A Design and Prototyping of In-Network Processing Platform to Enable Adaptive Network Services

The explosive growth of the usage along with a greater diversification of communication technologies and applications imposes the Internet to manage further scalability and diversity, requiring more adaptive and flexible sharing schemes of network resources. Especially when a number of large-scale distributed applications concurrently share the resource, efficacy of comprehensive usage of network, computation, and storage resources is needed from the viewpoint of information processing performance. Therefore, a reconsideration of the coordination and partitioning of functions between networks (providers) and applications (users) has become a recent research topic. In this paper, we first address the need and discuss the feasibility of adaptive network services by introducing special processing nodes inside the network. Then, a design and an implementation of an advanced relay node platform are presented, by which we can easily prototype and test a variety of advanced in-network processing on Linux and off-the-shelf PCs. A key feature of the proposed platform is that integration between kernel and userland spaces enables to easily and quickly develop various advanced relay processing. Finally, on the top of the advanced relay node platform, we implement and test an adaptive packet compression scheme that we previously proposed. The experimental results show the feasibility of both the developed platform and the proposed adaptive packet compression

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Non-learning Stereo-aided Depth Completion under Mis-projection via Selective Stereo Matching

We propose a non-learning depth completion method for a sparse depth map captured using a light detection and ranging (LiDAR) sensor guided by a pair of stereo images. Generally, conventional stereo-aided depth completion methods have two limiations. (i) They assume the given sparse depth map is accurately aligned to the input image, whereas the alignment is difficult to achieve in practice. (ii) They have limited accuracy in the long range because the depth is estimated by pixel disparity. To solve the abovementioned limitations, we propose selective stereo matching (SSM) that searches the most appropriate depth value for each image pixel from its neighborly projected LiDAR points based on an energy minimization framework. This depth selection approach can handle any type of mis-projection. Moreover, SSM has an advantage in terms of long-range depth accuracy because it directly uses the LiDAR measurement rather than the depth acquired from the stereo. SSM is a discrete process; thus, we apply variational smoothing with binary anisotropic diffusion tensor (B-ADT) to generate a continuous depth map while preserving depth discontinuity across object boundaries. Experimentally, compared with the previous state-of-the-art stereo-aided depth completion, the proposed method reduced the mean absolute error (MAE) of the depth estimation to 0.65 times and demonstrated approximately twice more accurate estimation in the long range. Moreover, under various LiDAR-camera calibration errors, the proposed method reduced the depth estimation MAE to 0.34-0.93 times from previous depth completion methods.Comment: 15 pages, 13 figure

Compressing Packets Adaptively Inside Networks

Introducing adaptive online data compression at network-internal nodes is considered for alleviating traffic congestion on the network. In this paper, we assume that advanced relay nodes, which possess both a relay function (network resource) and a processing function (computational and storage resources), are placed inside the network, and we propose an adaptive online lossless packet compression scheme utilized at these nodes. This scheme selectively compresses a packet according to its waiting time in the queue during congestion. Through preliminary investigation using actual traffic datasets, we investigate the compression ratio and processing time of packet-by-packet compression in actual network environments. Then, by means of computer simulations, we show that the proposed scheme reduces the packet delay time and discard rate and investigate factors necessary in achieving efficient packet relay

Evaluation of the Pichia pastoris expression system for the production of GPCRs for structural analysis

<p>Abstract</p> <p>Background</p> <p>Various protein expression systems, such as <it>Escherichia coli </it>(<it>E. coli</it>), <it>Saccharomyces cerevisiae </it>(<it>S. cerevisiae</it>), <it>Pichia pastoris </it>(<it>P. pastoris</it>), insect cells and mammalian cell lines, have been developed for the synthesis of G protein-coupled receptors (GPCRs) for structural studies. Recently, the crystal structures of four recombinant human GPCRs, namely β₂adrenergic receptor, adenosine A_2areceptor, CXCR4 and dopamine D3 receptor, were successfully determined using an insect cell expression system. GPCRs expressed in insect cells are believed to undergo mammalian-like posttranscriptional modifications and have similar functional properties than in mammals. Crystal structures of GPCRs have not yet been solved using yeast expression systems. In the present study, <it>P. pastoris </it>and insect cell expression systems for the human muscarinic acetylcholine receptor M2 subtype (CHRM2) were developed and the quantity and quality of CHRM2 synthesized by both expression systems were compared for the application in structural studies.</p> <p>Results</p> <p>The ideal conditions for the expression of CHRM2 in <it>P. pastoris </it>were 60 hr at 20°C in a buffer of pH 7.0. The specific activity of the expressed CHRM2 was 28.9 pmol/mg of membrane protein as determined by binding assays using [³H]-quinuclidinyl benzilate (QNB). Although the specific activity of the protein produced by <it>P. pastoris </it>was lower than that of Sf9 insect cells, CHRM2 yield in <it>P. pastoris </it>was 2-fold higher than in Sf9 insect cells because <it>P. pastoris </it>was cultured at high cell density. The dissociation constant (Kd) for QNB in <it>P. pastoris </it>was 101.14 ± 15.07 pM, which was similar to that in Sf9 insect cells (86.23 ± 8.57 pM). There were no differences in the binding affinity of CHRM2 for QNB between <it>P. pastoris </it>and Sf9 insect cells.</p> <p>Conclusion</p> <p>Compared to insect cells, <it>P. pastoris </it>is easier to handle, can be grown at lower cost, and can be expressed quicker at a large scale. Yeast, <it>P. pastoris</it>, and insect cells are all effective expression systems for GPCRs. The results of the present study strongly suggested that protein expression in <it>P. pastoris </it>can be applied to the structural and biochemical studies of GPCRs.</p

Penetration of the sigmoid colon to the posterior uterine wall secondary to diverticulitis: a case report

<p>Abstract</p> <p>Introduction</p> <p>Penetration of the colon to the posterior uterine wall secondary to diverticulitis is unusual, with diagnostic methods not yet established. Non-invasive imaging, such as computed tomography and magnetic resonance imaging may help to establish a proper diagnosis, but confirmation may be reached only after surgical exploration.</p> <p>Case presentation</p> <p>We report the case of a 78-year-old Japanese woman who presented with a low grade fever and mild diarrhea which occurred two or three times a week. Computed tomography and magnetic resonance imaging demonstrated a capsular lesion including an air structure with a diameter of 5 cm, between the posterior aspect of the uterine body and the sigmoid colon. A gastrograffin enema and colonoscopy demonstrated a giant diverticulum of the sigmoid colon with no evidence of malignancy. These data confirmed the diagnosis of diverticulitis complicated by a giant diverticulum. Because of a relapsing fever after therapy with antibiotics, the patient had en bloc surgical treatment of the uterus, fallopian tubes, ovaries and sigmoid colon, the organs involved in the diverticulitis, followed by an uneventful recovery.</p> <p>Conclusion</p> <p>This is a rare case report of penetration of the sigmoid colon to the posterior uterine wall secondary to diverticulitis.</p

Efficacy of BET bromodomain inhibition in Kras-mutant non-small cell lung cancer

PurposeAmplification of MYC is one of the most common genetic alterations in lung cancer, contributing to a myriad of phenotypes associated with growth, invasion and drug resistance. Murine genetics has established both the centrality of somatic alterations of Kras in lung cancer, as well as the dependency of mutant Kras tumors on MYC function. Unfortunately, drug-like small-molecule inhibitors of KRAS and MYC have yet to be realized. The recent discovery, in hematologic malignancies, that BET bromodomain inhibition impairs MYC expression and MYC transcriptional function established the rationale of targeting KRAS-driven NSCLC with BET inhibition.Experimental DesignWe performed functional assays to evaluate the effects of JQ1 in genetically defined NSCLC cells lines harboring KRAS and/or LKB1 mutations. Furthermore, we evaluated JQ1 in transgenic mouse lung cancer models expressing mutant kras or concurrent mutant kras and lkb1. Effects of bromodomain inhibition on transcriptional pathways were explored and validated by expression analysis.ResultsWhile JQ1 is broadly active in NSCLC cells, activity of JQ1 in mutant KRAS NSCLC is abrogated by concurrent alteration or genetic knock-down of LKB1. In sensitive NSCLC models, JQ1 treatment results in the coordinate downregulation of the MYC-dependent transcriptional program. We found that JQ1 treatment produces significant tumor regression in mutant kras mice. As predicted, tumors from mutant kras and lkb1 mice did not respond to JQ1.ConclusionBromodomain inhibition comprises a promising therapeutic strategy for KRAS mutant NSCLC with wild-type LKB1, via inhibition of MYC function. Clinical studies of BET bromodomain inhibitors in aggressive NSCLC will be actively pursued

PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data

BACKGROUND: Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy. RESULTS: We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility. CONCLUSIONS: PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org .The authors thank Joaquín Dopazo, Patricia León, and José Carbonell for kindly providing the modelled pathways employed in PanDrugs implementation; and Michael Tress for his helpful comments and suggestions in the earlier version of the manuscript.S