizontal square-wave grating that underwent counterphase flicker at temporal frequencies between 1 and 40 Hz. Data were obtained for 2 subjects with predominantly pendular IN and 8 normal observers in Experiment 1 and for 3 subjects with IN and 4 normal observers in Experiment 2. Temporal impulse response functions (TIRFs) were estimated as the impulse response of a linear second-order system that provided the best fit to the increment threshold data in Experiment 1 and to the temporal contrast sensitivity functions in Experiment 2. Estimated TIRFs of the subjects with pendular IN have natural temporal frequencies that are significantly faster than those of normal observers (ca. 13 vs. 9 Hz), indicating an accelerated temporal response to visual stimuli. This increase in response speed is too small to account by itself for the virtual absence of perceived motion smear in subjects with IN, and additional neural mechanisms are considered.

Prevalence and Clinical Significance of DSM-5-Attenuated Psychosis Syndrome in Adolescents and Young Adults in the General Population: The Bern Epidemiological At-Risk (BEAR) Study

Objective: Section III of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lists attenuated psychosis syndrome as a condition for further study. One important question is its prevalence and clinical significance in the general population. Method: Analyses involved 1229 participants (age 16-40 years) from the general population of Canton Bern, Switzerland, enrolled from June 2011 to July 2012. "Symptom," "onset/worsening," "frequency," and "distress/disability" criteria of attenuated psychosis syndrome were assessed using the structured interview for psychosis-risk syndromes. Furthermore, help-seeking, psychosocial functioning, and current nonpsychotic axis I disorders were surveyed. Well-trained psychologists performed assessments using the computer-assisted telephone interviewing technique. Results: The symptom criterion was met by 12.9% of participants, onset/worsening by 1.1%, frequency by 3.8%, and distress/disability by 7.0%. Symptom, frequency, and distress/disability were met by 3.2%. Excluding trait-like attenuated psychotic symptoms (APS) decreased the prevalence to 2.6%, while adding onset/worsening reduced it to 0.3%. APS were associated with functional impairments, current mental disorders, and help-seeking although they were not a reason for help-seeking. These associations were weaker for attenuated psychosis syndrome. Conclusions: At the population level, only 0.3% met current attenuated psychosis syndrome criteria. Particularly, the onset/worsening criterion, originally included to increase the likelihood of progression to psychosis, lowered its prevalence. Because progression is not required for a self-contained syndrome, a revision of the restrictive onset criterion is proposed to avoid the exclusion of 2.3% of persons who experience and are distressed by APS from mental health care. Secondary analyses suggest that a revised syndrome would also possess higher clinical significance than the current syndrome.

Molecular characterization of a gene required for entry into S phase of the mitotic cell cycle in the yeast {\it Saccharomyces cerevisiae\/}

A strain of Saccaromyces cerevisiae (SC3B) with a temperature sensitive defect in the synthesis of DNA has been isolated. This defect is due to a single recessive mutation in a gene named INS1 required for the initiation of S phase. Arrested cells carrying the ins1$\sp{ts}$ allele are defective in the completion of G1 to S phase transition events including SPB duplication or separation, initiation of DNA synthesis, normal control of budding, and bud neck stability. The mutation and a gene which complements the mutation were mapped to chromosome IV. The complementing gene was proved to be the wild type allele of the temperature sensitive mutation by genetic linkage of an integrated clone. A very low abundance 4.2 kb RNA message was observed in the strain SC3B which increased greatly in this strain transformed with a multiple copy plasmid carrying the complementing clone. The wild type gene was sequenced and found to encode a 1268 amino acid protein of with a molecular weight of 142,655 Daltons. Computer assisted searches for similar DNA sequences revealed no significant homology matches. However, searches for protein sequence homology revealed a protein (the DIS3 gene product of S. pombe) with a similar sequence over a 534 amino acid stretch to the predicted INS1 gene product. A later search revealed a near identical sequence for a gene (SRK1) also isolated from S. cerevisiae. ^

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.