Heat shock-induced phosphorylation of TAR DNA-binding protein 43 (TDP-43) by MAPK/ERK kinase regulates TDP-43 function

TAR DNA-binding protein (TDP-43) is a highly conserved and essential DNA- and RNA-binding protein that controls gene expression through RNA processing, in particular, regulation of splicing. Intracellular aggregation of TDP-43 is a hallmark of amyotrophic lateral sclerosis and ubiquitin-positive frontotemporal lobar degeneration. This TDP-43 pathology is also present in other types of neurodegeneration including Alzheimer's disease. We report here that TDP-43 is a substrate of MEK, a central kinase in the MAPK/ERK signaling pathway. TDP-43 dual phosphorylation by MEK, at threonine 153 and tyrosine 155 (p-T153/Y155), was dramatically increased by the heat shock response (HSR) in human cells. HSR promotes cell survival under proteotoxic conditions by maintaining protein homeostasis and preventing protein misfolding. MEK is activated by HSR and contributes to the regulation of proteome stability. Phosphorylated TDP-43 was not associated with TDP-43 aggregation, and p-T153/Y155 remained soluble under conditions that promote protein misfolding. We found that active MEK significantly alters TDP-43-regulated splicing and that phosphomimetic substitutions at these two residues reduce binding to GU-rich RNA. Cellular imaging using a phospho-specific p-T153/Y155 antibody showed that phosphorylated TDP-43 was specifically recruited to the nucleoli, suggesting that p-T153/Y155 regulates a previously unappreciated function of TDP-43 in the processing of nucleolar-associated RNA. These findings highlight a new mechanism that regulates TDP-43 function and homeostasis through phosphorylation and, therefore, may contribute to the development of strategies to prevent TDP-43 aggregation and to uncover previously unexplored roles of TDP-43 in cell metabolism

Recent advances on recursive filtering and sliding mode design for networked nonlinear stochastic systems: A survey

Copyright © 2013 Jun Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Some recent advances on the recursive filtering and sliding mode design problems for nonlinear stochastic systems with network-induced phenomena are surveyed. The network-induced phenomena under consideration mainly include missing measurements, fading measurements, signal quantization, probabilistic sensor delays, sensor saturations, randomly occurring nonlinearities, and randomly occurring uncertainties. With respect to these network-induced phenomena, the developments on filtering and sliding mode design problems are systematically reviewed. In particular, concerning the network-induced phenomena, some recent results on the recursive filtering for time-varying nonlinear stochastic systems and sliding mode design for time-invariant nonlinear stochastic systems are given, respectively. Finally, conclusions are proposed and some potential future research works are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grant nos. 61134009, 61329301, 61333012, 61374127 and 11301118, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant no. GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Factors of Influence on the Performance of a Short-Latency Non-Invasive Brain Switch: Evidence in Healthy Individuals and Implication for Motor Function Rehabilitation.

Brain-computer interfacing (BCI) has recently been applied as a rehabilitation approach for patients with motor disorders, such as stroke. In these closed-loop applications, a brain switch detects the motor intention from brain signals, e.g., scalp EEG, and triggers a neuroprosthetic device, either to deliver sensory feedback or to mimic real movements, thus re-establishing the compromised sensory-motor control loop and promoting neural plasticity. In this context, single trial detection of motor intention with short latency is a prerequisite. The performance of the event detection from EEG recordings is mainly determined by three factors: the type of motor imagery (e.g., repetitive, ballistic), the frequency band (or signal modality) used for discrimination (e.g., alpha, beta, gamma, and MRCP, i.e., movement-related cortical potential), and the processing technique (e.g., time-series analysis, sub-band power estimation). In this study, we investigated single trial EEG traces during movement imagination on healthy individuals, and provided a comprehensive analysis of the performance of a short-latency brain switch when varying these three factors. The morphological investigation showed a cross-subject consistency of a prolonged negative phase in MRCP, and a delayed beta rebound in sensory-motor rhythms during repetitive tasks. The detection performance had the greatest accuracy when using ballistic MRCP with time-series analysis. In this case, the true positive rate (TPR) was ~70% for a detection latency of ~200 ms. The results presented here are of practical relevance for designing BCI systems for motor function rehabilitation

Realtime processing of LOFAR data for the detection of nano-second pulses from the Moon

The low flux of the ultra-high energy cosmic rays (UHECR) at the highest energies provides a challenge to answer the long standing question about their origin and nature. Even lower fluxes of neutrinos with energies above $10^{22}$ eV are predicted in certain Grand-Unifying-Theories (GUTs) and e.g.\ models for super-heavy dark matter (SHDM). The significant increase in detector volume required to detect these particles can be achieved by searching for the nano-second radio pulses that are emitted when a particle interacts in Earth's moon with current and future radio telescopes. In this contribution we present the design of an online analysis and trigger pipeline for the detection of nano-second pulses with the LOFAR radio telescope. The most important steps of the processing pipeline are digital focusing of the antennas towards the Moon, correction of the signal for ionospheric dispersion, and synthesis of the time-domain signal from the polyphased-filtered signal in frequency domain. The implementation of the pipeline on a GPU/CPU cluster will be discussed together with the computing performance of the prototype.Comment: Proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP2016), US