Both doublecortin and doublecortin-like kinase play a role in cortical interneuron migration

Type I lissencephaly, a genetic disease characterized by disorganized cortical layers and gyral abnormalities, is associated with severe cognitive impairment and epilepsy. Two genes, LIS1 and doublecortin (DCX), have been shown to be responsible for a large proportion of cases of type I lissencephaly. Both genes encode microtubule-associated proteins that have been shown to be important for radial migration of cortical pyramidal neurons. To investigate whether DCX also plays a role in cortical interneuron migration, we inactivated DCX in the ganglionic eminence of rat embryonic day 17 brain slices using short hairpin RNA. We found that, when DCX expression was blocked, the migration of interneurons from the ganglionic eminence to the cerebral cortex was slowed but not absent, similar to what had previously been reported for radial neuronal migration. In addition, the processes of DCX-deficient migrating interneurons were more branched than their counterparts in control experiments. These effects were rescued by DCX overexpression, confirming the specificity to DCX inactivation. A similar delay in interneuron migration was observed when Doublecortin-like kinase (DCLK), a microtubule-associated protein related to DCX, was inactivated, although the morphology of the cells was not affected. The importance of these genes in interneuron migration was confirmed by our finding that the cortices of Dcx, Dclk, and Dcx/Dclk mutant mice contained a reduced number of such cells in the cortex and their distribution was different compared with wild-type controls. However, the defect was different for each group of mutant animals, suggesting that DCX and DCLK have distinct roles in cortical interneuron migration

Moment-based fast discrete sine transforms

This paper presents a novel approach to compute discrete sine transforms (DSTs). By using a modular mapping, DSTs are approximated by the sum of a finite sequence of discrete moments. Hence, by extending our earlier technique in computing moments with an adder network only, DSTs can also be implemented easily by a systolic array primarily involving additions. The method can be applied to multidimensional DSTs as well as their inverses.published_or_final_versio

A novel approach to fast discrete Hartley transform

The Discrete Hartley transform (DHT) is an important tool in digital signal processing. We propose a novel approach to perform DHT. We transform DHT into a form expressed in discrete moments via a modular mapping and truncating Taylor series expansion and present a completely new formula for computing DHT. We extend the use of our systolic array for fast computation of moments without any multiplications, to one that computes DHT with only a few multiplications and without any evaluations of triangular functions. The multiplication number used in our method is O(Nlog2N/log2log2N) superior to O(Nlog 2N) in the conventional FDT. The execution time of the systolic array is only O(Nlog2N/log2log2N) for 1-D DHT and O(N k) for k-D DHT (k⩾2). The systolic array consists of very simple processing elements and hence it implies an easy and potential hardware/VLSI implementation. The approach is also applicable to DHT inverses.published_or_final_versio

A quasi-Monte Carlo method for computing areas of point-sampled surfaces

A novel and efficient quasi-Monte Carlo method for computing the area of a point-sampled surface with associated surface normal for each point is presented. Our method operates directly on the point cloud without any surface reconstruction procedure. Using the Cauchy–Crofton formula, the area of the point-sampled surface is calculated by counting the number of intersection points between the point cloud and a set of uniformly distributed lines generated with low-discrepancy sequences. Based on a clustering technique, we also propose an effective algorithm for computing the intersection points of a line with the point-sampled surface. By testing on a number of point-based models, experiments suggest that our method is more robust and more efficient than those conventional approaches based on surface reconstruction.postprin

Genetic analysis of common factors underlying cardiovascular disease-related traits

BACKGROUND: Cardiovascular disease-related traits, such as body mass index (BMI), systolic blood pressure (SBP), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), and glucose levels (GLUC), have moderate to high correlations with each other. We hypothesized that there might be some common factors underlying the correlations of these traits, and attempted to identify these factors and their genetic structures. Cross-sectional measurements from the 330 extended Framingham Heart Study families were used in this study. Principal component factor analysis was applied to obtain the factors that were then analyzed using variance components linkage analysis. RESULTS: With the above six traits three factors were generated: BMI-SBP-GLUC, HDL-TG, and TC-TG. The heritabilities for these factors were 32%, 45%, and 49%, respectively. Comparing the linkage results of the factors with the results of their component traits, evidence for linkage was observed for the TC-TG factor to a locus on chromosome 2p23 with a two-point LOD score 2.73 (marker GATA8F07) and a multipoint LOD score 1.81 (at 54 cM), while the LOD scores for TC and TG did not exceed 1 at this region. CONCLUSION: Our analysis showed a locus on chromosome 2 might have a pleiotropic effect on the cardiovascular disease-related traits TC and TG

Adaptive neural network filter for visual evoked potential estimation

The authors describe a new approach to enhance the signal-to-noise-ratio (SNR) of visual evoked potential (VEP) based on an adaptive neural network filter. Neural networks are usually used in an nonadaptive way. The weights in the neural network are adjusted during training but remain constant in actual use. Here, the authors use an adaptive neural network filter with adaptation capabilities similar to those of the traditional linear adaptive filter and suitable training scheme is also examined. In contrast with linear adaptive filters, adaptive neural network filters possess nonlinear characteristics which can better match the nonlinear behaviour of evoked potential signals. Simulations employing VEP signals obtained experimentally confirm the superior performance of the adaptive neural network filter against traditional linear adaptive filter.published_or_final_versio

Gate-tuned normal and superconducting transport at the surface of a topological insulator

Three-dimensional topological insulators are characterized by the presence of a bandgap in their bulk and gapless Dirac fermions at their surfaces. New physical phenomena originating from the presence of the Dirac fermions are predicted to occur, and to be experimentally accessible via transport measurements in suitably designed electronic devices. Here we study transport through superconducting junctions fabricated on thin Bi2Se3 single crystals, equipped with a gate electrode. In the presence of perpendicular magnetic field B, sweeping the gate voltage enables us to observe the filling of the Dirac fermion Landau levels, whose character evolves continuously from electron- to hole-like. When B=0, a supercurrent appears, whose magnitude can be gate tuned, and is minimum at the charge neutrality point determined from the Landau level filling. Our results demonstrate how gated nano-electronic devices give control over normal and superconducting transport of Dirac fermions at an individual surface of a three-dimensional topological insulator.Comment: 28 pages, 5 figure

Improved electrical properties of metal-oxide-semiconductor capacitor with HfTiON gate dielectric by using HfSiON interlayer

Metal-oxide-semiconductor (MOS) capacitor with HfTiONHfSiON stack structure as high- k gate dielectric is fabricated, and its electrical properties are compared with those of a similar device with HfTiON only as gate dielectric. Experimental results show that the device with HfTiONHfSiON gate dielectric exhibits better interface properties, lower gate leakage current, and enhanced high-field reliability. All these improvements should be attributed to the fact that the HfSiON buffer layer effectively blocks the diffusion of Ti atoms to the Si substrate, thus resulting in a Si O2 Si -like HfSiONSi interface. © 2007 American Institute of Physics.published_or_final_versio

Giant magnetoelectric effect of a hybrid of magnetostrictive and piezoelectric composites

Author name used in this publication: H. L. W. Chand2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe