Опухоль брюшной стенки - грыжа спигелевой линии, содержащая метастатическую карциному с невыявленным первичным очагом

АДЕНОКАРЦИНОМАБРЮШНАЯ СТЕНКАГРЫЖИКАРЦИНОМАКОЛОРЕКТАЛЬНЫЕ НОВООБРАЗОВАНИЯНОВООБРАЗОВАНИЯТОЛСТАЯ КИШК

Vascular signalling mediated by ZWILLE potentiates WUSCHEL function during shoot meristem stem cell development in the Arabidopsis embryo

Stem cells are maintained in an undifferentiated state by signals from their microenvironment, the stem cell niche. Despite its central role for organogenesis throughout the plant's life, little is known about how niche development is regulated in the Arabidopsis embryo. Here we show that, in the absence of functional ZWILLE (ZLL), which is a member of the ARGONAUTE (AGO) family, stem cell-specific expression of the signal peptide gene CLAVATA3 (CLV3) is not maintained despite increased levels of the homeodomain transcription factor WUSCHEL (WUS), which is expressed in the organising centre (OC) of the niche and normally promotes stem cell identity. Tissue-specific expression indicates that ZLL acts to maintain the stem cells from the neighbouring vascular primordium, providing direct evidence for a non-cell-autonomous mechanism. Furthermore, mutant and marker gene analyses suggest that during shoot meristem formation, ZLL functions in a similar manner but in a sequential order with its close homologue AGO1, which mediates RNA interference. Thus, WUS-dependent OC signalling to the stem cells is promoted by AGO1 and subsequently maintained by a provascular ZLL-dependent signalling pathway.Matthew R. Tucker, Annika Hinze, Elise J. Tucker, Shinobu Takada, Gerd Jürgens and Thomas Lau

Why We Read Wikipedia

Wikipedia is one of the most popular sites on the Web, with millions of users relying on it to satisfy a broad range of information needs every day. Although it is crucial to understand what exactly these needs are in order to be able to meet them, little is currently known about why users visit Wikipedia. The goal of this paper is to fill this gap by combining a survey of Wikipedia readers with a log-based analysis of user activity. Based on an initial series of user surveys, we build a taxonomy of Wikipedia use cases along several dimensions, capturing users' motivations to visit Wikipedia, the depth of knowledge they are seeking, and their knowledge of the topic of interest prior to visiting Wikipedia. Then, we quantify the prevalence of these use cases via a large-scale user survey conducted on live Wikipedia with almost 30,000 responses. Our analyses highlight the variety of factors driving users to Wikipedia, such as current events, media coverage of a topic, personal curiosity, work or school assignments, or boredom. Finally, we match survey responses to the respondents' digital traces in Wikipedia's server logs, enabling the discovery of behavioral patterns associated with specific use cases. For instance, we observe long and fast-paced page sequences across topics for users who are bored or exploring randomly, whereas those using Wikipedia for work or school spend more time on individual articles focused on topics such as science. Our findings advance our understanding of reader motivations and behavior on Wikipedia and can have implications for developers aiming to improve Wikipedia's user experience, editors striving to cater to their readers' needs, third-party services (such as search engines) providing access to Wikipedia content, and researchers aiming to build tools such as recommendation engines.Comment: Published in WWW'17; v2 fixes caption of Table

Asynchronous Training of Word Embeddings for Large Text Corpora

Word embeddings are a powerful approach for analyzing language and have been widely popular in numerous tasks in information retrieval and text mining. Training embeddings over huge corpora is computationally expensive because the input is typically sequentially processed and parameters are synchronously updated. Distributed architectures for asynchronous training that have been proposed either focus on scaling vocabulary sizes and dimensionality or suffer from expensive synchronization latencies. In this paper, we propose a scalable approach to train word embeddings by partitioning the input space instead in order to scale to massive text corpora while not sacrificing the performance of the embeddings. Our training procedure does not involve any parameter synchronization except a final sub-model merge phase that typically executes in a few minutes. Our distributed training scales seamlessly to large corpus sizes and we get comparable and sometimes even up to 45% performance improvement in a variety of NLP benchmarks using models trained by our distributed procedure which requires $1/10$ of the time taken by the baseline approach. Finally we also show that we are robust to missing words in sub-models and are able to effectively reconstruct word representations.Comment: This paper contains 9 pages and has been accepted in the WSDM201

Domain-independent Extraction of Scientific Concepts from Research Articles

We examine the novel task of domain-independent scientific concept extraction from abstracts of scholarly articles and present two contributions. First, we suggest a set of generic scientific concepts that have been identified in a systematic annotation process. This set of concepts is utilised to annotate a corpus of scientific abstracts from 10 domains of Science, Technology and Medicine at the phrasal level in a joint effort with domain experts. The resulting dataset is used in a set of benchmark experiments to (a) provide baseline performance for this task, (b) examine the transferability of concepts between domains. Second, we present two deep learning systems as baselines. In particular, we propose active learning to deal with different domains in our task. The experimental results show that (1) a substantial agreement is achievable by non-experts after consultation with domain experts, (2) the baseline system achieves a fairly high F1 score, (3) active learning enables us to nearly halve the amount of required training data.Comment: Accepted for publishing in 42nd European Conference on IR Research, ECIR 202

Communication calls produced by electrical stimulation of four structures in the guinea pig brain

One of the main central processes affecting the cortical representation of conspecific vocalizations is the collateral output from the extended motor system for call generation. Before starting to study this interaction we sought to compare the characteristics of calls produced by stimulating four different parts of the brain in guinea pigs (Cavia porcellus). By using anaesthetised animals we were able to reposition electrodes without distressing the animals. Trains of 100 electrical pulses were used to stimulate the midbrain periaqueductal grey (PAG), hypothalamus, amygdala, and anterior cingulate cortex (ACC). Each structure produced a similar range of calls, but in significantly different proportions. Two of the spontaneous calls (chirrup and purr) were never produced by electrical stimulation and although we identified versions of chutter, durr and tooth chatter, they differed significantly from our natural call templates. However, we were routinely able to elicit seven other identifiable calls. All seven calls were produced both during the 1.6 s period of stimulation and subsequently in a period which could last for more than a minute. A single stimulation site could produce four or five different calls, but the amygdala was much less likely to produce a scream, whistle or rising whistle than any of the other structures. These three high-frequency calls were more likely to be produced by females than males. There were also differences in the timing of the call production with the amygdala primarily producing calls during the electrical stimulation and the hypothalamus mainly producing calls after the electrical stimulation. For all four structures a significantly higher stimulation current was required in males than females. We conclude that all four structures can be stimulated to produce fictive vocalizations that should be useful in studying the relationship between the vocal motor system and cortical sensory representation

Heart Failure Symptom Biology in Response to Ventricular Assist Device Implantation.

BACKGROUND: We have a limited understanding of the biological underpinnings of symptoms in heart failure (HF), particularly in response to left ventricular assist device (LVAD) implantation. OBJECTIVE: The aim of this study was to quantify the degree to which symptoms and biomarkers change in parallel from before implantation through the first 6 months after LVAD implantation in advanced HF. METHODS: This was a prospective cohort study of 101 patients receiving an LVAD for the management of advanced HF. Data on symptoms (dyspnea, early and subtle symptoms [HF Somatic Perception Scale], pain severity [Brief Pain Inventory], wake disturbance [Epworth Sleepiness Scale], depression [Patient Health Questionnaire], and anxiety [Brief Symptom Inventory]) and peripheral biomarkers of myocardial stretch, systemic inflammation, and hypervolumetric mechanical stress were measured before implantation with a commercially available LVAD and again at 30, 90, and 180 days after LVAD implantation. Latent growth curve and parallel process modeling were used to describe changes in symptoms and biomarkers and the degree to which they change in parallel in response to LVAD implantation. RESULTS: In response to LVAD implantation, changes in myocardial stretch were closely associated with changes in early and subtle physical symptoms as well as depression, and changes in hypervolumetric stress were closely associated with changes in pain severity and wake disturbances. Changes in systemic inflammation were not closely associated with changes in physical or affective symptoms in response to LVAD implantation. CONCLUSIONS: These findings provide new insights into the many ways in which symptoms and biomarkers provide concordant or discordant information about LVAD response

Caterpillars and fungal pathogens: two co-occurring parasites of an ant-plant mutualism

In mutualisms, each interacting species obtains resources from its partner that it would obtain less efficiently if alone, and so derives a net fitness benefit. In exchange for shelter (domatia) and food, mutualistic plant-ants protect their host myrmecophytes from herbivores, encroaching vines and fungal pathogens. Although selective filters enable myrmecophytes to host those ant species most favorable to their fitness, some insects can by-pass these filters, exploiting the rewards supplied whilst providing nothing in return. This is the case in French Guiana for Cecropia obtusa (Cecropiaceae) as Pseudocabima guianalis caterpillars (Lepidoptera, Pyralidae) can colonize saplings before the installation of their mutualistic Azteca ants. The caterpillars shelter in the domatia and feed on food bodies (FBs) whose production increases as a result. They delay colonization by ants by weaving a silk shield above the youngest trichilium, where the FBs are produced, blocking access to them. This probable temporal priority effect also allows female moths to lay new eggs on trees that already shelter caterpillars, and so to occupy the niche longer and exploit Cecropia resources before colonization by ants. However, once incipient ant colonies are able to develop, they prevent further colonization by the caterpillars. Although no higher herbivory rates were noted, these caterpillars are ineffective in protecting their host trees from a pathogenic fungus, Fusarium moniliforme (Deuteromycetes), that develops on the trichilium in the absence of mutualistic ants. Therefore, the Cecropia treelets can be parasitized by two often overlooked species: the caterpillars that shelter in the domatia and feed on FBs, delaying colonization by mutualistic ants, and the fungal pathogen that develops on old trichilia. The cost of greater FB production plus the presence of the pathogenic fungus likely affect tree growth

Electrons in High-Tc Compounds: Ab-Initio Correlation Results

Electronic correlations in the ground state of an idealized infinite-layer high-Tc compound are computed using the ab-initio method of local ansatz. Comparisons are made with the local-density approximation (LDA) results, and the correlation functions are analyzed in detail. These correlation functions are used to determine the effective atomic-interaction parameters for model Hamiltonians. On the resulting model, doping dependencies of the relevant correlations are investigated. Aside from the expected strong atomic correlations, particular spin correlations arise. The dominating contribution is a strong nearest neighbor correlation that is Stoner-enhanced due to the closeness of the ground state to the magnetic phase. This feature depends moderately on doping, and is absent in a single-band Hubbard model. Our calculated spin correlation function is in good qualitative agreement with that determined from the neutron scattering experiments for a metal.Comment: 21pp, 5fig, Phys. Rev. B (Oct. 98