Joint stage recognition and anatomical annotation of drosophila gene expression patterns

Motivation: Staining the mRNA of a gene via in situ hybridization (ISH) during the development of a Drosophila melanogaster embryo delivers the detailed spatio-temporal patterns of the gene expression. Many related biological problems such as the detection of co-expressed genes, co-regulated genes and transcription factor binding motifs rely heavily on the analysis of these image patterns. To provide the text-based pattern searching for facilitating related biological studies, the images in the Berkeley Drosophila Genome Project (BDGP) study are annotated with developmental stage term and anatomical ontology terms manually by domain experts. Due to the rapid increase in the number of such images and the inevitable bias annotations by human curators, it is necessary to develop an automatic method to recognize the developmental stage and annotate anatomical terms

Efficient detection of RNA–protein interactions using tethered RNAs

The diverse localization of transcripts in cells suggests that there are many specific RNA–protein interactions that have yet to be identified. Progress has been limited, however, by the lack of a robust method to detect and isolate the RNA-binding proteins. Here we describe the use of an RNA aptamer, scaffolded to a tRNA, to create an affinity matrix that efficiently pulls down transcript-specific RNA-binding proteins from cell lysates. The addition of the tRNA scaffold to a Streptavidin aptamer (tRSA) increased binding efficiency by ∼10-fold. The tRSA system with an attached G-quartet sequence also could efficiently and specifically capture endogenous Fragile X Mental Retardation Protein (FMRP), which recognizes this RNA sequence. An alternative method, using biotinylated RNA, captured FMRP less efficiently than did our tRSA method. Finally we demonstrate the identification of novel RNA-binding proteins that interact with intron2 or 3′-UTR of the polarity protein Crumbs3 transcript. Proteins captured by these RNA sequences attached to the tRNA scaffold were identified by mass spectrometry. GFP-tagged versions of these proteins also showed specific interaction with either the Crb3 intron2 or 3′-UTR. Our tRSA technique should find wide application in mapping the RNA–protein interactome

Examining the Connections within the Startup Ecosystem: A Case Study of St. Louis

This paper documents the resurgence of entrepreneurial activity in St. Louis by reporting on the collaboration and local learning within the startup community. This activity is happening both between entrepreneurs and between organizations that provide support, such as mentoring and funding, to entrepreneurs. As these connections deepen, the strength of the entrepreneurial ecosystem grows. Another finding from the research is that activity-based events, where entrepreneurs have the chance to use and practice the skills needed to grow their businesses, are most useful. St. Louis provides a multitude of these activities, such as Startup Weekend, 1 Million Cups, Code Until Dawn, StartLouis, and GlobalHack. Some of these are St. Louis specific, but others have nationwide or global operations, providing important implications for other cities

Electrostatic and electrokinetic contributions to the elastic moduli of a driven membrane

We discuss the electrostatic contribution to the elastic moduli of a cell or artificial membrane placed in an electrolyte and driven by a DC electric field. The field drives ion currents across the membrane, through specific channels, pumps or natural pores. In steady state, charges accumulate in the Debye layers close to the membrane, modifying the membrane elastic moduli. We first study a model of a membrane of zero thickness, later generalizing this treatment to allow for a finite thickness and finite dielectric constant. Our results clarify and extend the results presented in [D. Lacoste, M. Cosentino Lagomarsino, and J. F. Joanny, Europhys. Lett., {\bf 77}, 18006 (2007)], by providing a physical explanation for a destabilizing term proportional to \kps^3 in the fluctuation spectrum, which we relate to a nonlinear ($E^2$) electro-kinetic effect called induced-charge electro-osmosis (ICEO). Recent studies of ICEO have focused on electrodes and polarizable particles, where an applied bulk field is perturbed by capacitive charging of the double layer and drives flow along the field axis toward surface protrusions; in contrast, we predict "reverse" ICEO flows around driven membranes, due to curvature-induced tangential fields within a non-equilibrium double layer, which hydrodynamically enhance protrusions. We also consider the effect of incorporating the dynamics of a spatially dependent concentration field for the ion channels.Comment: 22 pages, 10 figures. Under review for EPJ

TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks

Automatic surgical phase recognition is a challenging and crucial task with the potential to improve patient safety and become an integral part of intra-operative decision-support systems. In this paper, we propose, for the first time in workflow analysis, a Multi-Stage Temporal Convolutional Network (MS-TCN) that performs hierarchical prediction refinement for surgical phase recognition. Causal, dilated convolutions allow for a large receptive field and online inference with smooth predictions even during ambiguous transitions. Our method is thoroughly evaluated on two datasets of laparoscopic cholecystectomy videos with and without the use of additional surgical tool information. Outperforming various state-of-the-art LSTM approaches, we verify the suitability of the proposed causal MS-TCN for surgical phase recognition.Comment: 10 pages, 2 figure

RNAmute: RNA secondary structure mutation analysis tool

BACKGROUND: RNAMute is an interactive Java application that calculates the secondary structure of all single point mutations, given an RNA sequence, and organizes them into categories according to their similarity with respect to the wild type predicted structure. The secondary structure predictions are performed using the Vienna RNA package. Several alternatives are used for the categorization of single point mutations: Vienna's RNAdistance based on dot-bracket representation, as well as tree edit distance and second eigenvalue of the Laplacian matrix based on Shapiro's coarse grain tree graph representation. RESULTS: Selecting a category in each one of the processed tables lists all single point mutations belonging to that category. Selecting a mutation displays a graphical drawing of the single point mutation and the wild type, and includes basic information such as associated energies, representations and distances. RNAMute can be used successfully with very little previous experience and without choosing any parameter value alongside the initial RNA sequence. The package runs under LINUX operating system. CONCLUSION: RNAMute is a user friendly tool that can be used to predict single point mutations leading to conformational rearrangements in the secondary structure of RNAs. In several cases of substantial interest, notably in virology, a point mutation may lead to a loss of important functionality such as the RNA virus replication and translation initiation because of a conformational rearrangement in the secondary structure

Using Visual Cues to Enhance Haptic Feedback for Palpation on Virtual Model of Soft Tissue

This paper explores methods that make use of visual cues aimed at generating actual haptic sensation to the user, namely pseudo-haptics. We propose a new pseudo-haptic feedback based method capable of conveying 3D haptic information and combining visual haptics with force feedback to enhance the user’s haptic experience. We focused on an application related to tumor identification during palpation and evaluated the proposed method in an experimental study where users interacted with a haptic device and graphical interface while exploring a virtual model of soft tissue, which represented stiffness distribution of a silicone phantom tissue with embedded hard inclusions. The performance of hard inclusion detection using force feedback only, pseudo-haptic feedback only, and the combination of the two feedbacks were compared with the direct hand touch. The combination method and direct hand touch had no significant difference in the detection results. Compared with the force feedback alone, our method increased the sensitivity by 5%, the positive predictive value by 4%, and decreased detection time by 48.7%. The proposed methodology has great potential for robot-assisted minimally invasive surgery and in all applications where remote haptic feedback is needed

Comparisons between Chemical Mapping and Binding to Isoenergetic Oligonucleotide Microarrays Reveal Unexpected Patterns of Binding to the Bacillus subtilis RNase P RNA Specificity Domain†

ABSTRACT: Microarrays with isoenergetic pentamer and hexamer 20-O-methyl oligonucleotide probes with LNA (locked nucleic acid) and 2,6-diaminopurine substitutions were used to probe the binding sites on theRNase P RNA specificity domain of Bacillus subtilis. Unexpected binding patterns were revealed. Because of their enhanced binding free energies, isoenergetic probes can break short duplexes, merge adjacent loops, and/or induce refolding. This suggests new approaches to the rational design of short oligonucleotide therapeutics but limits the utility of microarrays for providing constraints for RNA structure determination. The microarray results are compared to results from chemical mapping experiments, which do provide constraints. Results from both types of experiments indicate that the RNase P RNA folds similarly in 1MNaþ and 10 mMMg2þ. Binding of RNA to RNA is important for many natural func-tions, includingproteinsynthesis (1,2), translationregulation (3,4), gene silencing (5, 6), metabolic regulation (7), RNAmodification (8, 9), etc. (10-13). Binding of oligonucleotides toRNAs is impor-tant for therapeutic approaches, such as siRNA, ribozymes, and antisense therapy (14, 15).Much remains to bediscovered, however, of the rules for predicting binding sites andpotential therapeutics

Noise-Driven Stem Cell and Progenitor Population Dynamics

BACKGROUND: The balance between maintenance of the stem cell state and terminal differentiation is influenced by the cellular environment. The switching between these states has long been understood as a transition between attractor states of a molecular network. Herein, stochastic fluctuations are either suppressed or can trigger the transition, but they do not actually determine the attractor states. METHODOLOGY/PRINCIPAL FINDINGS: We present a novel mathematical concept in which stem cell and progenitor population dynamics are described as a probabilistic process that arises from cell proliferation and small fluctuations in the state of differentiation. These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network. Importantly, the associated noise amplitudes are state-dependent and set by the environment. Their variability determines the attractor states, and thus actually governs population dynamics. This model quantitatively reproduces the observed dynamics of differentiation and dedifferentiation in promyelocytic precursor cells. CONCLUSIONS/SIGNIFICANCE: Consequently, state-specific noise modulation by external signals can be instrumental in controlling stem cell and progenitor population dynamics. We propose follow-up experiments for quantifying the imprinting influence of the environment on cellular noise regulation.Engineering and Applied SciencesOther Research Uni

Sequence-specific binding of single-stranded RNA: is there a code for recognition?

A code predicting the RNA sequence that will be bound by a certain protein based on its amino acid sequence or its structure would provide a useful tool for the design of RNA binders with desired sequence-specificity. Such de novo designed RNA binders could be of extraordinary use in both medical and basic research applications. Furthermore, a code could help to predict the cellular functions of RNA-binding proteins that have not yet been extensively studied. A comparative analysis of Pumilio homology domains, zinc-containing RNA binders, hnRNP K homology domains and RNA recognition motifs is performed in this review. Based on this, a set of binding rules is proposed that hints towards a code for RNA recognition by these domains. Furthermore, we discuss the intermolecular interactions that are important for RNA binding and summarize their importance in providing affinity and specificity