Biophysically Accurate Brain Modeling and Simulation using Hybrid MPI/OpenMP Parallel Processing

In order to better understand the behavior of the human brain, it is very important to perform large scale neural network simulation which may reveal the relationship between the whole network activity and the biophysical dynamics of individual neurons. However, considering the complexity of the network and the large amount of variables, researchers choose to either simulate smaller neural networks or use simple spiking neuron models. Recently, supercomputing platforms have been employed to greatly speedup the simulation of large brain models. However, there are still limitations of these works such as the simplicity of the modeled network structures and lack of biophysical details in the neuron models. In this work, we propose a parallel simulator using biophysically realistic neural models for the simulation of large scale neural networks. In order to improve the performance of the simulator, we adopt several techniques such as merging linear synaptic receptors mathematically and using two level time steps, which significantly accelerate the simulation. In addition, we exploit the efficiency of parallel simulation through three parallel implementation strategies: MPI parallelization, MPI parallelization with dynamic load balancing schemes and Hybrid MPI/OpenMP parallelization. Through experimental studies, we illustrate the limitation of MPI implementation due to the imbalanced workload among processors. It is shown that the two developed MPI load balancing schemes are not able to improve the simulation efficiency on the targeted parallel platform. Using 32 processors, the proposed hybrid approach, on the other hand, is more efficient than the MPI implementation and is about 31X faster than a serial implementation of the simulator for a network consisting of more than 100,000 neurons. Finally, it is shown that for large neural networks, the presented approach is able to simulate the transition from the 3Hz delta oscillation to epileptic behaviors due to the alterations of underlying cellular mechanisms

Mitigating Coherent Noise by Balancing Weight-2 ZZ-Stabilizers

Physical platforms such as trapped ions suffer from coherent noise where errors manifest as rotations about a particular axis and can accumulate over time. We investigate passive mitigation through decoherence free subspaces, requiring the noise to preserve the code space of a stabilizer code, and to act as the logical identity operator on the protected information. Thus, we develop necessary and sufficient conditions for all transversal $Z$-rotations to preserve the code space of a stabilizer code, which require the weight-$2$ $Z$-stabilizers to cover all the qubits that are in the support of some $X$-component. Further, the weight-$2$ $Z$-stabilizers generate a direct product of single-parity-check codes with even block length. By adjusting the size of these components, we are able to construct a large family of QECC codes, oblivious to coherent noise, that includes the $[[4L^2, 1, 2L]]$ Shor codes. Moreover, given $M$ even and any $[[n,k,d]]$ stabilizer code, we can construct an $[[Mn, k, \ge d]]$ stabilizer code that is oblivious to coherent noise. If we require that transversal $Z$-rotations preserve the code space only up to some finite level $l$ in the Clifford hierarchy, then we can construct higher level gates necessary for universal quantum computation. The $Z$-stabilizers supported on each non-zero $X$-component form a classical binary code C, which is required to contain a self-dual code, and the classical Gleason's theorem constrains its weight enumerator. The conditions for a stabilizer code being preserved by transversal $2\pi/2^l$ $Z$-rotations at $4 \le l \le l_{\max} <\infty$ level in the Clifford hierarchy lead to generalizations of Gleason's theorem that may be of independent interest to classical coding theorists.Comment: Jingzhen Hu and Qingzhong Liang contributed equally to this work. The paper was accepted to IEEE Transactions on Information Theory. The ISIT paper is available as an ancillary fil

CERKL regulates autophagy via the NAD-dependent deacetylase SIRT1

<p>Macroautophagy/autophagy is an important intracellular mechanism for the maintenance of cellular homeostasis. Here we show that the <i>CERKL</i> (ceramide kinase like) gene, a retinal degeneration (RD) pathogenic gene, plays a critical role in regulating autophagy by stabilizing SIRT1. <i>In vitro</i> and <i>in vivo</i>, suppressing CERKL results in impaired autophagy. SIRT1 is one of the main regulators of acetylation/deacetylation in autophagy. In CERKL-depleted retinas and cells, SIRT1 is downregulated. ATG5 and ATG7, 2 essential components of autophagy, show a higher degree of acetylation in CERKL-depleted cells. Overexpression of SIRT1 rescues autophagy in CERKL-depleted cells, whereas CERKL loses its function of regulating autophagy in SIRT1-depleted cells, and overexpression of CERKL upregulates SIRT1. Finally, we show that CERKL directly interacts with SIRT1, and may regulate its phosphorylation at Ser27 to stabilize SIRT1. These results show that CERKL is an important regulator of autophagy and it plays this role by stabilizing the deacetylase SIRT1.</p

The splicing factor DHX38 enables retinal development through safeguarding genome integrity

DEAH-Box Helicase 38 (DHX38) is a pre-mRNA splicing factor and also a disease-causing gene of autosomal recessive retinitis pigmentosa (arRP). The role of DHX38 in the development and maintenance of the retina remains largely unknown. In this study, by using the dhx38 knockout zebrafish model, wedemonstrated that Dhx38 deficiency causes severe differentiation defects and apoptosis of retinal progenitor cells (RPCs) through disrupted mitosis and increased DNA damage. Furthermore, we found a significant accumulation of R-loops in the dhx38-deficient RPCs and human cell lines. Finally, we found that DNA replication stress is the prerequisite for R-loop-induced DNA damage in the DHX38 knockdown cells. Taken together, our study demonstrates a necessary role of DHX38 in the development of retina and reveals a DHX38/R-loop/replication stress/DNA damage regulatory axis that is relatively independent of the known functions of DHX38 in mitosis control

Enhanced Photocatalytic Production of H2O2 by Nafion Coatings on S,N-Codoped Graphene-Quantum-Dots-Modified TiO2

Photocatalytic production of H2O2 requires simultaneous promotion of the formation and the suppression of the decomposition of H2O2. This work explored a promising strategy of Nafion (perfluorinated polymer with sulfonate groups) coatings to enhance photocatalytic H2O2 production. The presence of Nafion layer on the S,N-codoped graphene-quantum-dots-modified TiO2 was characterized by transmission electron microscopy, Fourier transform infrared, and X-ray photoelectron spectroscopy measurements. The incorporation of Nafion coatings significantly improves the photocatalytic production of H2O2 (373 μM/h under simulated sunlight irradiation), which is about 70% higher than that without Nafion coatings. Both accelerated formation (34.8 μM/min) and dramatically inhibited decomposition (0.003 min-1) of H2O2 contribute to the efficient production of H2O2. Moreover, the ratios of H2O2 formation rate in the presence and absence of Nafion layers are more significantly improved at the neutral pH, which are 1.2 and 1.7 at pH 3 and 6.5, respectively. Nafion coatings show the abilities to induce a strongly negative charged hydrophobic surface, which can enhanced the local proton activity and oxygen concentration on the catalyst surface. The enhanced production of H2O2 by Nafion coatings can be attributed to the unaltered two-electron oxygen reduction reaction (ORR) pathway, the promoted charge transfer, the enhanced proton activity and oxygen diffusion, and the blocked formation of surface peroxide complexes. This work provides an insight for the modulation of proton-coupled electron-transfer-dominated ORR in photocatalysis through surface modification of Nafion coatings