Studies of gene rearrangements and the consequent oncogenic fusion proteins have laid the foundation for targeted cancer therapy. To identify oncogenic fusions associated with glioma progression, we catalogued fusion transcripts by RNA-seq of 272 gliomas. Fusion transcripts were more frequently found in high-grade gliomas, in the classical subtype of gliomas, and in gliomas treated with radiation/temozolomide. Sixty-seven in-frame fusion transcripts were identified, including three recurrent fusion transcripts: FGFR3-TACC3, RNF213-SLC26A11, and PTPRZ1-MET (ZM). Interestingly, the ZM fusion was found only in grade III astrocytomas (1/13; 7.7%) or secondary GBMs (sGBMs, 3/20; 15.0%). In an independent cohort of sGBMs, the ZM fusion was found in three of 20 (15%) specimens. Genomic analysis revealed that the fusion arose from translocation events involving introns 3 or 8 of PTPRZ and intron 1 of MET. ZM fusion transcripts were found in GBMs irrespective of isocitrate dehydrogenase 1 (IDH1) mutation status. sGBMs harboring ZM fusion showed higher expression of genes required for PIK3CA signaling and lowered expression of genes that suppressed RB1 or TP53 function. Expression of the ZM fusion was mutually exclusive with EGFR overexpression in sGBMs. Exogenous expression of the ZM fusion in the U87MG glioblastoma line enhanced cell migration and invasion. Clinically, patients afflicted with ZM fusion harboring glioblastomas survived poorly relative to those afflicted with non-ZM-harboring sGBMs (P < 0.001). Our study profiles the shifting RNA landscape of gliomas during progression and reveled ZM as a novel, recurrent fusion transcript in sGBMs.

Mutation point feature of power quality (PQ) disturbance signals are very conducive to the wavelet-based detection and localization of PQ events, but the PQ signals are often disturbed by noise. In order to suppress noise and keep mutation points, an improved threshold function was proposed. According to the fact that the wavelet coefficients of signal and noise distributed on different scale, the threshold σj2lnk amended by to calculate threshold value for each scale adaptively. (k is the number of wavelet coefficients at level j). In simulation, four type of PQ signals and three degrading degrees are testing; meanwhile, four existing algorithm with wavelet shrinkage are performed for comparison. Results reveal that the proposed scheme not only suppresses noise of PQ signal well but also keeps the mutation points nicely.

Many traditional tremor sensors are in direct contact with the human body, we tried a new non-contact manner, using the ZigBee standard protocol stack, and constitutes a wireless sensor network (Wireless Sensor Network, WSN), so that it can meet the pathological signal acquisition under low power consumption. In this experiment the main object is to capture the tremor signal from the surface of Parkinson's patients, as well as the feasibility of this new approach. Taking into account the reliability of the data and the transmission efficiency of the whole system, we use the structure of the ZigBee-based star network, and in the receiving terminal to achieve a variety of interfaces to facilitate the transfer, storage and use of other systems and data access.

The prominent role of cascading outages in recent blackouts has created a need in security applications for evaluating line outage distribution factors (LODFs) under the multiple-line outages. Two fast algorithms of LODFs with multiple-line outages are proposed in this paper. In the first method, the double-line outage LODFs are expressed in terms of single-line outage LODFs, and it can be extended to N-k (k≥2) contingencies without any complex matrix operation through the recursive theory. In the second method, a computationally efficient expression of LODFs based on power transfer distribution factors (PTDFs) in pre-contingency network is presented. Numerical simulations are carried out on IEEE 14 and 118-bus test systems. The results show that both methods can effectively improve the computation speed of multiple-line outage LODFs.

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