Role of GABAergic signaling and the GABAA receptor subunit gene cluster at 15q11-q13 in autism spectrum disorders, schizophrenia, and heroin addiction

AbstractAutism spectrum disorders, schizophrenia, and heroin addiction are all complex disorders with both genetic and environmental components to their etiology. The most common chromosomal abnormality in autism is a maternally derived duplication at 15q11-q13, which is where a cluster of gamma-aminobutyric acid (GABAA) receptor subunit genes lies. In addition, copy number variations in this area have been implicated in the pathogenesis of schizophrenia. These findings suggest that GABAergic signaling might play a crucial role in contributing to susceptibility to the development of autism and schizophrenia. Furthermore, there is considerable evidence supporting a role for GABA neurotransmission in mediating the addictive properties of heroin. Hence, this review explores recent findings related to the involvement of GABAergic system in autism, schizophrenia, and heroin addiction. We also outline the implications that the presence of genetic variants in the GABAA receptor subunit cluster at 15q11-q13 may have on the risk of developing these psychiatric disorders. Finally, we make recommendations for future work that might help define the mechanisms underpinning the neuropathology that contributes to these psychiatric disorders

Low-Power and Error-Resilient VLSI Circuits and Systems.

Efficient low-power operation is critically important for the success of the next-generation signal processing applications. Device and supply voltage have been continuously scaled to meet a more constrained power envelope, but scaling has created resiliency challenges, including increasing timing faults and soft errors. Our research aims at designing low-power and robust circuits and systems for signal processing by drawing circuit, architecture, and algorithm approaches. To gain an insight into the system faults due to supply voltage reduction, we researched the two primary effects that determine the minimum supply voltage (VMIN) in Intel’s tri-gate CMOS technology, namely process variations and gate-dielectric soft breakdown. We determined that voltage scaling increases the timing window that sequential circuits are vulnerable. Thus, we proposed a new hold-time violation metric to define hold-time VMIN, which has been adopted as a new design standard. Device scaling increases soft errors which affect circuit reliability. Through extensive soft error characterization using two 65nm CMOS test chips, we studied the soft error mechanisms and its dependence on supply voltage and clock frequency. This study laid the foundation of the first 65nm DSP chip design for a NASA spaceflight project. To mitigate such random errors, we proposed a new confidence-driven architecture that effectively enhances the error resiliency of deeply scaled CMOS and post-CMOS circuits. Designing low-power resilient systems can effectively leverage application-specific algorithmic approaches. To explore design opportunities in the algorithmic domain, we demonstrate an application-specific detection and decoding processor for multiple-input multiple-output (MIMO) wireless communication. To enhance the receive error rate for a robust wireless communication, we designed a joint detection and decoding technique by enclosing detection and decoding in an iterative loop to enhance both interference cancellation and error reduction. A proof-of-concept chip design was fabricated for the next-generation 4x4 256QAM MIMO systems. Through algorithm-architecture optimizations and low-power circuit techniques, our design achieves significant improvements in throughput, energy efficiency and error rate, paving the way for future developments in this area.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110323/1/uchchen_1.pd

Process Chart for Controlling Wafer Defects using Fuzzy Theory

Manufacturers of integrated circuits (IC) frequently utilize c-charts to monitor wafer defects. The clustering of wafer defects increases with the surface area of the wafers. The clustering of defects causes the Poisson-based c-chart to show many false alarms. Although Neyman-based c-chart has been developed to reduce the number of false alarms, it has some shortcomings in practical use. This study presents a process control chart that applies Fuzzy theory and the engineering experience to monitor the clustered defects on a wafer. The proposed method is simpler and more efficient than that of the Neyman-based c-chart. A case study of an IC company in Taiwan demonstrates the effectiveness of the proposed method

ACUTE EFFECT OF VIBRATORY STIMULATION ON ELBOW JOINT FLEXOR PERFORMANCE

A novel design of vibratory stimulation training system which can provide precisely controlled smooth force profile to the participants is introduced. All participants received 4 treatments with 20s of vibratory stimulation at a specific frequency and amplitude. The experimental data were analyzed through the two-way repeated-measures ANOVA analysis, with the independent variables being vibratory frequency and amplitude, and the dependent variables EMGrms, Fmax, RFD0.5s, and Fave. An optimal vibratory stimulation pattern was found from this study that has the most significant acute effect on the elbow joint flexor muscle performance: a 60% maximal force loading combined with vibratory stimulation at a frequency of 2.5 Hz and amplitude of 1 N sustained over 20s

IDENTIFYING GAIT ASYMMETRY USING DIGITAL SENSORS

The purpose of this study was to determine which phases and kinematics were easier to identify gait asymmetry by using digital sensors. Sixteen participants were recruited in this study. The participants were requested to walk naturally under two conditions (with or without asymmetrical load). Four digital sensor sets were attached on 4 limbs to collect kinematics data. The results showed that only the AS1 of Medial-Later acceleration of upper limb on the stance phase significantly different between unloading and loading conditions; on the lower limb were AS1 of Superior-Inferior acceleration and Flex/Extension angular velocity on the swing phase. The digital sensors that attach on upper and lower limbs both can detect gait asymmetry, but the asymmetrical phase and kinematics are different on upper and lower limbs

The Information-Leveling Role of Voluntary Disclosure Quality in Facilitating Investment Efficiency

This study examines whether and under what conditions voluntary disclosure quality plays an information-leveling role in facilitating investment efficiency. Measuring voluntary disclosure quality as the (inverse) standard deviation of managers’ prior earnings forecast errors (i.e., management forecast consistency), we document a positive association between management forecast consistency and investment efficiency that strengthens when the information environment becomes more constrained and when there are negative shocks to financial reporting quality. We also find that the management forecast consistency/investment efficiency association strengthens when firms are younger, faster growing, and financially constrained, but not when firms are weakly governed and financially unconstrained, which suggests that voluntary disclosure quality facilitates investment efficiency by mitigating adverse selection (but not moral hazard) frictions. Last, when we employ a changes-based model, we find that increases in management forecast consistency are associated with increases in investment efficiency, which mitigates concerns that voluntary disclosure quality’s empirical link to investment efficiency is purely driven by managers’ inherent forecasting abilities. Overall, we show that voluntary disclosure quality can facilitate investment efficiency when financial reporting and other elements of the information environment are constrained in their ability to mitigate market frictions that impede efficiency