Hypergraph model of social tagging networks

The past few years have witnessed the great success of a new family of paradigms, so-called folksonomy, which allows users to freely associate tags to resources and efficiently manage them. In order to uncover the underlying structures and user behaviors in folksonomy, in this paper, we propose an evolutionary hypergrah model to explain the emerging statistical properties. The present model introduces a novel mechanism that one can not only assign tags to resources, but also retrieve resources via collaborative tags. We then compare the model with a real-world dataset: \emph{Del.icio.us}. Indeed, the present model shows considerable agreement with the empirical data in following aspects: power-law hyperdegree distributions, negtive correlation between clustering coefficients and hyperdegrees, and small average distances. Furthermore, the model indicates that most tagging behaviors are motivated by labeling tags to resources, and tags play a significant role in effectively retrieving interesting resources and making acquaintance with congenial friends. The proposed model may shed some light on the in-depth understanding of the structure and function of folksonomy.Comment: 7 pages,7 figures, 32 reference

ruvA Mutants that resolve Holliday junctions but do not reverse replication forks

RuvAB and RuvABC complexes catalyze branch migration and resolution of Holliday junctions (HJs) respectively. In addition to their action in the last steps of homologous recombination, they process HJs made by replication fork reversal, a reaction which occurs at inactivated replication forks by the annealing of blocked leading and lagging strand ends. RuvAB was recently proposed to bind replication forks and directly catalyze their conversion into HJs. We report here the isolation and characterization of two separation-of-function ruvA mutants that resolve HJs, based on their capacity to promote conjugational recombination and recombinational repair of UV and mitomycin C lesions, but have lost the capacity to reverse forks. In vivo and in vitro evidence indicate that the ruvA mutations affect DNA binding and the stimulation of RuvB helicase activity. This work shows that RuvA's actions at forks and at HJs can be genetically separated, and that RuvA mutants compromised for fork reversal remain fully capable of homologous recombination

Clinical and age peculiarities of non-Hodgkin’s lymphomas with primary involvement of lymph nodes

Department of Oncology, Hematology and Radiotherapy, Nicolae Testemitsanu State University of Medicine and Pharmacy, Chisinau, the Republic of MoldovaBackground: Non-Hodgkin’s lymphomas (NHLs) are a heterogenous group of malignant tumors developing from the lymphoid tissue and having a wide range of clinical manifestations and varied evolution and prognosis. Material and methods: We have studied the clinical peculiarities of 228 patients of different age groups with NHLs and a primary involvement of lymph nodes. Results: The frequency of the lymph nodes primary involvement has constituted 37.6%. It has been established that NHLs most frequently had their primary onset in the peripheral lymph nodes (61.8%), less frequently – in the abdominal (23.3%) and mediastinal (14.9%) ones. NHLs most frequently begin their development in the peripheral lymph nodes, first in patients over 60 years old (84.6%), in the abdominal lymph nodes – in children (57.2%), in the mediastinum – in children and people aged between 19 and 39 (48.2%). Conclusions: Children develop only aggressive NHL forms, these forms also predominate in adults. Aggressive NHLs in adults have been most often diagnosed in the patients having the primary tumor focus location in the mediastinal and abdominal lymph nodes. The frequency of indolent NHLs is higher in the cases with the primary involvement of the peripheral lymph nodes, the patients’ age being over 60. Metastases in the bone marrow have most frequently been recorded in NHL patients with the primary involvement of peripheral lymph nodes (53.5%). The involvement of CNS has taken place most frequently in the patients with NHLs, having the onset in the abdominal (34.4%) and mediastinal (30.0%) lymph nodes

Towards real-time multiple surgical tool tracking

Surgical tool tracking is an essential building block for computer-assisted interventions (CAI) and applications like video summarisation, workflow analysis and surgical navigation. Vision-based instrument tracking in laparoscopic surgical data faces significant challenges such as fast instrument motion, multiple simultaneous instruments and re-initialisation due to out-of-view conditions or instrument occlusions. In this paper, we propose a real-time multiple object tracking framework for whole laparoscopic tools, which extends an existing single object tracker. We introduce a geometric object descriptor, which helps with overlapping bounding box disambiguation, fast motion and optimal assignment between existing trajectories and new hypotheses. We achieve 99.51% and 75.64% average accuracy on ex-vivo robotic data and in-vivo laparoscopic sequences respectively from the Endovis’15 Instrument Tracking Dataset. The proposed geometric descriptor increased the performance on laparoscopic data by 32%, significantly reducing identity switches, false negatives and false positives. Overall, the proposed pipeline can successfully recover trajectories over long-sequences and it runs in real-time at approximately 25–29 fps

Scalable Joint Detection and Segmentation of Surgical Instruments with Weak Supervision

Computer vision based models, such as object segmentation, detection and tracking, have the potential to assist surgeons intra-operatively and improve the quality and outcomes of minimally invasive surgery. Different work streams towards instrument detection include segmentation, bounding box localisation and classification. While segmentation models offer much more granular results, bounding box annotations are easier to annotate at scale. To leverage the granularity of segmentation approaches with the scalability of bounding box-based models, a multi-task model for joint bounding box detection and segmentation of surgical instruments is proposed. The model consists of a shared backbone and three independent heads for the tasks of classification, bounding box regression, and segmentation. Using adaptive losses together with simple yet effective weakly-supervised label inference, the proposed model use weak labels to learn to segment surgical instruments with a fraction of the dataset requiring segmentation masks. Results suggest that instrument detection and segmentation tasks share intrinsic challenges and jointly learning from both reduces the burden of annotating masks at scale. Experimental validation shows that the proposed model obtain comparable results to that of single-task state-of-the-art detector and segmentation models, while only requiring a fraction of the dataset to be annotated with masks. Specifically, the proposed model obtained 0.81 weighted average precision (wAP) and 0.73 mean intersection-over-union (IOU) in the Endovis2018 dataset with 1% annotated masks, while performing joint detection and segmentation at more than 20 frames per second

Anaplastic Lymphoma Kinase Is Required for Neurogenesis in the Developing Central Nervous System of Zebrafish

10.1371/journal.pone.0063757PLoS ONE85

SnappySonic: An Ultrasound Acquisition Replay Simulator

SnappySonic provides an ultrasound acquisition replay simulator designed for public engagement and training. It provides a simple interface to allow users to experience ultrasound acquisition without the need for specialist hardware or acoustically compatible phantoms. The software is implemented in Python, built on top of a set of open source Python modules targeted at surgical innovation. The library has high potential for reuse, most obviously for those who want to simulate ultrasound acquisition, but it could also be used as a user interface for displaying high dimensional images or video data

The impact in environment by presence in soil of chrome ions

Soil pollution is increasing day by day resulting in poor crop stand along with health hazards of human beings and animals. Major sources of soil pollution are: industrial effluents, sewage sludge, fertilizers and pesticides application, etc. Agricultural recycling of waste is growing too, and can be very worthwhile in both economic and agronomic terms, but it is crucial to minimize its environmental impact. In effect, it can cause contamination. Various pollutants are involved, including heavy metals (HMs) such as cadmium (Cd), chromium (Cr), mercury (Hg), lead (Pb), copper (Cu), nickel (Ni) and zinc (Zn), which need to be studied closely, since they are generally toxic to animals and plants. The purpose of this paper was to analyze soil samples from industrial area and observe if heavy metals ions as chromium can influence the environmental components. Six soil samples from 5 and 30 cm deep were analyzed in order to estimate the impact and risk for environment. The values of impact induced on soil (samples 3 and 4) underlay the fact that the environment is highly modified by the presence of chromium ions, causing a degraded environment, not proper for life forms (ecosystems). Mainly, the impact on soil is induced by the presence of chromium [VI]. The associated risk shows that all activities which involve uses of heavy metals should be stopped

CSAP localizes to polyglutamylated microtubules and promotes proper cilia function and zebrafish development

The diverse populations of microtubule polymers in cells are functionally distinguished by different posttranslational modifications, including polyglutamylation. Polyglutamylation is enriched on subsets of microtubules including those found in the centrioles, mitotic spindle, and cilia. However, whether this modification alters intrinsic microtubule dynamics or affects extrinsic associations with specific interacting partners remains to be determined. Here we identify the microtubule-binding protein centriole and spindle–associated protein (CSAP), which colocalizes with polyglutamylated tubulin to centrioles, spindle microtubules, and cilia in human tissue culture cells. Reducing tubulin polyglutamylation prevents CSAP localization to both spindle and cilia microtubules. In zebrafish, CSAP is required for normal brain development and proper left–right asymmetry, defects that are qualitatively similar to those reported previously for depletion of polyglutamylation-conjugating enzymes. We also find that CSAP is required for proper cilia beating. Our work supports a model in which polyglutamylation can target selected microtubule-associated proteins, such as CSAP, to microtubule subpopulations, providing specific functional capabilities to these populations.National Institutes of Health (U.S.) (Grant no. GM074746)American Cancer Society. Research Scholar Grant (121776)National Institute of General Medical Sciences (U.S.) (GM088313

Automatic, global registration in laparoscopic liver surgery

PURPOSE: The initial registration of a 3D pre-operative CT model to a 2D laparoscopic video image in augmented reality systems for liver surgery needs to be fast, intuitive to perform and with minimal interruptions to the surgical intervention. Several recent methods have focussed on using easily recognisable landmarks across modalities. However, these methods still need manual annotation or manual alignment. We propose a novel, fully automatic pipeline for 3D-2D global registration in laparoscopic liver interventions. METHODS: Firstly, we train a fully convolutional network for the semantic detection of liver contours in laparoscopic images. Secondly, we propose a novel contour-based global registration algorithm to estimate the camera pose without any manual input during surgery. The contours used are the anterior ridge and the silhouette of the liver. RESULTS: We show excellent generalisation of the semantic contour detection on test data from 8 clinical cases. In quantitative experiments, the proposed contour-based registration can successfully estimate a global alignment with as little as 30% of the liver surface, a visibility ratio which is characteristic of laparoscopic interventions. Moreover, the proposed pipeline showed very promising results in clinical data from 5 laparoscopic interventions. CONCLUSIONS: Our proposed automatic global registration could make augmented reality systems more intuitive and usable for surgeons and easier to translate to operating rooms. Yet, as the liver is deformed significantly during surgery, it will be very beneficial to incorporate deformation into our method for more accurate registration