Genome-wide DNA hypomethylation and RNA:DNA hybrid accumulation in Aicardi-Goutières syndrome.

Aicardi-Goutières syndrome (AGS) is a severe childhood inflammatory disorder that shows clinical and genetic overlap with systemic lupus erythematosus (SLE). AGS is thought to arise from the accumulation of incompletely metabolized endogenous nucleic acid species owing to mutations in nucleic acid-degrading enzymes TREX1 (AGS1), RNase H2 (AGS2, 3 and 4), and SAMHD1 (AGS5). However, the identity and source of such immunogenic nucleic acid species remain undefined. Using genome-wide approaches, we show that fibroblasts from AGS patients with AGS1-5 mutations are burdened by excessive loads of RNA:DNA hybrids. Using MethylC-seq, we show that AGS fibroblasts display pronounced and global loss of DNA methylation and demonstrate that AGS-specific RNA:DNA hybrids often occur within DNA hypomethylated regions. Altogether, our data suggest that RNA:DNA hybrids may represent a common immunogenic form of nucleic acids in AGS and provide the first evidence of epigenetic perturbations in AGS, furthering the links between AGS and SLE

Power Balance AODV Algorithm of WSN in Agriculture Monitoring

 WSN (wireless sensor networks) is a kind of energy-constrained network, which has been widely used in precision agriculture environment monitoring. However, power balance is not taken into account in traditional routing algorithms. In this paper, a novel Power Balance Ad hoc On-Demand Distance Vector (PB-AODV) routing algorithm is proposed on cross-layer design to solve the problem of power balance. The main idea of our proposed algorithm is that, routing path is established by the received signal strength indication (RSSI) value in the route discovery process of PB-AODV. The optimal transmitting power which can be computed by RSSI value, power threshold and node’s surplus energy is encapsulated into route reply packet (RRP). Thus, the sender node can adaptively adjust its transmission power to save energy with the RRP. Simulation results show that the proposed algorithm is effective for load balancing, and increases the WSN’s lifetime about 14.3%

Planning analysis for locally advanced lung cancer: dosimetric and efficiency comparisons between intensity-modulated radiotherapy (IMRT), single-arc/partial-arc volumetric modulated arc therapy (SA/PA-VMAT)

<p>Abstract</p> <p>Purpose</p> <p>To analyze the differences between the intensity-modulated radiotherapy (IMRT), single/partial-arc volumetric modulated arc therapy (SA/PA-VMAT) techniques in treatment planning for locally advanced lung cancer.</p> <p>Materials and methods</p> <p>12 patients were retrospectively studied. In each patient's case, several parameters were analyzed based on the dose-volume histograms (DVH) of the IMRT, SA/PA-VMAT plans respectively. Also, each plan was delivered to a phantom for time comparison.</p> <p>Results</p> <p>The SA-VMAT plans showed the superior target dose coverage, although the minimum/mean/maximum doses to the target were similar. For the total and contralateral lungs, the higher V_5/10, lower V_20/30and mean lung dose (MLD) were observed in the SA/PA-VMAT plans (<it>p </it>< 0.05, respectively). The PA-VMAT technique improves the dose sparing (V₂₀, V₃₀and MLD) of the controlateral lung more notably, comparing to those parameters of the IMRT and SA-VMAT plans respectively. The delivered monitor units (MUs) and treatment times were reduced significantly with VMAT plans, especially PA-VMAT plans (for MUs: mean 458.3 <it>vs</it>. 439.2 <it>vs</it>. 435.7 MUs, <it>p </it>< 0.05 and for treatment time: mean 13.7 <it>vs</it>. 10.6 <it>vs</it>. 6.4 minutes, <it>p </it>< 0.01).</p> <p>Conclusions</p> <p>The SA-VMAT technique achieves highly conformal dose distribution to the target. Comparing to the IMRT plans, the higher V_5/10, lower V_20/30and MLD were observed in the total and contralateral lungs in the VMAT plans, especially in the PA-VMAT plans. The SA/PA-VMAT plans also reduced treatment time with more efficient dose delivering. But the clinical benefit of the VMAT technique for locally advanced lung cancer needs further investigations.</p

Adversarial Attacks on Video Object Segmentation with Hard Region Discovery

Video object segmentation has been applied to various computer vision tasks, such as video editing, autonomous driving, and human-robot interaction. However, the methods based on deep neural networks are vulnerable to adversarial examples, which are the inputs attacked by almost human-imperceptible perturbations, and the adversary (i.e., attacker) will fool the segmentation model to make incorrect pixel-level predictions. This will rise the security issues in highly-demanding tasks because small perturbations to the input video will result in potential attack risks. Though adversarial examples have been extensively used for classification, it is rarely studied in video object segmentation. Existing related methods in computer vision either require prior knowledge of categories or cannot be directly applied due to the special design for certain tasks, failing to consider the pixel-wise region attack. Hence, this work develops an object-agnostic adversary that has adversarial impacts on VOS by first-frame attacking via hard region discovery. Particularly, the gradients from the segmentation model are exploited to discover the easily confused region, in which it is difficult to identify the pixel-wise objects from the background in a frame. This provides a hardness map that helps to generate perturbations with a stronger adversarial power for attacking the first frame. Empirical studies on three benchmarks indicate that our attacker significantly degrades the performance of several state-of-the-art video object segmentation models