Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture

We describe a new deep learning architecture for learning to rank question answer pairs. Our approach extends the long short-term memory (LSTM) network with holographic composition to model the relationship between question and answer representations. As opposed to the neural tensor layer that has been adopted recently, the holographic composition provides the benefits of scalable and rich representational learning approach without incurring huge parameter costs. Overall, we present Holographic Dual LSTM (HD-LSTM), a unified architecture for both deep sentence modeling and semantic matching. Essentially, our model is trained end-to-end whereby the parameters of the LSTM are optimized in a way that best explains the correlation between question and answer representations. In addition, our proposed deep learning architecture requires no extensive feature engineering. Via extensive experiments, we show that HD-LSTM outperforms many other neural architectures on two popular benchmark QA datasets. Empirical studies confirm the effectiveness of holographic composition over the neural tensor layer.Comment: SIGIR 2017 Full Pape

Camelid reporter gene imaging: a generic method for in vivo cell tracking

BACKGROUND: To combine the sensitivity of bioluminescent imaging (BLI) with the 3D and quantitative properties of pinhole single-photon emission computed tomography (SPECT)/micro-computed tomography (CT) (phSPECT/micro-CT), we generated stable cell lines that express a yellow-fluorescent protein (YFP) and Gaussia luciferase (GLuc) fusion protein (YFP/GLuc). For in vivo phSPECT detection of this YFP/GLuc protein, a nanobody, targeted against yellow and green fluorescent proteins (anti-YFP-Nb), was site specifically labelled with (99m)Tc. METHODS: Human embryonic kidney cells (HEK293T) were cultured and passaged every 3 days. 10E5 cells were transduced with YFP/GLuc-containing vector: both membrane-targeted (MT-YFP/GLuc) and non-targeted (YFP/GLuc) fusion proteins were developed. These vectors were compared against a SKOV-3 cell line stably expressing green fluorescent-firefly luciferase (GFP/Fluc) and HEK293T cells expressing red fluorescent protein in combination with a Gaussia luciferase (Red/GLuc). Transduction efficiencies were scored by fluorescence microscopy, and transduced cells were enriched by fluorescence-activated cell sorting (FACS). GLuc and FLuc functionality was tested in vitro by list-mode BLI. Subsequently, cells were transplanted subcutaneously in athymic (nu/nu) mice (MT-YFP/GLuc: n = 4, YFP/GLuc: n = 6, GFP/FLuc: n = 6, Red/GLuc: n = 4). Labelling efficiency of anti-YFP-Nb was measured using instant thin layer chromatography. One week after transplantation, (99m)Tc-labelled anti-YFP-Nb was injected intravenously and pinhole (ph) SPECT/micro-CT was performed, followed by in vivo BLI. RESULTS: Cells showed high levels of fluorescence after transduction. The cells containing the MT-YFP/GLuc were positive on fluorescence microscopy, with the fluorescent signal confined to the cell membrane. After cell sorting, transduced cells were assayed by BLI and showed a significantly higher light output both in vitro and in vivo compared with non-transduced HEK293T cells. The anti-YFP-Nb labelling efficiency was 98%, and subsequent phSPECT/micro-CT demonstrated visible cell binding and significantly higher transplant-to-muscle ratio for both the MT-YFP/GLuc and YFP/GLuc transplanted cells, compared with the GFP/FLuc and Red/GLuc group. CONCLUSION: This study provides a proof of principle for a nanobody-based cell tracking method, using a YFP/GLuc fusion protein and anti-YFP-Nb in a model of subcutaneously transplanted transduced HEK293T cells

Curriculum for diagnostic endoscopic ultrasound training in Europe : European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

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Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Inhibition of Firefly Luciferase by General Anesthetics: Effect on In Vitro and In Vivo Bioluminescence Imaging

<div><h3></h3><p>Bioluminescence imaging is routinely performed in anesthetized mice. Often isoflurane anesthesia is used because of its ease of use and fast induction/recovery. However, general anesthetics have been described as important inhibitors of the luciferase enzyme reaction.</p> <h3>Aim</h3><p>To investigate frequently used mouse anesthetics for their direct effect on the luciferase reaction, both in vitro and in vivo.</p> <h3>Materials and Methods</h3><p>isoflurane, sevoflurane, desflurane, ketamine, xylazine, medetomidine, pentobarbital and avertin were tested in vitro on luciferase-expressing intact cells, and for non-volatile anesthetics on intact cells and cell lysates. In vivo, isoflurane was compared to unanesthetized animals and different anesthetics. Differences in maximal photon emission and time-to-peak photon emission were analyzed.</p> <h3>Results</h3><p>All volatile anesthetics showed a clear inhibitory effect on the luciferase activity of 50% at physiological concentrations. Avertin had a stronger inhibitory effect of 80%. For ketamine and xylazine, increased photon emission was observed in intact cells, but this was not present in cell lysate assays, and was most likely due to cell toxicity and increased cell membrane permeability. In vivo, the highest signal intensities were measured in unanesthetized mice and pentobarbital anesthetized mice, followed by avertin. Isoflurane and ketamine/medetomidine anesthetized mice showed the lowest photon emission (40% of unanesthetized), with significantly longer time-to-peak than unanesthetized, pentobarbital or avertin-anesthetized mice. We conclude that, although strong inhibitory effects of anesthetics are present in vitro, their effect on in vivo BLI quantification is mainly due to their hemodynamic effects on mice and only to a lesser extent due to the direct inhibitory effect.</p> </div