CFVS: Coarse-to-Fine Visual Servoing for 6-DoF Object-Agnostic Peg-In-Hole Assembly

Robotic peg-in-hole assembly remains a challenging task due to its high accuracy demand. Previous work tends to simplify the problem by restricting the degree of freedom of the end-effector, or limiting the distance between the target and the initial pose position, which prevents them from being deployed in real-world manufacturing. Thus, we present a Coarse-to-Fine Visual Servoing (CFVS) peg-in-hole method, achieving 6-DoF end-effector motion control based on 3D visual feedback. CFVS can handle arbitrary tilt angles and large initial alignment errors through a fast pose estimation before refinement. Furthermore, by introducing a confidence map to ignore the irrelevant contour of objects, CFVS is robust against noise and can deal with various targets beyond training data. Extensive experiments show CFVS outperforms state-of-the-art methods and obtains 100%, 91%, and 82% average success rates in 3-DoF, 4-DoF, and 6-DoF peg-in-hole, respectively

D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation

In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations. Active learning, maximizing model performance with few informative labeled data, comes in handy for such a scenario. In this work, we present D2ADA, a general active domain adaptation framework for semantic segmentation. To adapt the model to the target domain with minimum queried labels, we propose acquiring labels of the samples with high probability density in the target domain yet with low probability density in the source domain, complementary to the existing source domain labeled data. To further facilitate labeling efficiency, we design a dynamic scheduling policy to adjust the labeling budgets between domain exploration and model uncertainty over time. Extensive experiments show that our method outperforms existing active learning and domain adaptation baselines on two benchmarks, GTA5 -> Cityscapes and SYNTHIA -> Cityscapes. With less than 5% target domain annotations, our method reaches comparable results with that of full supervision.Comment: 14 pages, 5 figure

Computational identification of ubiquitylation sites from protein sequences

<p>Abstract</p> <p>Background</p> <p>Ubiquitylation plays an important role in regulating protein functions. Recently, experimental methods were developed toward effective identification of ubiquitylation sites. To efficiently explore more undiscovered ubiquitylation sites, this study aims to develop an accurate sequence-based prediction method to identify promising ubiquitylation sites.</p> <p>Results</p> <p>We established an ubiquitylation dataset consisting of 157 ubiquitylation sites and 3676 putative non-ubiquitylation sites extracted from 105 proteins in the UbiProt database. This study first evaluates promising sequence-based features and classifiers for the prediction of ubiquitylation sites by assessing three kinds of features (amino acid identity, evolutionary information, and physicochemical property) and three classifiers (support vector machine, <it>k</it>-nearest neighbor, and NaïveBayes). Results show that the set of used 531 physicochemical properties and support vector machine (SVM) are the best kind of features and classifier respectively that their combination has a prediction accuracy of 72.19% using leave-one-out cross-validation.</p> <p>Consequently, an informative physicochemical property mining algorithm (IPMA) is proposed to select an informative subset of 531 physicochemical properties. A prediction system UbiPred was implemented by using an SVM with the feature set of 31 informative physicochemical properties selected by IPMA, which can improve the accuracy from 72.19% to 84.44%. To further analyze the informative physicochemical properties, a decision tree method C5.0 was used to acquire if-then rule-based knowledge of predicting ubiquitylation sites. UbiPred can screen promising ubiquitylation sites from putative non-ubiquitylation sites using prediction scores. By applying UbiPred, 23 promising ubiquitylation sites were identified from an independent dataset of 3424 putative non-ubiquitylation sites, which were also validated by using the obtained prediction rules.</p> <p>Conclusion</p> <p>We have proposed an algorithm IPMA for mining informative physicochemical properties from protein sequences to build an SVM-based prediction system UbiPred. UbiPred can predict ubiquitylation sites accompanied with a prediction score each to help biologists in identifying promising sites for experimental verification. UbiPred has been implemented as a web server and is available at <url>http://iclab.life.nctu.edu.tw/ubipred</url>.</p

In vitro modification of human centromere protein CENP-C fragments by small ubiquitin-like modifier (SUMO) protein: Definitive identification of the modification sites by tandem mass spectrometry analysis of the isopeptides

Protein sumoylation by small ubiquitin-like modifier (SUMO) proteins is an important post-translational regulatory modification. A role in the control of chromosome dynamics was first suggested when SUMO was identified as high-copy suppressor of the centromere protein CENP-C mutants. CENP-C itself contains a consensus sumoylation sequence motif that partially overlaps with its DNA binding and centromere localization domain. To ascertain whether CENP-C can be sumoylated, tandem mass spectrometry (MS) based strategy was developed for high sensitivity identification and sequencing of sumoylated isopeptides present among in-gel-digested tryptic peptides of SDS-PAGE fractionated target proteins. Without a predisposition to searching for the expected isopeptides based on calculated molecular mass and relying instead on the characteristic MS/MS fragmentation pattern to identify sumolylation, we demonstrate that several other lysine residues located not within the perfect consensus sumoylation motif {psi}KXE/D, where {psi} represents a large hydrophobic amino acid, and X represnts any amino acid, can be sumolylated with a reconstituted in vitro system containing only the SUMO proteins, E1-activating enzyme and E2-conjugating enzyme (Ubc9). In all cases, target sites that can be sumoylated by SUMO-2 were shown to be equally susceptible to SUMO-1 attachments which include specific sites on SUMO-2 itself, Ubc9, and the recombinant CENP-C fragments. Two non-consensus sites on one of the CENP-C fragments were found to be sumoylated in addition to the predicted site on the other fragment. The developed methodologies should facilitate future studies in delineating the dynamics and substrate specificities of SUMO-1/2/3 modifications and the respective roles of E3 ligases in the process

A method to improve protein subcellular localization prediction by integrating various biological data sources

<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is crucial information to elucidate protein functions. Owing to the need for large-scale genome analysis, computational method for efficiently predicting protein subcellular localization is highly required. Although many previous works have been done for this task, the problem is still challenging due to several reasons: the number of subcellular locations in practice is large; distribution of protein in locations is imbalanced, that is the number of protein in each location remarkably different; and there are many proteins located in multiple locations. Thus it is necessary to explore new features and appropriate classification methods to improve the prediction performance.</p> <p>Results</p> <p>In this paper we propose a new predicting method which combines two key ideas: 1) Information of neighbour proteins in a probabilistic gene network is integrated to enrich the prediction features. 2) Fuzzy k-NN, a classification method based on fuzzy set theory is applied to predict protein locating in multiple sites. Experiment was conducted on a dataset consisting of 22 locations from Budding yeast proteins and significant improvement was observed.</p> <p>Conclusion</p> <p>Our results suggest that the neighbourhood information from functional gene networks is predictive to subcellular localization. The proposed method thus can be integrated and complementary to other available prediction methods.</p

Longitudinal Evaluation of an N-Ethyl-N-Nitrosourea-Created Murine Model with Normal Pressure Hydrocephalus

Normal-pressure hydrocephalus (NPH) is a neurodegenerative disorder that usually occurs late in adult life. Clinically, the cardinal features include gait disturbances, urinary incontinence, and cognitive decline.Herein we report the characterization of a novel mouse model of NPH (designated p23-ST1), created by N-ethyl-N-nitrosourea (ENU)-induced mutagenesis. The ventricular size in the brain was measured by 3-dimensional micro-magnetic resonance imaging (3D-MRI) and was found to be enlarged. Intracranial pressure was measured and was found to fall within a normal range. A histological assessment and tracer flow study revealed that the cerebral spinal fluid (CSF) pathway of p23-ST1 mice was normal without obstruction. Motor functions were assessed using a rotarod apparatus and a CatWalk gait automatic analyzer. Mutant mice showed poor rotarod performance and gait disturbances. Cognitive function was evaluated using auditory fear-conditioned responses with the mutant displaying both short- and long-term memory deficits. With an increase in urination frequency and volume, the mutant showed features of incontinence. Nissl substance staining and cell-type-specific markers were used to examine the brain pathology. These studies revealed concurrent glial activation and neuronal loss in the periventricular regions of mutant animals. In particular, chronically activated microglia were found in septal areas at a relatively young age, implying that microglial activation might contribute to the pathogenesis of NPH. These defects were transmitted in an autosomal dominant mode with reduced penetrance. Using a whole-genome scan employing 287 single-nucleotide polymorphic (SNP) markers and further refinement using six additional SNP markers and four microsatellite markers, the causative mutation was mapped to a 5.3-cM region on chromosome 4.Our results collectively demonstrate that the p23-ST1 mouse is a novel mouse model of human NPH. Clinical observations suggest that dysfunctions and alterations in the brains of patients with NPH might occur much earlier than the appearance of clinical signs. p23-ST1 mice provide a unique opportunity to characterize molecular changes and the pathogenic mechanism of NPH

Matrix Metalloproteinase-8 Mediates the Unfavorable Systemic Impact of Local Irradiation on Pharmacokinetics of Anti-Cancer Drug 5-Fluorouracil

Concurrent chemoradiation with 5-fluorouracil (5-FU) is widely accepted for cancer treatment. However, the interactions between radiation and 5-FU remain unclear. Here, we evaluated the influence of local irradiation on the pharmacokinetics of 5-FU in rats. The single-fraction radiation was delivered to the whole pelvic fields of Sprague-Dawley rats after computerized tomography-based planning. 5-FU at 100 mg/kg was prescribed 24 hours after radiation. A high-performance liquid chromatography system was used to measure 5-FU in the blood. Matrix metalloproteinase-8 (MMP-8) inhibitor I was administered to examine whether or not RT modulation of 5-FU pharmacokinetic parameters could be blocked. Compared with sham-irradiated controls, whole pelvic irradiation reduced the area under the concentration versus time curve (AUC) of 5-FU in plasma and, in contrast, increased in bile with a radiation dose-dependent manner. Based on protein array analysis, the amount of plasma MMP-8 was increased by whole pelvic irradiation (2.8-fold by 0.5 Gy and 5.3-fold by 2 Gy) in comparison with controls. Pretreatment with MMP-8 inhibitor reversed the effect of irradiation on AUC of 5-FU in plasma. Our findings first indicate that local irradiation modulate the systemic pharmacokinetics of 5-FU through stimulating the release of MMP-8. The pharmacokinetics of 5-FU during concurrent chemoradiaiton therapy should be rechecked and the optimal 5-FU dose should be reevaluated, and adjusted if necessary, during CCRT

Regulation of gene expression in ovarian cancer cells by luteinizing hormone receptor expression and activation

<p>Abstract</p> <p>Background</p> <p>Since a substantial percentage of ovarian cancers express gonadotropin receptors and are responsive to the relatively high concentrations of pituitary gonadotropins during the postmenopausal years, it has been suggested that receptor activation may contribute to the etiology and/or progression of the neoplasm. The goal of the present study was to develop a cell model to determine the impact of luteinizing hormone (LH) receptor (LHR) expression and LH-mediated LHR activation on gene expression and thus obtain insights into the mechanism of gonadotropin action on ovarian surface epithelial (OSE) carcinoma cells.</p> <p>Methods</p> <p>The human ovarian cancer cell line, SKOV-3, was stably transfected to express functional LHR and incubated with LH for various periods of time (0-20 hours). Transcriptomic profiling was performed on these cells to identify LHR expression/activation-dependent changes in gene expression levels and pathways by microarray and qRT-PCR analyses.</p> <p>Results</p> <p>Through comparative analysis on the LHR-transfected SKOV-3 cells exposed to LH, we observed the differential expression of 1,783 genes in response to LH treatment, among which five significant families were enriched, including those of growth factors, translation regulators, transporters, G-protein coupled receptors, and ligand-dependent nuclear receptors. The most highly induced early and intermediate responses were found to occupy a network impacting transcriptional regulation, cell growth, apoptosis, and multiple signaling transductions, giving indications of LH-induced apoptosis and cell growth inhibition through the significant changes in, for example, tumor necrosis factor, Jun and many others, supportive of the observed cell growth reduction in <it>in vitro </it>assays. However, other observations, e.g. the substantial up-regulation of the genes encoding the endothelin-1 subtype A receptor, stromal cell-derived factor 1, and insulin-like growth factor II, all of which are potential therapeutic targets, may reflect a positive mediation of ovarian cancer growth.</p> <p>Conclusion</p> <p>Overall, the present study elucidates the extensive transcriptomic changes of ovarian cancer cells in response to LH receptor activation, which provides a comprehensive and objective assessment for determining new cancer therapies and potential serum markers, of which over 100 are suggested.</p

Analysis of the impact of length of stay on the quality of service experience, satisfaction and loyalty

Although length of stay is a relevant variable in destination management, little research has been produced connecting it with tourists' post-consumption behaviour. This research compares the post-consumption behaviour of same-day visitors with overnight tourists in a sample of 398 domestic vacationers at two Mediterranean heritage-and-beach destinations. Although economic research on length of stay posits that there are destination benefits in longer stays, same-day visitors score higher in most of the post-consumption variables under study. Significant differences arise in hedonic aspects of the tourist experience and destination loyalty. Thus, we propose that length of stay can be used as a segmentation variable. Furthermore, destination management organisations need to consider length of stay when designing tourism policies. The tourist product and communication strategies might be adapted to different vacation durations