High-confidence fusion gene detection in different tumor entities & biomarker discovery in breast cancer

Fusion genes play an important role in the tumorigenesis of many cancers. Next generation sequencing (NGS) methods such as RNA-seq provide accurate, high-resolution data, which makes unbiased fusion detection much more feasible. Most fusion detection tools based on RNA-seq data report a great number of candidates (mostly false positives), making it hard to prioritize candidates for validation. I therefore developed confFuse, a scoring algorithm to reliably select high-confidence fusion genes which are likely to be biologically relevant. Compared with alternative tools based on 96 published RNA-seq samples from six different tumor entities, confFuse dramatically reduces the number of fusion candidates (301 high-confidence from 8083 predicted fusion genes, ~3.7%) and retains high detection accuracy (recovery rate 85.7% of previously validated fusions). Another analysis of 27 unpublished tumors of various origins, results in a recovery rate of ~93% (25/27). Furthermore, a screen of 22 GBM tumors shows 242 high-confidence fusions from 6,018 candidates (~4%), of which ~62% (150/242) were previously validated or harbor supporting reads in DNA-seq. Similarly, in 11 published prostate cancer tumors ~72% high-confidence fusions (17/24 from 849 predictions) have supporting evidence. Validation of 18 high-confidence fusions detected in three primary breast tumor samples resulted in a 100% true positive rate. When applying confFuse on three CLL samples, 15 of 18 candidates were successfully validated. In summary, confFuse can reliably select high-confidence fusion genes that are more likely to be biologically relevant, achieving both high validation rate and high detection accuracy, while reducing the number of candidates to a restricted number for validation. A genetic analysis of primary and refractory breast cancer tumors identified different aberrations in CNVs, SNVs/Indels and rearrangements. Mutations of microtubule-associated serine-threonine kinase (MAST) and 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase beta (PLCB) gene family members were only detected in refractory tumors (3/50 and 4/50, respectively). Mutations of members of the calcium channel, voltage-dependent, alpha (CACNA) gene family members, which are involved in the MAPK signalling pathway, are highly prevalent in refractory tumors (24%, 12/50) compared to primary tumors (~2%, 1/46). Rearrangements of CACNA were also identified in one primary and two refractory tumors, and PLCB in three refractory tumors. This suggests that mutations of MAST, CACNA or PLCB gene families may be a novel acquired resistance mechanism in addition to ESR1 mutation. Hundreds of known or novel fusion genes were identified by confFuse in seven unpublished tumor cohorts, including more than 60 highly reliable fusion proteins in breast cancer. Furthermore, different chromosome-wide enrichments of fusion genes were identified across tumor entities. Overall, a comprehensive landscape of fusion genes in different tumor entities was provided to give an insight for biomarker discovery, especially in breast cancer

A Compact Wearable System for Detection and Estimation of Open Wound Status In Diabetic Patient

In this paper, a new smart health embedded system that can notify users the status of an open wound to assure correct cicatrisation in real-time for ulcer foot in diabetes prevention has been designed. Specifically, this system monitors the healing process through the saturation of exudate in the absorbent dressing and the pathogen of infection by estimating the top gas of wound based on the various bacteria's metabolites. The collected information has been transmitted on portable devices in real time to inform the patient the current condition of wound and give advice. Finally, the algorithm of diabetes wound healing process is explored in this work, which can also be applied for related medical research in the diabetes preventions. The measurement results have an error of 0.9% and 2.3%, respectively for temperature and humidity in detection of cicatrisation. In the evaluation of pathogen of wound infection, the error of predicting the concentration of different gases (Sulfo-compound, Ethanol and Aldehyde) was only 2.8%

Deriving a Control-Oriented Model for an Axisymmetric Vehicle With the Power-Law Revolution Nose

The purpose of this paper is to construct a new general vehicle model as an open fundamental material for the guidance and control research. In this study, parameterized configuration, aerodynamics calculation, control-oriented modeling, stability analysis, and nominal trajectory design are performed for the general vehicle model. First, the aerodynamic configuration is parameterized as an axisymmetric body with a power-law revolution nose. Then, an engineering method considering inviscid flow, base drag and skin friction is used for the aerodynamics calculation, and a control-oriented fitting model of longitudinal aerodynamics is established based on the analysis of the correlation between aerodynamic force and the parameters of Mach number, attack angle, elevator deflection and height. Next, the aerothermodynamic environment prediction of power-law revolution axisymmetric hypersonic vehicle (PRAHV) is discussed, and the nose heating rate formula of PRAHV is established. The stability analysis and nominal trajectory design of PRAHV is performed based on the fitting model and the heating rate formula. The stability analysis shows that both the static stability and dynamic stability of the vehicle are unstable. The nominal trajectory of unpowered longitudinal maneuvering is achieved by the hp-adaptive pseudospectral method, which demonstrated that the availability of the control-oriented model established in this paper. In conclusion, this work provides a fundamental object for further study of vehicle guidance, control, and evaluation

New aneurysm formation after endovascular embolization of a vertebral epidural AV fistula: a rare sequelae of NF AV fistulae

BackgroundNeurofibromatosis type 1 (NF-1) is a dominant genetic disorder often accompanied by lesions of the neurovascular system. Patients with NF-1 are predisposed to unique vertebral artery fistula (AVF).Case descriptionWe report on a rare case of multiple neurovascular abnormalities in a 47-year-old man with neurofibromatosis. He was admitted due to a sudden headache and was found to have suffered a subarachnoid hemorrhage from a left vertebral arteriovenous fistula. He underwent two endovascular procedures complicated by a delayed extraspinal mass 7 days after treatment. Angiography revealed a new vascular abnormality, and although we performed another embolization, it failed to respond to further embolization.ConclusionVascular abnormalities in patients with NF-1 can be complex. Endovascular intervention remains feasible for NF-1 related AVF, however, partial occlusion of the fistula should be avoided to limit and iatrogenic damage to the blood vessels

Computation offloading in blockchain-enabled MCS systems : A scalable deep reinforcement learning approach

In Mobile Crowdsensing (MCS) systems, cloud service providers (CSPs) pay for and analyze the sensing data collected by mobile devices (MDs) to enhance the Quality-of-Service (QoS). Therefore, it is necessary to guarantee security when CSPs and users conduct transactions. Blockchain can secure transactions between two parties by using the Proof-of-Work (PoW) to confirm transactions and add new blocks to the chain. Nevertheless, the complex PoW seriously hinders applying Blockchain into MCS since MDs are equipped with limited resources. To address these challenges, we first design a new consortium blockchain framework for MCS, aiming to assure high reliability in complex environments, where a novel Credit-based Proof-of-Work (C-PoW) algorithm is developed to relieve the complexity of PoW while keeping the reliability of blockchain. Next, we propose a new scalable Deep Reinforcement learning based Computation Offloading (DRCO) method to handle the computation-intensive tasks of C-PoW. By combining Proximal Policy Optimization (PPO) and Differentiable Neural Computer (DNC), the DRCO can efficiently make the optimal/near-optimal offloading decisions for C-PoW tasks in blockchain-enabled MCS systems. Extensive experiments demonstrate that the DRCO reaches a lower total cost (weighted sum of latency and power consumption) than state-of-the-art methods under various scenarios

Hybrid graphene metasurfaces for high-speed mid-infrared light modulation and single-pixel imaging

During the past decades, major advances have been made in both the generation and detection of infrared light; however, its efficient wavefront manipulation and information processing still encounter great challenges. Efficient and fast optoelectronic modulators and spatial light modulators are required for mid-infrared imaging, sensing, security screening, communication and navigation, to name a few. However, their development remains elusive, and prevailing methods reported so far have suffered from drawbacks that significantly limit their practical applications. In this study, by leveraging graphene and metasurfaces, we demonstrate a high-performance free-space mid-infrared modulator operating at gigahertz speeds, low gate voltage and room temperature. We further pixelate the hybrid graphene metasurface to form a prototype spatial light modulator for high frame rate single-pixel imaging, suggesting orders of magnitude improvement over conventional liquid crystal or micromirror-based spatial light modulators. This work opens up the possibility of exploring wavefront engineering for infrared technologies for which fast temporal and spatial modulations are indispensable

Application of CRISPR-Cas system in the diagnosis and therapy of ESKAPE infections

Antimicrobial-resistant ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens represent a global threat to human health. ESKAPE pathogens are the most common opportunistic pathogens in nosocomial infections, and a considerable number of their clinical isolates are not susceptible to conventional antimicrobial therapy. Therefore, innovative therapeutic strategies that can effectively deal with ESKAPE pathogens will bring huge social and economic benefits and ease the suffering of tens of thousands of patients. Among these strategies, CRISPR (clustered regularly interspaced short palindromic repeats) system has received extra attention due to its high specificity. Regrettably, there is currently no direct CRISPR-system-based anti-infective treatment. This paper reviews the applications of CRISPR-Cas system in the study of ESKAPE pathogens, aiming to provide directions for the research of ideal new drugs and provide a reference for solving a series of problems caused by multidrug-resistant bacteria (MDR) in the post-antibiotic era. However, most research is still far from clinical application

In silico SNP analysis of the breast cancer antigen NY-BR-1

Background: Breast cancer is one of the most common malignancies with increasing incidences every year and a leading cause of death among women. Although early stage breast cancer can be effectively treated, there are limited numbers of treatment options available for patients with advanced and metastatic disease. The novel breast cancer associated antigen NY-BR-1 was identified by SEREX analysis and is expressed in the majority (>70%) of breast tumors as well as metastases, in normal breast tissue, in testis and occasionally in prostate tissue. The biological function and regulation of NY-BR-1 is up to date unknown. Methods: We performed an in silico analysis on the genetic variations of the NY-BR-1 gene using data available in public SNP databases and the tools SIFT, Polyphen and Provean to find possible functional SNPs. Additionally, we considered the allele frequency of the found damaging SNPs and also analyzed data from an in-house sequencing project of 55 breast cancer samples for recurring SNPs, recorded in dbSNP. Results: Over 2800 SNPs are recorded in the dbSNP and NHLBI ESP databases for the NY-BR-1 gene. Of these, 65 (2.07%) are synonymous SNPs, 191 (6.09%) are non-synoymous SNPs, and 2430 (77.48%) are noncoding intronic SNPs. As a result, 69 non-synoymous SNPs were predicted to be damaging by at least two, and 16 SNPs were predicted as damaging by all three of the used tools. The SNPs rs200639888, rs367841401 and rs377750885 were categorized as highly damaging by all three tools. Eight damaging SNPs are located in the ankyrin repeat domain (ANK), a domain known for its frequent involvement in protein-protein interactions. No distinctive features could be observed in the allele frequency of the analyzed SNPs. Conclusion: Considering these results we expect to gain more insights into the variations of the NY-BR-1 gene and their possible impact on giving rise to splice variants and therefore influence the function of NY-BR-1 in healthy tissue as well as in breast cancer