Huaqiang Wu

Interaction of Sirt3 with OGG1 contributes to repair of mitochondrial DNA and protects from apoptotic cell death under oxidative stress

Sirtuin 3 (Sirt3), a major mitochondrial NAD+-dependent deacetylase, targets various mitochondrial proteins for lysine deacetylation and regulates important cellular functions such as energy metabolism, aging, and stress response. In this study, we identified the human 8-oxoguanine-DNA glycosylase 1 (OGG1), a DNA repair enzyme that excises 7,8-dihydro-8-oxoguanine (8-oxoG) from damaged genome, as a new target protein for Sirt3. We found that Sirt3 physically associated with OGG1 and deacetylated this DNA glycosylase and that deacetylation by Sirt3 prevented the degradation of the OGG1 protein and controlled its incision activity. We further showed that regulation of the acetylation and turnover of OGG1 by Sirt3 played a critical role in repairing mitochondrial DNA (mtDNA) damage, protecting mitochondrial integrity, and preventing apoptotic cell death under oxidative stress. We observed that following ionizing radiation, human tumor cells with silencing of Sirt3 expression exhibited deteriorated oxidative damage of mtDNA, as measured by the accumulation of 8-oxoG and 4977 common deletion, and showed more severe mitochondrial dysfunction and underwent greater apoptosis in comparison with the cells without silencing of Sirt3 expression. The results reported here not only reveal a new function and mechanism for Sirt3 in defending the mitochondrial genome against oxidative damage and protecting from the genotoxic stress-induced apoptotic cell death but also provide evidence supporting a new mtDNA repair pathway.

An artificial nociceptor based on a diffusive memristor

Axa0nociceptor is a critical and special receptor of a sensory neuron that is able to detect noxious stimulus and provide a rapid warning to the central nervous system to start the motor response in the human body and humanoid robotics. It differs from other common sensory receptors with its key features and functions, including the “no adaptation” and “sensitization” phenomena. In this study, we propose and experimentally demonstrate an artificial nociceptor based on a diffusive memristor with critical dynamics for the first time. Using this artificial nociceptor, we further built an artificial sensory alarm system to experimentally demonstrate the feasibility and simplicity of integrating such novel artificial nociceptor devices in artificial intelligence systems, such as humanoid robots.The development of humanoid robots with artificial intelligence calls for smart solutions for tactile sensing systems that respondxa0to dynamic changes in the environment. Here, Yoon et al. emulate non-adaption and sensitization function of axa0nociceptor—a sensory neuron—using diffusive oxide-based memristors.

A New Model for Two-Dimensional Electrical-Field-Dependent

The 2-D electrical-field-dependent hot-hole-related negative-bias temperature instability (HH-NBTI) behaviors of pMOSFETs with 1.7-nm decoupled-plasma-nitridation oxynitride dielectrics are investigated. The lateral-channel electric-field-induced turnaround HH-NBTI degradation that is associated with the enhanced breaking effect of the interfacial Si-H bonds at the Si interface is demonstrated. For the first time, the lateral-electric-field-dependent activation energy of ≡ Si- H bond dissociation is presented. A new model taking into account the 2-D electric field effects is proposed to depict the HH-NBTI behaviors related to the lateral- and vertical-channel electric fields. The proposed model is verified by the experimental data.

V_{\rm th}

Experimental demonstration of resistive neural networks has been the recent focus of hardware implementation of neuromorphic computing. Capacitive neural networks, which call for novel building blocks, provide an alternative physical embodiment of neural networks featuring a lower static power and a better emulation of neural functionalities. Here, we develop neuro-transistors by integrating dynamic pseudo-memcapacitors as the gates of transistors to produce electronic analogs of the soma and axon of a neuron, with “leaky integrate-and-fire” dynamics augmented by a signal gain on the output. Paired with non-volatile pseudo-memcapacitive synapses, axa0Hebbian-like learning mechanism is implemented in a capacitive switching network, leading to the observed associative learning. A prototypical fully integrated capacitive neural network is built and used to classify inputs of signals.Though memristors can potentially emulate neuron and synapse functionality, useful signal energy is lost to Joule heating. Here, the authors demonstrate neuro-transistors with a pseudo-memcapacitive gate that actively process signals via energy-efficient capacitively-coupled neural networks.